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Sample records for cancer genomics identifies

TCGA study identifies genomic features of cervical cancer

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Investigators with The Cancer Genome Atlas (TCGA) Research Network have identified novel genomic and molecular characteristics of cervical cancer that will aid in subclassification of the disease and may help target therapies that are most appropriate for each patient.
Computational approaches to identify functional genetic variants in cancer genomes

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Gonzalez-Perez, Abel; Mustonen, Ville; Reva, Boris

2013-01-01

The International Cancer Genome Consortium (ICGC) aims to catalog genomic abnormalities in tumors from 50 different cancer types. Genome sequencing reveals hundreds to thousands of somatic mutations in each tumor but only a minority of these drive tumor progression. We present the result of discu......The International Cancer Genome Consortium (ICGC) aims to catalog genomic abnormalities in tumors from 50 different cancer types. Genome sequencing reveals hundreds to thousands of somatic mutations in each tumor but only a minority of these drive tumor progression. We present the result...... of discussions within the ICGC on how to address the challenge of identifying mutations that contribute to oncogenesis, tumor maintenance or response to therapy, and recommend computational techniques to annotate somatic variants and predict their impact on cancer phenotype....
Genome-wide association analysis identifies three new breast cancer susceptibility loci

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Ghoussaini, Maya; Fletcher, Olivia; Michailidou, Kyriaki

2012-01-01

Breast cancer is the most common cancer among women. To date, 22 common breast cancer susceptibility loci have been identified accounting for ∼8% of the heritability of the disease. We attempted to replicate 72 promising associations from two independent genome-wide association studies (GWAS...
Mining genome sequencing data to identify the genomic features linked to breast cancer histopathology

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Ping, Zheng; Siegal, Gene P.; Almeida, Jonas S.; Schnitt, Stuart J.; Shen, Dejun

2014-01-01

Background: Genetics and genomics have radically altered our understanding of breast cancer progression. However, the genomic basis of various histopathologic features of breast cancer is not yet well-defined. Materials and Methods: The Cancer Genome Atlas (TCGA) is an international database containing a large collection of human cancer genome sequencing data. cBioPortal is a web tool developed for mining these sequencing data. We performed mining of TCGA sequencing data in an attempt to characterize the genomic features correlated with breast cancer histopathology. We first assessed the quality of the TCGA data using a group of genes with known alterations in various cancers. Both genome-wide gene mutation and copy number changes as well as a group of genes with a high frequency of genetic changes were then correlated with various histopathologic features of invasive breast cancer. Results: Validation of TCGA data using a group of genes with known alterations in breast cancer suggests that the TCGA has accurately documented the genomic abnormalities of multiple malignancies. Further analysis of TCGA breast cancer sequencing data shows that accumulation of specific genomic defects is associated with higher tumor grade, larger tumor size and receptor negativity. Distinct groups of genomic changes were found to be associated with the different grades of invasive ductal carcinoma. The mutator role of the TP53 gene was validated by genomic sequencing data of invasive breast cancer and TP53 mutation was found to play a critical role in defining high tumor grade. Conclusions: Data mining of the TCGA genome sequencing data is an innovative and reliable method to help characterize the genomic abnormalities associated with histopathologic features of invasive breast cancer. PMID:24672738
Mining genome sequencing data to identify the genomic features linked to breast cancer histopathology

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Zheng Ping

2014-01-01

Full Text Available Background: Genetics and genomics have radically altered our understanding of breast cancer progression. However, the genomic basis of various histopathologic features of breast cancer is not yet well-defined. Materials and Methods: The Cancer Genome Atlas (TCGA is an international database containing a large collection of human cancer genome sequencing data. cBioPortal is a web tool developed for mining these sequencing data. We performed mining of TCGA sequencing data in an attempt to characterize the genomic features correlated with breast cancer histopathology. We first assessed the quality of the TCGA data using a group of genes with known alterations in various cancers. Both genome-wide gene mutation and copy number changes as well as a group of genes with a high frequency of genetic changes were then correlated with various histopathologic features of invasive breast cancer. Results: Validation of TCGA data using a group of genes with known alterations in breast cancer suggests that the TCGA has accurately documented the genomic abnormalities of multiple malignancies. Further analysis of TCGA breast cancer sequencing data shows that accumulation of specific genomic defects is associated with higher tumor grade, larger tumor size and receptor negativity. Distinct groups of genomic changes were found to be associated with the different grades of invasive ductal carcinoma. The mutator role of the TP53 gene was validated by genomic sequencing data of invasive breast cancer and TP53 mutation was found to play a critical role in defining high tumor grade. Conclusions: Data mining of the TCGA genome sequencing data is an innovative and reliable method to help characterize the genomic abnormalities associated with histopathologic features of invasive breast cancer.
Whole-genome and Transcriptome Sequencing of Prostate Cancer Identify New Genetic Alterations Driving Disease Progression

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Ren, Shancheng; Wei, Gong-Hong; Liu, Dongbing

2018-01-01

BACKGROUND: Global disparities in prostate cancer (PCa) incidence highlight the urgent need to identify genomic abnormalities in prostate tumors in different ethnic populations including Asian men. OBJECTIVE: To systematically explore the genomic complexity and define disease-driven genetic......-scale and comprehensive genomic data of prostate cancer from Asian population. Identification of these genetic alterations may help advance prostate cancer diagnosis, prognosis, and treatment....... alterations in PCa. DESIGN, SETTING, AND PARTICIPANTS: The study sequenced whole-genome and transcriptome of tumor-benign paired tissues from 65 treatment-naive Chinese PCa patients. Subsequent targeted deep sequencing of 293 PCa-relevant genes was performed in another cohort of 145 prostate tumors. OUTCOME...
Genomic profiling identifies GATA6 as a candidate oncogene amplified in pancreatobiliary cancer.

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Kevin A Kwei

2008-05-01

Full Text Available Pancreatobiliary cancers have among the highest mortality rates of any cancer type. Discovering the full spectrum of molecular genetic alterations may suggest new avenues for therapy. To catalogue genomic alterations, we carried out array-based genomic profiling of 31 exocrine pancreatic cancers and 6 distal bile duct cancers, expanded as xenografts to enrich the tumor cell fraction. We identified numerous focal DNA amplifications and deletions, including in 19% of pancreatobiliary cases gain at cytoband 18q11.2, a locus uncommonly amplified in other tumor types. The smallest shared amplification at 18q11.2 included GATA6, a transcriptional regulator previously linked to normal pancreas development. When amplified, GATA6 was overexpressed at both the mRNA and protein levels, and strong immunostaining was observed in 25 of 54 (46% primary pancreatic cancers compared to 0 of 33 normal pancreas specimens surveyed. GATA6 expression in xenografts was associated with specific microarray gene-expression patterns, enriched for GATA binding sites and mitochondrial oxidative phosphorylation activity. siRNA mediated knockdown of GATA6 in pancreatic cancer cell lines with amplification led to reduced cell proliferation, cell cycle progression, and colony formation. Our findings indicate that GATA6 amplification and overexpression contribute to the oncogenic phenotypes of pancreatic cancer cells, and identify GATA6 as a candidate lineage-specific oncogene in pancreatobiliary cancer, with implications for novel treatment strategies.
Systematic Functional Interrogation of Rare Cancer Variants Identifies Oncogenic Alleles | Office of Cancer Genomics

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Cancer genome characterization efforts now provide an initial view of the somatic alterations in primary tumors. However, most point mutations occur at low frequency, and the function of these alleles remains undefined. We have developed a scalable systematic approach to interrogate the function of cancer-associated gene variants. We subjected 474 mutant alleles curated from 5,338 tumors to pooled in vivo tumor formation assays and gene expression profiling. We identified 12 transforming alleles, including two in genes (PIK3CB, POT1) that have not been shown to be tumorigenic.
Seven prostate cancer susceptibility loci identified by a multi-stage genome-wide association study

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Kote-Jarai, Zsofia; Olama, Ali Amin Al; Giles, Graham G

2011-01-01

Prostate cancer (PrCa) is the most frequently diagnosed male cancer in developed countries. We conducted a multi-stage genome-wide association study for PrCa and previously reported the results of the first two stages, which identified 16 PrCa susceptibility loci. We report here the results of st...
Use of deep whole-genome sequencing data to identify structure risk variants in breast cancer susceptibility genes.

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Guo, Xingyi; Shi, Jiajun; Cai, Qiuyin; Shu, Xiao-Ou; He, Jing; Wen, Wanqing; Allen, Jamie; Pharoah, Paul; Dunning, Alison; Hunter, David J; Kraft, Peter; Easton, Douglas F; Zheng, Wei; Long, Jirong

2018-03-01

Functional disruptions of susceptibility genes by large genomic structure variant (SV) deletions in germlines are known to be associated with cancer risk. However, few studies have been conducted to systematically search for SV deletions in breast cancer susceptibility genes. We analysed deep (> 30x) whole-genome sequencing (WGS) data generated in blood samples from 128 breast cancer patients of Asian and European descent with either a strong family history of breast cancer or early cancer onset disease. To identify SV deletions in known or suspected breast cancer susceptibility genes, we used multiple SV calling tools including Genome STRiP, Delly, Manta, BreakDancer and Pindel. SV deletions were detected by at least three of these bioinformatics tools in five genes. Specifically, we identified heterozygous deletions covering a fraction of the coding regions of BRCA1 (with approximately 80kb in two patients), and TP53 genes (with ∼1.6 kb in two patients), and of intronic regions (∼1 kb) of the PALB2 (one patient), PTEN (three patients) and RAD51C genes (one patient). We confirmed the presence of these deletions using real-time quantitative PCR (qPCR). Our study identified novel SV deletions in breast cancer susceptibility genes and the identification of such SV deletions may improve clinical testing.
Genome-wide association study identifies novel breast cancer susceptibility loci

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Easton, Douglas F.; Pooley, Karen A.; Dunning, Alison M.; Pharoah, Paul D. P.; Thompson, Deborah; Ballinger, Dennis G.; Struewing, Jeffery P.; Morrison, Jonathan; Field, Helen; Luben, Robert; Wareham, Nicholas; Ahmed, Shahana; Healey, Catherine S.; Bowman, Richard; Meyer, Kerstin B.; Haiman, Christopher A.; Kolonel, Laurence K.; Henderson, Brian E.; Marchand, Loic Le; Brennan, Paul; Sangrajrang, Suleeporn; Gaborieau, Valerie; Odefrey, Fabrice; Shen, Chen-Yang; Wu, Pei-Ei; Wang, Hui-Chun; Eccles, Diana; Evans, D. Gareth; Peto, Julian; Fletcher, Olivia; Johnson, Nichola; Seal, Sheila; Stratton, Michael R.; Rahman, Nazneen; Chenevix-Trench, Georgia; Bojesen, Stig E.; Nordestgaard, Børge G.; Axelsson, Christen K.; Garcia-Closas, Montserrat; Brinton, Louise; Chanock, Stephen; Lissowska, Jolanta; Peplonska, Beata; Nevanlinna, Heli; Fagerholm, Rainer; Eerola, Hannaleena; Kang, Daehee; Yoo, Keun-Young; Noh, Dong-Young; Ahn, Sei-Hyun; Hunter, David J.; Hankinson, Susan E.; Cox, David G.; Hall, Per; Wedren, Sara; Liu, Jianjun; Low, Yen-Ling; Bogdanova, Natalia; Schürmann, Peter; Dörk, Thilo; Tollenaar, Rob A. E. M.; Jacobi, Catharina E.; Devilee, Peter; Klijn, Jan G. M.; Sigurdson, Alice J.; Doody, Michele M.; Alexander, Bruce H.; Zhang, Jinghui; Cox, Angela; Brock, Ian W.; MacPherson, Gordon; Reed, Malcolm W. R.; Couch, Fergus J.; Goode, Ellen L.; Olson, Janet E.; Meijers-Heijboer, Hanne; van den Ouweland, Ans; Uitterlinden, André; Rivadeneira, Fernando; Milne, Roger L.; Ribas, Gloria; Gonzalez-Neira, Anna; Benitez, Javier; Hopper, John L.; McCredie, Margaret; Southey, Melissa; Giles, Graham G.; Schroen, Chris; Justenhoven, Christina; Brauch, Hiltrud; Hamann, Ute; Ko, Yon-Dschun; Spurdle, Amanda B.; Beesley, Jonathan; Chen, Xiaoqing; Mannermaa, Arto; Kosma, Veli-Matti; Kataja, Vesa; Hartikainen, Jaana; Day, Nicholas E.; Cox, David R.; Ponder, Bruce A. J.; Luccarini, Craig; Conroy, Don; Shah, Mitul; Munday, Hannah; Jordan, Clare; Perkins, Barbara; West, Judy; Redman, Karen; Driver, Kristy; Aghmesheh, Morteza; Amor, David; Andrews, Lesley; Antill, Yoland; Armes, Jane; Armitage, Shane; Arnold, Leanne; Balleine, Rosemary; Begley, Glenn; Beilby, John; Bennett, Ian; Bennett, Barbara; Berry, Geoffrey; Blackburn, Anneke; Brennan, Meagan; Brown, Melissa; Buckley, Michael; Burke, Jo; Butow, Phyllis; Byron, Keith; Callen, David; Campbell, Ian; Chenevix-Trench, Georgia; Clarke, Christine; Colley, Alison; Cotton, Dick; Cui, Jisheng; Culling, Bronwyn; Cummings, Margaret; Dawson, Sarah-Jane; Dixon, Joanne; Dobrovic, Alexander; Dudding, Tracy; Edkins, Ted; Eisenbruch, Maurice; Farshid, Gelareh; Fawcett, Susan; Field, Michael; Firgaira, Frank; Fleming, Jean; Forbes, John; Friedlander, Michael; Gaff, Clara; Gardner, Mac; Gattas, Mike; George, Peter; Giles, Graham; Gill, Grantley; Goldblatt, Jack; Greening, Sian; Grist, Scott; Haan, Eric; Harris, Marion; Hart, Stewart; Hayward, Nick; Hopper, John; Humphrey, Evelyn; Jenkins, Mark; Jones, Alison; Kefford, Rick; Kirk, Judy; Kollias, James; Kovalenko, Sergey; Lakhani, Sunil; Leary, Jennifer; Lim, Jacqueline; Lindeman, Geoff; Lipton, Lara; Lobb, Liz; Maclurcan, Mariette; Mann, Graham; Marsh, Deborah; McCredie, Margaret; McKay, Michael; McLachlan, Sue Anne; Meiser, Bettina; Milne, Roger; Mitchell, Gillian; Newman, Beth; O'Loughlin, Imelda; Osborne, Richard; Peters, Lester; Phillips, Kelly; Price, Melanie; Reeve, Jeanne; Reeve, Tony; Richards, Robert; Rinehart, Gina; Robinson, Bridget; Rudzki, Barney; Salisbury, Elizabeth; Sambrook, Joe; Saunders, Christobel; Scott, Clare; Scott, Elizabeth; Scott, Rodney; Seshadri, Ram; Shelling, Andrew; Southey, Melissa; Spurdle, Amanda; Suthers, Graeme; Taylor, Donna; Tennant, Christopher; Thorne, Heather; Townshend, Sharron; Tucker, Kathy; Tyler, Janet; Venter, Deon; Visvader, Jane; Walpole, Ian; Ward, Robin; Waring, Paul; Warner, Bev; Warren, Graham; Watson, Elizabeth; Williams, Rachael; Wilson, Judy; Winship, Ingrid; Young, Mary Ann; Bowtell, David; Green, Adele; deFazio, Anna; Chenevix-Trench, Georgia; Gertig, Dorota; Webb, Penny

2009-01-01

Breast cancer exhibits familial aggregation, consistent with variation in genetic susceptibility to the disease. Known susceptibility genes account for less than 25% of the familial risk of breast cancer, and the residual genetic variance is likely to be due to variants conferring more moderate risks. To identify further susceptibility alleles, we conducted a two-stage genome-wide association study in 4,398 breast cancer cases and 4,316 controls, followed by a third stage in which 30 single nucleotide polymorphisms (SNPs) were tested for confirmation in 21,860 cases and 22,578 controls from 22 studies. We used 227,876 SNPs that were estimated to correlate with 77% of known common SNPs in Europeans at r2>0.5. SNPs in five novel independent loci exhibited strong and consistent evidence of association with breast cancer (P<10−7). Four of these contain plausible causative genes (FGFR2, TNRC9, MAP3K1 and LSP1). At the second stage, 1,792 SNPs were significant at the P<0.05 level compared with an estimated 1,343 that would be expected by chance, indicating that many additional common susceptibility alleles may be identifiable by this approach. PMID:17529967
Genome-wide association analysis identifies new lung cancer susceptibility loci in never-smoking women in Asia.

NARCIS (Netherlands)

Lan, Q.; Hsiung, C.A.; Matsuo, K.; Hong, Y.C.; Seow, A.; Wang, Z.; Hosgood, H.D.; Chen, K.; Wang, J.C.; Chatterjee, N.; Hu, W.; Wong, M.P.; Zheng, W.; Caporaso, N.; Park, J.Y.; Chen, C.J.; Kim, Y.H.; Kim, Y.T.; Landi, M.T.; Shen, H.; Lawrence, C.; Burdett, L.; Yeager, M.; Yuenger, J.; Jacobs, K.B.; Chang, I.S.; Mitsudomi, T.; Kim, H.N.; Chang, G.C.; Bassig, B.A.; Tucker, M.; Wei, F.; Yin, Y.; Wu, C.; An, S.J.; Qian, B.; Lee, V.H.; Lu, D.; Liu, J.; Jeon, H.S.; Hsiao, C.F.; Sung, J.S.; Kim, J.H.; Gao, Y.T.; Tsai, Y.H.; Jung, Y.J.; Guo, H.; Hu, Z.; Hutchinson, A.; Wang, W.C.; Klein, R.; Chung, C.C.; Oh, I.J.; Chen, K.Y.; Berndt, S.I.; He, X.; Wu, W.; Chang, J.; Zhang, X.C.; Huang, M.S.; Zheng, H.; Wang, J.; Zhao, X.|info:eu-repo/dai/nl/413577805; Li, Y.; Choi, J.E.; Su, W.C.; Park, K.H.; Sung, S.W.; Shu, X.O.; Chen, Y.M.; Liu, L.; Kang, C.H.; Hu, L.; Chen, C.H.; Pao, W.; Kim, Y.C.; Yang, T.Y.; Xu, J.; Guan, P.; Tan, W.; Su, J.; Wang, C.L.; Li, H.; Sihoe, A.D.; Zhao, Z.|info:eu-repo/dai/nl/304120995; Chen, Y.; Choi, Y.Y.; Hung, J.Y.; Kim, J.S.; Yoon, H.I.; Cai, Q.; Lin, C.C.; Park, I.K.; Xu, P.; Dong, J.; Kim, C.; He, Q; Perng, R.P.; Kohno, T.; Kweon, S.S.; Chen, C.Y.; Vermeulen, R.|info:eu-repo/dai/nl/216532620; Wu, J.; Lim, W.Y.; Chen, K.C.; Chow, W.H.; Ji, B.T.; Chan, J.K.; Chu, M.; Li, Y.J.; Yokota, J.; Li, J.; Chen, H.; Xiang, Y.B.; Yu, C.J.; Kunitoh, H.; Wu, G.; Jin, L.; Lo, Y.L.; Shiraishi, K.; Chen, Y.H.; Lin, H.C.; Wu, T.; WU, Y.; Yang, P.C.; Zhou, B.; Shin, M.H.; Fraumeni, J.F.; Lin, D.; Chanock, S.J.; Rothman, N.

2012-01-01

To identify common genetic variants that contribute to lung cancer susceptibility, we conducted a multistage genome-wide association study of lung cancer in Asian women who never smoked. We scanned 5,510 never-smoking female lung cancer cases and 4,544 controls drawn from 14 studies from mainland
Functional genomics identifies specific vulnerabilities in PTEN-deficient breast cancer.

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Tang, Yew Chung; Ho, Szu-Chi; Tan, Elisabeth; Ng, Alvin Wei Tian; McPherson, John R; Goh, Germaine Yen Lin; Teh, Bin Tean; Bard, Frederic; Rozen, Steven G

2018-03-22

Phosphatase and tensin homolog (PTEN) is one of the most frequently inactivated tumor suppressors in breast cancer. While PTEN itself is not considered a druggable target, PTEN synthetic-sick or synthetic-lethal (PTEN-SSL) genes are potential drug targets in PTEN-deficient breast cancers. Therefore, with the aim of identifying potential targets for precision breast cancer therapy, we sought to discover PTEN-SSL genes present in a broad spectrum of breast cancers. To discover broad-spectrum PTEN-SSL genes in breast cancer, we used a multi-step approach that started with (1) a genome-wide short interfering RNA (siRNA) screen of ~ 21,000 genes in a pair of isogenic human mammary epithelial cell lines, followed by (2) a short hairpin RNA (shRNA) screen of ~ 1200 genes focused on hits from the first screen in a panel of 11 breast cancer cell lines; we then determined reproducibility of hits by (3) identification of overlaps between our results and reanalyzed data from 3 independent gene-essentiality screens, and finally, for selected candidate PTEN-SSL genes we (4) confirmed PTEN-SSL activity using either drug sensitivity experiments in a panel of 19 cell lines or mutual exclusivity analysis of publicly available pan-cancer somatic mutation data. The screens (steps 1 and 2) and the reproducibility analysis (step 3) identified six candidate broad-spectrum PTEN-SSL genes (PIK3CB, ADAMTS20, AP1M2, HMMR, STK11, and NUAK1). PIK3CB was previously identified as PTEN-SSL, while the other five genes represent novel PTEN-SSL candidates. Confirmation studies (step 4) provided additional evidence that NUAK1 and STK11 have PTEN-SSL patterns of activity. Consistent with PTEN-SSL status, inhibition of the NUAK1 protein kinase by the small molecule drug HTH-01-015 selectively impaired viability in multiple PTEN-deficient breast cancer cell lines, while mutations affecting STK11 and PTEN were largely mutually exclusive across large pan-cancer data sets. Six genes showed PTEN
The Pediatric Cancer Genome Project

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Downing, James R; Wilson, Richard K; Zhang, Jinghui; Mardis, Elaine R; Pui, Ching-Hon; Ding, Li; Ley, Timothy J; Evans, William E

2013-01-01

The St. Jude Children’s Research Hospital–Washington University Pediatric Cancer Genome Project (PCGP) is participating in the international effort to identify somatic mutations that drive cancer. These cancer genome sequencing efforts will not only yield an unparalleled view of the altered signaling pathways in cancer but should also identify new targets against which novel therapeutics can be developed. Although these projects are still deep in the phase of generating primary DNA sequence data, important results are emerging and valuable community resources are being generated that should catalyze future cancer research. We describe here the rationale for conducting the PCGP, present some of the early results of this project and discuss the major lessons learned and how these will affect the application of genomic sequencing in the clinic. PMID:22641210
Genome-wide association study identifies new prostate cancer susceptibility loci

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Schumacher, Fredrick R.; Berndt, Sonja I.; Siddiq, Afshan

2011-01-01

Prostate cancer (PrCa) is the most common non-skin cancer diagnosed among males in developed countries and the second leading cause of cancer mortality, yet little is known regarding its etiology and factors that influence clinical outcome. Genome-wide association studies (GWAS) of PrCa have iden...
Evaluating genome-wide association study-identified breast cancer risk variants in African-American women.

Directory of Open Access Journals (Sweden)

Jirong Long

Full Text Available Genome-wide association studies (GWAS, conducted mostly in European or Asian descendants, have identified approximately 67 genetic susceptibility loci for breast cancer. Given the large differences in genetic architecture between the African-ancestry genome and genomes of Asians and Europeans, it is important to investigate these loci in African-ancestry populations. We evaluated index SNPs in all 67 breast cancer susceptibility loci identified to date in our study including up to 3,300 African-American women (1,231 cases and 2,069 controls, recruited in the Southern Community Cohort Study (SCCS and the Nashville Breast Health Study (NBHS. Seven SNPs were statistically significant (P ≤ 0.05 with the risk of overall breast cancer in the same direction as previously reported: rs10069690 (5p15/TERT, rs999737 (14q24/RAD51L1, rs13387042 (2q35/TNP1, rs1219648 (10q26/FGFR2, rs8170 (19p13/BABAM1, rs17817449 (16q12/FTO, and rs13329835 (16q23/DYL2. A marginally significant association (P<0.10 was found for three additional SNPs: rs1045485 (2q33/CASP8, rs4849887 (2q14/INHBB, and rs4808801 (19p13/ELL. Three additional SNPs, including rs1011970 (9p21/CDKN2A/2B, rs941764 (14q32/CCDC88C, and rs17529111 (6q14/FAM46A, showed a significant association in analyses conducted by breast cancer subtype. The risk of breast cancer was elevated with an increasing number of risk variants, as measured by quintile of the genetic risk score, from 1.00 (reference, to 1.75 (1.30-2.37, 1.56 (1.15-2.11, 2.02 (1.50-2.74 and 2.63 (1.96-3.52, respectively, (P = 7.8 × 10(-10. Results from this study highlight the need for large genetic studies in AAs to identify risk variants impacting this population.
Punctuated evolution of prostate cancer genomes.

Science.gov (United States)

Baca, Sylvan C; Prandi, Davide; Lawrence, Michael S; Mosquera, Juan Miguel; Romanel, Alessandro; Drier, Yotam; Park, Kyung; Kitabayashi, Naoki; MacDonald, Theresa Y; Ghandi, Mahmoud; Van Allen, Eliezer; Kryukov, Gregory V; Sboner, Andrea; Theurillat, Jean-Philippe; Soong, T David; Nickerson, Elizabeth; Auclair, Daniel; Tewari, Ashutosh; Beltran, Himisha; Onofrio, Robert C; Boysen, Gunther; Guiducci, Candace; Barbieri, Christopher E; Cibulskis, Kristian; Sivachenko, Andrey; Carter, Scott L; Saksena, Gordon; Voet, Douglas; Ramos, Alex H; Winckler, Wendy; Cipicchio, Michelle; Ardlie, Kristin; Kantoff, Philip W; Berger, Michael F; Gabriel, Stacey B; Golub, Todd R; Meyerson, Matthew; Lander, Eric S; Elemento, Olivier; Getz, Gad; Demichelis, Francesca; Rubin, Mark A; Garraway, Levi A

2013-04-25

The analysis of exonic DNA from prostate cancers has identified recurrently mutated genes, but the spectrum of genome-wide alterations has not been profiled extensively in this disease. We sequenced the genomes of 57 prostate tumors and matched normal tissues to characterize somatic alterations and to study how they accumulate during oncogenesis and progression. By modeling the genesis of genomic rearrangements, we identified abundant DNA translocations and deletions that arise in a highly interdependent manner. This phenomenon, which we term "chromoplexy," frequently accounts for the dysregulation of prostate cancer genes and appears to disrupt multiple cancer genes coordinately. Our modeling suggests that chromoplexy may induce considerable genomic derangement over relatively few events in prostate cancer and other neoplasms, supporting a model of punctuated cancer evolution. By characterizing the clonal hierarchy of genomic lesions in prostate tumors, we charted a path of oncogenic events along which chromoplexy may drive prostate carcinogenesis. Copyright © 2013 Elsevier Inc. All rights reserved.
Genomic analyses identify molecular subtypes of pancreatic cancer.

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Bailey, Peter; Chang, David K; Nones, Katia; Johns, Amber L; Patch, Ann-Marie; Gingras, Marie-Claude; Miller, David K; Christ, Angelika N; Bruxner, Tim J C; Quinn, Michael C; Nourse, Craig; Murtaugh, L Charles; Harliwong, Ivon; Idrisoglu, Senel; Manning, Suzanne; Nourbakhsh, Ehsan; Wani, Shivangi; Fink, Lynn; Holmes, Oliver; Chin, Venessa; Anderson, Matthew J; Kazakoff, Stephen; Leonard, Conrad; Newell, Felicity; Waddell, Nick; Wood, Scott; Xu, Qinying; Wilson, Peter J; Cloonan, Nicole; Kassahn, Karin S; Taylor, Darrin; Quek, Kelly; Robertson, Alan; Pantano, Lorena; Mincarelli, Laura; Sanchez, Luis N; Evers, Lisa; Wu, Jianmin; Pinese, Mark; Cowley, Mark J; Jones, Marc D; Colvin, Emily K; Nagrial, Adnan M; Humphrey, Emily S; Chantrill, Lorraine A; Mawson, Amanda; Humphris, Jeremy; Chou, Angela; Pajic, Marina; Scarlett, Christopher J; Pinho, Andreia V; Giry-Laterriere, Marc; Rooman, Ilse; Samra, Jaswinder S; Kench, James G; Lovell, Jessica A; Merrett, Neil D; Toon, Christopher W; Epari, Krishna; Nguyen, Nam Q; Barbour, Andrew; Zeps, Nikolajs; Moran-Jones, Kim; Jamieson, Nigel B; Graham, Janet S; Duthie, Fraser; Oien, Karin; Hair, Jane; Grützmann, Robert; Maitra, Anirban; Iacobuzio-Donahue, Christine A; Wolfgang, Christopher L; Morgan, Richard A; Lawlor, Rita T; Corbo, Vincenzo; Bassi, Claudio; Rusev, Borislav; Capelli, Paola; Salvia, Roberto; Tortora, Giampaolo; Mukhopadhyay, Debabrata; Petersen, Gloria M; Munzy, Donna M; Fisher, William E; Karim, Saadia A; Eshleman, James R; Hruban, Ralph H; Pilarsky, Christian; Morton, Jennifer P; Sansom, Owen J; Scarpa, Aldo; Musgrove, Elizabeth A; Bailey, Ulla-Maja Hagbo; Hofmann, Oliver; Sutherland, Robert L; Wheeler, David A; Gill, Anthony J; Gibbs, Richard A; Pearson, John V; Waddell, Nicola; Biankin, Andrew V; Grimmond, Sean M

2016-03-03

Integrated genomic analysis of 456 pancreatic ductal adenocarcinomas identified 32 recurrently mutated genes that aggregate into 10 pathways: KRAS, TGF-β, WNT, NOTCH, ROBO/SLIT signalling, G1/S transition, SWI-SNF, chromatin modification, DNA repair and RNA processing. Expression analysis defined 4 subtypes: (1) squamous; (2) pancreatic progenitor; (3) immunogenic; and (4) aberrantly differentiated endocrine exocrine (ADEX) that correlate with histopathological characteristics. Squamous tumours are enriched for TP53 and KDM6A mutations, upregulation of the TP63∆N transcriptional network, hypermethylation of pancreatic endodermal cell-fate determining genes and have a poor prognosis. Pancreatic progenitor tumours preferentially express genes involved in early pancreatic development (FOXA2/3, PDX1 and MNX1). ADEX tumours displayed upregulation of genes that regulate networks involved in KRAS activation, exocrine (NR5A2 and RBPJL), and endocrine differentiation (NEUROD1 and NKX2-2). Immunogenic tumours contained upregulated immune networks including pathways involved in acquired immune suppression. These data infer differences in the molecular evolution of pancreatic cancer subtypes and identify opportunities for therapeutic development.
A genome-wide association study identifies susceptibility loci for ovarian cancer at 2q31 and 8q24

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Goode, Ellen L; Chenevix-Trench, Georgia; Song, Honglin

2010-01-01

Ovarian cancer accounts for more deaths than all other gynecological cancers combined. To identify common low-penetrance ovarian cancer susceptibility genes, we conducted a genome-wide association study of 507,094 SNPs in 1,768 individuals with ovarian cancer (cases) and 2,354 controls, with foll...
A Gene Gravity Model for the Evolution of Cancer Genomes: A Study of 3,000 Cancer Genomes across 9 Cancer Types

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Lin, Chen-Ching; Zhao, Junfei; Jia, Peilin; Li, Wen-Hsiung; Zhao, Zhongming

2015-01-01

Cancer development and progression result from somatic evolution by an accumulation of genomic alterations. The effects of those alterations on the fitness of somatic cells lead to evolutionary adaptations such as increased cell proliferation, angiogenesis, and altered anticancer drug responses. However, there are few general mathematical models to quantitatively examine how perturbations of a single gene shape subsequent evolution of the cancer genome. In this study, we proposed the gene gravity model to study the evolution of cancer genomes by incorporating the genome-wide transcription and somatic mutation profiles of ~3,000 tumors across 9 cancer types from The Cancer Genome Atlas into a broad gene network. We found that somatic mutations of a cancer driver gene may drive cancer genome evolution by inducing mutations in other genes. This functional consequence is often generated by the combined effect of genetic and epigenetic (e.g., chromatin regulation) alterations. By quantifying cancer genome evolution using the gene gravity model, we identified six putative cancer genes (AHNAK, COL11A1, DDX3X, FAT4, STAG2, and SYNE1). The tumor genomes harboring the nonsynonymous somatic mutations in these genes had a higher mutation density at the genome level compared to the wild-type groups. Furthermore, we provided statistical evidence that hypermutation of cancer driver genes on inactive X chromosomes is a general feature in female cancer genomes. In summary, this study sheds light on the functional consequences and evolutionary characteristics of somatic mutations during tumorigenesis by propelling adaptive cancer genome evolution, which would provide new perspectives for cancer research and therapeutics. PMID:26352260

Genome-wide association study identifies multiple loci associated with both mammographic density and breast cancer risk

Science.gov (United States)

Lindström, Sara; Thompson, Deborah J.; Paterson, Andrew D.; Li, Jingmei; Gierach, Gretchen L.; Scott, Christopher; Stone, Jennifer; Douglas, Julie A.; dos-Santos-Silva, Isabel; Fernandez-Navarro, Pablo; Verghase, Jajini; Smith, Paula; Brown, Judith; Luben, Robert; Wareham, Nicholas J.; Loos, Ruth J.F.; Heit, John A.; Pankratz, V. Shane; Norman, Aaron; Goode, Ellen L.; Cunningham, Julie M.; deAndrade, Mariza; Vierkant, Robert A.; Czene, Kamila; Fasching, Peter A.; Baglietto, Laura; Southey, Melissa C.; Giles, Graham G.; Shah, Kaanan P.; Chan, Heang-Ping; Helvie, Mark A.; Beck, Andrew H.; Knoblauch, Nicholas W.; Hazra, Aditi; Hunter, David J.; Kraft, Peter; Pollan, Marina; Figueroa, Jonine D.; Couch, Fergus J.; Hopper, John L.; Hall, Per; Easton, Douglas F.; Boyd, Norman F.; Vachon, Celine M.; Tamimi, Rulla M.

2015-01-01

Mammographic density reflects the amount of stromal and epithelial tissues in relation to adipose tissue in the breast and is a strong risk factor for breast cancer. Here we report the results from meta-analysis of genome-wide association studies (GWAS) of three mammographic density phenotypes: dense area, non-dense area and percent density in up to 7,916 women in stage 1 and an additional 10,379 women in stage 2. We identify genome-wide significant (P<5×10−8) loci for dense area (AREG, ESR1, ZNF365, LSP1/TNNT3, IGF1, TMEM184B, SGSM3/MKL1), non-dense area (8p11.23) and percent density (PRDM6, 8p11.23, TMEM184B). Four of these regions are known breast cancer susceptibility loci, and four additional regions were found to be associated with breast cancer (P<0.05) in a large meta-analysis. These results provide further evidence of a shared genetic basis between mammographic density and breast cancer and illustrate the power of studying intermediate quantitative phenotypes to identify putative disease susceptibility loci. PMID:25342443
Characterizing genomic alterations in cancer by complementary functional associations.

Science.gov (United States)

Kim, Jong Wook; Botvinnik, Olga B; Abudayyeh, Omar; Birger, Chet; Rosenbluh, Joseph; Shrestha, Yashaswi; Abazeed, Mohamed E; Hammerman, Peter S; DiCara, Daniel; Konieczkowski, David J; Johannessen, Cory M; Liberzon, Arthur; Alizad-Rahvar, Amir Reza; Alexe, Gabriela; Aguirre, Andrew; Ghandi, Mahmoud; Greulich, Heidi; Vazquez, Francisca; Weir, Barbara A; Van Allen, Eliezer M; Tsherniak, Aviad; Shao, Diane D; Zack, Travis I; Noble, Michael; Getz, Gad; Beroukhim, Rameen; Garraway, Levi A; Ardakani, Masoud; Romualdi, Chiara; Sales, Gabriele; Barbie, David A; Boehm, Jesse S; Hahn, William C; Mesirov, Jill P; Tamayo, Pablo

2016-05-01

Systematic efforts to sequence the cancer genome have identified large numbers of mutations and copy number alterations in human cancers. However, elucidating the functional consequences of these variants, and their interactions to drive or maintain oncogenic states, remains a challenge in cancer research. We developed REVEALER, a computational method that identifies combinations of mutually exclusive genomic alterations correlated with functional phenotypes, such as the activation or gene dependency of oncogenic pathways or sensitivity to a drug treatment. We used REVEALER to uncover complementary genomic alterations associated with the transcriptional activation of β-catenin and NRF2, MEK-inhibitor sensitivity, and KRAS dependency. REVEALER successfully identified both known and new associations, demonstrating the power of combining functional profiles with extensive characterization of genomic alterations in cancer genomes.
Genome-wide association analysis of more than 120,000 individuals identifies 15 new susceptibility loci for breast cancer.

Science.gov (United States)

Michailidou, Kyriaki; Beesley, Jonathan; Lindstrom, Sara; Canisius, Sander; Dennis, Joe; Lush, Michael J; Maranian, Mel J; Bolla, Manjeet K; Wang, Qin; Shah, Mitul; Perkins, Barbara J; Czene, Kamila; Eriksson, Mikael; Darabi, Hatef; Brand, Judith S; Bojesen, Stig E; Nordestgaard, Børge G; Flyger, Henrik; Nielsen, Sune F; Rahman, Nazneen; Turnbull, Clare; Fletcher, Olivia; Peto, Julian; Gibson, Lorna; dos-Santos-Silva, Isabel; Chang-Claude, Jenny; Flesch-Janys, Dieter; Rudolph, Anja; Eilber, Ursula; Behrens, Sabine; Nevanlinna, Heli; Muranen, Taru A; Aittomäki, Kristiina; Blomqvist, Carl; Khan, Sofia; Aaltonen, Kirsimari; Ahsan, Habibul; Kibriya, Muhammad G; Whittemore, Alice S; John, Esther M; Malone, Kathleen E; Gammon, Marilie D; Santella, Regina M; Ursin, Giske; Makalic, Enes; Schmidt, Daniel F; Casey, Graham; Hunter, David J; Gapstur, Susan M; Gaudet, Mia M; Diver, W Ryan; Haiman, Christopher A; Schumacher, Fredrick; Henderson, Brian E; Le Marchand, Loic; Berg, Christine D; Chanock, Stephen J; Figueroa, Jonine; Hoover, Robert N; Lambrechts, Diether; Neven, Patrick; Wildiers, Hans; van Limbergen, Erik; Schmidt, Marjanka K; Broeks, Annegien; Verhoef, Senno; Cornelissen, Sten; Couch, Fergus J; Olson, Janet E; Hallberg, Emily; Vachon, Celine; Waisfisz, Quinten; Meijers-Heijboer, Hanne; Adank, Muriel A; van der Luijt, Rob B; Li, Jingmei; Liu, Jianjun; Humphreys, Keith; Kang, Daehee; Choi, Ji-Yeob; Park, Sue K; Yoo, Keun-Young; Matsuo, Keitaro; Ito, Hidemi; Iwata, Hiroji; Tajima, Kazuo; Guénel, Pascal; Truong, Thérèse; Mulot, Claire; Sanchez, Marie; Burwinkel, Barbara; Marme, Frederik; Surowy, Harald; Sohn, Christof; Wu, Anna H; Tseng, Chiu-chen; Van Den Berg, David; Stram, Daniel O; González-Neira, Anna; Benitez, Javier; Zamora, M Pilar; Perez, Jose Ignacio Arias; Shu, Xiao-Ou; Lu, Wei; Gao, Yu-Tang; Cai, Hui; Cox, Angela; Cross, Simon S; Reed, Malcolm W R; Andrulis, Irene L; Knight, Julia A; Glendon, Gord; Mulligan, Anna Marie; Sawyer, Elinor J; Tomlinson, Ian; Kerin, Michael J; Miller, Nicola; Lindblom, Annika; Margolin, Sara; Teo, Soo Hwang; Yip, Cheng Har; Taib, Nur Aishah Mohd; Tan, Gie-Hooi; Hooning, Maartje J; Hollestelle, Antoinette; Martens, John W M; Collée, J Margriet; Blot, William; Signorello, Lisa B; Cai, Qiuyin; Hopper, John L; Southey, Melissa C; Tsimiklis, Helen; Apicella, Carmel; Shen, Chen-Yang; Hsiung, Chia-Ni; Wu, Pei-Ei; Hou, Ming-Feng; Kristensen, Vessela N; Nord, Silje; Alnaes, Grethe I Grenaker; Giles, Graham G; Milne, Roger L; McLean, Catriona; Canzian, Federico; Trichopoulos, Dimitrios; Peeters, Petra; Lund, Eiliv; Sund, Malin; Khaw, Kay-Tee; Gunter, Marc J; Palli, Domenico; Mortensen, Lotte Maxild; Dossus, Laure; Huerta, Jose-Maria; Meindl, Alfons; Schmutzler, Rita K; Sutter, Christian; Yang, Rongxi; Muir, Kenneth; Lophatananon, Artitaya; Stewart-Brown, Sarah; Siriwanarangsan, Pornthep; Hartman, Mikael; Miao, Hui; Chia, Kee Seng; Chan, Ching Wan; Fasching, Peter A; Hein, Alexander; Beckmann, Matthias W; Haeberle, Lothar; Brenner, Hermann; Dieffenbach, Aida Karina; Arndt, Volker; Stegmaier, Christa; Ashworth, Alan; Orr, Nick; Schoemaker, Minouk J; Swerdlow, Anthony J; Brinton, Louise; Garcia-Closas, Montserrat; Zheng, Wei; Halverson, Sandra L; Shrubsole, Martha; Long, Jirong; Goldberg, Mark S; Labrèche, France; Dumont, Martine; Winqvist, Robert; Pylkäs, Katri; Jukkola-Vuorinen, Arja; Grip, Mervi; Brauch, Hiltrud; Hamann, Ute; Brüning, Thomas; Radice, Paolo; Peterlongo, Paolo; Manoukian, Siranoush; Bernard, Loris; Bogdanova, Natalia V; Dörk, Thilo; Mannermaa, Arto; Kataja, Vesa; Kosma, Veli-Matti; Hartikainen, Jaana M; Devilee, Peter; Tollenaar, Robert A E M; Seynaeve, Caroline; Van Asperen, Christi J; Jakubowska, Anna; Lubinski, Jan; Jaworska, Katarzyna; Huzarski, Tomasz; Sangrajrang, Suleeporn; Gaborieau, Valerie; Brennan, Paul; McKay, James; Slager, Susan; Toland, Amanda E; Ambrosone, Christine B; Yannoukakos, Drakoulis; Kabisch, Maria; Torres, Diana; Neuhausen, Susan L; Anton-Culver, Hoda; Luccarini, Craig; Baynes, Caroline; Ahmed, Shahana; Healey, Catherine S; Tessier, Daniel C; Vincent, Daniel; Bacot, Francois; Pita, Guillermo; Alonso, M Rosario; Álvarez, Nuria; Herrero, Daniel; Simard, Jacques; Pharoah, Paul P D P; Kraft, Peter; Dunning, Alison M; Chenevix-Trench, Georgia; Hall, Per; Easton, Douglas F

2015-04-01

Genome-wide association studies (GWAS) and large-scale replication studies have identified common variants in 79 loci associated with breast cancer, explaining ∼14% of the familial risk of the disease. To identify new susceptibility loci, we performed a meta-analysis of 11 GWAS, comprising 15,748 breast cancer cases and 18,084 controls together with 46,785 cases and 42,892 controls from 41 studies genotyped on a 211,155-marker custom array (iCOGS). Analyses were restricted to women of European ancestry. We generated genotypes for more than 11 million SNPs by imputation using the 1000 Genomes Project reference panel, and we identified 15 new loci associated with breast cancer at P association analysis with ChIP-seq chromatin binding data in mammary cell lines and ChIA-PET chromatin interaction data from ENCODE, we identified likely target genes in two regions: SETBP1 at 18q12.3 and RNF115 and PDZK1 at 1q21.1. One association appears to be driven by an amino acid substitution encoded in EXO1.
Identification of coding and non-coding mutational hotspots in cancer genomes.

Science.gov (United States)

Piraino, Scott W; Furney, Simon J

2017-01-05

The identification of mutations that play a causal role in tumour development, so called "driver" mutations, is of critical importance for understanding how cancers form and how they might be treated. Several large cancer sequencing projects have identified genes that are recurrently mutated in cancer patients, suggesting a role in tumourigenesis. While the landscape of coding drivers has been extensively studied and many of the most prominent driver genes are well characterised, comparatively less is known about the role of mutations in the non-coding regions of the genome in cancer development. The continuing fall in genome sequencing costs has resulted in a concomitant increase in the number of cancer whole genome sequences being produced, facilitating systematic interrogation of both the coding and non-coding regions of cancer genomes. To examine the mutational landscapes of tumour genomes we have developed a novel method to identify mutational hotspots in tumour genomes using both mutational data and information on evolutionary conservation. We have applied our methodology to over 1300 whole cancer genomes and show that it identifies prominent coding and non-coding regions that are known or highly suspected to play a role in cancer. Importantly, we applied our method to the entire genome, rather than relying on predefined annotations (e.g. promoter regions) and we highlight recurrently mutated regions that may have resulted from increased exposure to mutational processes rather than selection, some of which have been identified previously as targets of selection. Finally, we implicate several pan-cancer and cancer-specific candidate non-coding regions, which could be involved in tumourigenesis. We have developed a framework to identify mutational hotspots in cancer genomes, which is applicable to the entire genome. This framework identifies known and novel coding and non-coding mutional hotspots and can be used to differentiate candidate driver regions from
Genome-wide association analysis of more than 120,000 individuals identifies 15 new susceptibility loci for breast cancer

NARCIS (Netherlands)

K. Michailidou (Kyriaki); J. Beesley (Jonathan); S. Lindstrom (Stephen); S. Canisius (Sander); J. Dennis (Joe); M. Lush (Michael); M. Maranian (Melanie); M.K. Bolla (Manjeet); Q. Wang (Qing); M. Shah (Mitul); B. Perkins (Barbara); K. Czene (Kamila); M. Eriksson (Mikael); H. Darabi (Hatef); J.S. Brand (Judith S.); S.E. Bojesen (Stig); B.G. Nordestgaard (Børge); H. Flyger (Henrik); S.F. Nielsen (Sune); N. Rahman (Nazneen); C. Turnbull (Clare); O. Fletcher (Olivia); J. Peto (Julian); L.J. Gibson (Lorna); I. dos Santos Silva (Isabel); J. Chang-Claude (Jenny); D. Flesch-Janys (Dieter); A. Rudolph (Anja); U. Eilber (Ursula); T.W. Behrens (Timothy); H. Nevanlinna (Heli); T.A. Muranen (Taru); K. Aittomäki (Kristiina); C. Blomqvist (Carl); S. Khan (Sofia); K. Aaltonen (Kirsimari); H. Ahsan (Habibul); M.G. Kibriya (Muhammad); A.S. Whittemore (Alice S.); E.M. John (Esther M.); K.E. Malone (Kathleen E.); M.D. Gammon (Marilie); R.M. Santella (Regina M.); G. Ursin (Giske); E. Makalic (Enes); D.F. Schmidt (Daniel); G. Casey (Graham); D.J. Hunter (David J.); S.M. Gapstur (Susan M.); M.M. Gaudet (Mia); W.R. Diver (Ryan); C.A. Haiman (Christopher A.); F.R. Schumacher (Fredrick); B.E. Henderson (Brian); L. Le Marchand (Loic); C.D. Berg (Christine); S.J. Chanock (Stephen); J.D. Figueroa (Jonine); R.N. Hoover (Robert N.); D. Lambrechts (Diether); P. Neven (Patrick); H. Wildiers (Hans); E. van Limbergen (Erik); M.K. Schmidt (Marjanka); A. Broeks (Annegien); S. Verhoef; S. Cornelissen (Sten); F.J. Couch (Fergus); J.E. Olson (Janet); B. Hallberg (Boubou); C. Vachon (Celine); Q. Waisfisz (Quinten); E.J. Meijers-Heijboer (Hanne); M.A. Adank (Muriel); R.B. van der Luijt (Rob); J. Li (Jingmei); J. Liu (Jianjun); M.K. Humphreys (Manjeet); D. Kang (Daehee); J.-Y. Choi (Ji-Yeob); S.K. Park (Sue K.); K.Y. Yoo; K. Matsuo (Keitaro); H. Ito (Hidemi); H. Iwata (Hiroji); K. Tajima (Kazuo); P. Guénel (Pascal); T. Truong (Thérèse); C. Mulot (Claire); M. Sanchez (Marie); B. Burwinkel (Barbara); F. Marme (Federick); H. Surowy (Harald); C. Sohn (Christof); A.H. Wu (Anna H); C.-C. Tseng (Chiu-chen); D. Van Den Berg (David); D.O. Stram (Daniel O.); A. González-Neira (Anna); J. Benítez (Javier); M.P. Zamora (Pilar); J.I.A. Perez (Jose Ignacio Arias); X.-O. Shu (Xiao-Ou); W. Lu (Wei); Y. Gao; H. Cai (Hui); A. Cox (Angela); S.S. Cross (Simon); M.W.R. Reed (Malcolm); I.L. Andrulis (Irene); J.A. Knight (Julia); G. Glendon (Gord); A.-M. Mulligan (Anna-Marie); E.J. Sawyer (Elinor); I.P. Tomlinson (Ian); M. Kerin (Michael); N. Miller (Nicola); A. Lindblom (Annika); S. Margolin (Sara); S.H. Teo (Soo Hwang); C.H. Yip (Cheng Har); N.A.M. Taib (Nur Aishah Mohd); G.-H. Tan (Gie-Hooi); M.J. Hooning (Maartje); A. Hollestelle (Antoinette); J.W.M. Martens (John); J.M. Collée (Margriet); W.J. Blot (William); L.B. Signorello (Lisa B.); Q. Cai (Qiuyin); J. Hopper (John); M.C. Southey (Melissa); H. Tsimiklis (Helen); C. Apicella (Carmel); C-Y. Shen (Chen-Yang); C.-N. Hsiung (Chia-Ni); P.-E. Wu (Pei-Ei); M.-F. Hou (Ming-Feng); V. Kristensen (Vessela); S. Nord (Silje); G.G. Alnæs (Grethe); G.G. Giles (Graham G.); R.L. Milne (Roger); C.A. McLean (Catriona Ann); F. Canzian (Federico); D. Trichopoulos (Dimitrios); P.H.M. Peeters; E. Lund (Eiliv); R. Sund (Reijo); K.T. Khaw; M.J. Gunter (Marc J.); D. Palli (Domenico); L.M. Mortensen (Lotte Maxild); L. Dossus (Laure); J.-M. Huerta (Jose-Maria); A. Meindl (Alfons); R.K. Schmutzler (Rita); C. Sutter (Christian); R. Yang (Rongxi); K. Muir (Kenneth); A. Lophatananon (Artitaya); S. Stewart-Brown (Sarah); P. Siriwanarangsan (Pornthep); J.M. Hartman (Joost); X. Miao; K.S. Chia (Kee Seng); C.W. Chan (Ching Wan); P.A. Fasching (Peter); R. Hein (Rebecca); M.W. Beckmann (Matthias); L. Haeberle (Lothar); H. Brenner (Hermann); A.K. Dieffenbach (Aida Karina); V. Arndt (Volker); C. Stegmaier (Christa); A. Ashworth (Alan); N. Orr (Nick); M. Schoemaker (Minouk); A.J. Swerdlow (Anthony ); L.A. Brinton (Louise); M. García-Closas (Montserrat); W. Zheng (Wei); S.L. Halverson (Sandra L.); M. Shrubsole (Martha); J. Long (Jirong); M.S. Goldberg (Mark); F. Labrèche (France); M. Dumont (Martine); R. Winqvist (Robert); K. Pykäs (Katri); A. Jukkola-Vuorinen (Arja); M. Grip (Mervi); H. Brauch (Hiltrud); U. Hamann (Ute); T. Brüning (Thomas); P. Radice (Paolo); P. Peterlongo (Paolo); S. Manoukian (Siranoush); L. Bernard (Loris); N.V. Bogdanova (Natalia); T. Dörk (Thilo); A. Mannermaa (Arto); V. Kataja (Vesa); V-M. Kosma (Veli-Matti); J.M. Hartikainen (J.); P. Devilee (Peter); R.A.E.M. Tollenaar (Rob); C.M. Seynaeve (Caroline); C.J. van Asperen (Christi); A. Jakubowska (Anna); J. Lubinski (Jan); K. Jaworska (Katarzyna); T. Huzarski (Tomasz); S. Sangrajrang (Suleeporn); V. Gaborieau (Valerie); P. Brennan (Paul); J.D. McKay (James); S. Slager (Susan); A.E. Toland (Amanda); C.B. Ambrosone (Christine); D. Yannoukakos (Drakoulis); M. Kabisch (Maria); D. Torres (Diana); S.L. Neuhausen (Susan); H. Anton-Culver (Hoda); C. Luccarini (Craig); C. Baynes (Caroline); S. Ahmed (Shahana); S. Healey (Sue); D.C. Tessier (Daniel C.); D. Vincent (Daniel); F. Bacot (Francois); G. Pita (Guillermo); M.R. Alonso (Rosario); N. Álvarez (Nuria); D. Herrero (Daniel); J. Simard (Jacques); P.P.D.P. Pharoah (Paul P.D.P.); P. Kraft (Peter); A.M. Dunning (Alison); G. Chenevix-Trench (Georgia); P. Hall (Per); D.F. Easton (Douglas)

2015-01-01

textabstractGenome-wide association studies (GWAS) and large-scale replication studies have identified common variants in 79 loci associated with breast cancer, explaining ∼14% of the familial risk of the disease. To identify new susceptibility loci, we performed a meta-analysis of 11 GWAS,
Genome-wide methylation analysis identifies a core set of hypermethylated genes in CIMP-H colorectal cancer.

Science.gov (United States)

McInnes, Tyler; Zou, Donghui; Rao, Dasari S; Munro, Francesca M; Phillips, Vicky L; McCall, John L; Black, Michael A; Reeve, Anthony E; Guilford, Parry J

2017-03-28

Aberrant DNA methylation profiles are a characteristic of all known cancer types, epitomized by the CpG island methylator phenotype (CIMP) in colorectal cancer (CRC). Hypermethylation has been observed at CpG islands throughout the genome, but it is unclear which factors determine whether an individual island becomes methylated in cancer. DNA methylation in CRC was analysed using the Illumina HumanMethylation450K array. Differentially methylated loci were identified using Significance Analysis of Microarrays (SAM) and the Wilcoxon Signed Rank (WSR) test. Unsupervised hierarchical clustering was used to identify methylation subtypes in CRC. In this study we characterized the DNA methylation profiles of 94 CRC tissues and their matched normal counterparts. Consistent with previous studies, unsupervized hierarchical clustering of genome-wide methylation data identified three subtypes within the tumour samples, designated CIMP-H, CIMP-L and CIMP-N, that showed high, low and very low methylation levels, respectively. Differential methylation between normal and tumour samples was analysed at the individual CpG level, and at the gene level. The distribution of hypermethylation in CIMP-N tumours showed high inter-tumour variability and appeared to be highly stochastic in nature, whereas CIMP-H tumours exhibited consistent hypermethylation at a subset of genes, in addition to a highly variable background of hypermethylated genes. EYA4, TFPI2 and TLX1 were hypermethylated in more than 90% of all tumours examined. One-hundred thirty-two genes were hypermethylated in 100% of CIMP-H tumours studied and these were highly enriched for functions relating to skeletal system development (Bonferroni adjusted p value =2.88E-15), segment specification (adjusted p value =9.62E-11), embryonic development (adjusted p value =1.52E-04), mesoderm development (adjusted p value =1.14E-20), and ectoderm development (adjusted p value =7.94E-16). Our genome-wide characterization of DNA
Genome-wide association analysis of more than 120,000 individuals identifies 15 new susceptibility loci for breast cancer

NARCIS (Netherlands)

Michailidou, Kyriaki; Beesley, Jonathan; Lindstrom, Sara; Canisius, Sander; Dennis, Joe; Lush, Michael J.; Maranian, Mel J.; Bolla, Manjeet K.; Wang, Qin; Shah, Mitul; Perkins, Barbara J.; Czene, Kamila; Eriksson, Mikael; Darabi, Hatef; Brand, Judith S.; Bojesen, Stig E.; Nordestgaard, Borge G.; Flyger, Henrik; Nielsen, Sune F.; Rahman, Nazneen; Turnbull, Clare; Fletcher, Olivia; Peto, Julian; Gibson, Lorna; dos-Santos-Silva, Isabel; Chang-Claude, Jenny; Flesch-Janys, Dieter; Rudolph, Anja; Eilber, Ursula; Behrens, Sabine; Nevanlinna, Heli; Muranen, Taru A.; Aittomaki, Kristiina; Blomqvist, Carl; Khan, Sofia; Aaltonen, Kirsimari; Ahsan, Habibul; Kibriya, Muhammad G.; Whittemore, Alice S.; John, Esther M.; Malone, Kathleen E.; Gammon, Marilie D.; Santella, Regina M.; Ursin, Giske; Makalic, Enes; Schmidt, Daniel F.; Casey, Graham; Hunter, David J.; Gapstur, Susan M.; Gaudet, Mia M.; Diver, W. Ryan; Haiman, Christopher A.; Schumacher, Fredrick; Henderson, Brian E.; Le Marchand, Loic; Berg, Christine D.; Chanock, Stephen J.; Figueroa, Jonine; Hoover, Robert N.; Lambrechts, Diether; Neven, Patrick; Wildiers, Hans; van Limbergen, Erik; Schmidt, Marjanka K.; Broeks, Annegien; Verhoef, Senno; Cornelissen, Sten; Couch, Fergus J.; Olson, Janet E.; Hallberg, Emily; Vachon, Celine; Waisfisz, Quinten; Meijers-Heijboer, Hanne; Adank, Muriel A.; van der Luijt, Rob B.; Li, Jingmei; Liu, Jianjun; Humphreys, Keith; Kang, Daehee; Choi, Ji-Yeob; Park, Sue K.; Yoo, Keun-Young; Matsuo, Keitaro; Ito, Hidemi; Iwata, Hiroji; Tajima, Kazuo; Guenel, Pascal; Truong, Therese; Mulot, Claire; Sanchez, Marie; Burwinkel, Barbara; Marme, Frederik; Surowy, Harald; Sohn, Christof; Wu, Anna H.; Tseng, Chiu-chen; Van den Berg, David; Stram, Daniel O.; Gonzalez-Neira, Anna; Benitez, Javier; Zamora, M. Pilar; Arias Perez, Jose Ignacio; Shu, Xiao-Ou; Lu, Wei; Gao, Yu-Tang; Cai, Hui; Cox, Angela; Cross, Simon S.; Reed, Malcolm W. R.; Andrulis, Irene L.; Knight, Julia A.; Glendon, Gord; Mulligan, Anna Marie; Sawyer, Elinor J.; Tomlinson, Ian; Kerin, Michael J.; Miller, Nicola; Lindblom, Annika; Margolin, Sara; Teo, Soo Hwang; Yip, Cheng Har; Taib, Nur Aishah Mohd; Tan, Gie-Hooi; Hooning, Maartje J.; Hollestelle, Antoinette; Martens, John W. M.; Collee, J. Margriet; Blot, William; Signorello, Lisa B.; Cai, Qiuyin; Hopper, John L.; Southey, Melissa C.; Tsimiklis, Helen; Apicella, Carmel; Shen, Chen-Yang; Hsiung, Chia-Ni; Wu, Pei-Ei; Hou, Ming-Feng; Kristensen, Vessela N.; Nord, Silje; Alnaes, Grethe I. Grenaker; Giles, Graham G.; Milne, Roger L.; McLean, Catriona; Canzian, Federico; Trichopoulos, Dimitrios; Peeters, Petra; Lund, Eiliv; Sund, Malin; Khaw, Kay-Tee; Gunter, Marc J.; Palli, Domenico; Mortensen, Lotte Maxild; Dossus, Laure; Huerta, Jose-Maria; Meindl, Alfons; Schmutzler, Rita K.; Sutter, Christian; Yang, Rongxi; Muir, Kenneth; Lophatananon, Artitaya; Stewart-Brown, Sarah; Siriwanarangsan, Pornthep; Hartman, Mikael; Miao, Hui; Chia, Kee Seng; Chan, Ching Wan; Fasching, Peter A.; Hein, Alexander; Beckmann, Matthias W.; Haeberle, Lothar; Brenner, Hermann; Dieffenbach, Aida Karina; Arndt, Volker; Stegmaier, Christa; Ashworth, Alan; Orr, Nick; Schoemaker, Minouk J.; Swerdlow, Anthony J.; Brinton, Louise; Garcia-Closas, Montserrat; Zheng, Wei; Halverson, Sandra L.; Shrubsole, Martha; Long, Jirong; Goldberg, Mark S.; Labreche, France; Dumont, Martine; Winqvist, Robert; Pylkas, Katri; Jukkola-Vuorinen, Arja; Grip, Mervi; Brauch, Hiltrud; Hamann, Ute; Bruening, Thomas; Radice, Paolo; Peterlongo, Paolo; Manoukian, Siranoush; Bernard, Loris; Bogdanova, Natalia V.; Doerk, Thilo; Mannermaa, Arto; Kataja, Vesa; Kosma, Veli-Matti; Hartikainen, Jaana M.; Devilee, Peter; Tollenaar, Robert A. E. M.; Seynaeve, Caroline; Van Asperen, Christi J.; Jakubowska, Anna; Lubinski, Jan; Jaworska, Katarzyna; Huzarski, Tomasz; Sangrajrang, Suleeporn; Gaborieau, Valerie; Brennan, Paul; Mckay, James; Slager, Susan; Toland, Amanda E.; Ambrosone, Christine B.; Yannoukakos, Drakoulis; Kabisch, Maria; Torres, Diana; Neuhausen, Susan L.; Anton-Culver, Hoda; Luccarini, Craig; Baynes, Caroline; Ahmed, Shahana; Healey, Catherine S.; Tessier, Daniel C.; Vincent, Daniel; Bacot, Francois; Pita, Guillermo; Rosario Alonso, M.; Alvarez, Nuria; Herrero, Daniel; Simard, Jacques; Pharoah, Paul P. D. P.; Kraft, Peter; Dunning, Alison M.; Chenevix-Trench, Georgia; Hall, Per; Easton, Douglas F.

Genome-wide association studies (GWAS) and large-scale replication studies have identified common variants in 79 loci associated with breast cancer, explaining similar to 14% of the familial risk of the disease. To identify new susceptibility loci, we performed a meta-analysis of 11 GWAS, comprising
Genome-wide association analysis of more than 120,000 individuals identifies 15 new susceptibility loci for breast cancer

DEFF Research Database (Denmark)

Michailidou, Kyriaki; Beesley, Jonathan; Lindstrom, Sara

2015-01-01

Genome-wide association studies (GWAS) and large-scale replication studies have identified common variants in 79 loci associated with breast cancer, explaining ∼14% of the familial risk of the disease. To identify new susceptibility loci, we performed a meta-analysis of 11 GWAS, comprising 15,748...
Genome-wide association analysis of more than 120,000 individuals identifies 15 new susceptibility loci for breast cancer.

OpenAIRE

Michailidou, Kyriaki; Beesley, Jonathan; Lindstrom, Sara; Canisius, Sander; Dennis, Joe; Lush, Michael J; Maranian, Mel J; Bolla, Manjeet K; Wang, Qin; Shah, Mitulkumar Nandlal; Perkins, Barbara J; Czene, Kamila; Eriksson, Mikael; Darabi, Hatef; Brand, Judith S

2015-01-01

Genome-wide association studies (GWAS) and large-scale replication studies have identified common variants in 79 loci associated with breast cancer, explaining ~14% of the familial risk of the disease. To identify new susceptibility loci, we performed a meta-analysis of 11 GWAS, comprising 15,748 breast cancer cases and 18,084 controls together with 46,785 cases and 42,892 controls from 41 studies genotyped on a 211,155-marker custom array (iCOGS). Analyses were restricted to women of Europea...
Genome-wide association analysis of more than 120,000 individuals identifies 15 new susceptibility loci for breast cancer

OpenAIRE

Michailidou, Kyriaki; Beesley, Jonathan; Lindstrom, Stephen; Canisius, Sander; Dennis, Joe; Lush, Michael; Maranian, Melanie; Bolla, Manjeet; Wang, Qing; Shah, Mitul; Perkins, Barbara; Czene, Kamila; Eriksson, Mikael; Darabi, Hatef; Brand, Judith S.

2015-01-01

textabstractGenome-wide association studies (GWAS) and large-scale replication studies have identified common variants in 79 loci associated with breast cancer, explaining ∼14% of the familial risk of the disease. To identify new susceptibility loci, we performed a meta-analysis of 11 GWAS, comprising 15,748 breast cancer cases and 18,084 controls together with 46,785 cases and 42,892 controls from 41 studies genotyped on a 211,155-marker custom array (iCOGS). Analyses were restricted to wome...
Genome-wide identification of significant aberrations in cancer genome.

Science.gov (United States)

Yuan, Xiguo; Yu, Guoqiang; Hou, Xuchu; Shih, Ie-Ming; Clarke, Robert; Zhang, Junying; Hoffman, Eric P; Wang, Roger R; Zhang, Zhen; Wang, Yue

2012-07-27

Somatic Copy Number Alterations (CNAs) in human genomes are present in almost all human cancers. Systematic efforts to characterize such structural variants must effectively distinguish significant consensus events from random background aberrations. Here we introduce Significant Aberration in Cancer (SAIC), a new method for characterizing and assessing the statistical significance of recurrent CNA units. Three main features of SAIC include: (1) exploiting the intrinsic correlation among consecutive probes to assign a score to each CNA unit instead of single probes; (2) performing permutations on CNA units that preserve correlations inherent in the copy number data; and (3) iteratively detecting Significant Copy Number Aberrations (SCAs) and estimating an unbiased null distribution by applying an SCA-exclusive permutation scheme. We test and compare the performance of SAIC against four peer methods (GISTIC, STAC, KC-SMART, CMDS) on a large number of simulation datasets. Experimental results show that SAIC outperforms peer methods in terms of larger area under the Receiver Operating Characteristics curve and increased detection power. We then apply SAIC to analyze structural genomic aberrations acquired in four real cancer genome-wide copy number data sets (ovarian cancer, metastatic prostate cancer, lung adenocarcinoma, glioblastoma). When compared with previously reported results, SAIC successfully identifies most SCAs known to be of biological significance and associated with oncogenes (e.g., KRAS, CCNE1, and MYC) or tumor suppressor genes (e.g., CDKN2A/B). Furthermore, SAIC identifies a number of novel SCAs in these copy number data that encompass tumor related genes and may warrant further studies. Supported by a well-grounded theoretical framework, SAIC has been developed and used to identify SCAs in various cancer copy number data sets, providing useful information to study the landscape of cancer genomes. Open-source and platform-independent SAIC software is
Genome-wide meta-analysis identifies five new susceptibility loci for pancreatic cancer.

Science.gov (United States)

Klein, Alison P; Wolpin, Brian M; Risch, Harvey A; Stolzenberg-Solomon, Rachael Z; Mocci, Evelina; Zhang, Mingfeng; Canzian, Federico; Childs, Erica J; Hoskins, Jason W; Jermusyk, Ashley; Zhong, Jun; Chen, Fei; Albanes, Demetrius; Andreotti, Gabriella; Arslan, Alan A; Babic, Ana; Bamlet, William R; Beane-Freeman, Laura; Berndt, Sonja I; Blackford, Amanda; Borges, Michael; Borgida, Ayelet; Bracci, Paige M; Brais, Lauren; Brennan, Paul; Brenner, Hermann; Bueno-de-Mesquita, Bas; Buring, Julie; Campa, Daniele; Capurso, Gabriele; Cavestro, Giulia Martina; Chaffee, Kari G; Chung, Charles C; Cleary, Sean; Cotterchio, Michelle; Dijk, Frederike; Duell, Eric J; Foretova, Lenka; Fuchs, Charles; Funel, Niccola; Gallinger, Steven; M Gaziano, J Michael; Gazouli, Maria; Giles, Graham G; Giovannucci, Edward; Goggins, Michael; Goodman, Gary E; Goodman, Phyllis J; Hackert, Thilo; Haiman, Christopher; Hartge, Patricia; Hasan, Manal; Hegyi, Peter; Helzlsouer, Kathy J; Herman, Joseph; Holcatova, Ivana; Holly, Elizabeth A; Hoover, Robert; Hung, Rayjean J; Jacobs, Eric J; Jamroziak, Krzysztof; Janout, Vladimir; Kaaks, Rudolf; Khaw, Kay-Tee; Klein, Eric A; Kogevinas, Manolis; Kooperberg, Charles; Kulke, Matthew H; Kupcinskas, Juozas; Kurtz, Robert J; Laheru, Daniel; Landi, Stefano; Lawlor, Rita T; Lee, I-Min; LeMarchand, Loic; Lu, Lingeng; Malats, Núria; Mambrini, Andrea; Mannisto, Satu; Milne, Roger L; Mohelníková-Duchoňová, Beatrice; Neale, Rachel E; Neoptolemos, John P; Oberg, Ann L; Olson, Sara H; Orlow, Irene; Pasquali, Claudio; Patel, Alpa V; Peters, Ulrike; Pezzilli, Raffaele; Porta, Miquel; Real, Francisco X; Rothman, Nathaniel; Scelo, Ghislaine; Sesso, Howard D; Severi, Gianluca; Shu, Xiao-Ou; Silverman, Debra; Smith, Jill P; Soucek, Pavel; Sund, Malin; Talar-Wojnarowska, Renata; Tavano, Francesca; Thornquist, Mark D; Tobias, Geoffrey S; Van Den Eeden, Stephen K; Vashist, Yogesh; Visvanathan, Kala; Vodicka, Pavel; Wactawski-Wende, Jean; Wang, Zhaoming; Wentzensen, Nicolas; White, Emily; Yu, Herbert; Yu, Kai; Zeleniuch-Jacquotte, Anne; Zheng, Wei; Kraft, Peter; Li, Donghui; Chanock, Stephen; Obazee, Ofure; Petersen, Gloria M; Amundadottir, Laufey T

2018-02-08

In 2020, 146,063 deaths due to pancreatic cancer are estimated to occur in Europe and the United States combined. To identify common susceptibility alleles, we performed the largest pancreatic cancer GWAS to date, including 9040 patients and 12,496 controls of European ancestry from the Pancreatic Cancer Cohort Consortium (PanScan) and the Pancreatic Cancer Case-Control Consortium (PanC4). Here, we find significant evidence of a novel association at rs78417682 (7p12/TNS3, P = 4.35 × 10 -8 ). Replication of 10 promising signals in up to 2737 patients and 4752 controls from the PANcreatic Disease ReseArch (PANDoRA) consortium yields new genome-wide significant loci: rs13303010 at 1p36.33 (NOC2L, P = 8.36 × 10 -14 ), rs2941471 at 8q21.11 (HNF4G, P = 6.60 × 10 -10 ), rs4795218 at 17q12 (HNF1B, P = 1.32 × 10 -8 ), and rs1517037 at 18q21.32 (GRP, P = 3.28 × 10 -8 ). rs78417682 is not statistically significantly associated with pancreatic cancer in PANDoRA. Expression quantitative trait locus analysis in three independent pancreatic data sets provides molecular support of NOC2L as a pancreatic cancer susceptibility gene.
Genomic and Molecular Landscape of DNA Damage Repair Deficiency across The Cancer Genome Atlas

Directory of Open Access Journals (Sweden)

Theo A. Knijnenburg

2018-04-01

Full Text Available Summary: DNA damage repair (DDR pathways modulate cancer risk, progression, and therapeutic response. We systematically analyzed somatic alterations to provide a comprehensive view of DDR deficiency across 33 cancer types. Mutations with accompanying loss of heterozygosity were observed in over 1/3 of DDR genes, including TP53 and BRCA1/2. Other prevalent alterations included epigenetic silencing of the direct repair genes EXO5, MGMT, and ALKBH3 in ∼20% of samples. Homologous recombination deficiency (HRD was present at varying frequency in many cancer types, most notably ovarian cancer. However, in contrast to ovarian cancer, HRD was associated with worse outcomes in several other cancers. Protein structure-based analyses allowed us to predict functional consequences of rare, recurrent DDR mutations. A new machine-learning-based classifier developed from gene expression data allowed us to identify alterations that phenocopy deleterious TP53 mutations. These frequent DDR gene alterations in many human cancers have functional consequences that may determine cancer progression and guide therapy. : Knijnenburg et al. present The Cancer Genome Atlas (TCGA Pan-Cancer analysis of DNA damage repair (DDR deficiency in cancer. They use integrative genomic and molecular analyses to identify frequent DDR alterations across 33 cancer types, correlate gene- and pathway-level alterations with genome-wide measures of genome instability and impaired function, and demonstrate the prognostic utility of DDR deficiency scores. Keywords: The Cancer Genome Atlas PanCanAtlas project, DNA damage repair, somatic mutations, somatic copy-number alterations, epigenetic silencing, DNA damage footprints, mutational signatures, integrative statistical analysis, protein structure analysis
Comprehensive Analysis of Cancer-Proteogenome to Identify Biomarkers for the Early Diagnosis and Prognosis of Cancer.

Science.gov (United States)

Shukla, Hem D

2017-10-25

During the past century, our understanding of cancer diagnosis and treatment has been based on a monogenic approach, and as a consequence our knowledge of the clinical genetic underpinnings of cancer is incomplete. Since the completion of the human genome in 2003, it has steered us into therapeutic target discovery, enabling us to mine the genome using cutting edge proteogenomics tools. A number of novel and promising cancer targets have emerged from the genome project for diagnostics, therapeutics, and prognostic markers, which are being used to monitor response to cancer treatment. The heterogeneous nature of cancer has hindered progress in understanding the underlying mechanisms that lead to abnormal cellular growth. Since, the start of The Cancer Genome Atlas (TCGA), and the International Genome consortium projects, there has been tremendous progress in genome sequencing and immense numbers of cancer genomes have been completed, and this approach has transformed our understanding of the diagnosis and treatment of different types of cancers. By employing Genomics and proteomics technologies, an immense amount of genomic data is being generated on clinical tumors, which has transformed the cancer landscape and has the potential to transform cancer diagnosis and prognosis. A complete molecular view of the cancer landscape is necessary for understanding the underlying mechanisms of cancer initiation to improve diagnosis and prognosis, which ultimately will lead to personalized treatment. Interestingly, cancer proteome analysis has also allowed us to identify biomarkers to monitor drug and radiation resistance in patients undergoing cancer treatment. Further, TCGA-funded studies have allowed for the genomic and transcriptomic characterization of targeted cancers, this analysis aiding the development of targeted therapies for highly lethal malignancy. High-throughput technologies, such as complete proteome, epigenome, protein-protein interaction, and pharmacogenomics
Genome-wide identification of significant aberrations in cancer genome

Directory of Open Access Journals (Sweden)

Yuan Xiguo

2012-07-01

Full Text Available Abstract Background Somatic Copy Number Alterations (CNAs in human genomes are present in almost all human cancers. Systematic efforts to characterize such structural variants must effectively distinguish significant consensus events from random background aberrations. Here we introduce Significant Aberration in Cancer (SAIC, a new method for characterizing and assessing the statistical significance of recurrent CNA units. Three main features of SAIC include: (1 exploiting the intrinsic correlation among consecutive probes to assign a score to each CNA unit instead of single probes; (2 performing permutations on CNA units that preserve correlations inherent in the copy number data; and (3 iteratively detecting Significant Copy Number Aberrations (SCAs and estimating an unbiased null distribution by applying an SCA-exclusive permutation scheme. Results We test and compare the performance of SAIC against four peer methods (GISTIC, STAC, KC-SMART, CMDS on a large number of simulation datasets. Experimental results show that SAIC outperforms peer methods in terms of larger area under the Receiver Operating Characteristics curve and increased detection power. We then apply SAIC to analyze structural genomic aberrations acquired in four real cancer genome-wide copy number data sets (ovarian cancer, metastatic prostate cancer, lung adenocarcinoma, glioblastoma. When compared with previously reported results, SAIC successfully identifies most SCAs known to be of biological significance and associated with oncogenes (e.g., KRAS, CCNE1, and MYC or tumor suppressor genes (e.g., CDKN2A/B. Furthermore, SAIC identifies a number of novel SCAs in these copy number data that encompass tumor related genes and may warrant further studies. Conclusions Supported by a well-grounded theoretical framework, SAIC has been developed and used to identify SCAs in various cancer copy number data sets, providing useful information to study the landscape of cancer genomes
Genome-wide association studies identify four ER negative-specific breast cancer risk loci.

Science.gov (United States)

Garcia-Closas, Montserrat; Couch, Fergus J; Lindstrom, Sara; Michailidou, Kyriaki; Schmidt, Marjanka K; Brook, Mark N; Orr, Nick; Rhie, Suhn Kyong; Riboli, Elio; Feigelson, Heather S; Le Marchand, Loic; Buring, Julie E; Eccles, Diana; Miron, Penelope; Fasching, Peter A; Brauch, Hiltrud; Chang-Claude, Jenny; Carpenter, Jane; Godwin, Andrew K; Nevanlinna, Heli; Giles, Graham G; Cox, Angela; Hopper, John L; Bolla, Manjeet K; Wang, Qin; Dennis, Joe; Dicks, Ed; Howat, Will J; Schoof, Nils; Bojesen, Stig E; Lambrechts, Diether; Broeks, Annegien; Andrulis, Irene L; Guénel, Pascal; Burwinkel, Barbara; Sawyer, Elinor J; Hollestelle, Antoinette; Fletcher, Olivia; Winqvist, Robert; Brenner, Hermann; Mannermaa, Arto; Hamann, Ute; Meindl, Alfons; Lindblom, Annika; Zheng, Wei; Devillee, Peter; Goldberg, Mark S; Lubinski, Jan; Kristensen, Vessela; Swerdlow, Anthony; Anton-Culver, Hoda; Dörk, Thilo; Muir, Kenneth; Matsuo, Keitaro; Wu, Anna H; Radice, Paolo; Teo, Soo Hwang; Shu, Xiao-Ou; Blot, William; Kang, Daehee; Hartman, Mikael; Sangrajrang, Suleeporn; Shen, Chen-Yang; Southey, Melissa C; Park, Daniel J; Hammet, Fleur; Stone, Jennifer; Veer, Laura J Van't; Rutgers, Emiel J; Lophatananon, Artitaya; Stewart-Brown, Sarah; Siriwanarangsan, Pornthep; Peto, Julian; Schrauder, Michael G; Ekici, Arif B; Beckmann, Matthias W; Dos Santos Silva, Isabel; Johnson, Nichola; Warren, Helen; Tomlinson, Ian; Kerin, Michael J; Miller, Nicola; Marme, Federick; Schneeweiss, Andreas; Sohn, Christof; Truong, Therese; Laurent-Puig, Pierre; Kerbrat, Pierre; Nordestgaard, Børge G; Nielsen, Sune F; Flyger, Henrik; Milne, Roger L; Perez, Jose Ignacio Arias; Menéndez, Primitiva; Müller, Heiko; Arndt, Volker; Stegmaier, Christa; Lichtner, Peter; Lochmann, Magdalena; Justenhoven, Christina; Ko, Yon-Dschun; Muranen, Taru A; Aittomäki, Kristiina; Blomqvist, Carl; Greco, Dario; Heikkinen, Tuomas; Ito, Hidemi; Iwata, Hiroji; Yatabe, Yasushi; Antonenkova, Natalia N; Margolin, Sara; Kataja, Vesa; Kosma, Veli-Matti; Hartikainen, Jaana M; Balleine, Rosemary; Tseng, Chiu-Chen; Berg, David Van Den; Stram, Daniel O; Neven, Patrick; Dieudonné, Anne-Sophie; Leunen, Karin; Rudolph, Anja; Nickels, Stefan; Flesch-Janys, Dieter; Peterlongo, Paolo; Peissel, Bernard; Bernard, Loris; Olson, Janet E; Wang, Xianshu; Stevens, Kristen; Severi, Gianluca; Baglietto, Laura; McLean, Catriona; Coetzee, Gerhard A; Feng, Ye; Henderson, Brian E; Schumacher, Fredrick; Bogdanova, Natalia V; Labrèche, France; Dumont, Martine; Yip, Cheng Har; Taib, Nur Aishah Mohd; Cheng, Ching-Yu; Shrubsole, Martha; Long, Jirong; Pylkäs, Katri; Jukkola-Vuorinen, Arja; Kauppila, Saila; Knight, Julia A; Glendon, Gord; Mulligan, Anna Marie; Tollenaar, Robertus A E M; Seynaeve, Caroline M; Kriege, Mieke; Hooning, Maartje J; van den Ouweland, Ans M W; van Deurzen, Carolien H M; Lu, Wei; Gao, Yu-Tang; Cai, Hui; Balasubramanian, Sabapathy P; Cross, Simon S; Reed, Malcolm W R; Signorello, Lisa; Cai, Qiuyin; Shah, Mitul; Miao, Hui; Chan, Ching Wan; Chia, Kee Seng; Jakubowska, Anna; Jaworska, Katarzyna; Durda, Katarzyna; Hsiung, Chia-Ni; Wu, Pei-Ei; Yu, Jyh-Cherng; Ashworth, Alan; Jones, Michael; Tessier, Daniel C; González-Neira, Anna; Pita, Guillermo; Alonso, M Rosario; Vincent, Daniel; Bacot, Francois; Ambrosone, Christine B; Bandera, Elisa V; John, Esther M; Chen, Gary K; Hu, Jennifer J; Rodriguez-Gil, Jorge L; Bernstein, Leslie; Press, Michael F; Ziegler, Regina G; Millikan, Robert M; Deming-Halverson, Sandra L; Nyante, Sarah; Ingles, Sue A; Waisfisz, Quinten; Tsimiklis, Helen; Makalic, Enes; Schmidt, Daniel; Bui, Minh; Gibson, Lorna; Müller-Myhsok, Bertram; Schmutzler, Rita K; Hein, Rebecca; Dahmen, Norbert; Beckmann, Lars; Aaltonen, Kirsimari; Czene, Kamila; Irwanto, Astrid; Liu, Jianjun; Turnbull, Clare; Rahman, Nazneen; Meijers-Heijboer, Hanne; Uitterlinden, Andre G; Rivadeneira, Fernando; Olswold, Curtis; Slager, Susan; Pilarski, Robert; Ademuyiwa, Foluso; Konstantopoulou, Irene; Martin, Nicholas G; Montgomery, Grant W; Slamon, Dennis J; Rauh, Claudia; Lux, Michael P; Jud, Sebastian M; Bruning, Thomas; Weaver, Joellen; Sharma, Priyanka; Pathak, Harsh; Tapper, Will; Gerty, Sue; Durcan, Lorraine; Trichopoulos, Dimitrios; Tumino, Rosario; Peeters, Petra H; Kaaks, Rudolf; Campa, Daniele; Canzian, Federico; Weiderpass, Elisabete; Johansson, Mattias; Khaw, Kay-Tee; Travis, Ruth; Clavel-Chapelon, Françoise; Kolonel, Laurence N; Chen, Constance; Beck, Andy; Hankinson, Susan E; Berg, Christine D; Hoover, Robert N; Lissowska, Jolanta; Figueroa, Jonine D; Chasman, Daniel I; Gaudet, Mia M; Diver, W Ryan; Willett, Walter C; Hunter, David J; Simard, Jacques; Benitez, Javier; Dunning, Alison M; Sherman, Mark E; Chenevix-Trench, Georgia; Chanock, Stephen J; Hall, Per; Pharoah, Paul D P; Vachon, Celine; Easton, Douglas F; Haiman, Christopher A; Kraft, Peter

2013-04-01

Estrogen receptor (ER)-negative tumors represent 20-30% of all breast cancers, with a higher proportion occurring in younger women and women of African ancestry. The etiology and clinical behavior of ER-negative tumors are different from those of tumors expressing ER (ER positive), including differences in genetic predisposition. To identify susceptibility loci specific to ER-negative disease, we combined in a meta-analysis 3 genome-wide association studies of 4,193 ER-negative breast cancer cases and 35,194 controls with a series of 40 follow-up studies (6,514 cases and 41,455 controls), genotyped using a custom Illumina array, iCOGS, developed by the Collaborative Oncological Gene-environment Study (COGS). SNPs at four loci, 1q32.1 (MDM4, P = 2.1 × 10(-12) and LGR6, P = 1.4 × 10(-8)), 2p24.1 (P = 4.6 × 10(-8)) and 16q12.2 (FTO, P = 4.0 × 10(-8)), were associated with ER-negative but not ER-positive breast cancer (P > 0.05). These findings provide further evidence for distinct etiological pathways associated with invasive ER-positive and ER-negative breast cancers.
Comprehensive Analysis of Cancer-Proteogenome to Identify Biomarkers for the Early Diagnosis and Prognosis of Cancer

Directory of Open Access Journals (Sweden)

Hem D. Shukla

2017-10-01

Full Text Available During the past century, our understanding of cancer diagnosis and treatment has been based on a monogenic approach, and as a consequence our knowledge of the clinical genetic underpinnings of cancer is incomplete. Since the completion of the human genome in 2003, it has steered us into therapeutic target discovery, enabling us to mine the genome using cutting edge proteogenomics tools. A number of novel and promising cancer targets have emerged from the genome project for diagnostics, therapeutics, and prognostic markers, which are being used to monitor response to cancer treatment. The heterogeneous nature of cancer has hindered progress in understanding the underlying mechanisms that lead to abnormal cellular growth. Since, the start of The Cancer Genome Atlas (TCGA, and the International Genome consortium projects, there has been tremendous progress in genome sequencing and immense numbers of cancer genomes have been completed, and this approach has transformed our understanding of the diagnosis and treatment of different types of cancers. By employing Genomics and proteomics technologies, an immense amount of genomic data is being generated on clinical tumors, which has transformed the cancer landscape and has the potential to transform cancer diagnosis and prognosis. A complete molecular view of the cancer landscape is necessary for understanding the underlying mechanisms of cancer initiation to improve diagnosis and prognosis, which ultimately will lead to personalized treatment. Interestingly, cancer proteome analysis has also allowed us to identify biomarkers to monitor drug and radiation resistance in patients undergoing cancer treatment. Further, TCGA-funded studies have allowed for the genomic and transcriptomic characterization of targeted cancers, this analysis aiding the development of targeted therapies for highly lethal malignancy. High-throughput technologies, such as complete proteome, epigenome, protein–protein interaction
Identifying anti-growth factors for human cancer cell lines through genome-scale metabolic modeling

DEFF Research Database (Denmark)

Ghaffari, Pouyan; Mardinoglu, Adil; Asplund, Anna

2015-01-01

Human cancer cell lines are used as important model systems to study molecular mechanisms associated with tumor growth, hereunder how genomic and biological heterogeneity found in primary tumors affect cellular phenotypes. We reconstructed Genome scale metabolic models (GEMs) for eleven cell lines...... based on RNA-Seq data and validated the functionality of these models with data from metabolite profiling. We used cell line-specific GEMs to analyze the differences in the metabolism of cancer cell lines, and to explore the heterogeneous expression of the metabolic subsystems. Furthermore, we predicted...... for inhibition of cell growth may provide leads for the development of efficient cancer treatment strategies....
A meta-analysis of genome-wide association studies to identify prostate cancer susceptibility loci associated with aggressive and non-aggressive disease

DEFF Research Database (Denmark)

Amin Al Olama, Ali; Kote-Jarai, Zsofia; Schumacher, Fredrick R

2013-01-01

Genome-wide association studies (GWAS) have identified multiple common genetic variants associated with an increased risk of prostate cancer (PrCa), but these explain less than one-third of the heritability. To identify further susceptibility alleles, we conducted a meta-analysis of four GWAS inc...
Whole-genome sequencing and comprehensive molecular profiling identify new driver mutations in gastric cancer

NARCIS (Netherlands)

Wang, Kai; Yuen, Siu Tsan; Xu, Jiangchun; Lee, Siu Po; Yan, Helen H N; Shi, Stephanie T; Siu, Hoi Cheong; Deng, Shibing; Chu, Kent Man; Law, Simon; Chan, Kok Hoe; Chan, Annie S Y; Tsui, Wai Yin; Ho, Siu Lun; Chan, Anthony K W; Man, Jonathan L K; Foglizzo, Valentina; Ng, Man Kin; Chan, April S; Ching, Yick Pang; Cheng, Grace H W; Xie, Tao; Fernandez, Julio; Li, Vivian S W; Clevers, Hans; Rejto, Paul A; Mao, Mao; Leung, Suet Yi

Gastric cancer is a heterogeneous disease with diverse molecular and histological subtypes. We performed whole-genome sequencing in 100 tumor-normal pairs, along with DNA copy number, gene expression and methylation profiling, for integrative genomic analysis. We found subtype-specific genetic and

Genome-wide association studies identify four ER negative–specific breast cancer risk loci

Science.gov (United States)

Garcia-Closas, Montserrat; Couch, Fergus J; Lindstrom, Sara; Michailidou, Kyriaki; Schmidt, Marjanka K; Brook, Mark N; orr, Nick; Rhie, Suhn Kyong; Riboli, Elio; Feigelson, Heather s; Le Marchand, Loic; Buring, Julie E; Eccles, Diana; Miron, Penelope; Fasching, Peter A; Brauch, Hiltrud; Chang-Claude, Jenny; Carpenter, Jane; Godwin, Andrew K; Nevanlinna, Heli; Giles, Graham G; Cox, Angela; Hopper, John L; Bolla, Manjeet K; Wang, Qin; Dennis, Joe; Dicks, Ed; Howat, Will J; Schoof, Nils; Bojesen, Stig E; Lambrechts, Diether; Broeks, Annegien; Andrulis, Irene L; Guénel, Pascal; Burwinkel, Barbara; Sawyer, Elinor J; Hollestelle, Antoinette; Fletcher, Olivia; Winqvist, Robert; Brenner, Hermann; Mannermaa, Arto; Hamann, Ute; Meindl, Alfons; Lindblom, Annika; Zheng, Wei; Devillee, Peter; Goldberg, Mark S; Lubinski, Jan; Kristensen, Vessela; Swerdlow, Anthony; Anton-Culver, Hoda; Dörk, Thilo; Muir, Kenneth; Matsuo, Keitaro; Wu, Anna H; Radice, Paolo; Teo, Soo Hwang; Shu, Xiao-Ou; Blot, William; Kang, Daehee; Hartman, Mikael; Sangrajrang, Suleeporn; Shen, Chen-Yang; Southey, Melissa C; Park, Daniel J; Hammet, Fleur; Stone, Jennifer; Veer, Laura J Van’t; Rutgers, Emiel J; Lophatananon, Artitaya; Stewart-Brown, Sarah; Siriwanarangsan, Pornthep; Peto, Julian; Schrauder, Michael G; Ekici, Arif B; Beckmann, Matthias W; Silva, Isabel dos Santos; Johnson, Nichola; Warren, Helen; Tomlinson, Ian; Kerin, Michael J; Miller, Nicola; Marme, Federick; Schneeweiss, Andreas; Sohn, Christof; Truong, Therese; Laurent-Puig, Pierre; Kerbrat, Pierre; Nordestgaard, Børge G; Nielsen, Sune F; Flyger, Henrik; Milne, Roger L; Perez, Jose Ignacio Arias; Menéndez, Primitiva; Müller, Heiko; Arndt, Volker; Stegmaier, Christa; Lichtner, Peter; Lochmann, Magdalena; Justenhoven, Christina; Ko, Yon-Dschun; Muranen, Taru A; Aittomäki, Kristiina; Blomqvist, Carl; Greco, Dario; Heikkinen, Tuomas; Ito, Hidemi; Iwata, Hiroji; Yatabe, Yasushi; Antonenkova, Natalia N; Margolin, Sara; Kataja, Vesa; Kosma, Veli-Matti; Hartikainen, Jaana M; Balleine, Rosemary; Tseng, Chiu-Chen; Van Den Berg, David; Stram, Daniel O; Neven, Patrick; Dieudonné, Anne-Sophie; Leunen, Karin; Rudolph, Anja; Nickels, Stefan; Flesch-Janys, Dieter; Peterlongo, Paolo; Peissel, Bernard; Bernard, Loris; Olson, Janet E; Wang, Xianshu; Stevens, Kristen; Severi, Gianluca; Baglietto, Laura; Mclean, Catriona; Coetzee, Gerhard A; Feng, Ye; Henderson, Brian E; Schumacher, Fredrick; Bogdanova, Natalia V; Labrèche, France; Dumont, Martine; Yip, Cheng Har; Taib, Nur Aishah Mohd; Cheng, Ching-Yu; Shrubsole, Martha; Long, Jirong; Pylkäs, Katri; Jukkola-Vuorinen, Arja; Kauppila, Saila; knight, Julia A; Glendon, Gord; Mulligan, Anna Marie; Tollenaar, Robertus A E M; Seynaeve, Caroline M; Kriege, Mieke; Hooning, Maartje J; Van den Ouweland, Ans M W; Van Deurzen, Carolien H M; Lu, Wei; Gao, Yu-Tang; Cai, Hui; Balasubramanian, Sabapathy P; Cross, Simon S; Reed, Malcolm W R; Signorello, Lisa; Cai, Qiuyin; Shah, Mitul; Miao, Hui; Chan, Ching Wan; Chia, Kee Seng; Jakubowska, Anna; Jaworska, Katarzyna; Durda, Katarzyna; Hsiung, Chia-Ni; Wu, Pei-Ei; Yu, Jyh-Cherng; Ashworth, Alan; Jones, Michael; Tessier, Daniel C; González-Neira, Anna; Pita, Guillermo; Alonso, M Rosario; Vincent, Daniel; Bacot, Francois; Ambrosone, Christine B; Bandera, Elisa V; John, Esther M; Chen, Gary K; Hu, Jennifer J; Rodriguez-gil, Jorge L; Bernstein, Leslie; Press, Michael F; Ziegler, Regina G; Millikan, Robert M; Deming-Halverson, Sandra L; Nyante, Sarah; Ingles, Sue A; Waisfisz, Quinten; Tsimiklis, Helen; Makalic, Enes; Schmidt, Daniel; Bui, Minh; Gibson, Lorna; Müller-Myhsok, Bertram; Schmutzler, Rita K; Hein, Rebecca; Dahmen, Norbert; Beckmann, Lars; Aaltonen, Kirsimari; Czene, Kamila; Irwanto, Astrid; Liu, Jianjun; Turnbull, Clare; Rahman, Nazneen; Meijers-Heijboer, Hanne; Uitterlinden, Andre G; Rivadeneira, Fernando; Olswold, Curtis; Slager, Susan; Pilarski, Robert; Ademuyiwa, Foluso; Konstantopoulou, Irene; Martin, Nicholas G; Montgomery, Grant W; Slamon, Dennis J; Rauh, Claudia; Lux, Michael P; Jud, Sebastian M; Bruning, Thomas; Weaver, Joellen; Sharma, Priyanka; Pathak, Harsh; Tapper, Will; Gerty, Sue; Durcan, Lorraine; Trichopoulos, Dimitrios; Tumino, Rosario; Peeters, Petra H; Kaaks, Rudolf; Campa, Daniele; Canzian, Federico; Weiderpass, Elisabete; Johansson, Mattias; Khaw, Kay-Tee; Travis, Ruth; Clavel-Chapelon, Françoise; Kolonel, Laurence N; Chen, Constance; Beck, Andy; Hankinson, Susan E; Berg, Christine D; Hoover, Robert N; Lissowska, Jolanta; Figueroa, Jonine D; Chasman, Daniel I; Gaudet, Mia M; Diver, W Ryan; Willett, Walter C; Hunter, David J; Simard, Jacques; Benitez, Javier; Dunning, Alison M; Sherman, Mark E; Chenevix-Trench, Georgia; Chanock, Stephen J; Hall, Per; Pharoah, Paul D P; Vachon, Celine; Easton, Douglas F; Haiman, Christopher A; Kraft, Peter

2013-01-01

Estrogen receptor (ER)-negative tumors represent 20–30% of all breast cancers, with a higher proportion occurring in younger women and women of African ancestry1. The etiology2 and clinical behavior3 of ER-negative tumors are different from those of tumors expressing ER (ER positive), including differences in genetic predisposition4. To identify susceptibility loci specific to ER-negative disease, we combined in a meta-analysis 3 genome-wide association studies of 4,193 ER-negative breast cancer cases and 35,194 controls with a series of 40 follow-up studies (6,514 cases and 41,455 controls), genotyped using a custom Illumina array, iCOGS, developed by the Collaborative Oncological Gene-environment Study (COGS). SNPs at four loci, 1q32.1 (MDM4, P = 2.1 × 10−12 and LGR6, P = 1.4 × 10−8), 2p24.1 (P = 4.6 × 10−8) and 16q12.2 (FTO, P = 4.0 × 10−8), were associated with ER-negative but not ER-positive breast cancer (P > 0.05). These findings provide further evidence for distinct etiological pathways associated with invasive ER-positive and ER-negative breast cancers. PMID:23535733
Genome-wide association study in discordant sibships identifies multiple inherited susceptibility alleles linked to lung cancer.

Science.gov (United States)

Galvan, Antonella; Falvella, Felicia S; Frullanti, Elisa; Spinola, Monica; Incarbone, Matteo; Nosotti, Mario; Santambrogio, Luigi; Conti, Barbara; Pastorino, Ugo; Gonzalez-Neira, Anna; Dragani, Tommaso A

2010-03-01

We analyzed a series of young (median age = 52 years) non-smoker lung cancer patients and their unaffected siblings as controls, using a genome-wide 620 901 single-nucleotide polymorphism (SNP) array analysis and a case-control DNA pooling approach. We identified 82 putatively associated SNPs that were retested by individual genotyping followed by use of the sib transmission disequilibrium test, pointing to 36 SNPs associated with lung cancer risk in the discordant sibs series. Analysis of these 36 SNPs in a polygenic model characterized by additive and interchangeable effects of rare alleles revealed a highly statistically significant dosage-dependent association between risk allele carrier status and proportion of cancer cases. Replication of the same 36 SNPs in a population-based series confirmed the association with lung cancer for three SNPs, suggesting that phenocopies and genetic heterogeneity can play a major role in the complex genetics of lung cancer risk in the general population.
Integration of multiple networks and pathways identifies cancer driver genes in pan-cancer analysis.

Science.gov (United States)

Cava, Claudia; Bertoli, Gloria; Colaprico, Antonio; Olsen, Catharina; Bontempi, Gianluca; Castiglioni, Isabella

2018-01-06

Modern high-throughput genomic technologies represent a comprehensive hallmark of molecular changes in pan-cancer studies. Although different cancer gene signatures have been revealed, the mechanism of tumourigenesis has yet to be completely understood. Pathways and networks are important tools to explain the role of genes in functional genomic studies. However, few methods consider the functional non-equal roles of genes in pathways and the complex gene-gene interactions in a network. We present a novel method in pan-cancer analysis that identifies de-regulated genes with a functional role by integrating pathway and network data. A pan-cancer analysis of 7158 tumour/normal samples from 16 cancer types identified 895 genes with a central role in pathways and de-regulated in cancer. Comparing our approach with 15 current tools that identify cancer driver genes, we found that 35.6% of the 895 genes identified by our method have been found as cancer driver genes with at least 2/15 tools. Finally, we applied a machine learning algorithm on 16 independent GEO cancer datasets to validate the diagnostic role of cancer driver genes for each cancer. We obtained a list of the top-ten cancer driver genes for each cancer considered in this study. Our analysis 1) confirmed that there are several known cancer driver genes in common among different types of cancer, 2) highlighted that cancer driver genes are able to regulate crucial pathways.
A meta-analysis of genome-wide association studies of breast cancer identifies two novel susceptibility loci at 6q14 and 20q11

NARCIS (Netherlands)

Siddiq, Afshan; Couch, Fergus J.; Chen, Gary K.; Lindström, Sara; Eccles, Diana; Millikan, Robert C.; Michailidou, Kyriaki; Stram, Daniel O.; Beckmann, Lars; Rhie, Suhn Kyong; Ambrosone, Christine B.; Aittomäki, Kristiina; Amiano, Pilar; Apicella, Carmel; Baglietto, Laura; Bandera, Elisa V.; Beckmann, Matthias W.; Berg, Christine D.; Bernstein, Leslie; Blomqvist, Carl; Brauch, Hiltrud; Brinton, Louise; Bui, Quang M.; Buring, Julie E.; Buys, Saundra S.; Campa, Daniele; Carpenter, Jane E.; Chasman, Daniel I.; Chang-Claude, Jenny; Chen, Constance; Clavel-Chapelon, Françoise; Cox, Angela; Cross, Simon S.; Czene, Kamila; Deming, Sandra L.; Diasio, Robert B.; Diver, W. Ryan; Dunning, Alison M.; Durcan, Lorraine; Ekici, Arif B.; Fasching, Peter A.; Feigelson, Heather Spencer; Fejerman, Laura; Figueroa, Jonine D.; Fletcher, Olivia; Flesch-Janys, Dieter; Gaudet, Mia M.; Gerty, Susan M.; Rodriguez-Gil, Jorge L.; Giles, Graham G.; van Gils, Carla H.; Godwin, Andrew K.; Graham, Nikki; Greco, Dario; Hall, Per; Hankinson, Susan E.; Hartmann, Arndt; Hein, Rebecca; Heinz, Judith; Hoover, Robert N.; Hopper, John L.; Hu, Jennifer J.; Huntsman, Scott; Ingles, Sue A.; Irwanto, Astrid; Isaacs, Claudine; Jacobs, Kevin B.; John, Esther M.; Justenhoven, Christina; Kaaks, Rudolf; Kolonel, Laurence N.; Coetzee, Gerhard A.; Lathrop, Mark; Le Marchand, Loic; Lee, Adam M.; Lee, I.-Min; Lesnick, Timothy; Lichtner, Peter; Liu, Jianjun; Lund, Eiliv; Makalic, Enes; Martin, Nicholas G.; McLean, Catriona A.; Meijers-Heijboer, Hanne; Meindl, Alfons; Miron, Penelope; Monroe, Kristine R.; Montgomery, Grant W.; Müller-Myhsok, Bertram; Nickels, Stefan; Nyante, Sarah J.; Olswold, Curtis; Overvad, Kim; Palli, Domenico; Park, Daniel J.; Palmer, Julie R.; Pathak, Harsh; Peto, Julian; Pharoah, Paul; Rahman, Nazneen; Rivadeneira, Fernando; Schmidt, Daniel F.; Schmutzler, Rita K.; Slager, Susan; Southey, Melissa C.; Stevens, Kristen N.; Sinn, Hans-Peter; Press, Michael F.; Ross, Eric; Riboli, Elio; Ridker, Paul M.; Schumacher, Fredrick R.; Severi, Gianluca; dos Santos Silva, Isabel; Stone, Jennifer; Sund, Malin; Tapper, William J.; Thun, Michael J.; Travis, Ruth C.; Turnbull, Clare; Uitterlinden, Andre G.; Waisfisz, Quinten; Wang, Xianshu; Wang, Zhaoming; Weaver, Joellen; Schulz-Wendtland, Rüdiger; Wilkens, Lynne R.; van den Berg, David; Zheng, Wei; Ziegler, Regina G.; Ziv, Elad; Nevanlinna, Heli; Easton, Douglas F.; Hunter, David J.; Henderson, Brian E.; Chanock, Stephen J.; Garcia-Closas, Montserrat; Kraft, Peter; Haiman, Christopher A.; Vachon, Celine M.

2012-01-01

Genome-wide association studies (GWAS) of breast cancer defined by hormone receptor status have revealed loci contributing to susceptibility of estrogen receptor (ER)-negative subtypes. To identify additional genetic variants for ER-negative breast cancer, we conducted the largest meta-analysis of
Integrated analysis of whole genome and transcriptome sequencing reveals diverse transcriptomic aberrations driven by somatic genomic changes in liver cancers.

Directory of Open Access Journals (Sweden)

Yuichi Shiraishi

Full Text Available Recent studies applying high-throughput sequencing technologies have identified several recurrently mutated genes and pathways in multiple cancer genomes. However, transcriptional consequences from these genomic alterations in cancer genome remain unclear. In this study, we performed integrated and comparative analyses of whole genomes and transcriptomes of 22 hepatitis B virus (HBV-related hepatocellular carcinomas (HCCs and their matched controls. Comparison of whole genome sequence (WGS and RNA-Seq revealed much evidence that various types of genomic mutations triggered diverse transcriptional changes. Not only splice-site mutations, but also silent mutations in coding regions, deep intronic mutations and structural changes caused splicing aberrations. HBV integrations generated diverse patterns of virus-human fusion transcripts depending on affected gene, such as TERT, CDK15, FN1 and MLL4. Structural variations could drive over-expression of genes such as WNT ligands, with/without creating gene fusions. Furthermore, by taking account of genomic mutations causing transcriptional aberrations, we could improve the sensitivity of deleterious mutation detection in known cancer driver genes (TP53, AXIN1, ARID2, RPS6KA3, and identified recurrent disruptions in putative cancer driver genes such as HNF4A, CPS1, TSC1 and THRAP3 in HCCs. These findings indicate genomic alterations in cancer genome have diverse transcriptomic effects, and integrated analysis of WGS and RNA-Seq can facilitate the interpretation of a large number of genomic alterations detected in cancer genome.
Whole-genome sequencing identifies genomic heterogeneity at a nucleotide and chromosomal level in bladder cancer

Science.gov (United States)

Morrison, Carl D.; Liu, Pengyuan; Woloszynska-Read, Anna; Zhang, Jianmin; Luo, Wei; Qin, Maochun; Bshara, Wiam; Conroy, Jeffrey M.; Sabatini, Linda; Vedell, Peter; Xiong, Donghai; Liu, Song; Wang, Jianmin; Shen, He; Li, Yinwei; Omilian, Angela R.; Hill, Annette; Head, Karen; Guru, Khurshid; Kunnev, Dimiter; Leach, Robert; Eng, Kevin H.; Darlak, Christopher; Hoeflich, Christopher; Veeranki, Srividya; Glenn, Sean; You, Ming; Pruitt, Steven C.; Johnson, Candace S.; Trump, Donald L.

2014-01-01

Using complete genome analysis, we sequenced five bladder tumors accrued from patients with muscle-invasive transitional cell carcinoma of the urinary bladder (TCC-UB) and identified a spectrum of genomic aberrations. In three tumors, complex genotype changes were noted. All three had tumor protein p53 mutations and a relatively large number of single-nucleotide variants (SNVs; average of 11.2 per megabase), structural variants (SVs; average of 46), or both. This group was best characterized by chromothripsis and the presence of subclonal populations of neoplastic cells or intratumoral mutational heterogeneity. Here, we provide evidence that the process of chromothripsis in TCC-UB is mediated by nonhomologous end-joining using kilobase, rather than megabase, fragments of DNA, which we refer to as “stitchers,” to repair this process. We postulate that a potential unifying theme among tumors with the more complex genotype group is a defective replication–licensing complex. A second group (two bladder tumors) had no chromothripsis, and a simpler genotype, WT tumor protein p53, had relatively few SNVs (average of 5.9 per megabase) and only a single SV. There was no evidence of a subclonal population of neoplastic cells. In this group, we used a preclinical model of bladder carcinoma cell lines to study a unique SV (translocation and amplification) of the gene glutamate receptor ionotropic N-methyl D-aspertate as a potential new therapeutic target in bladder cancer. PMID:24469795
University of Texas MD Anderson Cancer Center: High-Throughput Screening Identifying Driving Mutations in Endometrial Cancer | Office of Cancer Genomics

Science.gov (United States)

Recent advances in next-generation sequencing technology have enabled the unprecedented characterization of a full spectrum of somatic alterations in cancer genomes. Given the large numbers of somatic mutations typically detected by this approach, a key challenge in the downstream analysis is to distinguish “drivers” that functionally contribute to tumorigenesis from “passengers” that occur as the consequence of genomic instability.
Genome-wide association studies identify four ER negative-specific breast cancer risk loci

DEFF Research Database (Denmark)

Garcia-Closas, Montserrat; Couch, Fergus J; Lindstrom, Sara

2013-01-01

differences in genetic predisposition. To identify susceptibility loci specific to ER-negative disease, we combined in a meta-analysis 3 genome-wide association studies of 4,193 ER-negative breast cancer cases and 35,194 controls with a series of 40 follow-up studies (6,514 cases and 41,455 controls......), genotyped using a custom Illumina array, iCOGS, developed by the Collaborative Oncological Gene-environment Study (COGS). SNPs at four loci, 1q32.1 (MDM4, P = 2.1 × 10(-12) and LGR6, P = 1.4 × 10(-8)), 2p24.1 (P = 4.6 × 10(-8)) and 16q12.2 (FTO, P = 4.0 × 10(-8)), were associated with ER-negative but not ER...
Genomic analysis and selected molecular pathways in rare cancers

International Nuclear Information System (INIS)

Liu, Stephen V; Lenkiewicz, Elizabeth; Evers, Lisa; Holley, Tara; Kiefer, Jeffrey; Demeure, Michael J; Ramanathan, Ramesh K; Von Hoff, Daniel D; Barrett, Michael T; Ruiz, Christian; Glatz, Katharina; Bubendorf, Lukas; Eng, Cathy

2012-01-01

It is widely accepted that many cancers arise as a result of an acquired genomic instability and the subsequent evolution of tumor cells with variable patterns of selected and background aberrations. The presence and behaviors of distinct neoplastic cell populations within a patient's tumor may underlie multiple clinical phenotypes in cancers. A goal of many current cancer genome studies is the identification of recurring selected driver events that can be advanced for the development of personalized therapies. Unfortunately, in the majority of rare tumors, this type of analysis can be particularly challenging. Large series of specimens for analysis are simply not available, allowing recurring patterns to remain hidden. In this paper, we highlight the use of DNA content-based flow sorting to identify and isolate DNA-diploid and DNA-aneuploid populations from tumor biopsies as a strategy to comprehensively study the genomic composition and behaviors of individual cancers in a series of rare solid tumors: intrahepatic cholangiocarcinoma, anal carcinoma, adrenal leiomyosarcoma, and pancreatic neuroendocrine tumors. We propose that the identification of highly selected genomic events in distinct tumor populations within each tumor can identify candidate driver events that can facilitate the development of novel, personalized treatment strategies for patients with cancer. (paper)
Genome-wide Analysis Identifies Novel Loci Associated with Ovarian Cancer Outcomes

DEFF Research Database (Denmark)

Johnatty, Sharon E; Tyrer, Jonathan P; Kar, Siddhartha

2015-01-01

PURPOSE: Chemotherapy resistance remains a major challenge in the treatment of ovarian cancer. We hypothesize that germline polymorphisms might be associated with clinical outcome. EXPERIMENTAL DESIGN: We analyzed approximately 2.8 million genotyped and imputed SNPs from the iCOGS experiment...... for progression-free survival (PFS) and overall survival (OS) in 2,901 European epithelial ovarian cancer (EOC) patients who underwent first-line treatment of cytoreductive surgery and chemotherapy regardless of regimen, and in a subset of 1,098 patients treated with ≥ 4 cycles of paclitaxel and carboplatin...... at standard doses. We evaluated the top SNPs in 4,434 EOC patients, including patients from The Cancer Genome Atlas. In addition, we conducted pathway analysis of all intragenic SNPs and tested their association with PFS and OS using gene set enrichment analysis. RESULTS: Five SNPs were significantly...
Genome Wide Association Study to Identify SNPs and CNPs Associated with Development of Radiation Injury in Prostate Cancer Patients Treated with Radiotherapy

Science.gov (United States)

2012-10-01

association tests, we obtained low genomic inflation factors of 1.02 for the ED patients and 1.00 for the urinary morbidity patients, suggesting...study (GWAS) to identify genetic factors associated with urinary morbidity following radiotherapy for prostate cancer. Methods: Prostate cancer...increased urinary frequency, incomplete bladder emptying, weak urinary stream and incontinence , as well as more serious events such as bladder necrosis or
Cancer Genomics: Diversity and Disparity Across Ethnicity and Geography.

Science.gov (United States)

Tan, Daniel S W; Mok, Tony S K; Rebbeck, Timothy R

2016-01-01

Ethnic and geographic differences in cancer incidence, prognosis, and treatment outcomes can be attributed to diversity in the inherited (germline) and somatic genome. Although international large-scale sequencing efforts are beginning to unravel the genomic underpinnings of cancer traits, much remains to be known about the underlying mechanisms and determinants of genomic diversity. Carcinogenesis is a dynamic, complex phenomenon representing the interplay between genetic and environmental factors that results in divergent phenotypes across ethnicities and geography. For example, compared with whites, there is a higher incidence of prostate cancer among Africans and African Americans, and the disease is generally more aggressive and fatal. Genome-wide association studies have identified germline susceptibility loci that may account for differences between the African and non-African patients, but the lack of availability of appropriate cohorts for replication studies and the incomplete understanding of genomic architecture across populations pose major limitations. We further discuss the transformative potential of routine diagnostic evaluation for actionable somatic alterations, using lung cancer as an example, highlighting implications of population disparities, current hurdles in implementation, and the far-reaching potential of clinical genomics in enhancing cancer prevention, diagnosis, and treatment. As we enter the era of precision cancer medicine, a concerted multinational effort is key to addressing population and genomic diversity as well as overcoming barriers and geographical disparities in research and health care delivery. © 2015 by American Society of Clinical Oncology.
Defining a Cancer Dependency Map | Office of Cancer Genomics

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Most human epithelial tumors harbor numerous alterations, making it difficult to predict which genes are required for tumor survival. To systematically identify cancer dependencies, we analyzed 501 genome-scale loss-of-function screens performed in diverse human cancer cell lines. We developed DEMETER, an analytical framework that segregates on- from off-target effects of RNAi. 769 genes were differentially required in subsets of these cell lines at a threshold of six SDs from the mean.
Cancer associated epigenetic transitions identified by genome-wide histone methylation binding profiles in human colorectal cancer samples and paired normal mucosa

International Nuclear Information System (INIS)

Enroth, Stefan; Rada-Iglesisas, Alvaro; Andersson, Robin; Wallerman, Ola; Wanders, Alkwin; Påhlman, Lars; Komorowski, Jan; Wadelius, Claes

2011-01-01

Despite their well-established functional roles, histone modifications have received less attention than DNA methylation in the cancer field. In order to evaluate their importance in colorectal cancer (CRC), we generated the first genome-wide histone modification profiles in paired normal colon mucosa and tumor samples. Chromatin immunoprecipitation and microarray hybridization (ChIP-chip) was used to identify promoters enriched for histone H3 trimethylated on lysine 4 (H3K4me3) and lysine 27 (H3K27me3) in paired normal colon mucosa and tumor samples from two CRC patients and for the CRC cell line HT29. By comparing histone modification patterns in normal mucosa and tumors, we found that alterations predicted to have major functional consequences were quite rare. Furthermore, when normal or tumor tissue samples were compared to HT29, high similarities were observed for H3K4me3. However, the differences found for H3K27me3, which is important in determining cellular identity, indicates that cell lines do not represent optimal tissue models. Finally, using public expression data, we uncovered previously unknown changes in CRC expression patterns. Genes positive for H3K4me3 in normal and/or tumor samples, which are typically already active in normal mucosa, became hyperactivated in tumors, while genes with H3K27me3 in normal and/or tumor samples and which are expressed at low levels in normal mucosa, became hypersilenced in tumors. Genome wide histone modification profiles can be used to find epigenetic aberrations in genes associated with cancer. This strategy gives further insights into the epigenetic contribution to the oncogenic process and may identify new biomarkers
Fine mapping of breast cancer genome-wide association studies loci in women of African ancestry identifies novel susceptibility markers.

Science.gov (United States)

Zheng, Yonglan; Ogundiran, Temidayo O; Falusi, Adeyinka G; Nathanson, Katherine L; John, Esther M; Hennis, Anselm J M; Ambs, Stefan; Domchek, Susan M; Rebbeck, Timothy R; Simon, Michael S; Nemesure, Barbara; Wu, Suh-Yuh; Leske, Maria Cristina; Odetunde, Abayomi; Niu, Qun; Zhang, Jing; Afolabi, Chibuzor; Gamazon, Eric R; Cox, Nancy J; Olopade, Christopher O; Olopade, Olufunmilayo I; Huo, Dezheng

2013-07-01

Numerous single nucleotide polymorphisms (SNPs) associated with breast cancer susceptibility have been identified by genome-wide association studies (GWAS). However, these SNPs were primarily discovered and validated in women of European and Asian ancestry. Because linkage disequilibrium is ancestry-dependent and heterogeneous among racial/ethnic populations, we evaluated common genetic variants at 22 GWAS-identified breast cancer susceptibility loci in a pooled sample of 1502 breast cancer cases and 1378 controls of African ancestry. None of the 22 GWAS index SNPs could be validated, challenging the direct generalizability of breast cancer risk variants identified in Caucasians or Asians to other populations. Novel breast cancer risk variants for women of African ancestry were identified in regions including 5p12 (odds ratio [OR] = 1.40, 95% confidence interval [CI] = 1.11-1.76; P = 0.004), 5q11.2 (OR = 1.22, 95% CI = 1.09-1.36; P = 0.00053) and 10p15.1 (OR = 1.22, 95% CI = 1.08-1.38; P = 0.0015). We also found positive association signals in three regions (6q25.1, 10q26.13 and 16q12.1-q12.2) previously confirmed by fine mapping in women of African ancestry. In addition, polygenic model indicated that eight best markers in this study, compared with 22 GWAS-identified SNPs, could better predict breast cancer risk in women of African ancestry (per-allele OR = 1.21, 95% CI = 1.16-1.27; P = 9.7 × 10(-16)). Our results demonstrate that fine mapping is a powerful approach to better characterize the breast cancer risk alleles in diverse populations. Future studies and new GWAS in women of African ancestry hold promise to discover additional variants for breast cancer susceptibility with clinical implications throughout the African diaspora.
Integrated Bioinformatics, Environmental Epidemiologic and Genomic Approaches to Identify Environmental and Molecular Links between Endometriosis and Breast Cancer

Directory of Open Access Journals (Sweden)

Deodutta Roy

2015-10-01

Full Text Available We present a combined environmental epidemiologic, genomic, and bioinformatics approach to identify: exposure of environmental chemicals with estrogenic activity; epidemiologic association between endocrine disrupting chemical (EDC and health effects, such as, breast cancer or endometriosis; and gene-EDC interactions and disease associations. Human exposure measurement and modeling confirmed estrogenic activity of three selected class of environmental chemicals, polychlorinated biphenyls (PCBs, bisphenols (BPs, and phthalates. Meta-analysis showed that PCBs exposure, not Bisphenol A (BPA and phthalates, increased the summary odds ratio for breast cancer and endometriosis. Bioinformatics analysis of gene-EDC interactions and disease associations identified several hundred genes that were altered by exposure to PCBs, phthalate or BPA. EDCs-modified genes in breast neoplasms and endometriosis are part of steroid hormone signaling and inflammation pathways. All three EDCs–PCB 153, phthalates, and BPA influenced five common genes—CYP19A1, EGFR, ESR2, FOS, and IGF1—in breast cancer as well as in endometriosis. These genes are environmentally and estrogen responsive, altered in human breast and uterine tumors and endometriosis lesions, and part of Mitogen Activated Protein Kinase (MAPK signaling pathways in cancer. Our findings suggest that breast cancer and endometriosis share some common environmental and molecular risk factors.
Inferring causal genomic alterations in breast cancer using gene expression data

Science.gov (United States)

2011-01-01

Background One of the primary objectives in cancer research is to identify causal genomic alterations, such as somatic copy number variation (CNV) and somatic mutations, during tumor development. Many valuable studies lack genomic data to detect CNV; therefore, methods that are able to infer CNVs from gene expression data would help maximize the value of these studies. Results We developed a framework for identifying recurrent regions of CNV and distinguishing the cancer driver genes from the passenger genes in the regions. By inferring CNV regions across many datasets we were able to identify 109 recurrent amplified/deleted CNV regions. Many of these regions are enriched for genes involved in many important processes associated with tumorigenesis and cancer progression. Genes in these recurrent CNV regions were then examined in the context of gene regulatory networks to prioritize putative cancer driver genes. The cancer driver genes uncovered by the framework include not only well-known oncogenes but also a number of novel cancer susceptibility genes validated via siRNA experiments. Conclusions To our knowledge, this is the first effort to systematically identify and validate drivers for expression based CNV regions in breast cancer. The framework where the wavelet analysis of copy number alteration based on expression coupled with the gene regulatory network analysis, provides a blueprint for leveraging genomic data to identify key regulatory components and gene targets. This integrative approach can be applied to many other large-scale gene expression studies and other novel types of cancer data such as next-generation sequencing based expression (RNA-Seq) as well as CNV data. PMID:21806811
Genomes of early onset prostate cancer

DEFF Research Database (Denmark)

Weischenfeldt, Joachim; Korbel, Jan O.

2017-01-01

Purpose of review Prostate cancer is a disease of the elderly but a clinically relevant subset occurs early in life. In the current review, we discuss recent findings and the current understanding of the molecular underpinnings associated with early-onset prostate cancer (PCa) and the evidence...... supporting age-specific differences in the cancer genomes. Recent findings Recent surveys of PCa patient cohorts have provided novel age-dependent links between germline and somatic aberrations which points to differences in the molecular cause and treatment options. Summary Identifying the earliest...... receptor pathway....
Integrative genome analyses identify key somatic driver mutations of small-cell lung cancer

NARCIS (Netherlands)

Peifer, Martin; Fernandez-Cuesta, Lynnette; Sos, Martin L.; George, Julie; Seidel, Danila; Kasper, Lawryn H.; Plenker, Dennis; Leenders, Frauke; Sun, Ruping; Zander, Thomas; Menon, Roopika; Koker, Mirjam; Dahmen, Ilona; Mueller, Christian; Di Cerbo, Vincenzo; Schildhaus, Hans-Ulrich; Altmueller, Janine; Baessmann, Ingelore; Becker, Christian; de Wilde, Bram; Vandesompele, Jo; Boehm, Diana; Ansen, Sascha; Gabler, Franziska; Wilkening, Ines; Heynck, Stefanie; Heuckmann, Johannes M.; Lu, Xin; Carter, Scott L.; Cibulskis, Kristian; Banerji, Shantanu; Getz, Gad; Park, Kwon-Sik; Rauh, Daniel; Gruetter, Christian; Fischer, Matthias; Pasqualucci, Laura; Wright, Gavin; Wainer, Zoe; Russell, Prudence; Petersen, Iver; Chen, Yuan; Stoelben, Erich; Ludwig, Corinna; Schnabel, Philipp; Hoffmann, Hans; Muley, Thomas; Brockmann, Michael; Engel-Riedel, Walburga; Muscarella, Lucia A.; Fazio, Vito M.; Groen, Harry; Timens, Wim; Sietsma, Hannie; Thunnissen, Erik; Smit, Egbert; Heideman, Danielle A. M.; Snijders, Peter J. F.; Cappuzzo, Federico; Ligorio, Claudia; Damiani, Stefania; Field, John; Solberg, Steinar; Brustugun, Odd Terje; Lund-Iversen, Marius; Saenger, Joerg; Clement, Joachim H.; Soltermann, Alex; Moch, Holger; Weder, Walter; Solomon, Benjamin; Soria, Jean-Charles; Validire, Pierre; Besse, Benjamin; Brambilla, Elisabeth; Brambilla, Christian; Lantuejoul, Sylvie; Lorimier, Philippe; Schneider, Peter M.; Hallek, Michael; Pao, William; Meyerson, Matthew; Sage, Julien; Shendure, Jay; Schneider, Robert; Buettner, Reinhard; Wolf, Juergen; Nuernberg, Peter; Perner, Sven; Heukamp, Lukas C.; Brindle, Paul K.; Haas, Stefan; Thomas, Roman K.

2012-01-01

Small-cell lung cancer (SCLC) is an aggressive lung tumor subtype with poor prognosis(1-3). We sequenced 29 SCLC exomes, 2 genomes and 15 transcriptomes and found an extremely high mutation rate of 7.4 +/- 1 protein-changing mutations per million base pairs. Therefore, we conducted integrated
Association analysis identifies 65 new breast cancer risk loci

Science.gov (United States)

Lemaçon, Audrey; Soucy, Penny; Glubb, Dylan; Rostamianfar, Asha; Bolla, Manjeet K.; Wang, Qin; Tyrer, Jonathan; Dicks, Ed; Lee, Andrew; Wang, Zhaoming; Allen, Jamie; Keeman, Renske; Eilber, Ursula; French, Juliet D.; Chen, Xiao Qing; Fachal, Laura; McCue, Karen; McCart Reed, Amy E.; Ghoussaini, Maya; Carroll, Jason; Jiang, Xia; Finucane, Hilary; Adams, Marcia; Adank, Muriel A.; Ahsan, Habibul; Aittomäki, Kristiina; Anton-Culver, Hoda; Antonenkova, Natalia N.; Arndt, Volker; Aronson, Kristan J.; Arun, Banu; Auer, Paul L.; Bacot, François; Barrdahl, Myrto; Baynes, Caroline; Beckmann, Matthias W.; Behrens, Sabine; Benitez, Javier; Bermisheva, Marina; Bernstein, Leslie; Blomqvist, Carl; Bogdanova, Natalia V.; Bojesen, Stig E.; Bonanni, Bernardo; Børresen-Dale, Anne-Lise; Brand, Judith S.; Brauch, Hiltrud; Brennan, Paul; Brenner, Hermann; Brinton, Louise; Broberg, Per; Brock, Ian W.; Broeks, Annegien; Brooks-Wilson, Angela; Brucker, Sara Y.; Brüning, Thomas; Burwinkel, Barbara; Butterbach, Katja; Cai, Qiuyin; Cai, Hui; Caldés, Trinidad; Canzian, Federico; Carracedo, Angel; Carter, Brian D.; Castelao, Jose E.; Chan, Tsun L.; Cheng, Ting-Yuan David; Chia, Kee Seng; Choi, Ji-Yeob; Christiansen, Hans; Clarke, Christine L.; Collée, Margriet; Conroy, Don M.; Cordina-Duverger, Emilie; Cornelissen, Sten; Cox, David G; Cox, Angela; Cross, Simon S.; Cunningham, Julie M.; Czene, Kamila; Daly, Mary B.; Devilee, Peter; Doheny, Kimberly F.; Dörk, Thilo; dos-Santos-Silva, Isabel; Dumont, Martine; Durcan, Lorraine; Dwek, Miriam; Eccles, Diana M.; Ekici, Arif B.; Eliassen, A. Heather; Ellberg, Carolina; Elvira, Mingajeva; Engel, Christoph; Eriksson, Mikael; Fasching, Peter A.; Figueroa, Jonine; Flesch-Janys, Dieter; Fletcher, Olivia; Flyger, Henrik; Fritschi, Lin; Gaborieau, Valerie; Gabrielson, Marike; Gago-Dominguez, Manuela; Gao, Yu-Tang; Gapstur, Susan M.; García-Sáenz, José A.; Gaudet, Mia M.; Georgoulias, Vassilios; Giles, Graham G.; Glendon, Gord; Goldberg, Mark S.; Goldgar, David E.; González-Neira, Anna; Grenaker Alnæs, Grethe I.; Grip, Mervi; Gronwald, Jacek; Grundy, Anne; Guénel, Pascal; Haeberle, Lothar; Hahnen, Eric; Haiman, Christopher A.; Håkansson, Niclas; Hamann, Ute; Hamel, Nathalie; Hankinson, Susan; Harrington, Patricia; Hart, Steven N.; Hartikainen, Jaana M.; Hartman, Mikael; Hein, Alexander; Heyworth, Jane; Hicks, Belynda; Hillemanns, Peter; Ho, Dona N.; Hollestelle, Antoinette; Hooning, Maartje J.; Hoover, Robert N.; Hopper, John L.; Hou, Ming-Feng; Hsiung, Chia-Ni; Huang, Guanmengqian; Humphreys, Keith; Ishiguro, Junko; Ito, Hidemi; Iwasaki, Motoki; Iwata, Hiroji; Jakubowska, Anna; Janni, Wolfgang; John, Esther M.; Johnson, Nichola; Jones, Kristine; Jones, Michael; Jukkola-Vuorinen, Arja; Kaaks, Rudolf; Kabisch, Maria; Kaczmarek, Katarzyna; Kang, Daehee; Kasuga, Yoshio; Kerin, Michael J.; Khan, Sofia; Khusnutdinova, Elza; Kiiski, Johanna I.; Kim, Sung-Won; Knight, Julia A.; Kosma, Veli-Matti; Kristensen, Vessela N.; Krüger, Ute; Kwong, Ava; Lambrechts, Diether; Marchand, Loic Le; Lee, Eunjung; Lee, Min Hyuk; Lee, Jong Won; Lee, Chuen Neng; Lejbkowicz, Flavio; Li, Jingmei; Lilyquist, Jenna; Lindblom, Annika; Lissowska, Jolanta; Lo, Wing-Yee; Loibl, Sibylle; Long, Jirong; Lophatananon, Artitaya; Lubinski, Jan; Luccarini, Craig; Lux, Michael P.; Ma, Edmond S.K.; MacInnis, Robert J.; Maishman, Tom; Makalic, Enes; Malone, Kathleen E; Kostovska, Ivana Maleva; Mannermaa, Arto; Manoukian, Siranoush; Manson, JoAnn E.; Margolin, Sara; Mariapun, Shivaani; Martinez, Maria Elena; Matsuo, Keitaro; Mavroudis, Dimitrios; McKay, James; McLean, Catriona; Meijers-Heijboer, Hanne; Meindl, Alfons; Menéndez, Primitiva; Menon, Usha; Meyer, Jeffery; Miao, Hui; Miller, Nicola; Mohd Taib, Nur Aishah; Muir, Kenneth; Mulligan, Anna Marie; Mulot, Claire; Neuhausen, Susan L.; Nevanlinna, Heli; Neven, Patrick; Nielsen, Sune F.; Noh, Dong-Young; Nordestgaard, Børge G.; Norman, Aaron; Olopade, Olufunmilayo I.; Olson, Janet E.; Olsson, Håkan; Olswold, Curtis; Orr, Nick; Pankratz, V. Shane; Park, Sue K.; Park-Simon, Tjoung-Won; Lloyd, Rachel; Perez, Jose I.A.; Peterlongo, Paolo; Peto, Julian; Phillips, Kelly-Anne; Pinchev, Mila; Plaseska-Karanfilska, Dijana; Prentice, Ross; Presneau, Nadege; Prokofieva, Darya; Pugh, Elizabeth; Pylkäs, Katri; Rack, Brigitte; Radice, Paolo; Rahman, Nazneen; Rennert, Gadi; Rennert, Hedy S.; Rhenius, Valerie; Romero, Atocha; Romm, Jane; Ruddy, Kathryn J; Rüdiger, Thomas; Rudolph, Anja; Ruebner, Matthias; Rutgers, Emiel J. Th.; Saloustros, Emmanouil; Sandler, Dale P.; Sangrajrang, Suleeporn; Sawyer, Elinor J.; Schmidt, Daniel F.; Schmutzler, Rita K.; Schneeweiss, Andreas; Schoemaker, Minouk J.; Schumacher, Fredrick; Schürmann, Peter; Scott, Rodney J.; Scott, Christopher; Seal, Sheila; Seynaeve, Caroline; Shah, Mitul; Sharma, Priyanka; Shen, Chen-Yang; Sheng, Grace; Sherman, Mark E.; Shrubsole, Martha J.; Shu, Xiao-Ou; Smeets, Ann; Sohn, Christof; Southey, Melissa C.; Spinelli, John J.; Stegmaier, Christa; Stewart-Brown, Sarah; Stone, Jennifer; Stram, Daniel O.; Surowy, Harald; Swerdlow, Anthony; Tamimi, Rulla; Taylor, Jack A.; Tengström, Maria; Teo, Soo H.; Terry, Mary Beth; Tessier, Daniel C.; Thanasitthichai, Somchai; Thöne, Kathrin; Tollenaar, Rob A.E.M.; Tomlinson, Ian; Tong, Ling; Torres, Diana; Truong, Thérèse; Tseng, Chiu-chen; Tsugane, Shoichiro; Ulmer, Hans-Ulrich; Ursin, Giske; Untch, Michael; Vachon, Celine; van Asperen, Christi J.; Van Den Berg, David; van den Ouweland, Ans M.W.; van der Kolk, Lizet; van der Luijt, Rob B.; Vincent, Daniel; Vollenweider, Jason; Waisfisz, Quinten; Wang-Gohrke, Shan; Weinberg, Clarice R.; Wendt, Camilla; Whittemore, Alice S.; Wildiers, Hans; Willett, Walter; Winqvist, Robert; Wolk, Alicja; Wu, Anna H.; Xia, Lucy; Yamaji, Taiki; Yang, Xiaohong R.; Yip, Cheng Har; Yoo, Keun-Young; Yu, Jyh-Cherng; Zheng, Wei; Zheng, Ying; Zhu, Bin; Ziogas, Argyrios; Ziv, Elad; Lakhani, Sunil R.; Antoniou, Antonis C.; Droit, Arnaud; Andrulis, Irene L.; Amos, Christopher I.; Couch, Fergus J.; Pharoah, Paul D.P.; Chang-Claude, Jenny; Hall, Per; Hunter, David J.; Milne, Roger L.; García-Closas, Montserrat; Schmidt, Marjanka K.; Chanock, Stephen J.; Dunning, Alison M.; Edwards, Stacey L.; Bader, Gary D.; Chenevix-Trench, Georgia; Simard, Jacques; Kraft, Peter; Easton, Douglas F.

2017-01-01

Breast cancer risk is influenced by rare coding variants in susceptibility genes such as BRCA1 and many common, mainly non-coding variants. However, much of the genetic contribution to breast cancer risk remains unknown. We report results from a genome-wide association study (GWAS) of breast cancer in 122,977 cases and 105,974 controls of European ancestry and 14,068 cases and 13,104 controls of East Asian ancestry1. We identified 65 new loci associated with overall breast cancer at pcancer due to all SNPs in regulatory features was 2-5-fold enriched relative to the genome-wide average, with strong enrichment for particular transcription factor binding sites. These results provide further insight into genetic susceptibility to breast cancer and will improve the utility of genetic risk scores for individualized screening and prevention. PMID:29059683

Association analysis identifies 65 new breast cancer risk loci

DEFF Research Database (Denmark)

Michailidou, Kyriaki; Lindström, Sara; Dennis, Joe

2017-01-01

Breast cancer risk is influenced by rare coding variants in susceptibility genes, such as BRCA1, and many common, mostly non-coding variants. However, much of the genetic contribution to breast cancer risk remains unknown. Here we report the results of a genome-wide association study of breast...... cancer in 122,977 cases and 105,974 controls of European ancestry and 14,068 cases and 13,104 controls of East Asian ancestry. We identified 65 new loci that are associated with overall breast cancer risk at P risk single-nucleotide polymorphisms in these loci fall......-nucleotide polymorphisms in regulatory features was 2-5-fold enriched relative to the genome-wide average, with strong enrichment for particular transcription factor binding sites. These results provide further insight into genetic susceptibility to breast cancer and will improve the use of genetic risk scores...
Utilization of genomic signatures to identify phenotype-specific drugs.

Directory of Open Access Journals (Sweden)

Seiichi Mori

2009-08-01

Full Text Available Genetic and genomic studies highlight the substantial complexity and heterogeneity of human cancers and emphasize the general lack of therapeutics that can match this complexity. With the goal of expanding opportunities for drug discovery, we describe an approach that makes use of a phenotype-based screen combined with the use of multiple cancer cell lines. In particular, we have used the NCI-60 cancer cell line panel that includes drug sensitivity measures for over 40,000 compounds assayed on 59 independent cells lines. Targets are cancer-relevant phenotypes represented as gene expression signatures that are used to identify cells within the NCI-60 panel reflecting the signature phenotype and then connect to compounds that are selectively active against those cells. As a proof-of-concept, we show that this strategy effectively identifies compounds with selectivity to the RAS or PI3K pathways. We have then extended this strategy to identify compounds that have activity towards cells exhibiting the basal phenotype of breast cancer, a clinically-important breast cancer characterized as ER-, PR-, and Her2- that lacks viable therapeutic options. One of these compounds, Simvastatin, has previously been shown to inhibit breast cancer cell growth in vitro and importantly, has been associated with a reduction in ER-, PR- breast cancer in a clinical study. We suggest that this approach provides a novel strategy towards identification of therapeutic agents based on clinically relevant phenotypes that can augment the conventional strategies of target-based screens.
MVisAGe Identifies Concordant and Discordant Genomic Alterations of Driver Genes in Squamous Tumors.

Science.gov (United States)

Walter, Vonn; Du, Ying; Danilova, Ludmila; Hayward, Michele C; Hayes, D Neil

2018-06-15

Integrated analyses of multiple genomic datatypes are now common in cancer profiling studies. Such data present opportunities for numerous computational experiments, yet analytic pipelines are limited. Tools such as the cBioPortal and Regulome Explorer, although useful, are not easy to access programmatically or to implement locally. Here, we introduce the MVisAGe R package, which allows users to quantify gene-level associations between two genomic datatypes to investigate the effect of genomic alterations (e.g., DNA copy number changes on gene expression). Visualizing Pearson/Spearman correlation coefficients according to the genomic positions of the underlying genes provides a powerful yet novel tool for conducting exploratory analyses. We demonstrate its utility by analyzing three publicly available cancer datasets. Our approach highlights canonical oncogenes in chr11q13 that displayed the strongest associations between expression and copy number, including CCND1 and CTTN , genes not identified by copy number analysis in the primary reports. We demonstrate highly concordant usage of shared oncogenes on chr3q, yet strikingly diverse oncogene usage on chr11q as a function of HPV infection status. Regions of chr19 that display remarkable associations between methylation and gene expression were identified, as were previously unreported miRNA-gene expression associations that may contribute to the epithelial-to-mesenchymal transition. Significance: This study presents an important bioinformatics tool that will enable integrated analyses of multiple genomic datatypes. Cancer Res; 78(12); 3375-85. ©2018 AACR . ©2018 American Association for Cancer Research.
NCC-AUC: an AUC optimization method to identify multi-biomarker panel for cancer prognosis from genomic and clinical data.

Science.gov (United States)

Zou, Meng; Liu, Zhaoqi; Zhang, Xiang-Sun; Wang, Yong

2015-10-15

In prognosis and survival studies, an important goal is to identify multi-biomarker panels with predictive power using molecular characteristics or clinical observations. Such analysis is often challenged by censored, small-sample-size, but high-dimensional genomic profiles or clinical data. Therefore, sophisticated models and algorithms are in pressing need. In this study, we propose a novel Area Under Curve (AUC) optimization method for multi-biomarker panel identification named Nearest Centroid Classifier for AUC optimization (NCC-AUC). Our method is motived by the connection between AUC score for classification accuracy evaluation and Harrell's concordance index in survival analysis. This connection allows us to convert the survival time regression problem to a binary classification problem. Then an optimization model is formulated to directly maximize AUC and meanwhile minimize the number of selected features to construct a predictor in the nearest centroid classifier framework. NCC-AUC shows its great performance by validating both in genomic data of breast cancer and clinical data of stage IB Non-Small-Cell Lung Cancer (NSCLC). For the genomic data, NCC-AUC outperforms Support Vector Machine (SVM) and Support Vector Machine-based Recursive Feature Elimination (SVM-RFE) in classification accuracy. It tends to select a multi-biomarker panel with low average redundancy and enriched biological meanings. Also NCC-AUC is more significant in separation of low and high risk cohorts than widely used Cox model (Cox proportional-hazards regression model) and L1-Cox model (L1 penalized in Cox model). These performance gains of NCC-AUC are quite robust across 5 subtypes of breast cancer. Further in an independent clinical data, NCC-AUC outperforms SVM and SVM-RFE in predictive accuracy and is consistently better than Cox model and L1-Cox model in grouping patients into high and low risk categories. In summary, NCC-AUC provides a rigorous optimization framework to
Meta-analysis of Genome Wide Association Studies Identifies Genetic Markers of Late Toxicity Following Radiotherapy for Prostate Cancer

Directory of Open Access Journals (Sweden)

Sarah L. Kerns

2016-08-01

Full Text Available Nearly 50% of cancer patients undergo radiotherapy. Late radiotherapy toxicity affects quality-of-life in long-term cancer survivors and risk of side-effects in a minority limits doses prescribed to the majority of patients. Development of a test predicting risk of toxicity could benefit many cancer patients. We aimed to meta-analyze individual level data from four genome-wide association studies from prostate cancer radiotherapy cohorts including 1564 men to identify genetic markers of toxicity. Prospectively assessed two-year toxicity endpoints (urinary frequency, decreased urine stream, rectal bleeding, overall toxicity and single nucleotide polymorphism (SNP associations were tested using multivariable regression, adjusting for clinical and patient-related risk factors. A fixed-effects meta-analysis identified two SNPs: rs17599026 on 5q31.2 with urinary frequency (odds ratio [OR] 3.12, 95% confidence interval [CI] 2.08–4.69, p-value 4.16 × 10−8 and rs7720298 on 5p15.2 with decreased urine stream (OR 2.71, 95% CI 1.90–3.86, p-value = 3.21 × 10−8. These SNPs lie within genes that are expressed in tissues adversely affected by pelvic radiotherapy including bladder, kidney, rectum and small intestine. The results show that heterogeneous radiotherapy cohorts can be combined to identify new moderate-penetrance genetic variants associated with radiotherapy toxicity. The work provides a basis for larger collaborative efforts to identify enough variants for a future test involving polygenic risk profiling.
Large-scale genotyping identifies 41 new loci associated with breast cancer risk.

Science.gov (United States)

Michailidou, Kyriaki; Hall, Per; Gonzalez-Neira, Anna; Ghoussaini, Maya; Dennis, Joe; Milne, Roger L; Schmidt, Marjanka K; Chang-Claude, Jenny; Bojesen, Stig E; Bolla, Manjeet K; Wang, Qin; Dicks, Ed; Lee, Andrew; Turnbull, Clare; Rahman, Nazneen; Fletcher, Olivia; Peto, Julian; Gibson, Lorna; Dos Santos Silva, Isabel; Nevanlinna, Heli; Muranen, Taru A; Aittomäki, Kristiina; Blomqvist, Carl; Czene, Kamila; Irwanto, Astrid; Liu, Jianjun; Waisfisz, Quinten; Meijers-Heijboer, Hanne; Adank, Muriel; van der Luijt, Rob B; Hein, Rebecca; Dahmen, Norbert; Beckman, Lars; Meindl, Alfons; Schmutzler, Rita K; Müller-Myhsok, Bertram; Lichtner, Peter; Hopper, John L; Southey, Melissa C; Makalic, Enes; Schmidt, Daniel F; Uitterlinden, Andre G; Hofman, Albert; Hunter, David J; Chanock, Stephen J; Vincent, Daniel; Bacot, François; Tessier, Daniel C; Canisius, Sander; Wessels, Lodewyk F A; Haiman, Christopher A; Shah, Mitul; Luben, Robert; Brown, Judith; Luccarini, Craig; Schoof, Nils; Humphreys, Keith; Li, Jingmei; Nordestgaard, Børge G; Nielsen, Sune F; Flyger, Henrik; Couch, Fergus J; Wang, Xianshu; Vachon, Celine; Stevens, Kristen N; Lambrechts, Diether; Moisse, Matthieu; Paridaens, Robert; Christiaens, Marie-Rose; Rudolph, Anja; Nickels, Stefan; Flesch-Janys, Dieter; Johnson, Nichola; Aitken, Zoe; Aaltonen, Kirsimari; Heikkinen, Tuomas; Broeks, Annegien; Veer, Laura J Van't; van der Schoot, C Ellen; Guénel, Pascal; Truong, Thérèse; Laurent-Puig, Pierre; Menegaux, Florence; Marme, Frederik; Schneeweiss, Andreas; Sohn, Christof; Burwinkel, Barbara; Zamora, M Pilar; Perez, Jose Ignacio Arias; Pita, Guillermo; Alonso, M Rosario; Cox, Angela; Brock, Ian W; Cross, Simon S; Reed, Malcolm W R; Sawyer, Elinor J; Tomlinson, Ian; Kerin, Michael J; Miller, Nicola; Henderson, Brian E; Schumacher, Fredrick; Le Marchand, Loic; Andrulis, Irene L; Knight, Julia A; Glendon, Gord; Mulligan, Anna Marie; Lindblom, Annika; Margolin, Sara; Hooning, Maartje J; Hollestelle, Antoinette; van den Ouweland, Ans M W; Jager, Agnes; Bui, Quang M; Stone, Jennifer; Dite, Gillian S; Apicella, Carmel; Tsimiklis, Helen; Giles, Graham G; Severi, Gianluca; Baglietto, Laura; Fasching, Peter A; Haeberle, Lothar; Ekici, Arif B; Beckmann, Matthias W; Brenner, Hermann; Müller, Heiko; Arndt, Volker; Stegmaier, Christa; Swerdlow, Anthony; Ashworth, Alan; Orr, Nick; Jones, Michael; Figueroa, Jonine; Lissowska, Jolanta; Brinton, Louise; Goldberg, Mark S; Labrèche, France; Dumont, Martine; Winqvist, Robert; Pylkäs, Katri; Jukkola-Vuorinen, Arja; Grip, Mervi; Brauch, Hiltrud; Hamann, Ute; Brüning, Thomas; Radice, Paolo; Peterlongo, Paolo; Manoukian, Siranoush; Bonanni, Bernardo; Devilee, Peter; Tollenaar, Rob A E M; Seynaeve, Caroline; van Asperen, Christi J; Jakubowska, Anna; Lubinski, Jan; Jaworska, Katarzyna; Durda, Katarzyna; Mannermaa, Arto; Kataja, Vesa; Kosma, Veli-Matti; Hartikainen, Jaana M; Bogdanova, Natalia V; Antonenkova, Natalia N; Dörk, Thilo; Kristensen, Vessela N; Anton-Culver, Hoda; Slager, Susan; Toland, Amanda E; Edge, Stephen; Fostira, Florentia; Kang, Daehee; Yoo, Keun-Young; Noh, Dong-Young; Matsuo, Keitaro; Ito, Hidemi; Iwata, Hiroji; Sueta, Aiko; Wu, Anna H; Tseng, Chiu-Chen; Van Den Berg, David; Stram, Daniel O; Shu, Xiao-Ou; Lu, Wei; Gao, Yu-Tang; Cai, Hui; Teo, Soo Hwang; Yip, Cheng Har; Phuah, Sze Yee; Cornes, Belinda K; Hartman, Mikael; Miao, Hui; Lim, Wei Yen; Sng, Jen-Hwei; Muir, Kenneth; Lophatananon, Artitaya; Stewart-Brown, Sarah; Siriwanarangsan, Pornthep; Shen, Chen-Yang; Hsiung, Chia-Ni; Wu, Pei-Ei; Ding, Shian-Ling; Sangrajrang, Suleeporn; Gaborieau, Valerie; Brennan, Paul; McKay, James; Blot, William J; Signorello, Lisa B; Cai, Qiuyin; Zheng, Wei; Deming-Halverson, Sandra; Shrubsole, Martha; Long, Jirong; Simard, Jacques; Garcia-Closas, Montse; Pharoah, Paul D P; Chenevix-Trench, Georgia; Dunning, Alison M; Benitez, Javier; Easton, Douglas F

2013-04-01

Breast cancer is the most common cancer among women. Common variants at 27 loci have been identified as associated with susceptibility to breast cancer, and these account for ∼9% of the familial risk of the disease. We report here a meta-analysis of 9 genome-wide association studies, including 10,052 breast cancer cases and 12,575 controls of European ancestry, from which we selected 29,807 SNPs for further genotyping. These SNPs were genotyped in 45,290 cases and 41,880 controls of European ancestry from 41 studies in the Breast Cancer Association Consortium (BCAC). The SNPs were genotyped as part of a collaborative genotyping experiment involving four consortia (Collaborative Oncological Gene-environment Study, COGS) and used a custom Illumina iSelect genotyping array, iCOGS, comprising more than 200,000 SNPs. We identified SNPs at 41 new breast cancer susceptibility loci at genome-wide significance (P breast cancer susceptibility.
Dana-Farber Cancer Institute: Identification of Therapeutic Targets Across Cancer Types | Office of Cancer Genomics

Science.gov (United States)

The Dana Farber Cancer Institute CTD2 Center focuses on the use of high-throughput genetic and bioinformatic approaches to identify and credential oncogenes and co-dependencies in cancers. This Center aims to provide the cancer research community with information that will facilitate the prioritization of targets based on both genomic and functional evidence, inform the most appropriate genetic context for downstream mechanistic and validation studies, and enable the translation of this information into therapeutics and diagnostics.
Whole genome DNA copy number changes identified by high density oligonucleotide arrays

Directory of Open Access Journals (Sweden)

Huang Jing

2004-05-01

Full Text Available Abstract Changes in DNA copy number are one of the hallmarks of the genetic instability common to most human cancers. Previous micro-array-based methods have been used to identify chromosomal gains and losses; however, they are unable to genotype alleles at the level of single nucleotide polymorphisms (SNPs. Here we describe a novel algorithm that uses a recently developed high-density oligonucleotide array-based SNP genotyping method, whole genome sampling analysis (WGSA, to identify genome-wide chromosomal gains and losses at high resolution. WGSA simultaneously genotypes over 10,000 SNPs by allele-specific hybridisation to perfect match (PM and mismatch (MM probes synthesised on a single array. The copy number algorithm jointly uses PM intensity and discrimination ratios between paired PM and MM intensity values to identify and estimate genetic copy number changes. Values from an experimental sample are compared with SNP-specific distributions derived from a reference set containing over 100 normal individuals to gain statistical power. Genomic regions with statistically significant copy number changes can be identified using both single point analysis and contiguous point analysis of SNP intensities. We identified multiple regions of amplification and deletion using a panel of human breast cancer cell lines. We verified these results using an independent method based on quantitative polymerase chain reaction and found that our approach is both sensitive and specific and can tolerate samples which contain a mixture of both tumour and normal DNA. In addition, by using known allele frequencies from the reference set, statistically significant genomic intervals can be identified containing contiguous stretches of homozygous markers, potentially allowing the detection of regions undergoing loss of heterozygosity (LOH without the need for a matched normal control sample. The coupling of LOH analysis, via SNP genotyping, with copy number
Genome-wide Meta-analyses of Breast, Ovarian and Prostate Cancer Association Studies Identify Multiple New Susceptibility Loci Shared by At Least Two Cancer Types

Science.gov (United States)

Kar, Siddhartha P.; Beesley, Jonathan; Al Olama, Ali Amin; Michailidou, Kyriaki; Tyrer, Jonathan; Kote-Jarai, ZSofia; Lawrenson, Kate; Lindstrom, Sara; Ramus, Susan J.; Thompson, Deborah J.; Kibel, Adam S.; Dansonka-Mieszkowska, Agnieszka; Michael, Agnieszka; Dieffenbach, Aida K.; Gentry-Maharaj, Aleksandra; Whittemore, Alice S.; Wolk, Alicja; Monteiro, Alvaro; Peixoto, Ana; Kierzek, Andrzej; Cox, Angela; Rudolph, Anja; Gonzalez-Neira, Anna; Wu, Anna H.; Lindblom, Annika; Swerdlow, Anthony; Ziogas, Argyrios; Ekici, Arif B.; Burwinkel, Barbara; Karlan, Beth Y.; Nordestgaard, Børge G.; Blomqvist, Carl; Phelan, Catherine; McLean, Catriona; Pearce, Celeste Leigh; Vachon, Celine; Cybulski, Cezary; Slavov, Chavdar; Stegmaier, Christa; Maier, Christiane; Ambrosone, Christine B.; Høgdall, Claus K.; Teerlink, Craig C.; Kang, Daehee; Tessier, Daniel C.; Schaid, Daniel J.; Stram, Daniel O.; Cramer, Daniel W.; Neal, David E.; Eccles, Diana; Flesch-Janys, Dieter; Velez Edwards, Digna R.; Wokozorczyk, Dominika; Levine, Douglas A.; Yannoukakos, Drakoulis; Sawyer, Elinor J.; Bandera, Elisa V.; Poole, Elizabeth M.; Goode, Ellen L.; Khusnutdinova, Elza; Høgdall, Estrid; Song, Fengju; Bruinsma, Fiona; Heitz, Florian; Modugno, Francesmary; Hamdy, Freddie C.; Wiklund, Fredrik; Giles, Graham G.; Olsson, Håkan; Wildiers, Hans; Ulmer, Hans-Ulrich; Pandha, Hardev; Risch, Harvey A.; Darabi, Hatef; Salvesen, Helga B.; Nevanlinna, Heli; Gronberg, Henrik; Brenner, Hermann; Brauch, Hiltrud; Anton-Culver, Hoda; Song, Honglin; Lim, Hui-Yi; McNeish, Iain; Campbell, Ian; Vergote, Ignace; Gronwald, Jacek; Lubiński, Jan; Stanford, Janet L.; Benítez, Javier; Doherty, Jennifer A.; Permuth, Jennifer B.; Chang-Claude, Jenny; Donovan, Jenny L.; Dennis, Joe; Schildkraut, Joellen M.; Schleutker, Johanna; Hopper, John L.; Kupryjanczyk, Jolanta; Park, Jong Y.; Figueroa, Jonine; Clements, Judith A.; Knight, Julia A.; Peto, Julian; Cunningham, Julie M.; Pow-Sang, Julio; Batra, Jyotsna; Czene, Kamila; Lu, Karen H.; Herkommer, Kathleen; Khaw, Kay-Tee; Matsuo, Keitaro; Muir, Kenneth; Offitt, Kenneth; Chen, Kexin; Moysich, Kirsten B.; Aittomäki, Kristiina; Odunsi, Kunle; Kiemeney, Lambertus A.; Massuger, Leon F.A.G.; Fitzgerald, Liesel M.; Cook, Linda S.; Cannon-Albright, Lisa; Hooning, Maartje J.; Pike, Malcolm C.; Bolla, Manjeet K.; Luedeke, Manuel; Teixeira, Manuel R.; Goodman, Marc T.; Schmidt, Marjanka K.; Riggan, Marjorie; Aly, Markus; Rossing, Mary Anne; Beckmann, Matthias W.; Moisse, Matthieu; Sanderson, Maureen; Southey, Melissa C.; Jones, Michael; Lush, Michael; Hildebrandt, Michelle A. T.; Hou, Ming-Feng; Schoemaker, Minouk J.; Garcia-Closas, Montserrat; Bogdanova, Natalia; Rahman, Nazneen; Le, Nhu D.; Orr, Nick; Wentzensen, Nicolas; Pashayan, Nora; Peterlongo, Paolo; Guénel, Pascal; Brennan, Paul; Paulo, Paula; Webb, Penelope M.; Broberg, Per; Fasching, Peter A.; Devilee, Peter; Wang, Qin; Cai, Qiuyin; Li, Qiyuan; Kaneva, Radka; Butzow, Ralf; Kopperud, Reidun Kristin; Schmutzler, Rita K.; Stephenson, Robert A.; MacInnis, Robert J.; Hoover, Robert N.; Winqvist, Robert; Ness, Roberta; Milne, Roger L.; Travis, Ruth C.; Benlloch, Sara; Olson, Sara H.; McDonnell, Shannon K.; Tworoger, Shelley S.; Maia, Sofia; Berndt, Sonja; Lee, Soo Chin; Teo, Soo-Hwang; Thibodeau, Stephen N.; Bojesen, Stig E.; Gapstur, Susan M.; Kjær, Susanne Krüger; Pejovic, Tanja; Tammela, Teuvo L.J.; Dörk, Thilo; Brüning, Thomas; Wahlfors, Tiina; Key, Tim J.; Edwards, Todd L.; Menon, Usha; Hamann, Ute; Mitev, Vanio; Kosma, Veli-Matti; Setiawan, Veronica Wendy; Kristensen, Vessela; Arndt, Volker; Vogel, Walther; Zheng, Wei; Sieh, Weiva; Blot, William J.; Kluzniak, Wojciech; Shu, Xiao-Ou; Gao, Yu-Tang; Schumacher, Fredrick; Freedman, Matthew L.; Berchuck, Andrew; Dunning, Alison M.; Simard, Jacques; Haiman, Christopher A.; Spurdle, Amanda; Sellers, Thomas A.; Hunter, David J.; Henderson, Brian E.; Kraft, Peter; Chanock, Stephen J.; Couch, Fergus J.; Hall, Per; Gayther, Simon A.; Easton, Douglas F.; Chenevix-Trench, Georgia; Eeles, Rosalind; Pharoah, Paul D.P.; Lambrechts, Diether

2016-01-01

Breast, ovarian, and prostate cancers are hormone-related and may have a shared genetic basis but this has not been investigated systematically by genome-wide association (GWA) studies. Meta-analyses combining the largest GWA meta-analysis data sets for these cancers totaling 112,349 cases and 116,421 controls of European ancestry, all together and in pairs, identified at P cancer loci: three associated with susceptibility to all three cancers (rs17041869/2q13/BCL2L11; rs7937840/11q12/INCENP; rs1469713/19p13/GATAD2A), two breast and ovarian cancer risk loci (rs200182588/9q31/SMC2; rs8037137/15q26/RCCD1), and two breast and prostate cancer risk loci (rs5013329/1p34/NSUN4; rs9375701/6q23/L3MBTL3). Index variants in five additional regions previously associated with only one cancer also showed clear association with a second cancer type. Cell-type specific expression quantitative trait locus and enhancer-gene interaction annotations suggested target genes with potential cross-cancer roles at the new loci. Pathway analysis revealed significant enrichment of death receptor signaling genes near loci with P cancer meta-analysis. PMID:27432226
Association analysis identifies 65 new breast cancer risk loci

OpenAIRE

Michailidou, Kyriaki; Lindström, Sara; Dennis, Joe; Beesley, Jonathan; Hui, Shirley; Kar, Siddhartha; Lemaçon, Audrey; Soucy, Penny; Glubb, Dylan; Rostamianfar, Asha; Bolla, Manjeet K; Wang, Qin; Tyrer, Jonathan; Dicks, Ed; Lee, Andrew

2017-01-01

Breast cancer risk is influenced by rare coding variants in susceptibility genes, such as BRCA1, and many common, mostly non-coding variants. However, much of the genetic contribution to breast cancer risk remains unknown. Here we report the results of a genome-wide association study of breast cancer in 122,977 cases and 105,974 controls of European ancestry and 14,068 cases and 13,104 controls of East Asian ancestry. We identified 65 new loci that are associated with overall breast cancer ri...
Incidental copy-number variants identified by routine genome testing in a clinical population

Science.gov (United States)

Boone, Philip M.; Soens, Zachry T.; Campbell, Ian M.; Stankiewicz, Pawel; Cheung, Sau Wai; Patel, Ankita; Beaudet, Arthur L.; Plon, Sharon E.; Shaw, Chad A.; McGuire, Amy L.; Lupski, James R.

2013-01-01

Purpose Mutational load of susceptibility variants has not been studied on a genomic scale in a clinical population, nor has the potential to identify these mutations as incidental findings during clinical testing been systematically ascertained. Methods Array comparative genomic hybridization, a method for genome-wide detection of DNA copy-number variants, was performed clinically on DNA from 9,005 individuals. Copy-number variants encompassing or disrupting single genes were identified and analyzed for their potential to confer predisposition to dominant, adult-onset disease. Multigene copy-number variants affecting dominant, adult-onset cancer syndrome genes were also assessed. Results In our cohort, 83 single-gene copy-number variants affected 40 unique genes associated with dominant, adult-onset disorders and unrelated to the patients’ referring diagnoses (i.e., incidental) were found. Fourteen of these copy-number variants are likely disease-predisposing, 25 are likely benign, and 44 are of unknown clinical consequence. When incidental copy-number variants spanning up to 20 genes were considered, 27 copy-number variants affected 17 unique genes associated with dominant, adult-onset cancer predisposition. Conclusion Copy-number variants potentially conferring susceptibility to adult-onset disease can be identified as incidental findings during routine genome-wide testing. Some of these mutations may be medically actionable, enabling disease surveillance or prevention; however, most incidentally observed single-gene copy-number variants are currently of unclear significance to the patient. PMID:22878507
A meta-analysis of 87,040 individuals identifies 23 new susceptibility loci for prostate cancer

DEFF Research Database (Denmark)

Al Olama, Ali Amin; Kote-Jarai, Zsofia; Berndt, Sonja I

2014-01-01

Genome-wide association studies (GWAS) have identified 76 variants associated with prostate cancer risk predominantly in populations of European ancestry. To identify additional susceptibility loci for this common cancer, we conducted a meta-analysis of > 10 million SNPs in 43,303 prostate cancer...
Contributing to Tumor Molecular Characterization Projects with a Global Impact | Office of Cancer Genomics

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My name is Nicholas Griner and I am the Scientific Program Manager for the Cancer Genome Characterization Initiative (CGCI) in the Office of Cancer Genomics (OCG). Until recently, I spent most of my scientific career working in a cancer research laboratory. In my postdoctoral training, my research focused on identifying novel pathways that contribute to both prostate and breast cancers and studying proteins within these pathways that may be targeted with cancer drugs.
Identifying pathways affected by cancer mutations.

Science.gov (United States)

Iengar, Prathima

2017-12-16

Mutations in 15 cancers, sourced from the COSMIC Whole Genomes database, and 297 human pathways, arranged into pathway groups based on the processes they orchestrate, and sourced from the KEGG pathway database, have together been used to identify pathways affected by cancer mutations. Genes studied in ≥15, and mutated in ≥10 samples of a cancer have been considered recurrently mutated, and pathways with recurrently mutated genes have been considered affected in the cancer. Novel doughnut plots have been presented which enable visualization of the extent to which pathways and genes, in each pathway group, are targeted, in each cancer. The 'organismal systems' pathway group (including organism-level pathways; e.g., nervous system) is the most targeted, more than even the well-recognized signal transduction, cell-cycle and apoptosis, and DNA repair pathway groups. The important, yet poorly-recognized, role played by the group merits attention. Pathways affected in ≥7 cancers yielded insights into processes affected. Copyright © 2017 Elsevier Inc. All rights reserved.
Integrated Genomic Analysis of the Ubiquitin Pathway across Cancer Types

Directory of Open Access Journals (Sweden)

Zhongqi Ge

2018-04-01

Full Text Available Summary: Protein ubiquitination is a dynamic and reversible process of adding single ubiquitin molecules or various ubiquitin chains to target proteins. Here, using multidimensional omic data of 9,125 tumor samples across 33 cancer types from The Cancer Genome Atlas, we perform comprehensive molecular characterization of 929 ubiquitin-related genes and 95 deubiquitinase genes. Among them, we systematically identify top somatic driver candidates, including mutated FBXW7 with cancer-type-specific patterns and amplified MDM2 showing a mutually exclusive pattern with BRAF mutations. Ubiquitin pathway genes tend to be upregulated in cancer mediated by diverse mechanisms. By integrating pan-cancer multiomic data, we identify a group of tumor samples that exhibit worse prognosis. These samples are consistently associated with the upregulation of cell-cycle and DNA repair pathways, characterized by mutated TP53, MYC/TERT amplification, and APC/PTEN deletion. Our analysis highlights the importance of the ubiquitin pathway in cancer development and lays a foundation for developing relevant therapeutic strategies. : Ge et al. analyze a cohort of 9,125 TCGA samples across 33 cancer types to provide a comprehensive characterization of the ubiquitin pathway. They detect somatic driver candidates in the ubiquitin pathway and identify a cluster of patients with poor survival, highlighting the importance of this pathway in cancer development. Keywords: ubiquitin pathway, pan-cancer analysis, The Cancer Genome Atlas, tumor subtype, cancer prognosis, therapeutic targets, biomarker, FBXW7
Characterizing the cancer genome in lung adenocarcinoma

Science.gov (United States)

Weir, Barbara A.; Woo, Michele S.; Getz, Gad; Perner, Sven; Ding, Li; Beroukhim, Rameen; Lin, William M.; Province, Michael A.; Kraja, Aldi; Johnson, Laura A.; Shah, Kinjal; Sato, Mitsuo; Thomas, Roman K.; Barletta, Justine A.; Borecki, Ingrid B.; Broderick, Stephen; Chang, Andrew C.; Chiang, Derek Y.; Chirieac, Lucian R.; Cho, Jeonghee; Fujii, Yoshitaka; Gazdar, Adi F.; Giordano, Thomas; Greulich, Heidi; Hanna, Megan; Johnson, Bruce E.; Kris, Mark G.; Lash, Alex; Lin, Ling; Lindeman, Neal; Mardis, Elaine R.; McPherson, John D.; Minna, John D.; Morgan, Margaret B.; Nadel, Mark; Orringer, Mark B.; Osborne, John R.; Ozenberger, Brad; Ramos, Alex H.; Robinson, James; Roth, Jack A.; Rusch, Valerie; Sasaki, Hidefumi; Shepherd, Frances; Sougnez, Carrie; Spitz, Margaret R.; Tsao, Ming-Sound; Twomey, David; Verhaak, Roel G. W.; Weinstock, George M.; Wheeler, David A.; Winckler, Wendy; Yoshizawa, Akihiko; Yu, Soyoung; Zakowski, Maureen F.; Zhang, Qunyuan; Beer, David G.; Wistuba, Ignacio I.; Watson, Mark A.; Garraway, Levi A.; Ladanyi, Marc; Travis, William D.; Pao, William; Rubin, Mark A.; Gabriel, Stacey B.; Gibbs, Richard A.; Varmus, Harold E.; Wilson, Richard K.; Lander, Eric S.; Meyerson, Matthew

2008-01-01

Somatic alterations in cellular DNA underlie almost all human cancers1. The prospect of targeted therapies2 and the development of high-resolution, genome-wide approaches3–8 are now spurring systematic efforts to characterize cancer genomes. Here we report a large-scale project to characterize copy-number alterations in primary lung adenocarcinomas. By analysis of a large collection of tumors (n = 371) using dense single nucleotide polymorphism arrays, we identify a total of 57 significantly recurrent events. We find that 26 of 39 autosomal chromosome arms show consistent large-scale copy-number gain or loss, of which only a handful have been linked to a specific gene. We also identify 31 recurrent focal events, including 24 amplifications and 7 homozygous deletions. Only six of these focal events are currently associated with known mutations in lung carcinomas. The most common event, amplification of chromosome 14q13.3, is found in ~12% of samples. On the basis of genomic and functional analyses, we identify NKX2-1 (NK2 homeobox 1, also called TITF1), which lies in the minimal 14q13.3 amplification interval and encodes a lineage-specific transcription factor, as a novel candidate proto-oncogene involved in a significant fraction of lung adenocarcinomas. More generally, our results indicate that many of the genes that are involved in lung adenocarcinoma remain to be discovered. PMID:17982442
Genomic and Epigenomic Alterations in Cancer.

Science.gov (United States)

Chakravarthi, Balabhadrapatruni V S K; Nepal, Saroj; Varambally, Sooryanarayana

2016-07-01

Multiple genetic and epigenetic events characterize tumor progression and define the identity of the tumors. Advances in high-throughput technologies, like gene expression profiling, next-generation sequencing, proteomics, and metabolomics, have enabled detailed molecular characterization of various tumors. The integration and analyses of these high-throughput data have unraveled many novel molecular aberrations and network alterations in tumors. These molecular alterations include multiple cancer-driving mutations, gene fusions, amplification, deletion, and post-translational modifications, among others. Many of these genomic events are being used in cancer diagnosis, whereas others are therapeutically targeted with small-molecule inhibitors. Multiple genes/enzymes that play a role in DNA and histone modifications are also altered in various cancers, changing the epigenomic landscape during cancer initiation and progression. Apart from protein-coding genes, studies are uncovering the critical regulatory roles played by noncoding RNAs and noncoding regions of the genome during cancer progression. Many of these genomic and epigenetic events function in tandem to drive tumor development and metastasis. Concurrent advances in genome-modulating technologies, like gene silencing and genome editing, are providing ability to understand in detail the process of cancer initiation, progression, and signaling as well as opening up avenues for therapeutic targeting. In this review, we discuss some of the recent advances in cancer genomic and epigenomic research. Copyright © 2016 American Society for Investigative Pathology. Published by Elsevier Inc. All rights reserved.
Interest in genomic SNP testing for prostate cancer risk: a pilot survey.

Science.gov (United States)

Hall, Michael J; Ruth, Karen J; Chen, David Yt; Gross, Laura M; Giri, Veda N

2015-01-01

Advancements in genomic testing have led to the identification of single nucleotide polymorphisms (SNPs) associated with prostate cancer. The clinical utility of SNP tests to evaluate prostate cancer risk is unclear. Studies have not examined predictors of interest in novel genomic SNP tests for prostate cancer risk in a diverse population. Consecutive participants in the Fox Chase Prostate Cancer Risk Assessment Program (PRAP) (n = 40) and unselected men from surgical urology clinics (n = 40) completed a one-time survey. Items examined interest in genomic SNP testing for prostate cancer risk, knowledge, impact of unsolicited findings, and psychosocial factors including health literacy. Knowledge of genomic SNP tests was low in both groups, but interest was higher among PRAP men (p testing in both groups. Multivariable modeling identified several predictors of higher interest in a genomic SNP test including higher perceived risk (p = 0.025), indicating zero reasons for not wanting testing (vs ≥1 reason) (p = 0.013), and higher health literacy (p = 0.016). Knowledge of genomic SNP testing was low in this sample, but higher among high-risk men. High-risk status may increase interest in novel genomic tests, while low literacy may lessen interest.
Large-scale genotyping identifies 41 new loci associated with breast cancer risk

DEFF Research Database (Denmark)

Michailidou, Kyriaki; Hall, Per; Gonzalez-Neira, Anna

2013-01-01

Breast cancer is the most common cancer among women. Common variants at 27 loci have been identified as associated with susceptibility to breast cancer, and these account for ∼9% of the familial risk of the disease. We report here a meta-analysis of 9 genome-wide association studies, including 10...
Large-scale genotyping identifies 41 new loci associated with breast cancer risk

NARCIS (Netherlands)

Michailidou, Kyriaki; Hall, Per; Gonzalez-Neira, Anna; Ghoussaini, Maya; Dennis, Joe; Milne, Roger L.; Schmidt, Marjanka K.; Chang-Claude, Jenny; Bojesen, Stig E.; Bolla, Manjeet K.; Wang, Qin; Dicks, Ed; Lee, Andrew; Turnbull, Clare; Rahman, Nazneen; Fletcher, Olivia; Peto, Julian; Gibson, Lorna; dos Santos Silva, Isabel; Nevanlinna, Heli; Muranen, Taru A.; Aittomäki, Kristiina; Blomqvist, Carl; Czene, Kamila; Irwanto, Astrid; Liu, Jianjun; Waisfisz, Quinten; Meijers-Heijboer, Hanne; Adank, Muriel; van der Luijt, Rob B.; Hein, Rebecca; Dahmen, Norbert; Beckman, Lars; Meindl, Alfons; Schmutzler, Rita K.; Müller-Myhsok, Bertram; Lichtner, Peter; Hopper, John L.; Southey, Melissa C.; Makalic, Enes; Schmidt, Daniel F.; Uitterlinden, Andre G.; Hofman, Albert; Hunter, David J.; Chanock, Stephen J.; Vincent, Daniel; Bacot, François; Tessier, Daniel C.; Canisius, Sander; Wessels, Lodewyk F. A.; Haiman, Christopher A.; Shah, Mitul; Luben, Robert; Brown, Judith; Luccarini, Craig; Schoof, Nils; Humphreys, Keith; Li, Jingmei; Nordestgaard, Børge G.; Nielsen, Sune F.; Flyger, Henrik; Couch, Fergus J.; Wang, Xianshu; Vachon, Celine; Stevens, Kristen N.; Lambrechts, Diether; Moisse, Matthieu; Paridaens, Robert; Christiaens, Marie-Rose; Rudolph, Anja; Nickels, Stefan; Flesch-Janys, Dieter; Johnson, Nichola; Aitken, Zoe; Aaltonen, Kirsimari; Heikkinen, Tuomas; Broeks, Annegien; van 't Veer, Laura J.; van der Schoot, C. Ellen; Guénel, Pascal; Truong, Thérèse; Laurent-Puig, Pierre; Menegaux, Florence; Marme, Frederik; Schneeweiss, Andreas; Sohn, Christof; Burwinkel, Barbara; Zamora, M. Pilar; Perez, Jose Ignacio Arias; Pita, Guillermo; Alonso, M. Rosario; Cox, Angela; Brock, Ian W.; Cross, Simon S.; Reed, Malcolm W. R.; Sawyer, Elinor J.; Tomlinson, Ian; Kerin, Michael J.; Miller, Nicola; Henderson, Brian E.; Schumacher, Fredrick; Le Marchand, Loic; Andrulis, Irene L.; Knight, Julia A.; Glendon, Gord; Mulligan, Anna Marie; Lindblom, Annika; Margolin, Sara; Hooning, Maartje J.; Hollestelle, Antoinette; van den Ouweland, Ans M. W.; Jager, Agnes; Bui, Quang M.; Stone, Jennifer; Dite, Gillian S.; Apicella, Carmel; Tsimiklis, Helen; Giles, Graham G.; Severi, Gianluca; Baglietto, Laura; Fasching, Peter A.; Haeberle, Lothar; Ekici, Arif B.; Beckmann, Matthias W.; Brenner, Hermann; Müller, Heiko; Arndt, Volker; Stegmaier, Christa; Swerdlow, Anthony; Ashworth, Alan; Orr, Nick; Jones, Michael; Figueroa, Jonine; Lissowska, Jolanta; Brinton, Louise; Goldberg, Mark S.; Labrèche, France; Dumont, Martine; Winqvist, Robert; Pylkäs, Katri; Jukkola-Vuorinen, Arja; Grip, Mervi; Brauch, Hiltrud; Hamann, Ute; Brüning, Thomas; Radice, Paolo; Peterlongo, Paolo; Manoukian, Siranoush; Bonanni, Bernardo; Devilee, Peter; Tollenaar, Rob A. E. M.; Seynaeve, Caroline; van Asperen, Christi J.; Jakubowska, Anna; Lubinski, Jan; Jaworska, Katarzyna; Durda, Katarzyna; Mannermaa, Arto; Kataja, Vesa; Kosma, Veli-Matti; Hartikainen, Jaana M.; Bogdanova, Natalia V.; Antonenkova, Natalia N.; Dörk, Thilo; Kristensen, Vessela N.; Anton-Culver, Hoda; Slager, Susan; Toland, Amanda E.; Edge, Stephen; Fostira, Florentia; Kang, Daehee; Yoo, Keun-Young; Noh, Dong-Young; Matsuo, Keitaro; Ito, Hidemi; Iwata, Hiroji; Sueta, Aiko; Wu, Anna H.; Tseng, Chiu-Chen; van den Berg, David; Stram, Daniel O.; Shu, Xiao-Ou; Lu, Wei; Gao, Yu-Tang; Cai, Hui; teo, Soo Hwang; Yip, Cheng Har; Phuah, Sze Yee; Cornes, Belinda K.; Hartman, Mikael; Miao, Hui; Lim, Wei Yen; Sng, Jen-Hwei; Muir, Kenneth; Lophatananon, Artitaya; Stewart-Brown, Sarah; Siriwanarangsan, Pornthep; Shen, Chen-Yang; Hsiung, Chia-Ni; Wu, Pei-Ei; Ding, Shian-Ling; Sangrajrang, Suleeporn; Gaborieau, Valerie; Brennan, Paul; McKay, James; Blot, William J.; Signorello, Lisa B.; Cai, Qiuyin; Zheng, Wei; Deming-Halverson, Sandra; Shrubsole, Martha; Long, Jirong; Simard, Jacques; Garcia-Closas, Montse; Pharoah, Paul D. P.; Chenevix-Trench, Georgia; Dunning, Alison M.; Benitez, Javier; Easton, Douglas F.

2013-01-01

Breast cancer is the most common cancer among women. Common variants at 27 loci have been identified as associated with susceptibility to breast cancer, and these account for ∼9% of the familial risk of the disease. We report here a meta-analysis of 9 genome-wide association studies, including

SIGMA: A System for Integrative Genomic Microarray Analysis of Cancer Genomes

Directory of Open Access Journals (Sweden)

Davies Jonathan J

2006-12-01

Full Text Available Abstract Background The prevalence of high resolution profiling of genomes has created a need for the integrative analysis of information generated from multiple methodologies and platforms. Although the majority of data in the public domain are gene expression profiles, and expression analysis software are available, the increase of array CGH studies has enabled integration of high throughput genomic and gene expression datasets. However, tools for direct mining and analysis of array CGH data are limited. Hence, there is a great need for analytical and display software tailored to cross platform integrative analysis of cancer genomes. Results We have created a user-friendly java application to facilitate sophisticated visualization and analysis such as cross-tumor and cross-platform comparisons. To demonstrate the utility of this software, we assembled array CGH data representing Affymetrix SNP chip, Stanford cDNA arrays and whole genome tiling path array platforms for cross comparison. This cancer genome database contains 267 profiles from commonly used cancer cell lines representing 14 different tissue types. Conclusion In this study we have developed an application for the visualization and analysis of data from high resolution array CGH platforms that can be adapted for analysis of multiple types of high throughput genomic datasets. Furthermore, we invite researchers using array CGH technology to deposit both their raw and processed data, as this will be a continually expanding database of cancer genomes. This publicly available resource, the System for Integrative Genomic Microarray Analysis (SIGMA of cancer genomes, can be accessed at http://sigma.bccrc.ca.
Genomic analyses identify hundreds of variants associated with age at menarche and support a role for puberty timing in cancer risk.

Science.gov (United States)

Day, Felix R; Thompson, Deborah J; Helgason, Hannes; Chasman, Daniel I; Finucane, Hilary; Sulem, Patrick; Ruth, Katherine S; Whalen, Sean; Sarkar, Abhishek K; Albrecht, Eva; Altmaier, Elisabeth; Amini, Marzyeh; Barbieri, Caterina M; Boutin, Thibaud; Campbell, Archie; Demerath, Ellen; Giri, Ayush; He, Chunyan; Hottenga, Jouke J; Karlsson, Robert; Kolcic, Ivana; Loh, Po-Ru; Lunetta, Kathryn L; Mangino, Massimo; Marco, Brumat; McMahon, George; Medland, Sarah E; Nolte, Ilja M; Noordam, Raymond; Nutile, Teresa; Paternoster, Lavinia; Perjakova, Natalia; Porcu, Eleonora; Rose, Lynda M; Schraut, Katharina E; Segrè, Ayellet V; Smith, Albert V; Stolk, Lisette; Teumer, Alexander; Andrulis, Irene L; Bandinelli, Stefania; Beckmann, Matthias W; Benitez, Javier; Bergmann, Sven; Bochud, Murielle; Boerwinkle, Eric; Bojesen, Stig E; Bolla, Manjeet K; Brand, Judith S; Brauch, Hiltrud; Brenner, Hermann; Broer, Linda; Brüning, Thomas; Buring, Julie E; Campbell, Harry; Catamo, Eulalia; Chanock, Stephen; Chenevix-Trench, Georgia; Corre, Tanguy; Couch, Fergus J; Cousminer, Diana L; Cox, Angela; Crisponi, Laura; Czene, Kamila; Davey Smith, George; de Geus, Eco J C N; de Mutsert, Renée; De Vivo, Immaculata; Dennis, Joe; Devilee, Peter; Dos-Santos-Silva, Isabel; Dunning, Alison M; Eriksson, Johan G; Fasching, Peter A; Fernández-Rhodes, Lindsay; Ferrucci, Luigi; Flesch-Janys, Dieter; Franke, Lude; Gabrielson, Marike; Gandin, Ilaria; Giles, Graham G; Grallert, Harald; Gudbjartsson, Daniel F; Guénel, Pascal; Hall, Per; Hallberg, Emily; Hamann, Ute; Harris, Tamara B; Hartman, Catharina A; Heiss, Gerardo; Hooning, Maartje J; Hopper, John L; Hu, Frank; Hunter, David J; Ikram, M Arfan; Im, Hae Kyung; Järvelin, Marjo-Riitta; Joshi, Peter K; Karasik, David; Kellis, Manolis; Kutalik, Zoltan; LaChance, Genevieve; Lambrechts, Diether; Langenberg, Claudia; Launer, Lenore J; Laven, Joop S E; Lenarduzzi, Stefania; Li, Jingmei; Lind, Penelope A; Lindstrom, Sara; Liu, YongMei; Luan, Jian'an; Mägi, Reedik; Mannermaa, Arto; Mbarek, Hamdi; McCarthy, Mark I; Meisinger, Christa; Meitinger, Thomas; Menni, Cristina; Metspalu, Andres; Michailidou, Kyriaki; Milani, Lili; Milne, Roger L; Montgomery, Grant W; Mulligan, Anna M; Nalls, Mike A; Navarro, Pau; Nevanlinna, Heli; Nyholt, Dale R; Oldehinkel, Albertine J; O'Mara, Tracy A; Padmanabhan, Sandosh; Palotie, Aarno; Pedersen, Nancy; Peters, Annette; Peto, Julian; Pharoah, Paul D P; Pouta, Anneli; Radice, Paolo; Rahman, Iffat; Ring, Susan M; Robino, Antonietta; Rosendaal, Frits R; Rudan, Igor; Rueedi, Rico; Ruggiero, Daniela; Sala, Cinzia F; Schmidt, Marjanka K; Scott, Robert A; Shah, Mitul; Sorice, Rossella; Southey, Melissa C; Sovio, Ulla; Stampfer, Meir; Steri, Maristella; Strauch, Konstantin; Tanaka, Toshiko; Tikkanen, Emmi; Timpson, Nicholas J; Traglia, Michela; Truong, Thérèse; Tyrer, Jonathan P; Uitterlinden, André G; Edwards, Digna R Velez; Vitart, Veronique; Völker, Uwe; Vollenweider, Peter; Wang, Qin; Widen, Elisabeth; van Dijk, Ko Willems; Willemsen, Gonneke; Winqvist, Robert; Wolffenbuttel, Bruce H R; Zhao, Jing Hua; Zoledziewska, Magdalena; Zygmunt, Marek; Alizadeh, Behrooz Z; Boomsma, Dorret I; Ciullo, Marina; Cucca, Francesco; Esko, Tõnu; Franceschini, Nora; Gieger, Christian; Gudnason, Vilmundur; Hayward, Caroline; Kraft, Peter; Lawlor, Debbie A; Magnusson, Patrik K E; Martin, Nicholas G; Mook-Kanamori, Dennis O; Nohr, Ellen A; Polasek, Ozren; Porteous, David; Price, Alkes L; Ridker, Paul M; Snieder, Harold; Spector, Tim D; Stöckl, Doris; Toniolo, Daniela; Ulivi, Sheila; Visser, Jenny A; Völzke, Henry; Wareham, Nicholas J; Wilson, James F; Spurdle, Amanda B; Thorsteindottir, Unnur; Pollard, Katherine S; Easton, Douglas F; Tung, Joyce Y; Chang-Claude, Jenny; Hinds, David; Murray, Anna; Murabito, Joanne M; Stefansson, Kari; Ong, Ken K; Perry, John R B

2017-06-01

The timing of puberty is a highly polygenic childhood trait that is epidemiologically associated with various adult diseases. Using 1000 Genomes Project-imputed genotype data in up to ∼370,000 women, we identify 389 independent signals (P < 5 × 10 -8 ) for age at menarche, a milestone in female pubertal development. In Icelandic data, these signals explain ∼7.4% of the population variance in age at menarche, corresponding to ∼25% of the estimated heritability. We implicate ∼250 genes via coding variation or associated expression, demonstrating significant enrichment in neural tissues. Rare variants near the imprinted genes MKRN3 and DLK1 were identified, exhibiting large effects when paternally inherited. Mendelian randomization analyses suggest causal inverse associations, independent of body mass index (BMI), between puberty timing and risks for breast and endometrial cancers in women and prostate cancer in men. In aggregate, our findings highlight the complexity of the genetic regulation of puberty timing and support causal links with cancer susceptibility.
Integrative Annotation of Variants from 1092 Humans: Application to Cancer Genomics

DEFF Research Database (Denmark)

Khurana, Ekta; Fu, Yao; Colonna, Vincenza

2013-01-01

Identifying Important Identifiers Each of us has millions of sequence variations in our genomes. Signatures of purifying or negative selection should help identify which of those variations is functionally important. Khurana et al. (1235587) used sequence polymorphisms from 1092 humans across 14...... sites tended to occur in network hub promoters. Many recurrent somatic cancer variants occurred in noncoding regulatory regions and thus might indicate mutations that drive cancer....
Admixture mapping of African-American women in the AMBER Consortium identifies new loci for breast cancer and estrogen-receptor subtypes

Directory of Open Access Journals (Sweden)

Edward Antonio Ruiz-Narvaez

2016-09-01

Full Text Available Recent genetic admixture coupled with striking differences in incidence of estrogen receptor (ER breast cancer subtypes, as well as severity, between women of African and European ancestry, provides an excellent rationale for performing admixture mapping in African American women with breast cancer risk. We performed the largest breast cancer admixture mapping study with in African American women to identify novel genomic regions associated with the disease. We conducted a genome-wide admixture scan using 2,624 autosomal ancestry informative markers (AIMs in 3,629 breast cancer cases (including 1,968 ER-positive, 1093 ER-negative and 601 triple-negative and 4,658 controls from the African American Breast Cancer Epidemiology and Risk (AMBER Consortium, a collaborative study of four large geographically different epidemiological studies of breast cancer in African American women. We used an independent case-control study to test for SNP association in regions with genome-wide significant admixture signals. We found two novel genome-wide significant regions of excess African ancestry, 4p16.1 and 17q25.1, associated with ER-positive breast cancer. Two regions known to harbor breast cancer variants, 10q26 and 11q13, were also identified with excess of African ancestry. Fine-mapping of the identified genome-wide significant regions suggests the presence of significant genetic associations with ER-positive breast cancer in 4p16.1 and 11q13. In summary, we identified three novel genomic regions associated with breast cancer risk by ER status, suggesting that additional previously unidentified variants may contribute to the racial differences in breast cancer risk in the African American population.
Carcinogen susceptibility is regulated by genome architecture and predicts cancer mutagenesis.

Science.gov (United States)

García-Nieto, Pablo E; Schwartz, Erin K; King, Devin A; Paulsen, Jonas; Collas, Philippe; Herrera, Rafael E; Morrison, Ashby J

2017-10-02

The development of many sporadic cancers is directly initiated by carcinogen exposure. Carcinogens induce malignancies by creating DNA lesions (i.e., adducts) that can result in mutations if left unrepaired. Despite this knowledge, there has been remarkably little investigation into the regulation of susceptibility to acquire DNA lesions. In this study, we present the first quantitative human genome-wide map of DNA lesions induced by ultraviolet (UV) radiation, the ubiquitous carcinogen in sunlight that causes skin cancer. Remarkably, the pattern of carcinogen susceptibility across the genome of primary cells significantly reflects mutation frequency in malignant melanoma. Surprisingly, DNase-accessible euchromatin is protected from UV, while lamina-associated heterochromatin at the nuclear periphery is vulnerable. Many cancer driver genes have an intrinsic increase in carcinogen susceptibility, including the BRAF oncogene that has the highest mutation frequency in melanoma. These findings provide a genome-wide snapshot of DNA injuries at the earliest stage of carcinogenesis. Furthermore, they identify carcinogen susceptibility as an origin of genome instability that is regulated by nuclear architecture and mirrors mutagenesis in cancer. © 2017 The Authors.
Genome-wide association studies in women of African ancestry identified 3q26.21 as a novel susceptibility locus for oestrogen receptor negative breast cancer.

Science.gov (United States)

Huo, Dezheng; Feng, Ye; Haddad, Stephen; Zheng, Yonglan; Yao, Song; Han, Yoo-Jeong; Ogundiran, Temidayo O; Adebamowo, Clement; Ojengbede, Oladosu; Falusi, Adeyinka G; Zheng, Wei; Blot, William; Cai, Qiuyin; Signorello, Lisa; John, Esther M; Bernstein, Leslie; Hu, Jennifer J; Ziegler, Regina G; Nyante, Sarah; Bandera, Elisa V; Ingles, Sue A; Press, Michael F; Deming, Sandra L; Rodriguez-Gil, Jorge L; Nathanson, Katherine L; Domchek, Susan M; Rebbeck, Timothy R; Ruiz-Narváez, Edward A; Sucheston-Campbell, Lara E; Bensen, Jeannette T; Simon, Michael S; Hennis, Anselm; Nemesure, Barbara; Leske, M Cristina; Ambs, Stefan; Chen, Lin S; Qian, Frank; Gamazon, Eric R; Lunetta, Kathryn L; Cox, Nancy J; Chanock, Stephen J; Kolonel, Laurence N; Olshan, Andrew F; Ambrosone, Christine B; Olopade, Olufunmilayo I; Palmer, Julie R; Haiman, Christopher A

2016-11-01

Multiple breast cancer loci have been identified in previous genome-wide association studies, but they were mainly conducted in populations of European ancestry. Women of African ancestry are more likely to have young-onset and oestrogen receptor (ER) negative breast cancer for reasons that are unknown and understudied. To identify genetic risk factors for breast cancer in women of African descent, we conducted a meta-analysis of two genome-wide association studies of breast cancer; one study consists of 1,657 cases and 2,029 controls genotyped with Illumina’s HumanOmni2.5 BeadChip and the other study included 3,016 cases and 2,745 controls genotyped using Illumina Human1M-Duo BeadChip. The top 18,376 single nucleotide polymorphisms (SNP) from the meta-analysis were replicated in the third study that consists of 1,984 African Americans cases and 2,939 controls. We found that SNP rs13074711, 26.5 Kb upstream of TNFSF10 at 3q26.21, was significantly associated with risk of oestrogen receptor (ER)-negative breast cancer (odds ratio [OR]=1.29, 95% CI: 1.18-1.40; P = 1.8 × 10 − 8). Functional annotations suggest that the TNFSF10 gene may be involved in breast cancer aetiology, but further functional experiments are needed. In addition, we confirmed SNP rs10069690 was the best indicator for ER-negative breast cancer at 5p15.33 (OR = 1.30; P = 2.4 × 10 − 10) and identified rs12998806 as the best indicator for ER-positive breast cancer at 2q35 (OR = 1.34; P = 2.2 × 10 − 8) for women of African ancestry. These findings demonstrated additional susceptibility alleles for breast cancer can be revealed in diverse populations and have important public health implications in building race/ethnicity-specific risk prediction model for breast cancer.
Human Papillomavirus Genome Integration and Head and Neck Cancer.

Science.gov (United States)

Pinatti, L M; Walline, H M; Carey, T E

2018-06-01

We conducted a critical review of human papillomavirus (HPV) integration into the host genome in oral/oropharyngeal cancer, reviewed the literature for HPV-induced cancers, and obtained current data for HPV-related oral and oropharyngeal cancers. In addition, we performed studies to identify HPV integration sites and the relationship of integration to viral-host fusion transcripts and whether integration is required for HPV-associated oncogenesis. Viral integration of HPV into the host genome is not required for the viral life cycle and might not be necessary for cellular transformation, yet HPV integration is frequently reported in cervical and head and neck cancer specimens. Studies of large numbers of early cervical lesions revealed frequent viral integration into gene-poor regions of the host genome with comparatively rare integration into cellular genes, suggesting that integration is a stochastic event and that site of integration may be largely a function of chance. However, more recent studies of head and neck squamous cell carcinomas (HNSCCs) suggest that integration may represent an additional oncogenic mechanism through direct effects on cancer-related gene expression and generation of hybrid viral-host fusion transcripts. In HNSCC cell lines as well as primary tumors, integration into cancer-related genes leading to gene disruption has been reported. The studies have shown that integration-induced altered gene expression may be associated with tumor recurrence. Evidence from several studies indicates that viral integration into genic regions is accompanied by local amplification, increased expression in some cases, interruption of gene expression, and likely additional oncogenic effects. Similarly, reported examples of viral integration near microRNAs suggest that altered expression of these regulatory molecules may also contribute to oncogenesis. Future work is indicated to identify the mechanisms of these events on cancer cell behavior.
Dana-Farber Cancer Institute: Identification of Therapeutic Targets in KRAS Driven Lung Cancer | Office of Cancer Genomics

Science.gov (United States)

The CTD2 Center at Dana Farber Cancer Institute focuses on the use of high-throughput genetic and bioinformatic approaches to identify and credential oncogenes and co-dependencies in cancers. This Center aims to provide the cancer research community with information that will facilitate the prioritization of targets based on both genomic and functional evidence, inform the most appropriate genetic context for downstream mechanistic and validation studies, and enable the translation of this information into therapeutics and diagnostics.
Genomic instability--an evolving hallmark of cancer.

Science.gov (United States)

Negrini, Simona; Gorgoulis, Vassilis G; Halazonetis, Thanos D

2010-03-01

Genomic instability is a characteristic of most cancers. In hereditary cancers, genomic instability results from mutations in DNA repair genes and drives cancer development, as predicted by the mutator hypothesis. In sporadic (non-hereditary) cancers the molecular basis of genomic instability remains unclear, but recent high-throughput sequencing studies suggest that mutations in DNA repair genes are infrequent before therapy, arguing against the mutator hypothesis for these cancers. Instead, the mutation patterns of the tumour suppressor TP53 (which encodes p53), ataxia telangiectasia mutated (ATM) and cyclin-dependent kinase inhibitor 2A (CDKN2A; which encodes p16INK4A and p14ARF) support the oncogene-induced DNA replication stress model, which attributes genomic instability and TP53 and ATM mutations to oncogene-induced DNA damage.
Functional annotation of rare gene aberration drivers of pancreatic cancer | Office of Cancer Genomics

Science.gov (United States)

As we enter the era of precision medicine, characterization of cancer genomes will directly influence therapeutic decisions in the clinic. Here we describe a platform enabling functionalization of rare gene mutations through their high-throughput construction, molecular barcoding and delivery to cancer models for in vivo tumour driver screens. We apply these technologies to identify oncogenic drivers of pancreatic ductal adenocarcinoma (PDAC).
Cross-cancer genome-wide analysis of lung, ovary, breast, prostate, and colorectal cancer reveals novel pleiotropic associations

NARCIS (Netherlands)

Fehringer, G. (Gordon); P. Kraft (Peter); P.D.P. Pharoah (Paul); R. Eeles (Rosalind); Chatterjee, N. (Nilanjan); F.R. Schumacher (Fredrick R); J.M. Schildkraut (Joellen); S. Lindstrom (Stephen); P. Brennan (Paul); H. Bickeböller (Heike); R. Houlston (Richard); M.T. Landi (Maria Teresa); N.E. Caporaso (Neil); Risch, A. (Angela); A.A. Al Olama (Ali Amin); S.I. Berndt (Sonja); Giovannucci, E.L. (Edward L.); H. Grönberg (Henrik); Z. Kote-Jarai; Ma, J. (Jing); K.R. Muir (K.); M.J. Stampfer (Meir J.); Stevens, V.L. (Victoria L.); F. Wiklund (Fredrik); W.C. Willett (Walter C.); E.L. Goode (Ellen); Permuth, J.B. (Jennifer B.); H. Risch (Harvey); Reid, B.M. (Brett M.); Bezieau, S. (Stephane); H. Brenner (Hermann); Chan, A.T. (Andrew T.); J. Chang-Claude (Jenny); T.J. Hudson (Thomas); Kocarnik, J.K. (Jonathan K.); P. Newcomb (Polly); Schoen, R.E. (Robert E.); Slattery, M.L. (Martha L.); White, E. (Emily); M.A. Adank (Muriel); H. Ahsan (Habibul); K. Aittomäki (Kristiina); Baglietto, L. (Laura); Blomquist, C. (Carl); F. Canzian (Federico); K. Czene (Kamila); I. dos Santos Silva (Isabel); Eliassen, A.H. (A. Heather); J.D. Figueroa (Jonine); D. Flesch-Janys (Dieter); O. Fletcher (Olivia); M. García-Closas (Montserrat); M.M. Gaudet (Mia); Johnson, N. (Nichola); P. Hall (Per); A. Hazra (Aditi); R. Hein (Rebecca); Hofman, A. (Albert); J.L. Hopper (John); A. Irwanto (Astrid); M. Johansson (Mattias); R. Kaaks (Rudolf); M.G. Kibriya (Muhammad); P. Lichtner (Peter); J. Liu (Jianjun); E. Lund (Eiliv); Makalic, E. (Enes); A. Meindl (Alfons); B. Müller-Myhsok (B.); Muranen, T.A. (Taru A.); H. Nevanlinna (Heli); P.H.M. Peeters; J. Peto (Julian); R. Prentice (Ross); N. Rahman (Nazneen); M.-J. Sanchez (Maria-Jose); D.F. Schmidt (Daniel); R.K. Schmutzler (Rita); M.C. Southey (Melissa); Tamimi, R. (Rulla); S.P.L. Travis (Simon); C. Turnbull (Clare); Uitterlinden, A.G. (Andre G.); Z. Wang (Zhaoming); A.S. Whittemore (Alice); X.R. Yang (Xiaohong); W. Zheng (Wei); D. Buchanan (Daniel); G. Casey (Graham); G. Conti (Giario); C.K. Edlund (Christopher); S. Gallinger (Steve); R. Haile (Robert); M. Jenkins (Mark); Marchand, L. (Loïcle); Li, L. (Li); N.M. Lindor (Noralane); Schmit, S.L. (Stephanie L.); S.N. Thibodeau (Stephen); M.O. Woods (Michael); T. Rafnar (Thorunn); J. Gudmundsson (Julius); S.N. Stacey (Simon); Stefansson, K. (Kari); P. Sulem (Patrick); Chen, Y.A. (Y. Ann); J.P. Tyrer (Jonathan); Christiani, D.C. (David C.); Wei, Y. (Yongyue); H. Shen (Hongbing); Z. Hu (Zhibin); X.-O. Shu (Xiao-Ou); Shiraishi, K. (Kouya); A. Takahashi (Atsushi); Y. Bossé (Yohan); M. Obeidat (Ma'en); D.C. Nickle (David); W. Timens (Wim); M. Freedman (Matthew); Li, Q. (Qiyuan); D. Seminara (Daniela); S.J. Chanock (Stephen); Gong, J. (Jian); U. Peters (Ulrike); S.B. Gruber (Stephen); Amos, C.I. (Christopher I.); T.A. Sellers (Thomas A.); D.F. Easton (Douglas F.); D. Hunter (David); C.A. Haiman (Christopher A.); B.E. Henderson (Brian); R.J. Hung (Rayjean)

2016-01-01

textabstractIdentifying genetic variants with pleiotropic associations can uncover common pathways influencing multiple cancers. We took a two-stage approach to conduct genome-wide association studies for lung, ovary, breast, prostate, and colorectal cancer from the GAME-ON/GECCO Network (61,851
Genome-wide association study of susceptibility loci for breast cancer in Sardinian population.

Science.gov (United States)

Palomba, Grazia; Loi, Angela; Porcu, Eleonora; Cossu, Antonio; Zara, Ilenia; Budroni, Mario; Dei, Mariano; Lai, Sandra; Mulas, Antonella; Olmeo, Nina; Ionta, Maria Teresa; Atzori, Francesco; Cuccuru, Gianmauro; Pitzalis, Maristella; Zoledziewska, Magdalena; Olla, Nazario; Lovicu, Mario; Pisano, Marina; Abecasis, Gonçalo R; Uda, Manuela; Tanda, Francesco; Michailidou, Kyriaki; Easton, Douglas F; Chanock, Stephen J; Hoover, Robert N; Hunter, David J; Schlessinger, David; Sanna, Serena; Crisponi, Laura; Palmieri, Giuseppe

2015-05-10

Despite progress in identifying genes associated with breast cancer, many more risk loci exist. Genome-wide association analyses in genetically-homogeneous populations, such as that of Sardinia (Italy), could represent an additional approach to detect low penetrance alleles. We performed a genome-wide association study comparing 1431 Sardinian patients with non-familial, BRCA1/2-mutation-negative breast cancer to 2171 healthy Sardinian blood donors. DNA was genotyped using GeneChip Human Mapping 500 K Arrays or Genome-Wide Human SNP Arrays 6.0. To increase genomic coverage, genotypes of additional SNPs were imputed using data from HapMap Phase II. After quality control filtering of genotype data, 1367 cases (9 men) and 1658 controls (1156 men) were analyzed on a total of 2,067,645 SNPs. Overall, 33 genomic regions (67 candidate SNPs) were associated with breast cancer risk at the p < 0(-6) level. Twenty of these regions contained defined genes, including one already associated with breast cancer risk: TOX3. With a lower threshold for preliminary significance to p < 10(-5), we identified 11 additional SNPs in FGFR2, a well-established breast cancer-associated gene. Ten candidate SNPs were selected, excluding those already associated with breast cancer, for technical validation as well as replication in 1668 samples from the same population. Only SNP rs345299, located in intron 1 of VAV3, remained suggestively associated (p-value, 1.16 x 10(-5)), but it did not associate with breast cancer risk in pooled data from two large, mixed-population cohorts. This study indicated the role of TOX3 and FGFR2 as breast cancer susceptibility genes in BRCA1/2-wild-type breast cancer patients from Sardinian population.
Genome-wide association study of susceptibility loci for breast cancer in Sardinian population

International Nuclear Information System (INIS)

Palomba, Grazia; Loi, Angela; Porcu, Eleonora; Cossu, Antonio; Zara, Ilenia

2015-01-01

Despite progress in identifying genes associated with breast cancer, many more risk loci exist. Genome-wide association analyses in genetically-homogeneous populations, such as that of Sardinia (Italy), could represent an additional approach to detect low penetrance alleles. We performed a genome-wide association study comparing 1431 Sardinian patients with non-familial, BRCA1/2-mutation-negative breast cancer to 2171 healthy Sardinian blood donors. DNA was genotyped using GeneChip Human Mapping 500 K Arrays or Genome-Wide Human SNP Arrays 6.0. To increase genomic coverage, genotypes of additional SNPs were imputed using data from HapMap Phase II. After quality control filtering of genotype data, 1367 cases (9 men) and 1658 controls (1156 men) were analyzed on a total of 2,067,645 SNPs. Overall, 33 genomic regions (67 candidate SNPs) were associated with breast cancer risk at the p < 10 −6 level. Twenty of these regions contained defined genes, including one already associated with breast cancer risk: TOX3. With a lower threshold for preliminary significance to p < 10 −5 , we identified 11 additional SNPs in FGFR2, a well-established breast cancer-associated gene. Ten candidate SNPs were selected, excluding those already associated with breast cancer, for technical validation as well as replication in 1668 samples from the same population. Only SNP rs345299, located in intron 1 of VAV3, remained suggestively associated (p-value, 1.16x10 −5 ), but it did not associate with breast cancer risk in pooled data from two large, mixed-population cohorts. This study indicated the role of TOX3 and FGFR2 as breast cancer susceptibility genes in BRCA1/2-wild-type breast cancer patients from Sardinian population. The online version of this article (doi:10.1186/s12885-015-1392-9) contains supplementary material, which is available to authorized users
Population-based statistical inference for temporal sequence of somatic mutations in cancer genomes.

Science.gov (United States)

Rhee, Je-Keun; Kim, Tae-Min

2018-04-20

It is well recognized that accumulation of somatic mutations in cancer genomes plays a role in carcinogenesis; however, the temporal sequence and evolutionary relationship of somatic mutations remain largely unknown. In this study, we built a population-based statistical framework to infer the temporal sequence of acquisition of somatic mutations. Using the model, we analyzed the mutation profiles of 1954 tumor specimens across eight tumor types. As a result, we identified tumor type-specific directed networks composed of 2-15 cancer-related genes (nodes) and their mutational orders (edges). The most common ancestors identified in pairwise comparison of somatic mutations were TP53 mutations in breast, head/neck, and lung cancers. The known relationship of KRAS to TP53 mutations in colorectal cancers was identified, as well as potential ancestors of TP53 mutation such as NOTCH1, EGFR, and PTEN mutations in head/neck, lung and endometrial cancers, respectively. We also identified apoptosis-related genes enriched with ancestor mutations in lung cancers and a relationship between APC hotspot mutations and TP53 mutations in colorectal cancers. While evolutionary analysis of cancers has focused on clonal versus subclonal mutations identified in individual genomes, our analysis aims to further discriminate ancestor versus descendant mutations in population-scale mutation profiles that may help select cancer drivers with clinical relevance.
Fenton reaction induced cancer in wild type rats recapitulates genomic alterations observed in human cancer.

Directory of Open Access Journals (Sweden)

Shinya Akatsuka

Full Text Available Iron overload has been associated with carcinogenesis in humans. Intraperitoneal administration of ferric nitrilotriacetate initiates a Fenton reaction in renal proximal tubules of rodents that ultimately leads to a high incidence of renal cell carcinoma (RCC after repeated treatments. We performed high-resolution microarray comparative genomic hybridization to identify characteristics in the genomic profiles of this oxidative stress-induced rat RCCs. The results revealed extensive large-scale genomic alterations with a preference for deletions. Deletions and amplifications were numerous and sometimes fragmented, demonstrating that a Fenton reaction is a cause of such genomic alterations in vivo. Frequency plotting indicated that two of the most commonly altered loci corresponded to a Cdkn2a/2b deletion and a Met amplification. Tumor sizes were proportionally associated with Met expression and/or amplification, and clustering analysis confirmed our results. Furthermore, we developed a procedure to compare whole genomic patterns of the copy number alterations among different species based on chromosomal syntenic relationship. Patterns of the rat RCCs showed the strongest similarity to the human RCCs among five types of human cancers, followed by human malignant mesothelioma, an iron overload-associated cancer. Therefore, an iron-dependent Fenton chemical reaction causes large-scale genomic alterations during carcinogenesis, which may result in distinct genomic profiles. Based on the characteristics of extensive genome alterations in human cancer, our results suggest that this chemical reaction may play a major role during human carcinogenesis.
Cross-Cancer Genome-Wide Analysis of Lung, Ovary, Breast, Prostate, and Colorectal Cancer Reveals Novel Pleiotropic Associations

NARCIS (Netherlands)

Fehringer, Gordon; Kraft, Peter; Pharoah, Paul D.; Eeles, Rosalind A.; Chatterjee, Nilanjan; Schumacher, Fredrick R.; Schildkraut, Joellen M.; Lindstrom, Sara; Brennan, Paul; Bickeboller, Heike; Houlston, Richard S.; Landi, Maria Teresa; Caporaso, Neil; Risch, Angela; Al Olama, Ali Amin; Berndt, Sonja I.; Giovannucci, Edward L.; Gronberg, Henrik; Kote-Jarai, Zsofia; Ma, Jing; Muir, Kenneth; Stampfer, Meir J.; Stevens, Victoria L.; Wiklund, Fredrik; Willett, Walter C.; Goode, Ellen L.; Permuth, Jennifer B.; Risch, Harvey A.; Reid, Brett M.; Bezieau, Stephane; Brenner, Hermann; Chan, Andrew T.; Chang-Claude, Jenny; Hudson, Thomas J.; Kocarnik, Jonathan K.; Newcomb, Polly A.; Schoen, Robert E.; Slattery, Martha L.; White, Emily; Adank, Muriel A.; Ahsan, Habibul; Aittomaki, Kristiina; Baglietto, Laura; Blomquist, Carl; Canzian, Federico; Czene, Kamila; dos-Santos-Silva, Isabel; Eliassen, A. Heather; Figueroa, Jonine D.; Timens, Wim

2016-01-01

Identifying genetic variants with pleiotropic associations can uncover common pathways influencing multiple cancers. We took a two-stage approach to conduct genome-wide association studies for lung, ovary, breast, prostate, and colorectal cancer from the GAME-ON/GECCO Network (61,851 cases, 61,820
Cross-cancer genome-wide analysis of lung, ovary, breast, prostate, and colorectal cancer reveals novel pleiotropic associations

NARCIS (Netherlands)

Fehringer, Gordon; Kraft, Peter; Pharoah, Paul D.; Eeles, Rosalind A.; Chatterjee, Nilanjan; Schumacher, Fredrick R.; Schildkraut, Joellen M.; Lindström, Sara; Brennan, Paul; Bickeböller, Heike; Houlston, Richard S.; Landi, Maria Teresa; Caporaso, Neil; Risch, Angela; Al Olama, Ali Amin; Berndt, Sonja I.; Giovannucci, Edward L.; Grönberg, Henrik; Kote-Jarai, Zsofia; Ma, Jing; Muir, Kenneth; Stampfer, Meir J.; Stevens, Victoria L.; Wiklund, Fredrik; Willett, Walter C.; Goode, Ellen L.; Permuth, Jennifer B.; Risch, Harvey A.; Reid, Brett M.; Bezieau, Stephane; Brenner, Hermann; Chan, Andrew T.; Chang-Claude, Jenny; Hudson, Thomas J.; Kocarnik, Jonathan K.; Newcomb, Polly A.; Schoen, Robert E.; Slattery, Martha L.; White, Emily; Adank, Muriel A.; Ahsan, Habibul; Aittomäki, Kristiina; Baglietto, Laura; Blomquist, Carl; Canzian, Federico; Czene, Kamila; Dos-Santos-silva, Isabel; Eliassen, A. Heather; Figueroa, Jonine D.; Flesch-Janys, Dieter; Fletcher, Olivia; Garcia-Closas, Montserrat; Gaudet, Mia M.; Johnson, Nichola; Hall, Per; Hazra, Aditi; Hein, Rebecca; Hofman, Albert; Hopper, John L.; Irwanto, Astrid; Johansson, Mattias; Kaaks, Rudolf; Kibriya, Muhammad G.; Lichtner, Peter; Liu, Jianjun; Lund, Eiliv; Makalic, Enes; Meindl, Alfons; Müller-Myhsok, Bertram; Muranen, Taru A.; Nevanlinna, Heli; Peeters, Petra H.; Peto, Julian; Prentice, Ross L.; Rahman, Nazneen; Sanchez, Maria Jose; Schmidt, Daniel F.; Schmutzler, Rita K.; Southey, Melissa C.; Tamimi, Rulla; Travis, Ruth C.; Turnbull, Clare; Uitterlinden, Andre G.; Wang, Zhaoming; Whittemore, Alice S.; Yang, Xiaohong R.; Zheng, Wei; Buchanan, Daniel D.; Casey, Graham; Conti, David V.; Edlund, Christopher K.; Gallinger, Steven; Haile, Robert W.; Jenkins, Mark; Marchand, Loïcle; Li, Li; Lindor, Noralene M.; Schmit, Stephanie L.; Thibodeau, Stephen N.; Woods, Michael O.; Rafnar, Thorunn; Gudmundsson, Julius; Stacey, Simon N.; Stefansson, Kari; Sulem, Patrick; Chen, Y. Ann; Tyrer, Jonathan P.; Christiani, David C.; Wei, Yongyue; Shen, Hongbing; Hu, Zhibin; Shu, Xiao Ou; Shiraishi, Kouya; Takahashi, Atsushi; Bossé, Yohan; Obeidat, Ma'en; Nickle, David; Timens, Wim; Freedman, Matthew L.; Li, Qiyuan; Seminara, Daniela; Chanock, Stephen J.; Gong, Jian; Peters, Ulrike; Gruber, Stephen B.; Amos, Christopher I.; Sellers, Thomas A.; Easton, Douglas F.; Hunter, David J.; Haiman, Christopher A.; Henderson, Brian E.; Hung, Rayjean J.

2016-01-01

Identifying genetic variants with pleiotropic associations can uncover common pathways influencing multiple cancers. We took a two-stage approach to conduct genome-wide association studies for lung, ovary, breast, prostate, and colorectal cancer from the GAME-ON/GECCO Network (61,851 cases, 61,820
Genome-wide methylation analysis identifies genes silenced in non-seminoma cell lines.

Science.gov (United States)

Noor, Dzul Azri Mohamed; Jeyapalan, Jennie N; Alhazmi, Safiah; Carr, Matthew; Squibb, Benjamin; Wallace, Claire; Tan, Christopher; Cusack, Martin; Hughes, Jaime; Reader, Tom; Shipley, Janet; Sheer, Denise; Scotting, Paul J

2016-01-01

Silencing of genes by DNA methylation is a common phenomenon in many types of cancer. However, the genome-wide effect of DNA methylation on gene expression has been analysed in relatively few cancers. Germ cell tumours (GCTs) are a complex group of malignancies. They are unique in developing from a pluripotent progenitor cell. Previous analyses have suggested that non-seminomas exhibit much higher levels of DNA methylation than seminomas. The genomic targets that are methylated, the extent to which this results in gene silencing and the identity of the silenced genes most likely to play a role in the tumours' biology have not yet been established. In this study, genome-wide methylation and expression analysis of GCT cell lines was combined with gene expression data from primary tumours to address this question. Genome methylation was analysed using the Illumina infinium HumanMethylome450 bead chip system and gene expression was analysed using Affymetrix GeneChip Human Genome U133 Plus 2.0 arrays. Regulation by methylation was confirmed by demethylation using 5-aza-2-deoxycytidine and reverse transcription-quantitative PCR. Large differences in the level of methylation of the CpG islands of individual genes between tumour cell lines correlated well with differential gene expression. Treatment of non-seminoma cells with 5-aza-2-deoxycytidine verified that methylation of all genes tested played a role in their silencing in yolk sac tumour cells and many of these genes were also differentially expressed in primary tumours. Genes silenced by methylation in the various GCT cell lines were identified. Several pluripotency-associated genes were identified as a major functional group of silenced genes.
A genome-wide siRNA screen identifies proteasome addiction as a vulnerability of basal-like triple-negative breast cancer cells

Science.gov (United States)

Petrocca, Fabio; Altschuler, Gabriel; Tan, Shen Mynn; Mendillo, Marc L.; Yan, Haoheng; Jerry, D. Joseph; Kung, Andrew L.; Hide, Winston; Ince, Tan A.; Lieberman, Judy

2013-01-01

Summary Basal-like triple negative breast cancers (TNBC) have poor prognosis. To identify basal-like TNBC dependencies, a genome-wide siRNA lethality screen compared two human breast epithelial cell lines transformed with the same genes - basal-like BPLER and myoepithelial HMLER. Expression of the screen’s 154 BPLER dependency genes correlated with poor prognosis in breast, but not lung or colon, cancer. Proteasome genes were overrepresented hits. Basal-like TNBC lines were selectively sensitive to proteasome inhibitor drugs relative to normal epithelial, luminal and mesenchymal TNBC lines. Proteasome inhibition reduced growth of established basal-like TNBC tumors in mice and blocked tumor-initiating cell function and macrometastasis. Proteasome addiction in basal-like TNBCs was mediated by NOXA and linked to MCL-1 dependence. PMID:23948298
Machine Learning Detects Pan-cancer Ras Pathway Activation in The Cancer Genome Atlas

Directory of Open Access Journals (Sweden)

Gregory P. Way

2018-04-01

Full Text Available Summary: Precision oncology uses genomic evidence to match patients with treatment but often fails to identify all patients who may respond. The transcriptome of these “hidden responders” may reveal responsive molecular states. We describe and evaluate a machine-learning approach to classify aberrant pathway activity in tumors, which may aid in hidden responder identification. The algorithm integrates RNA-seq, copy number, and mutations from 33 different cancer types across The Cancer Genome Atlas (TCGA PanCanAtlas project to predict aberrant molecular states in tumors. Applied to the Ras pathway, the method detects Ras activation across cancer types and identifies phenocopying variants. The model, trained on human tumors, can predict response to MEK inhibitors in wild-type Ras cell lines. We also present data that suggest that multiple hits in the Ras pathway confer increased Ras activity. The transcriptome is underused in precision oncology and, combined with machine learning, can aid in the identification of hidden responders. : Way et al. develop a machine-learning approach using PanCanAtlas data to detect Ras activation in cancer. Integrating mutation, copy number, and expression data, the authors show that their method detects Ras-activating variants in tumors and sensitivity to MEK inhibitors in cell lines. Keywords: Gene expression, machine learning, Ras, NF1, KRAS, NRAS, HRAS, pan-cancer, TCGA, drug sensitivity

GWAS meta-analysis and replication identifies three new susceptibility loci for ovarian cancer

DEFF Research Database (Denmark)

Pharoah, Paul D P; Tsai, Ya-Yu; Ramus, Susan J

2013-01-01

Genome-wide association studies (GWAS) have identified four susceptibility loci for epithelial ovarian cancer (EOC), with another two suggestive loci reaching near genome-wide significance. We pooled data from a GWAS conducted in North America with another GWAS from the UK. We selected the top 24...
Microenvironmental Heterogeneity Parallels Breast Cancer Progression: A Histology-Genomic Integration Analysis.

Directory of Open Access Journals (Sweden)

Rachael Natrajan

2016-02-01

Full Text Available The intra-tumor diversity of cancer cells is under intense investigation; however, little is known about the heterogeneity of the tumor microenvironment that is key to cancer progression and evolution. We aimed to assess the degree of microenvironmental heterogeneity in breast cancer and correlate this with genomic and clinical parameters.We developed a quantitative measure of microenvironmental heterogeneity along three spatial dimensions (3-D in solid tumors, termed the tumor ecosystem diversity index (EDI, using fully automated histology image analysis coupled with statistical measures commonly used in ecology. This measure was compared with disease-specific survival, key mutations, genome-wide copy number, and expression profiling data in a retrospective study of 510 breast cancer patients as a test set and 516 breast cancer patients as an independent validation set. In high-grade (grade 3 breast cancers, we uncovered a striking link between high microenvironmental heterogeneity measured by EDI and a poor prognosis that cannot be explained by tumor size, genomics, or any other data types. However, this association was not observed in low-grade (grade 1 and 2 breast cancers. The prognostic value of EDI was superior to known prognostic factors and was enhanced with the addition of TP53 mutation status (multivariate analysis test set, p = 9 × 10-4, hazard ratio = 1.47, 95% CI 1.17-1.84; validation set, p = 0.0011, hazard ratio = 1.78, 95% CI 1.26-2.52. Integration with genome-wide profiling data identified losses of specific genes on 4p14 and 5q13 that were enriched in grade 3 tumors with high microenvironmental diversity that also substratified patients into poor prognostic groups. Limitations of this study include the number of cell types included in the model, that EDI has prognostic value only in grade 3 tumors, and that our spatial heterogeneity measure was dependent on spatial scale and tumor size.To our knowledge, this is the first
Integration of genomic, transcriptomic and proteomic data identifies two biologically distinct subtypes of invasive lobular breast cancer.

Science.gov (United States)

Michaut, Magali; Chin, Suet-Feung; Majewski, Ian; Severson, Tesa M; Bismeijer, Tycho; de Koning, Leanne; Peeters, Justine K; Schouten, Philip C; Rueda, Oscar M; Bosma, Astrid J; Tarrant, Finbarr; Fan, Yue; He, Beilei; Xue, Zheng; Mittempergher, Lorenza; Kluin, Roelof J C; Heijmans, Jeroen; Snel, Mireille; Pereira, Bernard; Schlicker, Andreas; Provenzano, Elena; Ali, Hamid Raza; Gaber, Alexander; O'Hurley, Gillian; Lehn, Sophie; Muris, Jettie J F; Wesseling, Jelle; Kay, Elaine; Sammut, Stephen John; Bardwell, Helen A; Barbet, Aurélie S; Bard, Floriane; Lecerf, Caroline; O'Connor, Darran P; Vis, Daniël J; Benes, Cyril H; McDermott, Ultan; Garnett, Mathew J; Simon, Iris M; Jirström, Karin; Dubois, Thierry; Linn, Sabine C; Gallagher, William M; Wessels, Lodewyk F A; Caldas, Carlos; Bernards, Rene

2016-01-05

Invasive lobular carcinoma (ILC) is the second most frequently occurring histological breast cancer subtype after invasive ductal carcinoma (IDC), accounting for around 10% of all breast cancers. The molecular processes that drive the development of ILC are still largely unknown. We have performed a comprehensive genomic, transcriptomic and proteomic analysis of a large ILC patient cohort and present here an integrated molecular portrait of ILC. Mutations in CDH1 and in the PI3K pathway are the most frequent molecular alterations in ILC. We identified two main subtypes of ILCs: (i) an immune related subtype with mRNA up-regulation of PD-L1, PD-1 and CTLA-4 and greater sensitivity to DNA-damaging agents in representative cell line models; (ii) a hormone related subtype, associated with Epithelial to Mesenchymal Transition (EMT), and gain of chromosomes 1q and 8q and loss of chromosome 11q. Using the somatic mutation rate and eIF4B protein level, we identified three groups with different clinical outcomes, including a group with extremely good prognosis. We provide a comprehensive overview of the molecular alterations driving ILC and have explored links with therapy response. This molecular characterization may help to tailor treatment of ILC through the application of specific targeted, chemo- and/or immune-therapies.
A site specific model and analysis of the neutral somatic mutation rate in whole-genome cancer data.

Science.gov (United States)

Bertl, Johanna; Guo, Qianyun; Juul, Malene; Besenbacher, Søren; Nielsen, Morten Muhlig; Hornshøj, Henrik; Pedersen, Jakob Skou; Hobolth, Asger

2018-04-19

Detailed modelling of the neutral mutational process in cancer cells is crucial for identifying driver mutations and understanding the mutational mechanisms that act during cancer development. The neutral mutational process is very complex: whole-genome analyses have revealed that the mutation rate differs between cancer types, between patients and along the genome depending on the genetic and epigenetic context. Therefore, methods that predict the number of different types of mutations in regions or specific genomic elements must consider local genomic explanatory variables. A major drawback of most methods is the need to average the explanatory variables across the entire region or genomic element. This procedure is particularly problematic if the explanatory variable varies dramatically in the element under consideration. To take into account the fine scale of the explanatory variables, we model the probabilities of different types of mutations for each position in the genome by multinomial logistic regression. We analyse 505 cancer genomes from 14 different cancer types and compare the performance in predicting mutation rate for both regional based models and site-specific models. We show that for 1000 randomly selected genomic positions, the site-specific model predicts the mutation rate much better than regional based models. We use a forward selection procedure to identify the most important explanatory variables. The procedure identifies site-specific conservation (phyloP), replication timing, and expression level as the best predictors for the mutation rate. Finally, our model confirms and quantifies certain well-known mutational signatures. We find that our site-specific multinomial regression model outperforms the regional based models. The possibility of including genomic variables on different scales and patient specific variables makes it a versatile framework for studying different mutational mechanisms. Our model can serve as the neutral null model
Identifying candidate driver genes by integrative ovarian cancer genomics data

Science.gov (United States)

Lu, Xinguo; Lu, Jibo

2017-08-01

Integrative analysis of molecular mechanics underlying cancer can distinguish interactions that cannot be revealed based on one kind of data for the appropriate diagnosis and treatment of cancer patients. Tumor samples exhibit heterogeneity in omics data, such as somatic mutations, Copy Number Variations CNVs), gene expression profiles and so on. In this paper we combined gene co-expression modules and mutation modulators separately in tumor patients to obtain the candidate driver genes for resistant and sensitive tumor from the heterogeneous data. The final list of modulators identified are well known in biological processes associated with ovarian cancer, such as CCL17, CACTIN, CCL16, CCL22, APOB, KDF1, CCL11, HNF1B, LRG1, MED1 and so on, which can help to facilitate the discovery of biomarkers, molecular diagnostics, and drug discovery.
Endometrial and acute myeloid leukemia cancer genomes characterized

Science.gov (United States)

Two studies from The Cancer Genome Atlas (TCGA) program reveal details about the genomic landscapes of acute myeloid leukemia (AML) and endometrial cancer. Both provide new insights into the molecular underpinnings of these cancers.
Genomic and Functional Approaches to Understanding Cancer Aneuploidy.

Science.gov (United States)

Taylor, Alison M; Shih, Juliann; Ha, Gavin; Gao, Galen F; Zhang, Xiaoyang; Berger, Ashton C; Schumacher, Steven E; Wang, Chen; Hu, Hai; Liu, Jianfang; Lazar, Alexander J; Cherniack, Andrew D; Beroukhim, Rameen; Meyerson, Matthew

2018-04-09

Aneuploidy, whole chromosome or chromosome arm imbalance, is a near-universal characteristic of human cancers. In 10,522 cancer genomes from The Cancer Genome Atlas, aneuploidy was correlated with TP53 mutation, somatic mutation rate, and expression of proliferation genes. Aneuploidy was anti-correlated with expression of immune signaling genes, due to decreased leukocyte infiltrates in high-aneuploidy samples. Chromosome arm-level alterations show cancer-specific patterns, including loss of chromosome arm 3p in squamous cancers. We applied genome engineering to delete 3p in lung cells, causing decreased proliferation rescued in part by chromosome 3 duplication. This study defines genomic and phenotypic correlates of cancer aneuploidy and provides an experimental approach to study chromosome arm aneuploidy. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.
Association analysis identifies 65 new breast cancer risk loci.

Science.gov (United States)

Michailidou, Kyriaki; Lindström, Sara; Dennis, Joe; Beesley, Jonathan; Hui, Shirley; Kar, Siddhartha; Lemaçon, Audrey; Soucy, Penny; Glubb, Dylan; Rostamianfar, Asha; Bolla, Manjeet K; Wang, Qin; Tyrer, Jonathan; Dicks, Ed; Lee, Andrew; Wang, Zhaoming; Allen, Jamie; Keeman, Renske; Eilber, Ursula; French, Juliet D; Qing Chen, Xiao; Fachal, Laura; McCue, Karen; McCart Reed, Amy E; Ghoussaini, Maya; Carroll, Jason S; Jiang, Xia; Finucane, Hilary; Adams, Marcia; Adank, Muriel A; Ahsan, Habibul; Aittomäki, Kristiina; Anton-Culver, Hoda; Antonenkova, Natalia N; Arndt, Volker; Aronson, Kristan J; Arun, Banu; Auer, Paul L; Bacot, François; Barrdahl, Myrto; Baynes, Caroline; Beckmann, Matthias W; Behrens, Sabine; Benitez, Javier; Bermisheva, Marina; Bernstein, Leslie; Blomqvist, Carl; Bogdanova, Natalia V; Bojesen, Stig E; Bonanni, Bernardo; Børresen-Dale, Anne-Lise; Brand, Judith S; Brauch, Hiltrud; Brennan, Paul; Brenner, Hermann; Brinton, Louise; Broberg, Per; Brock, Ian W; Broeks, Annegien; Brooks-Wilson, Angela; Brucker, Sara Y; Brüning, Thomas; Burwinkel, Barbara; Butterbach, Katja; Cai, Qiuyin; Cai, Hui; Caldés, Trinidad; Canzian, Federico; Carracedo, Angel; Carter, Brian D; Castelao, Jose E; Chan, Tsun L; David Cheng, Ting-Yuan; Seng Chia, Kee; Choi, Ji-Yeob; Christiansen, Hans; Clarke, Christine L; Collée, Margriet; Conroy, Don M; Cordina-Duverger, Emilie; Cornelissen, Sten; Cox, David G; Cox, Angela; Cross, Simon S; Cunningham, Julie M; Czene, Kamila; Daly, Mary B; Devilee, Peter; Doheny, Kimberly F; Dörk, Thilo; Dos-Santos-Silva, Isabel; Dumont, Martine; Durcan, Lorraine; Dwek, Miriam; Eccles, Diana M; Ekici, Arif B; Eliassen, A Heather; Ellberg, Carolina; Elvira, Mingajeva; Engel, Christoph; Eriksson, Mikael; Fasching, Peter A; Figueroa, Jonine; Flesch-Janys, Dieter; Fletcher, Olivia; Flyger, Henrik; Fritschi, Lin; Gaborieau, Valerie; Gabrielson, Marike; Gago-Dominguez, Manuela; Gao, Yu-Tang; Gapstur, Susan M; García-Sáenz, José A; Gaudet, Mia M; Georgoulias, Vassilios; Giles, Graham G; Glendon, Gord; Goldberg, Mark S; Goldgar, David E; González-Neira, Anna; Grenaker Alnæs, Grethe I; Grip, Mervi; Gronwald, Jacek; Grundy, Anne; Guénel, Pascal; Haeberle, Lothar; Hahnen, Eric; Haiman, Christopher A; Håkansson, Niclas; Hamann, Ute; Hamel, Nathalie; Hankinson, Susan; Harrington, Patricia; Hart, Steven N; Hartikainen, Jaana M; Hartman, Mikael; Hein, Alexander; Heyworth, Jane; Hicks, Belynda; Hillemanns, Peter; Ho, Dona N; Hollestelle, Antoinette; Hooning, Maartje J; Hoover, Robert N; Hopper, John L; Hou, Ming-Feng; Hsiung, Chia-Ni; Huang, Guanmengqian; Humphreys, Keith; Ishiguro, Junko; Ito, Hidemi; Iwasaki, Motoki; Iwata, Hiroji; Jakubowska, Anna; Janni, Wolfgang; John, Esther M; Johnson, Nichola; Jones, Kristine; Jones, Michael; Jukkola-Vuorinen, Arja; Kaaks, Rudolf; Kabisch, Maria; Kaczmarek, Katarzyna; Kang, Daehee; Kasuga, Yoshio; Kerin, Michael J; Khan, Sofia; Khusnutdinova, Elza; Kiiski, Johanna I; Kim, Sung-Won; Knight, Julia A; Kosma, Veli-Matti; Kristensen, Vessela N; Krüger, Ute; Kwong, Ava; Lambrechts, Diether; Le Marchand, Loic; Lee, Eunjung; Lee, Min Hyuk; Lee, Jong Won; Neng Lee, Chuen; Lejbkowicz, Flavio; Li, Jingmei; Lilyquist, Jenna; Lindblom, Annika; Lissowska, Jolanta; Lo, Wing-Yee; Loibl, Sibylle; Long, Jirong; Lophatananon, Artitaya; Lubinski, Jan; Luccarini, Craig; Lux, Michael P; Ma, Edmond S K; MacInnis, Robert J; Maishman, Tom; Makalic, Enes; Malone, Kathleen E; Kostovska, Ivana Maleva; Mannermaa, Arto; Manoukian, Siranoush; Manson, JoAnn E; Margolin, Sara; Mariapun, Shivaani; Martinez, Maria Elena; Matsuo, Keitaro; Mavroudis, Dimitrios; McKay, James; McLean, Catriona; Meijers-Heijboer, Hanne; Meindl, Alfons; Menéndez, Primitiva; Menon, Usha; Meyer, Jeffery; Miao, Hui; Miller, Nicola; Taib, Nur Aishah Mohd; Muir, Kenneth; Mulligan, Anna Marie; Mulot, Claire; Neuhausen, Susan L; Nevanlinna, Heli; Neven, Patrick; Nielsen, Sune F; Noh, Dong-Young; Nordestgaard, Børge G; Norman, Aaron; Olopade, Olufunmilayo I; Olson, Janet E; Olsson, Håkan; Olswold, Curtis; Orr, Nick; Pankratz, V Shane; Park, Sue K; Park-Simon, Tjoung-Won; Lloyd, Rachel; Perez, Jose I A; Peterlongo, Paolo; Peto, Julian; Phillips, Kelly-Anne; Pinchev, Mila; Plaseska-Karanfilska, Dijana; Prentice, Ross; Presneau, Nadege; Prokofyeva, Darya; Pugh, Elizabeth; Pylkäs, Katri; Rack, Brigitte; Radice, Paolo; Rahman, Nazneen; Rennert, Gadi; Rennert, Hedy S; Rhenius, Valerie; Romero, Atocha; Romm, Jane; Ruddy, Kathryn J; Rüdiger, Thomas; Rudolph, Anja; Ruebner, Matthias; Rutgers, Emiel J T; Saloustros, Emmanouil; Sandler, Dale P; Sangrajrang, Suleeporn; Sawyer, Elinor J; Schmidt, Daniel F; Schmutzler, Rita K; Schneeweiss, Andreas; Schoemaker, Minouk J; Schumacher, Fredrick; Schürmann, Peter; Scott, Rodney J; Scott, Christopher; Seal, Sheila; Seynaeve, Caroline; Shah, Mitul; Sharma, Priyanka; Shen, Chen-Yang; Sheng, Grace; Sherman, Mark E; Shrubsole, Martha J; Shu, Xiao-Ou; Smeets, Ann; Sohn, Christof; Southey, Melissa C; Spinelli, John J; Stegmaier, Christa; Stewart-Brown, Sarah; Stone, Jennifer; Stram, Daniel O; Surowy, Harald; Swerdlow, Anthony; Tamimi, Rulla; Taylor, Jack A; Tengström, Maria; Teo, Soo H; Beth Terry, Mary; Tessier, Daniel C; Thanasitthichai, Somchai; Thöne, Kathrin; Tollenaar, Rob A E M; Tomlinson, Ian; Tong, Ling; Torres, Diana; Truong, Thérèse; Tseng, Chiu-Chen; Tsugane, Shoichiro; Ulmer, Hans-Ulrich; Ursin, Giske; Untch, Michael; Vachon, Celine; van Asperen, Christi J; Van Den Berg, David; van den Ouweland, Ans M W; van der Kolk, Lizet; van der Luijt, Rob B; Vincent, Daniel; Vollenweider, Jason; Waisfisz, Quinten; Wang-Gohrke, Shan; Weinberg, Clarice R; Wendt, Camilla; Whittemore, Alice S; Wildiers, Hans; Willett, Walter; Winqvist, Robert; Wolk, Alicja; Wu, Anna H; Xia, Lucy; Yamaji, Taiki; Yang, Xiaohong R; Har Yip, Cheng; Yoo, Keun-Young; Yu, Jyh-Cherng; Zheng, Wei; Zheng, Ying; Zhu, Bin; Ziogas, Argyrios; Ziv, Elad; Lakhani, Sunil R; Antoniou, Antonis C; Droit, Arnaud; Andrulis, Irene L; Amos, Christopher I; Couch, Fergus J; Pharoah, Paul D P; Chang-Claude, Jenny; Hall, Per; Hunter, David J; Milne, Roger L; García-Closas, Montserrat; Schmidt, Marjanka K; Chanock, Stephen J; Dunning, Alison M; Edwards, Stacey L; Bader, Gary D; Chenevix-Trench, Georgia; Simard, Jacques; Kraft, Peter; Easton, Douglas F

2017-11-02

Breast cancer risk is influenced by rare coding variants in susceptibility genes, such as BRCA1, and many common, mostly non-coding variants. However, much of the genetic contribution to breast cancer risk remains unknown. Here we report the results of a genome-wide association study of breast cancer in 122,977 cases and 105,974 controls of European ancestry and 14,068 cases and 13,104 controls of East Asian ancestry. We identified 65 new loci that are associated with overall breast cancer risk at P < 5 × 10 -8 . The majority of credible risk single-nucleotide polymorphisms in these loci fall in distal regulatory elements, and by integrating in silico data to predict target genes in breast cells at each locus, we demonstrate a strong overlap between candidate target genes and somatic driver genes in breast tumours. We also find that heritability of breast cancer due to all single-nucleotide polymorphisms in regulatory features was 2-5-fold enriched relative to the genome-wide average, with strong enrichment for particular transcription factor binding sites. These results provide further insight into genetic susceptibility to breast cancer and will improve the use of genetic risk scores for individualized screening and prevention.
Genome-wide meta-analysis identifies five new susceptibility loci for pancreatic cancer

NARCIS (Netherlands)

Klein, Alison P.; Wolpin, Brian M.; Risch, Harvey A.; Stolzenberg-Solomon, Rachael Z.; Mocci, Evelina; Zhang, Mingfeng; Canzian, Federico; Childs, Erica J.; Hoskins, Jason W.; Jermusyk, Ashley; Zhong, Jun; Chen, Fei; Albanes, Demetrius; Andreotti, Gabriella; Arslan, Alan A.; Babic, Ana; Bamlet, William R.; Beane-Freeman, Laura; Berndt, Sonja I.; Blackford, Amanda; Borges, Michael; Borgida, Ayelet; Bracci, Paige M.; Brais, Lauren; Brennan, Paul; Brenner, Hermann; Bueno-de-Mesquita, Bas; Buring, Julie; Campa, Daniele; Capurso, Gabriele; Cavestro, Giulia Martina; Chaffee, Kari G.; Chung, Charles C.; Cleary, Sean; Cotterchio, Michelle; Dijk, Frederike; Duell, Eric J.; Foretova, Lenka; Fuchs, Charles; Funel, Niccola; Gallinger, Steven; M Gaziano, J. Michael; Gazouli, Maria; Giles, Graham G.; Giovannucci, Edward; Goggins, Michael; Goodman, Gary E.; Goodman, Phyllis J.; Hackert, Thilo; Haiman, Christopher; Hartge, Patricia; Hasan, Manal; Hegyi, Peter; Helzlsouer, Kathy J.; Herman, Joseph; Holcatova, Ivana; Holly, Elizabeth A.; Hoover, Robert; Hung, Rayjean J.; Jacobs, Eric J.; Jamroziak, Krzysztof; Janout, Vladimir; Kaaks, Rudolf; Khaw, Kay-Tee; Klein, Eric A.; Kogevinas, Manolis; Kooperberg, Charles; Kulke, Matthew H.; Kupcinskas, Juozas; Kurtz, Robert J.; Laheru, Daniel; Landi, Stefano; Lawlor, Rita T.; Lee, I.-Min; Lemarchand, Loic; Lu, Lingeng; Malats, Núria; Mambrini, Andrea; Mannisto, Satu; Milne, Roger L.; Mohelníková-Duchoňová, Beatrice; Neale, Rachel E.; Neoptolemos, John P.; Oberg, Ann L.; Olson, Sara H.; Orlow, Irene; Pasquali, Claudio; Patel, Alpa V.; Peters, Ulrike; Pezzilli, Raffaele; Porta, Miquel; Real, Francisco X.; Rothman, Nathaniel; Scelo, Ghislaine; Sesso, Howard D.; Severi, Gianluca; Shu, Xiao-Ou; Silverman, Debra; Smith, Jill P.; Soucek, Pavel; Sund, Malin; Talar-Wojnarowska, Renata; Tavano, Francesca; Thornquist, Mark D.; Tobias, Geoffrey S.; van den Eeden, Stephen K.; Vashist, Yogesh; Visvanathan, Kala; Vodicka, Pavel; Wactawski-Wende, Jean; Wang, Zhaoming; Wentzensen, Nicolas; White, Emily; Yu, Herbert; Yu, Kai; Zeleniuch-Jacquotte, Anne; Zheng, Wei; Kraft, Peter; Li, Donghui; Chanock, Stephen; Obazee, Ofure; Petersen, Gloria M.; Amundadottir, Laufey T.

2018-01-01

In 2020, 146,063 deaths due to pancreatic cancer are estimated to occur in Europe and the United States combined. To identify common susceptibility alleles, we performed the largest pancreatic cancer GWAS to date, including 9040 patients and 12,496 controls of European ancestry from the Pancreatic
Genome-wide meta-analysis identifies five new susceptibility loci for pancreatic cancer.

NARCIS (Netherlands)

Klein, Alison P; Wolpin, Brian M; Risch, Harvey A; Stolzenberg-Solomon, Rachael Z; Mocci, Evelina; Zhang, Mingfeng; Canzian, Federico; Childs, Erica J; Hoskins, Jason W; Jermusyk, Ashley; Zhong, Jun; Sund, Malin; Talar-Wojnarowska, Renata; Tavano, Francesca; Thornquist, Mark D; Tobias, Geoffrey S; Van Den Eeden, Stephen K; Vashist, Yogesh; Visvanathan, Kala; Vodicka, Pavel; Wactawski-Wende, Jean; Chen, Fei; Wang, Zhaoming; Wentzensen, Nicolas; White, Emily; Yu, Herbert; Yu, Kai; Zeleniuch-Jacquotte, Anne; Zheng, Wei; Kraft, Peter; Li, Donghui; Chanock, Stephen; Albanes, Demetrius; Obazee, Ofure; Petersen, Gloria M; Amundadottir, Laufey T; Andreotti, Gabriella; Arslan, Alan A; Babic, Ana; Bamlet, William R; Beane-Freeman, Laura; Berndt, Sonja I; Blackford, Amanda; Borges, Michael; Borgida, Ayelet; Bracci, Paige M; Brais, Lauren; Brennan, Paul; Brenner, Hermann; Bueno-de-Mesquita, Bas; Buring, Julie; Campa, Daniele; Capurso, Gabriele; Cavestro, Giulia Martina; Chaffee, Kari G; Chung, Charles C; Cleary, Sean; Cotterchio, Michelle; Dijk, Frederike; Duell, Eric J; Foretova, Lenka; Fuchs, Charles; Funel, Niccola; Gallinger, Steven; M Gaziano, J Michael; Gazouli, Maria; Giles, Graham G; Giovannucci, Edward; Goggins, Michael; Goodman, Gary E; Goodman, Phyllis J; Hackert, Thilo; Haiman, Christopher; Hartge, Patricia; Hasan, Manal; Hegyi, Peter; Helzlsouer, Kathy J; Herman, Joseph; Holcatova, Ivana; Holly, Elizabeth A; Hoover, Robert; Hung, Rayjean J; Jacobs, Eric J; Jamroziak, Krzysztof; Janout, Vladimir; Kaaks, Rudolf; Khaw, Kay-Tee; Klein, Eric A; Kogevinas, Manolis; Kooperberg, Charles; Kulke, Matthew H; Kupcinskas, Juozas; Kurtz, Robert J; Laheru, Daniel; Landi, Stefano; Lawlor, Rita T; Lee, I-Min; LeMarchand, Loic; Lu, Lingeng; Malats, Núria; Mambrini, Andrea; Mannisto, Satu; Milne, Roger L; Mohelníková-Duchoňová, Beatrice; Neale, Rachel E; Neoptolemos, John P; Oberg, Ann L; Olson, Sara H; Orlow, Irene; Pasquali, Claudio; Patel, Alpa V; Peters, Ulrike; Pezzilli, Raffaele; Porta, Miquel; Real, Francisco X; Rothman, Nathaniel; Scelo, Ghislaine; Sesso, Howard D; Severi, Gianluca; Shu, Xiao-Ou; Silverman, Debra; Smith, Jill P; Soucek, Pavel

2018-01-01

In 2020, 146,063 deaths due to pancreatic cancer are estimated to occur in Europe and the United States combined. To identify common susceptibility alleles, we performed the largest pancreatic cancer GWAS to date, including 9040 patients and 12,496 controls of European ancestry from the Pancreatic
Specific genomic regions are differentially affected by copy number alterations across distinct cancer types, in aggregated cytogenetic data.

Science.gov (United States)

Kumar, Nitin; Cai, Haoyang; von Mering, Christian; Baudis, Michael

2012-01-01

Regional genomic copy number alterations (CNA) are observed in the vast majority of cancers. Besides specifically targeting well-known, canonical oncogenes, CNAs may also play more subtle roles in terms of modulating genetic potential and broad gene expression patterns of developing tumors. Any significant differences in the overall CNA patterns between different cancer types may thus point towards specific biological mechanisms acting in those cancers. In addition, differences among CNA profiles may prove valuable for cancer classifications beyond existing annotation systems. We have analyzed molecular-cytogenetic data from 25579 tumors samples, which were classified into 160 cancer types according to the International Classification of Disease (ICD) coding system. When correcting for differences in the overall CNA frequencies between cancer types, related cancers were often found to cluster together according to similarities in their CNA profiles. Based on a randomization approach, distance measures from the cluster dendrograms were used to identify those specific genomic regions that contributed significantly to this signal. This approach identified 43 non-neutral genomic regions whose propensity for the occurrence of copy number alterations varied with the type of cancer at hand. Only a subset of these identified loci overlapped with previously implied, highly recurrent (hot-spot) cytogenetic imbalance regions. Thus, for many genomic regions, a simple null-hypothesis of independence between cancer type and relative copy number alteration frequency can be rejected. Since a subset of these regions display relatively low overall CNA frequencies, they may point towards second-tier genomic targets that are adaptively relevant but not necessarily essential for cancer development.
Cross-cancer genome-wide analysis of lung, ovary, breast, prostate and colorectal cancer reveals novel pleiotropic associations

Science.gov (United States)

Fehringer, Gordon; Kraft, Peter; Pharoah, Paul D.; Eeles, Rosalind A.; Chatterjee, Nilanjan; Schumacher, Fred; Schildkraut, Joellen; Lindström, Sara; Brennan, Paul; Bickeböller, Heike; Houlston, Richard S.; Landi, Maria Teresa; Caporaso, Neil; Risch, Angela; Olama, Ali Amin Al; Berndt, Sonja I; Giovannucci, Edward; Grönberg, Henrik; Kote-Jarai, Zsofia; Ma, Jing; Muir, Kenneth; Stampfer, Meir; Stevens, Victoria L.; Wiklund, Fredrik; Willett, Walter; Goode, Ellen L.; Permuth, Jennifer; Risch, Harvey A.; Reid, Brett M.; Bezieau, Stephane; Brenner, Hermann; Chan, Andrew T.; Chang-Claude, Jenny; Hudson, Thomas J.; Kocarnik, Jonathan K.; Newcomb, Polly A.; Schoen, Robert E.; Slattery, Martha L.; White, Emily; Adank, Muriel A.; Ahsan, Habibul; Aittomäki, Kristiina; Baglietto, Laura; Blomquist, Carl; Canzian, Federico; Czene, Kamila; dos-Santos-Silva, Isabel; Eliassen, A. Heather; Figueroa, Jonine; Flesch-Janys, Dieter; Fletcher, Olivia; Garcia-Closas, Montserrat; Gaudet, Mia M.; Johnson, Nichola; Hall, Per; Hazra, Aditi; Hein, Rebecca; Hofman, Albert; Hopper, John L.; Irwanto, Astrid; Johansson, Mattias; Kaaks, Rudolf; Kibriya, Muhammad G.; Lichtner, Peter; Liu, Jianjun; Lund, Eiliv; Makalic, Enes; Meindl, Alfons; Müller-Myhsok, Bertram; Muranen, Taru A.; Nevanlinna, Heli; Peeters, Petra H.; Peto, Julian; Prentice, Ross L.; Rahman, Nazneen; Sanchez, Maria Jose; Schmidt, Daniel F.; Schmutzler, Rita K.; Southey, Melissa C.; Tamimi, Rulla; Travis, Ruth C.; Turnbull, Clare; Uitterlinden, Andre G.; Wang, Zhaoming; Whittemore, Alice S.; Yang, Xiaohong R.; Zheng, Wei; Rafnar, Thorunn; Gudmundsson, Julius; Stacey, Simon N.; Stefansson, Kari; Sulem, Patrick; Chen, Y. Ann; Tyrer, Jonathan P.; Christiani, David C.; Wei, Yongyue; Shen, Hongbing; Hu, Zhibin; Shu, Xiao-Ou; Shiraishi, Kouya; Takahashi, Atsushi; Bossé, Yohan; Obeidat, Ma’en; Nickle, David; Timens, Wim; Freedman, Matthew L.; Li, Qiyuan; Seminara, Daniela; Chanock, Stephen J.; Gong, Jian; Peters, Ulrike; Gruber, Stephen B.; Amos, Christopher I.; Sellers, Thomas A.; Easton, Douglas F.; Hunter, David J.; Haiman, Christopher A.; Henderson, Brian E.; Hung, Rayjean J.

2016-01-01

Identifying genetic variants with pleiotropic associations can uncover common pathways influencing multiple cancers. We took a two-staged approach to conduct genome-wide association studies for lung, ovary, breast, prostate and colorectal cancer from the GAME-ON/GECCO Network (61,851 cases, 61,820 controls) to identify pleiotropic loci. Findings were replicated in independent association studies (55,789 cases, 330,490 controls). We identified a novel pleiotropic association at 1q22 involving breast and lung squamous cell carcinoma, with eQTL analysis showing an association with ADAM15/THBS3 gene expression in lung. We also identified a known breast cancer locus CASP8/ALS2CR12 associated with prostate cancer, a known cancer locus at CDKN2B-AS1 with different variants associated with lung adenocarcinoma and prostate cancer and confirmed the associations of a breast BRCA2 locus with lung and serous ovarian cancer. This is the largest study to date examining pleiotropy across multiple cancer-associated loci, identifying common mechanisms of cancer development and progression. PMID:27197191
Conditional Selection of Genomic Alterations Dictates Cancer Evolution and Oncogenic Dependencies.

Science.gov (United States)

Mina, Marco; Raynaud, Franck; Tavernari, Daniele; Battistello, Elena; Sungalee, Stephanie; Saghafinia, Sadegh; Laessle, Titouan; Sanchez-Vega, Francisco; Schultz, Nikolaus; Oricchio, Elisa; Ciriello, Giovanni

2017-08-14

Cancer evolves through the emergence and selection of molecular alterations. Cancer genome profiling has revealed that specific events are more or less likely to be co-selected, suggesting that the selection of one event depends on the others. However, the nature of these evolutionary dependencies and their impact remain unclear. Here, we designed SELECT, an algorithmic approach to systematically identify evolutionary dependencies from alteration patterns. By analyzing 6,456 genomes from multiple tumor types, we constructed a map of oncogenic dependencies associated with cellular pathways, transcriptional readouts, and therapeutic response. Finally, modeling of cancer evolution shows that alteration dependencies emerge only under conditional selection. These results provide a framework for the design of strategies to predict cancer progression and therapeutic response. Copyright © 2017 Elsevier Inc. All rights reserved.
Identifying driver mutations in sequenced cancer genomes

DEFF Research Database (Denmark)

Raphael, Benjamin J; Dobson, Jason R; Oesper, Layla

2014-01-01

High-throughput DNA sequencing is revolutionizing the study of cancer and enabling the measurement of the somatic mutations that drive cancer development. However, the resulting sequencing datasets are large and complex, obscuring the clinically important mutations in a background of errors, nois...... patterns of mutual exclusivity. These techniques, coupled with advances in high-throughput DNA sequencing, are enabling precision medicine approaches to the diagnosis and treatment of cancer....
Genomic and Functional Approaches to Understanding Cancer Aneuploidy

NARCIS (Netherlands)

Taylor, Alison M.; Shih, Juliann; Ha, Gavin; Gao, Galen F.; Zhang, Xiaoyang; Berger, Ashton C.; Schumacher, Steven E.; Wang, Chen; Hu, Hai; Liu, Jianfang; Lazar, Alexander J.; Caesar-Johnson, Samantha J.; Demchok, John A.; Felau, Ina; Kasapi, Melpomeni; Ferguson, Martin L.; Hutter, Carolyn M.; Sofia, Heidi J.; Tarnuzzer, Roy; Wang, Zhining; Yang, Liming; Zenklusen, Jean C.; Zhang, Jiashan (Julia); Chudamani, Sudha; Liu, Jia; Lolla, Laxmi; Naresh, Rashi; Pihl, Todd; Sun, Qiang; Wan, Yunhu; Wu, Ye; Cho, Juok; DeFreitas, Timothy; Frazer, Scott; Gehlenborg, Nils; Getz, Gad; Heiman, David I.; Kim, Jaegil; Lawrence, Michael S.; Lin, Pei; Meier, Sam; Noble, Michael S.; Saksena, Gordon; Voet, Doug; Zhang, Hailei; Bernard, Brady; Chambwe, Nyasha; Dhankani, Varsha; Knijnenburg, Theo; Kramer, Roger; Leinonen, Kalle; Liu, Yuexin; Miller, Michael; Reynolds, Sheila; Shmulevich, Ilya; Thorsson, Vesteinn; Zhang, Wei; Akbani, Rehan; Broom, Bradley M.; Hegde, Apurva M.; Ju, Zhenlin; Kanchi, Rupa S.; Korkut, Anil; Li, Jun; Liang, Han; Ling, Shiyun; Liu, Wenbin; Lu, Yiling; Mills, Gordon B.; Ng, Kwok Shing; Rao, Arvind; Ryan, Michael; Wang, Jing; Weinstein, John N.; Zhang, Jiexin; Abeshouse, Adam; Armenia, Joshua; Chakravarty, Debyani; Chatila, Walid K.; de Bruijn, Ino; Gao, Jianjiong; Gross, Benjamin E.; Heins, Zachary J.; Kundra, Ritika; La, Konnor; Ladanyi, Marc; Luna, Augustin; Nissan, Moriah G.; Ochoa, Angelica; Phillips, Sarah M.; Reznik, Ed; Sanchez-Vega, Francisco; Sander, Chris; Schultz, Nikolaus; Sheridan, Robert; Sumer, S. Onur; Sun, Yichao; Taylor, Barry S.; Wang, Jioajiao; Zhang, Hongxin; Anur, Pavana; Peto, Myron; Spellman, Paul; Benz, Christopher; Stuart, Joshua M.; Wong, Christopher K.; Yau, Christina; Hayes, D. Neil; Parker, Joel S.; Wilkerson, Matthew D.; Ally, Adrian; Balasundaram, Miruna; Bowlby, Reanne; Brooks, Denise; Carlsen, Rebecca; Chuah, Eric; Dhalla, Noreen; Holt, Robert; Jones, Steven J.M.; Kasaian, Katayoon; Lee, Darlene; Ma, Yussanne; Marra, Marco A.; Mayo, Michael; Moore, Richard A.; Mungall, Andrew J.; Mungall, Karen; Robertson, A. Gordon; Sadeghi, Sara; Schein, Jacqueline E.; Sipahimalani, Payal; Tam, Angela; Thiessen, Nina; Tse, Kane; Wong, Tina; Berger, Ashton C.; Beroukhim, Rameen; Cherniack, Andrew D.; Cibulskis, Carrie; Gabriel, Stacey B.; Gao, Galen F.; Ha, Gavin; Meyerson, Matthew; Schumacher, Steven E.; Shih, Juliann; Kucherlapati, Melanie H.; Kucherlapati, Raju S.; Baylin, Stephen; Cope, Leslie; Danilova, Ludmila; Bootwalla, Moiz S.; Lai, Phillip H.; Maglinte, Dennis T.; Van Den Berg, David J.; Weisenberger, Daniel J.; Auman, J. Todd; Balu, Saianand; Bodenheimer, Tom; Fan, Cheng; Hoadley, Katherine A.; Hoyle, Alan P.; Jefferys, Stuart R.; Jones, Corbin D.; Meng, Shaowu; Mieczkowski, Piotr A.; Mose, Lisle E.; Perou, Amy H.; Perou, Charles M.; Roach, Jeffrey; Shi, Yan; Simons, Janae V.; Skelly, Tara; Soloway, Matthew G.; Tan, Donghui; Veluvolu, Umadevi; Fan, Huihui; Hinoue, Toshinori; Laird, Peter W.; Shen, Hui; Zhou, Wanding; Bellair, Michelle; Chang, Kyle; Covington, Kyle; Creighton, Chad J.; Dinh, Huyen; Doddapaneni, Harsha Vardhan; Donehower, Lawrence A.; Drummond, Jennifer; Gibbs, Richard A.; Glenn, Robert; Hale, Walker; Han, Yi; Hu, Jianhong; Korchina, Viktoriya; Lee, Sandra; Lewis, Lora; Li, Wei; Liu, Xiuping; Morgan, Margaret; Morton, Donna; Muzny, Donna; Santibanez, Jireh; Sheth, Margi; Shinbrot, Eve; Wang, Linghua; Wang, Min; Wheeler, David A.; Xi, Liu; Zhao, Fengmei; Hess, Julian; Appelbaum, Elizabeth L.; Bailey, Matthew; Cordes, Matthew G.; Ding, Li; Fronick, Catrina C.; Fulton, Lucinda A.; Fulton, Robert S.; Kandoth, Cyriac; Mardis, Elaine R.; McLellan, Michael D.; Miller, Christopher A.; Schmidt, Heather K.; Wilson, Richard K.; Crain, Daniel; Curley, Erin; Gardner, Johanna; Lau, Kevin; Mallery, David; Morris, Scott; Paulauskis, Joseph; Penny, Robert; Shelton, Candace; Shelton, Troy; Sherman, Mark; Thompson, Eric; Yena, Peggy; Bowen, Jay; Gastier-Foster, Julie M.; Gerken, Mark; Leraas, Kristen M.; Lichtenberg, Tara M.; Ramirez, Nilsa C.; Wise, Lisa; Zmuda, Erik; Corcoran, Niall; Costello, Tony; Hovens, Christopher; Carvalho, Andre L.; de Carvalho, Ana C.; Fregnani, José H.; Longatto-Filho, Adhemar; Reis, Rui M.; Scapulatempo-Neto, Cristovam; Silveira, Henrique C.S.; Vidal, Daniel O.; Burnette, Andrew; Eschbacher, Jennifer; Hermes, Beth; Noss, Ardene; Singh, Rosy; Anderson, Matthew L.; Castro, Patricia D.; Ittmann, Michael; Huntsman, David; Kohl, Bernard; Le, Xuan; Thorp, Richard; Andry, Chris; Duffy, Elizabeth R.; Lyadov, Vladimir; Paklina, Oxana; Setdikova, Galiya; Shabunin, Alexey; Tavobilov, Mikhail; McPherson, Christopher; Warnick, Ronald; Berkowitz, Ross; Cramer, Daniel; Feltmate, Colleen; Horowitz, Neil; Kibel, Adam; Muto, Michael; Raut, Chandrajit P.; Malykh, Andrei; Barnholtz-Sloan, Jill S.; Barrett, Wendi; Devine, Karen; Fulop, Jordonna; Ostrom, Quinn T.; Shimmel, Kristen; Wolinsky, Yingli; Sloan, Andrew E.; De Rose, Agostino; Giuliante, Felice; Goodman, Marc; Karlan, Beth Y.; Hagedorn, Curt H.; Eckman, John; Harr, Jodi; Myers, Jerome; Tucker, Kelinda; Zach, Leigh Anne; Deyarmin, Brenda; Hu, Hai; Kvecher, Leonid; Larson, Caroline; Mural, Richard J.; Somiari, Stella; Vicha, Ales; Zelinka, Tomas; Bennett, Joseph; Iacocca, Mary; Rabeno, Brenda; Swanson, Patricia; Latour, Mathieu; Lacombe, Louis; Têtu, Bernard; Bergeron, Alain; McGraw, Mary; Staugaitis, Susan M.; Chabot, John; Hibshoosh, Hanina; Sepulveda, Antonia; Su, Tao; Wang, Timothy; Potapova, Olga; Voronina, Olga; Desjardins, Laurence; Mariani, Odette; Roman-Roman, Sergio; Sastre, Xavier; Stern, Marc Henri; Cheng, Feixiong; Signoretti, Sabina; Berchuck, Andrew; Bigner, Darell; Lipp, Eric; Marks, Jeffrey; McCall, Shannon; McLendon, Roger; Secord, Angeles; Sharp, Alexis; Behera, Madhusmita; Brat, Daniel J.; Chen, Amy; Delman, Keith; Force, Seth; Khuri, Fadlo; Magliocca, Kelly; Maithel, Shishir; Olson, Jeffrey J.; Owonikoko, Taofeek; Pickens, Alan; Ramalingam, Suresh; Shin, Dong M.; Sica, Gabriel; Van Meir, Erwin G.; Zhang, Hongzheng; Eijckenboom, Wil; Gillis, Ad; Korpershoek, Esther; Looijenga, Leendert; Oosterhuis, Wolter; Stoop, Hans; van Kessel, Kim E.; Zwarthoff, Ellen C.; Calatozzolo, Chiara; Cuppini, Lucia; Cuzzubbo, Stefania; DiMeco, Francesco; Finocchiaro, Gaetano; Mattei, Luca; Perin, Alessandro; Pollo, Bianca; Chen, Chu; Houck, John; Lohavanichbutr, Pawadee; Hartmann, Arndt; Stoehr, Christine; Stoehr, Robert; Taubert, Helge; Wach, Sven; Wullich, Bernd; Kycler, Witold; Murawa, Dawid; Wiznerowicz, Maciej; Chung, Ki; Edenfield, W. Jeffrey; Martin, Julie; Baudin, Eric; Bubley, Glenn; Bueno, Raphael; De Rienzo, Assunta; Richards, William G.; Kalkanis, Steven; Mikkelsen, Tom; Noushmehr, Houtan; Scarpace, Lisa; Girard, Nicolas; Aymerich, Marta; Campo, Elias; Giné, Eva; Guillermo, Armando López; Van Bang, Nguyen; Hanh, Phan Thi; Phu, Bui Duc; Tang, Yufang; Colman, Howard; Evason, Kimberley; Dottino, Peter R.; Martignetti, John A.; Gabra, Hani; Juhl, Hartmut; Akeredolu, Teniola; Stepa, Serghei; Hoon, Dave; Ahn, Keunsoo; Kang, Koo Jeong; Beuschlein, Felix; Breggia, Anne; Birrer, Michael; Bell, Debra; Borad, Mitesh; Bryce, Alan H.; Castle, Erik; Chandan, Vishal; Cheville, John; Copland, John A.; Farnell, Michael; Flotte, Thomas; Giama, Nasra; Ho, Thai; Kendrick, Michael; Kocher, Jean Pierre; Kopp, Karla; Moser, Catherine; Nagorney, David; O'Brien, Daniel; O'Neill, Brian Patrick; Patel, Tushar; Petersen, Gloria; Que, Florencia; Rivera, Michael; Roberts, Lewis; Smallridge, Robert; Smyrk, Thomas; Stanton, Melissa; Thompson, R. Houston; Torbenson, Michael; Yang, Ju Dong; Zhang, Lizhi; Brimo, Fadi; Ajani, Jaffer A.; Angulo Gonzalez, Ana Maria; Behrens, Carmen; Bondaruk, Jolanta; Broaddus, Russell; Czerniak, Bogdan; Esmaeli, Bita; Fujimoto, Junya; Gershenwald, Jeffrey; Guo, Charles; Lazar, Alexander J.; Logothetis, Christopher; Meric-Bernstam, Funda; Moran, Cesar; Ramondetta, Lois; Rice, David; Sood, Anil; Tamboli, Pheroze; Thompson, Timothy; Troncoso, Patricia; Tsao, Anne; Wistuba, Ignacio; Carter, Candace; Haydu, Lauren; Hersey, Peter; Jakrot, Valerie; Kakavand, Hojabr; Kefford, Richard; Lee, Kenneth; Long, Georgina; Mann, Graham; Quinn, Michael; Saw, Robyn; Scolyer, Richard; Shannon, Kerwin; Spillane, Andrew; Stretch, Jonathan; Synott, Maria; Thompson, John; Wilmott, James; Al-Ahmadie, Hikmat; Chan, Timothy A.; Ghossein, Ronald; Gopalan, Anuradha; Levine, Douglas A.; Reuter, Victor; Singer, Samuel; Singh, Bhuvanesh; Tien, Nguyen Viet; Broudy, Thomas; Mirsaidi, Cyrus; Nair, Praveen; Drwiega, Paul; Miller, Judy; Smith, Jennifer; Zaren, Howard; Park, Joong Won; Hung, Nguyen Phi; Kebebew, Electron; Linehan, W. Marston; Metwalli, Adam R.; Pacak, Karel; Pinto, Peter A.; Schiffman, Mark; Schmidt, Laura S.; Vocke, Cathy D.; Wentzensen, Nicolas; Worrell, Robert; Yang, Hannah; Moncrieff, Marc; Goparaju, Chandra; Melamed, Jonathan; Pass, Harvey; Botnariuc, Natalia; Caraman, Irina; Cernat, Mircea; Chemencedji, Inga; Clipca, Adrian; Doruc, Serghei; Gorincioi, Ghenadie; Mura, Sergiu; Pirtac, Maria; Stancul, Irina; Tcaciuc, Diana; Albert, Monique; Alexopoulou, Iakovina; Arnaout, Angel; Bartlett, John; Engel, Jay; Gilbert, Sebastien; Parfitt, Jeremy; Sekhon, Harman; Thomas, George; Rassl, Doris M.; Rintoul, Robert C.; Bifulco, Carlo; Tamakawa, Raina; Urba, Walter; Hayward, Nicholas; Timmers, Henri; Antenucci, Anna; Facciolo, Francesco; Grazi, Gianluca; Marino, Mirella; Merola, Roberta; de Krijger, Ronald; Gimenez-Roqueplo, Anne Paule; Piché, Alain; Chevalier, Simone; McKercher, Ginette; Birsoy, Kivanc; Barnett, Gene; Brewer, Cathy; Farver, Carol; Naska, Theresa; Pennell, Nathan A.; Raymond, Daniel; Schilero, Cathy; Smolenski, Kathy; Williams, Felicia; Morrison, Carl; Borgia, Jeffrey A.; Liptay, Michael J.; Pool, Mark; Seder, Christopher W.; Junker, Kerstin; Omberg, Larsson; Dinkin, Mikhail; Manikhas, George; Alvaro, Domenico; Bragazzi, Maria Consiglia; Cardinale, Vincenzo; Carpino, Guido; Gaudio, Eugenio; Chesla, David; Cottingham, Sandra; Dubina, Michael; Moiseenko, Fedor; Dhanasekaran, Renumathy; Becker, Karl Friedrich; Janssen, Klaus Peter; Slotta-Huspenina, Julia; Abdel-Rahman, Mohamed H.; Aziz, Dina; Bell, Sue; Cebulla, Colleen M.; Davis, Amy; Duell, Rebecca; Elder, J. Bradley; Hilty, Joe; Kumar, Bahavna; Lang, James; Lehman, Norman L.; Mandt, Randy; Nguyen, Phuong; Pilarski, Robert; Rai, Karan; Schoenfield, Lynn; Senecal, Kelly; Wakely, Paul; Hansen, Paul; Lechan, Ronald; Powers, James; Tischler, Arthur; Grizzle, William E.; Sexton, Katherine C.; Kastl, Alison; Henderson, Joel; Porten, Sima; Waldmann, Jens; Fassnacht, Martin; Asa, Sylvia L.; Schadendorf, Dirk; Couce, Marta; Graefen, Markus; Huland, Hartwig; Sauter, Guido; Schlomm, Thorsten; Simon, Ronald; Tennstedt, Pierre; Olabode, Oluwole; Nelson, Mark; Bathe, Oliver; Carroll, Peter R.; Chan, June M.; Disaia, Philip; Glenn, Pat; Kelley, Robin K.; Landen, Charles N.; Phillips, Joanna; Prados, Michael; Simko, Jeffry; Smith-McCune, Karen; VandenBerg, Scott; Roggin, Kevin; Fehrenbach, Ashley; Kendler, Ady; Sifri, Suzanne; Steele, Ruth; Jimeno, Antonio; Carey, Francis; Forgie, Ian; Mannelli, Massimo; Carney, Michael; Hernandez, Brenda; Campos, Benito; Herold-Mende, Christel; Jungk, Christin; Unterberg, Andreas; von Deimling, Andreas; Bossler, Aaron; Galbraith, Joseph; Jacobus, Laura; Knudson, Michael; Knutson, Tina; Ma, Deqin; Milhem, Mohammed; Sigmund, Rita; Godwin, Andrew K.; Madan, Rashna; Rosenthal, Howard G.; Adebamowo, Clement; Adebamowo, Sally N.; Boussioutas, Alex; Beer, David; Giordano, Thomas; Mes-Masson, Anne Marie; Saad, Fred; Bocklage, Therese; Landrum, Lisa; Mannel, Robert; Moore, Kathleen; Moxley, Katherine; Postier, Russel; Walker, Joan; Zuna, Rosemary; Feldman, Michael; Valdivieso, Federico; Dhir, Rajiv; Luketich, James; Mora Pinero, Edna M.; Quintero-Aguilo, Mario; Carlotti, Carlos Gilberto; Dos Santos, Jose Sebastião; Kemp, Rafael; Sankarankuty, Ajith; Tirapelli, Daniela; Catto, James; Agnew, Kathy; Swisher, Elizabeth; Creaney, Jenette; Robinson, Bruce; Shelley, Carl Simon; Godwin, Eryn M.; Kendall, Sara; Shipman, Cassaundra; Bradford, Carol; Carey, Thomas; Haddad, Andrea; Moyer, Jeffey; Peterson, Lisa; Prince, Mark; Rozek, Laura; Wolf, Gregory; Bowman, Rayleen; Fong, Kwun M.; Yang, Ian; Korst, Robert; Rathmell, W. Kimryn; Fantacone-Campbell, J. Leigh; Hooke, Jeffrey A.; Kovatich, Albert J.; Shriver, Craig D.; DiPersio, John; Drake, Bettina; Govindan, Ramaswamy; Heath, Sharon; Ley, Timothy; Van Tine, Brian; Westervelt, Peter; Rubin, Mark A.; Lee, Jung Il; Aredes, Natália D.; Mariamidze, Armaz; Cherniack, Andrew D.; Beroukhim, Rameen; Meyerson, Matthew

2018-01-01

Aneuploidy, whole chromosome or chromosome arm imbalance, is a near-universal characteristic of human cancers. In 10,522 cancer genomes from The Cancer Genome Atlas, aneuploidy was correlated with TP53 mutation, somatic mutation rate, and expression of proliferation genes. Aneuploidy was
Provision of personalized genomic diagnostic technologies for breast and colorectal cancer: an analysis of patient needs, expectations and priorities.

Science.gov (United States)

Issa, Amalia M; Hutchinson, Janis F; Tufail, Waqas; Fletcher, Erica; Ajike, Roseline; Tenorio, Jose

2011-07-01

Several novel pharmacogenomic diagnostic tests are commercially available for breast and colorectal cancer, and are increasingly being used in clinical practice for improving treatment decisions. However, there is little evidence evaluating the value of these new genomic technologies from the perspective of patients. As part of an ongoing effort to understand the continuum of the process of adoption of genomic diagnostics, our aim in this study was to examine the value of genomic diagnostics to breast and colorectal cancer patients, and their willingness to adopt and use genomic diagnostics. We conducted six focus groups of breast and colorectal cancer patients from the oncology clinics at The Methodist Hospital, Houston, TX, USA. An adapted Q-sort instrument was also administered to focus group participants. The majority of breast and colorectal cancer patients are interested in using novel genomic diagnostics for deciding about treatment options. Most participants in our study expressed a willingness to pay out-of-pocket for genomic testing (z = 0.736). Reliability and validity of genomic testing were of significant concern (z = 1.32) for the majority of breast and colorectal cancer patients. Participants identified several facilitators and barriers within health systems that might either facilitate or impede the widespread adoption and use of genomic diagnostics in healthcare delivery. This study demonstrates breast and colorectal cancer patients' willingness to adopt and pay for novel genomic diagnostics, as well as identifies several salient factors associated with patient preferences for genomic diagnostics.
Translating the cancer genome: Going beyond p values

Energy Technology Data Exchange (ETDEWEB)

Chin, Lynda; Chin, Lynda; Gray, Joe W.

2008-04-03

Cancer cells are endowed with diverse biological capabilities driven by myriad inherited and somatic genetic and epigenetic aberrations that commandeer key cancer-relevant pathways. Efforts to elucidate these aberrations began with Boveri's hypothesis of aberrant mitoses causing cancer and continue today with a suite of powerful high-resolution technologies that enable detailed catalogues of genomic aberrations and epigenomic modifications. Tomorrow will likely bring the complete atlas of reversible and irreversible alteration in individual cancers. The challenge now is to discern causal molecular abnormalities from genomic and epigenomic 'noise', to understand how the ensemble of these aberrations collaborate to drive cancer pathophysiology. Here, we highlight lessons learned from now classical examples of successful translation of genomic discoveries into clinical practice, lessons that may be used to guide and accelerate translation of emerging genomic insights into practical clinical endpoints that can impact on practice of cancer medicine.
Cross-Cancer Genome-Wide Analysis of Lung, Ovary, Breast, Prostate, and Colorectal Cancer Reveals Novel Pleiotropic Associations.

Science.gov (United States)

Fehringer, Gordon; Kraft, Peter; Pharoah, Paul D; Eeles, Rosalind A; Chatterjee, Nilanjan; Schumacher, Fredrick R; Schildkraut, Joellen M; Lindström, Sara; Brennan, Paul; Bickeböller, Heike; Houlston, Richard S; Landi, Maria Teresa; Caporaso, Neil; Risch, Angela; Amin Al Olama, Ali; Berndt, Sonja I; Giovannucci, Edward L; Grönberg, Henrik; Kote-Jarai, Zsofia; Ma, Jing; Muir, Kenneth; Stampfer, Meir J; Stevens, Victoria L; Wiklund, Fredrik; Willett, Walter C; Goode, Ellen L; Permuth, Jennifer B; Risch, Harvey A; Reid, Brett M; Bezieau, Stephane; Brenner, Hermann; Chan, Andrew T; Chang-Claude, Jenny; Hudson, Thomas J; Kocarnik, Jonathan K; Newcomb, Polly A; Schoen, Robert E; Slattery, Martha L; White, Emily; Adank, Muriel A; Ahsan, Habibul; Aittomäki, Kristiina; Baglietto, Laura; Blomquist, Carl; Canzian, Federico; Czene, Kamila; Dos-Santos-Silva, Isabel; Eliassen, A Heather; Figueroa, Jonine D; Flesch-Janys, Dieter; Fletcher, Olivia; Garcia-Closas, Montserrat; Gaudet, Mia M; Johnson, Nichola; Hall, Per; Hazra, Aditi; Hein, Rebecca; Hofman, Albert; Hopper, John L; Irwanto, Astrid; Johansson, Mattias; Kaaks, Rudolf; Kibriya, Muhammad G; Lichtner, Peter; Liu, Jianjun; Lund, Eiliv; Makalic, Enes; Meindl, Alfons; Müller-Myhsok, Bertram; Muranen, Taru A; Nevanlinna, Heli; Peeters, Petra H; Peto, Julian; Prentice, Ross L; Rahman, Nazneen; Sanchez, Maria Jose; Schmidt, Daniel F; Schmutzler, Rita K; Southey, Melissa C; Tamimi, Rulla; Travis, Ruth C; Turnbull, Clare; Uitterlinden, Andre G; Wang, Zhaoming; Whittemore, Alice S; Yang, Xiaohong R; Zheng, Wei; Buchanan, Daniel D; Casey, Graham; Conti, David V; Edlund, Christopher K; Gallinger, Steven; Haile, Robert W; Jenkins, Mark; Le Marchand, Loïc; Li, Li; Lindor, Noralene M; Schmit, Stephanie L; Thibodeau, Stephen N; Woods, Michael O; Rafnar, Thorunn; Gudmundsson, Julius; Stacey, Simon N; Stefansson, Kari; Sulem, Patrick; Chen, Y Ann; Tyrer, Jonathan P; Christiani, David C; Wei, Yongyue; Shen, Hongbing; Hu, Zhibin; Shu, Xiao-Ou; Shiraishi, Kouya; Takahashi, Atsushi; Bossé, Yohan; Obeidat, Ma'en; Nickle, David; Timens, Wim; Freedman, Matthew L; Li, Qiyuan; Seminara, Daniela; Chanock, Stephen J; Gong, Jian; Peters, Ulrike; Gruber, Stephen B; Amos, Christopher I; Sellers, Thomas A; Easton, Douglas F; Hunter, David J; Haiman, Christopher A; Henderson, Brian E; Hung, Rayjean J

2016-09-01

Identifying genetic variants with pleiotropic associations can uncover common pathways influencing multiple cancers. We took a two-stage approach to conduct genome-wide association studies for lung, ovary, breast, prostate, and colorectal cancer from the GAME-ON/GECCO Network (61,851 cases, 61,820 controls) to identify pleiotropic loci. Findings were replicated in independent association studies (55,789 cases, 330,490 controls). We identified a novel pleiotropic association at 1q22 involving breast and lung squamous cell carcinoma, with eQTL analysis showing an association with ADAM15/THBS3 gene expression in lung. We also identified a known breast cancer locus CASP8/ALS2CR12 associated with prostate cancer, a known cancer locus at CDKN2B-AS1 with different variants associated with lung adenocarcinoma and prostate cancer, and confirmed the associations of a breast BRCA2 locus with lung and serous ovarian cancer. This is the largest study to date examining pleiotropy across multiple cancer-associated loci, identifying common mechanisms of cancer development and progression. Cancer Res; 76(17); 5103-14. ©2016 AACR. ©2016 American Association for Cancer Research.
Genome scale metabolic modeling of cancer

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Nilsson, Avlant; Nielsen, Jens

2017-01-01

of metabolism which allows simulation and hypotheses testing of metabolic strategies. It has successfully been applied to many microorganisms and is now used to study cancer metabolism. Generic models of human metabolism have been reconstructed based on the existence of metabolic genes in the human genome......Cancer cells reprogram metabolism to support rapid proliferation and survival. Energy metabolism is particularly important for growth and genes encoding enzymes involved in energy metabolism are frequently altered in cancer cells. A genome scale metabolic model (GEM) is a mathematical formalization...
Actomyosin drives cancer cell nuclear dysmorphia and threatens genome stability.

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Takaki, Tohru; Montagner, Marco; Serres, Murielle P; Le Berre, Maël; Russell, Matt; Collinson, Lucy; Szuhai, Karoly; Howell, Michael; Boulton, Simon J; Sahai, Erik; Petronczki, Mark

2017-07-24

Altered nuclear shape is a defining feature of cancer cells. The mechanisms underlying nuclear dysmorphia in cancer remain poorly understood. Here we identify PPP1R12A and PPP1CB, two subunits of the myosin phosphatase complex that antagonizes actomyosin contractility, as proteins safeguarding nuclear integrity. Loss of PPP1R12A or PPP1CB causes nuclear fragmentation, nuclear envelope rupture, nuclear compartment breakdown and genome instability. Pharmacological or genetic inhibition of actomyosin contractility restores nuclear architecture and genome integrity in cells lacking PPP1R12A or PPP1CB. We detect actin filaments at nuclear envelope rupture sites and define the Rho-ROCK pathway as the driver of nuclear damage. Lamin A protects nuclei from the impact of actomyosin activity. Blocking contractility increases nuclear circularity in cultured cancer cells and suppresses deformations of xenograft nuclei in vivo. We conclude that actomyosin contractility is a major determinant of nuclear shape and that unrestrained contractility causes nuclear dysmorphia, nuclear envelope rupture and genome instability.

Distinct high resolution genome profiles of early onset and late onset colorectal cancer integrated with gene expression data identify candidate susceptibility loci

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Merok Marianne A

2010-05-01

Full Text Available Abstract Background Estimates suggest that up to 30% of colorectal cancers (CRC may develop due to an increased genetic risk. The mean age at diagnosis for CRC is about 70 years. Time of disease onset 20 years younger than the mean age is assumed to be indicative of genetic susceptibility. We have compared high resolution tumor genome copy number variation (CNV (Roche NimbleGen, 385 000 oligo CGH array in microsatellite stable (MSS tumors from two age groups, including 23 young at onset patients without known hereditary syndromes and with a median age of 44 years (range: 28-53 and 17 elderly patients with median age 79 years (range: 69-87. Our aim was to identify differences in the tumor genomes between these groups and pinpoint potential susceptibility loci. Integration analysis of CNV and genome wide mRNA expression data, available for the same tumors, was performed to identify a restricted candidate gene list. Results The total fraction of the genome with aberrant copy number, the overall genomic profile and the TP53 mutation spectrum were similar between the two age groups. However, both the number of chromosomal aberrations and the number of breakpoints differed significantly between the groups. Gains of 2q35, 10q21.3-22.1, 10q22.3 and 19q13.2-13.31 and losses from 1p31.3, 1q21.1, 2q21.2, 4p16.1-q28.3, 10p11.1 and 19p12, positions that in total contain more than 500 genes, were found significantly more often in the early onset group as compared to the late onset group. Integration analysis revealed a covariation of DNA copy number at these sites and mRNA expression for 107 of the genes. Seven of these genes, CLC, EIF4E, LTBP4, PLA2G12A, PPAT, RG9MTD2, and ZNF574, had significantly different mRNA expression comparing median expression levels across the transcriptome between the two groups. Conclusions Ten genomic loci, containing more than 500 protein coding genes, are identified as more often altered in tumors from early onset versus late
Pathway and network analysis of cancer genomes

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Creixell, Pau; Reimand, Jueri; Haider, Syed

2015-01-01

Genomic information on tumors from 50 cancer types cataloged by the International Cancer Genome Consortium (ICGC) shows that only a few well-studied driver genes are frequently mutated, in contrast to many infrequently mutated genes that may also contribute to tumor biology. Hence there has been...
Evolution and clinical impact of co-occurring genetic alterations in advanced-stage EGFR-mutant lung cancers. | Office of Cancer Genomics

Science.gov (United States)

A widespread approach to modern cancer therapy is to identify a single oncogenic driver gene and target its mutant-protein product (for example, EGFR-inhibitor treatment in EGFR-mutant lung cancers). However, genetically driven resistance to targeted therapy limits patient survival. Through genomic analysis of 1,122 EGFR-mutant lung cancer cell-free DNA samples and whole-exome analysis of seven longitudinally collected tumor samples from a patient with EGFR-mutant lung cancer, we identified critical co-occurring oncogenic events present in most advanced-stage EGFR-mutant lung cancers.
Genome-Wide Interaction Analyses between Genetic Variants and Alcohol Consumption and Smoking for Risk of Colorectal Cancer.

Directory of Open Access Journals (Sweden)

Jian Gong

2016-10-01

Full Text Available Genome-wide association studies (GWAS have identified many genetic susceptibility loci for colorectal cancer (CRC. However, variants in these loci explain only a small proportion of familial aggregation, and there are likely additional variants that are associated with CRC susceptibility. Genome-wide studies of gene-environment interactions may identify variants that are not detected in GWAS of marginal gene effects. To study this, we conducted a genome-wide analysis for interaction between genetic variants and alcohol consumption and cigarette smoking using data from the Colon Cancer Family Registry (CCFR and the Genetics and Epidemiology of Colorectal Cancer Consortium (GECCO. Interactions were tested using logistic regression. We identified interaction between CRC risk and alcohol consumption and variants in the 9q22.32/HIATL1 (Pinteraction = 1.76×10-8; permuted p-value 3.51x10-8 region. Compared to non-/occasional drinking light to moderate alcohol consumption was associated with a lower risk of colorectal cancer among individuals with rs9409565 CT genotype (OR, 0.82 [95% CI, 0.74-0.91]; P = 2.1×10-4 and TT genotypes (OR,0.62 [95% CI, 0.51-0.75]; P = 1.3×10-6 but not associated among those with the CC genotype (p = 0.059. No genome-wide statistically significant interactions were observed for smoking. If replicated our suggestive finding of a genome-wide significant interaction between genetic variants and alcohol consumption might contribute to understanding colorectal cancer etiology and identifying subpopulations with differential susceptibility to the effect of alcohol on CRC risk.
Break Breast Cancer Addiction by CRISPR/Cas9 Genome Editing.

Science.gov (United States)

Yang, Haitao; Jaeger, MariaLynn; Walker, Averi; Wei, Daniel; Leiker, Katie; Weitao, Tao

2018-01-01

Breast cancer is the leading diagnosed cancer for women globally. Evolution of breast cancer in tumorigenesis, metastasis and treatment resistance appears to be driven by the aberrant gene expression and protein degradation encoded by the cancer genomes. The uncontrolled cancer growth relies on these cellular events, thus constituting the cancerous programs and rendering the addiction towards them. These programs are likely the potential anticancer biomarkers for Personalized Medicine of breast cancer. This review intends to delineate the impact of the CRSPR/Cas-mediated genome editing in identification and validation of these anticancer biomarkers. It reviews the progress in three aspects of CRISPR/Cas9-mediated editing of the breast cancer genomes: Somatic genome editing, transcription and protein degradation addictions.
GWAS meta-analysis and replication identifies three new susceptibility loci for ovarian cancer

Science.gov (United States)

Pharoah, Paul D. P.; Tsai, Ya-Yu; Ramus, Susan J.; Phelan, Catherine M.; Goode, Ellen L.; Lawrenson, Kate; Price, Melissa; Fridley, Brooke L.; Tyrer, Jonathan P.; Shen, Howard; Weber, Rachel; Karevan, Rod; Larson, Melissa C.; Song, Honglin; Tessier, Daniel C.; Bacot, François; Vincent, Daniel; Cunningham, Julie M.; Dennis, Joe; Dicks, Ed; Aben, Katja K.; Anton-Culver, Hoda; Antonenkova, Natalia; Armasu, Sebastian M.; Baglietto, Laura; Bandera, Elisa V.; Beckmann, Matthias W.; Birrer, Michael J.; Bloom, Greg; Bogdanova, Natalia; Brenton, James D.; Brinton, Louise A.; Brooks-Wilson, Angela; Brown, Robert; Butzow, Ralf; Campbell, Ian; Carney, Michael E; Carvalho, Renato S.; Chang-Claude, Jenny; Chen, Y. Anne; Chen, Zhihua; Chow, Wong-Ho; Cicek, Mine S.; Coetzee, Gerhard; Cook, Linda S.; Cramer, Daniel W.; Cybulski, Cezary; Dansonka-Mieszkowska, Agnieszka; Despierre, Evelyn; Doherty, Jennifer A; Dörk, Thilo; du Bois, Andreas; Dürst, Matthias; Eccles, Diana; Edwards, Robert; Ekici, Arif B.; Fasching, Peter A.; Fenstermacher, David; Flanagan, James; Gao, Yu-Tang; Garcia-Closas, Montserrat; Gentry-Maharaj, Aleksandra; Giles, Graham; Gjyshi, Anxhela; Gore, Martin; Gronwald, Jacek; Guo, Qi; Halle, Mari K; Harter, Philipp; Hein, Alexander; Heitz, Florian; Hillemanns, Peter; Hoatlin, Maureen; Høgdall, Estrid; Høgdall, Claus K.; Hosono, Satoyo; Jakubowska, Anna; Jensen, Allan; Kalli, Kimberly R.; Karlan, Beth Y.; Kelemen, Linda E.; Kiemeney, Lambertus A.; Kjaer, Susanne Krüger; Konecny, Gottfried E.; Krakstad, Camilla; Kupryjanczyk, Jolanta; Lambrechts, Diether; Lambrechts, Sandrina; Le, Nhu D.; Lee, Nathan; Lee, Janet; Leminen, Arto; Lim, Boon Kiong; Lissowska, Jolanta; Lubiński, Jan; Lundvall, Lene; Lurie, Galina; Massuger, Leon F.A.G.; Matsuo, Keitaro; McGuire, Valerie; McLaughlin, John R; Menon, Usha; Modugno, Francesmary; Moysich, Kirsten B.; Nakanishi, Toru; Narod, Steven A.; Ness, Roberta B.; Nevanlinna, Heli; Nickels, Stefan; Noushmehr, Houtan; Odunsi, Kunle; Olson, Sara; Orlow, Irene; Paul, James; Pejovic, Tanja; Pelttari, Liisa M; Permuth-Wey, Jenny; Pike, Malcolm C; Poole, Elizabeth M; Qu, Xiaotao; Risch, Harvey A.; Rodriguez-Rodriguez, Lorna; Rossing, Mary Anne; Rudolph, Anja; Runnebaum, Ingo; Rzepecka, Iwona K; Salvesen, Helga B.; Schwaab, Ira; Severi, Gianluca; Shen, Hui; Shridhar, Vijayalakshmi; Shu, Xiao-Ou; Sieh, Weiva; Southey, Melissa C.; Spellman, Paul; Tajima, Kazuo; Teo, Soo-Hwang; Terry, Kathryn L.; Thompson, Pamela J; Timorek, Agnieszka; Tworoger, Shelley S.; van Altena, Anne M.; Berg, David Van Den; Vergote, Ignace; Vierkant, Robert A.; Vitonis, Allison F.; Wang-Gohrke, Shan; Wentzensen, Nicolas; Whittemore, Alice S.; Wik, Elisabeth; Winterhoff, Boris; Woo, Yin Ling; Wu, Anna H; Yang, Hannah P.; Zheng, Wei; Ziogas, Argyrios; Zulkifli, Famida; Goodman, Marc T.; Hall, Per; Easton, Douglas F; Pearce, Celeste L; Berchuck, Andrew; Chenevix-Trench, Georgia; Iversen, Edwin; Monteiro, Alvaro N.A.; Gayther, Simon A.; Schildkraut, Joellen M.; Sellers, Thomas A.

2013-01-01

Genome wide association studies (GWAS) have identified four susceptibility loci for epithelial ovarian cancer (EOC) with another two loci being close to genome-wide significance. We pooled data from a GWAS conducted in North America with another GWAS from the United Kingdom. We selected the top 24,551 SNPs for inclusion on the iCOGS custom genotyping array. Follow-up genotyping was carried out in 18,174 cases and 26,134 controls from 43 studies from the Ovarian Cancer Association Consortium. We validated the two loci at 3q25 and 17q21 previously near genome-wide significance and identified three novel loci associated with risk; two loci associated with all EOC subtypes, at 8q21 (rs11782652, P=5.5×10-9) and 10p12 (rs1243180; P=1.8×10-8), and another locus specific to the serous subtype at 17q12 (rs757210; P=8.1×10-10). An integrated molecular analysis of genes and regulatory regions at these loci provided evidence for functional mechanisms underlying susceptibility that implicates CHMP4C in the pathogenesis of ovarian cancer. PMID:23535730
COMPLEXO: identifying the missing heritability of breast cancer via next generation collaboration.

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Southey, Melissa C; Park, Daniel J; Nguyen-Dumont, Tu; Campbell, Ian; Thompson, Ella; Trainer, Alison H; Chenevix-Trench, Georgia; Simard, Jacques; Dumont, Martine; Soucy, Penny; Thomassen, Mads; Jønson, Lars; Pedersen, Inge S; Hansen, Thomas Vo; Nevanlinna, Heli; Khan, Sofia; Sinilnikova, Olga; Mazoyer, Sylvie; Lesueur, Fabienne; Damiola, Francesca; Schmutzler, Rita; Meindl, Alfons; Hahnen, Eric; Dufault, Michael R; Chris Chan, Tl; Kwong, Ava; Barkardóttir, Rosa; Radice, Paolo; Peterlongo, Paolo; Devilee, Peter; Hilbers, Florentine; Benitez, Javier; Kvist, Anders; Törngren, Therese; Easton, Douglas; Hunter, David; Lindstrom, Sara; Kraft, Peter; Zheng, Wei; Gao, Yu-Tang; Long, Jirong; Ramus, Susan; Feng, Bing-Jian; Weitzel, Jeffrey N; Nathanson, Katherine; Offit, Kenneth; Joseph, Vijai; Robson, Mark; Schrader, Kasmintan; Wang, San; Kim, Yeong C; Lynch, Henry; Snyder, Carrie; Tavtigian, Sean; Neuhausen, Susan; Couch, Fergus J; Goldgar, David E

2013-06-21

Linkage analysis, positional cloning, candidate gene mutation scanning and genome-wide association study approaches have all contributed significantly to our understanding of the underlying genetic architecture of breast cancer. Taken together, these approaches have identified genetic variation that explains approximately 30% of the overall familial risk of breast cancer, implying that more, and likely rarer, genetic susceptibility alleles remain to be discovered.
Genomic Copy Number Dictates a Gene-Independent Cell Response to CRISPR/Cas9 Targeting | Office of Cancer Genomics

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The CRISPR/Cas9 system enables genome editing and somatic cell genetic screens in mammalian cells. We performed genome-scale loss-of-function screens in 33 cancer cell lines to identify genes essential for proliferation/survival and found a strong correlation between increased gene copy number and decreased cell viability after genome editing. Within regions of copy-number gain, CRISPR/Cas9 targeting of both expressed and unexpressed genes, as well as intergenic loci, led to significantly decreased cell proliferation through induction of a G2 cell-cycle arrest.
Childhood Cancer Genomics Gaps and Opportunities - Workshop Summary

Science.gov (United States)

NCI convened a workshop of representative research teams that have been leaders in defining the genomic landscape of childhood cancers to discuss the influence of genomic discoveries on the future of childhood cancer research.
Cross Cancer Genomic Investigation of Inflammation Pathway for Five Common Cancers: Lung, Ovary, Prostate, Breast, and Colorectal Cancer.

Science.gov (United States)

Hung, Rayjean J; Ulrich, Cornelia M; Goode, Ellen L; Brhane, Yonathan; Muir, Kenneth; Chan, Andrew T; Marchand, Loic Le; Schildkraut, Joellen; Witte, John S; Eeles, Rosalind; Boffetta, Paolo; Spitz, Margaret R; Poirier, Julia G; Rider, David N; Fridley, Brooke L; Chen, Zhihua; Haiman, Christopher; Schumacher, Fredrick; Easton, Douglas F; Landi, Maria Teresa; Brennan, Paul; Houlston, Richard; Christiani, David C; Field, John K; Bickeböller, Heike; Risch, Angela; Kote-Jarai, Zsofia; Wiklund, Fredrik; Grönberg, Henrik; Chanock, Stephen; Berndt, Sonja I; Kraft, Peter; Lindström, Sara; Al Olama, Ali Amin; Song, Honglin; Phelan, Catherine; Wentzensen, Nicholas; Peters, Ulrike; Slattery, Martha L; Sellers, Thomas A; Casey, Graham; Gruber, Stephen B; Hunter, David J; Amos, Christopher I; Henderson, Brian

2015-11-01

Inflammation has been hypothesized to increase the risk of cancer development as an initiator or promoter, yet no large-scale study of inherited variation across cancer sites has been conducted. We conducted a cross-cancer genomic analysis for the inflammation pathway based on 48 genome-wide association studies within the National Cancer Institute GAME-ON Network across five common cancer sites, with a total of 64 591 cancer patients and 74 467 control patients. Subset-based meta-analysis was used to account for possible disease heterogeneity, and hierarchical modeling was employed to estimate the effect of the subcomponents within the inflammation pathway. The network was visualized by enrichment map. All statistical tests were two-sided. We identified three pleiotropic loci within the inflammation pathway, including one novel locus in Ch12q24 encoding SH2B3 (rs3184504), which reached GWAS significance with a P value of 1.78 x 10(-8), and it showed an association with lung cancer (P = 2.01 x 10(-6)), colorectal cancer (GECCO P = 6.72x10(-6); CORECT P = 3.32x10(-5)), and breast cancer (P = .009). We also identified five key subpathway components with genetic variants that are relevant for the risk of these five cancer sites: inflammatory response for colorectal cancer (P = .006), inflammation related cell cycle gene for lung cancer (P = 1.35x10(-6)), and activation of immune response for ovarian cancer (P = .009). In addition, sequence variations in immune system development played a role in breast cancer etiology (P = .001) and innate immune response was involved in the risk of both colorectal (P = .022) and ovarian cancer (P = .003). Genetic variations in inflammation and its related subpathway components are keys to the development of lung, colorectal, ovary, and breast cancer, including SH2B3, which is associated with lung, colorectal, and breast cancer. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e
Comprehensive Genomic Profiling Facilitates Implementation of the National Comprehensive Cancer Network Guidelines for Lung Cancer Biomarker Testing and Identifies Patients Who May Benefit From Enrollment in Mechanism-Driven Clinical Trials.

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Suh, James H; Johnson, Adrienne; Albacker, Lee; Wang, Kai; Chmielecki, Juliann; Frampton, Garrett; Gay, Laurie; Elvin, Julia A; Vergilio, Jo-Anne; Ali, Siraj; Miller, Vincent A; Stephens, Philip J; Ross, Jeffrey S

2016-06-01

The National Comprehensive Cancer Network (NCCN) guidelines for patients with metastatic non-small cell lung cancer (NSCLC) recommend testing for EGFR, BRAF, ERBB2, and MET mutations; ALK, ROS1, and RET rearrangements; and MET amplification. We investigated the feasibility and utility of comprehensive genomic profiling (CGP), a hybrid capture-based next-generation sequencing (NGS) test, in clinical practice. CGP was performed to a mean coverage depth of 576× on 6,832 consecutive cases of NSCLC (2012-2015). Genomic alterations (GAs) (point mutations, small indels, copy number changes, and rearrangements) involving EGFR, ALK, BRAF, ERBB2, MET, ROS1, RET, and KRAS were recorded. We also evaluated lung adenocarcinoma (AD) cases without GAs, involving these eight genes. The median age of the patients was 64 years (range: 13-88 years) and 53% were female. Among the patients studied, 4,876 (71%) harbored at least one GA involving EGFR (20%), ALK (4.1%), BRAF (5.7%), ERBB2 (6.0%), MET (5.6%), ROS1 (1.5%), RET (2.4%), or KRAS (32%). In the remaining cohort of lung AD without these known drivers, 273 cancer-related genes were altered in at least 0.1% of cases, including STK11 (21%), NF1 (13%), MYC (9.8%), RICTOR (6.4%), PIK3CA (5.4%), CDK4 (4.3%), CCND1 (4.0%), BRCA2 (2.5%), NRAS (2.3%), BRCA1 (1.7%), MAP2K1 (1.2%), HRAS (0.7%), NTRK1 (0.7%), and NTRK3 (0.2%). CGP is practical and facilitates implementation of the NCCN guidelines for NSCLC by enabling simultaneous detection of GAs involving all seven driver oncogenes and KRAS. Furthermore, without additional tissue use or cost, CGP identifies patients with "pan-negative" lung AD who may benefit from enrollment in mechanism-driven clinical trials. National Comprehensive Cancer Network guidelines for patients with metastatic non-small cell lung cancer (NSCLC) recommend testing for several genomic alterations (GAs). The feasibility and utility of comprehensive genomic profiling were studied in NSCLC and in lung adenocarcinoma
Pan-cancer analysis of genomic scar signatures associated with homologous recombination deficiency suggests novel indications for existing cancer drugs

DEFF Research Database (Denmark)

Marquard, Andrea Marion; Eklund, Aron Charles; Joshi, Tejal

2015-01-01

Ovarian and triple-negative breast cancers with BRCA1 or BRCA2 loss are highly sensitive to treatment with PARP inhibitors and platinum-based cytotoxic agents and show an accumulation of genomic scars in the form of gross DNA copy number aberrations. Cancers without BRCA1 or BRCA2 loss...... but with accumulation of similar genomic scars also show increased sensitivity to platinum-based chemotherapy. Therefore, reliable biomarkers to identify DNA repair-deficient cancers prior to treatment may be useful for directing patients to platinum chemotherapy and possibly PARP inhibitors. Recently, three SNP array...... may be strong candidates for clinical trials with PARP inhibitors or platinum-based chemotherapeutic regimens....
Identification of candidate new cancer susceptibility genes using yeast genomics

International Nuclear Information System (INIS)

Brown, M.; Brown, J.A.; Game, J.C.

2003-01-01

A large proportion of cancer susceptibility syndromes are the result of mutations in genes in DNA repair or in cell-cycle checkpoints in response to DNA damage, such as ataxia telangiectasia (AT), Fanconi's anemia (FA), Bloom's syndrome (BS), Nijmegen breakage syndrome (NBS), and xeroderma pigmentosum (XP). Mutations in these genes often cause gross chromosomal instability leading to an increased mutation rate of all genes including those directly responsible for cancer. We have proposed that because the orthologs of these genes in budding yeast, S. cerevisiae, confer protection against killing by DNA damaging agents it should be possible to identify new cancer susceptibility genes by identifying yeast genes whose deletion causes sensitivity to DNA damage. We therefore screened the recently completed collection of individual gene deletion mutants to identify genes that affect sensitivity to DNA-damaging agents. Screening for sensitivity in this obtained up to now with the F98 glioma model othe fact that each deleted gene is replaced by a cassette containing two molecular 'barcodes', or 20-mers, that uniquely identify the strain when DNA from a pool of strains is hybridized to an oligonucleotide array containing the complementary sequences of the barcodes. We performed the screen with UV, IR, H 2 0 2 and other DNA damaging agents. In addition to identifying genes already known to confer resistance to DNA damaging agents we have identified, and individually confirmed, several genes not previously associated with resistance. Several of these are of unknown function. We have also examined the chromosomal stability of selected strains and found that IR sensitive strains often but not always exhibit genomic instability. We are presently constructing a yeast artificial chromosome to globally interrogate all the genes in the deletion pool for their involvement in genomic stability. This work shows that budding yeast is a valuable eukaryotic model organism to identify
Recurrent targeted genes of hepatitis B virus in the liver cancer genomes identified by a next-generation sequencing-based approach.

Directory of Open Access Journals (Sweden)

Dong Ding

Full Text Available Integration of the viral DNA into host chromosomes was found in most of the hepatitis B virus (HBV-related hepatocellular carcinomas (HCCs. Here we devised a massive anchored parallel sequencing (MAPS method using next-generation sequencing to isolate and sequence HBV integrants. Applying MAPS to 40 pairs of HBV-related HCC tissues (cancer and adjacent tissues, we identified 296 HBV integration events corresponding to 286 unique integration sites (UISs with precise HBV-Human DNA junctions. HBV integration favored chromosome 17 and preferentially integrated into human transcript units. HBV targeted genes were enriched in GO terms: cAMP metabolic processes, T cell differentiation and activation, TGF beta receptor pathway, ncRNA catabolic process, and dsRNA fragmentation and cellular response to dsRNA. The HBV targeted genes include 7 genes (PTPRJ, CNTN6, IL12B, MYOM1, FNDC3B, LRFN2, FN1 containing IPR003961 (Fibronectin, type III domain, 7 genes (NRG3, MASP2, NELL1, LRP1B, ADAM21, NRXN1, FN1 containing IPR013032 (EGF-like region, conserved site, and three genes (PDE7A, PDE4B, PDE11A containing IPR002073 (3', 5'-cyclic-nucleotide phosphodiesterase. Enriched pathways include hsa04512 (ECM-receptor interaction, hsa04510 (Focal adhesion, and hsa04012 (ErbB signaling pathway. Fewer integration events were found in cancers compared to cancer-adjacent tissues, suggesting a clonal expansion model in HCC development. Finally, we identified 8 genes that were recurrent target genes by HBV integration including fibronectin 1 (FN1 and telomerase reverse transcriptase (TERT1, two known recurrent target genes, and additional novel target genes such as SMAD family member 5 (SMAD5, phosphatase and actin regulator 4 (PHACTR4, and RNA binding protein fox-1 homolog (C. elegans 1 (RBFOX1. Integrating analysis with recently published whole-genome sequencing analysis, we identified 14 additional recurrent HBV target genes, greatly expanding the HBV recurrent target list
NMD Microarray Analysis for Rapid Genome-Wide Screen of Mutated Genes in Cancer

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Maija Wolf

2005-01-01

Full Text Available Gene mutations play a critical role in cancer development and progression, and their identification offers possibilities for accurate diagnostics and therapeutic targeting. Finding genes undergoing mutations is challenging and slow, even in the post-genomic era. A new approach was recently developed by Noensie and Dietz to prioritize and focus the search, making use of nonsense-mediated mRNA decay (NMD inhibition and microarray analysis (NMD microarrays in the identification of transcripts containing nonsense mutations. We combined NMD microarrays with array-based CGH (comparative genomic hybridization in order to identify inactivation of tumor suppressor genes in cancer. Such a “mutatomics” screening of prostate cancer cell lines led to the identification of inactivating mutations in the EPHB2 gene. Up to 8% of metastatic uncultured prostate cancers also showed mutations of this gene whose loss of function may confer loss of tissue architecture. NMD microarray analysis could turn out to be a powerful research method to identify novel mutated genes in cancer cell lines, providing targets that could then be further investigated for their clinical relevance and therapeutic potential.
A genome-wide association study for colorectal cancer identifies a risk locus in 14q23.1

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Loo, Lenora W.M.; Zaidi, Syed H.E.; Wang, Hansong; Berndt, Sonja I.; Bézieau, Stéphane; Brenner, Hermann; Campbell, Peter T.; Chan, Andrew T.; Chang-Claude, Jenny; Du, Mengmeng; Edlund, Christopher K.; Gallinger, Steven; Haile, Robert W.; Harrison, Tabitha A.; Hoffmeister, Michael; Hopper, John L.; Hou, Lifang; Hsu, Li; Jacobs, Eric J.; Jenkins, Mark A.; Jeon, Jihyoun; Küry, Sébastien; Li, Li; Lindor, Noralane M.; Newcomb, Polly A.; Potter, John D.; Rennert, Gad; Rudolph, Anja; Schoen, Robert E.; Schumacher, Fredrick R.; Seminara, Daniela; Severi, Gianluca; Slattery, Martha L.; White, Emily; Woods, Michael O.; Cotterchio, Michelle; Marchand, Loic Le; Casey, Graham; Gruber, Steven B.; Peters, Ulrike; Hudson, Thomas J.

2015-01-01

Over 50 loci associated with colorectal cancer (CRC) have been uncovered by genome-wide association studies (GWAS). Identifying additional loci has the potential to help elucidate aspects of the underlying biological processes leading to better understanding of the pathogenesis of the disease. We re-evaluated a GWAS by excluding controls that have family history of CRC or personal history of CR polyps, as we hypothesized that their inclusion reduces power to detect associations. This is supported empirically and through simulations. Two-phase GWAS analysis was performed in a total of 16,517 cases and 14,487 controls. We identified rs17094983, a SNP associated with risk of CRC (p=2.5×10−10; odds ratio estimated by re-including all controls (OR)=0.87, 95% confidence interval (CI): 0.83–0.91; minor allele frequency (MAF)=13%). Results were replicated in samples of African descent (1,894 cases and 4,703 controls; p=0.01; OR=0.86, 95% CI: 0.77–0.97; MAF=16%). Gene expression data in 195 colon adenocarcinomas and 59 normal colon tissues from two different studies revealed that this locus has genotypes that are associated with RTN1 (Reticulon 1) expression (p=0.001), a protein-coding gene involved in survival and proliferation of cancer cells that is highly expressed in normal colon tissues but has significantly reduced expression in tumor cells (p=1.3×10−8). PMID:26404086
Applications of Support Vector Machine (SVM) Learning in Cancer Genomics.

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Huang, Shujun; Cai, Nianguang; Pacheco, Pedro Penzuti; Narrandes, Shavira; Wang, Yang; Xu, Wayne

2018-01-01

Machine learning with maximization (support) of separating margin (vector), called support vector machine (SVM) learning, is a powerful classification tool that has been used for cancer genomic classification or subtyping. Today, as advancements in high-throughput technologies lead to production of large amounts of genomic and epigenomic data, the classification feature of SVMs is expanding its use in cancer genomics, leading to the discovery of new biomarkers, new drug targets, and a better understanding of cancer driver genes. Herein we reviewed the recent progress of SVMs in cancer genomic studies. We intend to comprehend the strength of the SVM learning and its future perspective in cancer genomic applications. Copyright© 2018, International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved.
Distinct p53 genomic binding patterns in normal and cancer-derived human cells

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Botcheva K.; McCorkle S. R.; McCombie W. R.; Dunn J. J.; Anderson C. W.

2011-12-15

We report here genome-wide analysis of the tumor suppressor p53 binding sites in normal human cells. 743 high-confidence ChIP-seq peaks representing putative genomic binding sites were identified in normal IMR90 fibroblasts using a reference chromatin sample. More than 40% were located within 2 kb of a transcription start site (TSS), a distribution similar to that documented for individually studied, functional p53 binding sites and, to date, not observed by previous p53 genome-wide studies. Nearly half of the high-confidence binding sites in the IMR90 cells reside in CpG islands, in marked contrast to sites reported in cancer-derived cells. The distinct genomic features of the IMR90 binding sites do not reflect a distinct preference for specific sequences, since the de novo developed p53 motif based on our study is similar to those reported by genome-wide studies of cancer cells. More likely, the different chromatin landscape in normal, compared with cancer-derived cells, influences p53 binding via modulating availability of the sites. We compared the IMR90 ChIPseq peaks to the recently published IMR90 methylome1 and demonstrated that they are enriched at hypomethylated DNA. Our study represents the first genome-wide, de novo mapping of p53 binding sites in normal human cells and reveals that p53 binding sites reside in distinct genomic landscapes in normal and cancer-derived human cells.
Genome-Wide Interaction Analyses between Genetic Variants and Alcohol Consumption and Smoking for Risk of Colorectal Cancer

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Newcomb, Polly A.; Campbell, Peter T.; Baron, John A.; Berndt, Sonja I.; Bezieau, Stephane; Brenner, Hermann; Casey, Graham; Chan, Andrew T.; Chang-Claude, Jenny; Du, Mengmeng; Figueiredo, Jane C.; Gallinger, Steven; Giovannucci, Edward L.; Haile, Robert W.; Harrison, Tabitha A.; Hayes, Richard B.; Hoffmeister, Michael; Hopper, John L.; Hudson, Thomas J.; Jeon, Jihyoun; Jenkins, Mark A.; Küry, Sébastien; Le Marchand, Loic; Lin, Yi; Lindor, Noralane M.; Nishihara, Reiko; Ogino, Shuji; Potter, John D.; Rudolph, Anja; Schoen, Robert E.; Seminara, Daniela; Slattery, Martha L.; Thibodeau, Stephen N.; Thornquist, Mark; Toth, Reka; Wallace, Robert; White, Emily; Jiao, Shuo; Lemire, Mathieu; Hsu, Li; Peters, Ulrike

2016-01-01

Genome-wide association studies (GWAS) have identified many genetic susceptibility loci for colorectal cancer (CRC). However, variants in these loci explain only a small proportion of familial aggregation, and there are likely additional variants that are associated with CRC susceptibility. Genome-wide studies of gene-environment interactions may identify variants that are not detected in GWAS of marginal gene effects. To study this, we conducted a genome-wide analysis for interaction between genetic variants and alcohol consumption and cigarette smoking using data from the Colon Cancer Family Registry (CCFR) and the Genetics and Epidemiology of Colorectal Cancer Consortium (GECCO). Interactions were tested using logistic regression. We identified interaction between CRC risk and alcohol consumption and variants in the 9q22.32/HIATL1 (Pinteraction = 1.76×10−8; permuted p-value 3.51x10-8) region. Compared to non-/occasional drinking light to moderate alcohol consumption was associated with a lower risk of colorectal cancer among individuals with rs9409565 CT genotype (OR, 0.82 [95% CI, 0.74–0.91]; P = 2.1×10−4) and TT genotypes (OR,0.62 [95% CI, 0.51–0.75]; P = 1.3×10−6) but not associated among those with the CC genotype (p = 0.059). No genome-wide statistically significant interactions were observed for smoking. If replicated our suggestive finding of a genome-wide significant interaction between genetic variants and alcohol consumption might contribute to understanding colorectal cancer etiology and identifying subpopulations with differential susceptibility to the effect of alcohol on CRC risk. PMID:27723779
The Integrative Method Based on the Module-Network for Identifying Driver Genes in Cancer Subtypes

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Xinguo Lu

2018-01-01

Full Text Available With advances in next-generation sequencing(NGS technologies, a large number of multiple types of high-throughput genomics data are available. A great challenge in exploring cancer progression is to identify the driver genes from the variant genes by analyzing and integrating multi-types genomics data. Breast cancer is known as a heterogeneous disease. The identification of subtype-specific driver genes is critical to guide the diagnosis, assessment of prognosis and treatment of breast cancer. We developed an integrated frame based on gene expression profiles and copy number variation (CNV data to identify breast cancer subtype-specific driver genes. In this frame, we employed statistical machine-learning method to select gene subsets and utilized an module-network analysis method to identify potential candidate driver genes. The final subtype-specific driver genes were acquired by paired-wise comparison in subtypes. To validate specificity of the driver genes, the gene expression data of these genes were applied to classify the patient samples with 10-fold cross validation and the enrichment analysis were also conducted on the identified driver genes. The experimental results show that the proposed integrative method can identify the potential driver genes and the classifier with these genes acquired better performance than with genes identified by other methods.

Modifiers of notch transcriptional activity identified by genome-wide RNAi

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Firnhaber Christopher B

2010-10-01

Full Text Available Abstract Background The Notch signaling pathway regulates a diverse array of developmental processes, and aberrant Notch signaling can lead to diseases, including cancer. To obtain a more comprehensive understanding of the genetic network that integrates into Notch signaling, we performed a genome-wide RNAi screen in Drosophila cell culture to identify genes that modify Notch-dependent transcription. Results Employing complementary data analyses, we found 399 putative modifiers: 189 promoting and 210 antagonizing Notch activated transcription. These modifiers included several known Notch interactors, validating the robustness of the assay. Many novel modifiers were also identified, covering a range of cellular localizations from the extracellular matrix to the nucleus, as well as a large number of proteins with unknown function. Chromatin-modifying proteins represent a major class of genes identified, including histone deacetylase and demethylase complex components and other chromatin modifying, remodeling and replacement factors. A protein-protein interaction map of the Notch-dependent transcription modifiers revealed that a large number of the identified proteins interact physically with these core chromatin components. Conclusions The genome-wide RNAi screen identified many genes that can modulate Notch transcriptional output. A protein interaction map of the identified genes highlighted a network of chromatin-modifying enzymes and remodelers that regulate Notch transcription. Our results open new avenues to explore the mechanisms of Notch signal regulation and the integration of this pathway into diverse cellular processes.
Genome-wide association studies in bladder cancer: first results and potential relevance.

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Kiemeney, Lambertus A; Grotenhuis, Anne J; Vermeulen, Sita H; Wu, Xifeng

2009-09-01

The role of genetic susceptibility in the development of urinary bladder cancer is unclear, as it is in many other types of cancer. Since 2007, however, an innovative research approach (i.e. genome-wide association studies or GWASs) has led to the identification of numerous genomic loci that harbor susceptibility factors for one or more cancer sites. All GWASs have been published in high-impact journals and the strengths of the design are acknowledged by all experts, but there is criticism about the relevance of the results. Late 2008, the first GWAS in bladder cancer was published. In this review, the principles of GWASs are explained, as well as their strengths and limitations. The study in bladder cancer among 4000 cases and 38,000 controls identified three new susceptibility loci at 8q24, 3q28, and 5p15 that increase the risk of bladder cancer by 22, 19, and 16%, respectively. The results of two other GWASs in bladder cancer are expected to appear this year. Joint analysis of the three studies will probably identify additional susceptibility loci. The results of bladder cancer GWASs may point the way to yet unknown disease mechanisms. So far, the findings are not sufficiently discriminative for risk predictions to be used in clinical care or public health.
Genomic analyses identify hundreds of variants associated with age at menarche and support a role for puberty timing in cancer risk

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Day, Felix R; Thompson, Deborah J; Helgason, Hannes

2017-01-01

The timing of puberty is a highly polygenic childhood trait that is epidemiologically associated with various adult diseases. Using 1000 Genomes Project-imputed genotype data in up to ∼370,000 women, we identify 389 independent signals (P ... pubertal development. In Icelandic data, these signals explain ∼7.4% of the population variance in age at menarche, corresponding to ∼25% of the estimated heritability. We implicate ∼250 genes via coding variation or associated expression, demonstrating significant enrichment in neural tissues. Rare...... variants near the imprinted genes MKRN3 and DLK1 were identified, exhibiting large effects when paternally inherited. Mendelian randomization analyses suggest causal inverse associations, independent of body mass index (BMI), between puberty timing and risks for breast and endometrial cancers in women...
Human Cancer Models Initiative | Office of Cancer Genomics

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The Human Cancer Models Initiative (HCMI) is an international consortium that is generating novel human tumor-derived culture models, which are annotated with genomic and clinical data. In an effort to advance cancer research and more fully understand how in vitro findings are related to clinical biology, HCMI-developed models and related data will be available as a community resource for cancer research.
Understanding Cancer Genome and Its Evolution by Next Generation Sequencing

DEFF Research Database (Denmark)

Hou, Yong

Cancer will cause 13 million deaths by the year of 2030, ranking the second leading cause of death worldwide. Previous studies indicate that most of the cancers originate from cells that acquired somatic mutations and evolved as Darwin Theory. Ten biological insights of cancer have been summarized...... recently. Cutting-age technologies like next generation sequencing (NGS) enable exploring cancer genome and evolution much more efficiently. However, integrated cancer genome sequencing studies showed great inter-/intra-tumoral heterogeneity (ITH) and complex evolution patterns beyond the cancer biological...... knowledge we previously know. There is very limited knowledge of East Asia lung cancer genome except enrichment of EGFR mutations and lack of KRAS mutations. We carried out integrated genomic, transcriptomic and methylomic analysis of 335 primary Chinese lung adenocarcinomas (LUAD) and 35 corresponding...
Genome-Wide Association Study to Identify Susceptibility Loci That Modify Radiation-Related Risk for Breast Cancer After Childhood Cancer.

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Morton, Lindsay M; Sampson, Joshua N; Armstrong, Gregory T; Chen, Ting-Huei; Hudson, Melissa M; Karlins, Eric; Dagnall, Casey L; Li, Shengchao Alfred; Wilson, Carmen L; Srivastava, Deo Kumar; Liu, Wei; Kang, Guolian; Oeffinger, Kevin C; Henderson, Tara O; Moskowitz, Chaya S; Gibson, Todd M; Merino, Diana M; Wong, Jeannette R; Hammond, Sue; Neglia, Joseph P; Turcotte, Lucie M; Miller, Jeremy; Bowen, Laura; Wheeler, William A; Leisenring, Wendy M; Whitton, John A; Burdette, Laurie; Chung, Charles; Hicks, Belynda D; Jones, Kristine; Machiela, Mitchell J; Vogt, Aurelie; Wang, Zhaoming; Yeager, Meredith; Neale, Geoffrey; Lear, Matthew; Strong, Louise C; Yasui, Yutaka; Stovall, Marilyn; Weathers, Rita E; Smith, Susan A; Howell, Rebecca; Davies, Stella M; Radloff, Gretchen A; Onel, Kenan; Berrington de González, Amy; Inskip, Peter D; Rajaraman, Preetha; Fraumeni, Joseph F; Bhatia, Smita; Chanock, Stephen J; Tucker, Margaret A; Robison, Leslie L

2017-11-01

Childhood cancer survivors treated with chest-directed radiotherapy have substantially elevated risk for developing breast cancer. Although genetic susceptibility to breast cancer in the general population is well studied, large-scale evaluation of breast cancer susceptibility after chest-directed radiotherapy for childhood cancer is lacking. We conducted a genome-wide association study of breast cancer in female survivors of childhood cancer, pooling two cohorts with detailed treatment data and systematic, long-term follow-up: the Childhood Cancer Survivor Study and St. Jude Lifetime Cohort. The study population comprised 207 survivors who developed breast cancer and 2774 who had not developed any subsequent neoplasm as of last follow-up. Genotyping and subsequent imputation yielded 16 958 466 high-quality variants for analysis. We tested associations in the overall population and in subgroups stratified by receipt of lower than 10 and 10 or higher gray breast radiation exposure. We report P values and pooled per-allele risk estimates from Cox proportional hazards regression models. All statistical tests were two-sided. Among survivors who received 10 or higher gray breast radiation exposure, a locus on 1q41 was associated with subsequent breast cancer risk (rs4342822, nearest gene PROX1 , risk allele frequency in control subjects [RAF controls ] = 0.46, hazard ratio = 1.92, 95% confidence interval = 1.49 to 2.44, P = 7.09 × 10 -9 ). Two rare variants also showed potentially promising associations (breast radiation ≥10 gray: rs74949440, 11q23, TAGLN , RAF controls = 0.02, P = 5.84 × 10 -8 ; breast cancer risk after childhood cancer. Published by Oxford University Press 2017. This work is written by US Government employees and is in the public domain in the US.
Characterization of genomic alterations in radiation-associated breast cancer among childhood cancer survivors, using comparative genomic hybridization (CGH arrays.

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Xiaohong R Yang

Full Text Available Ionizing radiation is an established risk factor for breast cancer. Epidemiologic studies of radiation-exposed cohorts have been primarily descriptive; molecular events responsible for the development of radiation-associated breast cancer have not been elucidated. In this study, we used array comparative genomic hybridization (array-CGH to characterize genome-wide copy number changes in breast tumors collected in the Childhood Cancer Survivor Study (CCSS. Array-CGH data were obtained from 32 cases who developed a second primary breast cancer following chest irradiation at early ages for the treatment of their first cancers, mostly Hodgkin lymphoma. The majority of these cases developed breast cancer before age 45 (91%, n = 29, had invasive ductal tumors (81%, n = 26, estrogen receptor (ER-positive staining (68%, n = 19 out of 28, and high proliferation as indicated by high Ki-67 staining (77%, n = 17 out of 22. Genomic regions with low-copy number gains and losses and high-level amplifications were similar to what has been reported in sporadic breast tumors, however, the frequency of amplifications of the 17q12 region containing human epidermal growth factor receptor 2 (HER2 was much higher among CCSS cases (38%, n = 12. Our findings suggest that second primary breast cancers in CCSS were enriched for an "amplifier" genomic subgroup with highly proliferative breast tumors. Future investigation in a larger irradiated cohort will be needed to confirm our findings.
Cancer 2015: a longitudinal whole-of-system study of genomic cancer medicine.

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Thomas, David M; Fox, Stephen; Lorgelly, Paula K; Ashley, David; Richardson, Gary; Lipton, Lara; Parisot, John P; Lucas, Mark; McNeil, John; Wright, Michael

2015-12-01

Genomic cancer medicine promises revolutionary change in oncology. The impacts of 'personalized medicine', based upon a molecular classification of cancer and linked to targeted therapies, will extend from individual patient outcomes to the health economy at large. To address the 'whole-of-system' impact of genomic cancer medicine, we have established a prospective cohort of patients with newly diagnosed cancer in the state of Victoria, Australia, about whom we have collected a broad range of clinical, demographic, molecular, and patient-reported data, as well as data on health resource utilization. Our goal is to create a model for investigating public investment in genomic medicine that maximizes the cost:benefit ratio for the Australian community at large. Copyright © 2015 Elsevier Ltd. All rights reserved.
Common variants associated with breast cancer in genome-wide association studies are modifiers of breast cancer risk in BRCA1 and BRCA2 mutation carriers

NARCIS (Netherlands)

Wang, Xianshu; Pankratz, V. Shane; Fredericksen, Zachary; Tarrell, Robert; Karaus, Mary; McGuffog, Lesley; Pharaoh, Paul D. P.; Ponder, Bruce A. J.; Dunning, Alison M.; Peock, Susan; Cook, Margaret; Oliver, Clare; Frost, Debra; Sinilnikova, Olga M.; Stoppa-Lyonnet, Dominique; Mazoyer, Sylvie; Houdayer, Claude; Hogervorst, Frans B. L.; Hooning, Maartje J.; Ligtenberg, Marjolijn J.; Spurdle, Amanda; Chenevix-Trench, Georgia; Schmutzler, Rita K.; Wappenschmidt, Barbara; Engel, Christoph; Meindl, Alfons; Domchek, Susan M.; Nathanson, Katherine L.; Rebbeck, Timothy R.; Singer, Christian F.; Gschwantler-Kaulich, Daphne; Dressler, Catherina; Fink, Anneliese; Szabo, Csilla I.; Zikan, Michal; Foretova, Lenka; Claes, Kathleen; Thomas, Gilles; Hoover, Robert N.; Hunter, David J.; Chanock, Stephen J.; Easton, Douglas F.; Antoniou, Antonis C.; Couch, Fergus J.; Gregory, Helen; Miedzybrodzka, Zosia; Morrison, Patrick; Cole, Trevor; McKeown, Carole; Taylor, Amy; Donaldson, Alan; Paterson, Joan; Murray, Alexandra; Rogers, Mark; McCann, Emma; Kennedy, John; Barton, David; Porteous, Mary; Brewer, Carole; Kivuva, Emma; Searle, Anne; Goodman, Selina; Davidson, Rosemarie; Murday, Victoria; Bradshaw, Nicola; Snadden, Lesley; Longmuir, Mark; Watt, Catherine; Izatt, Louise; Pichert, Gabriella; Langman, Caroline; Dorkins, Huw; Barwell, Julian; Chu, Carol; Bishop, Tim; Miller, Julie; Ellis, Ian; Evans, D. Gareth; Lalloo, Fiona; Holt, Felicity; Male, Alison; Robinson, Anne; Gardiner, Carol; Douglas, Fiona; Claber, Oonagh; Walker, Lisa; McLeod, Diane; Eeles, Ros; Shanley, Susan; Rahman, Nazneen; Houlston, Richard; Bancroft, Elizabeth; D'Mello, Lucia; Page, Elizabeth; Ardern-Jones, Audrey; Mitra, Anita; Cook, Jackie; Quarrell, Oliver; Bardsley, Cathryn; Hodgson, Shirley; Goff, Sheila; Brice, Glen; Winchester, Lizzie; Eccles, Diana; Lucassen, Anneke; Crawford, Gillian; Tyler, Emma; McBride, Donna; Bérard, Léon; Sinilnikova, Olga; Barjhoux, Laure; Giraud, Sophie; Léone, Mélanie; Gauthier-Villars, Marion; Moncoutier, Virginie; Belotti, Muriel; de Pauw, Antoine; Bressac-de-Paillerets, Brigitte; Remenieras, Audrey; Byrde, Véronique; Caron, Olivier; Lenoir, Gilbert; Bignon, Yves-Jean; Uhrhammer, Nancy; Lasset, Christine; Bonadona, Valérie; Hardouin, Agnès; Berthet, Pascaline; Sobol, Hagay; Bourdon, Violaine; Eisinger, Françoise; Coulet, Florence; Colas, Chrystelle; Soubrier, Florent; Coupier, Isabelle; Payrat, Jean-Philippe; Fournier, Joëlle; Révillion, Françoise; Vennin, Philippe; Adenis, Claude; Rouleau, Etienne; Lidereau, Rosette; Demange, Liliane; Nogues, Catherine; Muller, Danièle; Fricker, Jean-Pierre; Longy, Michel; Sevenet, Nicolas; Toulas, Christine; Guimbaud, Rosine; Gladieff, Laurence; Feillel, Viviane; Leroux, Dominique; Dreyfus, Hélèn; Rebischung, Christine; Cassini, Cécile; Olivier-Faivre, Laurence; Prieur, Fabienne; Ferrer, Sandra Fert; Frénay, Marc; Vénat-Bouvet, Laurence; Lynch, Henry T.; Hogervorst, Frans; Vernhoef, Senno; Pijpe, Anouk; van 't Veer, Laura; van Leeuwen, Flora; Rookus, Matti; Collée, Margriet; van den Ouweland, Ans; Kriege, Mieke; Schutte, Mieke; Hooning, Maartje; Seynaeve, Caroline; van Asperen, Christi; Wijnen, Juul; Vreeswijk, Maaike; Tollenaar, Rob; Devilee, Peter; Ligtenberg, Marjolijn; Hoogerbrugge, Nicoline; Ausems, Margreet; van der Luijt, Rob; Aalfs, Cora; van Os, Theo; Gille, Hans; Waisfisz, Quinten; Meijers-Heijboer, Hanne; Gomez-Garcia, Encarna; van Roozendaal, Kees; Blok, Marinus; Oosterwijk, Jan; van der Hout, Annemieke; Mourits, Marian; Vasen, Hans; Szabo, Csilla; Pohlreich, Petr; Kleibl, Zdenek; Machackova, Eva; Lukesova, Miroslava; de Leeneer, Kim; Poppe, Bruce; de Paepe, Anne

2010-01-01

Recent studies have identified single nucleotide polymorphisms (SNPs) that significantly modify breast cancer risk in BRCA1 and BRCA2 mutation carriers. Since these risk modifiers were originally identified as genetic risk factors for breast cancer in genome-wide association studies (GWASs),
Genome organization, instabilities, stem cells, and cancer

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Senthil Kumar Pazhanisamy

2009-01-01

Full Text Available It is now widely recognized that advances in exploring genome organization provide remarkable insights on the induction and progression of chromosome abnormalities. Much of what we know about how mutations evolve and consequently transform into genome instabilities has been characterized in the spatial organization context of chromatin. Nevertheless, many underlying concepts of impact of the chromatin organization on perpetuation of multiple mutations and on propagation of chromosomal aberrations remain to be investigated in detail. Genesis of genome instabilities from accumulation of multiple mutations that drive tumorigenesis is increasingly becoming a focal theme in cancer studies. This review focuses on structural alterations evolve to raise a variety of genome instabilities that are manifested at the nucleotide, gene or sub-chromosomal, and whole chromosome level of genome. Here we explore an underlying connection between genome instability and cancer in the light of genome architecture. This review is limited to studies directed towards spatial organizational aspects of origin and propagation of aberrations into genetically unstable tumors.
Genome-wide association study for ovarian cancer susceptibility using pooled DNA.

NARCIS (Netherlands)

Lu, Y.; Chen, X.; Beesley, J.; Johnatty, S.E.; Defazio, A.; Lambrechts, S.; Lambrechts, D.; Despierre, E.; Vergotes, I.; Chang-Claude, J.; Hein, R.; Nickels, S.; Wang-Gohrke, S.; Dork, T.; Durst, M.; Antonenkova, N.; Bogdanova, N.; Goodman, M.T.; Lurie, G.; Wilkens, L.R.; Carney, M.E.; Butzow, R.; Nevanlinna, H.; Heikkinen, T.; Leminen, A.; Kiemeney, L.A.L.M.; Massuger, L.F.A.G.; Altena, A.M. van; Aben, K.K.H.; Kjaer, S.K.; Hogdall, E.; Jensen, A.; Brooks-Wilson, A.; Le, N.; Cook, L.; Earp, M.; Kelemen, L.; Easton, D.; Pharoah, P.; Song, H.; Tyrer, J.; Ramus, S.; Menon, U.; Gentry-Maharaj, A.; Gayther, S.A.; Bandera, E.V.; Olson, S.H.; Orlow, I.; Rodriguez-Rodriguez, L.; MacGregor, S.; Chenevix-Trench, G.

2012-01-01

Recent Genome-Wide Association Studies (GWAS) have identified four low-penetrance ovarian cancer susceptibility loci. We hypothesized that further moderate- or low-penetrance variants exist among the subset of single-nucleotide polymorphisms (SNPs) not well tagged by the genotyping arrays used in
Perspectives of Integrative Cancer Genomics in Next Generation Sequencing Era

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So Mee Kwon

2012-06-01

Full Text Available The explosive development of genomics technologies including microarrays and next generation sequencing (NGS has provided comprehensive maps of cancer genomes, including the expression of mRNAs and microRNAs, DNA copy numbers, sequence variations, and epigenetic changes. These genome-wide profiles of the genetic aberrations could reveal the candidates for diagnostic and/or prognostic biomarkers as well as mechanistic insights into tumor development and progression. Recent efforts to establish the huge cancer genome compendium and integrative omics analyses, so-called "integromics", have extended our understanding on the cancer genome, showing its daunting complexity and heterogeneity. However, the challenges of the structured integration, sharing, and interpretation of the big omics data still remain to be resolved. Here, we review several issues raised in cancer omics data analysis, including NGS, focusing particularly on the study design and analysis strategies. This might be helpful to understand the current trends and strategies of the rapidly evolving cancer genomics research.
Novel Somatic Copy Number Alteration Identified for Cervical Cancer in the Mexican American Population

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Alireza Torabi

2016-08-01

Full Text Available Cervical cancer affects millions of Americans, but the rate for cervical cancer in the Mexican American is approximately twice that for non-Mexican Americans. The etiologies of cervical cancer are still not fully understood. A number of somatic mutations, including several copy number alterations (CNAs, have been identified in the pathogenesis of cervical carcinomas in non-Mexican Americans. Thus, the purpose of this study was to investigate CNAs in association with cervical cancer in the Mexican American population. We conducted a pilot study of genome-wide CNA analysis using 2.5 million markers in four diagnostic groups: reference (n = 125, low grade dysplasia (cervical intraepithelial neoplasia (CIN-I, n = 4, high grade dysplasia (CIN-II and -III, n = 5 and invasive carcinoma (squamous cell carcinoma (SCC, n = 5 followed by data analyses using Partek. We observed a statistically-significant difference of CNA burden between case and reference groups of different sizes (>100 kb, 10–100 kb and 1–10 kb of CNAs that included deletions and amplifications, e.g., a statistically-significant difference of >100 kb deletions was observed between the reference (6.6% and pre-cancer and cancer (91.3% groups. Recurrent aberrations of 98 CNA regions were also identified in cases only. However, none of the CNAs have an impact on cancer progression. A total of 32 CNA regions identified contained tumor suppressor genes and oncogenes. Moreover, the pathway analysis revealed endometrial cancer and estrogen signaling pathways associated with this cancer (p < 0.05 using Kyoto Encyclopedia of Genes and Genomes (KEGG. This is the first report of CNAs identified for cervical cancer in the U.S. Latino population using high density markers. We are aware of the small sample size in the study. Thus, additional studies with a larger sample are needed to confirm the current findings.
Genomic rearrangements of PTEN in prostate cancer

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Sopheap ePhin

2013-09-01

Full Text Available The phosphatase and tensin homolog gene on chromosome 10q23.3 (PTEN is a negative regulator of the PIK3/Akt survival pathway and is the most frequently deleted tumor suppressor gene in prostate cancer. Monoallelic loss of PTEN is present in up to 60% of localized prostate cancers and complete loss of PTEN in prostate cancer is linked to metastasis and androgen independent progression. Studies on the genomic status of PTEN in prostate cancer initially used a two-color fluorescence in-situ hybridization (FISH assay for PTEN copy number detection in formalin fixed paraffin embedded tissue preparations. More recently, a four-color FISH assay containing two additional control probes flanking the PTEN locus with a lower false-positive rate was reported. Combined with the detection of other critical genomic biomarkers for prostate cancer such as ERG, AR, and MYC, the evaluation of PTEN genomic status has proven to be invaluable for patient stratification and management. Although less frequent than allelic deletions, point mutations in the gene and epigenetic silencing are also known to contribute to loss of PTEN function, and ultimately to prostate cancer initiation. Overall, it is clear that PTEN is a powerful biomarker for prostate cancer. Used as a companion diagnostic for emerging therapeutic drugs, FISH analysis of PTEN is promisingly moving human prostate cancer closer to more effective cancer management and therapies.
Xenopatients 2.0: reprogramming the epigenetic landscapes of patient-derived cancer genomes.

Science.gov (United States)

Menendez, Javier A; Alarcón, Tomás; Corominas-Faja, Bruna; Cuyàs, Elisabet; López-Bonet, Eugeni; Martin, Angel G; Vellon, Luciano

2014-01-01

In the science-fiction thriller film Minority Report, a specialized police department called "PreCrime" apprehends criminals identified in advance based on foreknowledge provided by 3 genetically altered humans called "PreCogs". We propose that Yamanaka stem cell technology can be similarly used to (epi)genetically reprogram tumor cells obtained directly from cancer patients and create self-evolving personalized translational platforms to foresee the evolutionary trajectory of individual tumors. This strategy yields a large stem cell population and captures the cancer genome of an affected individual, i.e., the PreCog-induced pluripotent stem (iPS) cancer cells, which are immediately available for experimental manipulation, including pharmacological screening for personalized "stemotoxic" cancer drugs. The PreCog-iPS cancer cells will re-differentiate upon orthotopic injection into the corresponding target tissues of immunodeficient mice (i.e., the PreCrime-iPS mouse avatars), and this in vivo model will run through specific cancer stages to directly explore their biological properties for drug screening, diagnosis, and personalized treatment in individual patients. The PreCog/PreCrime-iPS approach can perform sets of comparisons to directly observe changes in the cancer-iPS cell line vs. a normal iPS cell line derived from the same human genetic background. Genome editing of PreCog-iPS cells could create translational platforms to directly investigate the link between genomic expression changes and cellular malignization that is largely free from genetic and epigenetic noise and provide proof-of-principle evidence for cutting-edge "chromosome therapies" aimed against cancer aneuploidy. We might infer the epigenetic marks that correct the tumorigenic nature of the reprogrammed cancer cell population and normalize the malignant phenotype in vivo. Genetically engineered models of conditionally reprogrammable mice to transiently express the Yamanaka stemness factors
Open reading frames associated with cancer in the dark matter of the human genome.

Science.gov (United States)

Delgado, Ana Paula; Brandao, Pamela; Chapado, Maria Julia; Hamid, Sheilin; Narayanan, Ramaswamy

2014-01-01

The uncharacterized proteins (open reading frames, ORFs) in the human genome offer an opportunity to discover novel targets for cancer. A systematic analysis of the dark matter of the human proteome for druggability and biomarker discovery is crucial to mining the genome. Numerous data mining tools are available to mine these ORFs to develop a comprehensive knowledge base for future target discovery and validation. Using the Genetic Association Database, the ORFs of the human dark matter proteome were screened for evidence of association with neoplasms. The Phenome-Genome Integrator tool was used to establish phenotypic association with disease traits including cancer. Batch analysis of the tools for protein expression analysis, gene ontology and motifs and domains was used to characterize the ORFs. Sixty-two ORFs were identified for neoplasm association. The expression Quantitative Trait Loci (eQTL) analysis identified thirteen ORFs related to cancer traits. Protein expression, motifs and domain analysis and genome-wide association studies verified the relevance of these OncoORFs in diverse tumors. The OncoORFs are also associated with a wide variety of human diseases and disorders. Our results link the OncoORFs to diverse diseases and disorders. This suggests a complex landscape of the uncharacterized proteome in human diseases. These results open the dark matter of the proteome to novel cancer target research. Copyright© 2014, International Institute of Anticancer Research (Dr. John G. Delinasios), All rights reserved.
Understanding the development of human bladder cancer by using a whole-organ genomic mapping strategy.

Science.gov (United States)

Majewski, Tadeusz; Lee, Sangkyou; Jeong, Joon; Yoon, Dong-Sup; Kram, Andrzej; Kim, Mi-Sook; Tuziak, Tomasz; Bondaruk, Jolanta; Lee, Sooyong; Park, Weon-Seo; Tang, Kuang S; Chung, Woonbok; Shen, Lanlan; Ahmed, Saira S; Johnston, Dennis A; Grossman, H Barton; Dinney, Colin P; Zhou, Jain-Hua; Harris, R Alan; Snyder, Carrie; Filipek, Slawomir; Narod, Steven A; Watson, Patrice; Lynch, Henry T; Gazdar, Adi; Bar-Eli, Menashe; Wu, Xifeng F; McConkey, David J; Baggerly, Keith; Issa, Jean-Pierre; Benedict, William F; Scherer, Steven E; Czerniak, Bogdan

2008-07-01

The search for the genomic sequences involved in human cancers can be greatly facilitated by maps of genomic imbalances identifying the involved chromosomal regions, particularly those that participate in the development of occult preneoplastic conditions that progress to clinically aggressive invasive cancer. The integration of such regions with human genome sequence variation may provide valuable clues about their overall structure and gene content. By extension, such knowledge may help us understand the underlying genetic components involved in the initiation and progression of these cancers. We describe the development of a genome-wide map of human bladder cancer that tracks its progression from in situ precursor conditions to invasive disease. Testing for allelic losses using a genome-wide panel of 787 microsatellite markers was performed on multiple DNA samples, extracted from the entire mucosal surface of the bladder and corresponding to normal urothelium, in situ preneoplastic lesions, and invasive carcinoma. Using this approach, we matched the clonal allelic losses in distinct chromosomal regions to specific phases of bladder neoplasia and produced a detailed genetic map of bladder cancer development. These analyses revealed three major waves of genetic changes associated with growth advantages of successive clones and reflecting a stepwise conversion of normal urothelial cells into cancer cells. The genetic changes map to six regions at 3q22-q24, 5q22-q31, 9q21-q22, 10q26, 13q14, and 17p13, which may represent critical hits driving the development of bladder cancer. Finally, we performed high-resolution mapping using single nucleotide polymorphism markers within one region on chromosome 13q14, containing the model tumor suppressor gene RB1, and defined a minimal deleted region associated with clonal expansion of in situ neoplasia. These analyses provided new insights on the involvement of several non-coding sequences mapping to the region and identified
A meta-analysis of genome-wide association studies of breast cancer identifies two novel susceptibility loci at 6q14 and 20q11

Science.gov (United States)

Siddiq, Afshan; Couch, Fergus J.; Chen, Gary K.; Lindström, Sara; Eccles, Diana; Millikan, Robert C.; Michailidou, Kyriaki; Stram, Daniel O.; Beckmann, Lars; Rhie, Suhn Kyong; Ambrosone, Christine B.; Aittomäki, Kristiina; Amiano, Pilar; Apicella, Carmel; Baglietto, Laura; Bandera, Elisa V.; Beckmann, Matthias W.; Berg, Christine D.; Bernstein, Leslie; Blomqvist, Carl; Brauch, Hiltrud; Brinton, Louise; Bui, Quang M.; Buring, Julie E.; Buys, Saundra S.; Campa, Daniele; Carpenter, Jane E.; Chasman, Daniel I.; Chang-Claude, Jenny; Chen, Constance; Clavel-Chapelon, Françoise; Cox, Angela; Cross, Simon S.; Czene, Kamila; Deming, Sandra L.; Diasio, Robert B.; Diver, W. Ryan; Dunning, Alison M.; Durcan, Lorraine; Ekici, Arif B.; Fasching, Peter A.; Feigelson, Heather Spencer; Fejerman, Laura; Figueroa, Jonine D.; Fletcher, Olivia; Flesch-Janys, Dieter; Gaudet, Mia M.; Gerty, Susan M.; Rodriguez-Gil, Jorge L.; Giles, Graham G.; van Gils, Carla H.; Godwin, Andrew K.; Graham, Nikki; Greco, Dario; Hall, Per; Hankinson, Susan E.; Hartmann, Arndt; Hein, Rebecca; Heinz, Judith; Hoover, Robert N.; Hopper, John L.; Hu, Jennifer J.; Huntsman, Scott; Ingles, Sue A.; Irwanto, Astrid; Isaacs, Claudine; Jacobs, Kevin B.; John, Esther M.; Justenhoven, Christina; Kaaks, Rudolf; Kolonel, Laurence N.; Coetzee, Gerhard A.; Lathrop, Mark; Le Marchand, Loic; Lee, Adam M.; Lee, I-Min; Lesnick, Timothy; Lichtner, Peter; Liu, Jianjun; Lund, Eiliv; Makalic, Enes; Martin, Nicholas G.; McLean, Catriona A.; Meijers-Heijboer, Hanne; Meindl, Alfons; Miron, Penelope; Monroe, Kristine R.; Montgomery, Grant W.; Müller-Myhsok, Bertram; Nickels, Stefan; Nyante, Sarah J.; Olswold, Curtis; Overvad, Kim; Palli, Domenico; Park, Daniel J.; Palmer, Julie R.; Pathak, Harsh; Peto, Julian; Pharoah, Paul; Rahman, Nazneen; Rivadeneira, Fernando; Schmidt, Daniel F.; Schmutzler, Rita K.; Slager, Susan; Southey, Melissa C.; Stevens, Kristen N.; Sinn, Hans-Peter; Press, Michael F.; Ross, Eric; Riboli, Elio; Ridker, Paul M.; Schumacher, Fredrick R.; Severi, Gianluca; dos Santos Silva, Isabel; Stone, Jennifer; Sund, Malin; Tapper, William J.; Thun, Michael J.; Travis, Ruth C.; Turnbull, Clare; Uitterlinden, Andre G.; Waisfisz, Quinten; Wang, Xianshu; Wang, Zhaoming; Weaver, JoEllen; Schulz-Wendtland, Rüdiger; Wilkens, Lynne R.; Van Den Berg, David; Zheng, Wei; Ziegler, Regina G.; Ziv, Elad; Nevanlinna, Heli; Easton, Douglas F.; Hunter, David J.; Henderson, Brian E.; Chanock, Stephen J.; Garcia-Closas, Montserrat; Kraft, Peter; Haiman, Christopher A.; Vachon, Celine M.

2012-01-01

Genome-wide association studies (GWAS) of breast cancer defined by hormone receptor status have revealed loci contributing to susceptibility of estrogen receptor (ER)-negative subtypes. To identify additional genetic variants for ER-negative breast cancer, we conducted the largest meta-analysis of ER-negative disease to date, comprising 4754 ER-negative cases and 31 663 controls from three GWAS: NCI Breast and Prostate Cancer Cohort Consortium (BPC3) (2188 ER-negative cases; 25 519 controls of European ancestry), Triple Negative Breast Cancer Consortium (TNBCC) (1562 triple negative cases; 3399 controls of European ancestry) and African American Breast Cancer Consortium (AABC) (1004 ER-negative cases; 2745 controls). We performed in silico replication of 86 SNPs at P ≤ 1 × 10-5 in an additional 11 209 breast cancer cases (946 with ER-negative disease) and 16 057 controls of Japanese, Latino and European ancestry. We identified two novel loci for breast cancer at 20q11 and 6q14. SNP rs2284378 at 20q11 was associated with ER-negative breast cancer (combined two-stage OR = 1.16; P = 1.1 × 10−8) but showed a weaker association with overall breast cancer (OR = 1.08, P = 1.3 × 10–6) based on 17 869 cases and 43 745 controls and no association with ER-positive disease (OR = 1.01, P = 0.67) based on 9965 cases and 22 902 controls. Similarly, rs17530068 at 6q14 was associated with breast cancer (OR = 1.12; P = 1.1 × 10−9), and with both ER-positive (OR = 1.09; P = 1.5 × 10−5) and ER-negative (OR = 1.16, P = 2.5 × 10−7) disease. We also confirmed three known loci associated with ER-negative (19p13) and both ER-negative and ER-positive breast cancer (6q25 and 12p11). Our results highlight the value of large-scale collaborative studies to identify novel breast cancer risk loci. PMID:22976474
Transcriptome sequencing in prostate cancer identifies inter-tumor heterogeneity

Directory of Open Access Journals (Sweden)

Janet Mendonca

2015-06-01

Full Text Available Given the dearth of gene mutations in prostate cancer, [1] ,[2] it is likely that genomic rearrangements play a significant role in the evolution of prostate cancer. However, in the search for recurrent genomic alterations, "private alterations" have received less attention. Such alterations may provide insights into the evolution, behavior, and clinical outcome of an individual tumor. In a recent report in "Genome Biology" Wyatt et al. [3] defines unique alterations in a cohort of high-risk prostate cancer patient with a lethal phenotype. Utilizing a transcriptome sequencing approach they observe high inter-tumor heterogeneity; however, the genes altered distill into three distinct cancer-relevant pathways. Their analysis reveals the presence of several non-ETS fusions, which may contribute to the phenotype of individual tumors, and have significance for disease progression.
A splicing variant of TERT identified by GWAS interacts with menopausal estrogen therapy in risk of ovarian cancer

DEFF Research Database (Denmark)

Lee, Alice W; Bomkamp, Ashley; Bandera, Elisa V

2016-01-01

Menopausal estrogen-alone therapy (ET) is a well-established risk factor for serous and endometrioid ovarian cancer. Genetics also plays a role in ovarian cancer, which is partly attributable to 18 confirmed ovarian cancer susceptibility loci identified by genome-wide association studies. The int...

Predictive genomics: A cancer hallmark network framework for predicting tumor clinical phenotypes using genome sequencing data

OpenAIRE

Wang, Edwin; Zaman, Naif; Mcgee, Shauna; Milanese, Jean-Sébastien; Masoudi-Nejad, Ali; O'Connor, Maureen

2014-01-01

We discuss a cancer hallmark network framework for modelling genome-sequencing data to predict cancer clonal evolution and associated clinical phenotypes. Strategies of using this framework in conjunction with genome sequencing data in an attempt to predict personalized drug targets, drug resistance, and metastasis for a cancer patient, as well as cancer risks for a healthy individual are discussed. Accurate prediction of cancer clonal evolution and clinical phenotypes will have substantial i...
Tolerance of Whole-Genome Doubling Propagates Chromosomal Instability and Accelerates Cancer Genome Evolution

DEFF Research Database (Denmark)

Dewhurst, Sally M.; McGranahan, Nicholas; Burrell, Rebecca A.

2014-01-01

The contribution of whole-genome doubling to chromosomal instability (CIN) and tumor evolution is unclear. We use long-term culture of isogenic tetraploid cells from a stable diploid colon cancer progenitor to investigate how a genome-doubling event affects genome stability over time. Rare cells...
Modeling the integration of bacterial rRNA fragments into the human cancer genome.

Science.gov (United States)

Sieber, Karsten B; Gajer, Pawel; Dunning Hotopp, Julie C

2016-03-21

Cancer is a disease driven by the accumulation of genomic alterations, including the integration of exogenous DNA into the human somatic genome. We previously identified in silico evidence of DNA fragments from a Pseudomonas-like bacteria integrating into the 5'-UTR of four proto-oncogenes in stomach cancer sequencing data. The functional and biological consequences of these bacterial DNA integrations remain unknown. Modeling of these integrations suggests that the previously identified sequences cover most of the sequence flanking the junction between the bacterial and human DNA. Further examination of these reads reveals that these integrations are rich in guanine nucleotides and the integrated bacterial DNA may have complex transcript secondary structures. The models presented here lay the foundation for future experiments to test if bacterial DNA integrations alter the transcription of the human genes.
Chapter 27 -- Breast Cancer Genomics, Section VI, Pathology and Biological Markers of Invasive Breast Cancer

Energy Technology Data Exchange (ETDEWEB)

Spellman, Paul T.; Heiser, Laura; Gray, Joe W.

2009-06-18

Breast cancer is predominantly a disease of the genome with cancers arising and progressing through accumulation of aberrations that alter the genome - by changing DNA sequence, copy number, and structure in ways that that contribute to diverse aspects of cancer pathophysiology. Classic examples of genomic events that contribute to breast cancer pathophysiology include inherited mutations in BRCA1, BRCA2, TP53, and CHK2 that contribute to the initiation of breast cancer, amplification of ERBB2 (formerly HER2) and mutations of elements of the PI3-kinase pathway that activate aspects of epidermal growth factor receptor (EGFR) signaling and deletion of CDKN2A/B that contributes to cell cycle deregulation and genome instability. It is now apparent that accumulation of these aberrations is a time-dependent process that accelerates with age. Although American women living to an age of 85 have a 1 in 8 chance of developing breast cancer, the incidence of cancer in women younger than 30 years is uncommon. This is consistent with a multistep cancer progression model whereby mutation and selection drive the tumor's development, analogous to traditional Darwinian evolution. In the case of cancer, the driving events are changes in sequence, copy number, and structure of DNA and alterations in chromatin structure or other epigenetic marks. Our understanding of the genetic, genomic, and epigenomic events that influence the development and progression of breast cancer is increasing at a remarkable rate through application of powerful analysis tools that enable genome-wide analysis of DNA sequence and structure, copy number, allelic loss, and epigenomic modification. Application of these techniques to elucidation of the nature and timing of these events is enriching our understanding of mechanisms that increase breast cancer susceptibility, enable tumor initiation and progression to metastatic disease, and determine therapeutic response or resistance. These studies also
Clinical application of genomic profiling to find druggable targets for adolescent and young adult (AYA) cancer patients with metastasis

International Nuclear Information System (INIS)

Cha, Soojin; Lee, Jeongeun; Shin, Jong-Yeon; Kim, Ji-Yeon; Sim, Sung Hoon; Keam, Bhumsuk; Kim, Tae Min; Kim, Dong-Wan; Heo, Dae Seog; Lee, Se-Hoon; Kim, Jong-Il

2016-01-01

Although adolescent and young adult (AYA) cancers are characterized by biological features and clinical outcomes distinct from those of other age groups, the molecular profile of AYA cancers has not been well defined. In this study, we analyzed cancer genomes from rare types of metastatic AYA cancers to identify driving and/or druggable genetic alterations. Prospectively collected AYA tumor samples from seven different patients were analyzed using three different genomics platforms (whole-exome sequencing, whole-transcriptome sequencing or OncoScan™). Using well-known bioinformatics tools (bwa, Picard, GATK, MuTect, and Somatic Indel Detector) and our annotation approach with open access databases (DAVID and DGIdb), we processed sequencing data and identified driving genetic alterations and their druggability. The mutation frequencies of AYA cancers were lower than those of other adult cancers (median = 0.56), except for a germ cell tumor with hypermutation. We identified patient-specific genetic alterations in candidate driving genes: RASA2 and NF1 (prostate cancer), TP53 and CDKN2C (olfactory neuroblastoma), FAT1, NOTCH1, and SMAD4 (head and neck cancer), KRAS (urachal carcinoma), EML4-ALK (lung cancer), and MDM2 and PTEN (liposarcoma). We then suggested potential drugs for each patient according to his or her altered genes and related pathways. By comparing candidate driving genes between AYA cancers and those from all age groups for the same type of cancer, we identified different driving genes in prostate cancer and a germ cell tumor in AYAs compared with all age groups, whereas three common alterations (TP53, FAT1, and NOTCH1) in head and neck cancer were identified in both groups. We identified the patient-specific genetic alterations and druggability of seven rare types of AYA cancers using three genomics platforms. Additionally, genetic alterations in cancers from AYA and those from all age groups varied by cancer type. The online version of this article
MTAP deletion confers enhanced dependency on the PRMT5 arginine methyltransferase in cancer cells | Office of Cancer Genomics

Science.gov (United States)

The discovery of cancer dependencies has the potential to inform therapeutic strategies and to identify putative drug targets. Integrating data from comprehensive genomic profiling of cancer cell lines and from functional characterization of cancer cell dependencies, we discovered that loss of the enzyme methylthioadenosine phosphorylase (MTAP) confers a selective dependence on protein arginine methyltransferase 5 (PRMT5) and its binding partner WDR77. MTAP is frequently lost due to its proximity to the commonly deleted tumor suppressor gene, CDKN2A.
Oncogenomic portals for the visualization and analysis of genome-wide cancer data.

Science.gov (United States)

Klonowska, Katarzyna; Czubak, Karol; Wojciechowska, Marzena; Handschuh, Luiza; Zmienko, Agnieszka; Figlerowicz, Marek; Dams-Kozlowska, Hanna; Kozlowski, Piotr

2016-01-05

Somatically acquired genomic alterations that drive oncogenic cellular processes are of great scientific and clinical interest. Since the initiation of large-scale cancer genomic projects (e.g., the Cancer Genome Project, The Cancer Genome Atlas, and the International Cancer Genome Consortium cancer genome projects), a number of web-based portals have been created to facilitate access to multidimensional oncogenomic data and assist with the interpretation of the data. The portals provide the visualization of small-size mutations, copy number variations, methylation, and gene/protein expression data that can be correlated with the available clinical, epidemiological, and molecular features. Additionally, the portals enable to analyze the gathered data with the use of various user-friendly statistical tools. Herein, we present a highly illustrated review of seven portals, i.e., Tumorscape, UCSC Cancer Genomics Browser, ICGC Data Portal, COSMIC, cBioPortal, IntOGen, and BioProfiling.de. All of the selected portals are user-friendly and can be exploited by scientists from different cancer-associated fields, including those without bioinformatics background. It is expected that the use of the portals will contribute to a better understanding of cancer molecular etiology and will ultimately accelerate the translation of genomic knowledge into clinical practice.
Genome-Wide Association Study to Identify Single Nucleotide Polymorphisms (SNPs) Associated With the Development of Erectile Dysfunction in African-American Men After Radiotherapy for Prostate Cancer

International Nuclear Information System (INIS)

Kerns, Sarah L.; Ostrer, Harry; Stock, Richard; Li, William; Moore, Julian; Pearlman, Alexander; Campbell, Christopher; Shao Yongzhao; Stone, Nelson; Kusnetz, Lynda; Rosenstein, Barry S.

2010-01-01

Purpose: To identify single nucleotide polymorphisms (SNPs) associated with erectile dysfunction (ED) among African-American prostate cancer patients treated with external beam radiation therapy. Methods and Materials: A cohort of African-American prostate cancer patients treated with external beam radiation therapy was observed for the development of ED by use of the five-item Sexual Health Inventory for Men (SHIM) questionnaire. Final analysis included 27 cases (post-treatment SHIM score ≤7) and 52 control subjects (post-treatment SHIM score ≥16). A genome-wide association study was performed using approximately 909,000 SNPs genotyped on Affymetrix 6.0 arrays (Affymetrix, Santa Clara, CA). Results: We identified SNP rs2268363, located in the follicle-stimulating hormone receptor (FSHR) gene, as significantly associated with ED after correcting for multiple comparisons (unadjusted p = 5.46 x 10 -8 , Bonferroni p = 0.028). We identified four additional SNPs that tended toward a significant association with an unadjusted p value -6 . Inference of population substructure showed that cases had a higher proportion of African ancestry than control subjects (77% vs. 60%, p = 0.005). A multivariate logistic regression model that incorporated estimated ancestry and four of the top-ranked SNPs was a more accurate classifier of ED than a model that included only clinical variables. Conclusions: To our knowledge, this is the first genome-wide association study to identify SNPs associated with adverse effects resulting from radiotherapy. It is important to note that the SNP that proved to be significantly associated with ED is located within a gene whose encoded product plays a role in male gonad development and function. Another key finding of this project is that the four SNPs most strongly associated with ED were specific to persons of African ancestry and would therefore not have been identified had a cohort of European ancestry been screened. This study demonstrates
Genome Stability Pathways in Head and Neck Cancers

Directory of Open Access Journals (Sweden)

Glenn Jenkins

2013-01-01

Full Text Available Genomic instability underlies the transformation of host cells toward malignancy, promotes development of invasion and metastasis and shapes the response of established cancer to treatment. In this review, we discuss recent advances in our understanding of genomic stability in squamous cell carcinoma of the head and neck (HNSCC, with an emphasis on DNA repair pathways. HNSCC is characterized by distinct profiles in genome stability between similarly staged cancers that are reflected in risk, treatment response and outcomes. Defective DNA repair generates chromosomal derangement that can cause subsequent alterations in gene expression, and is a hallmark of progression toward carcinoma. Variable functionality of an increasing spectrum of repair gene polymorphisms is associated with increased cancer risk, while aetiological factors such as human papillomavirus, tobacco and alcohol induce significantly different behaviour in induced malignancy, underpinned by differences in genomic stability. Targeted inhibition of signalling receptors has proven to be a clinically-validated therapy, and protein expression of other DNA repair and signalling molecules associated with cancer behaviour could potentially provide a more refined clinical model for prognosis and treatment prediction. Development and expansion of current genomic stability models is furthering our understanding of HNSCC pathophysiology and uncovering new, promising treatment strategies.
Genome Stability Pathways in Head and Neck Cancers

Science.gov (United States)

O'Byrne, Kenneth J.; Panizza, Benedict; Richard, Derek J.

2013-01-01

Genomic instability underlies the transformation of host cells toward malignancy, promotes development of invasion and metastasis and shapes the response of established cancer to treatment. In this review, we discuss recent advances in our understanding of genomic stability in squamous cell carcinoma of the head and neck (HNSCC), with an emphasis on DNA repair pathways. HNSCC is characterized by distinct profiles in genome stability between similarly staged cancers that are reflected in risk, treatment response and outcomes. Defective DNA repair generates chromosomal derangement that can cause subsequent alterations in gene expression, and is a hallmark of progression toward carcinoma. Variable functionality of an increasing spectrum of repair gene polymorphisms is associated with increased cancer risk, while aetiological factors such as human papillomavirus, tobacco and alcohol induce significantly different behaviour in induced malignancy, underpinned by differences in genomic stability. Targeted inhibition of signalling receptors has proven to be a clinically-validated therapy, and protein expression of other DNA repair and signalling molecules associated with cancer behaviour could potentially provide a more refined clinical model for prognosis and treatment prediction. Development and expansion of current genomic stability models is furthering our understanding of HNSCC pathophysiology and uncovering new, promising treatment strategies. PMID:24364026
Childhood Cancer Genomics (PDQ®)—Health Professional Version

Science.gov (United States)

Genomic findings have been useful in the identification of subsets of patients that have distinct biological features and clinical characteristics (such as prognosis) for some pediatric cancers. Learn about the genomic alterations associated with central nervous system, leukemia, lymphoma, liver, sarcoma, neuroblastoma, retinoblastoma, melanoma, kidney, and thyroid cancers in children in this comprehensive summary for clinicians.
Pathways to Genome-targeted Therapies in Serous Ovarian Cancer.

Science.gov (United States)

Axelrod, Joshua; Delaney, Joe

2017-07-01

Genome sequencing technologies and corresponding oncology publications have generated enormous publicly available datasets for many cancer types. While this has enabled new treatments, and in some limited cases lifetime management of the disease, the treatment options for serous ovarian cancer remain dismal. This review summarizes recent advances in our understanding of ovarian cancer, with a focus on heterogeneity, functional genomics, and actionable data.
Genome-Wide Meta-Analyses of Breast, Ovarian, and Prostate Cancer Association Studies Identify Multiple New Susceptibility Loci Shared by at Least Two Cancer Types

DEFF Research Database (Denmark)

Kar, Siddhartha P; Beesley, Jonathan; Amin Al Olama, Ali

2016-01-01

UNLABELLED: Breast, ovarian, and prostate cancers are hormone-related and may have a shared genetic basis, but this has not been investigated systematically by genome-wide association (GWA) studies. Meta-analyses combining the largest GWA meta-analysis data sets for these cancers totaling 112...... (rs200182588/9q31/SMC2; rs8037137/15q26/RCCD1), and two breast and prostate cancer risk loci (rs5013329/1p34/NSUN4; rs9375701/6q23/L3MBTL3). Index variants in five additional regions previously associated with only one cancer also showed clear association with a second cancer type. Cell......-type-specific expression quantitative trait locus and enhancer-gene interaction annotations suggested target genes with potential cross-cancer roles at the new loci. Pathway analysis revealed significant enrichment of death receptor signaling genes near loci with P cancer meta-analysis. SIGNIFICANCE...
Genetic basis of kidney cancer: Role of genomics for the development of disease-based therapeutics

Science.gov (United States)

Linehan, W. Marston

2012-01-01

Kidney cancer is not a single disease; it is made up of a number of different types of cancer, including clear cell, type 1 papillary, type 2 papillary, chromophobe, TFE3, TFEB, and oncocytoma. Sporadic, nonfamilial kidney cancer includes clear cell kidney cancer (75%), type 1 papillary kidney cancer (10%), papillary type 2 kidney cancer (including collecting duct and medullary RCC) (5%), the microphalmia-associated transcription (MiT) family translocation kidney cancers (TFE3, TFEB, and MITF), chromophobe kidney cancer (5%), and oncocytoma (5%). Each has a distinct histology, a different clinical course, responds differently to therapy, and is caused by mutation in a different gene. Genomic studies identifying the genes for kidney cancer, including the VHL, MET, FLCN, fumarate hydratase, succinate dehydrogenase, TSC1, TSC2, and TFE3 genes, have significantly altered the ways in which patients with kidney cancer are managed. While seven FDA-approved agents that target the VHL pathway have been approved for the treatment of patients with advanced kidney cancer, further genomic studies, such as whole genome sequencing, gene expression patterns, and gene copy number, will be required to gain a complete understanding of the genetic basis of kidney cancer and of the kidney cancer gene pathways and, most importantly, to provide the foundation for the development of effective forms of therapy for patients with this disease. PMID:23038766
The Genomic Evolution of Prostate Cancer

Science.gov (United States)

2017-06-01

the proposed project : 1. To continue to acquire a comprehensive understanding of prostate cancer genomics . 2. To develop an understanding of... Genetics I • ECEV 35901 Evolutionary Genomics • Fundamentals of Clinical Research • HGEN 47400 Introduction to Probability and Statistics for Geneticists...Marc Gillard,2 David M. Hatcher,5 Westin R. Tom,5 Walter M. Stadler2 and Kevin P. White1,2,3 1Institute for Genomics and Systems Biology , Departments of
Copy-number and gene dependency analysis reveals partial copy loss of wild-type SF3B1 as a novel cancer vulnerability. | Office of Cancer Genomics

Science.gov (United States)

Genomic instability is a hallmark of human cancer, and results in widespread somatic copy number alterations. We used a genome-scale shRNA viability screen in human cancer cell lines to systematically identify genes that are essential in the context of particular copy-number alterations (copy-number associated gene dependencies). The most enriched class of copy-number associated gene dependencies was CYCLOPS (Copy-number alterations Yielding Cancer Liabilities Owing to Partial losS) genes, and spliceosome components were the most prevalent.
PBX1 Genomic Pioneer Function Drives ERα Signaling Underlying Progression in Breast Cancer

Science.gov (United States)

Magnani, Luca; Ballantyne, Elizabeth B.; Zhang, Xiaoyang; Lupien, Mathieu

2011-01-01

Altered transcriptional programs are a hallmark of diseases, yet how these are established is still ill-defined. PBX1 is a TALE homeodomain protein involved in the development of different types of cancers. The estrogen receptor alpha (ERα) is central to the development of two-thirds of all breast cancers. Here we demonstrate that PBX1 acts as a pioneer factor and is essential for the ERα-mediated transcriptional response driving aggressive tumors in breast cancer. Indeed, PBX1 expression correlates with ERα in primary breast tumors, and breast cancer cells depleted of PBX1 no longer proliferate following estrogen stimulation. Profiling PBX1 recruitment and chromatin accessibility across the genome of breast cancer cells through ChIP-seq and FAIRE-seq reveals that PBX1 is loaded and promotes chromatin openness at specific genomic locations through its capacity to read specific epigenetic signatures. Accordingly, PBX1 guides ERα recruitment to a specific subset of sites. Expression profiling studies demonstrate that PBX1 controls over 70% of the estrogen response. More importantly, the PBX1-dependent transcriptional program is associated with poor-outcome in breast cancer patients. Correspondingly, PBX1 expression alone can discriminate a priori the outcome in ERα-positive breast cancer patients. These features are markedly different from the previously characterized ERα-associated pioneer factor FoxA1. Indeed, PBX1 is the only pioneer factor identified to date that discriminates outcome such as metastasis in ERα-positive breast cancer patients. Together our results reveal that PBX1 is a novel pioneer factor defining aggressive ERα-positive breast tumors, as it guides ERα genomic activity to unique genomic regions promoting a transcriptional program favorable to breast cancer progression. PMID:22125492
Genomics of Colorectal Cancer in African Americans

OpenAIRE

Brim, Hassan; Ashktorab, Hassan

2016-01-01

Genome-wide studies are increasingly becoming a must, especially for complex diseases such as cancer where multiple genes and diverse molecular mechanisms are known to be involved in genes’ function alteration. In this review, we report our latest genomic and epigenomic findings in African-American colorectal cancer patients. This population suffers a higher burden of the disease and most investigators in this field are looking for the underlying genetic and epigenetic targets that might be r...
Genomic Resources for Cancer Epidemiology

Science.gov (United States)

This page provides links to research resources, complied by the Epidemiology and Genomics Research Program, that may be of interest to genetic epidemiologists conducting cancer research, but is not exhaustive.
Three new pancreatic cancer susceptibility signals identified on chromosomes 1q32.1, 5p15.33 and 8q24.21

NARCIS (Netherlands)

Zhang, Mingfeng; Wang, Zhaoming; Obazee, Ofure; Jia, Jinping; Childs, Erica J; Hoskins, Jason; Figlioli, Gisella; Mocci, Evelina; Collins, Irene; Chung, Charles C; Hautman, Christopher; Arslan, Alan A; Beane-Freeman, Laura; Bracci, Paige M; Buring, Julie; Duell, Eric J; Gallinger, Steven; Giles, Graham G; Goodman, Gary E; Goodman, Phyllis J; Kamineni, Aruna; Kolonel, Laurence N; Kulke, Matthew H; Malats, Núria; Olson, Sara H; Sesso, Howard D; Visvanathan, Kala; White, Emily; Zheng, Wei; Abnet, Christian C; Albanes, Demetrius; Andreotti, Gabriella; Brais, Lauren; Bueno-de-Mesquita, H Bas; Basso, Daniela; Berndt, Sonja I; Boutron-Ruault, Marie-Christine; Bijlsma, Maarten F; Brenner, Hermann; Burdette, Laurie; Campa, Daniele; Caporaso, Neil E; Capurso, Gabriele; Cavestro, Giulia Martina; Cotterchio, Michelle; Costello, Eithne; Elena, Joanne; Boggi, Ugo; Gaziano, J Michael; Gazouli, Maria; Giovannucci, Edward L; Goggins, Michael; Gross, Myron; Haiman, Christopher A; Hassan, Manal; Helzlsouer, Kathy J; Hu, Nan; Hunter, David J; Iskierka-Jazdzewska, Elzbieta; Jenab, Mazda; Kaaks, Rudolf; Key, Timothy J; Khaw, Kay-Tee; Klein, Eric A; Kogevinas, Manolis; Krogh, Vittorio; Kupcinskas, Juozas; Kurtz, Robert C; Landi, Maria T; Landi, Stefano; Le Marchand, Loic; Mambrini, Andrea; Mannisto, Satu; Milne, Roger L; Neale, Rachel E; Oberg, Ann L; Panico, Salvatore; Patel, Alpa V; Peeters, Petra H M; Peters, Ulrike; Pezzilli, Raffaele; Porta, Miquel; Purdue, Mark; Quiros, J Ramón; Riboli, Elio; Rothman, Nathaniel; Scarpa, Aldo; Scelo, Ghislaine; Shu, Xiao-Ou; Silverman, Debra T; Soucek, Pavel; Strobel, Oliver; Sund, Malin; Małecka-Panas, Ewa; Taylor, Philip R; Tavano, Francesca; Travis, Ruth C; Thornquist, Mark; Tjønneland, Anne; Tobias, Geoffrey S; Trichopoulos, Dimitrios; Vashist, Yogesh; Vodicka, Pavel; Wactawski-Wende, Jean; Wentzensen, Nicolas; Yu, Herbert; Yu, Kai; Zeleniuch-Jacquotte, Anne; Kooperberg, Charles; Risch, Harvey A; Jacobs, Eric J; Li, Donghui; Fuchs, Charles; Hoover, Robert; Hartge, Patricia; Chanock, Stephen J; Petersen, Gloria M; Stolzenberg-Solomon, Rachael S; Wolpin, Brian M; Kraft, Peter; Klein, Alison P; Canzian, Federico; Amundadottir, Laufey T

2016-01-01

Genome-wide association studies (GWAS) have identified common pancreatic cancer susceptibility variants at 13 chromosomal loci in individuals of European descent. To identify new susceptibility variants, we performed imputation based on 1000 Genomes (1000G) Project data and association analysis

Gene Signature in Sessile Serrated Polyps Identifies Colon Cancer Subtype

Science.gov (United States)

Kanth, Priyanka; Bronner, Mary P.; Boucher, Kenneth M.; Burt, Randall W.; Neklason, Deborah W.; Hagedorn, Curt H.; Delker, Don A.

2016-01-01

Sessile serrated colon adenoma/polyps (SSA/Ps) are found during routine screening colonoscopy and may account for 20–30% of colon cancers. However, differentiating SSA/Ps from hyperplastic polyps (HP) with little risk of cancer is challenging and complementary molecular markers are needed. Additionally, the molecular mechanisms of colon cancer development from SSA/Ps are poorly understood. RNA sequencing was performed on 21 SSA/Ps, 10 HPs, 10 adenomas, 21 uninvolved colon and 20 control colon specimens. Differential expression and leave-one-out cross validation methods were used to define a unique gene signature of SSA/Ps. Our SSA/P gene signature was evaluated in colon cancer RNA-Seq data from The Cancer Genome Atlas (TCGA) to identify a subtype of colon cancers that may develop from SSA/Ps. A total of 1422 differentially expressed genes were found in SSA/Ps relative to controls. Serrated polyposis syndrome (n=12) and sporadic SSA/Ps (n=9) exhibited almost complete (96%) gene overlap. A 51-gene panel in SSA/P showed similar expression in a subset of TCGA colon cancers with high microsatellite instability (MSI-H). A smaller seven-gene panel showed high sensitivity and specificity in identifying BRAF mutant, CpG island methylator phenotype high (CIMP-H) and MLH1 silenced colon cancers. We describe a unique gene signature in SSA/Ps that identifies a subset of colon cancers likely to develop through the serrated pathway. These gene panels may be utilized for improved differentiation of SSA/Ps from HPs and provide insights into novel molecular pathways altered in colon cancer arising from the serrated pathway. PMID:27026680
Combined and interactive effects of environmental and GWAS-identified risk factors in ovarian cancer

DEFF Research Database (Denmark)

Pearce, Celeste Leigh; Rossing, Mary Anne; Lee, Alice W

2013-01-01

There are several well-established environmental risk factors for ovarian cancer, and recent genome-wide association studies have also identified six variants that influence disease risk. However, the interplay between such risk factors and susceptibility loci has not been studied....
Clonal expansion and linear genome evolution through breast cancer progression from pre-invasive stages to asynchronous metastasis

DEFF Research Database (Denmark)

Krøigård, Anne Bruun; Larsen, Martin Jakob; Lænkholm, Anne Vibeke

2015-01-01

Evolution of the breast cancer genome from pre-invasive stages to asynchronous metastasis is complex and mostly unexplored, but highly demanded as it may provide novel markers for and mechanistic insights in cancer progression. The increasing use of personalized therapy of breast cancer necessita......Evolution of the breast cancer genome from pre-invasive stages to asynchronous metastasis is complex and mostly unexplored, but highly demanded as it may provide novel markers for and mechanistic insights in cancer progression. The increasing use of personalized therapy of breast cancer...... progression from one breast cancer patient, including two different regions of Ductal Carcinoma In Situ (DCIS), primary tumor and an asynchronous metastasis. We identify a remarkable landscape of somatic mutations, retained throughout breast cancer progression and with new mutational events emerging at each...
Genomic profiling toward precision medicine in non-small cell lung cancer: getting beyond EGFR

Directory of Open Access Journals (Sweden)

Richer AL

2015-02-01

Full Text Available Amanda L Richer,1 Jacqueline M Friel,1 Vashti M Carson,2 Landon J Inge,1 Timothy G Whitsett2 1Norton Thoracic Institute, St Joseph’s Hospital and Medical Center, 2Cancer and Cell Biology Division, Translational Genomics Research Institute, Phoenix, AZ, USA Abstract: Lung cancer remains the leading cause of cancer-related mortality worldwide. The application of next-generation genomic technologies has offered a more comprehensive look at the mutational landscape across the different subtypes of non-small cell lung cancer (NSCLC. A number of recurrent mutations such as TP53, KRAS, and epidermal growth factor receptor (EGFR have been identified in NSCLC. While targeted therapeutic successes have been demonstrated in the therapeutic targeting of EGFR and ALK, the majority of NSCLC tumors do not harbor these genomic events. This review looks at the current treatment paradigms for lung adenocarcinomas and squamous cell carcinomas, examining genomic aberrations that dictate therapy selection, as well as novel therapeutic strategies for tumors harboring mutations in KRAS, TP53, and LKB1 which, to date, have been considered “undruggable”. A more thorough understanding of the molecular alterations that govern NSCLC tumorigenesis, aided by next-generation sequencing, will lead to targeted therapeutic options expected to dramatically reduce the high mortality rate observed in lung cancer. Keywords: non-small cell lung cancer, precision medicine, epidermal growth factor receptor, Kirsten rat sarcoma viral oncogene homolog, serine/threonine kinase 11, tumor protein p53
Spectrum of mitochondrial genomic variation and associated clinical presentation of prostate cancer in South African men.

Science.gov (United States)

McCrow, John P; Petersen, Desiree C; Louw, Melanie; Chan, Eva K F; Harmeyer, Katherine; Vecchiarelli, Stefano; Lyons, Ruth J; Bornman, M S Riana; Hayes, Vanessa M

2016-03-01

Prostate cancer incidence and mortality rates are significantly increased in African-American men, but limited studies have been performed within Sub-Saharan African populations. As mitochondria control energy metabolism and apoptosis we speculate that somatic mutations within mitochondrial genomes are candidate drivers of aggressive prostate carcinogenesis. We used matched blood and prostate tissue samples from 87 South African men (77 with African ancestry) to perform deep sequencing of complete mitochondrial genomes. Clinical presentation was biased toward aggressive disease (Gleason score >7, 64%), and compared with men without prostate cancer either with or without benign prostatic hyperplasia. We identified 144 somatic mtDNA single nucleotide variants (SNVs), of which 80 were observed in 39 men presenting with aggressive disease. Both the number and frequency of somatic mtDNA SNVs were associated with higher pathological stage. Besides doubling the total number of somatic PCa-associated mitochondrial genome mutations identified to date, we associate mutational load with aggressive prostate cancer status in men of African ancestry. © 2015 The Authors. The Prostate published by Wiley Periodicals, Inc.
Predictive genomics: a cancer hallmark network framework for predicting tumor clinical phenotypes using genome sequencing data.

Science.gov (United States)

Wang, Edwin; Zaman, Naif; Mcgee, Shauna; Milanese, Jean-Sébastien; Masoudi-Nejad, Ali; O'Connor-McCourt, Maureen

2015-02-01

Tumor genome sequencing leads to documenting thousands of DNA mutations and other genomic alterations. At present, these data cannot be analyzed adequately to aid in the understanding of tumorigenesis and its evolution. Moreover, we have little insight into how to use these data to predict clinical phenotypes and tumor progression to better design patient treatment. To meet these challenges, we discuss a cancer hallmark network framework for modeling genome sequencing data to predict cancer clonal evolution and associated clinical phenotypes. The framework includes: (1) cancer hallmarks that can be represented by a few molecular/signaling networks. 'Network operational signatures' which represent gene regulatory logics/strengths enable to quantify state transitions and measures of hallmark traits. Thus, sets of genomic alterations which are associated with network operational signatures could be linked to the state/measure of hallmark traits. The network operational signature transforms genotypic data (i.e., genomic alterations) to regulatory phenotypic profiles (i.e., regulatory logics/strengths), to cellular phenotypic profiles (i.e., hallmark traits) which lead to clinical phenotypic profiles (i.e., a collection of hallmark traits). Furthermore, the framework considers regulatory logics of the hallmark networks under tumor evolutionary dynamics and therefore also includes: (2) a self-promoting positive feedback loop that is dominated by a genomic instability network and a cell survival/proliferation network is the main driver of tumor clonal evolution. Surrounding tumor stroma and its host immune systems shape the evolutionary paths; (3) cell motility initiating metastasis is a byproduct of the above self-promoting loop activity during tumorigenesis; (4) an emerging hallmark network which triggers genome duplication dominates a feed-forward loop which in turn could act as a rate-limiting step for tumor formation; (5) mutations and other genomic alterations have
Meta-analysis of five genome-wide association studies identifies multiple new loci associated with testicular germ cell tumor

DEFF Research Database (Denmark)

Wang, Zhaoming; McGlynn, Katherine A.; Rajpert-De Meyts, Ewa

2017-01-01

The international Testicular Cancer Consortium (TECAC) combined five published genome-wide association studies of testicular germ cell tumor (TGCT; 3,558 cases and 13,970 controls) to identify new susceptibility loci. We conducted a fixed-effects meta-analysis, including, to our knowledge, the fi...
Identification of chromosome aberrations in sporadic microsatellite stable and unstable colorectal cancers using array comparative genomic hybridization

DEFF Research Database (Denmark)

Jensen, Thomas Dyrsø; Li, Jian; Wang, Kai

2011-01-01

cancers constitute approximately 85% of sporadic cases, whereas microsatellite unstable (MSI) cases constitute the remaining 15%. In this study, we used array comparative genomic hybridization (aCGH) to identify genomic hotspot regions that harbor recurrent copy number changes. The study material...
A network-based drug repositioning infrastructure for precision cancer medicine through targeting significantly mutated genes in the human cancer genomes.

Science.gov (United States)

Cheng, Feixiong; Zhao, Junfei; Fooksa, Michaela; Zhao, Zhongming

2016-07-01

Development of computational approaches and tools to effectively integrate multidomain data is urgently needed for the development of newly targeted cancer therapeutics. We proposed an integrative network-based infrastructure to identify new druggable targets and anticancer indications for existing drugs through targeting significantly mutated genes (SMGs) discovered in the human cancer genomes. The underlying assumption is that a drug would have a high potential for anticancer indication if its up-/down-regulated genes from the Connectivity Map tended to be SMGs or their neighbors in the human protein interaction network. We assembled and curated 693 SMGs in 29 cancer types and found 121 proteins currently targeted by known anticancer or noncancer (repurposed) drugs. We found that the approved or experimental cancer drugs could potentially target these SMGs in 33.3% of the mutated cancer samples, and this number increased to 68.0% by drug repositioning through surveying exome-sequencing data in approximately 5000 normal-tumor pairs from The Cancer Genome Atlas. Furthermore, we identified 284 potential new indications connecting 28 cancer types and 48 existing drugs (adjusted P < .05), with a 66.7% success rate validated by literature data. Several existing drugs (e.g., niclosamide, valproic acid, captopril, and resveratrol) were predicted to have potential indications for multiple cancer types. Finally, we used integrative analysis to showcase a potential mechanism-of-action for resveratrol in breast and lung cancer treatment whereby it targets several SMGs (ARNTL, ASPM, CTTN, EIF4G1, FOXP1, and STIP1). In summary, we demonstrated that our integrative network-based infrastructure is a promising strategy to identify potential druggable targets and uncover new indications for existing drugs to speed up molecularly targeted cancer therapeutics. © The Author 2016. Published by Oxford University Press on behalf of the American Medical Informatics Association. All
A Genome-Wide Breast Cancer Scan in African Americans

Science.gov (United States)

2010-06-01

SNPs from the African American breast cancer scan to COGs , a European collaborative study which is has designed a SNP array with that will be genotyped...Award Number: W81XWH-08-1-0383 TITLE: A Genome-wide Breast Cancer Scan in African Americans PRINCIPAL INVESTIGATOR: Christopher A...SUBTITLE A Genome-wide Breast Cancer Scan in African Americans 5a. CONTRACT NUMBER 5b. GRANT NUMBER W81XWH-08-1-0383 5c. PROGRAM
Large-scale association analysis identifies new lung cancer susceptibility loci and heterogeneity in genetic susceptibility across histological subtypes.

Science.gov (United States)

McKay, James D; Hung, Rayjean J; Han, Younghun; Zong, Xuchen; Carreras-Torres, Robert; Christiani, David C; Caporaso, Neil E; Johansson, Mattias; Xiao, Xiangjun; Li, Yafang; Byun, Jinyoung; Dunning, Alison; Pooley, Karen A; Qian, David C; Ji, Xuemei; Liu, Geoffrey; Timofeeva, Maria N; Bojesen, Stig E; Wu, Xifeng; Le Marchand, Loic; Albanes, Demetrios; Bickeböller, Heike; Aldrich, Melinda C; Bush, William S; Tardon, Adonina; Rennert, Gad; Teare, M Dawn; Field, John K; Kiemeney, Lambertus A; Lazarus, Philip; Haugen, Aage; Lam, Stephen; Schabath, Matthew B; Andrew, Angeline S; Shen, Hongbing; Hong, Yun-Chul; Yuan, Jian-Min; Bertazzi, Pier Alberto; Pesatori, Angela C; Ye, Yuanqing; Diao, Nancy; Su, Li; Zhang, Ruyang; Brhane, Yonathan; Leighl, Natasha; Johansen, Jakob S; Mellemgaard, Anders; Saliba, Walid; Haiman, Christopher A; Wilkens, Lynne R; Fernandez-Somoano, Ana; Fernandez-Tardon, Guillermo; van der Heijden, Henricus F M; Kim, Jin Hee; Dai, Juncheng; Hu, Zhibin; Davies, Michael P A; Marcus, Michael W; Brunnström, Hans; Manjer, Jonas; Melander, Olle; Muller, David C; Overvad, Kim; Trichopoulou, Antonia; Tumino, Rosario; Doherty, Jennifer A; Barnett, Matt P; Chen, Chu; Goodman, Gary E; Cox, Angela; Taylor, Fiona; Woll, Penella; Brüske, Irene; Wichmann, H-Erich; Manz, Judith; Muley, Thomas R; Risch, Angela; Rosenberger, Albert; Grankvist, Kjell; Johansson, Mikael; Shepherd, Frances A; Tsao, Ming-Sound; Arnold, Susanne M; Haura, Eric B; Bolca, Ciprian; Holcatova, Ivana; Janout, Vladimir; Kontic, Milica; Lissowska, Jolanta; Mukeria, Anush; Ognjanovic, Simona; Orlowski, Tadeusz M; Scelo, Ghislaine; Swiatkowska, Beata; Zaridze, David; Bakke, Per; Skaug, Vidar; Zienolddiny, Shanbeh; Duell, Eric J; Butler, Lesley M; Koh, Woon-Puay; Gao, Yu-Tang; Houlston, Richard S; McLaughlin, John; Stevens, Victoria L; Joubert, Philippe; Lamontagne, Maxime; Nickle, David C; Obeidat, Ma'en; Timens, Wim; Zhu, Bin; Song, Lei; Kachuri, Linda; Artigas, María Soler; Tobin, Martin D; Wain, Louise V; Rafnar, Thorunn; Thorgeirsson, Thorgeir E; Reginsson, Gunnar W; Stefansson, Kari; Hancock, Dana B; Bierut, Laura J; Spitz, Margaret R; Gaddis, Nathan C; Lutz, Sharon M; Gu, Fangyi; Johnson, Eric O; Kamal, Ahsan; Pikielny, Claudio; Zhu, Dakai; Lindströem, Sara; Jiang, Xia; Tyndale, Rachel F; Chenevix-Trench, Georgia; Beesley, Jonathan; Bossé, Yohan; Chanock, Stephen; Brennan, Paul; Landi, Maria Teresa; Amos, Christopher I

2017-07-01

Although several lung cancer susceptibility loci have been identified, much of the heritability for lung cancer remains unexplained. Here 14,803 cases and 12,262 controls of European descent were genotyped on the OncoArray and combined with existing data for an aggregated genome-wide association study (GWAS) analysis of lung cancer in 29,266 cases and 56,450 controls. We identified 18 susceptibility loci achieving genome-wide significance, including 10 new loci. The new loci highlight the striking heterogeneity in genetic susceptibility across the histological subtypes of lung cancer, with four loci associated with lung cancer overall and six loci associated with lung adenocarcinoma. Gene expression quantitative trait locus (eQTL) analysis in 1,425 normal lung tissue samples highlights RNASET2, SECISBP2L and NRG1 as candidate genes. Other loci include genes such as a cholinergic nicotinic receptor, CHRNA2, and the telomere-related genes OFBC1 and RTEL1. Further exploration of the target genes will continue to provide new insights into the etiology of lung cancer.
Genome-wide retroviral insertional tagging of genes involved in cancer in Cdkn2a-deficient mice

DEFF Research Database (Denmark)

Lund, Anders H; Turner, Geoffrey; Trubetskoy, Alla

2002-01-01

We have used large-scale insertional mutagenesis to identify functional landmarks relevant to cancer in the recently completed mouse genome sequence. We infected Cdkn2a(-/-) mice with Moloney murine leukemia virus (MoMuLV) to screen for loci that can participate in tumorigenesis in collaboration...... retroviral integration sites and mapped them against the mouse genome sequence databases from Celera and Ensembl. In addition to 17 insertions targeting gene loci known to be cancer-related, we identified a total of 37 new common insertion sites (CISs), of which 8 encode components of signaling pathways...... that are involved in cancer. The effectiveness of large-scale insertional mutagenesis in a sensitized genetic background is demonstrated by the preference for activation of MAP kinase signaling, collaborating with Cdkn2a loss in generating the lymphoid and myeloid tumors. Collectively, our results show that large...
A Site Specific Model And Analysis Of The Neutral Somatic Mutation Rate In Whole-Genome Cancer Data

DEFF Research Database (Denmark)

Bertl, Johanna; Guo, Qianyun; Rasmussen, Malene Juul

2017-01-01

Detailed modelling of the neutral mutational process in cancer cells is crucial for identifying driver mutations and understanding the mutational mechanisms that act during cancer development. The neutral mutational process is very complex: whole-genome analyses have revealed that the mutation ra...
The genomic analysis of lactic acidosis and acidosis response in human cancers.

Directory of Open Access Journals (Sweden)

Julia Ling-Yu Chen

2008-12-01

Full Text Available The tumor microenvironment has a significant impact on tumor development. Two important determinants in this environment are hypoxia and lactic acidosis. Although lactic acidosis has long been recognized as an important factor in cancer, relatively little is known about how cells respond to lactic acidosis and how that response relates to cancer phenotypes. We develop genome-scale gene expression studies to dissect transcriptional responses of primary human mammary epithelial cells to lactic acidosis and hypoxia in vitro and to explore how they are linked to clinical tumor phenotypes in vivo. The resulting experimental signatures of responses to lactic acidosis and hypoxia are evaluated in a heterogeneous set of breast cancer datasets. A strong lactic acidosis response signature identifies a subgroup of low-risk breast cancer patients having distinct metabolic profiles suggestive of a preference for aerobic respiration. The association of lactic acidosis response with good survival outcomes may relate to the role of lactic acidosis in directing energy generation toward aerobic respiration and utilization of other energy sources via inhibition of glycolysis. This "inhibition of glycolysis" phenotype in tumors is likely caused by the repression of glycolysis gene expression and Akt inhibition. Our study presents a genomic evaluation of the prognostic information of a lactic acidosis response independent of the hypoxic response. Our results identify causal roles of lactic acidosis in metabolic reprogramming, and the direct functional consequence of lactic acidosis pathway activity on cellular responses and tumor development. The study also demonstrates the utility of genomic analysis that maps expression-based findings from in vitro experiments to human samples to assess links to in vivo clinical phenotypes.
Genome-wide association study identifies shared risk loci common to two malignancies in golden retrievers.

Directory of Open Access Journals (Sweden)

Noriko Tonomura

2015-02-01

Full Text Available Dogs, with their breed-determined limited genetic background, are great models of human disease including cancer. Canine B-cell lymphoma and hemangiosarcoma are both malignancies of the hematologic system that are clinically and histologically similar to human B-cell non-Hodgkin lymphoma and angiosarcoma, respectively. Golden retrievers in the US show significantly elevated lifetime risk for both B-cell lymphoma (6% and hemangiosarcoma (20%. We conducted genome-wide association studies for hemangiosarcoma and B-cell lymphoma, identifying two shared predisposing loci. The two associated loci are located on chromosome 5, and together contribute ~20% of the risk of developing these cancers. Genome-wide p-values for the top SNP of each locus are 4.6×10-7 and 2.7×10-6, respectively. Whole genome resequencing of nine cases and controls followed by genotyping and detailed analysis identified three shared and one B-cell lymphoma specific risk haplotypes within the two loci, but no coding changes were associated with the risk haplotypes. Gene expression analysis of B-cell lymphoma tumors revealed that carrying the risk haplotypes at the first locus is associated with down-regulation of several nearby genes including the proximal gene TRPC6, a transient receptor Ca2+-channel involved in T-cell activation, among other functions. The shared risk haplotype in the second locus overlaps the vesicle transport and release gene STX8. Carrying the shared risk haplotype is associated with gene expression changes of 100 genes enriched for pathways involved in immune cell activation. Thus, the predisposing germ-line mutations in B-cell lymphoma and hemangiosarcoma appear to be regulatory, and affect pathways involved in T-cell mediated immune response in the tumor. This suggests that the interaction between the immune system and malignant cells plays a common role in the tumorigenesis of these relatively different cancers.
Perspective on Oncogenic Processes at the End of the Beginning of Cancer Genomics

NARCIS (Netherlands)

Ding, Li; Bailey, Matthew H.; Porta-Pardo, Eduard; Thorsson, Vesteinn; Colaprico, Antonio; Bertrand, Denis; Gibbs, David L.; Weerasinghe, Amila; Huang, Kuan lin; Tokheim, Collin; Cortés-Ciriano, Isidro; Jayasinghe, Reyka; Chen, Feng; Yu, Lihua; Sun, Sam; Olsen, Catharina; Kim, Jaegil; Taylor, Alison M.; Cherniack, Andrew D.; Akbani, Rehan; Suphavilai, Chayaporn; Nagarajan, Niranjan; Stuart, Joshua M.; Mills, Gordon B.; Wyczalkowski, Matthew A.; Vincent, Benjamin G.; Hutter, Carolyn M.; Zenklusen, Jean Claude; Hoadley, Katherine A.; Wendl, Michael C.; Shmulevich, llya; Lazar, Alexander J.; Wheeler, David A.; Getz, Gad; Caesar-Johnson, Samantha J.; Demchok, John A.; Felau, Ina; Kasapi, Melpomeni; Ferguson, Martin L.; Hutter, Carolyn M.; Sofia, Heidi J.; Tarnuzzer, Roy; Wang, Zhining; Yang, Liming; Zenklusen, Jean C.; Zhang, Jiashan (Julia); Chudamani, Sudha; Liu, Jia; Lolla, Laxmi; Naresh, Rashi; Pihl, Todd; Sun, Qiang; Wan, Yunhu; Wu, Ye; Cho, Juok; DeFreitas, Timothy; Frazer, Scott; Gehlenborg, Nils; Getz, Gad; Heiman, David I.; Kim, Jaegil; Lawrence, Michael S.; Lin, Pei; Meier, Sam; Noble, Michael S.; Saksena, Gordon; Voet, Doug; Zhang, Hailei; Bernard, Brady; Chambwe, Nyasha; Dhankani, Varsha; Knijnenburg, Theo; Kramer, Roger; Leinonen, Kalle; Liu, Yuexin; Miller, Michael; Reynolds, Sheila; Shmulevich, Ilya; Thorsson, Vesteinn; Zhang, Wei; Akbani, Rehan; Broom, Bradley M.; Hegde, Apurva M.; Ju, Zhenlin; Kanchi, Rupa S.; Korkut, Anil; Li, Jun; Liang, Han; Ling, Shiyun; Liu, Wenbin; Lu, Yiling; Mills, Gordon B.; Ng, Kwok Shing; Rao, Arvind; Ryan, Michael; Wang, Jing; Weinstein, John N.; Zhang, Jiexin; Abeshouse, Adam; Armenia, Joshua; Chakravarty, Debyani; Chatila, Walid K.; de Bruijn, Ino; Gao, Jianjiong; Gross, Benjamin E.; Heins, Zachary J.; Kundra, Ritika; La, Konnor; Ladanyi, Marc; Luna, Augustin; Nissan, Moriah G.; Ochoa, Angelica; Phillips, Sarah M.; Reznik, Ed; Sanchez-Vega, Francisco; Sander, Chris; Schultz, Nikolaus; Sheridan, Robert; Sumer, S. Onur; Sun, Yichao; Taylor, Barry S.; Wang, Jioajiao; Zhang, Hongxin; Anur, Pavana; Peto, Myron; Spellman, Paul; Benz, Christopher; Stuart, Joshua M.; Wong, Christopher K.; Yau, Christina; Hayes, D. Neil; Parker, Joel S.; Wilkerson, Matthew D.; Ally, Adrian; Balasundaram, Miruna; Bowlby, Reanne; Brooks, Denise; Carlsen, Rebecca; Chuah, Eric; Dhalla, Noreen; Holt, Robert; Jones, Steven J.M.; Kasaian, Katayoon; Lee, Darlene; Ma, Yussanne; Marra, Marco A.; Mayo, Michael; Moore, Richard A.; Mungall, Andrew J.; Mungall, Karen; Robertson, A. Gordon; Sadeghi, Sara; Schein, Jacqueline E.; Sipahimalani, Payal; Tam, Angela; Thiessen, Nina; Tse, Kane; Wong, Tina; Berger, Ashton C.; Beroukhim, Rameen; Cherniack, Andrew D.; Cibulskis, Carrie; Gabriel, Stacey B.; Gao, Galen F.; Ha, Gavin; Meyerson, Matthew; Schumacher, Steven E.; Shih, Juliann; Kucherlapati, Melanie H.; Kucherlapati, Raju S.; Baylin, Stephen; Cope, Leslie; Danilova, Ludmila; Bootwalla, Moiz S.; Lai, Phillip H.; Maglinte, Dennis T.; Van Den Berg, David J.; Weisenberger, Daniel J.; Auman, J. Todd; Balu, Saianand; Bodenheimer, Tom; Fan, Cheng; Hoadley, Katherine A.; Hoyle, Alan P.; Jefferys, Stuart R.; Jones, Corbin D.; Meng, Shaowu; Mieczkowski, Piotr A.; Mose, Lisle E.; Perou, Amy H.; Perou, Charles M.; Roach, Jeffrey; Shi, Yan; Simons, Janae V.; Skelly, Tara; Soloway, Matthew G.; Tan, Donghui; Veluvolu, Umadevi; Fan, Huihui; Hinoue, Toshinori; Laird, Peter W.; Shen, Hui; Zhou, Wanding; Bellair, Michelle; Chang, Kyle; Covington, Kyle; Creighton, Chad J.; Dinh, Huyen; Doddapaneni, Harsha Vardhan; Donehower, Lawrence A.; Drummond, Jennifer; Gibbs, Richard A.; Glenn, Robert; Hale, Walker; Han, Yi; Hu, Jianhong; Korchina, Viktoriya; Lee, Sandra; Lewis, Lora; Li, Wei; Liu, Xiuping; Morgan, Margaret; Morton, Donna; Muzny, Donna; Santibanez, Jireh; Sheth, Margi; Shinbrot, Eve; Wang, Linghua; Wang, Min; Wheeler, David A.; Xi, Liu; Zhao, Fengmei; Hess, Julian; Appelbaum, Elizabeth L.; Bailey, Matthew; Cordes, Matthew G.; Ding, Li; Fronick, Catrina C.; Fulton, Lucinda A.; Fulton, Robert S.; Kandoth, Cyriac; Mardis, Elaine R.; McLellan, Michael D.; Miller, Christopher A.; Schmidt, Heather K.; Wilson, Richard K.; Crain, Daniel; Curley, Erin; Gardner, Johanna; Lau, Kevin; Mallery, David; Morris, Scott; Paulauskis, Joseph; Penny, Robert; Shelton, Candace; Shelton, Troy; Sherman, Mark; Thompson, Eric; Yena, Peggy; Bowen, Jay; Gastier-Foster, Julie M.; Gerken, Mark; Leraas, Kristen M.; Lichtenberg, Tara M.; Ramirez, Nilsa C.; Wise, Lisa; Zmuda, Erik; Corcoran, Niall; Costello, Tony; Hovens, Christopher; Carvalho, Andre L.; de Carvalho, Ana C.; Fregnani, José H.; Longatto-Filho, Adhemar; Reis, Rui M.; Scapulatempo-Neto, Cristovam; Silveira, Henrique C.S.; Vidal, Daniel O.; Burnette, Andrew; Eschbacher, Jennifer; Hermes, Beth; Noss, Ardene; Singh, Rosy; Anderson, Matthew L.; Castro, Patricia D.; Ittmann, Michael; Huntsman, David; Kohl, Bernard; Le, Xuan; Thorp, Richard; Andry, Chris; Duffy, Elizabeth R.; Lyadov, Vladimir; Paklina, Oxana; Setdikova, Galiya; Shabunin, Alexey; Tavobilov, Mikhail; McPherson, Christopher; Warnick, Ronald; Berkowitz, Ross; Cramer, Daniel; Feltmate, Colleen; Horowitz, Neil; Kibel, Adam; Muto, Michael; Raut, Chandrajit P.; Malykh, Andrei; Barnholtz-Sloan, Jill S.; Barrett, Wendi; Devine, Karen; Fulop, Jordonna; Ostrom, Quinn T.; Shimmel, Kristen; Wolinsky, Yingli; Sloan, Andrew E.; De Rose, Agostino; Giuliante, Felice; Goodman, Marc; Karlan, Beth Y.; Hagedorn, Curt H.; Eckman, John; Harr, Jodi; Myers, Jerome; Tucker, Kelinda; Zach, Leigh Anne; Deyarmin, Brenda; Hu, Hai; Kvecher, Leonid; Larson, Caroline; Mural, Richard J.; Somiari, Stella; Vicha, Ales; Zelinka, Tomas; Bennett, Joseph; Iacocca, Mary; Rabeno, Brenda; Swanson, Patricia; Latour, Mathieu; Lacombe, Louis; Têtu, Bernard; Bergeron, Alain; McGraw, Mary; Staugaitis, Susan M.; Chabot, John; Hibshoosh, Hanina; Sepulveda, Antonia; Su, Tao; Wang, Timothy; Potapova, Olga; Voronina, Olga; Desjardins, Laurence; Mariani, Odette; Roman-Roman, Sergio; Sastre, Xavier; Stern, Marc Henri; Cheng, Feixiong; Signoretti, Sabina; Berchuck, Andrew; Bigner, Darell; Lipp, Eric; Marks, Jeffrey; McCall, Shannon; McLendon, Roger; Secord, Angeles; Sharp, Alexis; Behera, Madhusmita; Brat, Daniel J.; Chen, Amy; Delman, Keith; Force, Seth; Khuri, Fadlo; Magliocca, Kelly; Maithel, Shishir; Olson, Jeffrey J.; Owonikoko, Taofeek; Pickens, Alan; Ramalingam, Suresh; Shin, Dong M.; Sica, Gabriel; Van Meir, Erwin G.; Zhang, Hongzheng; Eijckenboom, Wil; Gillis, Ad; Korpershoek, Esther; Looijenga, Leendert; Oosterhuis, Wolter; Stoop, Hans; van Kessel, Kim E.; Zwarthoff, Ellen C.; Calatozzolo, Chiara; Cuppini, Lucia; Cuzzubbo, Stefania; DiMeco, Francesco; Finocchiaro, Gaetano; Mattei, Luca; Perin, Alessandro; Pollo, Bianca; Chen, Chu; Houck, John; Lohavanichbutr, Pawadee; Hartmann, Arndt; Stoehr, Christine; Stoehr, Robert; Taubert, Helge; Wach, Sven; Wullich, Bernd; Kycler, Witold; Murawa, Dawid; Wiznerowicz, Maciej; Chung, Ki; Edenfield, W. Jeffrey; Martin, Julie; Baudin, Eric; Bubley, Glenn; Bueno, Raphael; De Rienzo, Assunta; Richards, William G.; Kalkanis, Steven; Mikkelsen, Tom; Noushmehr, Houtan; Scarpace, Lisa; Girard, Nicolas; Aymerich, Marta; Campo, Elias; Giné, Eva; Guillermo, Armando López; Van Bang, Nguyen; Hanh, Phan Thi; Phu, Bui Duc; Tang, Yufang; Colman, Howard; Evason, Kimberley; Dottino, Peter R.; Martignetti, John A.; Gabra, Hani; Juhl, Hartmut; Akeredolu, Teniola; Stepa, Serghei; Hoon, Dave; Ahn, Keunsoo; Kang, Koo Jeong; Beuschlein, Felix; Breggia, Anne; Birrer, Michael; Bell, Debra; Borad, Mitesh; Bryce, Alan H.; Castle, Erik; Chandan, Vishal; Cheville, John; Copland, John A.; Farnell, Michael; Flotte, Thomas; Giama, Nasra; Ho, Thai; Kendrick, Michael; Kocher, Jean Pierre; Kopp, Karla; Moser, Catherine; Nagorney, David; O'Brien, Daniel; O'Neill, Brian Patrick; Patel, Tushar; Petersen, Gloria; Que, Florencia; Rivera, Michael; Roberts, Lewis; Smallridge, Robert; Smyrk, Thomas; Stanton, Melissa; Thompson, R. Houston; Torbenson, Michael; Yang, Ju Dong; Zhang, Lizhi; Brimo, Fadi; Ajani, Jaffer A.; Gonzalez, Ana Maria Angulo; Behrens, Carmen; Bondaruk, Jolanta; Broaddus, Russell; Czerniak, Bogdan; Esmaeli, Bita; Fujimoto, Junya; Gershenwald, Jeffrey; Guo, Charles; Lazar, Alexander J.; Logothetis, Christopher; Meric-Bernstam, Funda; Moran, Cesar; Ramondetta, Lois; Rice, David; Sood, Anil; Tamboli, Pheroze; Thompson, Timothy; Troncoso, Patricia; Tsao, Anne; Wistuba, Ignacio; Carter, Candace; Haydu, Lauren; Hersey, Peter; Jakrot, Valerie; Kakavand, Hojabr; Kefford, Richard; Lee, Kenneth; Long, Georgina; Mann, Graham; Quinn, Michael; Saw, Robyn; Scolyer, Richard; Shannon, Kerwin; Spillane, Andrew; Stretch, Jonathan; Synott, Maria; Thompson, John; Wilmott, James; Al-Ahmadie, Hikmat; Chan, Timothy A.; Ghossein, Ronald; Gopalan, Anuradha; Levine, Douglas A.; Reuter, Victor; Singer, Samuel; Singh, Bhuvanesh; Tien, Nguyen Viet; Broudy, Thomas; Mirsaidi, Cyrus; Nair, Praveen; Drwiega, Paul; Miller, Judy; Smith, Jennifer; Zaren, Howard; Park, Joong Won; Hung, Nguyen Phi; Kebebew, Electron; Linehan, W. Marston; Metwalli, Adam R.; Pacak, Karel; Pinto, Peter A.; Schiffman, Mark; Schmidt, Laura S.; Vocke, Cathy D.; Wentzensen, Nicolas; Worrell, Robert; Yang, Hannah; Moncrieff, Marc; Goparaju, Chandra; Melamed, Jonathan; Pass, Harvey; Botnariuc, Natalia; Caraman, Irina; Cernat, Mircea; Chemencedji, Inga; Clipca, Adrian; Doruc, Serghei; Gorincioi, Ghenadie; Mura, Sergiu; Pirtac, Maria; Stancul, Irina; Tcaciuc, Diana; Albert, Monique; Alexopoulou, Iakovina; Arnaout, Angel; Bartlett, John; Engel, Jay; Gilbert, Sebastien; Parfitt, Jeremy; Sekhon, Harman; Thomas, George; Rassl, Doris M.; Rintoul, Robert C.; Bifulco, Carlo; Tamakawa, Raina; Urba, Walter; Hayward, Nicholas; Timmers, Henri; Antenucci, Anna; Facciolo, Francesco; Grazi, Gianluca; Marino, Mirella; Merola, Roberta; de Krijger, Ronald; Gimenez-Roqueplo, Anne Paule; Piché, Alain; Chevalier, Simone; McKercher, Ginette; Birsoy, Kivanc; Barnett, Gene; Brewer, Cathy; Farver, Carol; Naska, Theresa; Pennell, Nathan A.; Raymond, Daniel; Schilero, Cathy; Smolenski, Kathy; Williams, Felicia; Morrison, Carl; Borgia, Jeffrey A.; Liptay, Michael J.; Pool, Mark; Seder, Christopher W.; Junker, Kerstin; Omberg, Larsson; Dinkin, Mikhail; Manikhas, George; Alvaro, Domenico; Bragazzi, Maria Consiglia; Cardinale, Vincenzo; Carpino, Guido; Gaudio, Eugenio; Chesla, David; Cottingham, Sandra; Dubina, Michael; Moiseenko, Fedor; Dhanasekaran, Renumathy; Becker, Karl Friedrich; Janssen, Klaus Peter; Slotta-Huspenina, Julia; Abdel-Rahman, Mohamed H.; Aziz, Dina; Bell, Sue; Cebulla, Colleen M.; Davis, Amy; Duell, Rebecca; Elder, J. Bradley; Hilty, Joe; Kumar, Bahavna; Lang, James; Lehman, Norman L.; Mandt, Randy; Nguyen, Phuong; Pilarski, Robert; Rai, Karan; Schoenfield, Lynn; Senecal, Kelly; Wakely, Paul; Hansen, Paul; Lechan, Ronald; Powers, James; Tischler, Arthur; Grizzle, William E.; Sexton, Katherine C.; Kastl, Alison; Henderson, Joel; Porten, Sima; Waldmann, Jens; Fassnacht, Martin; Asa, Sylvia L.; Schadendorf, Dirk; Couce, Marta; Graefen, Markus; Huland, Hartwig; Sauter, Guido; Schlomm, Thorsten; Simon, Ronald; Tennstedt, Pierre; Olabode, Oluwole; Nelson, Mark; Bathe, Oliver; Carroll, Peter R.; Chan, June M.; Disaia, Philip; Glenn, Pat; Kelley, Robin K.; Landen, Charles N.; Phillips, Joanna; Prados, Michael; Simko, Jeffry; Smith-McCune, Karen; VandenBerg, Scott; Roggin, Kevin; Fehrenbach, Ashley; Kendler, Ady; Sifri, Suzanne; Steele, Ruth; Jimeno, Antonio; Carey, Francis; Forgie, Ian; Mannelli, Massimo; Carney, Michael; Hernandez, Brenda; Campos, Benito; Herold-Mende, Christel; Jungk, Christin; Unterberg, Andreas; von Deimling, Andreas; Bossler, Aaron; Galbraith, Joseph; Jacobus, Laura; Knudson, Michael; Knutson, Tina; Ma, Deqin; Milhem, Mohammed; Sigmund, Rita; Godwin, Andrew K.; Madan, Rashna; Rosenthal, Howard G.; Adebamowo, Clement; Adebamowo, Sally N.; Boussioutas, Alex; Beer, David; Giordano, Thomas; Mes-Masson, Anne Marie; Saad, Fred; Bocklage, Therese; Landrum, Lisa; Mannel, Robert; Moore, Kathleen; Moxley, Katherine; Postier, Russel; Walker, Joan; Zuna, Rosemary; Feldman, Michael; Valdivieso, Federico; Dhir, Rajiv; Luketich, James; Pinero, Edna M.Mora; Quintero-Aguilo, Mario; Carlotti, Carlos Gilberto; Dos Santos, Jose Sebastião; Kemp, Rafael; Sankarankuty, Ajith; Tirapelli, Daniela; Catto, James; Agnew, Kathy; Swisher, Elizabeth; Creaney, Jenette; Robinson, Bruce; Shelley, Carl Simon; Godwin, Eryn M.; Kendall, Sara; Shipman, Cassaundra; Bradford, Carol; Carey, Thomas; Haddad, Andrea; Moyer, Jeffey; Peterson, Lisa; Prince, Mark; Rozek, Laura; Wolf, Gregory; Bowman, Rayleen; Fong, Kwun M.; Yang, Ian; Korst, Robert; Rathmell, W. Kimryn; Fantacone-Campbell, J. Leigh; Hooke, Jeffrey A.; Kovatich, Albert J.; Shriver, Craig D.; DiPersio, John; Drake, Bettina; Govindan, Ramaswamy; Heath, Sharon; Ley, Timothy; Van Tine, Brian; Westervelt, Peter; Rubin, Mark A.; Lee, Jung Il; Aredes, Natália D.; Mariamidze, Armaz

2018-01-01

The Cancer Genome Atlas (TCGA) has catalyzed systematic characterization of diverse genomic alterations underlying human cancers. At this historic junction marking the completion of genomic characterization of over 11,000 tumors from 33 cancer types, we present our current understanding of the
Genome-wide profiling of HPV integration in cervical cancer identifies clustered genomic hot spots and a potential microhomology-mediated integration mechanism

DEFF Research Database (Denmark)

Hu, Zheng; Zhu, Da; Wang, Wei

2015-01-01

Human papillomavirus (HPV) integration is a key genetic event in cervical carcinogenesis1. By conducting whole-genome sequencing and high-throughput viral integration detection, we identified 3,667 HPV integration breakpoints in 26 cervical intraepithelial neoplasias, 104 cervical carcinomas and ...
Genome-wide local ancestry approach identifies genes and variants associated with chemotherapeutic susceptibility in African Americans.

Directory of Open Access Journals (Sweden)

Heather E Wheeler

Full Text Available Chemotherapeutic agents are used in the treatment of many cancers, yet variable resistance and toxicities among individuals limit successful outcomes. Several studies have indicated outcome differences associated with ancestry among patients with various cancer types. Using both traditional SNP-based and newly developed gene-based genome-wide approaches, we investigated the genetics of chemotherapeutic susceptibility in lymphoblastoid cell lines derived from 83 African Americans, a population for which there is a disparity in the number of genome-wide studies performed. To account for population structure in this admixed population, we incorporated local ancestry information into our association model. We tested over 2 million SNPs and identified 325, 176, 240, and 190 SNPs that were suggestively associated with cytarabine-, 5'-deoxyfluorouridine (5'-DFUR-, carboplatin-, and cisplatin-induced cytotoxicity, respectively (p≤10(-4. Importantly, some of these variants are found only in populations of African descent. We also show that cisplatin-susceptibility SNPs are enriched for carboplatin-susceptibility SNPs. Using a gene-based genome-wide association approach, we identified 26, 11, 20, and 41 suggestive candidate genes for association with cytarabine-, 5'-DFUR-, carboplatin-, and cisplatin-induced cytotoxicity, respectively (p≤10(-3. Fourteen of these genes showed evidence of association with their respective chemotherapeutic phenotypes in the Yoruba from Ibadan, Nigeria (p<0.05, including TP53I11, COPS5 and GAS8, which are known to be involved in tumorigenesis. Although our results require further study, we have identified variants and genes associated with chemotherapeutic susceptibility in African Americans by using an approach that incorporates local ancestry information.
Genome evolution during progression to breast cancer

KAUST Repository

Newburger, D. E.; Kashef-Haghighi, D.; Weng, Z.; Salari, R.; Sweeney, R. T.; Brunner, A. L.; Zhu, S. X.; Guo, X.; Varma, S.; Troxell, M. L.; West, R. B.; Batzoglou, S.; Sidow, A.

2013-01-01

Cancer evolution involves cycles of genomic damage, epigenetic deregulation, and increased cellular proliferation that eventually culminate in the carcinoma phenotype. Early neoplasias, which are often found concurrently with carcinomas and are histologically distinguishable from normal breast tissue, are less advanced in phenotype than carcinomas and are thought to represent precursor stages. To elucidate their role in cancer evolution we performed comparative whole-genome sequencing of early neoplasias, matched normal tissue, and carcinomas from six patients, for a total of 31 samples. By using somatic mutations as lineage markers we built trees that relate the tissue samples within each patient. On the basis of these lineage trees we inferred the order, timing, and rates of genomic events. In four out of six cases, an early neoplasia and the carcinoma share a mutated common ancestor with recurring aneuploidies, and in all six cases evolution accelerated in the carcinoma lineage. Transition spectra of somatic mutations are stable and consistent across cases, suggesting that accumulation of somatic mutations is a result of increased ancestral cell division rather than specific mutational mechanisms. In contrast to highly advanced tumors that are the focus of much of the current cancer genome sequencing, neither the early neoplasia genomes nor the carcinomas are enriched with potentially functional somatic point mutations. Aneuploidies that occur in common ancestors of neoplastic and tumor cells are the earliest events that affect a large number of genes and may predispose breast tissue to eventual development of invasive carcinoma.
Genome evolution during progression to breast cancer

KAUST Repository

Newburger, D. E.

2013-04-08

Cancer evolution involves cycles of genomic damage, epigenetic deregulation, and increased cellular proliferation that eventually culminate in the carcinoma phenotype. Early neoplasias, which are often found concurrently with carcinomas and are histologically distinguishable from normal breast tissue, are less advanced in phenotype than carcinomas and are thought to represent precursor stages. To elucidate their role in cancer evolution we performed comparative whole-genome sequencing of early neoplasias, matched normal tissue, and carcinomas from six patients, for a total of 31 samples. By using somatic mutations as lineage markers we built trees that relate the tissue samples within each patient. On the basis of these lineage trees we inferred the order, timing, and rates of genomic events. In four out of six cases, an early neoplasia and the carcinoma share a mutated common ancestor with recurring aneuploidies, and in all six cases evolution accelerated in the carcinoma lineage. Transition spectra of somatic mutations are stable and consistent across cases, suggesting that accumulation of somatic mutations is a result of increased ancestral cell division rather than specific mutational mechanisms. In contrast to highly advanced tumors that are the focus of much of the current cancer genome sequencing, neither the early neoplasia genomes nor the carcinomas are enriched with potentially functional somatic point mutations. Aneuploidies that occur in common ancestors of neoplastic and tumor cells are the earliest events that affect a large number of genes and may predispose breast tissue to eventual development of invasive carcinoma.

Identification of somatic mutations in cancer through Bayesian-based analysis of sequenced genome pairs.

Science.gov (United States)

Christoforides, Alexis; Carpten, John D; Weiss, Glen J; Demeure, Michael J; Von Hoff, Daniel D; Craig, David W

2013-05-04

The field of cancer genomics has rapidly adopted next-generation sequencing (NGS) in order to study and characterize malignant tumors with unprecedented resolution. In particular for cancer, one is often trying to identify somatic mutations--changes specific to a tumor and not within an individual's germline. However, false positive and false negative detections often result from lack of sufficient variant evidence, contamination of the biopsy by stromal tissue, sequencing errors, and the erroneous classification of germline variation as tumor-specific. We have developed a generalized Bayesian analysis framework for matched tumor/normal samples with the purpose of identifying tumor-specific alterations such as single nucleotide mutations, small insertions/deletions, and structural variation. We describe our methodology, and discuss its application to other types of paired-tissue analysis such as the detection of loss of heterozygosity as well as allelic imbalance. We also demonstrate the high level of sensitivity and specificity in discovering simulated somatic mutations, for various combinations of a) genomic coverage and b) emulated heterogeneity. We present a Java-based implementation of our methods named Seurat, which is made available for free academic use. We have demonstrated and reported on the discovery of different types of somatic change by applying Seurat to an experimentally-derived cancer dataset using our methods; and have discussed considerations and practices regarding the accurate detection of somatic events in cancer genomes. Seurat is available at https://sites.google.com/site/seuratsomatic.
Systematic Identification and Assessment of Therapeutic Targets for Breast Cancer Based on Genome-Wide RNA Interference Transcriptomes

Directory of Open Access Journals (Sweden)

Yang Liu

2017-02-01

Full Text Available With accumulating public omics data, great efforts have been made to characterize the genetic heterogeneity of breast cancer. However, identifying novel targets and selecting the best from the sizeable lists of candidate targets is still a key challenge for targeted therapy, largely owing to the lack of economical, efficient and systematic discovery and assessment to prioritize potential therapeutic targets. Here, we describe an approach that combines the computational evaluation and objective, multifaceted assessment to systematically identify and prioritize targets for biological validation and therapeutic exploration. We first establish the reference gene expression profiles from breast cancer cell line MCF7 upon genome-wide RNA interference (RNAi of a total of 3689 genes, and the breast cancer query signatures using RNA-seq data generated from tissue samples of clinical breast cancer patients in the Cancer Genome Atlas (TCGA. Based on gene set enrichment analysis, we identified a set of 510 genes that when knocked down could significantly reverse the transcriptome of breast cancer state. We then perform multifaceted assessment to analyze the gene set to prioritize potential targets for gene therapy. We also propose drug repurposing opportunities and identify potentially druggable proteins that have been poorly explored with regard to the discovery of small-molecule modulators. Finally, we obtained a small list of candidate therapeutic targets for four major breast cancer subtypes, i.e., luminal A, luminal B, HER2+ and triple negative breast cancer. This RNAi transcriptome-based approach can be a helpful paradigm for relevant researches to identify and prioritize candidate targets for experimental validation.
The expanding universe of cohesin functions: a new genome stability caretaker involved in human disease and cancer.

Science.gov (United States)

Mannini, Linda; Menga, Stefania; Musio, Antonio

2010-06-01

Cohesin is responsible for sister chromatid cohesion, ensuring the correct chromosome segregation. Beyond this role, cohesin and regulatory cohesin genes seem to play a role in preserving genome stability and gene transcription regulation. DNA damage is thought to be a major culprit for many human diseases, including cancer. Our present knowledge of the molecular basis underlying genome instability is extremely limited. Mutations in cohesin genes cause human diseases such as Cornelia de Lange syndrome and Roberts syndrome/SC phocomelia, and all the cell lines derived from affected patients show genome instability. Cohesin mutations have also been identified in colorectal cancer. Here, we will discuss the human disorders caused by alterations of cohesin function, with emphasis on the emerging role of cohesin as a genome stability caretaker.
A Million Cancer Genome Warehouse

Science.gov (United States)

2012-11-20

of a national program for Cancer Information Donors, the American Society for Clinical Oncology (ASCO) has proposed a rapid learning system for...or Scala and Spark; “scrum” organization of small programming teams; calculating “velocity” to predict time to develop new features; and Agile...2012 to 00-00-2012 4. TITLE AND SUBTITLE A Million Cancer Genome Warehouse 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6
An expanding universe of the non-coding genome in cancer biology.

Science.gov (United States)

Xue, Bin; He, Lin

2014-06-01

Neoplastic transformation is caused by accumulation of genetic and epigenetic alterations that ultimately convert normal cells into tumor cells with uncontrolled proliferation and survival, unlimited replicative potential and invasive growth [Hanahan,D. et al. (2011) Hallmarks of cancer: the next generation. Cell, 144, 646-674]. Although the majority of the cancer studies have focused on the functions of protein-coding genes, emerging evidence has started to reveal the importance of the vast non-coding genome, which constitutes more than 98% of the human genome. A number of non-coding RNAs (ncRNAs) derived from the 'dark matter' of the human genome exhibit cancer-specific differential expression and/or genomic alterations, and it is increasingly clear that ncRNAs, including small ncRNAs and long ncRNAs (lncRNAs), play an important role in cancer development by regulating protein-coding gene expression through diverse mechanisms. In addition to ncRNAs, nearly half of the mammalian genomes consist of transposable elements, particularly retrotransposons. Once depicted as selfish genomic parasites that propagate at the expense of host fitness, retrotransposon elements could also confer regulatory complexity to the host genomes during development and disease. Reactivation of retrotransposons in cancer, while capable of causing insertional mutagenesis and genome rearrangements to promote oncogenesis, could also alter host gene expression networks to favor tumor development. Taken together, the functional significance of non-coding genome in tumorigenesis has been previously underestimated, and diverse transcripts derived from the non-coding genome could act as integral functional components of the oncogene and tumor suppressor network. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.
Identifying Breast Cancer Oncogenes

Science.gov (United States)

2011-10-01

cells we observed that it promoted transformation of HMLE cells, suggesting a tumor suppressive role of Merlin in breast cancer (Figure 4B). A...08-1-0767 TITLE: Identifying Breast Cancer Oncogenes PRINCIPAL INVESTIGATOR: Yashaswi Shrestha...Standard Form 298 (Rev. 8-98) Prescribed by ANSI Std. Z39.18 W81XWH-08-1-0767 Identifying Breast Cancer Oncogenes Yashaswi Shrestha Dana-Farber
Genomic Profiling of Prostate Cancers from African American Men

Directory of Open Access Journals (Sweden)

Patricia Castro

2009-03-01

Full Text Available African American (AA men have a higher incidence and significantly higher mortality rates from prostate cancer than white men, but the biological basis for these differences are poorly understood. Few studies have been carried out to determine whether there are areas of allelic loss or gain in prostate cancers from AA men that are over-represented in or specific to this group. To better understand the molecular mechanisms of prostate cancer in AA men, we have analyzed 20 prostate cancers from AA men with high-density single-nucleotide polymorphism arrays to detect genomic copy number alterations. We identified 17 regions showing significant loss and 4 regions with significant gains. Most of these regions had been linked to prostate cancer by previous studies of copy number alterations of predominantly white patients. We identified a novel region of loss at 4p16.3, which has been shown to be lost in breast, colon, and bladder cancers. Comparison of our primary tumors with tumors from white patients from a previously published cohort with similar pathological characteristics showed higher frequency of loss of at numerous loci including 6q13-22, 8p21, 13q13-14, and 16q11-24 and gains of 7p21 and 8q24, all of which had higher frequencies in metastatic lesions in this previously published cohort. Thus, the clinically localized cancers from AA men more closely resembled metastatic cancers from white men. This difference may in part explain the more aggressive clinical behavior of prostate cancer in AA men.
Novel genomes and genome constitutions identified by GISH and 5S rDNA and knotted1 genomic sequences in the genus Setaria.

Science.gov (United States)

Zhao, Meicheng; Zhi, Hui; Doust, Andrew N; Li, Wei; Wang, Yongfang; Li, Haiquan; Jia, Guanqing; Wang, Yongqiang; Zhang, Ning; Diao, Xianmin

2013-04-11

The Setaria genus is increasingly of interest to researchers, as its two species, S. viridis and S. italica, are being developed as models for understanding C4 photosynthesis and plant functional genomics. The genome constitution of Setaria species has been studied in the diploid species S. viridis, S. adhaerans and S. grisebachii, where three genomes A, B and C were identified respectively. Two allotetraploid species, S. verticillata and S. faberi, were found to have AABB genomes, and one autotetraploid species, S. queenslandica, with an AAAA genome, has also been identified. The genomes and genome constitutions of most other species remain unknown, even though it was thought there are approximately 125 species in the genus distributed world-wide. GISH was performed to detect the genome constitutions of Eurasia species of S. glauca, S. plicata, and S. arenaria, with the known A, B and C genomes as probes. No or very poor hybridization signal was detected indicating that their genomes are different from those already described. GISH was also performed reciprocally between S. glauca, S. plicata, and S. arenaria genomes, but no hybridization signals between each other were found. The two sets of chromosomes of S. lachnea both hybridized strong signals with only the known C genome of S. grisebachii. Chromosomes of Qing 9, an accession formerly considered as S. viridis, hybridized strong signal only to B genome of S. adherans. Phylogenetic trees constructed with 5S rDNA and knotted1 markers, clearly classify the samples in this study into six clusters, matching the GISH results, and suggesting that the F genome of S. arenaria is basal in the genus. Three novel genomes in the Setaria genus were identified and designated as genome D (S. glauca), E (S. plicata) and F (S. arenaria) respectively. The genome constitution of tetraploid S. lachnea is putatively CCC'C'. Qing 9 is a B genome species indigenous to China and is hypothesized to be a newly identified species. The
Genomic suppression subtractive hybridization as a tool to identify differences in mycorrhizal fungal genomes.

Science.gov (United States)

Murat, Claude; Zampieri, Elisa; Vallino, Marta; Daghino, Stefania; Perotto, Silvia; Bonfante, Paola

2011-05-01

Characterization of genomic variation among different microbial species, or different strains of the same species, is a field of significant interest with a wide range of potential applications. We have investigated the genomic variation in mycorrhizal fungal genomes through genomic suppressive subtractive hybridization. The comparison was between phylogenetically distant and close truffle species (Tuber spp.), and between isolates of the ericoid mycorrhizal fungus Oidiodendron maius featuring different degrees of metal tolerance. In the interspecies experiment, almost all the sequences that were identified in the Tuber melanosporum genome and absent in Tuber borchii and Tuber indicum corresponded to transposable elements. In the intraspecies comparison, some specific sequences corresponded to regions coding for enzymes, among them a glutathione synthetase known to be involved in metal tolerance. This approach is a quick and rather inexpensive tool to develop molecular markers for mycorrhizal fungi tracking and barcoding, to identify functional genes and to investigate the genome plasticity, adaptation and evolution. © 2011 Federation of European Microbiological Societies. Published by Blackwell Publishing Ltd. All rights reserved.
The Naked Mole Rat Genome Resource : facilitating analyses of cancer and longevity-related adaptations

OpenAIRE

Keane, Michael; Craig, Thomas; Alfoldi, Jessica; Berlin, Aaron M; Johnson, Jeremy; Seluanov, Andrei; Gorbunova, Vera; Di Palma, Federica; Lindblad-Toh, Kerstin; Church, George M; de Magalhaes, Joao Pedro

2014-01-01

MOTIVATION: The naked mole rat (Heterocephalus glaber) is an exceptionally long-lived and cancer-resistant rodent native to East Africa. Although its genome was previously sequenced, here we report a new assembly sequenced by us with substantially higher N50 values for scaffolds and contigs. RESULTS: We analyzed the annotation of this new improved assembly and identified candidate genomic adaptations which may have contributed to the evolution of the naked mole rat's extraordinary traits, inc...
Applications of Support Vector Machine (SVM) Learning in Cancer Genomics

OpenAIRE

HUANG, SHUJUN; CAI, NIANGUANG; PACHECO, PEDRO PENZUTI; NARANDES, SHAVIRA; WANG, YANG; XU, WAYNE

2017-01-01

Machine learning with maximization (support) of separating margin (vector), called support vector machine (SVM) learning, is a powerful classification tool that has been used for cancer genomic classification or subtyping. Today, as advancements in high-throughput technologies lead to production of large amounts of genomic and epigenomic data, the classification feature of SVMs is expanding its use in cancer genomics, leading to the discovery of new biomarkers, new drug targets, and a better ...
Databases and web tools for cancer genomics study.

Science.gov (United States)

Yang, Yadong; Dong, Xunong; Xie, Bingbing; Ding, Nan; Chen, Juan; Li, Yongjun; Zhang, Qian; Qu, Hongzhu; Fang, Xiangdong

2015-02-01

Publicly-accessible resources have promoted the advance of scientific discovery. The era of genomics and big data has brought the need for collaboration and data sharing in order to make effective use of this new knowledge. Here, we describe the web resources for cancer genomics research and rate them on the basis of the diversity of cancer types, sample size, omics data comprehensiveness, and user experience. The resources reviewed include data repository and analysis tools; and we hope such introduction will promote the awareness and facilitate the usage of these resources in the cancer research community. Copyright © 2015 The Authors. Production and hosting by Elsevier Ltd.. All rights reserved.
A genome-wide association study of upper aerodigestive tract cancers conducted within the INHANCE consortium.

LENUS (Irish Health Repository)

McKay, James D

2011-03-01

Genome-wide association studies (GWAS) have been successful in identifying common genetic variation involved in susceptibility to etiologically complex disease. We conducted a GWAS to identify common genetic variation involved in susceptibility to upper aero-digestive tract (UADT) cancers. Genome-wide genotyping was carried out using the Illumina HumanHap300 beadchips in 2,091 UADT cancer cases and 3,513 controls from two large European multi-centre UADT cancer studies, as well as 4,821 generic controls. The 19 top-ranked variants were investigated further in an additional 6,514 UADT cancer cases and 7,892 controls of European descent from an additional 13 UADT cancer studies participating in the INHANCE consortium. Five common variants presented evidence for significant association in the combined analysis (p ≤ 5 × 10⁻⁷). Two novel variants were identified, a 4q21 variant (rs1494961, p = 1×10⁻⁸) located near DNA repair related genes HEL308 and FAM175A (or Abraxas) and a 12q24 variant (rs4767364, p =2 × 10⁻⁸) located in an extended linkage disequilibrium region that contains multiple genes including the aldehyde dehydrogenase 2 (ALDH2) gene. Three remaining variants are located in the ADH gene cluster and were identified previously in a candidate gene study involving some of these samples. The association between these three variants and UADT cancers was independently replicated in 5,092 UADT cancer cases and 6,794 controls non-overlapping samples presented here (rs1573496-ADH7, p = 5 × 10⁻⁸); rs1229984-ADH1B, p = 7 × 10⁻⁹; and rs698-ADH1C, p = 0.02). These results implicate two variants at 4q21 and 12q24 and further highlight three ADH variants in UADT cancer susceptibility.
A genome-wide association study of upper aerodigestive tract cancers conducted within the INHANCE consortium.

Directory of Open Access Journals (Sweden)

James D McKay

2011-03-01

Full Text Available Genome-wide association studies (GWAS have been successful in identifying common genetic variation involved in susceptibility to etiologically complex disease. We conducted a GWAS to identify common genetic variation involved in susceptibility to upper aero-digestive tract (UADT cancers. Genome-wide genotyping was carried out using the Illumina HumanHap300 beadchips in 2,091 UADT cancer cases and 3,513 controls from two large European multi-centre UADT cancer studies, as well as 4,821 generic controls. The 19 top-ranked variants were investigated further in an additional 6,514 UADT cancer cases and 7,892 controls of European descent from an additional 13 UADT cancer studies participating in the INHANCE consortium. Five common variants presented evidence for significant association in the combined analysis (p ≤ 5 × 10⁻⁷. Two novel variants were identified, a 4q21 variant (rs1494961, p = 1×10⁻⁸ located near DNA repair related genes HEL308 and FAM175A (or Abraxas and a 12q24 variant (rs4767364, p =2 × 10⁻⁸ located in an extended linkage disequilibrium region that contains multiple genes including the aldehyde dehydrogenase 2 (ALDH2 gene. Three remaining variants are located in the ADH gene cluster and were identified previously in a candidate gene study involving some of these samples. The association between these three variants and UADT cancers was independently replicated in 5,092 UADT cancer cases and 6,794 controls non-overlapping samples presented here (rs1573496-ADH7, p = 5 × 10⁻⁸; rs1229984-ADH1B, p = 7 × 10⁻⁹; and rs698-ADH1C, p = 0.02. These results implicate two variants at 4q21 and 12q24 and further highlight three ADH variants in UADT cancer susceptibility.
Integrating cancer genomic data into electronic health records

Directory of Open Access Journals (Sweden)

Jeremy L. Warner

2016-10-01

Full Text Available Abstract The rise of genomically targeted therapies and immunotherapy has revolutionized the practice of oncology in the last 10–15 years. At the same time, new technologies and the electronic health record (EHR in particular have permeated the oncology clinic. Initially designed as billing and clinical documentation systems, EHR systems have not anticipated the complexity and variety of genomic information that needs to be reviewed, interpreted, and acted upon on a daily basis. Improved integration of cancer genomic data with EHR systems will help guide clinician decision making, support secondary uses, and ultimately improve patient care within oncology clinics. Some of the key factors relating to the challenge of integrating cancer genomic data into EHRs include: the bioinformatics pipelines that translate raw genomic data into meaningful, actionable results; the role of human curation in the interpretation of variant calls; and the need for consistent standards with regard to genomic and clinical data. Several emerging paradigms for integration are discussed in this review, including: non-standardized efforts between individual institutions and genomic testing laboratories; “middleware” products that portray genomic information, albeit outside of the clinical workflow; and application programming interfaces that have the potential to work within clinical workflow. The critical need for clinical-genomic knowledge bases, which can be independent or integrated into the aforementioned solutions, is also discussed.
Mechanisms of Base Substitution Mutagenesis in Cancer Genomes

Directory of Open Access Journals (Sweden)

Albino Bacolla

2014-03-01

Full Text Available Cancer genome sequence data provide an invaluable resource for inferring the key mechanisms by which mutations arise in cancer cells, favoring their survival, proliferation and invasiveness. Here we examine recent advances in understanding the molecular mechanisms responsible for the predominant type of genetic alteration found in cancer cells, somatic single base substitutions (SBSs. Cytosine methylation, demethylation and deamination, charge transfer reactions in DNA, DNA replication timing, chromatin status and altered DNA proofreading activities are all now known to contribute to the mechanisms leading to base substitution mutagenesis. We review current hypotheses as to the major processes that give rise to SBSs and evaluate their relative relevance in the light of knowledge acquired from cancer genome sequencing projects and the study of base modifications, DNA repair and lesion bypass. Although gene expression data on APOBEC3B enzymes provide support for a role in cancer mutagenesis through U:G mismatch intermediates, the enzyme preference for single-stranded DNA may limit its activity genome-wide. For SBSs at both CG:CG and YC:GR sites, we outline evidence for a prominent role of damage by charge transfer reactions that follow interactions of the DNA with reactive oxygen species (ROS and other endogenous or exogenous electron-abstracting molecules.
Mechanisms of base substitution mutagenesis in cancer genomes.

Science.gov (United States)

Bacolla, Albino; Cooper, David N; Vasquez, Karen M

2014-03-05

Cancer genome sequence data provide an invaluable resource for inferring the key mechanisms by which mutations arise in cancer cells, favoring their survival, proliferation and invasiveness. Here we examine recent advances in understanding the molecular mechanisms responsible for the predominant type of genetic alteration found in cancer cells, somatic single base substitutions (SBSs). Cytosine methylation, demethylation and deamination, charge transfer reactions in DNA, DNA replication timing, chromatin status and altered DNA proofreading activities are all now known to contribute to the mechanisms leading to base substitution mutagenesis. We review current hypotheses as to the major processes that give rise to SBSs and evaluate their relative relevance in the light of knowledge acquired from cancer genome sequencing projects and the study of base modifications, DNA repair and lesion bypass. Although gene expression data on APOBEC3B enzymes provide support for a role in cancer mutagenesis through U:G mismatch intermediates, the enzyme preference for single-stranded DNA may limit its activity genome-wide. For SBSs at both CG:CG and YC:GR sites, we outline evidence for a prominent role of damage by charge transfer reactions that follow interactions of the DNA with reactive oxygen species (ROS) and other endogenous or exogenous electron-abstracting molecules.
Genomics, Endoscopy, and Control of Gastroesophageal Cancers: A PerspectiveSummary

Directory of Open Access Journals (Sweden)

Brian J. Reid

2017-05-01

Full Text Available In The Cancer Genome Atlas the goals were to define how to treat advanced cancers with targeted therapy. However, the challenges facing cancer interception for early detection and prevention include length bias in which current screening and surveillance approaches frequently miss rapidly progressing cancers that then present at advanced stages in the clinic with symptoms (underdiagnosis. In contrast, many early detection strategies detect benign conditions that may never progress to cancer during a lifetime, and the patient dies of unrelated causes (overdiagnosis. This challenge to cancer interception is believed to be due to the speed at which the neoplasm evolves, called length bias sampling; rapidly progressing cancers are missed by current early detection strategies. In contrast, slowly or non-progressing cancers or their precursors are selectively detected. This has led to the concept of cancer interception, which can be defined as active interception of a biological process that drives cancer development before the patient presents in the clinic with an advanced, symptomatic cancer. The solutions needed to advance strategies for cancer interception require assessing the rate at which the cancer evolves over time and space. This is an essential challenge that needs to be addressed by robust study designs including normal and non-progressing controls when known to be appropriate. Keywords: Barrett's Esophagus, Biomarkers, Chromosome Aberrations, Esophageal Neoplasms, Gastroesophageal Reflux, Genomic Instability, Genomics, Stomach
Genomic and oncoproteomic advances in detection and treatment of colorectal cancer.

LENUS (Irish Health Repository)

McHugh, Seamus M

2012-02-01

AIMS: We will examine the latest advances in genomic and proteomic laboratory technology. Through an extensive literature review we aim to critically appraise those studies which have utilized these latest technologies and ascertain their potential to identify clinically useful biomarkers. METHODS: An extensive review of the literature was carried out in both online medical journals and through the Royal College of Surgeons in Ireland library. RESULTS: Laboratory technology has advanced in the fields of genomics and oncoproteomics. Gene expression profiling with DNA microarray technology has allowed us to begin genetic profiling of colorectal cancer tissue. The response to chemotherapy can differ amongst individual tumors. For the first time researchers have begun to isolate and identify the genes responsible. New laboratory techniques allow us to isolate proteins preferentially expressed in colorectal cancer tissue. This could potentially lead to identification of a clinically useful protein biomarker in colorectal cancer screening and treatment. CONCLUSION: If a set of discriminating genes could be used for characterization and prediction of chemotherapeutic response, an individualized tailored therapeutic regime could become the standard of care for those undergoing systemic treatment for colorectal cancer. New laboratory techniques of protein identification may eventually allow identification of a clinically useful biomarker that could be used for screening and treatment. At present however, both expression of different gene signatures and isolation of various protein peaks has been limited by study size. Independent multi-centre correlation of results with larger sample sizes is needed to allow translation into clinical practice.
Genomic and oncoproteomic advances in detection and treatment of colorectal cancer.

LENUS (Irish Health Repository)

McHugh, Seamus M

2009-01-01

AIMS: We will examine the latest advances in genomic and proteomic laboratory technology. Through an extensive literature review we aim to critically appraise those studies which have utilized these latest technologies and ascertain their potential to identify clinically useful biomarkers. METHODS: An extensive review of the literature was carried out in both online medical journals and through the Royal College of Surgeons in Ireland library. RESULTS: Laboratory technology has advanced in the fields of genomics and oncoproteomics. Gene expression profiling with DNA microarray technology has allowed us to begin genetic profiling of colorectal cancer tissue. The response to chemotherapy can differ amongst individual tumors. For the first time researchers have begun to isolate and identify the genes responsible. New laboratory techniques allow us to isolate proteins preferentially expressed in colorectal cancer tissue. This could potentially lead to identification of a clinically useful protein biomarker in colorectal cancer screening and treatment. CONCLUSION: If a set of discriminating genes could be used for characterization and prediction of chemotherapeutic response, an individualized tailored therapeutic regime could become the standard of care for those undergoing systemic treatment for colorectal cancer. New laboratory techniques of protein identification may eventually allow identification of a clinically useful biomarker that could be used for screening and treatment. At present however, both expression of different gene signatures and isolation of various protein peaks has been limited by study size. Independent multi-centre correlation of results with larger sample sizes is needed to allow translation into clinical practice.

Fine-scale mapping of 8q24 locus identifies multiple independent risk variants for breast cancer

NARCIS (Netherlands)

J. Shi (Jiajun); Zhang, Y. (Yanfeng); W. Zheng (Wei); K. Michailidou (Kyriaki); M. Ghoussaini (Maya); M.K. Bolla (Manjeet K.); Wang, Q. (Qin); J. Dennis (Joe); Lush, M. (Michael); R.L. Milne (Roger); X.-O. Shu (Xiao-Ou); J. Beesley (Jonathan); S. Kar (Siddhartha); I.L. Andrulis (Irene); H. Anton-Culver (Hoda); Arndt, V. (Volker); M.W. Beckmann (Matthias); Z. Zhao (Zhiguo); Guo, X. (Xingyi); J. Benítez (Javier); A. Beeghly-Fadiel (Alicia); W.J. Blot (William); N.V. Bogdanova (Natalia); S.E. Bojesen (Stig); H. Brauch (Hiltrud); H. Brenner (Hermann); L.A. Brinton (Louise); A. Broeks (Annegien); T. Brüning (Thomas); B. Burwinkel (Barbara); H. Cai (Hui); S. Canisius (Sander); J. Chang-Claude (Jenny); Choi, J.-Y. (Ji-Yeob); F.J. Couch (Fergus); A. Cox (Angela); S.S. Cross (Simon); K. Czene (Kamila); H. Darabi (Hatef); P. Devilee (Peter); A. Droit (Arnaud); T. Dörk (Thilo); P.A. Fasching (Peter); O. Fletcher (Olivia); H. Flyger (Henrik); F. Fostira (Florentia); Gaborieau, V. (Valerie); M. García-Closas (Montserrat); G.G. Giles (Graham); Grip, M. (Mervi); P. Guénel (Pascal); C.A. Haiman (Christopher A.); U. Hamann (Ute); J.M. Hartman (Joost); X. Miao; A. Hollestelle (Antoinette); J.L. Hopper (John); Hsiung, C.-N. (Chia-Ni); H. Ito (Hidemi); A. Jakubowska (Anna); Johnson, N. (Nichola); D. Torres (Diana); M. Kabisch (Maria); D. Kang (Daehee); S. Khan (Sofia); J.A. Knight (Julia); V-M. Kosma (Veli-Matti); Lambrechts, D. (Diether); J. Li (Jingmei); A. Lindblom (Annika); A. Lophatananon (Artitaya); J. Lubinski (Jan); A. Mannermaa (Arto); S. Manoukian (Siranoush); L. Le Marchand (Loic); S. Margolin (Sara); Marme, F. (Frederik); K. Matsuo (Keitaro); C.A. McLean (Catriona Ann); A. Meindl (Alfons); K.R. Muir (K.); S.L. Neuhausen (Susan); H. Nevanlinna (Heli); S. Nord (Silje); A.-L. Borresen-Dale (Anne-Lise); J.E. Olson (Janet); N. Orr (Nick); A.M.W. van den Ouweland (Ans); P. Peterlongo (Paolo); T.C. Putti (Thomas Choudary); Rudolph, A. (Anja); Sangrajrang, S. (Suleeporn); E.J. Sawyer (Elinor); M.K. Schmidt (Marjanka); R.K. Schmutzler (Rita); C.-Y. Shen (Chen-Yang); M.-F. Hou (Ming-Feng); M. Shrubsole (Martha); M.C. Southey (Melissa); A.J. Swerdlow (Anthony ); Hwang Teo, S. (Soo); B. Thienpont (Bernard); A.E. Toland (Amanda); R.A.E.M. Tollenaar (Rob); I.P. Tomlinson (Ian); T. Truong (Thérèse); C.-C. Tseng (Chiu-Chen); W. Wen (Wanqing); R. Winqvist (Robert); A.H. Wu (Anna); C. Har Yip (Cheng); P.M. Zamora (Pilar M.); Zheng, Y. (Ying); O.A.M. Floris; Cheng, C.-Y. (Ching-Yu); M.J. Hooning (Maartje); J.W.M. Martens (John); C.M. Seynaeve (Caroline); V. Kristensen (Vessela); P. Hall (Per); P.D.P. Pharoah (Paul); J. Simard (Jacques); G. Chenevix-Trench (Georgia); A.M. Dunning (Alison); A.C. Antoniou (Antonis C.); D.F. Easton (Douglas F.); Q. Cai (Qiuyin); J. Long (Jirong)

2016-01-01

textabstractPrevious genome-wide association studies among women of European ancestry identified two independent breast cancer susceptibility loci represented by single nucleotide polymorphisms (SNPs) rs13281615 and rs11780156 at 8q24. A fine-mapping study across 2.06 Mb
Gene-environment interaction involving recently identified colorectal cancer susceptibility loci

Science.gov (United States)

Kantor, Elizabeth D.; Hutter, Carolyn M.; Minnier, Jessica; Berndt, Sonja I.; Brenner, Hermann; Caan, Bette J.; Campbell, Peter T.; Carlson, Christopher S.; Casey, Graham; Chan, Andrew T.; Chang-Claude, Jenny; Chanock, Stephen J.; Cotterchio, Michelle; Du, Mengmeng; Duggan, David; Fuchs, Charles S.; Giovannucci, Edward L.; Gong, Jian; Harrison, Tabitha A.; Hayes, Richard B.; Henderson, Brian E.; Hoffmeister, Michael; Hopper, John L.; Jenkins, Mark A.; Jiao, Shuo; Kolonel, Laurence N.; Le Marchand, Loic; Lemire, Mathieu; Ma, Jing; Newcomb, Polly A.; Ochs-Balcom, Heather M.; Pflugeisen, Bethann M.; Potter, John D.; Rudolph, Anja; Schoen, Robert E.; Seminara, Daniela; Slattery, Martha L.; Stelling, Deanna L.; Thomas, Fridtjof; Thornquist, Mark; Ulrich, Cornelia M.; Warnick, Greg S.; Zanke, Brent W.; Peters, Ulrike; Hsu, Li; White, Emily

2014-01-01

BACKGROUND Genome-wide association studies have identified several single nucleotide polymorphisms (SNPs) that are associated with risk of colorectal cancer (CRC). Prior research has evaluated the presence of gene-environment interaction involving the first 10 identified susceptibility loci, but little work has been conducted on interaction involving SNPs at recently identified susceptibility loci, including: rs10911251, rs6691170, rs6687758, rs11903757, rs10936599, rs647161, rs1321311, rs719725, rs1665650, rs3824999, rs7136702, rs11169552, rs59336, rs3217810, rs4925386, and rs2423279. METHODS Data on 9160 cases and 9280 controls from the Genetics and Epidemiology of Colorectal Cancer Consortium (GECCO) and Colon Cancer Family Registry (CCFR) were used to evaluate the presence of interaction involving the above-listed SNPs and sex, body mass index (BMI), alcohol consumption, smoking, aspirin use, post-menopausal hormone (PMH) use, as well as intake of dietary calcium, dietary fiber, dietary folate, red meat, processed meat, fruit, and vegetables. Interaction was evaluated using a fixed-effects meta-analysis of an efficient Empirical Bayes estimator, and permutation was used to account for multiple comparisons. RESULTS None of the permutation-adjusted p-values reached statistical significance. CONCLUSIONS The associations between recently identified genetic susceptibility loci and CRC are not strongly modified by sex, BMI, alcohol, smoking, aspirin, PMH use, and various dietary factors. IMPACT Results suggest no evidence of strong gene-environment interactions involving the recently identified 16 susceptibility loci for CRC taken one at a time. PMID:24994789
Whole-genome sequencing identifies recurrent mutations in chronic lymphocytic leukaemia

Science.gov (United States)

Puente, Xose S.; Pinyol, Magda; Quesada, Víctor; Conde, Laura; Ordóñez, Gonzalo R.; Villamor, Neus; Escaramis, Georgia; Jares, Pedro; Beà, Sílvia; González-Díaz, Marcos; Bassaganyas, Laia; Baumann, Tycho; Juan, Manel; López-Guerra, Mónica; Colomer, Dolors; Tubío, José M. C.; López, Cristina; Navarro, Alba; Tornador, Cristian; Aymerich, Marta; Rozman, María; Hernández, Jesús M.; Puente, Diana A.; Freije, José M. P.; Velasco, Gloria; Gutiérrez-Fernández, Ana; Costa, Dolors; Carrió, Anna; Guijarro, Sara; Enjuanes, Anna; Hernández, Lluís; Yagüe, Jordi; Nicolás, Pilar; Romeo-Casabona, Carlos M.; Himmelbauer, Heinz; Castillo, Ester; Dohm, Juliane C.; de Sanjosé, Silvia; Piris, Miguel A.; de Alava, Enrique; Miguel, Jesús San; Royo, Romina; Gelpí, Josep L.; Torrents, David; Orozco, Modesto; Pisano, David G.; Valencia, Alfonso; Guigó, Roderic; Bayés, Mónica; Heath, Simon; Gut, Marta; Klatt, Peter; Marshall, John; Raine, Keiran; Stebbings, Lucy A.; Futreal, P. Andrew; Stratton, Michael R.; Campbell, Peter J.; Gut, Ivo; López-Guillermo, Armando; Estivill, Xavier; Montserrat, Emili; López-Otín, Carlos; Campo, Elías

2012-01-01

Chronic lymphocytic leukaemia (CLL), the most frequent leukaemia in adults in Western countries, is a heterogeneous disease with variable clinical presentation and evolution1,2. Two major molecular subtypes can be distinguished, characterized respectively by a high or low number of somatic hypermutations in the variable region of immunoglobulin genes3,4. The molecular changes leading to the pathogenesis of the disease are still poorly understood. Here we performed whole-genome sequencing of four cases of CLL and identified 46 somatic mutations that potentially affect gene function. Further analysis of these mutations in 363 patients with CLL identified four genes that are recurrently mutated: notch 1 (NOTCH1), exportin 1 (XPO1), myeloid differentiation primary response gene 88 (MYD88) and kelch-like 6 (KLHL6). Mutations in MYD88 and KLHL6 are predominant in cases of CLL with mutated immunoglobulin genes, whereas NOTCH1 and XPO1 mutations are mainly detected in patients with unmutated immunoglobulins. The patterns of somatic mutation, supported by functional and clinical analyses, strongly indicate that the recurrent NOTCH1, MYD88 and XPO1 mutations are oncogenic changes that contribute to the clinical evolution of the disease. To our knowledge, this is the first comprehensive analysis of CLL combining whole-genome sequencing with clinical characteristics and clinical outcomes. It highlights the usefulness of this approach for the identification of clinically relevant mutations in cancer. PMID:21642962
Breast Cancer in Africa: Limitations and Opportunities for Application of Genomic Medicine

Directory of Open Access Journals (Sweden)

Allison Silverstein

2016-01-01

Full Text Available As genomic medicine gains clinical applicability across a spectrum of diseases, insufficient application in low-income settings stands to increase health disparity. Breast cancer screening, diagnosis, and treatment have benefited greatly from genomic medicine in high-income settings. As breast cancer is a leading cause of both cancer incidence and mortality in Africa, attention and resources must be applied to research and clinical initiatives to integrate genomic medicine into breast cancer care. In terms of research, there is a paucity of investigations into genetic determinants of breast cancer specific to African populations, despite consensus in the literature that predisposition and susceptibility genes vary between populations. Therefore, we need targeted strengthening of existing research efforts and support of new initiatives. Results will improve clinical care through screening and diagnosis with genetic testing specific to breast cancer in African populations. Clinically, genomic medicine can provide information capable of improving resource allocation to the population which most stands to benefit from increased screening or tailored treatment modalities. In situations where mammography or chemotherapy options are limited, this information will allow for the greatest impact. Implementation of genomic medicine will face numerous systemic barriers but is essential to improve breast cancer outcomes and survival.
Identification of genes containing expanded purine repeats in the human genome and their apparent protective role against cancer.

Science.gov (United States)

Singh, Himanshu Narayan; Rajeswari, Moganty R

2016-01-01

Purine repeat sequences present in a gene are unique as they have high propensity to form unusual DNA-triple helix structures. Friedreich's ataxia is the only human disease that is well known to be associated with DNA-triplexes formed by purine repeats. The purpose of this study was to recognize the expanded purine repeats (EPRs) in human genome and find their correlation with cancer pathogenesis. We developed "PuRepeatFinder.pl" algorithm to identify non-overlapping EPRs without pyrimidine interruptions in the human genome and customized for searching repeat lengths, n ≥ 200. A total of 1158 EPRs were identified in the genome which followed Wakeby distribution. Two hundred and ninety-six EPRs were found in geneic regions of 282 genes (EPR-genes). Gene clustering of EPR-genes was done based on their cellular function and a large number of EPR-genes were found to be enzymes/enzyme modulators. Meta-analysis of 282 EPR-genes identified only 63 EPR-genes in association with cancer, mostly in breast, lung, and blood cancers. Protein-protein interaction network analysis of all 282 EPR-genes identified proteins including those in cadherins and VEGF. The two observations, that EPRs can induce mutations under malignant conditions and that identification of some EPR-gene products in vital cell signaling-mediated pathways, together suggest the crucial role of EPRs in carcinogenesis. The new link between EPR-genes and their functionally interacting proteins throws a new dimension in the present understanding of cancer pathogenesis and can help in planning therapeutic strategies. Validation of present results using techniques like NGS is required to establish the role of the EPR genes in cancer pathology.
Causes of genome instability

DEFF Research Database (Denmark)

Langie, Sabine A S; Koppen, Gudrun; Desaulniers, Daniel

2015-01-01

function, chromosome segregation, telomere length). The purpose of this review is to describe the crucial aspects of genome instability, to outline the ways in which environmental chemicals can affect this cancer hallmark and to identify candidate chemicals for further study. The overall aim is to make......Genome instability is a prerequisite for the development of cancer. It occurs when genome maintenance systems fail to safeguard the genome's integrity, whether as a consequence of inherited defects or induced via exposure to environmental agents (chemicals, biological agents and radiation). Thus...
Genome-wide search for gene-gene interactions in colorectal cancer.

Directory of Open Access Journals (Sweden)

Shuo Jiao

Full Text Available Genome-wide association studies (GWAS have successfully identified a number of single-nucleotide polymorphisms (SNPs associated with colorectal cancer (CRC risk. However, these susceptibility loci known today explain only a small fraction of the genetic risk. Gene-gene interaction (GxG is considered to be one source of the missing heritability. To address this, we performed a genome-wide search for pair-wise GxG associated with CRC risk using 8,380 cases and 10,558 controls in the discovery phase and 2,527 cases and 2,658 controls in the replication phase. We developed a simple, but powerful method for testing interaction, which we term the Average Risk Due to Interaction (ARDI. With this method, we conducted a genome-wide search to identify SNPs showing evidence for GxG with previously identified CRC susceptibility loci from 14 independent regions. We also conducted a genome-wide search for GxG using the marginal association screening and examining interaction among SNPs that pass the screening threshold (p<10(-4. For the known locus rs10795668 (10p14, we found an interacting SNP rs367615 (5q21 with replication p = 0.01 and combined p = 4.19×10(-8. Among the top marginal SNPs after LD pruning (n = 163, we identified an interaction between rs1571218 (20p12.3 and rs10879357 (12q21.1 (nominal combined p = 2.51×10(-6; Bonferroni adjusted p = 0.03. Our study represents the first comprehensive search for GxG in CRC, and our results may provide new insight into the genetic etiology of CRC.
A target based approach identifies genomic predictors of breast cancer patient response to chemotherapy

Directory of Open Access Journals (Sweden)

Hallett Robin M

2012-05-01

Full Text Available Abstract Background The efficacy of chemotherapy regimens in breast cancer patients is variable and unpredictable. Whether individual patients either achieve long-term remission or suffer recurrence after therapy may be dictated by intrinsic properties of their breast tumors including genetic lesions and consequent aberrant transcriptional programs. Global gene expression profiling provides a powerful tool to identify such tumor-intrinsic transcriptional programs, whose analyses provide insight into the underlying biology of individual patient tumors. For example, multi-gene expression signatures have been identified that can predict the likelihood of disease reccurrence, and thus guide patient prognosis. Whereas such prognostic signatures are being introduced in the clinical setting, similar signatures that predict sensitivity or resistance to chemotherapy are not currently clinically available. Methods We used gene expression profiling to identify genes that were co-expressed with genes whose transcripts encode the protein targets of commonly used chemotherapeutic agents. Results Here, we present target based expression indices that predict breast tumor response to anthracycline and taxane based chemotherapy. Indeed, these signatures were independently predictive of chemotherapy response after adjusting for standard clinic-pathological variables such as age, grade, and estrogen receptor status in a cohort of 488 breast cancer patients treated with adriamycin and taxotere/taxol. Conclusions Importantly, our findings suggest the practicality of developing target based indices that predict response to therapeutics, as well as highlight the possibility of using gene signatures to guide the use of chemotherapy during treatment of breast cancer patients.
Genomic Alterations Observed in Colitis-Associated Cancers Are Distinct From Those Found in Sporadic Colorectal Cancers and Vary by Type of Inflammatory Bowel Disease.

Science.gov (United States)

Yaeger, Rona; Shah, Manish A; Miller, Vincent A; Kelsen, Judith R; Wang, Kai; Heins, Zachary J; Ross, Jeffrey S; He, Yuting; Sanford, Eric; Yantiss, Rhonda K; Balasubramanian, Sohail; Stephens, Philip J; Schultz, Nikolaus; Oren, Moshe; Tang, Laura; Kelsen, David

2016-08-01

Patients with inflammatory bowel diseases, such as Crohn's disease (CD) and ulcerative colitis (UC), are at increased risk for small bowel or colorectal cancers (colitis-associated cancers [CACs]). We compared the spectrum of genomic alterations in CACs with those of sporadic colorectal cancers (CRCs) and investigated differences between CACs from patients with CD vs UC. We studied tumor tissues from patients with CACs treated at Memorial Sloan Kettering Cancer Center or Weill Cornell Medical College from 2003 through 2015. We performed hybrid capture-based next-generation sequencing analysis of >300 cancer-related genes to comprehensively characterize genomic alterations. We performed genomic analyses of 47 CACs (from 29 patients with UC and 18 with CD; 43 primary tumors and 4 metastases). Primary tumors developed in the ileum (n = 2), right colon (n = 18), left colon (n = 6), and rectosigmoid or rectum (n = 21). We found genomic alterations in TP53, IDH1, and MYC to be significantly more frequent, and mutations in APC to be significantly less frequent, than those reported in sporadic CRCs by The Cancer Genome Atlas or Foundation Medicine. We identified genomic alterations that might be targeted by a therapeutic agent in 17 of 47 (36%) CACs. These included the mutation encoding IDH1 R132; amplification of FGFR1, FGFR2, and ERBB2; and mutations encoding BRAF V600E and an EML4-ALK fusion protein. Alterations in IDH1 and APC were significantly more common in CACs from patients with CD than UC. In an analysis of CACs from 47 patients, we found significant differences in the spectrum of genomic alterations in CACs compared with sporadic CRCs. We observed a high frequency of IDH1 R132 mutations in patients with CD but not UC, as well as a high frequency of MYC amplification in CACs. Many genetic alterations observed in CACs could serve as therapeutic targets. Copyright © 2016 AGA Institute. Published by Elsevier Inc. All rights reserved.
Novel approach to cancer therapeutics using comparative cancer biology

OpenAIRE

Revi, Bhindu

2018-01-01

Developing personalized cancer therapies based on cancer genomics methodologies forms the basis for future cancer therapeutics. A genomics platform was developed based on canine cancer to produce a proof-of-concept for personalized genomics led therapeutic choices but also developing personalized therapeutics for canine cancer patients themselves. The platform identified the genetic state of a canine cancer patient within two drugable pathways; p53 and HSP90/IRF1. The former ge...
Emory University: MEDICI (Mining Essentiality Data to Identify Critical Interactions) for Cancer Drug Target Discovery and Development | Office of Cancer Genomics

Science.gov (United States)

The CTD2 Center at Emory University has developed a computational methodology to combine high-throughput knockdown data with known protein network topologies to infer the importance of protein-protein interactions (PPIs) for the survival of cancer cells. Applying these data to the Achilles shRNA results, the CCLE cell line characterizations, and known and newly identified PPIs provides novel insights for potential new drug targets for cancer therapies and identifies important PPI hubs.
Causation of cancer by ionizing radiation and genomic instability

International Nuclear Information System (INIS)

Streffer, Christian

2013-01-01

The causation of cancer by ionizing radiation has been shown in many epidemiological (with exposed humans) as well as experimental studies with mammals especially mice but also rats, dogs and monkeys. Risk values have been determined in medium radiation dose ranges (∼100 to 2,000 mSv). However, in the low dose range (<100 mSv) the situation is unclear and unsolved up to now. A better knowledge of the mechanisms for the development of cancer in humans over decades after low to medium radiation exposures is necessary for the understanding of the open questions. An increase of chromosomal aberrations and other genetic changes have been frequently observed directly after radiation exposures in many cell systems including human cells. However, in 1989 it was found that an increase of genomic instability occurred after irradiation of mouse zygotes in the fibroblasts of the neonates developing from the irradiated zygotes. That means genomic instability developed many cell generations later in cells which never had been exposed to various qualities of ionizing radiations in vivo and any treatment and secondary cancers developed in photon irradiated M.Hodgkin patients preferentially in those patients who showed a comparatively high genomic instability in their lymphocytes. Since several decades it has been experienced that certain cancer patients show an extremely high radio-sensitivity. This clinical observation has been confirmed by experimental investigations with cells of such patients. It has been proven that this increased radio-sensitivity is due to genetic mutations. A number of syndromes could be defined on such a genetic basis like ataxia telangiectasia, bloom's syndrome, fanconi anemia, retinoblasoma and others. In all these syndromes mutations occur in genes which are to regulation of the cell cycle or DNA repair (preferentially repair of DSBs). These patients with an increased radio-sensitivity frequently develop cancer - very often lymphoma - and they also
Focusing on function to mine cancer genome data | Center for Cancer Research

Science.gov (United States)

CCR scientists have devised a strategy to sift through the tens of thousands of mutations in cancer genome data to find mutations that actually drive the disease. They have used the method to discover that the JNK signaling pathway, which in different contexts can either spur cancerous growth or rein it in, acts as a tumor suppressor in gastric cancers.
Common structural and epigenetic changes in the genome of castration-resistant prostate cancer.

Science.gov (United States)

Friedlander, Terence W; Roy, Ritu; Tomlins, Scott A; Ngo, Vy T; Kobayashi, Yasuko; Azameera, Aruna; Rubin, Mark A; Pienta, Kenneth J; Chinnaiyan, Arul; Ittmann, Michael M; Ryan, Charles J; Paris, Pamela L

2012-02-01

Progression of primary prostate cancer to castration-resistant prostate cancer (CRPC) is associated with numerous genetic and epigenetic alterations that are thought to promote survival at metastatic sites. In this study, we investigated gene copy number and CpG methylation status in CRPC to gain insight into specific pathophysiologic pathways that are active in this advanced form of prostate cancer. Our analysis defined and validated 495 genes exhibiting significant differences in CRPC in gene copy number, including gains in androgen receptor (AR) and losses of PTEN and retinoblastoma 1 (RB1). Significant copy number differences existed between tumors with or without AR gene amplification, including a common loss of AR repressors in AR-unamplified tumors. Simultaneous gene methylation and allelic deletion occurred frequently in RB1 and HSD17B2, the latter of which is involved in testosterone metabolism. Lastly, genomic DNA from most CRPC was hypermethylated compared with benign prostate tissue. Our findings establish a comprehensive methylation signature that couples epigenomic and structural analyses, thereby offering insights into the genomic alterations in CRPC that are associated with a circumvention of hormonal therapy. Genes identified in this integrated genomic study point to new drug targets in CRPC, an incurable disease state which remains the chief therapeutic challenge. ©2012 AACR.
Fine-scale mapping of 8q24 locus identifies multiple independent risk variants for breast cancer.

Science.gov (United States)

Shi, Jiajun; Zhang, Yanfeng; Zheng, Wei; Michailidou, Kyriaki; Ghoussaini, Maya; Bolla, Manjeet K; Wang, Qin; Dennis, Joe; Lush, Michael; Milne, Roger L; Shu, Xiao-Ou; Beesley, Jonathan; Kar, Siddhartha; Andrulis, Irene L; Anton-Culver, Hoda; Arndt, Volker; Beckmann, Matthias W; Zhao, Zhiguo; Guo, Xingyi; Benitez, Javier; Beeghly-Fadiel, Alicia; Blot, William; Bogdanova, Natalia V; Bojesen, Stig E; Brauch, Hiltrud; Brenner, Hermann; Brinton, Louise; Broeks, Annegien; Brüning, Thomas; Burwinkel, Barbara; Cai, Hui; Canisius, Sander; Chang-Claude, Jenny; Choi, Ji-Yeob; Couch, Fergus J; Cox, Angela; Cross, Simon S; Czene, Kamila; Darabi, Hatef; Devilee, Peter; Droit, Arnaud; Dork, Thilo; Fasching, Peter A; Fletcher, Olivia; Flyger, Henrik; Fostira, Florentia; Gaborieau, Valerie; García-Closas, Montserrat; Giles, Graham G; Guenel, Pascal; Haiman, Christopher A; Hamann, Ute; Hartman, Mikael; Miao, Hui; Hollestelle, Antoinette; Hopper, John L; Hsiung, Chia-Ni; Ito, Hidemi; Jakubowska, Anna; Johnson, Nichola; Torres, Diana; Kabisch, Maria; Kang, Daehee; Khan, Sofia; Knight, Julia A; Kosma, Veli-Matti; Lambrechts, Diether; Li, Jingmei; Lindblom, Annika; Lophatananon, Artitaya; Lubinski, Jan; Mannermaa, Arto; Manoukian, Siranoush; Le Marchand, Loic; Margolin, Sara; Marme, Frederik; Matsuo, Keitaro; McLean, Catriona; Meindl, Alfons; Muir, Kenneth; Neuhausen, Susan L; Nevanlinna, Heli; Nord, Silje; Børresen-Dale, Anne-Lise; Olson, Janet E; Orr, Nick; van den Ouweland, Ans M W; Peterlongo, Paolo; Putti, Thomas Choudary; Rudolph, Anja; Sangrajrang, Suleeporn; Sawyer, Elinor J; Schmidt, Marjanka K; Schmutzler, Rita K; Shen, Chen-Yang; Hou, Ming-Feng; Shrubsole, Matha J; Southey, Melissa C; Swerdlow, Anthony; Teo, Soo Hwang; Thienpont, Bernard; Toland, Amanda E; Tollenaar, Robert A E M; Tomlinson, Ian; Truong, Therese; Tseng, Chiu-Chen; Wen, Wanqing; Winqvist, Robert; Wu, Anna H; Yip, Cheng Har; Zamora, Pilar M; Zheng, Ying; Floris, Giuseppe; Cheng, Ching-Yu; Hooning, Maartje J; Martens, John W M; Seynaeve, Caroline; Kristensen, Vessela N; Hall, Per; Pharoah, Paul D P; Simard, Jacques; Chenevix-Trench, Georgia; Dunning, Alison M; Antoniou, Antonis C; Easton, Douglas F; Cai, Qiuyin; Long, Jirong

2016-09-15

Previous genome-wide association studies among women of European ancestry identified two independent breast cancer susceptibility loci represented by single nucleotide polymorphisms (SNPs) rs13281615 and rs11780156 at 8q24. A fine-mapping study across 2.06 Mb (chr8:127,561,724-129,624,067, hg19) in 55,540 breast cancer cases and 51,168 controls within the Breast Cancer Association Consortium was conducted. Three additional independent association signals in women of European ancestry, represented by rs35961416 (OR = 0.95, 95% CI = 0.93-0.97, conditional p = 5.8 × 10(-6) ), rs7815245 (OR = 0.94, 95% CI = 0.91-0.96, conditional p = 1.1 × 10(-6) ) and rs2033101 (OR = 1.05, 95% CI = 1.02-1.07, conditional p = 1.1 × 10(-4) ) were found. Integrative analysis using functional genomic data from the Roadmap Epigenomics, the Encyclopedia of DNA Elements project, the Cancer Genome Atlas and other public resources implied that SNPs rs7815245 in Signal 3, and rs1121948 in Signal 5 (in linkage disequilibrium with rs11780156, r(2) = 0.77), were putatively functional variants for two of the five independent association signals. The results highlighted multiple 8q24 variants associated with breast cancer susceptibility in women of European ancestry. © 2016 UICC.
Systematic screening of isogenic cancer cells identifies DUSP6 as context-specific synthetic lethal target in melanoma

DEFF Research Database (Denmark)

Wittig-Blaich, Stephanie; Wittig, Rainer; Schmidt, Steffen

2017-01-01

Next-generation sequencing has dramatically increased genome-wide profiling options and conceptually initiates the possibility for personalized cancer therapy. State-of-the-art sequencing studies yield large candidate gene sets comprising dozens or hundreds of mutated genes. However, few technolo......Next-generation sequencing has dramatically increased genome-wide profiling options and conceptually initiates the possibility for personalized cancer therapy. State-of-the-art sequencing studies yield large candidate gene sets comprising dozens or hundreds of mutated genes. However, few...... technologies are available for the systematic downstream evaluation of these results to identify novel starting points of future cancer therapies. We improved and extended a site-specific recombination-based system for systematic analysis of the individual functions of a large number of candidate genes......, a library of 108 isogenic melanoma cell lines was constructed and 8 genes were identified that significantly reduced viability in a discovery screen and in an independent validation screen. Here, we demonstrate the broad applicability of this recombination-based method and we proved its potential...
The mediator complex in genomic and non-genomic signaling in cancer.

Science.gov (United States)

Weber, Hannah; Garabedian, Michael J

2018-05-01

Mediator is a conserved, multi-subunit macromolecular machine divided structurally into head, middle, and tail modules, along with a transiently associating kinase module. Mediator functions as an integrator of transcriptional regulatory activity by interacting with DNA-bound transcription factors and with RNA polymerase II (Pol II) to both activate and repress gene expression. Mediator has been shown to affect multiple steps in transcription, including chromatin looping between enhancers and promoters, pre-initiation complex formation, transcriptional elongation, and mRNA splicing. Individual Mediator subunits participate in regulation of gene expression by the estrogen and androgen receptors and are altered in a number of endocrine cancers, including breast and prostate cancer. In addition to its role in genomic signaling, MED12 has been implicated in non-genomic signaling by interacting with and activating TGF-beta receptor 2 in the cytoplasm. Recent structural studies have revealed extensive inter-domain interactions and complex architecture of the Mediator-Pol II complex, suggesting that Mediator is capable of reorganizing its conformation and composition to fit cellular needs. We propose that alterations in Mediator subunit expression that occur in various cancers could impact the organization and function of Mediator, resulting in changes in gene expression that promote malignancy. A better understanding of the role of Mediator in cancer could reveal new approaches to the diagnosis and treatment of Mediator-dependent endocrine cancers, especially in settings of therapy resistance. Copyright © 2017 Elsevier Inc. All rights reserved.
Comparative analyses identified species-specific functional roles in oral microbial genomes

Science.gov (United States)

Chen, Tsute; Gajare, Prasad; Olsen, Ingar; Dewhirst, Floyd E.

2017-01-01

ABSTRACT The advent of next generation sequencing is producing more genomic sequences for various strains of many human oral microbial species and allows for insightful functional comparisons at both intra- and inter-species levels. This study performed in-silico functional comparisons for currently available genomic sequences of major species associated with periodontitis including Aggregatibacter actinomycetemcomitans (AA), Porphyromonas gingivalis (PG), Treponema denticola (TD), and Tannerella forsythia (TF), as well as several cariogenic and commensal streptococcal species. Complete or draft sequences were annotated with the RAST to infer structured functional subsystems for each genome. The subsystems profiles were clustered to groups of functions with similar patterns. Functional enrichment and depletion were evaluated based on hypergeometric distribution to identify subsystems that are unique or missing between two groups of genomes. Unique or missing metabolic pathways and biological functions were identified in different species. For example, components involved in flagellar motility were found only in the motile species TD, as expected, with few exceptions scattered in several streptococcal species, likely associated with chemotaxis. Transposable elements were only found in the two Bacteroidales species PG and TF, and half of the AA genomes. Genes involved in CRISPR were prevalent in most oral species. Furthermore, prophage related subsystems were also commonly found in most species except for PG and Streptococcus mutans, in which very few genomes contain prophage components. Comparisons between pathogenic (P) and nonpathogenic (NP) genomes also identified genes potentially important for virulence. Two such comparisons were performed between AA (P) and several A. aphrophilus (NP) strains, and between S. mutans + S. sobrinus (P) and other oral streptococcal species (NP). This comparative genomics approach can be readily used to identify functions unique to
Network-Based Integration of GWAS and Gene Expression Identifies a HOX-Centric Network Associated with Serous Ovarian Cancer Risk

DEFF Research Database (Denmark)

Kar, Siddhartha P; Tyrer, Jonathan P; Li, Qiyuan

2015-01-01

BACKGROUND: Genome-wide association studies (GWAS) have so far reported 12 loci associated with serous epithelial ovarian cancer (EOC) risk. We hypothesized that some of these loci function through nearby transcription factor (TF) genes and that putative target genes of these TFs as identified...... in the unified microarray dataset of 489 serous EOC tumors from The Cancer Genome Atlas. Genes represented in this dataset were subsequently ranked using a gene-level test based on results for germline SNPs from a serous EOC GWAS meta-analysis (2,196 cases/4,396 controls). RESULTS: Gene set enrichment analysis...
Large-scale association analysis identifies new lung cancer susceptibility loci and heterogeneity in genetic susceptibility across histological subtypes

DEFF Research Database (Denmark)

McKay, James D; Hung, Rayjean J; Han, Younghun

2017-01-01

Although several lung cancer susceptibility loci have been identified, much of the heritability for lung cancer remains unexplained. Here 14,803 cases and 12,262 controls of European descent were genotyped on the OncoArray and combined with existing data for an aggregated genome-wide association ...... receptor, CHRNA2, and the telomere-related genes OFBC1 and RTEL1. Further exploration of the target genes will continue to provide new insights into the etiology of lung cancer....

Association analysis identifies 65 new breast cancer risk loci

NARCIS (Netherlands)

Michailidou, Kyriaki; Lindström, Sara; Dennis, Joe; Beesley, Jonathan; Hui, Shirley; Kar, Siddhartha; Lemaçon, Audrey; Soucy, Penny; Glubb, Dylan; Rostamianfar, Asha; Bolla, Manjeet K.; Wang, Qin; Tyrer, Jonathan; Dicks, Ed; Lee, Andrew; Wang, Zhaoming; Allen, Jamie; Keeman, Renske; Eilber, Ursula; French, Juliet D.; Qing Chen, Xiao; Fachal, Laura; McCue, Karen; McCart Reed, Amy E.; Ghoussaini, Maya; Carroll, Jason S.; Jiang, Xia; Finucane, Hilary; Adams, Marcia; Adank, Muriel A.; Ahsan, Habibul; Aittomäki, Kristiina; Anton-Culver, Hoda; Antonenkova, Natalia N.; Arndt, Volker; Aronson, Kristan J.; Arun, Banu; Auer, Paul L.; Bacot, François; Barrdahl, Myrto; Baynes, Caroline; Beckmann, Matthias W.; Behrens, Sabine; Benitez, Javier; Bermisheva, Marina; Bernstein, Leslie; Blomqvist, Carl; Bogdanova, Natalia V.; Bojesen, Stig E.; Bonanni, Bernardo; Børresen-Dale, Anne-Lise; Brand, Judith S.; Brauch, Hiltrud; Brennan, Paul; Brenner, Hermann; Brinton, Louise; Broberg, Per; Brock, Ian W.; Broeks, Annegien; Brooks-Wilson, Angela; Brucker, Sara Y.; Brüning, Thomas; Burwinkel, Barbara; Butterbach, Katja; Cai, Qiuyin; Cai, Hui; Caldés, Trinidad; Canzian, Federico; Carracedo, Angel; Carter, Brian D.; Castelao, Jose E.; Chan, Tsun L.; David Cheng, Ting-Yuan; Seng Chia, Kee; Choi, Ji-Yeob; Christiansen, Hans; Clarke, Christine L.; Collée, Margriet; Conroy, Don M.; Cordina-Duverger, Emilie; Cornelissen, Sten; Cox, David G.; Cox, Angela; Cross, Simon S.; Cunningham, Julie M.; Czene, Kamila; Daly, Mary B.; Devilee, Peter; Doheny, Kimberly F.; Dörk, Thilo; Dos-Santos-Silva, Isabel; Dumont, Martine; Durcan, Lorraine; Dwek, Miriam; Eccles, Diana M.; Ekici, Arif B.; Eliassen, A. Heather; Ellberg, Carolina; Elvira, Mingajeva; Engel, Christoph; Eriksson, Mikael; Fasching, Peter A.; Figueroa, Jonine; Flesch-Janys, Dieter; Fletcher, Olivia; Flyger, Henrik; Fritschi, Lin; Gaborieau, Valerie; Gabrielson, Marike; Gago-Dominguez, Manuela; Gao, Yu-Tang; Gapstur, Susan M.; García-Sáenz, José A.; Gaudet, Mia M.; Georgoulias, Vassilios; Giles, Graham G.; Glendon, Gord; Goldberg, Mark S.; Goldgar, David E.; González-Neira, Anna; Grenaker Alnæs, Grethe I.; Grip, Mervi; Gronwald, Jacek; Grundy, Anne; Guénel, Pascal; Haeberle, Lothar; Hahnen, Eric; Haiman, Christopher A.; Håkansson, Niclas; Hamann, Ute; Hamel, Nathalie; Hankinson, Susan; Harrington, Patricia; Hart, Steven N.; Hartikainen, Jaana M.; Hartman, Mikael; Hein, Alexander; Heyworth, Jane; Hicks, Belynda; Hillemanns, Peter; Ho, Dona N.; Hollestelle, Antoinette; Hooning, Maartje J.; Hoover, Robert N.; Hopper, John L.; Hou, Ming-Feng; Hsiung, Chia-Ni; Huang, Guanmengqian; Humphreys, Keith; Ishiguro, Junko; Ito, Hidemi; Iwasaki, Motoki; Iwata, Hiroji; Jakubowska, Anna; Janni, Wolfgang; John, Esther M.; Johnson, Nichola; Jones, Kristine; Jones, Michael; Jukkola-Vuorinen, Arja; Kaaks, Rudolf; Kabisch, Maria; Kaczmarek, Katarzyna; Kang, Daehee; Kasuga, Yoshio; Kerin, Michael J.; Khan, Sofia; Khusnutdinova, Elza; Kiiski, Johanna I.; Kim, Sung-Won; Knight, Julia A.; Kosma, Veli-Matti; Kristensen, Vessela N.; Krüger, Ute; Kwong, Ava; Lambrechts, Diether; Le Marchand, Loic; Lee, Eunjung; Lee, Min Hyuk; Lee, Jong Won; Neng Lee, Chuen; Lejbkowicz, Flavio; Li, Jingmei; Lilyquist, Jenna; Lindblom, Annika; Lissowska, Jolanta; Lo, Wing-Yee; Loibl, Sibylle; Long, Jirong; Lophatananon, Artitaya; Lubinski, Jan; Luccarini, Craig; Lux, Michael P.; Ma, Edmond S. K.; MacInnis, Robert J.; Maishman, Tom; Makalic, Enes; Malone, Kathleen E.; Kostovska, Ivana Maleva; Mannermaa, Arto; Manoukian, Siranoush; Manson, JoAnn E.; Margolin, Sara; Mariapun, Shivaani; Martinez, Maria Elena; Matsuo, Keitaro; Mavroudis, Dimitrios; McKay, James; McLean, Catriona; Meijers-Heijboer, Hanne; Meindl, Alfons; Menéndez, Primitiva; Menon, Usha; Meyer, Jeffery; Miao, Hui; Miller, Nicola; Taib, Nur Aishah Mohd; Muir, Kenneth; Mulligan, Anna Marie; Mulot, Claire; Neuhausen, Susan L.; Nevanlinna, Heli; Neven, Patrick; Nielsen, Sune F.; Noh, Dong-Young; Nordestgaard, Børge G.; Norman, Aaron; Olopade, Olufunmilayo I.; Olson, Janet E.; Olsson, Håkan; Olswold, Curtis; Orr, Nick; Pankratz, V. Shane; Park, Sue K.; Park-Simon, Tjoung-Won; Lloyd, Rachel; Perez, Jose I. A.; Peterlongo, Paolo; Peto, Julian; Phillips, Kelly-Anne; Pinchev, Mila; Plaseska-Karanfilska, Dijana; Prentice, Ross; Presneau, Nadege; Prokofyeva, Darya; Pugh, Elizabeth; Pylkäs, Katri; Rack, Brigitte; Radice, Paolo; Rahman, Nazneen; Rennert, Gadi; Rennert, Hedy S.; Rhenius, Valerie; Romero, Atocha; Romm, Jane; Ruddy, Kathryn J.; Rüdiger, Thomas; Rudolph, Anja; Ruebner, Matthias; Rutgers, Emiel J. T.; Saloustros, Emmanouil; Sandler, Dale P.; Sangrajrang, Suleeporn; Sawyer, Elinor J.; Schmidt, Daniel F.; Schmutzler, Rita K.; Schneeweiss, Andreas; Schoemaker, Minouk J.; Schumacher, Fredrick; Schürmann, Peter; Scott, Rodney J.; Scott, Christopher; Seal, Sheila; Seynaeve, Caroline; Shah, Mitul; Sharma, Priyanka; Shen, Chen-Yang; Sheng, Grace; Sherman, Mark E.; Shrubsole, Martha J.; Shu, Xiao-Ou; Smeets, Ann; Sohn, Christof; Southey, Melissa C.; Spinelli, John J.; Stegmaier, Christa; Stewart-Brown, Sarah; Stone, Jennifer; Stram, Daniel O.; Surowy, Harald; Swerdlow, Anthony; Tamimi, Rulla; Taylor, Jack A.; Tengström, Maria; teo, Soo H.; Beth Terry, Mary; Tessier, Daniel C.; Thanasitthichai, Somchai; Thöne, Kathrin; Tollenaar, Rob A. E. M.; Tomlinson, Ian; Tong, Ling; Torres, Diana; Truong, Thérèse; Tseng, Chiu-Chen; Tsugane, Shoichiro; Ulmer, Hans-Ulrich; Ursin, Giske; Untch, Michael; Vachon, Celine; van Asperen, Christi J.; van den Berg, David; van den Ouweland, Ans M. W.; van der Kolk, Lizet; van der Luijt, Rob B.; Vincent, Daniel; Vollenweider, Jason; Waisfisz, Quinten; Wang-Gohrke, Shan; Weinberg, Clarice R.; Wendt, Camilla; Whittemore, Alice S.; Wildiers, Hans; Willett, Walter; Winqvist, Robert; Wolk, Alicja; Wu, Anna H.; Xia, Lucy; Yamaji, Taiki; Yang, Xiaohong R.; Har Yip, Cheng; Yoo, Keun-Young; Yu, Jyh-Cherng; Zheng, Wei; Zheng, Ying; Zhu, Bin; Ziogas, Argyrios; Ziv, Elad; Lakhani, Sunil R.; Antoniou, Antonis C.; Droit, Arnaud; Andrulis, Irene L.; Amos, Christopher I.; Couch, Fergus J.; Pharoah, Paul D. P.; Chang-Claude, Jenny; Hall, Per; Hunter, David J.; Milne, Roger L.; García-Closas, Montserrat; Schmidt, Marjanka K.; Chanock, Stephen J.; Dunning, Alison M.; Edwards, Stacey L.; Bader, Gary D.; Chenevix-Trench, Georgia; Simard, Jacques; Kraft, Peter; Easton, Douglas F.

2017-01-01

Breast cancer risk is influenced by rare coding variants in susceptibility genes, such as BRCA1, and many common, mostly non-coding variants. However, much of the genetic contribution to breast cancer risk remains unknown. Here we report the results of a genome-wide association study of breast
Preferential Allele Expression Analysis Identifies Shared Germline and Somatic Driver Genes in Advanced Ovarian Cancer

Science.gov (United States)

Halabi, Najeeb M.; Martinez, Alejandra; Al-Farsi, Halema; Mery, Eliane; Puydenus, Laurence; Pujol, Pascal; Khalak, Hanif G.; McLurcan, Cameron; Ferron, Gwenael; Querleu, Denis; Al-Azwani, Iman; Al-Dous, Eman; Mohamoud, Yasmin A.; Malek, Joel A.; Rafii, Arash

2016-01-01

Identifying genes where a variant allele is preferentially expressed in tumors could lead to a better understanding of cancer biology and optimization of targeted therapy. However, tumor sample heterogeneity complicates standard approaches for detecting preferential allele expression. We therefore developed a novel approach combining genome and transcriptome sequencing data from the same sample that corrects for sample heterogeneity and identifies significant preferentially expressed alleles. We applied this analysis to epithelial ovarian cancer samples consisting of matched primary ovary and peritoneum and lymph node metastasis. We find that preferentially expressed variant alleles include germline and somatic variants, are shared at a relatively high frequency between patients, and are in gene networks known to be involved in cancer processes. Analysis at a patient level identifies patient-specific preferentially expressed alleles in genes that are targets for known drugs. Analysis at a site level identifies patterns of site specific preferential allele expression with similar pathways being impacted in the primary and metastasis sites. We conclude that genes with preferentially expressed variant alleles can act as cancer drivers and that targeting those genes could lead to new therapeutic strategies. PMID:26735499
Engineering and Functional Characterization of Fusion Genes Identifies Novel Oncogenic Drivers of Cancer. | Office of Cancer Genomics

Science.gov (United States)

Oncogenic gene fusions drive many human cancers, but tools to more quickly unravel their functional contributions are needed. Here we describe methodology permitting fusion gene construction for functional evaluation. Using this strategy, we engineered the known fusion oncogenes, BCR-ABL1, EML4-ALK, and ETV6-NTRK3, as well as 20 previously uncharacterized fusion genes identified in TCGA datasets.
Genome-wide profiling of the PIWI-interacting RNA-mRNA regulatory networks in epithelial ovarian cancers.

Science.gov (United States)

Singh, Garima; Roy, Jyoti; Rout, Pratiti; Mallick, Bibekanand

2018-01-01

PIWI-interacting (piRNAs), ~23-36 nucleotide-long small non-coding RNAs (sncRNAs), earlier believed to be germline-specific, have now been identified in somatic cells, including cancer cells. These sncRNAs impact critical biological processes by fine-tuning gene expression at post-transcriptional and epigenetic levels. The expression of piRNAs in ovarian cancer, the most lethal gynecologic cancer is largely uncharted. In this study, we investigated the expression of PIWILs by qRT-PCR and western blotting and then identified piRNA transcriptomes in tissues of normal ovary and two most prevalent epithelial ovarian cancer subtypes, serous and endometrioid by small RNA sequencing. We detected 219, 256 and 234 piRNAs in normal ovary, endometrioid and serous ovarian cancer samples respectively. We observed piRNAs are encoded from various genomic regions, among which introns harbor the majority of them. Surprisingly, piRNAs originated from different genomic contexts showed the varied level of conservations across vertebrates. The functional analysis of predicted targets of differentially expressed piRNAs revealed these could modulate key processes and pathways involved in ovarian oncogenesis. Our study provides the first comprehensive piRNA landscape in these samples and a useful resource for further functional studies to decipher new mechanistic views of piRNA-mediated gene regulatory networks affecting ovarian oncogenesis. The RNA-seq data is submitted to GEO database (GSE83794).
GENOMIC PREDICTOR OF RESPONSE AND SURVIVAL FOLLOWING TAXANE-ANTHRACYCLINE CHEMOTHERAPY FOR INVASIVE BREAST CANCER

Science.gov (United States)

Hatzis, Christos; Pusztai, Lajos; Valero, Vicente; Booser, Daniel J.; Esserman, Laura; Lluch, Ana; Vidaurre, Tatiana; Holmes, Frankie; Souchon, Eduardo; Martin, Miguel; Cotrina, José; Gomez, Henry; Hubbard, Rebekah; Chacón, J. Ignacio; Ferrer-Lozano, Jaime; Dyer, Richard; Buxton, Meredith; Gong, Yun; Wu, Yun; Ibrahim, Nuhad; Andreopoulou, Eleni; Ueno, Naoto T.; Hunt, Kelly; Yang, Wei; Nazario, Arlene; DeMichele, Angela; O’Shaughnessy, Joyce; Hortobagyi, Gabriel N.; Symmans, W. Fraser

2017-01-01

CONTEXT Accurate prediction of who will (or won’t) have high probability of survival benefit from standard treatments is fundamental for individualized cancer treatment strategies. OBJECTIVE To develop a predictor of response and survival from chemotherapy for newly diagnosed invasive breast cancer. DESIGN Development of different predictive signatures for resistance and response to neoadjuvant chemotherapy (stratified according to estrogen receptor (ER) status) from gene expression microarrays of newly diagnosed breast cancer (310 patients). Then prediction of breast cancer treatment-sensitivity using the combination of signatures for: 1) sensitivity to endocrine therapy, 2) chemo-resistance, and 3) chemo-sensitivity. Independent validation (198 patients) and comparison with other reported genomic predictors of chemotherapy response. SETTING Prospective multicenter study to develop and test genomic predictors for neoadjuvant chemotherapy. PATIENTS Newly diagnosed HER2-negative breast cancer treated with chemotherapy containing sequential taxane and anthracycline-based regimens then endocrine therapy (if hormone receptor-positive). MAIN OUTCOME MEASURES Distant relapse-free survival (DRFS) if predicted treatment-sensitive and absolute risk reduction (ARR, difference in DRFS of the two predicted groups) at median follow-up (3 years), and their 95% confidence intervals (CI). RESULTS Patients in the independent validation cohort (99% clinical Stage II–III) who were predicted to be treatment-sensitive (28% of total) had DRFS of 92% (CI 85–100) and survival benefit compared to others (absolute risk reduction (ARR) 18%; CI 6–28). Predictions were accurate if breast cancer was ER-positive (30% predicted sensitive, DRFS 97%, CI 91–100; ARR 11%, CI 0.1–21) or ER-negative (26% predicted sensitive, DRFS 83%, CI 68–100; ARR 26%, CI 4–28), and were significant in multivariate analysis after adjusting for relevant clinical-pathologic characteristics. Other
Tumor xenograft modeling identifies an association between TCF4 loss and breast cancer chemoresistance

Directory of Open Access Journals (Sweden)

Gorka Ruiz de Garibay

2018-05-01

Full Text Available Understanding the mechanisms of cancer therapeutic resistance is fundamental to improving cancer care. There is clear benefit from chemotherapy in different breast cancer settings; however, knowledge of the mutations and genes that mediate resistance is incomplete. In this study, by modeling chemoresistance in patient-derived xenografts (PDXs, we show that adaptation to therapy is genetically complex and identify that loss of transcription factor 4 (TCF4; also known as ITF2 is associated with this process. A triple-negative BRCA1-mutated PDX was used to study the genetics of chemoresistance. The PDX was treated in parallel with four chemotherapies for five iterative cycles. Exome sequencing identified few genes with de novo or enriched mutations in common among the different therapies, whereas many common depleted mutations/genes were observed. Analysis of somatic mutations from The Cancer Genome Atlas (TCGA supported the prognostic relevance of the identified genes. A mutation in TCF4 was found de novo in all treatments, and analysis of drug sensitivity profiles across cancer cell lines supported the link to chemoresistance. Loss of TCF4 conferred chemoresistance in breast cancer cell models, possibly by altering cell cycle regulation. Targeted sequencing in chemoresistant tumors identified an intronic variant of TCF4 that may represent an expression quantitative trait locus associated with relapse outcome in TCGA. Immunohistochemical studies suggest a common loss of nuclear TCF4 expression post-chemotherapy. Together, these results from tumor xenograft modeling depict a link between altered TCF4 expression and breast cancer chemoresistance.
Genome-wide linkage scan for colorectal cancer susceptibility genes supports linkage to chromosome 3q

Directory of Open Access Journals (Sweden)

Velculescu Victor E

2008-04-01

Full Text Available Abstract Background Colorectal cancer is one of the most common causes of cancer-related mortality. The disease is clinically and genetically heterogeneous though a strong hereditary component has been identified. However, only a small proportion of the inherited susceptibility can be ascribed to dominant syndromes, such as Hereditary Non-Polyposis Colorectal Cancer (HNPCC or Familial Adenomatous Polyposis (FAP. In an attempt to identify novel colorectal cancer predisposing genes, we have performed a genome-wide linkage analysis in 30 Swedish non-FAP/non-HNPCC families with a strong family history of colorectal cancer. Methods Statistical analysis was performed using multipoint parametric and nonparametric linkage. Results Parametric analysis under the assumption of locus homogeneity excluded any common susceptibility regions harbouring a predisposing gene for colorectal cancer. However, several loci on chromosomes 2q, 3q, 6q, and 7q with suggestive linkage were detected in the parametric analysis under the assumption of locus heterogeneity as well as in the nonparametric analysis. Among these loci, the locus on chromosome 3q21.1-q26.2 was the most consistent finding providing positive results in both parametric and nonparametric analyses Heterogeneity LOD score (HLOD = 1.90, alpha = 0.45, Non-Parametric LOD score (NPL = 2.1. Conclusion The strongest evidence of linkage was seen for the region on chromosome 3. Interestingly, the same region has recently been reported as the most significant finding in a genome-wide analysis performed with SNP arrays; thus our results independently support the finding on chromosome 3q.
Ectopic Expression of Testis Germ Cell Proteins in Cancer and Its Potential Role in Genomic Instability

Directory of Open Access Journals (Sweden)

Aaraby Yoheswaran Nielsen

2016-06-01

Full Text Available Genomic instability is a hallmark of human cancer and an enabling factor for the genetic alterations that drive cancer development. The processes involved in genomic instability resemble those of meiosis, where genetic material is interchanged between homologous chromosomes. In most types of human cancer, epigenetic changes, including hypomethylation of gene promoters, lead to the ectopic expression of a large number of proteins normally restricted to the germ cells of the testis. Due to the similarities between meiosis and genomic instability, it has been proposed that activation of meiotic programs may drive genomic instability in cancer cells. Some germ cell proteins with ectopic expression in cancer cells indeed seem to promote genomic instability, while others reduce polyploidy and maintain mitotic fidelity. Furthermore, oncogenic germ cell proteins may indirectly contribute to genomic instability through induction of replication stress, similar to classic oncogenes. Thus, current evidence suggests that testis germ cell proteins are implicated in cancer development by regulating genomic instability during tumorigenesis, and these proteins therefore represent promising targets for novel therapeutic strategies.
Quantitative high-resolution genomic analysis of single cancer cells.

Science.gov (United States)

Hannemann, Juliane; Meyer-Staeckling, Sönke; Kemming, Dirk; Alpers, Iris; Joosse, Simon A; Pospisil, Heike; Kurtz, Stefan; Görndt, Jennifer; Püschel, Klaus; Riethdorf, Sabine; Pantel, Klaus; Brandt, Burkhard

2011-01-01

During cancer progression, specific genomic aberrations arise that can determine the scope of the disease and can be used as predictive or prognostic markers. The detection of specific gene amplifications or deletions in single blood-borne or disseminated tumour cells that may give rise to the development of metastases is of great clinical interest but technically challenging. In this study, we present a method for quantitative high-resolution genomic analysis of single cells. Cells were isolated under permanent microscopic control followed by high-fidelity whole genome amplification and subsequent analyses by fine tiling array-CGH and qPCR. The assay was applied to single breast cancer cells to analyze the chromosomal region centred by the therapeutical relevant EGFR gene. This method allows precise quantitative analysis of copy number variations in single cell diagnostics.
Synergistic Interactions with PI3K Inhibition that Induce Apoptosis. | Office of Cancer Genomics

Science.gov (United States)

Activating mutations involving the PI3K pathway occur frequently in human cancers. However, PI3K inhibitors primarily induce cell cycle arrest, leaving a significant reservoir of tumor cells that may acquire or exhibit resistance. We searched for genes that are required for the survival of PI3K mutant cancer cells in the presence of PI3K inhibition by conducting a genome scale shRNA-based apoptosis screen in a PIK3CA mutant human breast cancer cell. We identified 5 genes (PIM2, ZAK, TACC1, ZFR, ZNF565) whose suppression induced cell death upon PI3K inhibition.
Genome-wide association study identifies novel breast cancer susceptibility loci

NARCIS (Netherlands)

Easton, Douglas F.; Pooley, Karen A.; Dunning, Alison M.; Pharoah, Paul D. P.; Thompson, Deborah; Ballinger, Dennis G.; Struewing, Jeffery P.; Morrison, Jonathan; Field, Helen; Luben, Robert; Wareham, Nicholas; Ahmed, Shahana; Healey, Catherine S.; Bowman, Richard; Meyer, Kerstin B.; Haiman, Christopher A.; Kolonel, Laurence K.; Henderson, Brian E.; Le Marchand, Loic; Brennan, Paul; Sangrajrang, Suleeporn; Gaborieau, Valerie; Odefrey, Fabrice; Shen, Chen-Yang; Wu, Pei-Ei; Wang, Hui-Chun; Eccles, Diana; Evans, D. Gareth; Peto, Julian; Fletcher, Olivia; Johnson, Nichola; Seal, Sheila; Stratton, Michael R.; Rahman, Nazneen; Chenevix-Trench, Georgia; Bojesen, Stig E.; Nordestgaard, Børge G.; Axelsson, Christen K.; Garcia-Closas, Montserrat; Brinton, Louise; Chanock, Stephen; Lissowska, Jolanta; Peplonska, Beata; Nevanlinna, Heli; Fagerholm, Rainer; Eerola, Hannaleena; Kang, Daehee; Yoo, Keun-Young; Noh, Dong-Young; Ahn, Sei-Hyun; Hunter, David J.; Hankinson, Susan E.; Cox, David G.; Hall, Per; Wedren, Sara; Liu, Jianjun; Low, Yen-Ling; Bogdanova, Natalia; Schürmann, Peter; Dörk, Thilo; Tollenaar, Rob A. E. M.; Jacobi, Catharina E.; Devilee, Peter; Klijn, Jan G. M.; Sigurdson, Alice J.; Doody, Michele M.; Alexander, Bruce H.; Zhang, Jinghui; Cox, Angela; Brock, Ian W.; MacPherson, Gordon; Reed, Malcolm W. R.; Couch, Fergus J.; Goode, Ellen L.; Olson, Janet E.; Meijers-Heijboer, Hanne; van den Ouweland, Ans; Uitterlinden, André; Rivadeneira, Fernando; Milne, Roger L.; Ribas, Gloria; Gonzalez-Neira, Anna; Benitez, Javier; Hopper, John L.; McCredie, Margaret; Southey, Melissa; Giles, Graham G.; Schroen, Chris; Justenhoven, Christina; Brauch, Hiltrud; Hamann, Ute; Ko, Yon-Dschun; Spurdle, Amanda B.; Beesley, Jonathan; Chen, Xiaoqing; Mannermaa, Arto; Kosma, Veli-Matti; Kataja, Vesa; Hartikainen, Jaana; Day, Nicholas E.; Cox, David R.; Ponder, Bruce A. J.

2007-01-01

Breast cancer exhibits familial aggregation, consistent with variation in genetic susceptibility to the disease. Known susceptibility genes account for less than 25% of the familial risk of breast cancer, and the residual genetic variance is likely to be due to variants conferring more moderate
Crossing the LINE toward genomic instability: LINE-1 retrotransposition in cancer

Science.gov (United States)

Kemp, Jacqueline; Longworth, Michelle

2015-12-01

Retrotransposons are repetitive DNA sequences that are positioned throughout the human genome. Retrotransposons are capable of copying themselves and mobilizing new copies to novel genomic locations in a process called retrotransposition. While most retrotransposon sequences in the human genome are incomplete and incapable of mobilization, the LINE-1 retrotransposon, which comprises approximately 17% of the human genome, remains active. The disruption of cellular mechanisms that suppress retrotransposon activity is linked to the generation of aneuploidy, a potential driver of tumor development. When retrotransposons insert into a novel genomic region, they have the potential to disrupt the coding sequence of endogenous genes and alter gene expression, which can lead to deleterious consequences for the organism. Additionally, increased LINE-1 copy numbers provide more chances for recombination events to occur between retrotransposons, which can lead to chromosomal breaks and rearrangements. LINE-1 activity is increased in various cancer cell lines and in patient tissues resected from primary tumors. LINE-1 activity also correlates with increased cancer metastasis. This review aims to give a brief overview of the connections between LINE-1 retrotransposition and the loss of genome stability. We will also discuss the mechanisms that repress retrotransposition in human cells and their links to cancer.
Lipid Biomarkers Identified for Liver Cancer | Center for Cancer Research

Science.gov (United States)

Hepatocellular carcinoma (HCC) is an aggressive cancer of the liver with poor prognosis and growing incidence in developed countries. Pathology and genetic profiles of HCC are heterogeneous, suggesting that it can begin growing in different cell types. Although human tumors such as HCC have been profiled in-depth by genomics-based studies, not much is known about their overall
Genome-wide association study of pancreatic cancer in Japanese population.

Directory of Open Access Journals (Sweden)

Siew-Kee Low

Full Text Available Pancreatic cancer shows very poor prognosis and is the fifth leading cause of cancer death in Japan. Previous studies indicated some genetic factors contributing to the development and progression of pancreatic cancer; however, there are limited reports for common genetic variants to be associated with this disease, especially in the Asian population. We have conducted a genome-wide association study (GWAS using 991 invasive pancreatic ductal adenocarcinoma cases and 5,209 controls, and identified three loci showing significant association (P-value<5x10(-7 with susceptibility to pancreatic cancer. The SNPs that showed significant association carried estimated odds ratios of 1.29, 1.32, and 3.73 with 95% confidence intervals of 1.17-1.43, 1.19-1.47, and 2.24-6.21; P-value of 3.30x10(-7, 3.30x10(-7, and 4.41x10(-7; located on chromosomes 6p25.3, 12p11.21 and 7q36.2, respectively. These associated SNPs are located within linkage disequilibrium blocks containing genes that have been implicated some roles in the oncogenesis of pancreatic cancer.
Break Breast Cancer Addiction by CRISPR/Cas9 Genome Editing

OpenAIRE

Yang, Haitao; Jaeger, MariaLynn; Walker, Averi; Wei, Daniel; Leiker, Katie; Weitao, Tao

2018-01-01

Breast cancer is the leading diagnosed cancer for women globally. Evolution of breast cancer in tumorigenesis, metastasis and treatment resistance appears to be driven by the aberrant gene expression and protein degradation encoded by the cancer genomes. The uncontrolled cancer growth relies on these cellular events, thus constituting the cancerous programs and rendering the addiction towards them. These programs are likely the potential anticancer biomarkers for Personalized Medicine of brea...
Genome-wide association scan for variants associated with early-onset prostate cancer.

Directory of Open Access Journals (Sweden)

Ethan M Lange

Full Text Available Prostate cancer is the most common non-skin cancer and the second leading cause of cancer related mortality for men in the United States. There is strong empirical and epidemiological evidence supporting a stronger role of genetics in early-onset prostate cancer. We performed a genome-wide association scan for early-onset prostate cancer. Novel aspects of this study include the focus on early-onset disease (defined as men with prostate cancer diagnosed before age 56 years and use of publically available control genotype data from previous genome-wide association studies. We found genome-wide significant (p<5×10(-8 evidence for variants at 8q24 and 11p15 and strong supportive evidence for a number of previously reported loci. We found little evidence for individual or systematic inflated association findings resulting from using public controls, demonstrating the utility of using public control data in large-scale genetic association studies of common variants. Taken together, these results demonstrate the importance of established common genetic variants for early-onset prostate cancer and the power of including early-onset prostate cancer cases in genetic association studies.
Network-Based Integration of GWAS and Gene Expression Identifies a HOX-Centric Network Associated with Serous Ovarian Cancer Risk.

Science.gov (United States)

Kar, Siddhartha P; Tyrer, Jonathan P; Li, Qiyuan; Lawrenson, Kate; Aben, Katja K H; Anton-Culver, Hoda; Antonenkova, Natalia; Chenevix-Trench, Georgia; Baker, Helen; Bandera, Elisa V; Bean, Yukie T; Beckmann, Matthias W; Berchuck, Andrew; Bisogna, Maria; Bjørge, Line; Bogdanova, Natalia; Brinton, Louise; Brooks-Wilson, Angela; Butzow, Ralf; Campbell, Ian; Carty, Karen; Chang-Claude, Jenny; Chen, Yian Ann; Chen, Zhihua; Cook, Linda S; Cramer, Daniel; Cunningham, Julie M; Cybulski, Cezary; Dansonka-Mieszkowska, Agnieszka; Dennis, Joe; Dicks, Ed; Doherty, Jennifer A; Dörk, Thilo; du Bois, Andreas; Dürst, Matthias; Eccles, Diana; Easton, Douglas F; Edwards, Robert P; Ekici, Arif B; Fasching, Peter A; Fridley, Brooke L; Gao, Yu-Tang; Gentry-Maharaj, Aleksandra; Giles, Graham G; Glasspool, Rosalind; Goode, Ellen L; Goodman, Marc T; Grownwald, Jacek; Harrington, Patricia; Harter, Philipp; Hein, Alexander; Heitz, Florian; Hildebrandt, Michelle A T; Hillemanns, Peter; Hogdall, Estrid; Hogdall, Claus K; Hosono, Satoyo; Iversen, Edwin S; Jakubowska, Anna; Paul, James; Jensen, Allan; Ji, Bu-Tian; Karlan, Beth Y; Kjaer, Susanne K; Kelemen, Linda E; Kellar, Melissa; Kelley, Joseph; Kiemeney, Lambertus A; Krakstad, Camilla; Kupryjanczyk, Jolanta; Lambrechts, Diether; Lambrechts, Sandrina; Le, Nhu D; Lee, Alice W; Lele, Shashi; Leminen, Arto; Lester, Jenny; Levine, Douglas A; Liang, Dong; Lissowska, Jolanta; Lu, Karen; Lubinski, Jan; Lundvall, Lene; Massuger, Leon; Matsuo, Keitaro; McGuire, Valerie; McLaughlin, John R; McNeish, Iain A; Menon, Usha; Modugno, Francesmary; Moysich, Kirsten B; Narod, Steven A; Nedergaard, Lotte; Ness, Roberta B; Nevanlinna, Heli; Odunsi, Kunle; Olson, Sara H; Orlow, Irene; Orsulic, Sandra; Weber, Rachel Palmieri; Pearce, Celeste Leigh; Pejovic, Tanja; Pelttari, Liisa M; Permuth-Wey, Jennifer; Phelan, Catherine M; Pike, Malcolm C; Poole, Elizabeth M; Ramus, Susan J; Risch, Harvey A; Rosen, Barry; Rossing, Mary Anne; Rothstein, Joseph H; Rudolph, Anja; Runnebaum, Ingo B; Rzepecka, Iwona K; Salvesen, Helga B; Schildkraut, Joellen M; Schwaab, Ira; Shu, Xiao-Ou; Shvetsov, Yurii B; Siddiqui, Nadeem; Sieh, Weiva; Song, Honglin; Southey, Melissa C; Sucheston-Campbell, Lara E; Tangen, Ingvild L; Teo, Soo-Hwang; Terry, Kathryn L; Thompson, Pamela J; Timorek, Agnieszka; Tsai, Ya-Yu; Tworoger, Shelley S; van Altena, Anne M; Van Nieuwenhuysen, Els; Vergote, Ignace; Vierkant, Robert A; Wang-Gohrke, Shan; Walsh, Christine; Wentzensen, Nicolas; Whittemore, Alice S; Wicklund, Kristine G; Wilkens, Lynne R; Woo, Yin-Ling; Wu, Xifeng; Wu, Anna; Yang, Hannah; Zheng, Wei; Ziogas, Argyrios; Sellers, Thomas A; Monteiro, Alvaro N A; Freedman, Matthew L; Gayther, Simon A; Pharoah, Paul D P

2015-10-01

Genome-wide association studies (GWAS) have so far reported 12 loci associated with serous epithelial ovarian cancer (EOC) risk. We hypothesized that some of these loci function through nearby transcription factor (TF) genes and that putative target genes of these TFs as identified by coexpression may also be enriched for additional EOC risk associations. We selected TF genes within 1 Mb of the top signal at the 12 genome-wide significant risk loci. Mutual information, a form of correlation, was used to build networks of genes strongly coexpressed with each selected TF gene in the unified microarray dataset of 489 serous EOC tumors from The Cancer Genome Atlas. Genes represented in this dataset were subsequently ranked using a gene-level test based on results for germline SNPs from a serous EOC GWAS meta-analysis (2,196 cases/4,396 controls). Gene set enrichment analysis identified six networks centered on TF genes (HOXB2, HOXB5, HOXB6, HOXB7 at 17q21.32 and HOXD1, HOXD3 at 2q31) that were significantly enriched for genes from the risk-associated end of the ranked list (P < 0.05 and FDR < 0.05). These results were replicated (P < 0.05) using an independent association study (7,035 cases/21,693 controls). Genes underlying enrichment in the six networks were pooled into a combined network. We identified a HOX-centric network associated with serous EOC risk containing several genes with known or emerging roles in serous EOC development. Network analysis integrating large, context-specific datasets has the potential to offer mechanistic insights into cancer susceptibility and prioritize genes for experimental characterization. ©2015 American Association for Cancer Research.
Integrative Genomic Analysis of Cholangiocarcinoma Identifies Distinct IDH-Mutant Molecular Profiles

DEFF Research Database (Denmark)

Farshidfar, Farshad; Zheng, Siyuan; Gingras, Marie-Claude

2017-01-01

Cholangiocarcinoma (CCA) is an aggressive malignancy of the bile ducts, with poor prognosis and limited treatment options. Here, we describe the integrated analysis of somatic mutations, RNA expression, copy number, and DNA methylation by The Cancer Genome Atlas of a set of predominantly intrahep...
A new generation of cancer genome diagnostics for routine clinical use: overcoming the roadblocks to personalized cancer medicine.

Science.gov (United States)

Heuckmann, J M; Thomas, R K

2015-09-01

The identification of 'druggable' kinase gene alterations has revolutionized cancer treatment in the last decade by providing new and successfully targetable drug targets. Thus, genotyping tumors for matching the right patients with the right drugs have become a clinical routine. Today, advances in sequencing technology and computational genome analyses enable the discovery of a constantly growing number of genome alterations relevant for clinical decision making. As a consequence, several technological approaches have emerged in order to deal with these rapidly increasing demands for clinical cancer genome analyses. Here, we describe challenges on the path to the broad introduction of diagnostic cancer genome analyses and the technologies that can be applied to overcome them. We define three generations of molecular diagnostics that are in clinical use. The latest generation of these approaches involves deep and thus, highly sensitive sequencing of all therapeutically relevant types of genome alterations-mutations, copy number alterations and rearrangements/fusions-in a single assay. Such approaches therefore have substantial advantages (less time and less tissue required) over PCR-based methods that typically have to be combined with fluorescence in situ hybridization for detection of gene amplifications and fusions. Since these new technologies work reliably on routine diagnostic formalin-fixed, paraffin-embedded specimens, they can help expedite the broad introduction of personalized cancer therapy into the clinic by providing comprehensive, sensitive and accurate cancer genome diagnoses in 'real-time'. © The Author 2015. Published by Oxford University Press on behalf of the European Society for Medical Oncology. All rights reserved. For permissions, please email: journals.permissions@oup.com.
Characterization of HPV and host genome interactions in primary head and neck cancers

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Parfenov, Michael; Pedamallu, Chandra Sekhar; Gehlenborg, Nils; Freeman, Samuel S.; Danilova, Ludmila; Bristow, Christopher A.; Lee, Semin; Hadjipanayis, Angela G.; Ivanova, Elena V.; Wilkerson, Matthew D.; Protopopov, Alexei; Yang, Lixing; Seth, Sahil; Song, Xingzhi; Tang, Jiabin; Ren, Xiaojia; Zhang, Jianhua; Pantazi, Angeliki; Santoso, Netty; Xu, Andrew W.; Mahadeshwar, Harshad; Wheeler, David A.; Haddad, Robert I.; Jung, Joonil; Ojesina, Akinyemi I.; Issaeva, Natalia; Yarbrough, Wendell G.; Hayes, D. Neil; Grandis, Jennifer R.; El-Naggar, Adel K.; Meyerson, Matthew; Park, Peter J.; Chin, Lynda; Seidman, J. G.; Hammerman, Peter S.; Kucherlapati, Raju; Ally, Adrian; Balasundaram, Miruna; Birol, Inanc; Bowlby, Reanne; Butterfield, Yaron S.N.; Carlsen, Rebecca; Cheng, Dean; Chu, Andy; Dhalla, Noreen; Guin, Ranabir; Holt, Robert A.; Jones, Steven J.M.; Lee, Darlene; Li, Haiyan I.; Marra, Marco A.; Mayo, Michael; Moore, Richard A.; Mungall, Andrew J.; Robertson, A. Gordon; Schein, Jacqueline E.; Sipahimalani, Payal; Tam, Angela; Thiessen, Nina; Wong, Tina; Protopopov, Alexei; Santoso, Netty; Lee, Semin; Parfenov, Michael; Zhang, Jianhua; Mahadeshwar, Harshad S.; Tang, Jiabin; Ren, Xiaojia; Seth, Sahil; Haseley, Psalm; Zeng, Dong; Yang, Lixing; Xu, Andrew W.; Song, Xingzhi; Pantazi, Angeliki; Bristow, Christopher; Hadjipanayis, Angela; Seidman, Jonathan; Chin, Lynda; Park, Peter J.; Kucherlapati, Raju; Akbani, Rehan; Casasent, Tod; Liu, Wenbin; Lu, Yiling; Mills, Gordon; Motter, Thomas; Weinstein, John; Diao, Lixia; Wang, Jing; Fan, You Hong; Liu, Jinze; Wang, Kai; Auman, J. Todd; Balu, Saianand; Bodenheimer, Tom; Buda, Elizabeth; Hayes, D. Neil; Hoadley, Katherine A.; Hoyle, Alan P.; Jefferys, Stuart R.; Jones, Corbin D.; Kimes, Patrick K.; Marron, J.S.; Meng, Shaowu; Mieczkowski, Piotr A.; Mose, Lisle E.; Parker, Joel S.; Perou, Charles M.; Prins, Jan F.; Roach, Jeffrey; Shi, Yan; Simons, Janae V.; Singh, Darshan; Soloway, Mathew G.; Tan, Donghui; Veluvolu, Umadevi; Walter, Vonn; Waring, Scot; Wilkerson, Matthew D.; Wu, Junyuan; Zhao, Ni; Cherniack, Andrew D.; Hammerman, Peter S.; Tward, Aaron D.; Pedamallu, Chandra Sekhar; Saksena, Gordon; Jung, Joonil; Ojesina, Akinyemi I.; Carter, Scott L.; Zack, Travis I.; Schumacher, Steven E.; Beroukhim, Rameen; Freeman, Samuel S.; Meyerson, Matthew; Cho, Juok; Chin, Lynda; Getz, Gad; Noble, Michael S.; DiCara, Daniel; Zhang, Hailei; Heiman, David I.; Gehlenborg, Nils; Voet, Doug; Lin, Pei; Frazer, Scott; Stojanov, Petar; Liu, Yingchun; Zou, Lihua; Kim, Jaegil; Lawrence, Michael S.; Sougnez, Carrie; Lichtenstein, Lee; Cibulskis, Kristian; Lander, Eric; Gabriel, Stacey B.; Muzny, Donna; Doddapaneni, HarshaVardhan; Kovar, Christie; Reid, Jeff; Morton, Donna; Han, Yi; Hale, Walker; Chao, Hsu; Chang, Kyle; Drummond, Jennifer A.; Gibbs, Richard A.; Kakkar, Nipun; Wheeler, David; Xi, Liu; Ciriello, Giovanni; Ladanyi, Marc; Lee, William; Ramirez, Ricardo; Sander, Chris; Shen, Ronglai; Sinha, Rileen; Weinhold, Nils; Taylor, Barry S.; Aksoy, B. Arman; Dresdner, Gideon; Gao, Jianjiong; Gross, Benjamin; Jacobsen, Anders; Reva, Boris; Schultz, Nikolaus; Sumer, S. Onur; Sun, Yichao; Chan, Timothy; Morris, Luc; Stuart, Joshua; Benz, Stephen; Ng, Sam; Benz, Christopher; Yau, Christina; Baylin, Stephen B.; Cope, Leslie; Danilova, Ludmila; Herman, James G.; Bootwalla, Moiz; Maglinte, Dennis T.; Laird, Peter W.; Triche, Timothy; Weisenberger, Daniel J.; Van Den Berg, David J.; Agrawal, Nishant; Bishop, Justin; Boutros, Paul C.; Bruce, Jeff P; Byers, Lauren Averett; Califano, Joseph; Carey, Thomas E.; Chen, Zhong; Cheng, Hui; Chiosea, Simion I.; Cohen, Ezra; Diergaarde, Brenda; Egloff, Ann Marie; El-Naggar, Adel K.; Ferris, Robert L.; Frederick, Mitchell J.; Grandis, Jennifer R.; Guo, Yan; Haddad, Robert I.; Hammerman, Peter S.; Harris, Thomas; Hayes, D. Neil; Hui, Angela BY; Lee, J. Jack; Lippman, Scott M.; Liu, Fei-Fei; McHugh, Jonathan B.; Myers, Jeff; Ng, Patrick Kwok Shing; Perez-Ordonez, Bayardo; Pickering, Curtis R.; Prystowsky, Michael; Romkes, Marjorie; Saleh, Anthony D.; Sartor, Maureen A.; Seethala, Raja; Seiwert, Tanguy Y.; Si, Han; Tward, Aaron D.; Van Waes, Carter; Waggott, Daryl M.; Wiznerowicz, Maciej; Yarbrough, Wendell; Zhang, Jiexin; Zuo, Zhixiang; Burnett, Ken; Crain, Daniel; Gardner, Johanna; Lau, Kevin; Mallery, David; Morris, Scott; Paulauskis, Joseph; Penny, Robert; Shelton, Candance; Shelton, Troy; Sherman, Mark; Yena, Peggy; Black, Aaron D.; Bowen, Jay; Frick, Jessica; Gastier-Foster, Julie M.; Harper, Hollie A.; Lichtenberg, Tara M.; Ramirez, Nilsa C.; Wise, Lisa; Zmuda, Erik; Baboud, Julien; Jensen, Mark A.; Kahn, Ari B.; Pihl, Todd D.; Pot, David A.; Srinivasan, Deepak; Walton, Jessica S.; Wan, Yunhu; Burton, Robert; Davidsen, Tanja; Demchok, John A.; Eley, Greg; Ferguson, Martin L.; Shaw, Kenna R. Mills; Ozenberger, Bradley A.; Sheth, Margi; Sofia, Heidi J.; Tarnuzzer, Roy; Wang, Zhining; Yang, Liming; Zenklusen, Jean Claude; Saller, Charles; Tarvin, Katherine; Chen, Chu; Bollag, Roni; Weinberger, Paul; Golusiński, Wojciech; Golusiński, Paweł; Ibbs, Matthiew; Korski, Konstanty; Mackiewicz, Andrzej; Suchorska, Wiktoria; Szybiak, Bartosz; Wiznerowicz, Maciej; Burnett, Ken; Curley, Erin; Gardner, Johanna; Mallery, David; Penny, Robert; Shelton, Troy; Yena, Peggy; Beard, Christina; Mitchell, Colleen; Sandusky, George; Agrawal, Nishant; Ahn, Julie; Bishop, Justin; Califano, Joseph; Khan, Zubair; Bruce, Jeff P; Hui, Angela BY; Irish, Jonathan; Liu, Fei-Fei; Perez-Ordonez, Bayardo; Waldron, John; Boutros, Paul C.; Waggott, Daryl M.; Myers, Jeff; Lippman, Scott M.; Egea, Sophie; Gomez-Fernandez, Carmen; Herbert, Lynn; Bradford, Carol R.; Carey, Thomas E.; Chepeha, Douglas B.; Haddad, Andrea S.; Jones, Tamara R.; Komarck, Christine M.; Malakh, Mayya; McHugh, Jonathan B.; Moyer, Jeffrey S.; Nguyen, Ariane; Peterson, Lisa A.; Prince, Mark E.; Rozek, Laura S.; Sartor, Maureen A.; Taylor, Evan G.; Walline, Heather M.; Wolf, Gregory T.; Boice, Lori; Chera, Bhishamjit S.; Funkhouser, William K.; Gulley, Margaret L.; Hackman, Trevor G.; Hayes, D. Neil; Hayward, Michele C.; Huang, Mei; Rathmell, W. Kimryn; Salazar, Ashley H.; Shockley, William W.; Shores, Carol G.; Thorne, Leigh; Weissler, Mark C.; Wrenn, Sylvia; Zanation, Adam M.; Chiosea, Simion I.; Diergaarde, Brenda; Egloff, Ann Marie; Ferris, Robert L.; Romkes, Marjorie; Seethala, Raja; Brown, Brandee T.; Guo, Yan; Pham, Michelle; Yarbrough, Wendell G.

2014-01-01

Previous studies have established that a subset of head and neck tumors contains human papillomavirus (HPV) sequences and that HPV-driven head and neck cancers display distinct biological and clinical features. HPV is known to drive cancer by the actions of the E6 and E7 oncoproteins, but the molecular architecture of HPV infection and its interaction with the host genome in head and neck cancers have not been comprehensively described. We profiled a cohort of 279 head and neck cancers with next generation RNA and DNA sequencing and show that 35 (12.5%) tumors displayed evidence of high-risk HPV types 16, 33, or 35. Twenty-five cases had integration of the viral genome into one or more locations in the human genome with statistical enrichment for genic regions. Integrations had a marked impact on the human genome and were associated with alterations in DNA copy number, mRNA transcript abundance and splicing, and both inter- and intrachromosomal rearrangements. Many of these events involved genes with documented roles in cancer. Cancers with integrated vs. nonintegrated HPV displayed different patterns of DNA methylation and both human and viral gene expressions. Together, these data provide insight into the mechanisms by which HPV interacts with the human genome beyond expression of viral oncoproteins and suggest that specific integration events are an integral component of viral oncogenesis. PMID:25313082

Functional profiling of microtumors to identify cancer associated fibroblast-derived drug targets.

Science.gov (United States)

Horman, Shane R; To, Jeremy; Lamb, John; Zoll, Jocelyn H; Leonetti, Nicole; Tu, Buu; Moran, Rita; Newlin, Robbin; Walker, John R; Orth, Anthony P

2017-11-21

Recent advances in chemotherapeutics highlight the importance of molecularly-targeted perturbagens. Although these therapies typically address dysregulated cancer cell proteins, there are increasing therapeutic modalities that take into consideration cancer cell-extrinsic factors. Targeting components of tumor stroma such as vascular or immune cells has been shown to represent an efficacious approach in cancer treatment. Cancer-associated fibroblasts (CAFs) exemplify an important stromal component that can be exploited in targeted therapeutics, though their employment in drug discovery campaigns has been relatively minimal due to technical logistics in assaying for CAF-tumor interactions. Here we report a 3-dimensional multi-culture tumor:CAF spheroid phenotypic screening platform that can be applied to high-content drug discovery initiatives. Using a functional genomics approach we systematically profiled 1,024 candidate genes for CAF-intrinsic anti-spheroid activity; identifying several CAF genes important for development and maintenance of tumor:CAF co-culture spheroids. Along with previously reported genes such as WNT, we identify CAF-derived targets such as ARAF and COL3A1 upon which the tumor compartment depends for spheroid development. Specifically, we highlight the G-protein-coupled receptor OGR1 as a unique CAF-specific protein that may represent an attractive drug target for treating colorectal cancer. In vivo , murine colon tumor implants in OGR1 knockout mice displayed delayed tumor growth compared to tumors implanted in wild type littermate controls. These findings demonstrate a robust microphysiological screening approach for identifying new CAF targets that may be applied to drug discovery efforts.
A genomic copy number signature predicts radiation exposure in post-Chernobyl breast cancer.

Science.gov (United States)

Wilke, Christina M; Braselmann, Herbert; Hess, Julia; Klymenko, Sergiy V; Chumak, Vadim V; Zakhartseva, Liubov M; Bakhanova, Elena V; Walch, Axel K; Selmansberger, Martin; Samaga, Daniel; Weber, Peter; Schneider, Ludmila; Fend, Falko; Bösmüller, Hans C; Zitzelsberger, Horst; Unger, Kristian

2018-04-16

Breast cancer is the second leading cause of cancer death among women worldwide and besides life style, age and genetic risk factors, exposure to ionizing radiation is known to increase the risk for breast cancer. Further, DNA copy number alterations (CNAs), which can result from radiation-induced double-strand breaks, are frequently occurring in breast cancer cells. We set out to identify a signature of CNAs discriminating breast cancers from radiation-exposed and non-exposed female patients. We analyzed resected breast cancer tissues from 68 exposed female Chernobyl clean-up workers and evacuees and 68 matched non-exposed control patients for CNAs by array comparative genomic hybridization analysis (aCGH). Using a stepwise forward-backward selection approach a non-complex CNA signature, that is, less than ten features, was identified in the training data set, which could be subsequently validated in the validation data set (p value < 0.05). The signature consisted of nine copy number regions located on chromosomal bands 7q11.22-11.23, 7q21.3, 16q24.3, 17q21.31, 20p11.23-11.21, 1p21.1, 2q35, 2q35, 6p22.2. The signature was independent of any clinical characteristics of the patients. In all, we identified a CNA signature that has the potential to allow identification of radiation-associated breast cancer at the individual level. © 2018 UICC.
Genomic Characterization of Primary Invasive Lobular Breast Cancer.

Science.gov (United States)

Desmedt, Christine; Zoppoli, Gabriele; Gundem, Gunes; Pruneri, Giancarlo; Larsimont, Denis; Fornili, Marco; Fumagalli, Debora; Brown, David; Rothé, Françoise; Vincent, Delphine; Kheddoumi, Naima; Rouas, Ghizlane; Majjaj, Samira; Brohée, Sylvain; Van Loo, Peter; Maisonneuve, Patrick; Salgado, Roberto; Van Brussel, Thomas; Lambrechts, Diether; Bose, Ron; Metzger, Otto; Galant, Christine; Bertucci, François; Piccart-Gebhart, Martine; Viale, Giuseppe; Biganzoli, Elia; Campbell, Peter J; Sotiriou, Christos

2016-06-01

Invasive lobular breast cancer (ILBC) is the second most common histologic subtype after invasive ductal breast cancer (IDBC). Despite clinical and pathologic differences, ILBC is still treated as IDBC. We aimed to identify genomic alterations in ILBC with potential clinical implications. From an initial 630 ILBC primary tumors, we interrogated oncogenic substitutions and insertions and deletions of 360 cancer genes and genome-wide copy number aberrations in 413 and 170 ILBC samples, respectively, and correlated those findings with clinicopathologic and outcome features. Besides the high mutation frequency of CDH1 in 65% of tumors, alterations in one of the three key genes of the phosphatidylinositol 3-kinase pathway, PIK3CA, PTEN, and AKT1, were present in more than one-half of the cases. HER2 and HER3 were mutated in 5.1% and 3.6% of the tumors, with most of these mutations having a proven role in activating the human epidermal growth factor receptor/ERBB pathway. Mutations in FOXA1 and ESR1 copy number gains were detected in 9% and 25% of the samples. All these alterations were more frequent in ILBC than in IDBC. The histologic diversity of ILBC was associated with specific alterations, such as enrichment for HER2 mutations in the mixed, nonclassic, and ESR1 gains in the solid subtype. Survival analyses revealed that chromosome 1q and 11p gains showed independent prognostic value in ILBC and that HER2 and AKT1 mutations were associated with increased risk of early relapse. This study demonstrates that we can now begin to individualize the treatment of ILBC, with HER2, HER3, and AKT1 mutations representing high-prevalence therapeutic targets and FOXA1 mutations and ESR1 gains deserving urgent dedicated clinical investigation, especially in the context of endocrine treatment. © 2016 by American Society of Clinical Oncology.
Integrative Analysis of Complex Cancer Genomics and Clinical Profiles Using the cBioPortal

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Gao, Jianjiong; Aksoy, Bülent Arman; Dogrusoz, Ugur; Dresdner, Gideon; Gross, Benjamin; Sumer, S. Onur; Sun, Yichao; Jacobsen, Anders; Sinha, Rileen; Larsson, Erik; Cerami, Ethan; Sander, Chris; Schultz, Nikolaus

2014-01-01

The cBioPortal for Cancer Genomics (http://cbioportal.org) provides a Web resource for exploring, visualizing, and analyzing multidimensional cancer genomics data. The portal reduces molecular profiling data from cancer tissues and cell lines into readily understandable genetic, epigenetic, gene expression, and proteomic events. The query interface combined with customized data storage enables researchers to interactively explore genetic alterations across samples, genes, and pathways and, when available in the underlying data, to link these to clinical outcomes. The portal provides graphical summaries of gene-level data from multiple platforms, network visualization and analysis, survival analysis, patient-centric queries, and software programmatic access. The intuitive Web interface of the portal makes complex cancer genomics profiles accessible to researchers and clinicians without requiring bioinformatics expertise, thus facilitating biological discoveries. Here, we provide a practical guide to the analysis and visualization features of the cBioPortal for Cancer Genomics. PMID:23550210
Fine-Scale Mapping at 9p22.2 Identifies Candidate Causal Variants That Modify Ovarian Cancer Risk in BRCA1 and BRCA2 Mutation Carriers

NARCIS (Netherlands)

Vigorito, E.; Kuchenbaecker, K.B.; Beesley, J.; Adlard, J.; Agnarsson, B.A.; Andrulis, I.L.; Arun, B.K.; Barjhoux, L.; Belotti, M.; Benitez, J.; Berger, A.; Bojesen, A.; Bonanni, B.; Brewer, C.; Caldes, T.; Caligo, M.A.; Campbell, I.; Chan, S.B.; Claes, K.B.; Cohn, D.E.; Cook, J.; Daly, M.B.; Damiola, F.; Davidson, R.; Pauw, A. de; Delnatte, C.; Diez, O.; Domchek, S.M.; Dumont, M.; Durda, K.; Dworniczak, B.; Easton, D.F.; Eccles, D.; Edwinsdotter Ardnor, C.; Eeles, R.; Ejlertsen, B.; Ellis, S.; Evans, D.G.; Feliubadalo, L.; Fostira, F.; Foulkes, W.D.; Friedman, E.; Frost, D.; Gaddam, P.; Ganz, P.A.; Garber, J.; Garcia-Barberan, V.; Gauthier-Villars, M.; Gehrig, A.; Gerdes, A.M.; Giraud, S.; Godwin, A.K.; Goldgar, D.E.; Hake, C.R.; Hansen, T.V.; Healey, S.; Hodgson, S.; Hogervorst, F.B.; Houdayer, C.; Hulick, P.J.; Imyanitov, E.N.; Isaacs, C.; Izatt, L.; Izquierdo, A.; Jacobs, L; Jakubowska, A.; Janavicius, R.; Jaworska-Bieniek, K.; Jensen, U.B.; John, E.M.; Vijai, J.; Karlan, B.Y.; Kast, K.; Khan, S.; Kwong, A.; Laitman, Y.; Lester, J.; Lesueur, F.; Liljegren, A.; Lubinski, J.; Mai, P.L.; Manoukian, S.; Mazoyer, S.; Meindl, A.; Mensenkamp, A.R.; Montagna, M.; Nathanson, K.L.; Neuhausen, S.L.; Nevanlinna, H.; Niederacher, D.; Olah, E.; Olopade, O.I.; Ong, K.R.; Osorio, A.; Park, S.K.; Paulsson-Karlsson, Y.; Pedersen, I.S.; Peissel, B.; Peterlongo, P.; et al.,

2016-01-01

Population-based genome wide association studies have identified a locus at 9p22.2 associated with ovarian cancer risk, which also modifies ovarian cancer risk in BRCA1 and BRCA2 mutation carriers. We conducted fine-scale mapping at 9p22.2 to identify potential causal variants in BRCA1 and BRCA2
Fine-Scale Mapping at 9p22.2 Identifies Candidate Causal Variants That Modify Ovarian Cancer Risk in BRCA1 and BRCA2 Mutation Carriers

DEFF Research Database (Denmark)

Vigorito, Elena; Kuchenbaecker, Karoline B; Beesley, Jonathan

2016-01-01

Population-based genome wide association studies have identified a locus at 9p22.2 associated with ovarian cancer risk, which also modifies ovarian cancer risk in BRCA1 and BRCA2 mutation carriers. We conducted fine-scale mapping at 9p22.2 to identify potential causal variants in BRCA1 and BRCA2 ...
Genome-wide association analysis in East Asians identifies breast cancer susceptibility loci at 1q32.1, 5q14.3 and 15q26.1

Science.gov (United States)

Cai, Qiuyin; Zhang, Ben; Sung, Hyuna; Low, Siew-Kee; Kweon, Sun-Seog; Lu, Wei; Shi, Jiajun; Long, Jirong; Wen, Wanqing; Choi, Ji-Yeob; Noh, Dong-Young; Shen, Chen-Yang; Matsuo, Keitaro; Teo, Soo-Hwang; Kim, Mi Kyung; Khoo, Ui Soon; Iwasaki, Motoki; Hartman, Mikael; Takahashi, Atsushi; Ashikawa, Kyota; Matsuda, Koichi; Shin, Min-Ho; Park, Min Ho; Zheng, Ying; Xiang, Yong-Bing; Ji, Bu-Tian; Park, Sue K.; Wu, Pei-Ei; Hsiung, Chia-Ni; Ito, Hidemi; Kasuga, Yoshio; Kang, Peter; Mariapun, Shivaani; Ahn, Sei Hyun; Kang, Han Sung; Chan, Kelvin Y. K.; Man, Ellen P. S.; Iwata, Hiroji; Tsugane, Shoichiro; Miao, Hui; Liao, Jiemin; Nakamura, Yusuke; Kubo, Michiaki; Delahanty, Ryan J.; Zhang, Yanfeng; Li, Bingshan; Li, Chun; Gao, Yu-Tang; Shu, Xiao-Ou; Kang, Daehee; Zheng, Wei

2014-01-01

In a three-stage genome-wide association study among East Asian women including 22,780 cases and 24,181 controls, we identified three novel genetic loci associated with breast cancer risk, including rs4951011 at 1q32.1 (in intron 2 of the ZC3H11A gene, P = 8.82 × 10−9), rs10474352 at 5q14.3 (near the ARRDC3 gene, P = 1.67 × 10−9), and rs2290203 at 15q26.1 (in intron 14 of the PRC1 gene, P = 4.25 × 10−8). These associations were replicated in European-ancestry populations including 16,003 cases and 41,335 controls (P = 0.030, 0.004, and 0.010, respectively). Data from the ENCODE project suggest that variants rs4951011 and rs10474352 may be located in an enhancer region and transcription factor binding sites, respectively. This study provides additional insights into the genetics and biology of breast cancer. PMID:25038754
Differentiation among prostate cancer patients with Gleason score of 7 using histopathology whole-slide image and genomic data

Science.gov (United States)

Ren, Jian; Karagoz, Kubra; Gatza, Michael; Foran, David J.; Qi, Xin

2018-03-01

Prostate cancer is the most common non-skin related cancer affecting 1 in 7 men in the United States. Treatment of patients with prostate cancer still remains a difficult decision-making process that requires physicians to balance clinical benefits, life expectancy, comorbidities, and treatment-related side effects. Gleason score (a sum of the primary and secondary Gleason patterns) solely based on morphological prostate glandular architecture has shown as one of the best predictors of prostate cancer outcome. Significant progress has been made on molecular subtyping prostate cancer delineated through the increasing use of gene sequencing. Prostate cancer patients with Gleason score of 7 show heterogeneity in recurrence and survival outcomes. Therefore, we propose to assess the correlation between histopathology images and genomic data with disease recurrence in prostate tumors with a Gleason 7 score to identify prognostic markers. In the study, we identify image biomarkers within tissue WSIs by modeling the spatial relationship from automatically created patches as a sequence within WSI by adopting a recurrence network model, namely long short-term memory (LSTM). Our preliminary results demonstrate that integrating image biomarkers from CNN with LSTM and genomic pathway scores, is more strongly correlated with patients recurrence of disease compared to standard clinical markers and engineered image texture features. The study further demonstrates that prostate cancer patients with Gleason score of 4+3 have a higher risk of disease progression and recurrence compared to prostate cancer patients with Gleason score of 3+4.
Quantitative high-resolution genomic analysis of single cancer cells.

Directory of Open Access Journals (Sweden)

Juliane Hannemann

Full Text Available During cancer progression, specific genomic aberrations arise that can determine the scope of the disease and can be used as predictive or prognostic markers. The detection of specific gene amplifications or deletions in single blood-borne or disseminated tumour cells that may give rise to the development of metastases is of great clinical interest but technically challenging. In this study, we present a method for quantitative high-resolution genomic analysis of single cells. Cells were isolated under permanent microscopic control followed by high-fidelity whole genome amplification and subsequent analyses by fine tiling array-CGH and qPCR. The assay was applied to single breast cancer cells to analyze the chromosomal region centred by the therapeutical relevant EGFR gene. This method allows precise quantitative analysis of copy number variations in single cell diagnostics.
Cloud Based Resource for Data Hosting, Visualization and Analysis Using UCSC Cancer Genomics Browser | Informatics Technology for Cancer Research (ITCR)

Science.gov (United States)

The Cancer Analysis Virtual Machine (CAVM) project will leverage cloud technology, the UCSC Cancer Genomics Browser, and the Galaxy analysis workflow system to provide investigators with a flexible, scalable platform for hosting, visualizing and analyzing their own genomic data.
Managing the genomic revolution in cancer diagnostics.

Science.gov (United States)

Nguyen, Doreen; Gocke, Christopher D

2017-08-01

Molecular tumor profiling is now a routine part of patient care, revealing targetable genomic alterations and molecularly distinct tumor subtypes with therapeutic and prognostic implications. The widespread adoption of next-generation sequencing technologies has greatly facilitated clinical implementation of genomic data and opened the door for high-throughput multigene-targeted sequencing. Herein, we discuss the variability of cancer genetic profiling currently offered by clinical laboratories, the challenges of applying rapidly evolving medical knowledge to individual patients, and the need for more standardized population-based molecular profiling.
Use of genome-wide association studies for cancer research and drug repositioning.

Directory of Open Access Journals (Sweden)

Jizhun Zhang

Full Text Available Although genome-wide association studies have identified many risk loci associated with colorectal cancer, the molecular basis of these associations are still unclear. We aimed to infer biological insights and highlight candidate genes of interest within GWAS risk loci. We used an in silico pipeline based on functional annotation, quantitative trait loci mapping of cis-acting gene, PubMed text-mining, protein-protein interaction studies, genetic overlaps with cancer somatic mutations and knockout mouse phenotypes, and functional enrichment analysis to prioritize the candidate genes at the colorectal cancer risk loci. Based on these analyses, we observed that these genes were the targets of approved therapies for colorectal cancer, and suggested that drugs approved for other indications may be repurposed for the treatment of colorectal cancer. This study highlights the use of publicly available data as a cost effective solution to derive biological insights, and provides an empirical evidence that the molecular basis of colorectal cancer can provide important leads for the discovery of new drugs.
Genomic features of lobular breast carcinoma

Science.gov (United States)

Investigators with The Cancer Genome Atlas (TCGA) Research Network have identified molecular characteristics of a type of breast cancer, invasive lobular carcinoma (ILC), that distinguishes it from invasive ductal carcinoma (IDC), the most common invasive breast cancer subtype.
Noncoding Genomics in Gastric Cancer and the Gastric Precancerous Cascade: Pathogenesis and Biomarkers

Directory of Open Access Journals (Sweden)

Alejandra Sandoval-Bórquez

2015-01-01

Full Text Available Gastric cancer is the fifth most common cancer and the third leading cause of cancer-related death, whose patterns vary among geographical regions and ethnicities. It is a multifactorial disease, and its development depends on infection by Helicobacter pylori (H. pylori and Epstein-Barr virus (EBV, host genetic factors, and environmental factors. The heterogeneity of the disease has begun to be unraveled by a comprehensive mutational evaluation of primary tumors. The low-abundance of mutations suggests that other mechanisms participate in the evolution of the disease, such as those found through analyses of noncoding genomics. Noncoding genomics includes single nucleotide polymorphisms (SNPs, regulation of gene expression through DNA methylation of promoter sites, miRNAs, other noncoding RNAs in regulatory regions, and other topics. These processes and molecules ultimately control gene expression. Potential biomarkers are appearing from analyses of noncoding genomics. This review focuses on noncoding genomics and potential biomarkers in the context of gastric cancer and the gastric precancerous cascade.
The Naked Mole Rat Genome Resource: facilitating analyses of cancer and longevity-related adaptations.

Science.gov (United States)

Keane, Michael; Craig, Thomas; Alföldi, Jessica; Berlin, Aaron M; Johnson, Jeremy; Seluanov, Andrei; Gorbunova, Vera; Di Palma, Federica; Lindblad-Toh, Kerstin; Church, George M; de Magalhães, João Pedro

2014-12-15

The naked mole rat (Heterocephalus glaber) is an exceptionally long-lived and cancer-resistant rodent native to East Africa. Although its genome was previously sequenced, here we report a new assembly sequenced by us with substantially higher N50 values for scaffolds and contigs. We analyzed the annotation of this new improved assembly and identified candidate genomic adaptations which may have contributed to the evolution of the naked mole rat's extraordinary traits, including in regions of p53, and the hyaluronan receptors CD44 and HMMR (RHAMM). Furthermore, we developed a freely available web portal, the Naked Mole Rat Genome Resource (http://www.naked-mole-rat.org), featuring the data and results of our analysis, to assist researchers interested in the genome and genes of the naked mole rat, and also to facilitate further studies on this fascinating species. © The Author 2014. Published by Oxford University Press.
Early Onset Malignancies - Genomic Study of Cancer Disparities

Science.gov (United States)

The Early Onset Malignancies Initiative studies the genomic basis of six cancers that develop at an earlier age, occur in higher rates, and are typically more aggressive in certain minority populations.
Prospective Genomic Profiling of Prostate Cancer Across Disease States Reveals Germline and Somatic Alterations That May Affect Clinical Decision Making.

Science.gov (United States)

Abida, Wassim; Armenia, Joshua; Gopalan, Anuradha; Brennan, Ryan; Walsh, Michael; Barron, David; Danila, Daniel; Rathkopf, Dana; Morris, Michael; Slovin, Susan; McLaughlin, Brigit; Curtis, Kristen; Hyman, David M; Durack, Jeremy C; Solomon, Stephen B; Arcila, Maria E; Zehir, Ahmet; Syed, Aijazuddin; Gao, Jianjiong; Chakravarty, Debyani; Vargas, Hebert Alberto; Robson, Mark E; Joseph, Vijai; Offit, Kenneth; Donoghue, Mark T A; Abeshouse, Adam A; Kundra, Ritika; Heins, Zachary J; Penson, Alexander V; Harris, Christopher; Taylor, Barry S; Ladanyi, Marc; Mandelker, Diana; Zhang, Liying; Reuter, Victor E; Kantoff, Philip W; Solit, David B; Berger, Michael F; Sawyers, Charles L; Schultz, Nikolaus; Scher, Howard I

2017-07-01

A long natural history and a predominant osseous pattern of metastatic spread are impediments to the adoption of precision medicine in patients with prostate cancer. To establish the feasibility of clinical genomic profiling in the disease, we performed targeted deep sequencing of tumor and normal DNA from patients with locoregional, metastatic non-castrate, and metastatic castration-resistant prostate cancer (CRPC). Patients consented to genomic analysis of their tumor and germline DNA. A hybridization capture-based clinical assay was employed to identify single nucleotide variations, small insertions and deletions, copy number alterations and structural rearrangements in over 300 cancer-related genes in tumors and matched normal blood. We successfully sequenced 504 tumors from 451 patients with prostate cancer. Potentially actionable alterations were identified in DNA damage repair (DDR), PI3K, and MAP kinase pathways. 27% of patients harbored a germline or a somatic alteration in a DDR gene that may predict for response to PARP inhibition. Profiling of matched tumors from individual patients revealed that somatic TP53 and BRCA2 alterations arose early in tumors from patients who eventually developed metastatic disease. In contrast, comparative analysis across disease states revealed that APC alterations were enriched in metastatic tumors, while ATM alterations were specifically enriched in CRPC. Through genomic profiling of prostate tumors representing the disease clinical spectrum, we identified a high frequency of potentially actionable alterations and possible drivers of disease initiation, metastasis and castration-resistance. Our findings support the routine use of tumor and germline DNA profiling for patients with advanced prostate cancer, for the purpose of guiding enrollment in targeted clinical trials and counseling families at increased risk of malignancy.
Multi-platform whole-genome microarray analyses refine the epigenetic signature of breast cancer metastasis with gene expression and copy number.

Directory of Open Access Journals (Sweden)

Joseph Andrews

2010-01-01

Full Text Available We have previously identified genome-wide DNA methylation changes in a cell line model of breast cancer metastasis. These complex epigenetic changes that we observed, along with concurrent karyotype analyses, have led us to hypothesize that complex genomic alterations in cancer cells (deletions, translocations and ploidy are superimposed over promoter-specific methylation events that are responsible for gene-specific expression changes observed in breast cancer metastasis.We undertook simultaneous high-resolution, whole-genome analyses of MDA-MB-468GFP and MDA-MB-468GFP-LN human breast cancer cell lines (an isogenic, paired lymphatic metastasis cell line model using Affymetrix gene expression (U133, promoter (1.0R, and SNP/CNV (SNP 6.0 microarray platforms to correlate data from gene expression, epigenetic (DNA methylation, and combination copy number variant/single nucleotide polymorphism microarrays. Using Partek Software and Ingenuity Pathway Analysis we integrated datasets from these three platforms and detected multiple hypomethylation and hypermethylation events. Many of these epigenetic alterations correlated with gene expression changes. In addition, gene dosage events correlated with the karyotypic differences observed between the cell lines and were reflected in specific promoter methylation patterns. Gene subsets were identified that correlated hyper (and hypo methylation with the loss (or gain of gene expression and in parallel, with gene dosage losses and gains, respectively. Individual gene targets from these subsets were also validated for their methylation, expression and copy number status, and susceptible gene pathways were identified that may indicate how selective advantage drives the processes of tumourigenesis and metastasis.Our approach allows more precisely profiling of functionally relevant epigenetic signatures that are associated with cancer progression and metastasis.
Genetic profiles of gastroesophageal cancer: combined analysis using expression array and tiling array--comparative genomic hybridization

DEFF Research Database (Denmark)

Isinger-Ekstrand, Anna; Johansson, Jan; Ohlsson, Mattias

2010-01-01

15, 13q34, and 12q13, whereas different profiles with gains at 5p15, 7p22, 2q35, and 13q34 characterized gastric cancers. CDK6 and EGFR were identified as putative target genes in cancers of the esophagus and the gastroesophageal junction, with upregulation in one quarter of the tumors. Gains......We aimed to characterize the genomic profiles of adenocarcinomas in the gastroesophageal junction in relation to cancers in the esophagus and the stomach. Profiles of gains/losses as well as gene expression profiles were obtained from 27 gastroesophageal adenocarcinomas by means of 32k high......-resolution array-based comparative genomic hybridization and 27k oligo gene expression arrays, and putative target genes were validated in an extended series. Adenocarcinomas in the distal esophagus and the gastroesophageal junction showed strong similarities with the most common gains at 20q13, 8q24, 1q21-23, 5p...
Identifying molecular subtypes in human colon cancer using gene expression and DNA methylation microarray data.

Science.gov (United States)

Ren, Zhonglu; Wang, Wenhui; Li, Jinming

2016-02-01

Identifying colon cancer subtypes based on molecular signatures may allow for a more rational, patient-specific approach to therapy in the future. Classifications using gene expression data have been attempted before with little concordance between the different studies carried out. In this study we aimed to uncover subtypes of colon cancer that have distinct biological characteristics and identify a set of novel biomarkers which could best reflect the clinical and/or biological characteristics of each subtype. Clustering analysis and discriminant analysis were utilized to discover the subtypes in two different molecular levels on 153 colon cancer samples from The Cancer Genome Atlas (TCGA) Data Portal. At gene expression level, we identified two major subtypes, ECL1 (expression cluster 1) and ECL2 (expression cluster 2) and a list of signature genes. Due to the heterogeneity of colon cancer, the subtype ECL1 can be further subdivided into three nested subclasses, and HOTAIR were found upregulated in subclass 2. At DNA methylation level, we uncovered three major subtypes, MCL1 (methylation cluster 1), MCL2 (methylation cluster 2) and MCL3 (methylation cluster 3). We found only three subtypes of CpG island methylator phenotype (CIMP) in colon cancer instead of the four subtypes in the previous reports, and we found no sufficient evidence to subdivide MCL3 into two distinct subgroups.

Large-scale association analysis identifies new lung cancer susceptibility loci and heterogeneity in genetic susceptibility across histological subtypes

Science.gov (United States)

McKay, James D.; Hung, Rayjean J.; Han, Younghun; Zong, Xuchen; Carreras-Torres, Robert; Christiani, David C.; Caporaso, Neil E.; Johansson, Mattias; Xiao, Xiangjun; Li, Yafang; Byun, Jinyoung; Dunning, Alison; Pooley, Karen A.; Qian, David C.; Ji, Xuemei; Liu, Geoffrey; Timofeeva, Maria N.; Bojesen, Stig E.; Wu, Xifeng; Le Marchand, Loic; Albanes, Demetrios; Bickeböller, Heike; Aldrich, Melinda C.; Bush, William S.; Tardon, Adonina; Rennert, Gad; Teare, M. Dawn; Field, John K.; Kiemeney, Lambertus A.; Lazarus, Philip; Haugen, Aage; Lam, Stephen; Schabath, Matthew B.; Andrew, Angeline S.; Shen, Hongbing; Hong, Yun-Chul; Yuan, Jian-Min; Bertazzi, Pier Alberto; Pesatori, Angela C.; Ye, Yuanqing; Diao, Nancy; Su, Li; Zhang, Ruyang; Brhane, Yonathan; Leighl, Natasha; Johansen, Jakob S.; Mellemgaard, Anders; Saliba, Walid; Haiman, Christopher A.; Wilkens, Lynne R.; Fernandez-Somoano, Ana; Fernandez-Tardon, Guillermo; van der Heijden, Henricus F.M.; Kim, Jin Hee; Dai, Juncheng; Hu, Zhibin; Davies, Michael PA; Marcus, Michael W.; Brunnström, Hans; Manjer, Jonas; Melander, Olle; Muller, David C.; Overvad, Kim; Trichopoulou, Antonia; Tumino, Rosario; Doherty, Jennifer A.; Barnett, Matt P.; Chen, Chu; Goodman, Gary E.; Cox, Angela; Taylor, Fiona; Woll, Penella; Brüske, Irene; Wichmann, H.-Erich; Manz, Judith; Muley, Thomas R.; Risch, Angela; Rosenberger, Albert; Grankvist, Kjell; Johansson, Mikael; Shepherd, Frances A.; Tsao, Ming-Sound; Arnold, Susanne M.; Haura, Eric B.; Bolca, Ciprian; Holcatova, Ivana; Janout, Vladimir; Kontic, Milica; Lissowska, Jolanta; Mukeria, Anush; Ognjanovic, Simona; Orlowski, Tadeusz M.; Scelo, Ghislaine; Swiatkowska, Beata; Zaridze, David; Bakke, Per; Skaug, Vidar; Zienolddiny, Shanbeh; Duell, Eric J.; Butler, Lesley M.; Koh, Woon-Puay; Gao, Yu-Tang; Houlston, Richard S.; McLaughlin, John; Stevens, Victoria L.; Joubert, Philippe; Lamontagne, Maxime; Nickle, David C.; Obeidat, Ma’en; Timens, Wim; Zhu, Bin; Song, Lei; Kachuri, Linda; Artigas, María Soler; Tobin, Martin D.; Wain, Louise V.; Rafnar, Thorunn; Thorgeirsson, Thorgeir E.; Reginsson, Gunnar W.; Stefansson, Kari; Hancock, Dana B.; Bierut, Laura J.; Spitz, Margaret R.; Gaddis, Nathan C.; Lutz, Sharon M.; Gu, Fangyi; Johnson, Eric O.; Kamal, Ahsan; Pikielny, Claudio; Zhu, Dakai; Lindströem, Sara; Jiang, Xia; Tyndale, Rachel F.; Chenevix-Trench, Georgia; Beesley, Jonathan; Bossé, Yohan; Chanock, Stephen; Brennan, Paul; Landi, Maria Teresa; Amos, Christopher I.

2017-01-01

Summary While several lung cancer susceptibility loci have been identified, much of lung cancer heritability remains unexplained. Here, 14,803 cases and 12,262 controls of European descent were genotyped on the OncoArray and combined with existing data for an aggregated GWAS analysis of lung cancer on 29,266 patients and 56,450 controls. We identified 18 susceptibility loci achieving genome wide significance, including 10 novel loci. The novel loci highlighted the striking heterogeneity in genetic susceptibility across lung cancer histological subtypes, with four loci associated with lung cancer overall and six with lung adenocarcinoma. Gene expression quantitative trait analysis (eQTL) in 1,425 normal lung tissues highlighted RNASET2, SECISBP2L and NRG1 as candidate genes. Other loci include genes such as a cholinergic nicotinic receptor, CHRNA2, and the telomere-related genes, OFBC1 and RTEL1. Further exploration of the target genes will continue to provide new insights into the etiology of lung cancer. PMID:28604730
Genome-Wide Association Study in BRCA1 Mutation Carriers Identifies Novel Loci Associated with Breast and Ovarian Cancer Risk

NARCIS (Netherlands)

F.J. Couch (Fergus); X. Wang (Xing); L. McGuffog (Lesley); A. Lee (Andrew); C. Olswold (Curtis); K.B. Kuchenbaecker (Karoline); P. Soucy (Penny); Z. Fredericksen (Zachary); D. Barrowdale (Daniel); J. Dennis (Joe); M.M. Gaudet (Mia); E. Dicks (Ed); M. Kosel (Matthew); S. Healey (Sue); O. Sinilnikova (Olga); F. Bacot (Francois); D. Vincent (Daniel); F.B.L. Hogervorst (Frans); S. Peock (Susan); D. Stoppa-Lyonnet (Dominique); A. Jakubowska (Anna); P. Radice (Paolo); R.K. Schmutzler (Rita); S.M. Domchek (Susan); M. Piedmonte (Marion); C.F. Singer (Christian); E. Friedman (Eitan); M. Thomassen (Mads); T.V.O. Hansen (Thomas); S.L. Neuhausen (Susan); C. Szabo (Csilla); I. Blanco (Ignacio); M.H. Greene (Mark); B.Y. Karlan (Beth); J. Garber; C. Phelan (Catherine); J.N. Weitzel (Jeffrey); M. Montagna (Marco); E. Olah; I.L. Andrulis (Irene); A.K. Godwin (Andrew); D. Yannoukakos (Drakoulis); D. Goldgar (David); T. Caldes (Trinidad); H. Nevanlinna (Heli); A. Osorio (Ana); M.-B. Terry (Mary-Beth); M.B. Daly (Mary); E.J. van Rensburg (Elizabeth); U. Hamann (Ute); S.J. Ramus (Susan); A. Ewart-Toland (Amanda); M.A. Caligo (Maria); O.I. Olopade (Olofunmilayo); N. Tung (Nadine); K. Claes (Kathleen); M.S. Beattie (Mary); M.C. Southey (Melissa); E.N. Imyanitov (Evgeny); M. Tischkowitz (Marc); R. Janavicius (Ramunas); E.M. John (Esther); A. Kwong (Ava); O. Diez (Orland); J. Balmana (Judith); R.B. Barkardottir (Rosa); B.K. Arun (Banu); G. Rennert (Gad); S.-H. Teo (Soo-Hwang); P.A. Ganz (Patricia); I. Campbell (Ian); A.H. van der Hout (Annemarie); C.H.M. van Deurzen (Carolien); C.M. Seynaeve (Caroline); E.B. Gómez García (Encarna); F.E. van Leeuwen (F.); H. Meijers-Heijboer (Hanne); J.J. Gille (Johan); M.G.E.M. Ausems (Margreet); M.J. Blok (Marinus); M.J. Ligtenberg (Marjolijn); M.A. Rookus (Matti); P. Devilee (Peter); S. Verhoef; T.A.M. van Os (Theo); J.T. Wijnen (Juul); D. Frost (Debra); S. Ellis (Steve); E. Fineberg (Elena); R. Platte (Radka); D.G. Evans (Gareth); L. Izatt (Louise); R. Eeles (Rosalind); J.W. Adlard (Julian); D. Eccles (Diana); J. Cook (Jackie); C. Brewer (C.); F. Douglas (Fiona); S.V. Hodgson (Shirley); P.J. Morrison (Patrick); L. Side (Lucy); A. Donaldson (Alan); C. Houghton (Catherine); M.T. Rogers (Mark); H. Dorkins (Huw); J. Eason (Jacqueline); H. Gregory (Helen); E. McCann (Emma); A. Murray (Alexandra); A. Calender (Alain); A. Hardouin (Agnès); P. Berthet (Pascaline); C.D. Delnatte (Capucine); C. Nogues (Catherine); C. Lasset (Christine); C. Houdayer (Claude); D. Leroux (Dominique); E. Rouleau (Etienne); F. Prieur (Fabienne); F. Damiola (Francesca); H. Sobol (Hagay); I. Coupier (Isabelle); L. Vénat-Bouvet (Laurence); L. Castera (Laurent); M. Gauthier-Villars (Marion); M. Léone (Mélanie); P. Pujol (Pascal); S. Mazoyer (Sylvie); Y.-J. Bignon (Yves-Jean); E. Złowocka-Perłowska (Elzbieta); J. Gronwald (Jacek); J. Lubinski (Jan); K. Durda (Katarzyna); K. Jaworska (Katarzyna); T. Huzarski (Tomasz); A.B. Spurdle (Amanda); A. Viel (Alessandra); B. Peissel (Bernard); B. Bonnani (Bernardo); G. Melloni (Giulia); L. Ottini (Laura); L. Papi (Laura); L. Varesco (Liliana); M.G. Tibiletti (Maria Grazia); P. Peterlongo (Paolo); S. Volorio (Sara); S. Manoukian (Siranoush); V. Pensotti (Valeria); N. Arnold (Norbert); C. Engel (Christoph); H. Deissler (Helmut); D. Gadzicki (Dorothea); P.A. Gehrig (Paola A.); K. Kast (Karin); K. Rhiem (Kerstin); A. Meindl (Alfons); D. Niederacher (Dieter); N. Ditsch (Nina); H. Plendl (Hansjoerg); S. Preisler-Adams (Sabine); S. Engert (Stefanie); C. Sutter (Christian); R. Varon-Mateeva (Raymonda); B. Wapenschmidt (Barbara); B.H.F. Weber (Bernhard); B. Arver (Brita Wasteson); M. Stenmark-Askmalm (M.); N. Loman (Niklas); R. Rosenquist (R.); Z. Einbeigi (Zakaria); K.L. Nathanson (Katherine); R. Rebbeck (Timothy); S.V. Blank (Stephanie); D.E. Cohn (David); G.C. Rodriguez (Gustavo); L. Small (Laurie); M. Friedlander (Michael); V.L. Bae-Jump (Victoria L.); A. Fink-Retter (Anneliese); C. Rappaport (Christine); D. Gschwantler-Kaulich (Daphne); G. Pfeiler (Georg); M.-K. Tea; N.M. Lindor (Noralane); B. Kaufman (Bella); S. Shimon Paluch (Shani); Y. Laitman (Yael); A.-B. Skytte (Anne-Bine); A-M. Gerdes (Anne-Marie); I.S. Pedersen (Inge Sokilde); S.T. Moeller (Sanne Traasdahl); T.A. Kruse (Torben); U.B. Jensen; J. Vijai (Joseph); K. Sarrel (Kara); M. Robson (Mark); N. Kauff (Noah); A.M. Mulligan (Anna Marie); G. Glendon (Gord); H. Ozcelik (Hilmi); B. Ejlertsen (Bent); F.C. Nielsen (Finn); L. Jønson (Lars); M.K. Andersen (Mette); Y.C. Ding (Yuan); L. Steele (Linda); L. Foretova (Lenka); A. Teulé (A.); C. Lazaro (Conxi); J. Brunet (Joan); M.A. Pujana (Miguel); P.L. Mai (Phuong); J.T. Loud (Jennifer); C.S. Walsh (Christine); K.J. Lester (Kathryn); S. Orsulic (Sandra); S. Narod (Steven); J. Herzog (Josef); S.R. Sand (Sharon); S. Tognazzo (Silvia); S. Agata (Simona); T. Vaszko (Tibor); J. Weaver (JoEllen); A. Stavropoulou (Alexandra); S.S. Buys (Saundra); A. Romero (Alfonso); M. de La Hoya (Miguel); K. Aittomäki (Kristiina); T.A. Muranen (Taru); M. Durán (Mercedes); W.K. Chung (Wendy); A. Lasa (Adriana); C.M. Dorfling (Cecelia); A. Miron (Alexander); J. Benítez (Javier); L. Senter (Leigha); D. Huo (Dezheng); S. Chan (Salina); A. Sokolenko (Anna); J. Chiquette (Jocelyne); L. Tihomirova (Laima); M.O.W. Friebel (Mark ); B.A. Agnarsson (Bjarni); K.H. Lu (Karen); F. Lejbkowicz (Flavio); P.A. James (Paul ); A.S. Hall (Alistair); A.M. Dunning (Alison); Y. Tessier (Yann); J. Cunningham (Jane); S. Slager (Susan); C. Wang (Chen); S. Hart (Stewart); K. Stevens (Kristen); J. Simard (Jacques); T. Pastinen (Tomi); V.S. Pankratz (Shane); K. Offit (Kenneth); D.F. Easton (Douglas); G. Chenevix-Trench (Georgia); A.C. Antoniou (Antonis); H. Thorne (Heather); E. Niedermayr (Eveline); Å. Borg (Åke); H. Olsson; H. Jernström (H.); K. Henriksson (Karin); K. Harbst (Katja); M. Soller (Maria); U. Kristoffersson (Ulf); A. Öfverholm (Anna); M. Nordling (Margareta); P. Karlsson (Per); A. von Wachenfeldt (Anna); A. Liljegren (Annelie); A. Lindblom (Annika); G.B. Bustinza; J. Rantala (Johanna); B. Melin (Beatrice); C.E. Ardnor (Christina Edwinsdotter); M. Emanuelsson (Monica); H. Ehrencrona (Hans); M.H. Pigg (Maritta ); S. Liedgren (Sigrun); M.A. Rookus (M.); S. Verhoef (S.); F.E. van Leeuwen (F.); M.K. Schmidt (Marjanka); J.L. de Lange (J.); J.M. Collée (Margriet); A.M.W. van den Ouweland (Ans); M.J. Hooning (Maartje); C.J. van Asperen (Christi); J.T. Wijnen (Juul); R.A.E.M. Tollenaar (Rob); P. Devilee (Peter); T.C.T.E.F. van Cronenburg; C.M. Kets; A.R. Mensenkamp (Arjen); R.B. van der Luijt (Rob); C.M. Aalfs (Cora); T.A.M. van Os (Theo); Q. Waisfisz (Quinten); E.J. Meijers-Heijboer (Hanne); E.B. Gomez Garcia (Encarna); J.C. Oosterwijk (Jan); M.J. Mourits (Marjan); G.H. de Bock (Geertruida); S.D. Ellis (Steve); E. Fineberg (Elena); Z. Miedzybrodzka (Zosia); L. Jeffers (Lisa); T.J. Cole (Trevor); K.-R. Ong (Kai-Ren); J. Hoffman (Jonathan); M. James (Margaret); J. Paterson (Joan); A. Taylor (Amy); A. Murray (Anna); M.J. Kennedy (John); D.E. Barton (David); M.E. Porteous (Mary); S. Drummond (Sarah); C. Brewer (Carole); E. Kivuva (Emma); A. Searle (Anne); S. Goodman (Selina); R. Davidson (Rosemarie); V. Murday (Victoria); N. Bradshaw (Nicola); L. Snadden (Lesley); M. Longmuir (Mark); C. Watt (Catherine); S. Gibson (Sarah); E. Haque (Eshika); E. Tobias (Ed); A. Duncan (Alexis); L. Izatt (Louise); C. Jacobs (Chris); C. Langman (Caroline); A.F. Brady (Angela); S.A. Melville (Scott); K. Randhawa (Kashmir); J. Barwell (Julian); G. Serra-Feliu (Gemma); I.O. Ellis (Ian); F. Lalloo (Fiona); J. Taylor (James); A. Male (Alison); C. Berlin (Cheryl); R. Collier (Rebecca); F. Douglas (Fiona); O. Claber (Oonagh); I. Jobson (Irene); L.J. Walker (Lisa); D. McLeod (Diane); D. Halliday (Dorothy); S. Durell (Sarah); B. Stayner (Barbara); S. Shanley (Susan); N. Rahman (Nazneen); R. Houlston (Richard); A. Stormorken (Astrid); E.K. Bancroft (Elizabeth); E. Page (Elizabeth); A. Ardern-Jones (Audrey); K. Kohut (Kelly); J. Wiggins (Jennifer); E. Castro (Elena); S.R. Killick; S. Martin (Sue); D. Rea (Dan); A. Kulkarni (Anjana); O. Quarrell (Oliver); C. Bardsley (Cathryn); S. Goff (Sheila); G. Brice (Glen); L. Winchester (Lizzie); C. Eddy (Charlotte); V. Tripathi (Vishakha); V. Attard (Virginia); A. Lehmann (Anna); A. Lucassen (Anneke); G. Crawford (Gabe); D. McBride (Donna); S. Smalley (Sarah); S. Mazoyer (Sylvie); F. Damiola (Francesca); L. Barjhoux (Laure); C. Verny-Pierre (Carole); S. Giraud (Sophie); D. Stoppa-Lyonnet (Dominique); B. Buecher (Bruno); V. Moncoutier (Virginie); M. Belotti (Muriel); C. Tirapo (Carole); A. de Pauw (Antoine); B. Bressac-de Paillerets (Brigitte); O. Caron (Olivier); Y.-J. Bignon (Yves-Jean); N. Uhrhammer (Nancy); V. Bonadona (Valérie); S. Handallou (Sandrine); A. hardouin (Agnès); H. Sobol (Hagay); V. Bourdon (Violaine); T. Noguchi (Tetsuro); A. Remenieras (Audrey); F. Eisinger (François); J.-P. Peyrat; J. Fournier (Joëlle); F. Révillion (Françoise); P. Vennin (Philippe); C. Adenis (Claude); R. Lidereau (Rosette); L. Demange (Liliane); D.W. Muller (Danièle); J.P. Fricker (Jean Pierre); E. Barouk-Simonet (Emmanuelle); F. Bonnet (Françoise); V. Bubien (Virginie); N. Sevenet (Nicolas); M. Longy (Michel); C. Toulas (Christine); R. Guimbaud (Rosine); L. Gladieff (Laurence); V. Feillel (Viviane); H. Dreyfus (Hélène); C. Rebischung (Christine); M. Peysselon (Magalie); F. Coron (Fanny); L. Faivre (Laurence); M. Lebrun (Marine); C. Kientz (Caroline); S.F. Ferrer; M. Frenay (Marc); I. Mortemousque (Isabelle); F. Coulet (Florence); C. Colas (Chrystelle); F. Soubrier; J. Sokolowska (Johanna); M. Bronner (Myriam); H. Lynch (Henry); C.L. Snyder (Carrie); M. Angelakos (Maggie); J. Maskiell (Judi); G.S. Dite (Gillian)

2013-01-01

textabstractBRCA1-associated breast and ovarian cancer risks can be modified by common genetic variants. To identify further cancer risk-modifying loci, we performed a multi-stage GWAS of 11,705 BRCA1 carriers (of whom 5,920 were diagnosed with breast and 1,839 were diagnosed with ovarian cancer),
Integrated analysis of epigenomic and genomic changes by DNA methylation dependent mechanisms provides potential novel biomarkers for prostate cancer.

Science.gov (United States)

White-Al Habeeb, Nicole M A; Ho, Linh T; Olkhov-Mitsel, Ekaterina; Kron, Ken; Pethe, Vaijayanti; Lehman, Melanie; Jovanovic, Lidija; Fleshner, Neil; van der Kwast, Theodorus; Nelson, Colleen C; Bapat, Bharati

2014-09-15

Epigenetic silencing mediated by CpG methylation is a common feature of many cancers. Characterizing aberrant DNA methylation changes associated with tumor progression may identify potential prognostic markers for prostate cancer (PCa). We treated two PCa cell lines, 22Rv1 and DU-145 with the demethylating agent 5-Aza 2'-deoxycitidine (DAC) and global methylation status was analyzed by performing methylation-sensitive restriction enzyme based differential methylation hybridization strategy followed by genome-wide CpG methylation array profiling. In addition, we examined gene expression changes using a custom microarray. Gene Set Enrichment Analysis (GSEA) identified the most significantly dysregulated pathways. In addition, we assessed methylation status of candidate genes that showed reduced CpG methylation and increased gene expression after DAC treatment, in Gleason score (GS) 8 vs. GS6 patients using three independent cohorts of patients; the publically available The Cancer Genome Atlas (TCGA) dataset, and two separate patient cohorts. Our analysis, by integrating methylation and gene expression in PCa cell lines, combined with patient tumor data, identified novel potential biomarkers for PCa patients. These markers may help elucidate the pathogenesis of PCa and represent potential prognostic markers for PCa patients.
An integrative multi-dimensional genetic and epigenetic strategy to identify aberrant genes and pathways in cancer

Directory of Open Access Journals (Sweden)

Lockwood William W

2010-05-01

Full Text Available Abstract Background Genomics has substantially changed our approach to cancer research. Gene expression profiling, for example, has been utilized to delineate subtypes of cancer, and facilitated derivation of predictive and prognostic signatures. The emergence of technologies for the high resolution and genome-wide description of genetic and epigenetic features has enabled the identification of a multitude of causal DNA events in tumors. This has afforded the potential for large scale integration of genome and transcriptome data generated from a variety of technology platforms to acquire a better understanding of cancer. Results Here we show how multi-dimensional genomics data analysis would enable the deciphering of mechanisms that disrupt regulatory/signaling cascades and downstream effects. Since not all gene expression changes observed in a tumor are causal to cancer development, we demonstrate an approach based on multiple concerted disruption (MCD analysis of genes that facilitates the rational deduction of aberrant genes and pathways, which otherwise would be overlooked in single genomic dimension investigations. Conclusions Notably, this is the first comprehensive study of breast cancer cells by parallel integrative genome wide analyses of DNA copy number, LOH, and DNA methylation status to interpret changes in gene expression pattern. Our findings demonstrate the power of a multi-dimensional approach to elucidate events which would escape conventional single dimensional analysis and as such, reduce the cohort sample size for cancer gene discovery.
Identification of genomic copy number variations associated with specific clinical features of head and neck cancer.

Science.gov (United States)

Zagradišnik, Boris; Krgović, Danijela; Herodež, Špela Stangler; Zagorac, Andreja; Ćižmarević, Bogdan; Vokač, Nadja Kokalj

2018-01-01

Copy number variations (CNSs) of large genomic regions are an important mechanism implicated in the development of head and neck cancer, however, for most changes their exact role is not well understood. The aim of this study was to find possible associations between gains/losses of genomic regions and clinically distinct subgroups of head and neck cancer patients. Array comparative genomic hybridization (aCGH) analysis was performed on DNA samples in 64 patients with cancer in oral cavity, oropharynx or hypopharynx. Overlapping genomic regions created from gains and losses were used for statistical analysis. Following regions were overrepresented: in tumors with stage I or II a gain of 2.98 Mb on 6p21.2-p11 and a gain of 7.4 Mb on 8q11.1-q11.23; in tumors with grade I histology a gain of 1.1 Mb on 8q24.13, a loss of a large part of p arm of chromosome 3, a loss of a 1.24 Mb on 6q14.3, and a loss of terminal 32 Mb region of 8p23.3; in cases with affected lymph nodes a gain of 0.75 Mb on 3q24, and a gain of 0.9 Mb on 3q26.32-q26.33; in cases with unaffected lymph nodes a gain of 1.1 Mb on 8q23.3, in patients not treated with surgery a gain of 12.2 Mb on 7q21.3-q22.3 and a gain of 0.33 Mb on 20q11.22. Our study identified several genomic regions of interest which appear to be associated with various clinically distinct subgroups of head and neck cancer. They represent a potentially important source of biomarkers useful for the clinical management of head and neck cancer. In particular, the PIK3CA and AGTR1 genes could be singled out to predict the lymph node involvement.
Integrative Genomic Analysis of Coincident Cancer Foci Implicates CTNNB1 and PTEN Alterations in Ductal Prostate Cancer.

Science.gov (United States)

Gillard, Marc; Lack, Justin; Pontier, Andrea; Gandla, Divya; Hatcher, David; Sowalsky, Adam G; Rodriguez-Nieves, Jose; Vander Griend, Donald; Paner, Gladell; VanderWeele, David

2017-12-08

Ductal adenocarcinoma of the prostate is an aggressive subtype, with high rates of biochemical recurrence and overall poor prognosis. It is frequently found coincident with conventional acinar adenocarcinoma. The genomic features driving evolution to its ductal histology and the biology associated with its poor prognosis remain unknown. To characterize genomic features distinguishing ductal adenocarcinoma from coincident acinar adenocarcinoma foci from the same patient. Ten patients with coincident acinar and ductal prostate cancer underwent prostatectomy. Laser microdissection was used to separately isolate acinar and ductal foci. DNA and RNA were extracted, and used for integrative genomic and transcriptomic analyses. Single nucleotide mutations, small indels, copy number estimates, and expression profiles were identified. Phylogenetic relationships between coincident foci were determined, and characteristics distinguishing ductal from acinar foci were identified. Exome sequencing, copy number estimates, and fusion genes demonstrated coincident ductal and acinar adenocarcinoma diverged from a common progenitor, yet they harbored distinct alterations unique to each focus. AR expression and activity were similar in both histologies. Nine of 10 cases had mutually exclusive CTNNB1 hotspot mutations or phosphatase and tensin homolog (PTEN) alterations in the ductal component, and these were absent in the acinar foci. These alterations were associated with changes in expression in WNT- and PI3K-pathway genes. Coincident ductal and acinar histologies typically are clonally related and thus arise from the same cell of origin. Ductal foci are enriched for cases with either a CTNNB1 hotspot mutation or a PTEN alteration, and are associated with WNT- or PI3K-pathway activation. These alterations are mutually exclusive and may represent distinct subtypes. The aggressive subtype ductal adenocarcinoma is closely related to conventional acinar prostate cancer. Ductal foci
The Genome-Wide Analysis of Carcinoembryonic Antigen Signaling by Colorectal Cancer Cells Using RNA Sequencing.

Directory of Open Access Journals (Sweden)

Olga Bajenova

Full Text Available Сarcinoembryonic antigen (CEA, CEACAM5, CD66 is a promoter of metastasis in epithelial cancers that is widely used as a prognostic clinical marker of metastasis. The aim of this study is to identify the network of genes that are associated with CEA-induced colorectal cancer liver metastasis. We compared the genome-wide transcriptomic profiles of CEA positive (MIP101 clone 8 and CEA negative (MIP 101 colorectal cancer cell lines with different metastatic potential in vivo. The CEA-producing cells displayed quantitative changes in the level of expression for 100 genes (over-expressed or down-regulated. They were confirmed by quantitative RT-PCR. The KEGG pathway analysis identified 4 significantly enriched pathways: cytokine-cytokine receptor interaction, MAPK signaling pathway, TGF-beta signaling pathway and pyrimidine metabolism. Our results suggest that CEA production by colorectal cancer cells triggers colorectal cancer progression by inducing the epithelial- mesenchymal transition, increasing tumor cell invasiveness into the surrounding tissues and suppressing stress and apoptotic signaling. The novel gene expression distinctions establish the relationships between the existing cancer markers and implicate new potential biomarkers for colorectal cancer hepatic metastasis.
Genome-wide association study in BRCA1 mutation carriers identifies novel loci associated with breast and ovarian cancer risk

NARCIS (Netherlands)

Couch, Fergus J.; Wang, Xianshu; McGuffog, Lesley; Lee, Andrew; Olswold, Curtis; Kuchenbaecker, Karoline B.; Soucy, Penny; Fredericksen, Zachary; Barrowdale, Daniel; Dennis, Joe; Gaudet, Mia M.; Dicks, Ed; Kosel, Matthew; Healey, Sue; Sinilnikova, Olga M.; Lee, Adam; Bacot, François; Vincent, Daniel; Hogervorst, Frans B. L.; Peock, Susan; Stoppa-Lyonnet, Dominique; Jakubowska, Anna; Radice, Paolo; Schmutzler, Rita Katharina; Domchek, Susan M.; Piedmonte, Marion; Singer, Christian F.; Friedman, Eitan; Thomassen, Mads; Hansen, Thomas V. O.; Neuhausen, Susan L.; Szabo, Csilla I.; Blanco, Ignacio; Greene, Mark H.; Karlan, Beth Y.; Garber, Judy; Phelan, Catherine M.; Weitzel, Jeffrey N.; Montagna, Marco; Olah, Edith; Andrulis, Irene L.; Godwin, Andrew K.; Yannoukakos, Drakoulis; Goldgar, David E.; Caldes, Trinidad; Nevanlinna, Heli; Osorio, Ana; Terry, Mary Beth; Daly, Mary B.; van Rensburg, Elizabeth J.; Hamann, Ute; Ramus, Susan J.; Toland, Amanda Ewart; Caligo, Maria A.; Olopade, Olufunmilayo I.; Tung, Nadine; Claes, Kathleen; Beattie, Mary S.; Southey, Melissa C.; Imyanitov, Evgeny N.; Tischkowitz, Marc; Janavicius, Ramunas; John, Esther M.; Kwong, Ava; Diez, Orland; Balmaña, Judith; Barkardottir, Rosa B.; Arun, Banu K.; Rennert, Gad; teo, Soo-Hwang; Ganz, Patricia A.; Campbell, Ian; van der Hout, Annemarie H.; van Deurzen, Carolien H. M.; Seynaeve, Caroline; Gómez Garcia, Encarna B.; van Leeuwen, Flora E.; Meijers-Heijboer, Hanne E. J.; Gille, Johannes J. P.; Ausems, Margreet G. E. M.; Blok, Marinus J.; Ligtenberg, Marjolijn J. L.; Rookus, Matti A.; Devilee, Peter; Verhoef, Senno; van Os, Theo A. M.; Wijnen, Juul T.; Frost, Debra; Ellis, Steve; Fineberg, Elena; Platte, Radka; Evans, D. Gareth; Izatt, Louise; Eeles, Rosalind A.; Adlard, Julian; Eccles, Diana M.; Cook, Jackie; Brewer, Carole; Douglas, Fiona; Hodgson, Shirley; Morrison, Patrick J.; Side, Lucy E.; Donaldson, Alan; Houghton, Catherine; Rogers, Mark T.; Dorkins, Huw; Eason, Jacqueline; Gregory, Helen; McCann, Emma; Murray, Alex; Calender, Alain; Hardouin, Agnès; Berthet, Pascaline; Delnatte, Capucine; Nogues, Catherine; Lasset, Christine; Houdayer, Claude; Leroux, Dominique; Rouleau, Etienne; Prieur, Fabienne; Damiola, Francesca; Sobol, Hagay; Coupier, Isabelle; Venat-Bouvet, Laurence; Castera, Laurent; Gauthier-Villars, Marion; Léoné, Mélanie; Pujol, Pascal; Mazoyer, Sylvie; Bignon, Yves-Jean; Złowocka-Perłowska, Elżbieta; Gronwald, Jacek; Lubinski, Jan; Durda, Katarzyna; Jaworska, Katarzyna; Huzarski, Tomasz; Spurdle, Amanda B.; Viel, Alessandra; Peissel, Bernard; Bonanni, Bernardo; Melloni, Giulia; Ottini, Laura; Papi, Laura; Varesco, Liliana; Tibiletti, Maria Grazia; Peterlongo, Paolo; Volorio, Sara; Manoukian, Siranoush; Pensotti, Valeria; Arnold, Norbert; Engel, Christoph; Deissler, Helmut; Gadzicki, Dorothea; Gehrig, Andrea; Kast, Karin; Rhiem, Kerstin; Meindl, Alfons; Niederacher, Dieter; Ditsch, Nina; Plendl, Hansjoerg; Preisler-Adams, Sabine; Engert, Stefanie; Sutter, Christian; Varon-Mateeva, Raymonda; Wappenschmidt, Barbara; Weber, Bernhard H. F.; Arver, Brita; Stenmark-Askmalm, Marie; Loman, Niklas; Rosenquist, Richard; Einbeigi, Zakaria; Nathanson, Katherine L.; Rebbeck, Timothy R.; Blank, Stephanie V.; Cohn, David E.; Rodriguez, Gustavo C.; Small, Laurie; Friedlander, Michael; Bae-Jump, Victoria L.; Fink-Retter, Anneliese; Rappaport, Christine; Gschwantler-Kaulich, Daphne; Pfeiler, Georg; tea, Muy-Kheng; Lindor, Noralane M.; Kaufman, Bella; Shimon Paluch, Shani; Laitman, Yael; Skytte, Anne-Bine; Gerdes, Anne-Marie; Pedersen, Inge Sokilde; Moeller, Sanne Traasdahl; Kruse, Torben A.; Jensen, Uffe Birk; Vijai, Joseph; Sarrel, Kara; Robson, Mark; Kauff, Noah; Mulligan, Anna Marie; Glendon, Gord; Ozcelik, Hilmi; Ejlertsen, Bent; Nielsen, Finn C.; Jønson, Lars; Andersen, Mette K.; Ding, Yuan Chun; Steele, Linda; Foretova, Lenka; Teulé, Alex; Lazaro, Conxi; Brunet, Joan; Pujana, Miquel Angel; Mai, Phuong L.; Loud, Jennifer T.; Walsh, Christine; Lester, Jenny; Orsulic, Sandra; Narod, Steven A.; Herzog, Josef; Sand, Sharon R.; Tognazzo, Silvia; Agata, Simona; Vaszko, Tibor; Weaver, Joellen; Stavropoulou, Alexandra V.; Buys, Saundra S.; Romero, Atocha; de la Hoya, Miguel; Aittomäki, Kristiina; Muranen, Taru A.; Duran, Mercedes; Chung, Wendy K.; Lasa, Adriana; Dorfling, Cecilia M.; Miron, Alexander; Benitez, Javier; Senter, Leigha; Huo, Dezheng; Chan, Salina B.; Sokolenko, Anna P.; Chiquette, Jocelyne; Tihomirova, Laima; Friebel, Tara M.; Agnarsson, Bjarni A.; Lu, Karen H.; Lejbkowicz, Flavio; James, Paul A.; Hall, Per; Dunning, Alison M.; Tessier, Daniel; Cunningham, Julie; Slager, Susan L.; Wang, Chen; Hart, Steven; Stevens, Kristen; Simard, Jacques; Pastinen, Tomi; Pankratz, Vernon S.; Offit, Kenneth; Easton, Douglas F.; Chenevix-Trench, Georgia; Antoniou, Antonis C.

2013-01-01

BRCA1-associated breast and ovarian cancer risks can be modified by common genetic variants. To identify further cancer risk-modifying loci, we performed a multi-stage GWAS of 11,705 BRCA1 carriers (of whom 5,920 were diagnosed with breast and 1,839 were diagnosed with ovarian cancer), with a
Genome-wide association study in BRCA1 mutation carriers identifies novel loci associated with breast and ovarian cancer risk

DEFF Research Database (Denmark)

Couch, Fergus J; Wang, Xianshu; McGuffog, Lesley

2013-01-01

BRCA1-associated breast and ovarian cancer risks can be modified by common genetic variants. To identify further cancer risk-modifying loci, we performed a multi-stage GWAS of 11,705 BRCA1 carriers (of whom 5,920 were diagnosed with breast and 1,839 were diagnosed with ovarian cancer), with a fur...
Integrative Genomic Analysis of Cholangiocarcinoma Identifies Distinct IDH-Mutant Molecular Profiles

Directory of Open Access Journals (Sweden)

Farshad Farshidfar

2017-03-01

Full Text Available Cholangiocarcinoma (CCA is an aggressive malignancy of the bile ducts, with poor prognosis and limited treatment options. Here, we describe the integrated analysis of somatic mutations, RNA expression, copy number, and DNA methylation by The Cancer Genome Atlas of a set of predominantly intrahepatic CCA cases and propose a molecular classification scheme. We identified an IDH mutant-enriched subtype with distinct molecular features including low expression of chromatin modifiers, elevated expression of mitochondrial genes, and increased mitochondrial DNA copy number. Leveraging the multi-platform data, we observed that ARID1A exhibited DNA hypermethylation and decreased expression in the IDH mutant subtype. More broadly, we found that IDH mutations are associated with an expanded histological spectrum of liver tumors with molecular features that stratify with CCA. Our studies reveal insights into the molecular pathogenesis and heterogeneity of cholangiocarcinoma and provide classification information of potential therapeutic significance.
Structural variation discovery in the cancer genome using next generation sequencing: Computational solutions and perspectives

Science.gov (United States)

Liu, Biao; Conroy, Jeffrey M.; Morrison, Carl D.; Odunsi, Adekunle O.; Qin, Maochun; Wei, Lei; Trump, Donald L.; Johnson, Candace S.; Liu, Song; Wang, Jianmin

2015-01-01

Somatic Structural Variations (SVs) are a complex collection of chromosomal mutations that could directly contribute to carcinogenesis. Next Generation Sequencing (NGS) technology has emerged as the primary means of interrogating the SVs of the cancer genome in recent investigations. Sophisticated computational methods are required to accurately identify the SV events and delineate their breakpoints from the massive amounts of reads generated by a NGS experiment. In this review, we provide an overview of current analytic tools used for SV detection in NGS-based cancer studies. We summarize the features of common SV groups and the primary types of NGS signatures that can be used in SV detection methods. We discuss the principles and key similarities and differences of existing computational programs and comment on unresolved issues related to this research field. The aim of this article is to provide a practical guide of relevant concepts, computational methods, software tools and important factors for analyzing and interpreting NGS data for the detection of SVs in the cancer genome. PMID:25849937
Association between genomic recurrence risk and well-being among breast cancer patients

International Nuclear Information System (INIS)

Retèl, Valesca P; Groothuis-Oudshoorn, Catharina GM; Aaronson, Neil K; Brewer, Noel T; Rutgers, Emiel JT; Harten, Wim H van

2013-01-01

Gene expression profiling (GEP) is increasingly used in the rapidly evolving field of personalized medicine. We sought to evaluate the association between GEP-assessed of breast cancer recurrence risk and patients’ well-being. Participants were Dutch women from 10 hospitals being treated for early stage breast cancer who were enrolled in the MINDACT trial (Microarray In Node-negative and 1 to 3 positive lymph node Disease may Avoid ChemoTherapy). As part of the trial, they received a disease recurrence risk estimate based on a 70-gene signature and on standard clinical criteria as scored via a modified version of Adjuvant! Online. /Women completed a questionnaire 6–8 weeks after surgery and after their decision regarding adjuvant chemotherapy. The questionnaire assessed perceived understanding, knowledge, risk perception, satisfaction, distress, cancer worry and health-related quality of life (HRQoL), 6–8 weeks after surgery and decision regarding adjuvant chemotherapy. Women (n = 347, response rate 62%) reported high satisfaction with and a good understanding of the GEP information they received. Women with low risk estimates from both the standard and genomic tests reported the lowest distress levels. Distress was higher predominately among patients who had received high genomic risk estimates, who did not receive genomic risk estimates, or who received conflicting estimates based on genomic and clinical criteria. Cancer worry was highest for patients with higher risk perceptions and lower satisfaction. Patients with concordant high-risk profiles and those for whom such profiles were not available reported lower quality of life. Patients were generally satisfied with the information they received about recurrence risk based on genomic testing. Some types of genomic test results were associated with greater distress levels, but not with cancer worry or HRQoL. ISRCTN: http://www.controlled-trials.com/ISRCTN18543567/MINDACT
Health psychology and translational genomic research: bringing innovation to cancer-related behavioral interventions.

Science.gov (United States)

McBride, Colleen M; Birmingham, Wendy C; Kinney, Anita Y

2015-01-01

The past decade has witnessed rapid advances in human genome sequencing technology and in the understanding of the role of genetic and epigenetic alterations in cancer development. These advances have raised hopes that such knowledge could lead to improvements in behavioral risk reduction interventions, tailored screening recommendations, and treatment matching that together could accelerate the war on cancer. Despite this optimism, translation of genomic discovery for clinical and public health applications has moved relatively slowly. To date, health psychologists and the behavioral sciences generally have played a very limited role in translation research. In this report we discuss what we mean by genomic translational research and consider the social forces that have slowed translational research, including normative assumptions that translation research must occur downstream of basic science, thus relegating health psychology and other behavioral sciences to a distal role. We then outline two broad priority areas in cancer prevention, detection, and treatment where evidence will be needed to guide evaluation and implementation of personalized genomics: (a) effective communication, to broaden dissemination of genomic discovery, including patient-provider communication and familial communication, and (b) the need to improve the motivational impact of behavior change interventions, including those aimed at altering lifestyle choices and those focusing on decision making regarding targeted cancer treatments and chemopreventive adherence. We further discuss the role that health psychologists can play in interdisciplinary teams to shape translational research priorities and to evaluate the utility of emerging genomic discoveries for cancer prevention and control. PsycINFO Database Record (c) 2015 APA, all rights reserved.
NGS-based approach to determine the presence of HPV and their sites of integration in human cancer genome.

Science.gov (United States)

Chandrani, P; Kulkarni, V; Iyer, P; Upadhyay, P; Chaubal, R; Das, P; Mulherkar, R; Singh, R; Dutt, A

2015-06-09

Human papilloma virus (HPV) accounts for the most common cause of all virus-associated human cancers. Here, we describe the first graphic user interface (GUI)-based automated tool 'HPVDetector', for non-computational biologists, exclusively for detection and annotation of the HPV genome based on next-generation sequencing data sets. We developed a custom-made reference genome that comprises of human chromosomes along with annotated genome of 143 HPV types as pseudochromosomes. The tool runs on a dual mode as defined by the user: a 'quick mode' to identify presence of HPV types and an 'integration mode' to determine genomic location for the site of integration. The input data can be a paired-end whole-exome, whole-genome or whole-transcriptome data set. The HPVDetector is available in public domain for download: http://www.actrec.gov.in/pi-webpages/AmitDutt/HPVdetector/HPVDetector.html. On the basis of our evaluation of 116 whole-exome, 23 whole-transcriptome and 2 whole-genome data, we were able to identify presence of HPV in 20 exomes and 4 transcriptomes of cervical and head and neck cancer tumour samples. Using the inbuilt annotation module of HPVDetector, we found predominant integration of viral gene E7, a known oncogene, at known 17q21, 3q27, 7q35, Xq28 and novel sites of integration in the human genome. Furthermore, co-infection with high-risk HPVs such as 16 and 31 were found to be mutually exclusive compared with low-risk HPV71. HPVDetector is a simple yet precise and robust tool for detecting HPV from tumour samples using variety of next-generation sequencing platforms including whole genome, whole exome and transcriptome. Two different modes (quick detection and integration mode) along with a GUI widen the usability of HPVDetector for biologists and clinicians with minimal computational knowledge.
ATXN1L, CIC, and ETS Transcription Factors Modulate Sensitivity to MAPK Pathway Inhibition | Office of Cancer Genomics

Science.gov (United States)

Intrinsic resistance and RTK-RAS-MAPK pathway reactivation has limited the effectiveness of MEK and RAF inhibitors (MAPKi) in RAS- and RAF-mutant cancers. To identify genes that modulate sensitivity to MAPKi, we performed genome-scale CRISPR-Cas9 loss-of-function screens in two KRAS mutant pancreatic cancer cell lines treated with the MEK1/2 inhibitor trametinib. Loss of CIC, a transcriptional repressor of ETV1, ETV4, and ETV5, promoted survival in the setting of MAPKi in cancer cells derived from several lineages.
Genome-wide association study in BRCA1 mutation carriers identifies novel loci associated with breast and ovarian cancer risk.

Directory of Open Access Journals (Sweden)

Fergus J Couch

Full Text Available BRCA1-associated breast and ovarian cancer risks can be modified by common genetic variants. To identify further cancer risk-modifying loci, we performed a multi-stage GWAS of 11,705 BRCA1 carriers (of whom 5,920 were diagnosed with breast and 1,839 were diagnosed with ovarian cancer, with a further replication in an additional sample of 2,646 BRCA1 carriers. We identified a novel breast cancer risk modifier locus at 1q32 for BRCA1 carriers (rs2290854, P = 2.7 × 10(-8, HR = 1.14, 95% CI: 1.09-1.20. In addition, we identified two novel ovarian cancer risk modifier loci: 17q21.31 (rs17631303, P = 1.4 × 10(-8, HR = 1.27, 95% CI: 1.17-1.38 and 4q32.3 (rs4691139, P = 3.4 × 10(-8, HR = 1.20, 95% CI: 1.17-1.38. The 4q32.3 locus was not associated with ovarian cancer risk in the general population or BRCA2 carriers, suggesting a BRCA1-specific association. The 17q21.31 locus was also associated with ovarian cancer risk in 8,211 BRCA2 carriers (P = 2×10(-4. These loci may lead to an improved understanding of the etiology of breast and ovarian tumors in BRCA1 carriers. Based on the joint distribution of the known BRCA1 breast cancer risk-modifying loci, we estimated that the breast cancer lifetime risks for the 5% of BRCA1 carriers at lowest risk are 28%-50% compared to 81%-100% for the 5% at highest risk. Similarly, based on the known ovarian cancer risk-modifying loci, the 5% of BRCA1 carriers at lowest risk have an estimated lifetime risk of developing ovarian cancer of 28% or lower, whereas the 5% at highest risk will have a risk of 63% or higher. Such differences in risk may have important implications for risk prediction and clinical management for BRCA1 carriers.
Personal Genomic Testing for Cancer Risk: Results From the Impact of Personal Genomics Study.

Science.gov (United States)

Gray, Stacy W; Gollust, Sarah E; Carere, Deanna Alexis; Chen, Clara A; Cronin, Angel; Kalia, Sarah S; Rana, Huma Q; Ruffin, Mack T; Wang, Catharine; Roberts, J Scott; Green, Robert C

2017-02-20

Purpose Significant concerns exist regarding the potential for unwarranted behavior changes and the overuse of health care resources in response to direct-to-consumer personal genomic testing (PGT). However, little is known about customers' behaviors after PGT. Methods Longitudinal surveys were given to new customers of 23andMe (Mountain View, CA) and Pathway Genomics (San Diego, CA). Survey data were linked to individual-level PGT results through a secure data transfer process. Results Of the 1,042 customers who completed baseline and 6-month surveys (response rate, 71.2%), 762 had complete cancer-related data and were analyzed. Most customers reported that learning about their genetic risk of cancers was a motivation for testing (colorectal, 88%; prostate, 95%; breast, 94%). No customers tested positive for pathogenic mutations in highly penetrant cancer susceptibility genes. A minority of individuals received elevated single nucleotide polymorphism-based PGT cancer risk estimates (colorectal, 24%; prostate, 24%; breast, 12%). At 6 months, customers who received elevated PGT cancer risk estimates were not significantly more likely to change their diet, exercise, or advanced planning behaviors or engage in cancer screening, compared with individuals at average or reduced risk. Men who received elevated PGT prostate cancer risk estimates changed their vitamin and supplement use more than those at average or reduced risk (22% v 7.6%, respectively; adjusted odds ratio, 3.41; 95% CI, 1.44 to 8.18). Predictors of 6-month behavior include baseline behavior (exercise, vitamin or supplement use, and screening), worse health status (diet and vitamin or supplement use), and older age (advanced planning, screening). Conclusion Most adults receiving elevated direct-to-consumer PGT single nucleotide polymorphism-based cancer risk estimates did not significantly change their diet, exercise, advanced care planning, or cancer screening behaviors.
Cancer Genome Interpreter annotates the biological and clinical relevance of tumor alterations.

Science.gov (United States)

Tamborero, David; Rubio-Perez, Carlota; Deu-Pons, Jordi; Schroeder, Michael P; Vivancos, Ana; Rovira, Ana; Tusquets, Ignasi; Albanell, Joan; Rodon, Jordi; Tabernero, Josep; de Torres, Carmen; Dienstmann, Rodrigo; Gonzalez-Perez, Abel; Lopez-Bigas, Nuria

2018-03-28

While tumor genome sequencing has become widely available in clinical and research settings, the interpretation of tumor somatic variants remains an important bottleneck. Here we present the Cancer Genome Interpreter, a versatile platform that automates the interpretation of newly sequenced cancer genomes, annotating the potential of alterations detected in tumors to act as drivers and their possible effect on treatment response. The results are organized in different levels of evidence according to current knowledge, which we envision can support a broad range of oncology use cases. The resource is publicly available at http://www.cancergenomeinterpreter.org .
Altered mitochondrial genome content signals worse pathology and prognosis in prostate cancer.

Science.gov (United States)

Kalsbeek, Anton M F; Chan, Eva K F; Grogan, Judith; Petersen, Desiree C; Jaratlerdsiri, Weerachai; Gupta, Ruta; Lyons, Ruth J; Haynes, Anne-Maree; Horvath, Lisa G; Kench, James G; Stricker, Phillip D; Hayes, Vanessa M

2018-01-01

Mitochondrial genome (mtDNA) content is depleted in many cancers. In prostate cancer, there is intra-glandular as well as inter-patient mtDNA copy number variation. In this study, we determine if mtDNA content can be used as a predictor for prostate cancer staging and outcomes. Fresh prostate cancer biopsies from 115 patients were obtained at time of surgery. All cores underwent pathological review, followed by isolation of cancer and normal tissue. DNA was extracted and qPCR performed to quantify the total amount of mtDNA as a ratio to genomic DNA. Differences in mtDNA content were compared for prostate cancer pathology features and disease outcomes. We showed a significantly reduced mtDNA content in prostate cancer compared with normal adjacent prostate tissue (mean difference 1.73-fold, P-value Prostate cancer with increased mtDNA content showed unfavorable pathologic characteristics including, higher disease stage (PT2 vs PT3 P-value = 0.018), extracapsular extension (P-value = 0.02) and a trend toward an increased Gleason score (P-value = 0.064). No significant association was observed between changes in mtDNA content and biochemical recurrence (median follow up of 107 months). Contrary to other cancer types, prostate cancer tissue shows no universally depleted mtDNA content. Rather, the change in mtDNA content is highly variable, mirroring known prostate cancer genome heterogeneity. Patients with high mtDNA content have an unfavorable pathology, while a high mtDNA content in normal adjacent prostate tissue is associated with worse prognosis. © 2017 Wiley Periodicals, Inc.
Enhancing knowledge discovery from cancer genomics data with Galaxy.

Science.gov (United States)

Albuquerque, Marco A; Grande, Bruno M; Ritch, Elie J; Pararajalingam, Prasath; Jessa, Selin; Krzywinski, Martin; Grewal, Jasleen K; Shah, Sohrab P; Boutros, Paul C; Morin, Ryan D

2017-05-01

The field of cancer genomics has demonstrated the power of massively parallel sequencing techniques to inform on the genes and specific alterations that drive tumor onset and progression. Although large comprehensive sequence data sets continue to be made increasingly available, data analysis remains an ongoing challenge, particularly for laboratories lacking dedicated resources and bioinformatics expertise. To address this, we have produced a collection of Galaxy tools that represent many popular algorithms for detecting somatic genetic alterations from cancer genome and exome data. We developed new methods for parallelization of these tools within Galaxy to accelerate runtime and have demonstrated their usability and summarized their runtimes on multiple cloud service providers. Some tools represent extensions or refinement of existing toolkits to yield visualizations suited to cohort-wide cancer genomic analysis. For example, we present Oncocircos and Oncoprintplus, which generate data-rich summaries of exome-derived somatic mutation. Workflows that integrate these to achieve data integration and visualizations are demonstrated on a cohort of 96 diffuse large B-cell lymphomas and enabled the discovery of multiple candidate lymphoma-related genes. Our toolkit is available from our GitHub repository as Galaxy tool and dependency definitions and has been deployed using virtualization on multiple platforms including Docker. © The Author 2017. Published by Oxford University Press.

Integrated genomic and gene expression profiling identifies two major genomic circuits in urothelial carcinoma.

Directory of Open Access Journals (Sweden)

David Lindgren

Full Text Available Similar to other malignancies, urothelial carcinoma (UC is characterized by specific recurrent chromosomal aberrations and gene mutations. However, the interconnection between specific genomic alterations, and how patterns of chromosomal alterations adhere to different molecular subgroups of UC, is less clear. We applied tiling resolution array CGH to 146 cases of UC and identified a number of regions harboring recurrent focal genomic amplifications and deletions. Several potential oncogenes were included in the amplified regions, including known oncogenes like E2F3, CCND1, and CCNE1, as well as new candidate genes, such as SETDB1 (1q21, and BCL2L1 (20q11. We next combined genome profiling with global gene expression, gene mutation, and protein expression data and identified two major genomic circuits operating in urothelial carcinoma. The first circuit was characterized by FGFR3 alterations, overexpression of CCND1, and 9q and CDKN2A deletions. The second circuit was defined by E3F3 amplifications and RB1 deletions, as well as gains of 5p, deletions at PTEN and 2q36, 16q, 20q, and elevated CDKN2A levels. TP53/MDM2 alterations were common for advanced tumors within the two circuits. Our data also suggest a possible RAS/RAF circuit. The tumors with worst prognosis showed a gene expression profile that indicated a keratinized phenotype. Taken together, our integrative approach revealed at least two separate networks of genomic alterations linked to the molecular diversity seen in UC, and that these circuits may reflect distinct pathways of tumor development.
The Genomic and Proteomic Content of Cancer Cell-Derived Exosomes

International Nuclear Information System (INIS)

Henderson, Meredith C.; Azorsa, David O.

2012-01-01

Exosomes are secreted membrane vesicles that have been proposed as an effective means to detect a variety of disease states, including cancer. The properties of exosomes, including stability in biological fluids, allow for their efficient isolation and make them an ideal vehicle for studies on early disease detection and evaluation. Much data has been collected over recent years regarding the messenger RNA, microRNA, and protein contents of exosomes. In addition, many studies have described the functional role that exosomes play in disease initiation and progression. Tumor cells have been shown to secrete exosomes, often in increased amounts compared to normal cells, and these exosomes can carry the genomic and proteomic signatures characteristic of the tumor cells from which they were derived. While these unique signatures make exosomes ideal for cancer detection, exosomes derived from cancer cells have also been shown to play a functional role in cancer progression. Here, we review the unique genomic and proteomic contents of exosomes originating from cancer cells as well as their functional effects to promote tumor progression.
Prognostic Impact of Array-based Genomic Profiles in Esophageal Squamous Cell Cancer

International Nuclear Information System (INIS)

Carneiro, Ana; Isinger, Anna; Karlsson, Anna; Johansson, Jan; Jönsson, Göran; Bendahl, Pär-Ola; Falkenback, Dan; Halvarsson, Britta; Nilbert, Mef

2008-01-01

Esophageal squamous cell carcinoma (ESCC) is a genetically complex tumor type and a major cause of cancer related mortality. Although distinct genetic alterations have been linked to ESCC development and prognosis, the genetic alterations have not gained clinical applicability. We applied array-based comparative genomic hybridization (aCGH) to obtain a whole genome copy number profile relevant for identifying deranged pathways and clinically applicable markers. A 32 k aCGH platform was used for high resolution mapping of copy number changes in 30 stage I-IV ESCC. Potential interdependent alterations and deranged pathways were identified and copy number changes were correlated to stage, differentiation and survival. Copy number alterations affected median 19% of the genome and included recurrent gains of chromosome regions 5p, 7p, 7q, 8q, 10q, 11q, 12p, 14q, 16p, 17p, 19p, 19q, and 20q and losses of 3p, 5q, 8p, 9p and 11q. High-level amplifications were observed in 30 regions and recurrently involved 7p11 (EGFR), 11q13 (MYEOV, CCND1, FGF4, FGF3, PPFIA, FAD, TMEM16A, CTTS and SHANK2) and 11q22 (PDFG). Gain of 7p22.3 predicted nodal metastases and gains of 1p36.32 and 19p13.3 independently predicted poor survival in multivariate analysis. aCGH profiling verified genetic complexity in ESCC and herein identified imbalances of multiple central tumorigenic pathways. Distinct gains correlate with clinicopathological variables and independently predict survival, suggesting clinical applicability of genomic profiling in ESCC
Centrosome Dysfunction Contributes To Chromosome Instability, Chromoanagenesis And Genome Reprograming In Cancer.

Directory of Open Access Journals (Sweden)

German A Pihan

2013-11-01

Full Text Available The unique ability of centrosomes to nucleate and organize microtubules makes them unrivaled conductors of important interphase processes, such as intracellular payload traffic, cell polarity, cell locomotion, and organization of the immunologic synapse. But it is in mitosis that centrosomes loom large, for they orchestrate, with clockmaker’s precision, the assembly and functioning of the mitotic spindle, ensuring the equal partitioning of the replicated genome into daughter cells. Centrosome dysfunction is inextricably linked to aneuploidy and chromosome instability, both hallmarks of cancer cells. Several aspects of centrosome function in normal and cancer cells have been molecularly characterized during the last two decades, greatly enhancing our mechanistic understanding of this tiny organelle. Whether centrosome defects alone can cause cancer, remains unanswered. Until recently, the aggregate of the evidence had suggested that centrosome dysfunction, by deregulating the fidelity of chromosome segregation, promotes and accelerates the characteristic Darwinian evolution of the cancer genome enabled by increased mutational load and/or decreased DNA repair. Very recent experimental work has shown that missegreated chromosomes resulting from centrosome dysfunction may experience extensive DNA damage, suggesting additional dimensions to the role of centrosomes in cancer. Centrosome dysfunction is particularly prevalent in tumors in which the genome has undergone extensive structural rearrangements and chromosome domain reshuffling. Ongoing gene reshuffling reprograms the genome for continuous growth, survival, and evasion of the immune system. Manipulation of molecular networks controlling centrosome function may soon become a viable target for specific therapeutic intervention in cancer, particularly since normal cells, which lack centrosome alterations, may be spared the toxicity of such therapies.
An integrated clinical and genomic information system for cancer precision medicine.

Science.gov (United States)

Jang, Yeongjun; Choi, Taekjin; Kim, Jongho; Park, Jisub; Seo, Jihae; Kim, Sangok; Kwon, Yeajee; Lee, Seungjae; Lee, Sanghyuk

2018-04-20

Increasing affordability of next-generation sequencing (NGS) has created an opportunity for realizing genomically-informed personalized cancer therapy as a path to precision oncology. However, the complex nature of genomic information presents a huge challenge for clinicians in interpreting the patient's genomic alterations and selecting the optimum approved or investigational therapy. An elaborate and practical information system is urgently needed to support clinical decision as well as to test clinical hypotheses quickly. Here, we present an integrated clinical and genomic information system (CGIS) based on NGS data analyses. Major components include modules for handling clinical data, NGS data processing, variant annotation and prioritization, drug-target-pathway analysis, and population cohort explorer. We built a comprehensive knowledgebase of genes, variants, drugs by collecting annotated information from public and in-house resources. Structured reports for molecular pathology are generated using standardized terminology in order to help clinicians interpret genomic variants and utilize them for targeted cancer therapy. We also implemented many features useful for testing hypotheses to develop prognostic markers from mutation and gene expression data. Our CGIS software is an attempt to provide useful information for both clinicians and scientists who want to explore genomic information for precision oncology.
Integrative genomic approaches to dissect clinically-significant relationships between the VDR cistrome and gene expression in primary colon cancer.

Science.gov (United States)

Long, Mark D; Campbell, Moray J

2017-10-01

Recently, we undertook a pan-cancer analyses of the nuclear hormone receptor (NR) superfamily in The Cancer Genome Atlas (TCGA), and revealed that the vitamin D receptor (NR1I1/VDR) was commonly and significantly down-regulated specifically in colon adenocarcinoma cohort (COAD). To examine the consequence of down-regulated VDR expression we re-analyzed VDR chromatin immunoprecipitation sequencing (ChIP-Seq) data from LS180 colon cancer cells (GSE31939). This analysis identified 1809 loci that displayed significant (p.adjcolon tumor suppressor, Galactin 4) had significantly shorted disease free survival. These analyses suggest that reduced expression of VDR in colon cancer (but neither loss nor mutation) changes the actions of the VDR by both dampening the expression of tumor suppressors (e.g. LGALS4) whilst either stabilizing or not down-regulating expression of oncogenes (e.g. Carbonic Anhydrase 9 (CA9)). These integrative genomic approaches are relatively generic and applicable to the study of any transcription factor. Copyright © 2016. Published by Elsevier Ltd.
Genome-Wide Association Study in BRCA1 Mutation Carriers Identifies Novel Loci Associated with Breast and Ovarian Cancer Risk

Science.gov (United States)

Wang, Xianshu; McGuffog, Lesley; Lee, Andrew; Olswold, Curtis; Kuchenbaecker, Karoline B.; Soucy, Penny; Fredericksen, Zachary; Barrowdale, Daniel; Dennis, Joe; Gaudet, Mia M.; Dicks, Ed; Kosel, Matthew; Healey, Sue; Sinilnikova, Olga M.; Lee, Adam; Bacot, François; Vincent, Daniel; Hogervorst, Frans B. L.; Peock, Susan; Stoppa-Lyonnet, Dominique; Jakubowska, Anna; Investigators, kConFab; Radice, Paolo; Schmutzler, Rita Katharina; Domchek, Susan M.; Piedmonte, Marion; Singer, Christian F.; Friedman, Eitan; Thomassen, Mads; Hansen, Thomas V. O.; Neuhausen, Susan L.; Szabo, Csilla I.; Blanco, Ignacio; Greene, Mark H.; Karlan, Beth Y.; Garber, Judy; Phelan, Catherine M.; Weitzel, Jeffrey N.; Montagna, Marco; Olah, Edith; Andrulis, Irene L.; Godwin, Andrew K.; Yannoukakos, Drakoulis; Goldgar, David E.; Caldes, Trinidad; Nevanlinna, Heli; Osorio, Ana; Terry, Mary Beth; Daly, Mary B.; van Rensburg, Elizabeth J.; Hamann, Ute; Ramus, Susan J.; Ewart Toland, Amanda; Caligo, Maria A.; Olopade, Olufunmilayo I.; Tung, Nadine; Claes, Kathleen; Beattie, Mary S.; Southey, Melissa C.; Imyanitov, Evgeny N.; Tischkowitz, Marc; Janavicius, Ramunas; John, Esther M.; Kwong, Ava; Diez, Orland; Balmaña, Judith; Barkardottir, Rosa B.; Arun, Banu K.; Rennert, Gad; Teo, Soo-Hwang; Ganz, Patricia A.; Campbell, Ian; van der Hout, Annemarie H.; van Deurzen, Carolien H. M.; Seynaeve, Caroline; Gómez Garcia, Encarna B.; van Leeuwen, Flora E.; Meijers-Heijboer, Hanne E. J.; Gille, Johannes J. P.; Ausems, Margreet G. E. M.; Blok, Marinus J.; Ligtenberg, Marjolijn J. L.; Rookus, Matti A.; Devilee, Peter; Verhoef, Senno; van Os, Theo A. M.; Wijnen, Juul T.; Frost, Debra; Ellis, Steve; Fineberg, Elena; Platte, Radka; Evans, D. Gareth; Izatt, Louise; Eeles, Rosalind A.; Adlard, Julian; Eccles, Diana M.; Cook, Jackie; Brewer, Carole; Douglas, Fiona; Hodgson, Shirley; Morrison, Patrick J.; Side, Lucy E.; Donaldson, Alan; Houghton, Catherine; Rogers, Mark T.; Dorkins, Huw; Eason, Jacqueline; Gregory, Helen; McCann, Emma; Murray, Alex; Calender, Alain; Hardouin, Agnès; Berthet, Pascaline; Delnatte, Capucine; Nogues, Catherine; Lasset, Christine; Houdayer, Claude; Leroux, Dominique; Rouleau, Etienne; Prieur, Fabienne; Damiola, Francesca; Sobol, Hagay; Coupier, Isabelle; Venat-Bouvet, Laurence; Castera, Laurent; Gauthier-Villars, Marion; Léoné, Mélanie; Pujol, Pascal; Mazoyer, Sylvie; Bignon, Yves-Jean; Złowocka-Perłowska, Elżbieta; Gronwald, Jacek; Lubinski, Jan; Durda, Katarzyna; Jaworska, Katarzyna; Huzarski, Tomasz; Spurdle, Amanda B.; Viel, Alessandra; Peissel, Bernard; Bonanni, Bernardo; Melloni, Giulia; Ottini, Laura; Papi, Laura; Varesco, Liliana; Tibiletti, Maria Grazia; Peterlongo, Paolo; Volorio, Sara; Manoukian, Siranoush; Pensotti, Valeria; Arnold, Norbert; Engel, Christoph; Deissler, Helmut; Gadzicki, Dorothea; Gehrig, Andrea; Kast, Karin; Rhiem, Kerstin; Meindl, Alfons; Niederacher, Dieter; Ditsch, Nina; Plendl, Hansjoerg; Preisler-Adams, Sabine; Engert, Stefanie; Sutter, Christian; Varon-Mateeva, Raymonda; Wappenschmidt, Barbara; Weber, Bernhard H. F.; Arver, Brita; Stenmark-Askmalm, Marie; Loman, Niklas; Rosenquist, Richard; Einbeigi, Zakaria; Nathanson, Katherine L.; Rebbeck, Timothy R.; Blank, Stephanie V.; Cohn, David E.; Rodriguez, Gustavo C.; Small, Laurie; Friedlander, Michael; Bae-Jump, Victoria L.; Fink-Retter, Anneliese; Rappaport, Christine; Gschwantler-Kaulich, Daphne; Pfeiler, Georg; Tea, Muy-Kheng; Lindor, Noralane M.; Kaufman, Bella; Shimon Paluch, Shani; Laitman, Yael; Skytte, Anne-Bine; Gerdes, Anne-Marie; Pedersen, Inge Sokilde; Moeller, Sanne Traasdahl; Kruse, Torben A.; Jensen, Uffe Birk; Vijai, Joseph; Sarrel, Kara; Robson, Mark; Kauff, Noah; Mulligan, Anna Marie; Glendon, Gord; Ozcelik, Hilmi; Ejlertsen, Bent; Nielsen, Finn C.; Jønson, Lars; Andersen, Mette K.; Ding, Yuan Chun; Steele, Linda; Foretova, Lenka; Teulé, Alex; Lazaro, Conxi; Brunet, Joan; Pujana, Miquel Angel; Mai, Phuong L.; Loud, Jennifer T.; Walsh, Christine; Lester, Jenny; Orsulic, Sandra; Narod, Steven A.; Herzog, Josef; Sand, Sharon R.; Tognazzo, Silvia; Agata, Simona; Vaszko, Tibor; Weaver, Joellen; Stavropoulou, Alexandra V.; Buys, Saundra S.; Romero, Atocha; de la Hoya, Miguel; Aittomäki, Kristiina; Muranen, Taru A.; Duran, Mercedes; Chung, Wendy K.; Lasa, Adriana; Dorfling, Cecilia M.; Miron, Alexander; Benitez, Javier; Senter, Leigha; Huo, Dezheng; Chan, Salina B.; Sokolenko, Anna P.; Chiquette, Jocelyne; Tihomirova, Laima; Friebel, Tara M.; Agnarsson, Bjarni A.; Lu, Karen H.; Lejbkowicz, Flavio; James, Paul A.; Hall, Per; Dunning, Alison M.; Tessier, Daniel; Cunningham, Julie; Slager, Susan L.; Wang, Chen; Hart, Steven; Stevens, Kristen; Simard, Jacques; Pastinen, Tomi; Pankratz, Vernon S.; Offit, Kenneth; Antoniou, Antonis C.

2013-01-01

BRCA1-associated breast and ovarian cancer risks can be modified by common genetic variants. To identify further cancer risk-modifying loci, we performed a multi-stage GWAS of 11,705 BRCA1 carriers (of whom 5,920 were diagnosed with breast and 1,839 were diagnosed with ovarian cancer), with a further replication in an additional sample of 2,646 BRCA1 carriers. We identified a novel breast cancer risk modifier locus at 1q32 for BRCA1 carriers (rs2290854, P = 2.7×10−8, HR = 1.14, 95% CI: 1.09–1.20). In addition, we identified two novel ovarian cancer risk modifier loci: 17q21.31 (rs17631303, P = 1.4×10−8, HR = 1.27, 95% CI: 1.17–1.38) and 4q32.3 (rs4691139, P = 3.4×10−8, HR = 1.20, 95% CI: 1.17–1.38). The 4q32.3 locus was not associated with ovarian cancer risk in the general population or BRCA2 carriers, suggesting a BRCA1-specific association. The 17q21.31 locus was also associated with ovarian cancer risk in 8,211 BRCA2 carriers (P = 2×10−4). These loci may lead to an improved understanding of the etiology of breast and ovarian tumors in BRCA1 carriers. Based on the joint distribution of the known BRCA1 breast cancer risk-modifying loci, we estimated that the breast cancer lifetime risks for the 5% of BRCA1 carriers at lowest risk are 28%–50% compared to 81%–100% for the 5% at highest risk. Similarly, based on the known ovarian cancer risk-modifying loci, the 5% of BRCA1 carriers at lowest risk have an estimated lifetime risk of developing ovarian cancer of 28% or lower, whereas the 5% at highest risk will have a risk of 63% or higher. Such differences in risk may have important implications for risk prediction and clinical management for BRCA1 carriers. PMID:23544013
Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

NARCIS (Netherlands)

Schaub, Franz X.; Dhankani, Varsha; Berger, Ashton C.; Trivedi, Mihir; Richardson, Anne B.; Shaw, Reid; Zhao, Wei; Zhang, Xiaoyang; Ventura, Andrea; Liu, Yuexin; Ayer, Donald E.; Hurlin, Peter J.; Cherniack, Andrew D.; Eisenman, Robert N.; Bernard, Brady; Grandori, Carla; Caesar-Johnson, Samantha J.; Demchok, John A.; Felau, Ina; Kasapi, Melpomeni; Ferguson, Martin L.; Hutter, Carolyn M.; Sofia, Heidi J.; Tarnuzzer, Roy; Wang, Zhining; Yang, Liming; Zenklusen, Jean C.; Zhang, Jiashan (Julia); Chudamani, Sudha; Liu, Jia; Lolla, Laxmi; Naresh, Rashi; Pihl, Todd; Sun, Qiang; Wan, Yunhu; Wu, Ye; Cho, Juok; DeFreitas, Timothy; Frazer, Scott; Gehlenborg, Nils; Getz, Gad; Heiman, David I.; Kim, Jaegil; Lawrence, Michael S.; Lin, Pei; Meier, Sam; Noble, Michael S.; Saksena, Gordon; Voet, Doug; Zhang, Hailei; Bernard, Brady; Chambwe, Nyasha; Dhankani, Varsha; Knijnenburg, Theo; Kramer, Roger; Leinonen, Kalle; Liu, Yuexin; Miller, Michael; Reynolds, Sheila; Shmulevich, Ilya; Thorsson, Vesteinn; Zhang, Wei; Akbani, Rehan; Broom, Bradley M.; Hegde, Apurva M.; Ju, Zhenlin; Kanchi, Rupa S.; Korkut, Anil; Li, Jun; Liang, Han; Ling, Shiyun; Liu, Wenbin; Lu, Yiling; Mills, Gordon B.; Ng, Kwok Shing; Rao, Arvind; Ryan, Michael; Wang, Jing; Weinstein, John N.; Zhang, Jiexin; Abeshouse, Adam; Armenia, Joshua; Chakravarty, Debyani; Chatila, Walid K.; de Bruijn, Ino; Gao, Jianjiong; Gross, Benjamin E.; Heins, Zachary J.; Kundra, Ritika; La, Konnor; Ladanyi, Marc; Luna, Augustin; Nissan, Moriah G.; Ochoa, Angelica; Phillips, Sarah M.; Reznik, Ed; Sanchez-Vega, Francisco; Sander, Chris; Schultz, Nikolaus; Sheridan, Robert; Sumer, S. Onur; Sun, Yichao; Taylor, Barry S.; Wang, Jioajiao; Zhang, Hongxin; Anur, Pavana; Peto, Myron; Spellman, Paul; Benz, Christopher; Stuart, Joshua M.; Wong, Christopher K.; Yau, Christina; Hayes, D. Neil; Parker, Joel S.; Wilkerson, Matthew D.; Ally, Adrian; Balasundaram, Miruna; Bowlby, Reanne; Brooks, Denise; Carlsen, Rebecca; Chuah, Eric; Dhalla, Noreen; Holt, Robert; Jones, Steven J.M.; Kasaian, Katayoon; Lee, Darlene; Ma, Yussanne; Marra, Marco A.; Mayo, Michael; Moore, Richard A.; Mungall, Andrew J.; Mungall, Karen; Robertson, A. Gordon; Sadeghi, Sara; Schein, Jacqueline E.; Sipahimalani, Payal; Tam, Angela; Thiessen, Nina; Tse, Kane; Wong, Tina; Berger, Ashton C.; Beroukhim, Rameen; Cherniack, Andrew D.; Cibulskis, Carrie; Gabriel, Stacey B.; Gao, Galen F.; Ha, Gavin; Meyerson, Matthew; Schumacher, Steven E.; Shih, Juliann; Kucherlapati, Melanie H.; Kucherlapati, Raju S.; Baylin, Stephen; Cope, Leslie; Danilova, Ludmila; Bootwalla, Moiz S.; Lai, Phillip H.; Maglinte, Dennis T.; Van Den Berg, David J.; Weisenberger, Daniel J.; Auman, J. Todd; Balu, Saianand; Bodenheimer, Tom; Fan, Cheng; Hoadley, Katherine A.; Hoyle, Alan P.; Jefferys, Stuart R.; Jones, Corbin D.; Meng, Shaowu; Mieczkowski, Piotr A.; Mose, Lisle E.; Perou, Amy H.; Perou, Charles M.; Roach, Jeffrey; Shi, Yan; Simons, Janae V.; Skelly, Tara; Soloway, Matthew G.; Tan, Donghui; Veluvolu, Umadevi; Fan, Huihui; Hinoue, Toshinori; Laird, Peter W.; Shen, Hui; Zhou, Wanding; Bellair, Michelle; Chang, Kyle; Covington, Kyle; Creighton, Chad J.; Dinh, Huyen; Doddapaneni, Harsha Vardhan; Donehower, Lawrence A.; Drummond, Jennifer; Gibbs, Richard A.; Glenn, Robert; Hale, Walker; Han, Yi; Hu, Jianhong; Korchina, Viktoriya; Lee, Sandra; Lewis, Lora; Li, Wei; Liu, Xiuping; Morgan, Margaret; Morton, Donna; Muzny, Donna; Santibanez, Jireh; Sheth, Margi; Shinbrot, Eve; Wang, Linghua; Wang, Min; Wheeler, David A.; Xi, Liu; Zhao, Fengmei; Hess, Julian; Appelbaum, Elizabeth L.; Bailey, Matthew; Cordes, Matthew G.; Ding, Li; Fronick, Catrina C.; Fulton, Lucinda A.; Fulton, Robert S.; Kandoth, Cyriac; Mardis, Elaine R.; McLellan, Michael D.; Miller, Christopher A.; Schmidt, Heather K.; Wilson, Richard K.; Crain, Daniel; Curley, Erin; Gardner, Johanna; Lau, Kevin; Mallery, David; Morris, Scott; Paulauskis, Joseph; Penny, Robert; Shelton, Candace; Shelton, Troy; Sherman, Mark; Thompson, Eric; Yena, Peggy; Bowen, Jay; Gastier-Foster, Julie M.; Gerken, Mark; Leraas, Kristen M.; Lichtenberg, Tara M.; Ramirez, Nilsa C.; Wise, Lisa; Zmuda, Erik; Corcoran, Niall; Costello, Tony; Hovens, Christopher; Carvalho, Andre L.; de Carvalho, Ana C.; Fregnani, José H.; Longatto-Filho, Adhemar; Reis, Rui M.; Scapulatempo-Neto, Cristovam; Silveira, Henrique C.S.; Vidal, Daniel O.; Burnette, Andrew; Eschbacher, Jennifer; Hermes, Beth; Noss, Ardene; Singh, Rosy; Anderson, Matthew L.; Castro, Patricia D.; Ittmann, Michael; Huntsman, David; Kohl, Bernard; Le, Xuan; Thorp, Richard; Andry, Chris; Duffy, Elizabeth R.; Lyadov, Vladimir; Paklina, Oxana; Setdikova, Galiya; Shabunin, Alexey; Tavobilov, Mikhail; McPherson, Christopher; Warnick, Ronald; Berkowitz, Ross; Cramer, Daniel; Feltmate, Colleen; Horowitz, Neil; Kibel, Adam; Muto, Michael; Raut, Chandrajit P.; Malykh, Andrei; Barnholtz-Sloan, Jill S.; Barrett, Wendi; Devine, Karen; Fulop, Jordonna; Ostrom, Quinn T.; Shimmel, Kristen; Wolinsky, Yingli; Sloan, Andrew E.; De Rose, Agostino; Giuliante, Felice; Goodman, Marc; Karlan, Beth Y.; Hagedorn, Curt H.; Eckman, John; Harr, Jodi; Myers, Jerome; Tucker, Kelinda; Zach, Leigh Anne; Deyarmin, Brenda; Hu, Hai; Kvecher, Leonid; Larson, Caroline; Mural, Richard J.; Somiari, Stella; Vicha, Ales; Zelinka, Tomas; Bennett, Joseph; Iacocca, Mary; Rabeno, Brenda; Swanson, Patricia; Latour, Mathieu; Lacombe, Louis; Têtu, Bernard; Bergeron, Alain; McGraw, Mary; Staugaitis, Susan M.; Chabot, John; Hibshoosh, Hanina; Sepulveda, Antonia; Su, Tao; Wang, Timothy; Potapova, Olga; Voronina, Olga; Desjardins, Laurence; Mariani, Odette; Roman-Roman, Sergio; Sastre, Xavier; Stern, Marc Henri; Cheng, Feixiong; Signoretti, Sabina; Berchuck, Andrew; Bigner, Darell; Lipp, Eric; Marks, Jeffrey; McCall, Shannon; McLendon, Roger; Secord, Angeles; Sharp, Alexis; Behera, Madhusmita; Brat, Daniel J.; Chen, Amy; Delman, Keith; Force, Seth; Khuri, Fadlo; Magliocca, Kelly; Maithel, Shishir; Olson, Jeffrey J.; Owonikoko, Taofeek; Pickens, Alan; Ramalingam, Suresh; Shin, Dong M.; Sica, Gabriel; Van Meir, Erwin G.; Zhang, Hongzheng; Eijckenboom, Wil; Gillis, Ad; Korpershoek, Esther; Looijenga, Leendert; Oosterhuis, Wolter; Stoop, Hans; van Kessel, Kim E.; Zwarthoff, Ellen C.; Calatozzolo, Chiara; Cuppini, Lucia; Cuzzubbo, Stefania; DiMeco, Francesco; Finocchiaro, Gaetano; Mattei, Luca; Perin, Alessandro; Pollo, Bianca; Chen, Chu; Houck, John; Lohavanichbutr, Pawadee; Hartmann, Arndt; Stoehr, Christine; Stoehr, Robert; Taubert, Helge; Wach, Sven; Wullich, Bernd; Kycler, Witold; Murawa, Dawid; Wiznerowicz, Maciej; Chung, Ki; Edenfield, W. Jeffrey; Martin, Julie; Baudin, Eric; Bubley, Glenn; Bueno, Raphael; De Rienzo, Assunta; Richards, William G.; Kalkanis, Steven; Mikkelsen, Tom; Noushmehr, Houtan; Scarpace, Lisa; Girard, Nicolas; Aymerich, Marta; Campo, Elias; Giné, Eva; Guillermo, Armando López; Van Bang, Nguyen; Hanh, Phan Thi; Phu, Bui Duc; Tang, Yufang; Colman, Howard; Evason, Kimberley; Dottino, Peter R.; Martignetti, John A.; Gabra, Hani; Juhl, Hartmut; Akeredolu, Teniola; Stepa, Serghei; Hoon, Dave; Ahn, Keunsoo; Kang, Koo Jeong; Beuschlein, Felix; Breggia, Anne; Birrer, Michael; Bell, Debra; Borad, Mitesh; Bryce, Alan H.; Castle, Erik; Chandan, Vishal; Cheville, John; Copland, John A.; Farnell, Michael; Flotte, Thomas; Giama, Nasra; Ho, Thai; Kendrick, Michael; Kocher, Jean Pierre; Kopp, Karla; Moser, Catherine; Nagorney, David; O'Brien, Daniel; O'Neill, Brian Patrick; Patel, Tushar; Petersen, Gloria; Que, Florencia; Rivera, Michael; Roberts, Lewis; Smallridge, Robert; Smyrk, Thomas; Stanton, Melissa; Thompson, R. Houston; Torbenson, Michael; Yang, Ju Dong; Zhang, Lizhi; Brimo, Fadi; Ajani, Jaffer A.; Angulo Gonzalez, Ana Maria; Behrens, Carmen; Bondaruk, Jolanta; Broaddus, Russell; Czerniak, Bogdan; Esmaeli, Bita; Fujimoto, Junya; Gershenwald, Jeffrey; Guo, Charles; Lazar, Alexander J.; Logothetis, Christopher; Meric-Bernstam, Funda; Moran, Cesar; Ramondetta, Lois; Rice, David; Sood, Anil; Tamboli, Pheroze; Thompson, Timothy; Troncoso, Patricia; Tsao, Anne; Wistuba, Ignacio; Carter, Candace; Haydu, Lauren; Hersey, Peter; Jakrot, Valerie; Kakavand, Hojabr; Kefford, Richard; Lee, Kenneth; Long, Georgina; Mann, Graham; Quinn, Michael; Saw, Robyn; Scolyer, Richard; Shannon, Kerwin; Spillane, Andrew; Stretch, Jonathan; Synott, Maria; Thompson, John; Wilmott, James; Al-Ahmadie, Hikmat; Chan, Timothy A.; Ghossein, Ronald; Gopalan, Anuradha; Levine, Douglas A.; Reuter, Victor; Singer, Samuel; Singh, Bhuvanesh; Tien, Nguyen Viet; Broudy, Thomas; Mirsaidi, Cyrus; Nair, Praveen; Drwiega, Paul; Miller, Judy; Smith, Jennifer; Zaren, Howard; Park, Joong Won; Hung, Nguyen Phi; Kebebew, Electron; Linehan, W. Marston; Metwalli, Adam R.; Pacak, Karel; Pinto, Peter A.; Schiffman, Mark; Schmidt, Laura S.; Vocke, Cathy D.; Wentzensen, Nicolas; Worrell, Robert; Yang, Hannah; Moncrieff, Marc; Goparaju, Chandra; Melamed, Jonathan; Pass, Harvey; Botnariuc, Natalia; Caraman, Irina; Cernat, Mircea; Chemencedji, Inga; Clipca, Adrian; Doruc, Serghei; Gorincioi, Ghenadie; Mura, Sergiu; Pirtac, Maria; Stancul, Irina; Tcaciuc, Diana; Albert, Monique; Alexopoulou, Iakovina; Arnaout, Angel; Bartlett, John; Engel, Jay; Gilbert, Sebastien; Parfitt, Jeremy; Sekhon, Harman; Thomas, George; Rassl, Doris M.; Rintoul, Robert C.; Bifulco, Carlo; Tamakawa, Raina; Urba, Walter; Hayward, Nicholas; Timmers, Henri; Antenucci, Anna; Facciolo, Francesco; Grazi, Gianluca; Marino, Mirella; Merola, Roberta; de Krijger, Ronald; Gimenez-Roqueplo, Anne Paule; Piché, Alain; Chevalier, Simone; McKercher, Ginette; Birsoy, Kivanc; Barnett, Gene; Brewer, Cathy; Farver, Carol; Naska, Theresa; Pennell, Nathan A.; Raymond, Daniel; Schilero, Cathy; Smolenski, Kathy; Williams, Felicia; Morrison, Carl; Borgia, Jeffrey A.; Liptay, Michael J.; Pool, Mark; Seder, Christopher W.; Junker, Kerstin; Omberg, Larsson; Dinkin, Mikhail; Manikhas, George; Alvaro, Domenico; Bragazzi, Maria Consiglia; Cardinale, Vincenzo; Carpino, Guido; Gaudio, Eugenio; Chesla, David; Cottingham, Sandra; Dubina, Michael; Moiseenko, Fedor; Dhanasekaran, Renumathy; Becker, Karl Friedrich; Janssen, Klaus Peter; Slotta-Huspenina, Julia; Abdel-Rahman, Mohamed H.; Aziz, Dina; Bell, Sue; Cebulla, Colleen M.; Davis, Amy; Duell, Rebecca; Elder, J. Bradley; Hilty, Joe; Kumar, Bahavna; Lang, James; Lehman, Norman L.; Mandt, Randy; Nguyen, Phuong; Pilarski, Robert; Rai, Karan; Schoenfield, Lynn; Senecal, Kelly; Wakely, Paul; Hansen, Paul; Lechan, Ronald; Powers, James; Tischler, Arthur; Grizzle, William E.; Sexton, Katherine C.; Kastl, Alison; Henderson, Joel; Porten, Sima; Waldmann, Jens; Fassnacht, Martin; Asa, Sylvia L.; Schadendorf, Dirk; Couce, Marta; Graefen, Markus; Huland, Hartwig; Sauter, Guido; Schlomm, Thorsten; Simon, Ronald; Tennstedt, Pierre; Olabode, Oluwole; Nelson, Mark; Bathe, Oliver; Carroll, Peter R.; Chan, June M.; Disaia, Philip; Glenn, Pat; Kelley, Robin K.; Landen, Charles N.; Phillips, Joanna; Prados, Michael; Simko, Jeffry; Smith-McCune, Karen; VandenBerg, Scott; Roggin, Kevin; Fehrenbach, Ashley; Kendler, Ady; Sifri, Suzanne; Steele, Ruth; Jimeno, Antonio; Carey, Francis; Forgie, Ian; Mannelli, Massimo; Carney, Michael; Hernandez, Brenda; Campos, Benito; Herold-Mende, Christel; Jungk, Christin; Unterberg, Andreas; von Deimling, Andreas; Bossler, Aaron; Galbraith, Joseph; Jacobus, Laura; Knudson, Michael; Knutson, Tina; Ma, Deqin; Milhem, Mohammed; Sigmund, Rita; Godwin, Andrew K.; Madan, Rashna; Rosenthal, Howard G.; Adebamowo, Clement; Adebamowo, Sally N.; Boussioutas, Alex; Beer, David; Giordano, Thomas; Mes-Masson, Anne Marie; Saad, Fred; Bocklage, Therese; Landrum, Lisa; Mannel, Robert; Moore, Kathleen; Moxley, Katherine; Postier, Russel; Walker, Joan; Zuna, Rosemary; Feldman, Michael; Valdivieso, Federico; Dhir, Rajiv; Luketich, James; Mora Pinero, Edna M.; Quintero-Aguilo, Mario; Carlotti, Carlos Gilberto; Dos Santos, Jose Sebastião; Kemp, Rafael; Sankarankuty, Ajith; Tirapelli, Daniela; Catto, James; Agnew, Kathy; Swisher, Elizabeth; Creaney, Jenette; Robinson, Bruce; Shelley, Carl Simon; Godwin, Eryn M.; Kendall, Sara; Shipman, Cassaundra; Bradford, Carol; Carey, Thomas; Haddad, Andrea; Moyer, Jeffey; Peterson, Lisa; Prince, Mark; Rozek, Laura; Wolf, Gregory; Bowman, Rayleen; Fong, Kwun M.; Yang, Ian; Korst, Robert; Rathmell, W. Kimryn; Fantacone-Campbell, J. Leigh; Hooke, Jeffrey A.; Kovatich, Albert J.; Shriver, Craig D.; DiPersio, John; Drake, Bettina; Govindan, Ramaswamy; Heath, Sharon; Ley, Timothy; Van Tine, Brian; Westervelt, Peter; Rubin, Mark A.; Lee, Jung Il; Aredes, Natália D.; Mariamidze, Armaz

2018-01-01

Although the MYC oncogene has been implicated in cancer, a systematic assessment of alterations of MYC, related transcription factors, and co-regulatory proteins, forming the proximal MYC network (PMN), across human cancers is lacking. Using computational approaches, we define genomic and proteomic
Whole-Genome Sequence of the Metastatic PC3 and LNCaP Human Prostate Cancer Cell Lines

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Inge Seim

2017-06-01

Full Text Available The bone metastasis-derived PC3 and the lymph node metastasis-derived LNCaP prostate cancer cell lines are widely studied, having been described in thousands of publications over the last four decades. Here, we report short-read whole-genome sequencing (WGS and de novo assembly of PC3 (ATCC CRL-1435 and LNCaP (clone FGC; ATCC CRL-1740 at ∼70 × coverage. A known homozygous mutation in TP53 and homozygous loss of PTEN were robustly identified in the PC3 cell line, whereas the LNCaP cell line exhibited a larger number of putative inactivating somatic point and indel mutations (and in particular a loss of stop codon events. This study also provides preliminary evidence that loss of one or both copies of the tumor suppressor Capicua (CIC contributes to primary tumor relapse and metastatic progression, potentially offering a treatment target for castration-resistant prostate cancer (CRPC. Our work provides a resource for genetic, genomic, and biological studies employing two commonly-used prostate cancer cell lines.
Whole-Genome Sequence of the Metastatic PC3 and LNCaP Human Prostate Cancer Cell Lines.

Science.gov (United States)

Seim, Inge; Jeffery, Penny L; Thomas, Patrick B; Nelson, Colleen C; Chopin, Lisa K

2017-06-07

The bone metastasis-derived PC3 and the lymph node metastasis-derived LNCaP prostate cancer cell lines are widely studied, having been described in thousands of publications over the last four decades. Here, we report short-read whole-genome sequencing (WGS) and de novo assembly of PC3 (ATCC CRL-1435) and LNCaP (clone FGC; ATCC CRL-1740) at ∼70 × coverage. A known homozygous mutation in TP53 and homozygous loss of PTEN were robustly identified in the PC3 cell line, whereas the LNCaP cell line exhibited a larger number of putative inactivating somatic point and indel mutations (and in particular a loss of stop codon events). This study also provides preliminary evidence that loss of one or both copies of the tumor suppressor Capicua ( CIC ) contributes to primary tumor relapse and metastatic progression, potentially offering a treatment target for castration-resistant prostate cancer (CRPC). Our work provides a resource for genetic, genomic, and biological studies employing two commonly-used prostate cancer cell lines. Copyright © 2017 Seim et al.
Network Biomarkers of Bladder Cancer Based on a Genome-Wide Genetic and Epigenetic Network Derived from Next-Generation Sequencing Data.

Science.gov (United States)

Li, Cheng-Wei; Chen, Bor-Sen

2016-01-01

Epigenetic and microRNA (miRNA) regulation are associated with carcinogenesis and the development of cancer. By using the available omics data, including those from next-generation sequencing (NGS), genome-wide methylation profiling, candidate integrated genetic and epigenetic network (IGEN) analysis, and drug response genome-wide microarray analysis, we constructed an IGEN system based on three coupling regression models that characterize protein-protein interaction networks (PPINs), gene regulatory networks (GRNs), miRNA regulatory networks (MRNs), and epigenetic regulatory networks (ERNs). By applying system identification method and principal genome-wide network projection (PGNP) to IGEN analysis, we identified the core network biomarkers to investigate bladder carcinogenic mechanisms and design multiple drug combinations for treating bladder cancer with minimal side-effects. The progression of DNA repair and cell proliferation in stage 1 bladder cancer ultimately results not only in the derepression of miR-200a and miR-200b but also in the regulation of the TNF pathway to metastasis-related genes or proteins, cell proliferation, and DNA repair in stage 4 bladder cancer. We designed a multiple drug combination comprising gefitinib, estradiol, yohimbine, and fulvestrant for treating stage 1 bladder cancer with minimal side-effects, and another multiple drug combination comprising gefitinib, estradiol, chlorpromazine, and LY294002 for treating stage 4 bladder cancer with minimal side-effects.
Genetic Alterations in the Molecular Subtypes of Bladder Cancer: Illustration in the Cancer Genome Atlas Dataset.

Science.gov (United States)

Choi, Woonyoung; Ochoa, Andrea; McConkey, David J; Aine, Mattias; Höglund, Mattias; Kim, William Y; Real, Francisco X; Kiltie, Anne E; Milsom, Ian; Dyrskjøt, Lars; Lerner, Seth P

2017-09-01

Recent whole genome mRNA expression profiling studies revealed that bladder cancers can be grouped into molecular subtypes, some of which share clinical properties and gene expression patterns with the intrinsic subtypes of breast cancer and the molecular subtypes found in other solid tumors. The molecular subtypes in other solid tumors are enriched with specific mutations and copy number aberrations that are thought to underlie their distinct progression patterns, and biological and clinical properties. The availability of comprehensive genomic data from The Cancer Genome Atlas (TCGA) and other large projects made it possible to correlate the presence of DNA alterations with tumor molecular subtype membership. Our overall goal was to determine whether specific DNA mutations and/or copy number variations are enriched in specific molecular subtypes. We used the complete TCGA RNA-seq dataset and three different published classifiers developed by our groups to assign TCGA's bladder cancers to molecular subtypes, and examined the prevalence of the most common DNA alterations within them. We interpreted the results against the background of what was known from the published literature about the prevalence of these alterations in nonmuscle-invasive and muscle-invasive bladder cancers. The results confirmed that alterations involving RB1 and NFE2L2 were enriched in basal cancers, whereas alterations involving FGFR3 and KDM6A were enriched in luminal tumors. The results further reinforce the conclusion that the molecular subtypes of bladder cancer are distinct disease entities with specific genetic alterations. Our observation showed that some of subtype-enriched mutations and copy number aberrations are clinically actionable, which has direct implications for the clinical management of patients with bladder cancer. Copyright © 2017 European Association of Urology. Published by Elsevier B.V. All rights reserved.
Identifying structural variants using linked-read sequencing data.

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Elyanow, Rebecca; Wu, Hsin-Ta; Raphael, Benjamin J

2017-11-03

Structural variation, including large deletions, duplications, inversions, translocations, and other rearrangements, is common in human and cancer genomes. A number of methods have been developed to identify structural variants from Illumina short-read sequencing data. However, reliable identification of structural variants remains challenging because many variants have breakpoints in repetitive regions of the genome and thus are difficult to identify with short reads. The recently developed linked-read sequencing technology from 10X Genomics combines a novel barcoding strategy with Illumina sequencing. This technology labels all reads that originate from a small number (~5-10) DNA molecules ~50Kbp in length with the same molecular barcode. These barcoded reads contain long-range sequence information that is advantageous for identification of structural variants. We present Novel Adjacency Identification with Barcoded Reads (NAIBR), an algorithm to identify structural variants in linked-read sequencing data. NAIBR predicts novel adjacencies in a individual genome resulting from structural variants using a probabilistic model that combines multiple signals in barcoded reads. We show that NAIBR outperforms several existing methods for structural variant identification - including two recent methods that also analyze linked-reads - on simulated sequencing data and 10X whole-genome sequencing data from the NA12878 human genome and the HCC1954 breast cancer cell line. Several of the novel somatic structural variants identified in HCC1954 overlap known cancer genes. Software is available at compbio.cs.brown.edu/software. braphael@princeton.edu. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com
Integration and comparison of different genomic data for outcome prediction in cancer

OpenAIRE

Gomez Rueda, Hugo; Martínez Ledesma, Emmanuel; Martínez Torteya, Antonio; Palacios Corona, Rebeca; Treviño, Victor

2005-01-01

Background In cancer, large-scale technologies such as next-generation sequencing and microarrays have produced a wide number of genomic features such as DNA copy number alterations (CNA), mRNA expression (EXPR), microRNA expression (MIRNA), and DNA somatic mutations (MUT), among others. Several analyses of a specific type of these genomic data have generated many prognostic biomarkers in cancer. However, it is uncertain which of these data is more powerful and whether the best data-type is c...
The national cancer institute (NCI) and cancer biology in a 'post genome world'

International Nuclear Information System (INIS)

Klausner, Richard D.

1996-01-01

The National Cancer Institute (NCI) exists to reduce the burden of all cancers through research and discovery. Extensive restructuring of the NCI over the past year has been aimed at assuring that the institution functions in all ways to promote opportunities for discovery in the laboratory, in the clinic, and in the community. To do this well requires the difficult and almost paradoxical problem of planning for scientific discovery which, in turn is based on the freedom to pursue the unanticipated. The intellectual and structural landscape of science is changing and it places new challenges, new demands and new opportunities for facilitating discovery. The nature of cancer as a disease of genomic instability and of accumulated genetic change, coupled with a possibility of the development of new technologies for reading, utilizing, interpreting and manipulating the genome of single cells, provides unprecedented opportunities for a new type of high through-put biology that will change the nature of discovery, cancer detection, diagnosis, prognosis, therapeutic decision-making and therapeutic discovery. To capture these new opportunities will require attention to be paid to integrate the development of technology and new scientific discoveries with the ability to apply advances rapidly and efficiently through clinical trials
Identifying microRNA/mRNA dysregulations in ovarian cancer.

Science.gov (United States)

Miles, Gregory D; Seiler, Michael; Rodriguez, Lorna; Rajagopal, Gunaretnam; Bhanot, Gyan

2012-03-27

MicroRNAs are a class of noncoding RNA molecules that co-regulate the expression of multiple genes via mRNA transcript degradation or translation inhibition. Since they often target entire pathways, they may be better drug targets than genes or proteins. MicroRNAs are known to be dysregulated in many tumours and associated with aggressive or poor prognosis phenotypes. Since they regulate mRNA in a tissue specific manner, their functional mRNA targets are poorly understood. In previous work, we developed a method to identify direct mRNA targets of microRNA using patient matched microRNA/mRNA expression data using an anti-correlation signature. This method, applied to clear cell Renal Cell Carcinoma (ccRCC), revealed many new regulatory pathways compromised in ccRCC. In the present paper, we apply this method to identify dysregulated microRNA/mRNA mechanisms in ovarian cancer using data from The Cancer Genome Atlas (TCGA). TCGA Microarray data was normalized and samples whose class labels (tumour or normal) were ambiguous with respect to consensus ensemble K-Means clustering were removed. Significantly anti-correlated and correlated genes/microRNA differentially expressed between tumour and normal samples were identified. TargetScan was used to identify gene targets of microRNA. We identified novel microRNA/mRNA mechanisms in ovarian cancer. For example, the expression level of RAD51AP1 was found to be strongly anti-correlated with the expression of hsa-miR-140-3p, which was significantly down-regulated in the tumour samples. The anti-correlation signature was present separately in the tumour and normal samples, suggesting a direct causal dysregulation of RAD51AP1 by hsa-miR-140-3p in the ovary. Other pairs of potentially biological relevance include: hsa-miR-145/E2F3, hsa-miR-139-5p/TOP2A, and hsa-miR-133a/GCLC. We also identified sets of positively correlated microRNA/mRNA pairs that are most likely result from indirect regulatory mechanisms. Our findings identify
Genomic Regions Affecting Cheese Making Properties Identified in Danish Holsteins

DEFF Research Database (Denmark)

Gregersen, Vivi Raundahl; Bertelsen, Henriette Pasgaard; Poulsen, Nina Aagaard

The cheese renneting process is affected by a number of factors associated to milk composition and a number of Danish Holsteins has previously been identified to have poor milk coagulation ability. Therefore, the aim of this study was to identify genomic regions affecting the technological...
Association between invasive ovarian cancer susceptibility and 11 best candidate SNPs from breast cancer genome-wide association study

DEFF Research Database (Denmark)

Song, Honglin; Ramus, Susan J; Kjaer, Susanne Krüger

2009-01-01

Because both ovarian and breast cancer are hormone-related and are known to have some predisposition genes in common, we evaluated 11 of the most significant hits (six with confirmed associations with breast cancer) from the breast cancer genome-wide association study for association with invasiv...
Genomic instability and radiation risk in molecular pathways to colon cancer.

Directory of Open Access Journals (Sweden)

Jan Christian Kaiser

Full Text Available Colon cancer is caused by multiple genomic alterations which lead to genomic instability (GI. GI appears in molecular pathways of microsatellite instability (MSI and chromosomal instability (CIN with clinically observed case shares of about 15-20% and 80-85%. Radiation enhances the colon cancer risk by inducing GI, but little is known about different outcomes for MSI and CIN. Computer-based modelling can facilitate the understanding of the phenomena named above. Comprehensive biological models, which combine the two main molecular pathways to colon cancer, are fitted to incidence data of Japanese a-bomb survivors. The preferred model is selected according to statistical criteria and biological plausibility. Imprints of cell-based processes in the succession from adenoma to carcinoma are identified by the model from age dependences and secular trends of the incidence data. Model parameters show remarkable compliance with mutation rates and growth rates for adenoma, which has been reported over the last fifteen years. Model results suggest that CIN begins during fission of intestinal crypts. Chromosomal aberrations are generated at a markedly elevated rate which favors the accelerated growth of premalignant adenoma. Possibly driven by a trend of Westernization in the Japanese diet, incidence rates for the CIN pathway increased notably in subsequent birth cohorts, whereas rates pertaining to MSI remained constant. An imbalance between number of CIN and MSI cases began to emerge in the 1980s, whereas in previous decades the number of cases was almost equal. The CIN pathway exhibits a strong radio-sensitivity, probably more intensive in men. Among young birth cohorts of both sexes the excess absolute radiation risk related to CIN is larger by an order of magnitude compared to the MSI-related risk. Observance of pathway-specific risks improves the determination of the probability of causation for radiation-induced colon cancer in individual patients
Novel immune-modulator identified by a rapid, functional screen of the parapoxvirus ovis (Orf virus genome

Directory of Open Access Journals (Sweden)

McGuire Michael J

2012-01-01

Full Text Available Abstract Background The success of new sequencing technologies and informatic methods for identifying genes has made establishing gene product function a critical rate limiting step in progressing the molecular sciences. We present a method to functionally mine genomes for useful activities in vivo, using an unusual property of a member of the poxvirus family to demonstrate this screening approach. Results The genome of Parapoxvirus ovis (Orf virus was sequenced, annotated, and then used to PCR-amplify its open-reading-frames. Employing a cloning-independent protocol, a viral expression-library was rapidly built and arrayed into sub-library pools. These were directly delivered into mice as expressible cassettes and assayed for an immune-modulating activity associated with parapoxvirus infection. The product of the B2L gene, a homolog of vaccinia F13L, was identified as the factor eliciting immune cell accumulation at sites of skin inoculation. Administration of purified B2 protein also elicited immune cell accumulation activity, and additionally was found to serve as an adjuvant for antigen-specific responses. Co-delivery of the B2L gene with an influenza gene-vaccine significantly improved protection in mice. Furthermore, delivery of the B2L expression construct, without antigen, non-specifically reduced tumor growth in murine models of cancer. Conclusion A streamlined, functional approach to genome-wide screening of a biological activity in vivo is presented. Its application to screening in mice for an immune activity elicited by the pathogen genome of Parapoxvirus ovis yielded a novel immunomodulator. In this inverted discovery method, it was possible to identify the adjuvant responsible for a function of interest prior to a mechanistic study of the adjuvant. The non-specific immune activity of this modulator, B2, is similar to that associated with administration of inactivated particles to a host or to a live viral infection. Administration

Pancreatic cancer genomes reveal aberrations in axon guidance pathway genes.

Science.gov (United States)

Biankin, Andrew V; Waddell, Nicola; Kassahn, Karin S; Gingras, Marie-Claude; Muthuswamy, Lakshmi B; Johns, Amber L; Miller, David K; Wilson, Peter J; Patch, Ann-Marie; Wu, Jianmin; Chang, David K; Cowley, Mark J; Gardiner, Brooke B; Song, Sarah; Harliwong, Ivon; Idrisoglu, Senel; Nourse, Craig; Nourbakhsh, Ehsan; Manning, Suzanne; Wani, Shivangi; Gongora, Milena; Pajic, Marina; Scarlett, Christopher J; Gill, Anthony J; Pinho, Andreia V; Rooman, Ilse; Anderson, Matthew; Holmes, Oliver; Leonard, Conrad; Taylor, Darrin; Wood, Scott; Xu, Qinying; Nones, Katia; Fink, J Lynn; Christ, Angelika; Bruxner, Tim; Cloonan, Nicole; Kolle, Gabriel; Newell, Felicity; Pinese, Mark; Mead, R Scott; Humphris, Jeremy L; Kaplan, Warren; Jones, Marc D; Colvin, Emily K; Nagrial, Adnan M; Humphrey, Emily S; Chou, Angela; Chin, Venessa T; Chantrill, Lorraine A; Mawson, Amanda; Samra, Jaswinder S; Kench, James G; Lovell, Jessica A; Daly, Roger J; Merrett, Neil D; Toon, Christopher; Epari, Krishna; Nguyen, Nam Q; Barbour, Andrew; Zeps, Nikolajs; Kakkar, Nipun; Zhao, Fengmei; Wu, Yuan Qing; Wang, Min; Muzny, Donna M; Fisher, William E; Brunicardi, F Charles; Hodges, Sally E; Reid, Jeffrey G; Drummond, Jennifer; Chang, Kyle; Han, Yi; Lewis, Lora R; Dinh, Huyen; Buhay, Christian J; Beck, Timothy; Timms, Lee; Sam, Michelle; Begley, Kimberly; Brown, Andrew; Pai, Deepa; Panchal, Ami; Buchner, Nicholas; De Borja, Richard; Denroche, Robert E; Yung, Christina K; Serra, Stefano; Onetto, Nicole; Mukhopadhyay, Debabrata; Tsao, Ming-Sound; Shaw, Patricia A; Petersen, Gloria M; Gallinger, Steven; Hruban, Ralph H; Maitra, Anirban; Iacobuzio-Donahue, Christine A; Schulick, Richard D; Wolfgang, Christopher L; Morgan, Richard A; Lawlor, Rita T; Capelli, Paola; Corbo, Vincenzo; Scardoni, Maria; Tortora, Giampaolo; Tempero, Margaret A; Mann, Karen M; Jenkins, Nancy A; Perez-Mancera, Pedro A; Adams, David J; Largaespada, David A; Wessels, Lodewyk F A; Rust, Alistair G; Stein, Lincoln D; Tuveson, David A; Copeland, Neal G; Musgrove, Elizabeth A; Scarpa, Aldo; Eshleman, James R; Hudson, Thomas J; Sutherland, Robert L; Wheeler, David A; Pearson, John V; McPherson, John D; Gibbs, Richard A; Grimmond, Sean M

2012-11-15

Pancreatic cancer is a highly lethal malignancy with few effective therapies. We performed exome sequencing and copy number analysis to define genomic aberrations in a prospectively accrued clinical cohort (n = 142) of early (stage I and II) sporadic pancreatic ductal adenocarcinoma. Detailed analysis of 99 informative tumours identified substantial heterogeneity with 2,016 non-silent mutations and 1,628 copy-number variations. We define 16 significantly mutated genes, reaffirming known mutations (KRAS, TP53, CDKN2A, SMAD4, MLL3, TGFBR2, ARID1A and SF3B1), and uncover novel mutated genes including additional genes involved in chromatin modification (EPC1 and ARID2), DNA damage repair (ATM) and other mechanisms (ZIM2, MAP2K4, NALCN, SLC16A4 and MAGEA6). Integrative analysis with in vitro functional data and animal models provided supportive evidence for potential roles for these genetic aberrations in carcinogenesis. Pathway-based analysis of recurrently mutated genes recapitulated clustering in core signalling pathways in pancreatic ductal adenocarcinoma, and identified new mutated genes in each pathway. We also identified frequent and diverse somatic aberrations in genes described traditionally as embryonic regulators of axon guidance, particularly SLIT/ROBO signalling, which was also evident in murine Sleeping Beauty transposon-mediated somatic mutagenesis models of pancreatic cancer, providing further supportive evidence for the potential involvement of axon guidance genes in pancreatic carcinogenesis.
Exome sequencing identifies rare deleterious mutations in DNA repair genes FANCC and BLM as potential breast cancer susceptibility alleles.

Directory of Open Access Journals (Sweden)

Ella R Thompson

2012-09-01

Full Text Available Despite intensive efforts using linkage and candidate gene approaches, the genetic etiology for the majority of families with a multi-generational breast cancer predisposition is unknown. In this study, we used whole-exome sequencing of thirty-three individuals from 15 breast cancer families to identify potential predisposing genes. Our analysis identified families with heterozygous, deleterious mutations in the DNA repair genes FANCC and BLM, which are responsible for the autosomal recessive disorders Fanconi Anemia and Bloom syndrome. In total, screening of all exons in these genes in 438 breast cancer families identified three with truncating mutations in FANCC and two with truncating mutations in BLM. Additional screening of FANCC mutation hotspot exons identified one pathogenic mutation among an additional 957 breast cancer families. Importantly, none of the deleterious mutations were identified among 464 healthy controls and are not reported in the 1,000 Genomes data. Given the rarity of Fanconi Anemia and Bloom syndrome disorders among Caucasian populations, the finding of multiple deleterious mutations in these critical DNA repair genes among high-risk breast cancer families is intriguing and suggestive of a predisposing role. Our data demonstrate the utility of intra-family exome-sequencing approaches to uncover cancer predisposition genes, but highlight the major challenge of definitively validating candidates where the incidence of sporadic disease is high, germline mutations are not fully penetrant, and individual predisposition genes may only account for a tiny proportion of breast cancer families.
Genomic profiles of lung cancer associated with idiopathic pulmonary fibrosis.

Science.gov (United States)

Hwang, Ji An; Kim, Deokhoon; Chun, Sung-Min; Bae, SooHyun; Song, Joon Seon; Kim, Mi Young; Koo, Hyun Jung; Song, Jin Woo; Kim, Woo Sung; Lee, Jae Cheol; Kim, Hyeong Ryul; Choi, Chang-Min; Jang, Se Jin

2018-01-01

Little is known about the pathogenesis or molecular profiles of idiopathic pulmonary fibrosis-associated lung cancer (IPF-LC). This study was performed to investigate the genomic profiles of IPF-LC and to explore the possibility of defining potential therapeutic targets in IPF-LC. We assessed genomic profiles of IPF-LC by using targeted exome sequencing (OncoPanel version 2) in 35 matched tumour/normal pairs surgically resected between 2004 and 2014. Germline and somatic variant calling was performed with GATK HaplotypeCaller and MuTect with GATK SomaticIndelocator, respectively. Copy number analysis was conducted with CNVkit, with focal events determined by Genomic Identification of Significant Targets in Cancer 2.0, and pathway analysis (KEGG) with DAVID. Germline mutations in TERT (rs2736100, n = 33) and CDKN1A (rs2395655, n = 27) associated with idiopathic pulmonary fibrosis risk were detected in most samples. A total of 410 somatic mutations were identified, with an average of 11.7 per tumour, including 69 synonymous, 177 missense, 17 nonsense, 1 nonstop and 11 splice-site mutations, and 135 small coding indels. Spectra of the somatic mutations revealed predominant C > T transitions despite an extensive smoking history in most patients, suggesting a potential association between APOBEC-related mutagenesis and the development of IPF-LC. TP53 (22/35, 62.9%) and BRAF (6/35, 17.1%) were found to be significantly mutated in IPF-LC. Recurrent focal amplifications in three chromosomal loci (3q26.33, 7q31.2, and 12q14.3) and 9p21.3 deletion were identified, and genes associated with the JAK-STAT signalling pathway were significantly amplified in IPF-LC (P = 0.012). This study demonstrates that IPF-LC is genetically characterized by the presence of somatic mutations reflecting a variety of environmental exposures on the background of specific germline mutations, and is associated with potentially targetable alterations such as BRAF mutations. Copyright © 2017
A genomic and transcriptomic approach for a differential diagnosis between primary and secondary ovarian carcinomas in patients with a previous history of breast cancer

International Nuclear Information System (INIS)

Meyniel, Jean-Philippe; Alran, Séverine; Rapinat, Audrey; Gentien, David; Roman-Roman, Sergio; Mignot, Laurent; Sastre-Garau, Xavier; Cottu, Paul H; Decraene, Charles; Stern, Marc-Henri; Couturier, Jérôme; Lebigot, Ingrid; Nicolas, André; Weber, Nina; Fourchotte, Virginie

2010-01-01

The distinction between primary and secondary ovarian tumors may be challenging for pathologists. The purpose of the present work was to develop genomic and transcriptomic tools to further refine the pathological diagnosis of ovarian tumors after a previous history of breast cancer. Sixteen paired breast-ovary tumors from patients with a former diagnosis of breast cancer were collected. The genomic profiles of paired tumors were analyzed using the Affymetrix GeneChip ® Mapping 50 K Xba Array or Genome-Wide Human SNP Array 6.0 (for one pair), and the data were normalized with ITALICS (ITerative and Alternative normaLIzation and Copy number calling for affymetrix Snp arrays) algorithm or Partek Genomic Suite, respectively. The transcriptome of paired samples was analyzed using Affymetrix GeneChip ® Human Genome U133 Plus 2.0 Arrays, and the data were normalized with gc-Robust Multi-array Average (gcRMA) algorithm. A hierarchical clustering of these samples was performed, combined with a dataset of well-identified primary and secondary ovarian tumors. In 12 of the 16 paired tumors analyzed, the comparison of genomic profiles confirmed the pathological diagnosis of primary ovarian tumor (n = 5) or metastasis of breast cancer (n = 7). Among four cases with uncertain pathological diagnosis, genomic profiles were clearly distinct between the ovarian and breast tumors in two pairs, thus indicating primary ovarian carcinomas, and showed common patterns in the two others, indicating metastases from breast cancer. In all pairs, the result of the transcriptomic analysis was concordant with that of the genomic analysis. In patients with ovarian carcinoma and a previous history of breast cancer, SNP array analysis can be used to distinguish primary and secondary ovarian tumors. Transcriptomic analysis may be used when primary breast tissue specimen is not available
A Somatically Acquired Enhancer of the Androgen Receptor Is a Noncoding Driver in Advanced Prostate Cancer. | Office of Cancer Genomics

Science.gov (United States)

Increased androgen receptor (AR) activity drives therapeutic resistance in advanced prostate cancer. The most common resistance mechanism is amplification of this locus presumably targeting the AR gene. Here, we identify and characterize a somatically acquired AR enhancer located 650 kb centromeric to the AR. Systematic perturbation of this enhancer using genome editing decreased proliferation by suppressing AR levels. Insertion of an additional copy of this region sufficed to increase proliferation under low androgen conditions and to decrease sensitivity to enzalutamide.
Genome-wide association study for ovarian cancer susceptibility using pooled DNA

DEFF Research Database (Denmark)

Lu, Yi; Chen, Xiaoqing; Beesley, Jonathan

2012-01-01

stage 1 GWAS rather than due to problems with the pooling approach. We conclude that there are unlikely to be any moderate or large effects on ovarian cancer risk untagged by less dense arrays. However, our study lacked power to make clear statements on the existence of hitherto untagged small......Recent Genome-Wide Association Studies (GWAS) have identified four low-penetrance ovarian cancer susceptibility loci. We hypothesized that further moderate- or low-penetrance variants exist among the subset of single-nucleotide polymorphisms (SNPs) not well tagged by the genotyping arrays used...... in the previous studies, which would account for some of the remaining risk. We therefore conducted a time- and cost-effective stage 1 GWAS on 342 invasive serous cases and 643 controls genotyped on pooled DNA using the high-density Illumina 1M-Duo array. We followed up 20 of the most significantly associated...
Interactions between household air pollution and GWAS-identified lung cancer susceptibility markers in the Female Lung Cancer Consortium in Asia (FLCCA).

Science.gov (United States)

Hosgood, H Dean; Song, Minsun; Hsiung, Chao Agnes; Yin, Zhihua; Shu, Xiao-Ou; Wang, Zhaoming; Chatterjee, Nilanjan; Zheng, Wei; Caporaso, Neil; Burdette, Laurie; Yeager, Meredith; Berndt, Sonja I; Landi, Maria Teresa; Chen, Chien-Jen; Chang, Gee-Chen; Hsiao, Chin-Fu; Tsai, Ying-Huang; Chien, Li-Hsin; Chen, Kuan-Yu; Huang, Ming-Shyan; Su, Wu-Chou; Chen, Yuh-Min; Chen, Chung-Hsing; Yang, Tsung-Ying; Wang, Chih-Liang; Hung, Jen-Yu; Lin, Chien-Chung; Perng, Reury-Perng; Chen, Chih-Yi; Chen, Kun-Chieh; Li, Yao-Jen; Yu, Chong-Jen; Chen, Yi-Song; Chen, Ying-Hsiang; Tsai, Fang-Yu; Kim, Christopher; Seow, Wei Jie; Bassig, Bryan A; Wu, Wei; Guan, Peng; He, Qincheng; Gao, Yu-Tang; Cai, Qiuyin; Chow, Wong-Ho; Xiang, Yong-Bing; Lin, Dongxin; Wu, Chen; Wu, Yi-Long; Shin, Min-Ho; Hong, Yun-Chul; Matsuo, Keitaro; Chen, Kexin; Wong, Maria Pik; Lu, Dara; Jin, Li; Wang, Jiu-Cun; Seow, Adeline; Wu, Tangchun; Shen, Hongbing; Fraumeni, Joseph F; Yang, Pan-Chyr; Chang, I-Shou; Zhou, Baosen; Chanock, Stephen J; Rothman, Nathaniel; Lan, Qing

2015-03-01

We previously carried out a multi-stage genome-wide association study (GWAS) on lung cancer among never smokers in the Female Lung Cancer Consortium in Asia (FLCCA) (6,609 cases, 7,457 controls) that identified novel susceptibility loci at 10q25.2, 6q22.2, and 6p21.32, and confirmed two previously identified loci at 5p15.33 and 3q28. Household air pollution (HAP) attributed to solid fuel burning for heating and cooking, is the leading cause of the overall disease burden in Southeast Asia, and is known to contain lung carcinogens. To evaluate the gene-HAP interactions associated with lung cancer in loci independent of smoking, we analyzed data from studies participating in FLCCA with fuel use information available (n = 3; 1,731 cases; 1,349 controls). Coal use was associated with a 30% increased risk of lung cancer (OR 1.3, 95% CI 1.0-1.6). Among the five a priori SNPs identified by our GWAS, two showed a significant interaction with coal use (HLA Class II rs2395185, p = 0.02; TP63 rs4488809 (rs4600802), p = 0.04). The risk of lung cancer associated with coal exposure varied with the respective alleles for these two SNPs. Our observations provide evidence that genetic variation in HLA Class II and TP63 may modify the association between HAP and lung cancer risk. The roles played in the cell cycle and inflammation pathways by the proteins encoded by these two genes provide biological plausibility for these interactions; however, additional replication studies are needed in other non-smoking populations.
The Personal Genome Project Canada: findings from whole genome sequences of the inaugural 56 participants.

Science.gov (United States)

Reuter, Miriam S; Walker, Susan; Thiruvahindrapuram, Bhooma; Whitney, Joe; Cohn, Iris; Sondheimer, Neal; Yuen, Ryan K C; Trost, Brett; Paton, Tara A; Pereira, Sergio L; Herbrick, Jo-Anne; Wintle, Richard F; Merico, Daniele; Howe, Jennifer; MacDonald, Jeffrey R; Lu, Chao; Nalpathamkalam, Thomas; Sung, Wilson W L; Wang, Zhuozhi; Patel, Rohan V; Pellecchia, Giovanna; Wei, John; Strug, Lisa J; Bell, Sherilyn; Kellam, Barbara; Mahtani, Melanie M; Bassett, Anne S; Bombard, Yvonne; Weksberg, Rosanna; Shuman, Cheryl; Cohn, Ronald D; Stavropoulos, Dimitri J; Bowdin, Sarah; Hildebrandt, Matthew R; Wei, Wei; Romm, Asli; Pasceri, Peter; Ellis, James; Ray, Peter; Meyn, M Stephen; Monfared, Nasim; Hosseini, S Mohsen; Joseph-George, Ann M; Keeley, Fred W; Cook, Ryan A; Fiume, Marc; Lee, Hin C; Marshall, Christian R; Davies, Jill; Hazell, Allison; Buchanan, Janet A; Szego, Michael J; Scherer, Stephen W

2018-02-05

The Personal Genome Project Canada is a comprehensive public data resource that integrates whole genome sequencing data and health information. We describe genomic variation identified in the initial recruitment cohort of 56 volunteers. Volunteers were screened for eligibility and provided informed consent for open data sharing. Using blood DNA, we performed whole genome sequencing and identified all possible classes of DNA variants. A genetic counsellor explained the implication of the results to each participant. Whole genome sequencing of the first 56 participants identified 207 662 805 sequence variants and 27 494 copy number variations. We analyzed a prioritized disease-associated data set ( n = 1606 variants) according to standardized guidelines, and interpreted 19 variants in 14 participants (25%) as having obvious health implications. Six of these variants (e.g., in BRCA1 or mosaic loss of an X chromosome) were pathogenic or likely pathogenic. Seven were risk factors for cancer, cardiovascular or neurobehavioural conditions. Four other variants - associated with cancer, cardiac or neurodegenerative phenotypes - remained of uncertain significance because of discrepancies among databases. We also identified a large structural chromosome aberration and a likely pathogenic mitochondrial variant. There were 172 recessive disease alleles (e.g., 5 individuals carried mutations for cystic fibrosis). Pharmacogenomics analyses revealed another 3.9 potentially relevant genotypes per individual. Our analyses identified a spectrum of genetic variants with potential health impact in 25% of participants. When also considering recessive alleles and variants with potential pharmacologic relevance, all 56 participants had medically relevant findings. Although access is mostly limited to research, whole genome sequencing can provide specific and novel information with the potential of major impact for health care. © 2018 Joule Inc. or its licensors.
Multi-region and single-cell sequencing reveal variable genomic heterogeneity in rectal cancer.

Science.gov (United States)

Liu, Mingshan; Liu, Yang; Di, Jiabo; Su, Zhe; Yang, Hong; Jiang, Beihai; Wang, Zaozao; Zhuang, Meng; Bai, Fan; Su, Xiangqian

2017-11-23

Colorectal cancer is a heterogeneous group of malignancies with complex molecular subtypes. While colon cancer has been widely investigated, studies on rectal cancer are very limited. Here, we performed multi-region whole-exome sequencing and single-cell whole-genome sequencing to examine the genomic intratumor heterogeneity (ITH) of rectal tumors. We sequenced nine tumor regions and 88 single cells from two rectal cancer patients with tumors of the same molecular classification and characterized their mutation profiles and somatic copy number alterations (SCNAs) at the multi-region and the single-cell levels. A variable extent of genomic heterogeneity was observed between the two patients, and the degree of ITH increased when analyzed on the single-cell level. We found that major SCNAs were early events in cancer development and inherited steadily. Single-cell sequencing revealed mutations and SCNAs which were hidden in bulk sequencing. In summary, we studied the ITH of rectal cancer at regional and single-cell resolution and demonstrated that variable heterogeneity existed in two patients. The mutational scenarios and SCNA profiles of two patients with treatment naïve from the same molecular subtype are quite different. Our results suggest each tumor possesses its own architecture, which may result in different diagnosis, prognosis, and drug responses. Remarkable ITH exists in the two patients we have studied, providing a preliminary impression of ITH in rectal cancer.
dbEM: A database of epigenetic modifiers curated from cancerous and normal genomes

Science.gov (United States)

Singh Nanda, Jagpreet; Kumar, Rahul; Raghava, Gajendra P. S.

2016-01-01

We have developed a database called dbEM (database of Epigenetic Modifiers) to maintain the genomic information of about 167 epigenetic modifiers/proteins, which are considered as potential cancer targets. In dbEM, modifiers are classified on functional basis and comprise of 48 histone methyl transferases, 33 chromatin remodelers and 31 histone demethylases. dbEM maintains the genomic information like mutations, copy number variation and gene expression in thousands of tumor samples, cancer cell lines and healthy samples. This information is obtained from public resources viz. COSMIC, CCLE and 1000-genome project. Gene essentiality data retrieved from COLT database further highlights the importance of various epigenetic proteins for cancer survival. We have also reported the sequence profiles, tertiary structures and post-translational modifications of these epigenetic proteins in cancer. It also contains information of 54 drug molecules against different epigenetic proteins. A wide range of tools have been integrated in dbEM e.g. Search, BLAST, Alignment and Profile based prediction. In our analysis, we found that epigenetic proteins DNMT3A, HDAC2, KDM6A, and TET2 are highly mutated in variety of cancers. We are confident that dbEM will be very useful in cancer research particularly in the field of epigenetic proteins based cancer therapeutics. This database is available for public at URL: http://crdd.osdd.net/raghava/dbem.
Genome-scale analysis of aberrant DNA methylation in colorectal cancer

Science.gov (United States)

Hinoue, Toshinori; Weisenberger, Daniel J.; Lange, Christopher P.E.; Shen, Hui; Byun, Hyang-Min; Van Den Berg, David; Malik, Simeen; Pan, Fei; Noushmehr, Houtan; van Dijk, Cornelis M.; Tollenaar, Rob A.E.M.; Laird, Peter W.

2012-01-01

Colorectal cancer (CRC) is a heterogeneous disease in which unique subtypes are characterized by distinct genetic and epigenetic alterations. Here we performed comprehensive genome-scale DNA methylation profiling of 125 colorectal tumors and 29 adjacent normal tissues. We identified four DNA methylation–based subgroups of CRC using model-based cluster analyses. Each subtype shows characteristic genetic and clinical features, indicating that they represent biologically distinct subgroups. A CIMP-high (CIMP-H) subgroup, which exhibits an exceptionally high frequency of cancer-specific DNA hypermethylation, is strongly associated with MLH1 DNA hypermethylation and the BRAFV600E mutation. A CIMP-low (CIMP-L) subgroup is enriched for KRAS mutations and characterized by DNA hypermethylation of a subset of CIMP-H-associated markers rather than a unique group of CpG islands. Non-CIMP tumors are separated into two distinct clusters. One non-CIMP subgroup is distinguished by a significantly higher frequency of TP53 mutations and frequent occurrence in the distal colon, while the tumors that belong to the fourth group exhibit a low frequency of both cancer-specific DNA hypermethylation and gene mutations and are significantly enriched for rectal tumors. Furthermore, we identified 112 genes that were down-regulated more than twofold in CIMP-H tumors together with promoter DNA hypermethylation. These represent ∼7% of genes that acquired promoter DNA methylation in CIMP-H tumors. Intriguingly, 48/112 genes were also transcriptionally down-regulated in non-CIMP subgroups, but this was not attributable to promoter DNA hypermethylation. Together, we identified four distinct DNA methylation subgroups of CRC and provided novel insight regarding the role of CIMP-specific DNA hypermethylation in gene silencing. PMID:21659424
A national study of breast and colorectal cancer patients' decision-making for novel personalized medicine genomic diagnostics.

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Issa, Amalia M; Tufail, Waqas; Atehortua, Nelson; McKeever, John

2013-05-01

Molecular diagnostics are increasingly being used to help guide decision-making for personalized medical treatment of breast and colorectal cancer patients. The main aim of this study was to better understand and determine breast and colorectal cancer patients' decision-making strategies and the trade-offs they make in deciding about characteristics of molecular genomic diagnostics for breast and colorectal cancer. We surveyed a nationally representative sample of 300 breast and colorectal cancer patients using a previously developed web-administered instrument. Eligibility criteria included patients aged 18 years and older with either breast or colorectal cancer. We explored several attributes and attribute levels of molecular genomic diagnostics in 20 scenarios. Our analysis revealed that both breast and colorectal cancer patients weighted the capability of molecular genomic diagnostics to determine the probability of treatment efficacy as being of greater importance than information provided to detect adverse events. The probability of either false-positive or -negative results was ranked highly as a potential barrier by both breast and colorectal patients. However, 78.6% of breast cancer patients ranked the possibility of a 'false-negative test result leading to undertreatment' higher than the 'chance of a false positive, which may lead to overtreatment' (68%). This finding contrasted with the views of colorectal cancer patients who ranked the chance of a false positive as being of greater concern than a false negative (72.8 vs 63%). Overall, cancer patients exhibited a high willingness to accept and pay for genomic diagnostic tests, especially among breast cancer patients. Cancer patients seek a test accuracy rate of 90% or higher. Breast and colorectal cancer patients' decisions about genomic diagnostics are influenced more by the probability of being cured than by avoiding potential severe adverse events. This study provides insights into the relative weight
The database of chromosome imbalance regions and genes resided in lung cancer from Asian and Caucasian identified by array-comparative genomic hybridization

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Lo Fang-Yi

2012-06-01

Full Text Available Abstract Background Cancer-related genes show racial differences. Therefore, identification and characterization of DNA copy number alteration regions in different racial groups helps to dissect the mechanism of tumorigenesis. Methods Array-comparative genomic hybridization (array-CGH was analyzed for DNA copy number profile in 40 Asian and 20 Caucasian lung cancer patients. Three methods including MetaCore analysis for disease and pathway correlations, concordance analysis between array-CGH database and the expression array database, and literature search for copy number variation genes were performed to select novel lung cancer candidate genes. Four candidate oncogenes were validated for DNA copy number and mRNA and protein expression by quantitative polymerase chain reaction (qPCR, chromogenic in situ hybridization (CISH, reverse transcriptase-qPCR (RT-qPCR, and immunohistochemistry (IHC in more patients. Results We identified 20 chromosomal imbalance regions harboring 459 genes for Caucasian and 17 regions containing 476 genes for Asian lung cancer patients. Seven common chromosomal imbalance regions harboring 117 genes, included gain on 3p13-14, 6p22.1, 9q21.13, 13q14.1, and 17p13.3; and loss on 3p22.2-22.3 and 13q13.3 were found both in Asian and Caucasian patients. Gene validation for four genes including ARHGAP19 (10q24.1 functioning in Rho activity control, FRAT2 (10q24.1 involved in Wnt signaling, PAFAH1B1 (17p13.3 functioning in motility control, and ZNF322A (6p22.1 involved in MAPK signaling was performed using qPCR and RT-qPCR. Mean gene dosage and mRNA expression level of the four candidate genes in tumor tissues were significantly higher than the corresponding normal tissues (PP=0.06. In addition, CISH analysis of patients indicated that copy number amplification indeed occurred for ARHGAP19 and ZNF322A genes in lung cancer patients. IHC analysis of paraffin blocks from Asian Caucasian patients demonstrated that the frequency of
The database of chromosome imbalance regions and genes resided in lung cancer from Asian and Caucasian identified by array-comparative genomic hybridization

International Nuclear Information System (INIS)

Lo, Fang-Yi; Nandi, Suvobroto; Salgia, Ravi; Wang, Yi-Ching; Chang, Jer-Wei; Chang, I-Shou; Chen, Yann-Jang; Hsu, Han-Shui; Huang, Shiu-Feng Kathy; Tsai, Fang-Yu; Jiang, Shih Sheng; Kanteti, Rajani

2012-01-01

Cancer-related genes show racial differences. Therefore, identification and characterization of DNA copy number alteration regions in different racial groups helps to dissect the mechanism of tumorigenesis. Array-comparative genomic hybridization (array-CGH) was analyzed for DNA copy number profile in 40 Asian and 20 Caucasian lung cancer patients. Three methods including MetaCore analysis for disease and pathway correlations, concordance analysis between array-CGH database and the expression array database, and literature search for copy number variation genes were performed to select novel lung cancer candidate genes. Four candidate oncogenes were validated for DNA copy number and mRNA and protein expression by quantitative polymerase chain reaction (qPCR), chromogenic in situ hybridization (CISH), reverse transcriptase-qPCR (RT-qPCR), and immunohistochemistry (IHC) in more patients. We identified 20 chromosomal imbalance regions harboring 459 genes for Caucasian and 17 regions containing 476 genes for Asian lung cancer patients. Seven common chromosomal imbalance regions harboring 117 genes, included gain on 3p13-14, 6p22.1, 9q21.13, 13q14.1, and 17p13.3; and loss on 3p22.2-22.3 and 13q13.3 were found both in Asian and Caucasian patients. Gene validation for four genes including ARHGAP19 (10q24.1) functioning in Rho activity control, FRAT2 (10q24.1) involved in Wnt signaling, PAFAH1B1 (17p13.3) functioning in motility control, and ZNF322A (6p22.1) involved in MAPK signaling was performed using qPCR and RT-qPCR. Mean gene dosage and mRNA expression level of the four candidate genes in tumor tissues were significantly higher than the corresponding normal tissues (P<0.001~P=0.06). In addition, CISH analysis of patients indicated that copy number amplification indeed occurred for ARHGAP19 and ZNF322A genes in lung cancer patients. IHC analysis of paraffin blocks from Asian Caucasian patients demonstrated that the frequency of PAFAH1B1 protein overexpression was 68
Genome chaos: survival strategy during crisis.

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Liu, Guo; Stevens, Joshua B; Horne, Steven D; Abdallah, Batoul Y; Ye, Karen J; Bremer, Steven W; Ye, Christine J; Chen, David J; Heng, Henry H

2014-01-01

Genome chaos, a process of complex, rapid genome re-organization, results in the formation of chaotic genomes, which is followed by the potential to establish stable genomes. It was initially detected through cytogenetic analyses, and recently confirmed by whole-genome sequencing efforts which identified multiple subtypes including "chromothripsis", "chromoplexy", "chromoanasynthesis", and "chromoanagenesis". Although genome chaos occurs commonly in tumors, both the mechanism and detailed aspects of the process are unknown due to the inability of observing its evolution over time in clinical samples. Here, an experimental system to monitor the evolutionary process of genome chaos was developed to elucidate its mechanisms. Genome chaos occurs following exposure to chemotherapeutics with different mechanisms, which act collectively as stressors. Characterization of the karyotype and its dynamic changes prior to, during, and after induction of genome chaos demonstrates that chromosome fragmentation (C-Frag) occurs just prior to chaotic genome formation. Chaotic genomes seem to form by random rejoining of chromosomal fragments, in part through non-homologous end joining (NHEJ). Stress induced genome chaos results in increased karyotypic heterogeneity. Such increased evolutionary potential is demonstrated by the identification of increased transcriptome dynamics associated with high levels of karyotypic variance. In contrast to impacting on a limited number of cancer genes, re-organized genomes lead to new system dynamics essential for cancer evolution. Genome chaos acts as a mechanism of rapid, adaptive, genome-based evolution that plays an essential role in promoting rapid macroevolution of new genome-defined systems during crisis, which may explain some unwanted consequences of cancer treatment.
Cancer genomics

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Norrild, Bodil; Guldberg, Per; Ralfkiær, Elisabeth Methner

2007-01-01

Almost all cells in the human body contain a complete copy of the genome with an estimated number of 25,000 genes. The sequences of these genes make up about three percent of the genome and comprise the inherited set of genetic information. The genome also contains information that determines whe...
Data Mining Approaches for Genomic Biomarker Development: Applications Using Drug Screening Data from the Cancer Genome Project and the Cancer Cell Line Encyclopedia.

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David G Covell

Full Text Available Developing reliable biomarkers of tumor cell drug sensitivity and resistance can guide hypothesis-driven basic science research and influence pre-therapy clinical decisions. A popular strategy for developing biomarkers uses characterizations of human tumor samples against a range of cancer drug responses that correlate with genomic change; developed largely from the efforts of the Cancer Cell Line Encyclopedia (CCLE and Sanger Cancer Genome Project (CGP. The purpose of this study is to provide an independent analysis of this data that aims to vet existing and add novel perspectives to biomarker discoveries and applications. Existing and alternative data mining and statistical methods will be used to a evaluate drug responses of compounds with similar mechanism of action (MOA, b examine measures of gene expression (GE, copy number (CN and mutation status (MUT biomarkers, combined with gene set enrichment analysis (GSEA, for hypothesizing biological processes important for drug response, c conduct global comparisons of GE, CN and MUT as biomarkers across all drugs screened in the CGP dataset, and d assess the positive predictive power of CGP-derived GE biomarkers as predictors of drug response in CCLE tumor cells. The perspectives derived from individual and global examinations of GEs, MUTs and CNs confirm existing and reveal unique and shared roles for these biomarkers in tumor cell drug sensitivity and resistance. Applications of CGP-derived genomic biomarkers to predict the drug response of CCLE tumor cells finds a highly significant ROC, with a positive predictive power of 0.78. The results of this study expand the available data mining and analysis methods for genomic biomarker development and provide additional support for using biomarkers to guide hypothesis-driven basic science research and pre-therapy clinical decisions.
Funding Opportunity: Genomic Data Centers

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Funding Opportunity CCG, Funding Opportunity Center for Cancer Genomics, CCG, Center for Cancer Genomics, CCG RFA, Center for cancer genomics rfa, genomic data analysis network, genomic data analysis network centers,
Whole-genome analysis of a patient with early-stage small-cell lung cancer.

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Han, J-Y; Lee, Y-S; Kim, B C; Lee, G K; Lee, S; Kim, E-H; Kim, H-M; Bhak, J

2014-12-01

We performed whole-genome sequencing (WGS) of a case of early-stage small-cell lung cancer (SCLC) to analyze the genomic features. WGS revealed a lot of single-nucleotide variations (SNVs), small insertion/deletions and chromosomal abnormality. Chromosomes 4p, 5q, 13q, 15q, 17p and 22q contained many block deletions. Especially, copy loss was observed in tumor suppressor genes RB1 and TP53, and copy gain in oncogene hTERT. Somatic mutations were found in TP53 and CREBBP. Novel nonsynonymous (ns) SNVs in C6ORF103 and SLC5A4 genes were also found. Sanger sequencing of the SLC5A4 gene in 23 independent SCLC samples showed another nsSNV in the SLC5A4 gene, indicating that nsSNVs in the SLC5A4 gene are recurrent in SCLC. WGS of an early-stage SCLC identified novel recurrent mutations and validated known variations, including copy number variations. These findings provide insight into the genomic landscape contributing to SCLC development.
Methylation profiling identified novel differentially methylated markers including OPCML and FLRT2 in prostate cancer.

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Wu, Yu; Davison, Jerry; Qu, Xiaoyu; Morrissey, Colm; Storer, Barry; Brown, Lisha; Vessella, Robert; Nelson, Peter; Fang, Min

2016-04-02

To develop new methods to distinguish indolent from aggressive prostate cancers (PCa), we utilized comprehensive high-throughput array-based relative methylation (CHARM) assay to identify differentially methylated regions (DMRs) throughout the genome, including both CpG island (CGI) and non-CGI regions in PCa patients based on Gleason grade. Initially, 26 samples, including 8 each of low [Gleason score (GS) 6] and high (GS ≥7) grade PCa samples and 10 matched normal prostate tissues, were analyzed as a discovery cohort. We identified 3,567 DMRs between normal and cancer tissues, and 913 DMRs distinguishing low from high-grade cancers. Most of these DMRs were located at CGI shores. The top 5 candidate DMRs from the low vs. high Gleason comparison, including OPCML, ELAVL2, EXT1, IRX5, and FLRT2, were validated by pyrosequencing using the discovery cohort. OPCML and FLRT2 were further validated in an independent cohort consisting of 20 low-Gleason and 33 high-Gleason tissues. We then compared patients with biochemical recurrence (n=70) vs. those without (n=86) in a third cohort, and they showed no difference in methylation at these DMR loci. When GS 3+4 cases and GS 4+3 cases were compared, OPCML-DMR methylation showed a trend of lower methylation in the recurrence group (n=30) than in the no-recurrence (n=52) group. We conclude that whole-genome methylation profiling with CHARM revealed distinct patterns of differential DNA methylation between normal prostate and PCa tissues, as well as between different risk groups of PCa as defined by Gleason scores. A panel of selected DMRs may serve as novel surrogate biomarkers for Gleason score in PCa.

Genome-wide association study of prostate cancer-specific survival

DEFF Research Database (Denmark)

Szulkin, Robert; Karlsson, Robert; Whitington, Thomas

2015-01-01

BACKGROUND: Unnecessary intervention and overtreatment of indolent disease are common challenges in clinical management of prostate cancer. Improved tools to distinguish lethal from indolent disease are critical. METHODS: We performed a genome-wide survival analysis of cause-specific death in 24,...
Genetic profiles of gastroesophageal cancer: combined analysis using expression array and tiling array--comparative genomic hybridization

DEFF Research Database (Denmark)

Isinger-Ekstrand, Anna; Johansson, Jan; Ohlsson, Mattias

2010-01-01

We aimed to characterize the genomic profiles of adenocarcinomas in the gastroesophageal junction in relation to cancers in the esophagus and the stomach. Profiles of gains/losses as well as gene expression profiles were obtained from 27 gastroesophageal adenocarcinomas by means of 32k high......15, 13q34, and 12q13, whereas different profiles with gains at 5p15, 7p22, 2q35, and 13q34 characterized gastric cancers. CDK6 and EGFR were identified as putative target genes in cancers of the esophagus and the gastroesophageal junction, with upregulation in one quarter of the tumors. Gains....../losses and gene expression profiles show strong similarity between cancers in the distal esophagus and the gastroesophageal junction with frequent upregulation of CDK6 and EGFR, whereas gastric cancer displays distinct genetic changes. These data suggest that molecular diagnostics and targeted therapies can...
New families of human regulatory RNA structures identified by comparative analysis of vertebrate genomes

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Parker, Brian John; Moltke, Ida; Roth, Adam

2011-01-01

a comparative method, EvoFam, for genome-wide identification of families of regulatory RNA structures, based on primary sequence and secondary structure similarity. We apply EvoFam to a 41-way genomic vertebrate alignment. Genome-wide, we identify 220 human, high-confidence families outside protein...
Whole genomes redefine the mutational landscape of pancreatic cancer

OpenAIRE

Waddell, Nicola; Pajic, Marina; Patch, Ann-Marie; Chang, David K.; Kassahn, Karin S.; Bailey, Peter; Johns, Amber L.; Miller, David; Nones, Katia; Quek, Kelly; Quinn, Michael C. J.; Robertson, Alan J.; Fadlullah, Muhammad Z. H.; Bruxner, Tim J. C.; Christ, Angelika N.

2015-01-01

Pancreatic cancer remains one of the most lethal of malignancies and a major health burden. We performed whole-genome sequencing and copy number variation (CNV) analysis of 100 pancreatic ductal adenocarcinomas (PDACs). Chromosomal rearrangements leading to gene disruption were prevalent, affecting genes known to be important in pancreatic cancer (TP53, SMAD4, CDKN2A, ARID1A and ROBO2) and new candidate drivers of pancreatic carcinogenesis (KDM6A and PREX2). Patterns of structural variation (...
Gender-Associated Genomic Differences in Colorectal Cancer: Clinical Insight from Feminization of Male Cancer Cells

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Rola H. Ali

2014-09-01

Full Text Available Gender-related differences in colorectal cancer (CRC are not fully understood. Recent studies have shown that CRC arising in females are significantly associated with CpG island methylator phenotype (CIMP-high. Using array comparative genomic hybridization, we analyzed a cohort of 116 CRCs (57 males, 59 females for chromosomal copy number aberrations (CNA and found that CRC in females had significantly higher numbers of gains involving chromosome arms 1q21.2–q21.3, 4q13.2, 6p21.1 and 16p11.2 and copy number losses of chromosome arm 11q25 compared to males. Interestingly, a subset of male CRCs (46% exhibited a "feminization" phenomenon in the form of gains of X chromosomes (or an arm of X and/or losses of the Y chromosome. Feminization of cancer cells was significantly associated with microsatellite-stable CRCs (p-value 0.003 and wild-type BRAF gene status (p-value 0.009. No significant association with other clinicopathological parameters was identified including disease-free survival. In summary, our data show that some CNAs in CRC may be gender specific and that male cancers characterized by feminization may constitute a specific subset of CRCs that warrants further investigation.
Matrix-comparative genomic hybridization from multicenter formalin-fixed paraffin-embedded colorectal cancer tissue blocks

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Köhne Claus-Henning

2007-04-01

Full Text Available Abstract Background The identification of genomic signatures of colorectal cancer for risk stratification requires the study of large series of cancer patients with an extensive clinical follow-up. Multicentric clinical studies represent an ideal source of well documented archived material for this type of analyses. Methods To verify if this material is technically suitable to perform matrix-CGH, we performed a pilot study using macrodissected 29 formalin-fixed, paraffin-embedded tissue samples collected within the framework of the EORTC-GI/PETACC-2 trial for colorectal cancer. The scientific aim was to identify prognostic genomic signatures differentiating locally restricted (UICC stages II-III from systemically advanced (UICC stage IV colorectal tumours. Results The majority of archived tissue samples collected in the different centers was suitable to perform matrix-CGH. 5/7 advanced tumours displayed 13q-gain and 18q-loss. In locally restricted tumours, only 6/12 tumours showed a gain on 13q and 7/12 tumours showed a loss on 18q. Interphase-FISH and high-resolution array-mapping of the gain on 13q confirmed the validity of the array-data and narrowed the chromosomal interval containing potential oncogenes. Conclusion Archival, paraffin-embedded tissue samples collected in multicentric clinical trials are suitable for matrix-CGH analyses and allow the identification of prognostic signatures and aberrations harbouring potential new oncogenes.
Telomere Length Dynamics and the Evolution of Cancer Genome Architecture

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Kez Cleal

2018-02-01

Full Text Available Telomeres are progressively eroded during repeated rounds of cell division due to the end replication problem but also undergo additional more substantial stochastic shortening events. In most cases, shortened telomeres induce a cell-cycle arrest or trigger apoptosis, although for those cells that bypass such signals during tumour progression, a critical length threshold is reached at which telomere dysfunction may ensue. Dysfunction of the telomere nucleoprotein complex can expose free chromosome ends to the DNA double-strand break (DSB repair machinery, leading to telomere fusion with both telomeric and non-telomeric loci. The consequences of telomere fusions in promoting genome instability have long been appreciated through the breakage–fusion–bridge (BFB cycle mechanism, although recent studies using high-throughput sequencing technologies have uncovered evidence of involvement in a wider spectrum of genomic rearrangements including chromothripsis. A critical step in cancer progression is the transition of a clone to immortality, through the stabilisation of the telomere repeat array. This can be achieved via the reactivation of telomerase, or the induction of the alternative lengthening of telomeres (ALT pathway. Whilst telomere dysfunction may promote genome instability and tumour progression, by limiting the replicative potential of a cell and enforcing senescence, telomere shortening can act as a tumour suppressor mechanism. However, the burden of senescent cells has also been implicated as a driver of ageing and age-related pathology, and in the promotion of cancer through inflammatory signalling. Considering the critical role of telomere length in governing cancer biology, we review questions related to the prognostic value of studying the dynamics of telomere shortening and fusion, and discuss mechanisms and consequences of telomere-induced genome rearrangements.
Translational and functional oncogenomics. From cancer-oriented genomic screenings to new diagnostic tools and improved cancer treatment.

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Medico, Enzo

2008-01-01

We present here an experimental pipeline for the systematic identification and functional characterization of genes with high potential diagnostic and therapeutic value in human cancer. Complementary competences and resources have been brought together in the TRANSFOG Consortium to reach the following integrated research objectives: 1) execution of cancer-oriented genomic screenings on tumor tissues and experimental models and merging of the results to generate a prioritized panel of candidate genes involved in cancer progression and metastasis; 2) setup of systems for high-throughput delivery of full-length cDNAs, for gain-of-function analysis of the prioritized candidate genes; 3) collection of vectors and oligonucleotides for systematic, RNA interference-mediated down-regulation of the candidate genes; 4) adaptation of existing cell-based and model organism assays to a systematic analysis of gain and loss of function of the candidate genes, for identification and preliminary validation of novel potential therapeutic targets; 5) proteomic analysis of signal transduction and protein-protein interaction for better dissection of aberrant cancer signaling pathways; 6) validation of the diagnostic potential of the identified cancer genes towards the clinical use of diagnostic molecular signatures; 7) generation of a shared informatics platform for data handling and gene functional annotation. The results of the first three years of activity of the TRANSFOG Consortium are also briefly presented and discussed.
General Approach to Identifying Potential Targets for Cancer Imaging by Integrated Bioinformatics Analysis of Publicly Available Genomic Profiles

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Yongliang Yang

2011-03-01

Full Text Available Molecular imaging has moved to the forefront of drug development and biomedical research. The identification of appropriate imaging targets has become the touchstone for the accurate diagnosis and prognosis of human cancer. Particularly, cell surface- or membrane-bound proteins are attractive imaging targets for their aberrant expression, easily accessible location, and unique biochemical functions in tumor cells. Previously, we published a literature mining of potential targets for our in-house enzyme-mediated cancer imaging and therapy technology. Here we present a simple and integrated bioinformatics analysis approach that assembles a public cancer microarray database with a pathway knowledge base for ascertaining and prioritizing upregulated genes encoding cell surface- or membrane-bound proteins, which could serve imaging targets. As examples, we obtained lists of potential hits for six common and lethal human tumors in the prostate, breast, lung, colon, ovary, and pancreas. As control tests, a number of well-known cancer imaging targets were detected and confirmed by our study. Further, by consulting gene-disease and protein-disease databases, we suggest a number of significantly upregulated genes as promising imaging targets, including cell surface-associated mucin-1, prostate-specific membrane antigen, hepsin, urokinase plasminogen activator receptor, and folate receptors. By integrating pathway analysis, we are able to organize and map “focused” interaction networks derived from significantly dysregulated entity pairs to reflect important cellular functions in disease processes. We provide herein an example of identifying a tumor cell growth and proliferation subnetwork for prostate cancer. This systematic mining approach can be broadly applied to identify imaging or therapeutic targets for other human diseases.
Identifying elemental genomic track types and representing them uniformly

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Gundersen Sveinung

2011-12-01

Full Text Available Abstract Background With the recent advances and availability of various high-throughput sequencing technologies, data on many molecular aspects, such as gene regulation, chromatin dynamics, and the three-dimensional organization of DNA, are rapidly being generated in an increasing number of laboratories. The variation in biological context, and the increasingly dispersed mode of data generation, imply a need for precise, interoperable and flexible representations of genomic features through formats that are easy to parse. A host of alternative formats are currently available and in use, complicating analysis and tool development. The issue of whether and how the multitude of formats reflects varying underlying characteristics of data has to our knowledge not previously been systematically treated. Results We here identify intrinsic distinctions between genomic features, and argue that the distinctions imply that a certain variation in the representation of features as genomic tracks is warranted. Four core informational properties of tracks are discussed: gaps, lengths, values and interconnections. From this we delineate fifteen generic track types. Based on the track type distinctions, we characterize major existing representational formats and find that the track types are not adequately supported by any single format. We also find, in contrast to the XML formats, that none of the existing tabular formats are conveniently extendable to support all track types. We thus propose two unified formats for track data, an improved XML format, BioXSD 1.1, and a new tabular format, GTrack 1.0. Conclusions The defined track types are shown to capture relevant distinctions between genomic annotation tracks, resulting in varying representational needs and analysis possibilities. The proposed formats, GTrack 1.0 and BioXSD 1.1, cater to the identified track distinctions and emphasize preciseness, flexibility and parsing convenience.
Prognostic impact of array-based genomic profiles in esophageal squamous cell cancer

DEFF Research Database (Denmark)

Carneiro, Ana; Isinger, Anna; Karlsson, Anna

2008-01-01

BACKGROUND: Esophageal squamous cell carcinoma (ESCC) is a genetically complex tumor type and a major cause of cancer related mortality. Although distinct genetic alterations have been linked to ESCC development and prognosis, the genetic alterations have not gained clinical applicability. We...... interdependent alterations and deranged pathways were identified and copy number changes were correlated to stage, differentiation and survival. RESULTS: Copy number alterations affected median 19% of the genome and included recurrent gains of chromosome regions 5p, 7p, 7q, 8q, 10q, 11q, 12p, 14q, 16p, 17p, 19p......p13.3 independently predicted poor survival in multivariate analysis. CONCLUSION: aCGH profiling verified genetic complexity in ESCC and herein identified imbalances of multiple central tumorigenic pathways. Distinct gains correlate with clinicopathological variables and independently predict...
Network-Based Integration of Disparate Omic Data To Identify "Silent Players" in Cancer.

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Matthew Ruffalo

2015-12-01

Full Text Available Development of high-throughput monitoring technologies enables interrogation of cancer samples at various levels of cellular activity. Capitalizing on these developments, various public efforts such as The Cancer Genome Atlas (TCGA generate disparate omic data for large patient cohorts. As demonstrated by recent studies, these heterogeneous data sources provide the opportunity to gain insights into the molecular changes that drive cancer pathogenesis and progression. However, these insights are limited by the vast search space and as a result low statistical power to make new discoveries. In this paper, we propose methods for integrating disparate omic data using molecular interaction networks, with a view to gaining mechanistic insights into the relationship between molecular changes at different levels of cellular activity. Namely, we hypothesize that genes that play a role in cancer development and progression may be implicated by neither frequent mutation nor differential expression, and that network-based integration of mutation and differential expression data can reveal these "silent players". For this purpose, we utilize network-propagation algorithms to simulate the information flow in the cell at a sample-specific resolution. We then use the propagated mutation and expression signals to identify genes that are not necessarily mutated or differentially expressed genes, but have an essential role in tumor development and patient outcome. We test the proposed method on breast cancer and glioblastoma multiforme data obtained from TCGA. Our results show that the proposed method can identify important proteins that are not readily revealed by molecular data, providing insights beyond what can be gleaned by analyzing different types of molecular data in isolation.
Genetics and Genomics: Discovery, Validation, and Utility of Novel Tools for management of Prostate Cancer

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Alan W. Shindel

2017-01-01

Full Text Available Genomics is the science of how genes influence human health and disease states. It differs from traditional genetic screening in that the transcriptional activity (or other markers in full panels of related genes are studied. Compared to simple genetic testing, assessment of expression levels in a panel of genes provides a more nuanced and holistic understanding of genetic modulation of human disease. Genomic testing may be used to great effect in resolving controversial questions on detection and treatment of prostate cancer. Genomic tests are currently in use for numerous facets of prostate cancer care, including screening, biopsy, and treatment planning. The clinical validity (predictive capacity of these assays has been well established; studies on clinical utility (i.e. usefulness of these tests in guiding patient/provider decisions have shown promising results. Men’s health specialists should be familiar with the role genomic testing will play in contemporary management of prostate cancer.
Functional Genomics Uncover the Biology behind the Responsiveness of Head and Neck Squamous Cell Cancer Patients to Cetuximab.

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Bossi, Paolo; Bergamini, Cristiana; Siano, Marco; Cossu Rocca, Maria; Sponghini, Andrea P; Favales, Federica; Giannoccaro, Marco; Marchesi, Edoardo; Cortelazzi, Barbara; Perrone, Federica; Pilotti, Silvana; Locati, Laura D; Licitra, Lisa; Canevari, Silvana; De Cecco, Loris

2016-08-01

To identify the tumor portrait of the minority of head and neck squamous cell carcinoma (HNSCC) patients with recurrent-metastatic (RM) disease who upon treatment with platinum-based chemotherapy plus cetuximab present a long-lasting response. The gene expression of pretreatment samples from 40 HNSCC-RM patients, divided in two groups [14 long-progression-free survival (PFS) and 26 short-PFS (median = 19 and 3 months, respectively)], was associated with PFS and was challenged against a dataset from metastatic colon cancer patients treated with cetuximab. For biologic analysis, we performed functional and subtype association using gene set enrichment analysis, associated biology across all currently available HNSCC signatures, and inferred drug sensitivity using data from the Cancer Genomic Project. The identified genomic profile exhibited a significant predictive value that was essentially confirmed in the single publicly available dataset of cetuximab-treated patients. The main divergence between long- and short-PFS groups was based on developmental/differentiation status. The long-PFS patients are characterized by basal subtype traits such as strong EGFR signaling phenotype and hypoxic differentiation, further validated by the significantly higher association with the hypoxia metagene. The short-PFS patients presented a strong activation of RAS signaling confirmed in an in vitro model of two isogenic HNSCC cell lines sensitive or resistant to cetuximab. The predicted drug sensitivity for all four EGFR inhibitors was higher in long- versus short-PFS patients (P range: biology behind response to platinum-based chemotherapy plus cetuximab in RM-HNSCC cancer and may have translational implications improving treatment selection. Clin Cancer Res; 22(15); 3961-70. ©2016 AACRSee related commentary by Chau and Hammerman, p. 3710. ©2016 American Association for Cancer Research.
Novel expressed sequences identified in a model of androgen independent prostate cancer

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Jones Steven JM

2007-01-01

Full Text Available Abstract Background Prostate cancer is the most frequently diagnosed cancer in American men, and few effective treatment options are available to patients who develop hormone-refractory prostate cancer. The molecular changes that occur to allow prostate cells to proliferate in the absence of androgens are not fully understood. Results Subtractive hybridization experiments performed with samples from an in vivo model of hormonal progression identified 25 expressed sequences representing novel human transcripts. Intriguingly, these 25 sequences have small open-reading frames and are not highly conserved through evolution, suggesting many of these novel expressed sequences may be derived from untranslated regions of novel transcripts or from non-coding transcripts. Examination of a large metalibrary of human Serial Analysis of Gene Expression (SAGE tags demonstrated that only three of these novel sequences had been previously detected. RT-PCR experiments confirmed that the 6 sequences tested were expressed in specific human tissues, as well as in clinical samples of prostate cancer. Further RT-PCR experiments for five of these fragments indicated they originated from large untranslated regions of unannotated transcripts. Conclusion This study underlines the value of using complementary techniques in the annotation of the human genome. The tissue-specific expression of 4 of the 6 clones tested indicates the expression of these novel transcripts is tightly regulated, and future work will determine the possible role(s these novel transcripts may play in the progression of prostate cancer.
Tumor Genomic Profiling in Breast Cancer Patients Using Targeted Massively Parallel Sequencing

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2016-03-01

2015 “Cancer Care as a Model for Precision Medicine” MIT Collaborative Series Massachusetts Institute of Technology Invited Talk 2016 “Cancer...Precision Medicine” MIT -CHIEF Series Massachusetts Institute of Technology Invited Talk National 2013 “CanSeq: The Use of Whole Exome Sequencing To...Pennsylvania Philadelphia, PA Invited Talk 2014 “Clinical Genomics and Precision Cancer Medicine” Center for Molecular Oncology Memorial Sloan
Genomic Data Commons and Genomic Cloud Pilots - Google Hangout

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Join us for a live, moderated discussion about two NCI efforts to expand access to cancer genomics data: the Genomic Data Commons and Genomic Cloud Pilots. NCI subject matters experts will include Louis M. Staudt, M.D., Ph.D., Director Center for Cancer Genomics, Warren Kibbe, Ph.D., Director, NCI Center for Biomedical Informatics and Information Technology, and moderated by Anthony Kerlavage, Ph.D., Chief, Cancer Informatics Branch, Center for Biomedical Informatics and Information Technology. We welcome your questions before and during the Hangout on Twitter using the hashtag #AskNCI.
Genome-wide identification of key modulators of gene-gene interaction networks in breast cancer.

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Chiu, Yu-Chiao; Wang, Li-Ju; Hsiao, Tzu-Hung; Chuang, Eric Y; Chen, Yidong

2017-10-03

With the advances in high-throughput gene profiling technologies, a large volume of gene interaction maps has been constructed. A higher-level layer of gene-gene interaction, namely modulate gene interaction, is composed of gene pairs of which interaction strengths are modulated by (i.e., dependent on) the expression level of a key modulator gene. Systematic investigations into the modulation by estrogen receptor (ER), the best-known modulator gene, have revealed the functional and prognostic significance in breast cancer. However, a genome-wide identification of key modulator genes that may further unveil the landscape of modulated gene interaction is still lacking. We proposed a systematic workflow to screen for key modulators based on genome-wide gene expression profiles. We designed four modularity parameters to measure the ability of a putative modulator to perturb gene interaction networks. Applying the method to a dataset of 286 breast tumors, we comprehensively characterized the modularity parameters and identified a total of 973 key modulator genes. The modularity of these modulators was verified in three independent breast cancer datasets. ESR1, the encoding gene of ER, appeared in the list, and abundant novel modulators were illuminated. For instance, a prognostic predictor of breast cancer, SFRP1, was found the second modulator. Functional annotation analysis of the 973 modulators revealed involvements in ER-related cellular processes as well as immune- and tumor-associated functions. Here we present, as far as we know, the first comprehensive analysis of key modulator genes on a genome-wide scale. The validity of filtering parameters as well as the conservativity of modulators among cohorts were corroborated. Our data bring new insights into the modulated layer of gene-gene interaction and provide candidates for further biological investigations.
Identifying Cancer Driver Genes Using Replication-Incompetent Retroviral Vectors

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Victor M. Bii

2016-10-01

Full Text Available Identifying novel genes that drive tumor metastasis and drug resistance has significant potential to improve patient outcomes. High-throughput sequencing approaches have identified cancer genes, but distinguishing driver genes from passengers remains challenging. Insertional mutagenesis screens using replication-incompetent retroviral vectors have emerged as a powerful tool to identify cancer genes. Unlike replicating retroviruses and transposons, replication-incompetent retroviral vectors lack additional mutagenesis events that can complicate the identification of driver mutations from passenger mutations. They can also be used for almost any human cancer due to the broad tropism of the vectors. Replication-incompetent retroviral vectors have the ability to dysregulate nearby cancer genes via several mechanisms including enhancer-mediated activation of gene promoters. The integrated provirus acts as a unique molecular tag for nearby candidate driver genes which can be rapidly identified using well established methods that utilize next generation sequencing and bioinformatics programs. Recently, retroviral vector screens have been used to efficiently identify candidate driver genes in prostate, breast, liver and pancreatic cancers. Validated driver genes can be potential therapeutic targets and biomarkers. In this review, we describe the emergence of retroviral insertional mutagenesis screens using replication-incompetent retroviral vectors as a novel tool to identify cancer driver genes in different cancer types.
Identifying artificial selection signals in the chicken genome.

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Yunlong Ma

Full Text Available Identifying the signals of artificial selection can contribute to further shaping economically important traits. Here, a chicken 600k SNP-array was employed to detect the signals of artificial selection using 331 individuals from 9 breeds, including Jingfen (JF, Jinghong (JH, Araucanas (AR, White Leghorn (WL, Pekin-Bantam (PB, Shamo (SH, Gallus-Gallus-Spadiceus (GA, Rheinlander (RH and Vorwerkhuhn (VO. Per the population genetic structure, 9 breeds were combined into 5 breed-pools, and a 'two-step' strategy was used to reveal the signals of artificial selection. GA, which has little artificial selection, was defined as the reference population, and a total of 204, 155, 305 and 323 potential artificial selection signals were identified in AR_VO, PB, RH_WL and JH_JF, respectively. We also found signals derived from standing and de-novo genetic variations have contributed to adaptive evolution during artificial selection. Further enrichment analysis suggests that the genomic regions of artificial selection signals harbour genes, including THSR, PTHLH and PMCH, responsible for economic traits, such as fertility, growth and immunization. Overall, this study found a series of genes that contribute to the improvement of chicken breeds and revealed the genetic mechanisms of adaptive evolution, which can be used as fundamental information in future chicken functional genomics study.

Transposon activation mutagenesis as a screening tool for identifying resistance to cancer therapeutics

International Nuclear Information System (INIS)

Chen, Li; Schmidt, Emmett V; Stuart, Lynda; Ohsumi, Toshiro K; Burgess, Shawn; Varshney, Gaurav K; Dastur, Anahita; Borowsky, Mark; Benes, Cyril; Lacy-Hulbert, Adam

2013-01-01

The development of resistance to chemotherapies represents a significant barrier to successful cancer treatment. Resistance mechanisms are complex, can involve diverse and often unexpected cellular processes, and can vary with both the underlying genetic lesion and the origin or type of tumor. For these reasons developing experimental strategies that could be used to understand, identify and predict mechanisms of resistance in different malignant cells would be a major advance. Here we describe a gain-of-function forward genetic approach for identifying mechanisms of resistance. This approach uses a modified piggyBac transposon to generate libraries of mutagenized cells, each containing transposon insertions that randomly activate nearby gene expression. Genes of interest are identified using next-gen high-throughput sequencing and barcode multiplexing is used to reduce experimental cost. Using this approach we successfully identify genes involved in paclitaxel resistance in a variety of cancer cell lines, including the multidrug transporter ABCB1, a previously identified major paclitaxel resistance gene. Analysis of co-occurring transposons integration sites in single cell clone allows for the identification of genes that might act cooperatively to produce drug resistance a level of information not accessible using RNAi or ORF expression screening approaches. We have developed a powerful pipeline to systematically discover drug resistance in mammalian cells in vitro. This cost-effective approach can be readily applied to different cell lines, to identify canonical or context specific resistance mechanisms. Its ability to probe complex genetic context and non-coding genomic elements as well as cooperative resistance events makes it a good complement to RNAi or ORF expression based screens
CMS: a web-based system for visualization and analysis of genome-wide methylation data of human cancers.

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Gu, Fei; Doderer, Mark S; Huang, Yi-Wen; Roa, Juan C; Goodfellow, Paul J; Kizer, E Lynette; Huang, Tim H M; Chen, Yidong

2013-01-01

DNA methylation of promoter CpG islands is associated with gene suppression, and its unique genome-wide profiles have been linked to tumor progression. Coupled with high-throughput sequencing technologies, it can now efficiently determine genome-wide methylation profiles in cancer cells. Also, experimental and computational technologies make it possible to find the functional relationship between cancer-specific methylation patterns and their clinicopathological parameters. Cancer methylome system (CMS) is a web-based database application designed for the visualization, comparison and statistical analysis of human cancer-specific DNA methylation. Methylation intensities were obtained from MBDCap-sequencing, pre-processed and stored in the database. 191 patient samples (169 tumor and 22 normal specimen) and 41 breast cancer cell-lines are deposited in the database, comprising about 6.6 billion uniquely mapped sequence reads. This provides comprehensive and genome-wide epigenetic portraits of human breast cancer and endometrial cancer to date. Two views are proposed for users to better understand methylation structure at the genomic level or systemic methylation alteration at the gene level. In addition, a variety of annotation tracks are provided to cover genomic information. CMS includes important analytic functions for interpretation of methylation data, such as the detection of differentially methylated regions, statistical calculation of global methylation intensities, multiple gene sets of biologically significant categories, interactivity with UCSC via custom-track data. We also present examples of discoveries utilizing the framework. CMS provides visualization and analytic functions for cancer methylome datasets. A comprehensive collection of datasets, a variety of embedded analytic functions and extensive applications with biological and translational significance make this system powerful and unique in cancer methylation research. CMS is freely accessible
Building a semantic web-based metadata repository for facilitating detailed clinical modeling in cancer genome studies.

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Sharma, Deepak K; Solbrig, Harold R; Tao, Cui; Weng, Chunhua; Chute, Christopher G; Jiang, Guoqian

2017-06-05

Detailed Clinical Models (DCMs) have been regarded as the basis for retaining computable meaning when data are exchanged between heterogeneous computer systems. To better support clinical cancer data capturing and reporting, there is an emerging need to develop informatics solutions for standards-based clinical models in cancer study domains. The objective of the study is to develop and evaluate a cancer genome study metadata management system that serves as a key infrastructure in supporting clinical information modeling in cancer genome study domains. We leveraged a Semantic Web-based metadata repository enhanced with both ISO11179 metadata standard and Clinical Information Modeling Initiative (CIMI) Reference Model. We used the common data elements (CDEs) defined in The Cancer Genome Atlas (TCGA) data dictionary, and extracted the metadata of the CDEs using the NCI Cancer Data Standards Repository (caDSR) CDE dataset rendered in the Resource Description Framework (RDF). The ITEM/ITEM_GROUP pattern defined in the latest CIMI Reference Model is used to represent reusable model elements (mini-Archetypes). We produced a metadata repository with 38 clinical cancer genome study domains, comprising a rich collection of mini-Archetype pattern instances. We performed a case study of the domain "clinical pharmaceutical" in the TCGA data dictionary and demonstrated enriched data elements in the metadata repository are very useful in support of building detailed clinical models. Our informatics approach leveraging Semantic Web technologies provides an effective way to build a CIMI-compliant metadata repository that would facilitate the detailed clinical modeling to support use cases beyond TCGA in clinical cancer study domains.
Genome network medicine: innovation to overcome huge challenges in cancer therapy.

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Roukos, Dimitrios H

2014-01-01

The post-ENCODE era shapes now a new biomedical research direction for understanding transcriptional and signaling networks driving gene expression and core cellular processes such as cell fate, survival, and apoptosis. Over the past half century, the Francis Crick 'central dogma' of single n gene/protein-phenotype (trait/disease) has defined biology, human physiology, disease, diagnostics, and drugs discovery. However, the ENCODE project and several other genomic studies using high-throughput sequencing technologies, computational strategies, and imaging techniques to visualize regulatory networks, provide evidence that transcriptional process and gene expression are regulated by highly complex dynamic molecular and signaling networks. This Focus article describes the linear experimentation-based limitations of diagnostics and therapeutics to cure advanced cancer and the need to move on from reductionist to network-based approaches. With evident a wide genomic heterogeneity, the power and challenges of next-generation sequencing (NGS) technologies to identify a patient's personal mutational landscape for tailoring the best target drugs in the individual patient are discussed. However, the available drugs are not capable of targeting aberrant signaling networks and research on functional transcriptional heterogeneity and functional genome organization is poorly understood. Therefore, the future clinical genome network medicine aiming at overcoming multiple problems in the new fields of regulatory DNA mapping, noncoding RNA, enhancer RNAs, and dynamic complexity of transcriptional circuitry are also discussed expecting in new innovation technology and strong appreciation of clinical data and evidence-based medicine. The problematic and potential solutions in the discovery of next-generation, molecular, and signaling circuitry-based biomarkers and drugs are explored. © 2013 Wiley Periodicals, Inc.
Multiple-integrations of HPV16 genome and altered transcription of viral oncogenes and cellular genes are associated with the development of cervical cancer.

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Xulian Lu

Full Text Available The constitutive expression of the high-risk HPV E6 and E7 viral oncogenes is the major cause of cervical cancer. To comprehensively explore the composition of HPV16 early transcripts and their genomic annotation, cervical squamous epithelial tissues from 40 HPV16-infected patients were collected for analysis of papillomavirus oncogene transcripts (APOT. We observed different transcription patterns of HPV16 oncogenes in progression of cervical lesions to cervical cancer and identified one novel transcript. Multiple-integration events in the tissues of cervical carcinoma (CxCa are significantly more often than those of low-grade squamous intraepithelial lesions (LSIL and high-grade squamous intraepithelial lesions (HSIL. Moreover, most cellular genes within or near these integration sites are cancer-associated genes. Taken together, this study suggests that the multiple-integrations of HPV genome during persistent viral infection, which thereby alters the expression patterns of viral oncogenes and integration-related cellular genes, play a crucial role in progression of cervical lesions to cervix cancer.
Comparative genomics of 12 strains of Erwinia amylovora identifies a pan-genome with a large conserved core.

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Rachel A Mann

Full Text Available The plant pathogen Erwinia amylovora can be divided into two host-specific groupings; strains infecting a broad range of hosts within the Rosaceae subfamily Spiraeoideae (e.g., Malus, Pyrus, Crataegus, Sorbus and strains infecting Rubus (raspberries and blackberries. Comparative genomic analysis of 12 strains representing distinct populations (e.g., geographic, temporal, host origin of E. amylovora was used to describe the pan-genome of this major pathogen. The pan-genome contains 5751 coding sequences and is highly conserved relative to other phytopathogenic bacteria comprising on average 89% conserved, core genes. The chromosomes of Spiraeoideae-infecting strains were highly homogeneous, while greater genetic diversity was observed between Spiraeoideae- and Rubus-infecting strains (and among individual Rubus-infecting strains, the majority of which was attributed to variable genomic islands. Based on genomic distance scores and phylogenetic analysis, the Rubus-infecting strain ATCC BAA-2158 was genetically more closely related to the Spiraeoideae-infecting strains of E. amylovora than it was to the other Rubus-infecting strains. Analysis of the accessory genomes of Spiraeoideae- and Rubus-infecting strains has identified putative host-specific determinants including variation in the effector protein HopX1(Ea and a putative secondary metabolite pathway only present in Rubus-infecting strains.
Genome-Wide Progesterone Receptor Binding: Cell Type-Specific and Shared Mechanisms in T47D Breast Cancer Cells and Primary Leiomyoma Cells

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Huang, Lei; Owen, Jonas K.; Xie, Anna; Navarro, Antonia; Monsivais, Diana; Coon V, John S.; Kim, J. Julie; Dai, Yang; Bulun, Serdar E.

2012-01-01

Background Progesterone, via its nuclear receptor (PR), exerts an overall tumorigenic effect on both uterine fibroid (leiomyoma) and breast cancer tissues, whereas the antiprogestin RU486 inhibits growth of these tissues through an unknown mechanism. Here, we determined the interaction between common or cell-specific genome-wide binding sites of PR and mRNA expression in RU486-treated uterine leiomyoma and breast cancer cells. Principal Findings ChIP-sequencing revealed 31,457 and 7,034 PR-binding sites in breast cancer and uterine leiomyoma cells, respectively; 1,035 sites overlapped in both cell types. Based on the chromatin-PR interaction in both cell types, we statistically refined the consensus progesterone response element to G•ACA• • •TGT•C. We identified two striking differences between uterine leiomyoma and breast cancer cells. First, the cis-regulatory elements for HSF, TEF-1, and C/EBPα and β were statistically enriched at genomic RU486/PR-targets in uterine leiomyoma, whereas E2F, FOXO1, FOXA1, and FOXF sites were preferentially enriched in breast cancer cells. Second, 51.5% of RU486-regulated genes in breast cancer cells but only 6.6% of RU486-regulated genes in uterine leiomyoma cells contained a PR-binding site within 5 kb from their transcription start sites (TSSs), whereas 75.4% of RU486-regulated genes contained a PR-binding site farther than 50 kb from their TSSs in uterine leiomyoma cells. RU486 regulated only seven mRNAs in both cell types. Among these, adipophilin (PLIN2), a pro-differentiation gene, was induced via RU486 and PR via the same regulatory region in both cell types. Conclusions Our studies have identified molecular components in a RU486/PR-controlled gene network involved in the regulation of cell growth, cell migration, and extracellular matrix function. Tissue-specific and common patterns of genome-wide PR binding and gene regulation may determine the therapeutic effects of antiprogestins in uterine fibroids and
Genome-wide analysis identifies 12 loci influencing human reproductive behavior

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Barban, Nicola; Jansen, Rick; de Vlaming, Ronald; Vaez, Ahmad; Mandemakers, Jornt J.; Tropf, Felix C.; Shen, Xia; Wilson, James F.; Chasman, Daniel I.; Nolte, Ilja M.; Tragante, Vinicius; van der Laan, Sander W.; Perry, John R. B.; Kong, Augustine; Ahluwalia, Tarunveer; Albrecht, Eva; Yerges-Armstrong, Laura; Atzmon, Gil; Auro, Kirsi; Ayers, Kristin; Bakshi, Andrew; Ben-Avraham, Danny; Berger, Klaus; Bergman, Aviv; Bertram, Lars; Bielak, Lawrence F.; Bjornsdottir, Gyda; Bonder, Marc Jan; Broer, Linda; Bui, Minh; Barbieri, Caterina; Cavadino, Alana; Chavarro, Jorge E; Turman, Constance; Concas, Maria Pina; Cordell, Heather J.; Davies, Gail; Eibich, Peter; Eriksson, Nicholas; Esko, Tõnu; Eriksson, Joel; Falahi, Fahimeh; Felix, Janine F.; Fontana, Mark Alan; Franke, Lude; Gandin, Ilaria; Gaskins, Audrey J.; Gieger, Christian; Gunderson, Erica P.; Guo, Xiuqing; Hayward, Caroline; He, Chunyan; Hofer, Edith; Huang, Hongyan; Joshi, Peter K.; Kanoni, Stavroula; Karlsson, Robert; Kiechl, Stefan; Kifley, Annette; Kluttig, Alexander; Kraft, Peter; Lagou, Vasiliki; Lecoeur, Cecile; Lahti, Jari; Li-Gao, Ruifang; Lind, Penelope A.; Liu, Tian; Makalic, Enes; Mamasoula, Crysovalanto; Matteson, Lindsay; Mbarek, Hamdi; McArdle, Patrick F.; McMahon, George; Meddens, S. Fleur W.; Mihailov, Evelin; Miller, Mike; Missmer, Stacey A.; Monnereau, Claire; van der Most, Peter J.; Myhre, Ronny; Nalls, Mike A.; Nutile, Teresa; Panagiota, Kalafati Ioanna; Porcu, Eleonora; Prokopenko, Inga; Rajan, Kumar B.; Rich-Edwards, Janet; Rietveld, Cornelius A.; Robino, Antonietta; Rose, Lynda M.; Rueedi, Rico; Ryan, Kathy; Saba, Yasaman; Schmidt, Daniel; Smith, Jennifer A.; Stolk, Lisette; Streeten, Elizabeth; Tonjes, Anke; Thorleifsson, Gudmar; Ulivi, Sheila; Wedenoja, Juho; Wellmann, Juergen; Willeit, Peter; Yao, Jie; Yengo, Loic; Zhao, Jing Hua; Zhao, Wei; Zhernakova, Daria V.; Amin, Najaf; Andrews, Howard; Balkau, Beverley; Barzilai, Nir; Bergmann, Sven; Biino, Ginevra; Bisgaard, Hans; Bønnelykke, Klaus; Boomsma, Dorret I.; Buring, Julie E.; Campbell, Harry; Cappellani, Stefania; Ciullo, Marina; Cox, Simon R.; Cucca, Francesco; Daniela, Toniolo; Davey-Smith, George; Deary, Ian J.; Dedoussis, George; Deloukas, Panos; van Duijn, Cornelia M.; de Geus, Eco JC.; Eriksson, Johan G.; Evans, Denis A.; Faul, Jessica D.; Felicita, Sala Cinzia; Froguel, Philippe; Gasparini, Paolo; Girotto, Giorgia; Grabe, Hans-Jörgen; Greiser, Karin Halina; Groenen, Patrick J.F.; de Haan, Hugoline G.; Haerting, Johannes; Harris, Tamara B.; Heath, Andrew C.; Heikkilä, Kauko; Hofman, Albert; Homuth, Georg; Holliday, Elizabeth G; Hopper, John; Hypponen, Elina; Jacobsson, Bo; Jaddoe, Vincent W. V.; Johannesson, Magnus; Jugessur, Astanand; Kähönen, Mika; Kajantie, Eero; Kardia, Sharon L.R.; Keavney, Bernard; Kolcic, Ivana; Koponen, Päivikki; Kovacs, Peter; Kronenberg, Florian; Kutalik, Zoltan; La Bianca, Martina; Lachance, Genevieve; Iacono, William; Lai, Sandra; Lehtimäki, Terho; Liewald, David C; Lindgren, Cecilia; Liu, Yongmei; Luben, Robert; Lucht, Michael; Luoto, Riitta; Magnus, Per; Magnusson, Patrik K.E.; Martin, Nicholas G.; McGue, Matt; McQuillan, Ruth; Medland, Sarah E.; Meisinger, Christa; Mellström, Dan; Metspalu, Andres; Michela, Traglia; Milani, Lili; Mitchell, Paul; Montgomery, Grant W.; Mook-Kanamori, Dennis; de Mutsert, Renée; Nohr, Ellen A; Ohlsson, Claes; Olsen, Jørn; Ong, Ken K.; Paternoster, Lavinia; Pattie, Alison; Penninx, Brenda WJH; Perola, Markus; Peyser, Patricia A.; Pirastu, Mario; Polasek, Ozren; Power, Chris; Kaprio, Jaakko; Raffel, Leslie J.; Räikkönen, Katri; Raitakari, Olli; Ridker, Paul M.; Ring, Susan M.; Roll, Kathryn; Rudan, Igor; Ruggiero, Daniela; Rujescu, Dan; Salomaa, Veikko; Schlessinger, David; Schmidt, Helena; Schmidt, Reinhold; Schupf, Nicole; Smit, Johannes; Sorice, Rossella; Spector, Tim D.; Starr, John M.; Stöckl, Doris; Strauch, Konstantin; Stumvoll, Michael; Swertz, Morris A.; Thorsteinsdottir, Unnur; Thurik, A. Roy; Timpson, Nicholas J.; Tönjes, Anke; Tung, Joyce Y.; Uitterlinden, André G.; Vaccargiu, Simona; Viikari, Jorma; Vitart, Veronique; Völzke, Henry; Vollenweider, Peter; Vuckovic, Dragana; Waage, Johannes; Wagner, Gert G.; Wang, Jie Jin; Wareham, Nicholas J.; Weir, David R.; Willemsen, Gonneke; Willeit, Johann; Wright, Alan F.; Zondervan, Krina T.; Stefansson, Kari; Krueger, Robert F.; Lee, James J.; Benjamin, Daniel J.; Cesarini, David; Koellinger, Philipp D.; den Hoed, Marcel; Snieder, Harold; Mills, Melinda C.

2017-01-01

The genetic architecture of human reproductive behavior – age at first birth (AFB) and number of children ever born (NEB) – has a strong relationship with fitness, human development, infertility and risk of neuropsychiatric disorders. However, very few genetic loci have been identified and the underlying mechanisms of AFB and NEB are poorly understood. We report the largest genome-wide association study to date of both sexes including 251,151 individuals for AFB and 343,072 for NEB. We identified 12 independent loci that are significantly associated with AFB and/or NEB in a SNP-based genome-wide association study, and four additional loci in a gene-based effort. These loci harbor genes that are likely to play a role – either directly or by affecting non-local gene expression – in human reproduction and infertility, thereby increasing our understanding of these complex traits. PMID:27798627
Implementing a screening tool for identifying patients at risk for hereditary breast and ovarian cancer: a statewide initiative.

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Brannon Traxler, L; Martin, Monique L; Kerber, Alice S; Bellcross, Cecelia A; Crane, Barbara E; Green, Victoria; Matthews, Roland; Paris, Nancy M; Gabram, Sheryl G A

2014-10-01

The Georgia Breast Cancer Genomic Health Consortium is a partnership created with funding from the Centers for Disease Control and Prevention (CDC) to the Georgia Department of Public Health to reduce cancer disparities among high-risk minority women. The project addresses young women at increased risk for hereditary breast and ovarian cancer (HBOC) syndrome through outreach efforts. The consortium provides education and collects surveillance data using the breast cancer genetics referral screening tool (B-RST) available at www.BreastCancerGeneScreen.org . The HBOC educational protocol was presented to 73 staff in 6 public health centers. Staff used the tool during the collection of medical history. Further family history assessments and testing for mutations in the BRCA1/2 genes were facilitated if appropriate. Data was collected from November 2012 through December 2013, including 2,159 screened women. The majority of patients identified as black/African American and were 18-49 years old. Also, 6.0 % (n = 130) had positive screens, and 60.9 % (n = 67) of the 110 patients who agreed to be contacted provided a detailed family history. A total of 47 patients (42.7 %) met National Comprehensive Cancer Network guidelines when family history was clarified. Fourteen (12.7 %) underwent genetic testing; 1 patient was positive for a BRCA2 mutation, and 1 patient was found to carry a variant of uncertain significance. The introduction of genomics practice within public health departments has provided access to comprehensive cancer care for uninsured individuals. The successful implementation of the B-RST into public health centers demonstrates the opportunity for integration of HBOC screening into primary care practices.
Implementing Genome-Driven Oncology

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Hyman, David M.; Taylor, Barry S.; Baselga, José

2017-01-01

Early successes in identifying and targeting individual oncogenic drivers, together with the increasing feasibility of sequencing tumor genomes, have brought forth the promise of genome-driven oncology care. As we expand the breadth and depth of genomic analyses, the biological and clinical complexity of its implementation will be unparalleled. Challenges include target credentialing and validation, implementing drug combinations, clinical trial designs, targeting tumor heterogeneity, and deploying technologies beyond DNA sequencing, among others. We review how contemporary approaches are tackling these challenges and will ultimately serve as an engine for biological discovery and increase our insight into cancer and its treatment. PMID:28187282
Cancer prevention, the need to preserve the integrity of the genome at all cost.

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Okafor, M T; Nwagha, T U; Anusiem, C; Okoli, U A; Nubila, N I; Al-Alloosh, F; Udenyia, I J

2018-05-01

The entire genetic information carried by an organism makes up its genome. Genes have a diverse number of functions. They code different proteins for normal proliferation of cells. However, changes in the base sequence of genes affect their protein by-products which act as messengers for normal cellular functions such as proliferation and repairs. Salient processes for maintaining the integrity of the genome are hinged on intricate mechanisms put in place for the evolution to tackle genomic stresses. To discuss how cells sense and repair damage to their deoxyribonucleic acid (DNA) as well as to highlight how defects in the genes involved in DNA repair contribute to cancer development. Methodology: Online searches on the following databases such as Google Scholar, PubMed, Biomed Central, and SciELO were done. Attempt was made to review articles with keywords such as cancer, cell cycle, tumor suppressor genes, and DNA repair. The cell cycle, tumor suppression genes, DNA repair mechanism, as well as their contribution to cancer development, were discussed and reviewed. Knowledge on how cells detect and repair DNA damage through an array of mechanisms should allay our anxiety as regards cancer development. More studies on DNA damage detection and repair processes are important toward a holistic approach to cancer treatment.
Significance of genomic instability in breast cancer in atomic bomb survivors: analysis of microarray-comparative genomic hybridization

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Oikawa Masahiro

2011-12-01

Full Text Available Abstract Background It has been postulated that ionizing radiation induces breast cancers among atomic bomb (A-bomb survivors. We have reported a higher incidence of HER2 and C-MYC oncogene amplification in breast cancers from A-bomb survivors. The purpose of this study was to clarify the effect of A-bomb radiation exposure on genomic instability (GIN, which is an important hallmark of carcinogenesis, in archival formalin-fixed paraffin-embedded (FFPE tissues of breast cancer by using microarray-comparative genomic hybridization (aCGH. Methods Tumor DNA was extracted from FFPE tissues of invasive ductal cancers from 15 survivors who were exposed at 1.5 km or less from the hypocenter and 13 calendar year-matched non-exposed patients followed by aCGH analysis using a high-density oligonucleotide microarray. The total length of copy number aberrations (CNA was used as an indicator of GIN, and correlation with clinicopathological factors were statistically tested. Results The mean of the derivative log ratio spread (DLRSpread, which estimates the noise by calculating the spread of log ratio differences between consecutive probes for all chromosomes, was 0.54 (range, 0.26 to 1.05. The concordance of results between aCGH and fluorescence in situ hybridization (FISH for HER2 gene amplification was 88%. The incidence of HER2 amplification and histological grade was significantly higher in the A-bomb survivors than control group (P = 0.04, respectively. The total length of CNA tended to be larger in the A-bomb survivors (P = 0.15. Correlation analysis of CNA and clinicopathological factors revealed that DLRSpread was negatively correlated with that significantly (P = 0.034, r = -0.40. Multivariate analysis with covariance revealed that the exposure to A-bomb was a significant (P = 0.005 independent factor which was associated with larger total length of CNA of breast cancers. Conclusions Thus, archival FFPE tissues from A-bomb survivors are useful for
Significance of genomic instability in breast cancer in atomic bomb survivors: analysis of microarray-comparative genomic hybridization

International Nuclear Information System (INIS)

Oikawa, Masahiro; Yoshiura, Koh-ichiro; Kondo, Hisayoshi; Miura, Shiro; Nagayasu, Takeshi; Nakashima, Masahiro

2011-01-01

It has been postulated that ionizing radiation induces breast cancers among atomic bomb (A-bomb) survivors. We have reported a higher incidence of HER2 and C-MYC oncogene amplification in breast cancers from A-bomb survivors. The purpose of this study was to clarify the effect of A-bomb radiation exposure on genomic instability (GIN), which is an important hallmark of carcinogenesis, in archival formalin-fixed paraffin-embedded (FFPE) tissues of breast cancer by using microarray-comparative genomic hybridization (aCGH). Tumor DNA was extracted from FFPE tissues of invasive ductal cancers from 15 survivors who were exposed at 1.5 km or less from the hypocenter and 13 calendar year-matched non-exposed patients followed by aCGH analysis using a high-density oligonucleotide microarray. The total length of copy number aberrations (CNA) was used as an indicator of GIN, and correlation with clinicopathological factors were statistically tested. The mean of the derivative log ratio spread (DLRSpread), which estimates the noise by calculating the spread of log ratio differences between consecutive probes for all chromosomes, was 0.54 (range, 0.26 to 1.05). The concordance of results between aCGH and fluorescence in situ hybridization (FISH) for HER2 gene amplification was 88%. The incidence of HER2 amplification and histological grade was significantly higher in the A-bomb survivors than control group (P = 0.04, respectively). The total length of CNA tended to be larger in the A-bomb survivors (P = 0.15). Correlation analysis of CNA and clinicopathological factors revealed that DLRSpread was negatively correlated with that significantly (P = 0.034, r = -0.40). Multivariate analysis with covariance revealed that the exposure to A-bomb was a significant (P = 0.005) independent factor which was associated with larger total length of CNA of breast cancers. Thus, archival FFPE tissues from A-bomb survivors are useful for genome-wide aCGH analysis. Our results suggested that A
Significance of genomic instability in breast cancer in atomic bomb survivors: analysis of microarray-comparative genomic hybridization.

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Oikawa, Masahiro; Yoshiura, Koh-ichiro; Kondo, Hisayoshi; Miura, Shiro; Nagayasu, Takeshi; Nakashima, Masahiro

2011-12-07

It has been postulated that ionizing radiation induces breast cancers among atomic bomb (A-bomb) survivors. We have reported a higher incidence of HER2 and C-MYC oncogene amplification in breast cancers from A-bomb survivors. The purpose of this study was to clarify the effect of A-bomb radiation exposure on genomic instability (GIN), which is an important hallmark of carcinogenesis, in archival formalin-fixed paraffin-embedded (FFPE) tissues of breast cancer by using microarray-comparative genomic hybridization (aCGH). Tumor DNA was extracted from FFPE tissues of invasive ductal cancers from 15 survivors who were exposed at 1.5 km or less from the hypocenter and 13 calendar year-matched non-exposed patients followed by aCGH analysis using a high-density oligonucleotide microarray. The total length of copy number aberrations (CNA) was used as an indicator of GIN, and correlation with clinicopathological factors were statistically tested. The mean of the derivative log ratio spread (DLRSpread), which estimates the noise by calculating the spread of log ratio differences between consecutive probes for all chromosomes, was 0.54 (range, 0.26 to 1.05). The concordance of results between aCGH and fluorescence in situ hybridization (FISH) for HER2 gene amplification was 88%. The incidence of HER2 amplification and histological grade was significantly higher in the A-bomb survivors than control group (P = 0.04, respectively). The total length of CNA tended to be larger in the A-bomb survivors (P = 0.15). Correlation analysis of CNA and clinicopathological factors revealed that DLRSpread was negatively correlated with that significantly (P = 0.034, r = -0.40). Multivariate analysis with covariance revealed that the exposure to A-bomb was a significant (P = 0.005) independent factor which was associated with larger total length of CNA of breast cancers. Thus, archival FFPE tissues from A-bomb survivors are useful for genome-wide aCGH analysis. Our results suggested that A
Analysis of The Cancer Genome Atlas sequencing data reveals novel properties of the human papillomavirus 16 genome in head and neck squamous cell carcinoma.

Science.gov (United States)

Nulton, Tara J; Olex, Amy L; Dozmorov, Mikhail; Morgan, Iain M; Windle, Brad

2017-03-14

Human papillomavirus (HPV) DNA is detected in up to 80% of oropharyngeal carcinomas (OPC) and this HPV positive disease has reached epidemic proportions. To increase our understanding of the disease, we investigated the status of the HPV16 genome in HPV-positive head and neck cancers (HNC). Raw RNA-Seq and Whole Genome Sequence data from The Cancer Genome Atlas HNC samples were analyzed to gain a full understanding of the HPV genome status for these tumors. Several remarkable and novel observations were made following this analysis. Firstly, there are three main HPV genome states in these tumors that are split relatively evenly: An episomal only state, an integrated state, and a state in which the viral genome exists as a hybrid episome with human DNA. Secondly, none of the tumors expressed high levels of E6; E6*I is the dominant variant expressed in all tumors. The most striking conclusion from this study is that around three quarters of HPV16 positive HNC contain episomal versions of the viral genome that are likely replicating in an E1-E2 dependent manner. The clinical and therapeutic implications of these observations are discussed.
Fine-scale mapping of the 4q24 locus identifies two independent loci associated with breast cancer risk.

Science.gov (United States)

Guo, Xingyi; Long, Jirong; Zeng, Chenjie; Michailidou, Kyriaki; Ghoussaini, Maya; Bolla, Manjeet K; Wang, Qin; Milne, Roger L; Shu, Xiao-Ou; Cai, Qiuyin; Beesley, Jonathan; Kar, Siddhartha P; Andrulis, Irene L; Anton-Culver, Hoda; Arndt, Volker; Beckmann, Matthias W; Beeghly-Fadiel, Alicia; Benitez, Javier; Blot, William; Bogdanova, Natalia; Bojesen, Stig E; Brauch, Hiltrud; Brenner, Hermann; Brinton, Louise; Broeks, Annegien; Brüning, Thomas; Burwinkel, Barbara; Cai, Hui; Canisius, Sander; Chang-Claude, Jenny; Choi, Ji-Yeob; Couch, Fergus J; Cox, Angela; Cross, Simon S; Czene, Kamila; Darabi, Hatef; Devilee, Peter; Droit, Arnaud; Dörk, Thilo; Fasching, Peter A; Fletcher, Olivia; Flyger, Henrik; Fostira, Florentia; Gaborieau, Valerie; García-Closas, Montserrat; Giles, Graham G; Grip, Mervi; Guénel, Pascal; Haiman, Christopher A; Hamann, Ute; Hartman, Mikael; Hollestelle, Antoinette; Hopper, John L; Hsiung, Chia-Ni; Ito, Hidemi; Jakubowska, Anna; Johnson, Nichola; Kabisch, Maria; Kang, Daehee; Khan, Sofia; Knight, Julia A; Kosma, Veli-Matti; Lambrechts, Diether; Le Marchand, Loic; Li, Jingmei; Lindblom, Annika; Lophatananon, Artitaya; Lubinski, Jan; Mannermaa, Arto; Manoukian, Siranoush; Margolin, Sara; Marme, Frederik; Matsuo, Keitaro; McLean, Catriona A; Meindl, Alfons; Muir, Kenneth; Neuhausen, Susan L; Nevanlinna, Heli; Nord, Silje; Olson, Janet E; Orr, Nick; Peterlongo, Paolo; Putti, Thomas Choudary; Rudolph, Anja; Sangrajrang, Suleeporn; Sawyer, Elinor J; Schmidt, Marjanka K; Schmutzler, Rita K; Shen, Chen-Yang; Shi, Jiajun; Shrubsole, Martha J; Southey, Melissa C; Swerdlow, Anthony; Teo, Soo Hwang; Thienpont, Bernard; Toland, Amanda Ewart; Tollenaar, Robert A E M; Tomlinson, Ian P M; Truong, Thérèse; Tseng, Chiu-Chen; van den Ouweland, Ans; Wen, Wanqing; Winqvist, Robert; Wu, Anna; Yip, Cheng Har; Zamora, M Pilar; Zheng, Ying; Hall, Per; Pharoah, Paul D P; Simard, Jacques; Chenevix-Trench, Georgia; Dunning, Alison M; Easton, Douglas F; Zheng, Wei

2015-11-01

A recent association study identified a common variant (rs9790517) at 4q24 to be associated with breast cancer risk. Independent association signals and potential functional variants in this locus have not been explored. We conducted a fine-mapping analysis in 55,540 breast cancer cases and 51,168 controls from the Breast Cancer Association Consortium. Conditional analyses identified two independent association signals among women of European ancestry, represented by rs9790517 [conditional P = 2.51 × 10(-4); OR, 1.04; 95% confidence interval (CI), 1.02-1.07] and rs77928427 (P = 1.86 × 10(-4); OR, 1.04; 95% CI, 1.02-1.07). Functional annotation using data from the Encyclopedia of DNA Elements (ENCODE) project revealed two putative functional variants, rs62331150 and rs73838678 in linkage disequilibrium (LD) with rs9790517 (r(2) ≥ 0.90) residing in the active promoter or enhancer, respectively, of the nearest gene, TET2. Both variants are located in DNase I hypersensitivity and transcription factor-binding sites. Using data from both The Cancer Genome Atlas (TCGA) and Molecular Taxonomy of Breast Cancer International Consortium (METABRIC), we showed that rs62331150 was associated with level of expression of TET2 in breast normal and tumor tissue. Our study identified two independent association signals at 4q24 in relation to breast cancer risk and suggested that observed association in this locus may be mediated through the regulation of TET2. Fine-mapping study with large sample size warranted for identification of independent loci for breast cancer risk. ©2015 American Association for Cancer Research.
Emory University: High-Throughput Protein-Protein Interaction Dataset for Lung Cancer-Associated Genes | Office of Cancer Genomics

Science.gov (United States)

To discover novel PPI signaling hubs for lung cancer, CTD2 Center at Emory utilized large-scale genomics datasets and literature to compile a set of lung cancer-associated genes. A library of expression vectors were generated for these genes and utilized for detecting pairwise PPIs with cell lysate-based TR-FRET assays in high-throughput screening format. Read the abstract.
CTD² Dashboard: a searchable web interface to connect validated results from the Cancer Target Discovery and Development Network* | Office of Cancer Genomics

Science.gov (United States)

The Cancer Target Discovery and Development (CTD2) Network aims to use functional genomics to accelerate the translation of high-throughput and high-content genomic and small-molecule data towards use in precision oncology.
Profiles of Genomic Instability in High-Grade Serous Ovarian Cancer Predict Treatment Outcome

DEFF Research Database (Denmark)

Wang, Zhigang C.; Birkbak, Nicolai Juul; Culhane, Aedín C.

2012-01-01

Purpose: High-grade serous cancer (HGSC) is the most common cancer of the ovary and is characterized by chromosomal instability. Defects in homologous recombination repair (HRR) are associated with genomic instability in HGSC, and are exploited by therapy targeting DNA repair. Defective HRR cause...
Genomic analyses identify hundreds of variants associated with age at menarche and support a role for puberty timing in cancer risk

NARCIS (Netherlands)

Day, Felix R; Thompson, Deborah J; Helgason, Hannes; Chasman, Daniel I; Finucane, Hilary; Sulem, Patrick; Ruth, Katherine S; Whalen, Sean; Sarkar, Abhishek K; Albrecht, Eva; Altmaier, Elisabeth; Amini, Marzyeh; Barbieri, Caterina M; Boutin, Thibaud; Campbell, Archie; Demerath, Ellen; Giri, Ayush; He, Chunyan; Hottenga, Jouke J; Karlsson, Robert; Kolcic, Ivana; Loh, Po-Ru; Lunetta, Kathryn L; Mangino, Massimo; Marco, Brumat; McMahon, George; Medland, Sarah E; Nolte, Ilja M; Noordam, Raymond; Nutile, Teresa; Paternoster, Lavinia; Perjakova, Natalia; Porcu, Eleonora; Rose, Lynda M; Schraut, Katharina E; Segrè, Ayellet V; Smith, Albert V; Stolk, Lisette; Teumer, Alexander; Andrulis, Irene L; Bandinelli, Stefania; Beckmann, Matthias W; Benitez, Javier; Bergmann, Sven; Bochud, Murielle; de Geus, Eco J C N; Mbarek, Hamdi; Willemsen, Gonneke; Boomsma, Dorret I; Visser, Jenny A

2017-01-01

The timing of puberty is a highly polygenic childhood trait that is epidemiologically associated with various adult diseases. Using 1000 Genomes Project-imputed genotype data in up to ∼370,000 women, we identify 389 independent signals (P < 5 × 10(-8)) for age at menarche, a milestone in female

Somatic mutation profiles of MSI and MSS colorectal cancer identified by whole exome next generation sequencing and bioinformatics analysis.

Directory of Open Access Journals (Sweden)

Bernd Timmermann

Full Text Available BACKGROUND: Colorectal cancer (CRC is with approximately 1 million cases the third most common cancer worldwide. Extensive research is ongoing to decipher the underlying genetic patterns with the hope to improve early cancer diagnosis and treatment. In this direction, the recent progress in next generation sequencing technologies has revolutionized the field of cancer genomics. However, one caveat of these studies remains the large amount of genetic variations identified and their interpretation. METHODOLOGY/PRINCIPAL FINDINGS: Here we present the first work on whole exome NGS of primary colon cancers. We performed 454 whole exome pyrosequencing of tumor as well as adjacent not affected normal colonic tissue from microsatellite stable (MSS and microsatellite instable (MSI colon cancer patients and identified more than 50,000 small nucleotide variations for each tissue. According to predictions based on MSS and MSI pathomechanisms we identified eight times more somatic non-synonymous variations in MSI cancers than in MSS and we were able to reproduce the result in four additional CRCs. Our bioinformatics filtering approach narrowed down the rate of most significant mutations to 359 for MSI and 45 for MSS CRCs with predicted altered protein functions. In both CRCs, MSI and MSS, we found somatic mutations in the intracellular kinase domain of bone morphogenetic protein receptor 1A, BMPR1A, a gene where so far germline mutations are associated with juvenile polyposis syndrome, and show that the mutations functionally impair the protein function. CONCLUSIONS/SIGNIFICANCE: We conclude that with deep sequencing of tumor exomes one may be able to predict the microsatellite status of CRC and in addition identify potentially clinically relevant mutations.
Genetic variants identified by GWAS was associated with colorectal cancer in the Han Chinese population

Directory of Open Access Journals (Sweden)

Hui-Ping Qiao

2015-01-01

Full Text Available Aim of Study: Colorectal cancer (CRC, now the third most common cancer across the world, is known to aggregate in families. Recently, genome-wide association studies have identified two single nucleotide polymorphisms (SNP associated with CRC in Caucasians. Materials and Methods: To validate whether the same variations conferred risk to CRC in the Han Chinese population, we genotyped 760 individuals (380 controls and 380 cases samples recruited from the Han Chinese origin. Results: We found rs11987193 in 8p12 (P = 0.0472 after correction, OR = 0.751 was significantly associated with CRC but rs12080929 in 1p33 (P = 0.0650 after correction, OR = 0.750 was not. Conclusion: Our findings supported that rs11987193 is a susceptibility locus for CRC, and gene DUSP4 was possible to play a role in the pathology of CRC.
Genome wide association study identifies KCNMA1 contributing to human obesity

DEFF Research Database (Denmark)

Jiao, Hong; Arner, Peter; Hoffstedt, Johan

2011-01-01

Recent genome-wide association (GWA) analyses have identified common single nucleotide polymorphisms (SNPs) that are associated with obesity. However, the reported genetic variation in obesity explains only a minor fraction of the total genetic variation expected to be present in the population....... Thus many genetic variants controlling obesity remain to be identified. The aim of this study was to use GWA followed by multiple stepwise validations to identify additional genes associated with obesity....
Genome-wide association study identifies 74 loci associated with educational attainment

Science.gov (United States)

Okbay, Aysu; Beauchamp, Jonathan P.; Fontana, Mark A.; Lee, James J.; Pers, Tune H.; Rietveld, Cornelius A.; Turley, Patrick; Chen, Guo-Bo; Emilsson, Valur; Meddens, S. Fleur W.; Oskarsson, Sven; Pickrell, Joseph K.; Thom, Kevin; Timshel, Pascal; de Vlaming, Ronald; Abdellaoui, Abdel; Ahluwalia, Tarunveer S.; Bacelis, Jonas; Baumbach, Clemens; Bjornsdottir, Gyda; Brandsma, Johannes H.; Concas, Maria Pina; Derringer, Jaime; Furlotte, Nicholas A.; Galesloot, Tessel E.; Girotto, Giorgia; Gupta, Richa; Hall, Leanne M.; Harris, Sarah E.; Hofer, Edith; Horikoshi, Momoko; Huffman, Jennifer E.; Kaasik, Kadri; Kalafati, Ioanna P.; Karlsson, Robert; Kong, Augustine; Lahti, Jari; van der Lee, Sven J.; de Leeuw, Christiaan; Lind, Penelope A.; Lindgren, Karl-Oskar; Liu, Tian; Mangino, Massimo; Marten, Jonathan; Mihailov, Evelin; Miller, Michael B.; van der Most, Peter J.; Oldmeadow, Christopher; Payton, Antony; Pervjakova, Natalia; Peyrot, Wouter J.; Qian, Yong; Raitakari, Olli; Rueedi, Rico; Salvi, Erika; Schmidt, Börge; Schraut, Katharina E.; Shi, Jianxin; Smith, Albert V.; Poot, Raymond A.; Pourcain, Beate; Teumer, Alexander; Thorleifsson, Gudmar; Verweij, Niek; Vuckovic, Dragana; Wellmann, Juergen; Westra, Harm-Jan; Yang, Jingyun; Zhao, Wei; Zhu, Zhihong; Alizadeh, Behrooz Z.; Amin, Najaf; Bakshi, Andrew; Baumeister, Sebastian E.; Biino, Ginevra; Bønnelykke, Klaus; Boyle, Patricia A.; Campbell, Harry; Cappuccio, Francesco P.; Davies, Gail; De Neve, Jan-Emmanuel; Deloukas, Panos; Demuth, Ilja; Ding, Jun; Eibich, Peter; Eisele, Lewin; Eklund, Niina; Evans68, David M.; Faul, Jessica D.; Feitosa, Mary F.; Forstner, Andreas J.; Gandin, Ilaria; Gunnarsson, Bjarni; Halldórsson, Bjarni V.; Harris, Tamara B.; Heath, Andrew C.; Hocking, Lynne J.; Holliday, Elizabeth G.; Homuth, Georg; Horan, Michael A.; Hottenga, Jouke-Jan; de Jager, Philip L.; Joshi, Peter K.; Jugessur, Astanand; Kaakinen, Marika A.; Kähönen, Mika; Kanoni, Stavroula; Keltigangas-Järvinen, Liisa; Kiemeney, Lambertus A.L.M.; Kolcic, Ivana; Koskinen, Seppo; Kraja, Aldi T.; Kroh, Martin; Kutalik, Zoltan; Latvala, Antti; Launer, Lenore J.; Lebreton, Maël P.; Levinson, Douglas F.; Lichtenstein, Paul; Lichtner, Peter; Liewald, David C.M.; Loukola, Anu; Madden, Pamela A.; Mägi, Reedik; Mäki-Opas, Tomi; Marioni, Riccardo E.; Marques-Vidal, Pedro; Meddens, Gerardus A.; McMahon, George; Meisinger, Christa; Meitinger, Thomas; Milaneschi, Yusplitri; Milani, Lili; Montgomery, Grant W.; Myhre, Ronny; Nelson, Christopher P.; Nyholt, Dale R.; Ollier, William E.R.; Palotie, Aarno; Paternoster, Lavinia; Pedersen, Nancy L.; Petrovic, Katja E.; Porteous, David J.; Räikkönen, Katri; Ring, Susan M.; Robino, Antonietta; Rostapshova, Olga; Rudan, Igor; Rustichini, Aldo; Salomaa, Veikko; Sanders, Alan R.; Sarin, Antti-Pekka; Schmidt, Helena; Scott, Rodney J.; Smith, Blair H.; Smith, Jennifer A.; Staessen, Jan A.; Steinhagen-Thiessen, Elisabeth; Strauch, Konstantin; Terracciano, Antonio; Tobin, Martin D.; Ulivi, Sheila; Vaccargiu, Simona; Quaye, Lydia; van Rooij, Frank J.A.; Venturini, Cristina; Vinkhuyzen, Anna A.E.; Völker, Uwe; Völzke, Henry; Vonk, Judith M.; Vozzi, Diego; Waage, Johannes; Ware, Erin B.; Willemsen, Gonneke; Attia, John R.; Bennett, David A.; Berger, Klaus; Bertram, Lars; Bisgaard, Hans; Boomsma, Dorret I.; Borecki, Ingrid B.; Bultmann, Ute; Chabris, Christopher F.; Cucca, Francesco; Cusi, Daniele; Deary, Ian J.; Dedoussis, George V.; van Duijn, Cornelia M.; Eriksson, Johan G.; Franke, Barbara; Franke, Lude; Gasparini, Paolo; Gejman, Pablo V.; Gieger, Christian; Grabe, Hans-Jörgen; Gratten, Jacob; Groenen, Patrick J.F.; Gudnason, Vilmundur; van der Harst, Pim; Hayward, Caroline; Hinds, David A.; Hoffmann, Wolfgang; Hyppönen, Elina; Iacono, William G.; Jacobsson, Bo; Järvelin, Marjo-Riitta; Jöckel, Karl-Heinz; Kaprio, Jaakko; Kardia, Sharon L.R.; Lehtimäki, Terho; Lehrer, Steven F.; Magnusson, Patrik K.E.; Martin, Nicholas G.; McGue, Matt; Metspalu, Andres; Pendleton, Neil; Penninx, Brenda W.J.H.; Perola, Markus; Pirastu, Nicola; Pirastu, Mario; Polasek, Ozren; Posthuma, Danielle; Power, Christine; Province, Michael A.; Samani, Nilesh J.; Schlessinger, David; Schmidt, Reinhold; Sørensen, Thorkild I.A.; Spector, Tim D.; Stefansson, Kari; Thorsteinsdottir, Unnur; Thurik, A. Roy; Timpson, Nicholas J.; Tiemeier, Henning; Tung, Joyce Y.; Uitterlinden, André G.; Vitart, Veronique; Vollenweider, Peter; Weir, David R.; Wilson, James F.; Wright, Alan F.; Conley, Dalton C.; Krueger, Robert F.; Smith, George Davey; Hofman, Albert; Laibson, David I.; Medland, Sarah E.; Meyer, Michelle N.; Yang, Jian; Johannesson, Magnus; Visscher, Peter M.; Esko, Tõnu; Koellinger, Philipp D.; Cesarini, David; Benjamin, Daniel J.

2016-01-01

Summary Educational attainment (EA) is strongly influenced by social and other environmental factors, but genetic factors are also estimated to account for at least 20% of the variation across individuals1. We report the results of a genome-wide association study (GWAS) for EA that extends our earlier discovery sample1,2 of 101,069 individuals to 293,723 individuals, and a replication in an independent sample of 111,349 individuals from the UK Biobank. We now identify 74 genome-wide significant loci associated with number of years of schooling completed. Single-nucleotide polymorphisms (SNPs) associated with educational attainment are disproportionately found in genomic regions regulating gene expression in the fetal brain. Candidate genes are preferentially expressed in neural tissue, especially during the prenatal period, and enriched for biological pathways involved in neural development. Our findings demonstrate that, even for a behavioral phenotype that is mostly environmentally determined, a well-powered GWAS identifies replicable associated genetic variants that suggest biologically relevant pathways. Because EA is measured in large numbers of individuals, it will continue to be useful as a proxy phenotype in efforts to characterize the genetic influences of related phenotypes, including cognition and neuropsychiatric disease. PMID:27225129
Whole genomes redefine the mutational landscape of pancreatic cancer.

Science.gov (United States)

Waddell, Nicola; Pajic, Marina; Patch, Ann-Marie; Chang, David K; Kassahn, Karin S; Bailey, Peter; Johns, Amber L; Miller, David; Nones, Katia; Quek, Kelly; Quinn, Michael C J; Robertson, Alan J; Fadlullah, Muhammad Z H; Bruxner, Tim J C; Christ, Angelika N; Harliwong, Ivon; Idrisoglu, Senel; Manning, Suzanne; Nourse, Craig; Nourbakhsh, Ehsan; Wani, Shivangi; Wilson, Peter J; Markham, Emma; Cloonan, Nicole; Anderson, Matthew J; Fink, J Lynn; Holmes, Oliver; Kazakoff, Stephen H; Leonard, Conrad; Newell, Felicity; Poudel, Barsha; Song, Sarah; Taylor, Darrin; Waddell, Nick; Wood, Scott; Xu, Qinying; Wu, Jianmin; Pinese, Mark; Cowley, Mark J; Lee, Hong C; Jones, Marc D; Nagrial, Adnan M; Humphris, Jeremy; Chantrill, Lorraine A; Chin, Venessa; Steinmann, Angela M; Mawson, Amanda; Humphrey, Emily S; Colvin, Emily K; Chou, Angela; Scarlett, Christopher J; Pinho, Andreia V; Giry-Laterriere, Marc; Rooman, Ilse; Samra, Jaswinder S; Kench, James G; Pettitt, Jessica A; Merrett, Neil D; Toon, Christopher; Epari, Krishna; Nguyen, Nam Q; Barbour, Andrew; Zeps, Nikolajs; Jamieson, Nigel B; Graham, Janet S; Niclou, Simone P; Bjerkvig, Rolf; Grützmann, Robert; Aust, Daniela; Hruban, Ralph H; Maitra, Anirban; Iacobuzio-Donahue, Christine A; Wolfgang, Christopher L; Morgan, Richard A; Lawlor, Rita T; Corbo, Vincenzo; Bassi, Claudio; Falconi, Massimo; Zamboni, Giuseppe; Tortora, Giampaolo; Tempero, Margaret A; Gill, Anthony J; Eshleman, James R; Pilarsky, Christian; Scarpa, Aldo; Musgrove, Elizabeth A; Pearson, John V; Biankin, Andrew V; Grimmond, Sean M

2015-02-26

Pancreatic cancer remains one of the most lethal of malignancies and a major health burden. We performed whole-genome sequencing and copy number variation (CNV) analysis of 100 pancreatic ductal adenocarcinomas (PDACs). Chromosomal rearrangements leading to gene disruption were prevalent, affecting genes known to be important in pancreatic cancer (TP53, SMAD4, CDKN2A, ARID1A and ROBO2) and new candidate drivers of pancreatic carcinogenesis (KDM6A and PREX2). Patterns of structural variation (variation in chromosomal structure) classified PDACs into 4 subtypes with potential clinical utility: the subtypes were termed stable, locally rearranged, scattered and unstable. A significant proportion harboured focal amplifications, many of which contained druggable oncogenes (ERBB2, MET, FGFR1, CDK6, PIK3R3 and PIK3CA), but at low individual patient prevalence. Genomic instability co-segregated with inactivation of DNA maintenance genes (BRCA1, BRCA2 or PALB2) and a mutational signature of DNA damage repair deficiency. Of 8 patients who received platinum therapy, 4 of 5 individuals with these measures of defective DNA maintenance responded.
Whole genomes redefine the mutational landscape of pancreatic cancer

Science.gov (United States)

Waddell, Nicola; Pajic, Marina; Patch, Ann-Marie; Chang, David K.; Kassahn, Karin S.; Bailey, Peter; Johns, Amber L.; Miller, David; Nones, Katia; Quek, Kelly; Quinn, Michael C. J.; Robertson, Alan J.; Fadlullah, Muhammad Z. H.; Bruxner, Tim J. C.; Christ, Angelika N.; Harliwong, Ivon; Idrisoglu, Senel; Manning, Suzanne; Nourse, Craig; Nourbakhsh, Ehsan; Wani, Shivangi; Wilson, Peter J; Markham, Emma; Cloonan, Nicole; Anderson, Matthew J.; Fink, J. Lynn; Holmes, Oliver; Kazakoff, Stephen H.; Leonard, Conrad; Newell, Felicity; Poudel, Barsha; Song, Sarah; Taylor, Darrin; Waddell, Nick; Wood, Scott; Xu, Qinying; Wu, Jianmin; Pinese, Mark; Cowley, Mark J.; Lee, Hong C.; Jones, Marc D.; Nagrial, Adnan M.; Humphris, Jeremy; Chantrill, Lorraine A.; Chin, Venessa; Steinmann, Angela M.; Mawson, Amanda; Humphrey, Emily S.; Colvin, Emily K.; Chou, Angela; Scarlett, Christopher J.; Pinho, Andreia V.; Giry-Laterriere, Marc; Rooman, Ilse; Samra, Jaswinder S.; Kench, James G.; Pettitt, Jessica A.; Merrett, Neil D.; Toon, Christopher; Epari, Krishna; Nguyen, Nam Q.; Barbour, Andrew; Zeps, Nikolajs; Jamieson, Nigel B.; Graham, Janet S.; Niclou, Simone P.; Bjerkvig, Rolf; Grützmann, Robert; Aust, Daniela; Hruban, Ralph H.; Maitra, Anirban; Iacobuzio-Donahue, Christine A.; Wolfgang, Christopher L.; Morgan, Richard A.; Lawlor, Rita T.; Corbo, Vincenzo; Bassi, Claudio; Falconi, Massimo; Zamboni, Giuseppe; Tortora, Giampaolo; Tempero, Margaret A.; Gill, Anthony J.; Eshleman, James R.; Pilarsky, Christian; Scarpa, Aldo; Musgrove, Elizabeth A.; Pearson, John V.; Biankin, Andrew V.; Grimmond, Sean M.

2015-01-01

Pancreatic cancer remains one of the most lethal of malignancies and a major health burden. We performed whole-genome sequencing and copy number variation (CNV) analysis of 100 pancreatic ductal adenocarcinomas (PDACs). Chromosomal rearrangements leading to gene disruption were prevalent, affecting genes known to be important in pancreatic cancer (TP53, SMAD4, CDKN2A, ARID1A and ROBO2) and new candidate drivers of pancreatic carcinogenesis (KDM6A and PREX2). Patterns of structural variation (variation in chromosomal structure) classified PDACs into 4 subtypes with potential clinical utility: the subtypes were termed stable, locally rearranged, scattered and unstable. A significant proportion harboured focal amplifications, many of which contained druggable oncogenes (ERBB2, MET, FGFR1, CDK6, PIK3R3 and PIK3CA), but at low individual patient prevalence. Genomic instability co-segregated with inactivation of DNA maintenance genes (BRCA1, BRCA2 or PALB2) and a mutational signature of DNA damage repair deficiency. Of 8 patients who received platinum therapy, 4 of 5 individuals with these measures of defective DNA maintenance responded. PMID:25719666
Precision medicine for advanced prostate cancer.

Science.gov (United States)

Mullane, Stephanie A; Van Allen, Eliezer M

2016-05-01

Precision cancer medicine, the use of genomic profiling of patient tumors at the point-of-care to inform treatment decisions, is rapidly changing treatment strategies across cancer types. Precision medicine for advanced prostate cancer may identify new treatment strategies and change clinical practice. In this review, we discuss the potential and challenges of precision medicine in advanced prostate cancer. Although primary prostate cancers do not harbor highly recurrent targetable genomic alterations, recent reports on the genomics of metastatic castration-resistant prostate cancer has shown multiple targetable alterations in castration-resistant prostate cancer metastatic biopsies. Therapeutic implications include targeting prevalent DNA repair pathway alterations with PARP-1 inhibition in genomically defined subsets of patients, among other genomically stratified targets. In addition, multiple recent efforts have demonstrated the promise of liquid tumor profiling (e.g., profiling circulating tumor cells or cell-free tumor DNA) and highlighted the necessary steps to scale these approaches in prostate cancer. Although still in the initial phase of precision medicine for prostate cancer, there is extraordinary potential for clinical impact. Efforts to overcome current scientific and clinical barriers will enable widespread use of precision medicine approaches for advanced prostate cancer patients.
Characterizing associations and SNP-environment interactions for GWAS-identified prostate cancer risk markers--results from BPC3.

Directory of Open Access Journals (Sweden)

Sara Lindstrom

2011-02-01

Full Text Available Genome-wide association studies (GWAS have identified multiple single nucleotide polymorphisms (SNPs associated with prostate cancer risk. However, whether these associations can be consistently replicated, vary with disease aggressiveness (tumor stage and grade and/or interact with non-genetic potential risk factors or other SNPs is unknown. We therefore genotyped 39 SNPs from regions identified by several prostate cancer GWAS in 10,501 prostate cancer cases and 10,831 controls from the NCI Breast and Prostate Cancer Cohort Consortium (BPC3. We replicated 36 out of 39 SNPs (P-values ranging from 0.01 to 10⁻²⁸. Two SNPs located near KLK3 associated with PSA levels showed differential association with Gleason grade (rs2735839, P = 0.0001 and rs266849, P = 0.0004; case-only test, where the alleles associated with decreasing PSA levels were inversely associated with low-grade (as defined by Gleason grade < 8 tumors but positively associated with high-grade tumors. No other SNP showed differential associations according to disease stage or grade. We observed no effect modification by SNP for association with age at diagnosis, family history of prostate cancer, diabetes, BMI, height, smoking or alcohol intake. Moreover, we found no evidence of pair-wise SNP-SNP interactions. While these SNPs represent new independent risk factors for prostate cancer, we saw little evidence for effect modification by other SNPs or by the environmental factors examined.
Transcription Restores DNA Repair to Heterochromatin, Determining Regional Mutation Rates in Cancer Genomes

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Christina L. Zheng

2014-11-01

Full Text Available Somatic mutations in cancer are more frequent in heterochromatic and late-replicating regions of the genome. We report that regional disparities in mutation density are virtually abolished within transcriptionally silent genomic regions of cutaneous squamous cell carcinomas (cSCCs arising in an XPC−/− background. XPC−/− cells lack global genome nucleotide excision repair (GG-NER, thus establishing differential access of DNA repair machinery within chromatin-rich regions of the genome as the primary cause for the regional disparity. Strikingly, we find that increasing levels of transcription reduce mutation prevalence on both strands of gene bodies embedded within H3K9me3-dense regions, and only to those levels observed in H3K9me3-sparse regions, also in an XPC-dependent manner. Therefore, transcription appears to reduce mutation prevalence specifically by relieving the constraints imposed by chromatin structure on DNA repair. We model this relationship among transcription, chromatin state, and DNA repair, revealing a new, personalized determinant of cancer risk.
“A rising tide lifts all boats”: establishing a multidisciplinary genomic tumor board for breast cancer patients with advanced disease

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Michelle L. McGowan

2016-11-01

Full Text Available Abstract Background Research suggests that multidisciplinary genomic tumor boards (MGTB can inform cancer patient care, though little is known about factors influencing how MGTBs interpret genomic test results, make recommendations, and perceive the utility of this approach. This study’s objective was to observe, describe, and assess the establishment of the Breast Multidisciplinary Genomic Tumor Board, the first MGTB focused on interpreting genomic test results for breast cancer patients with advanced disease. Methods We conducted a qualitative case study involving participant observation at monthly MGTB meetings from October 2013 through November 2014 and interviews with 12 MGTB members. We analyzed social dynamics and interactions within the MGTB regarding interpretation of genomic findings and participants’ views on effectiveness of the MGTB in using genomics to inform patient care. Results Twenty-two physicians, physician-scientists, basic scientists, bioethicists, and allied care professionals comprised the MGTB. The MGTB reviewed FoundationOne™ results for 40 metastatic breast cancer patients. Based on findings, the board mostly recommended referring patients to clinical trials (34 and medical genetics (15, and Food and Drug Administration-approved (FDA breast cancer therapies (13. Though multidisciplinary, recommendations were driven by medical oncologists. Interviewees described providing more precise care recommendations and professional development as advantages and the limited actionability of genomic test results as a challenge for the MGTB. Conclusions Findings suggest both feasibility and desirability of pooling professional expertise in genomically-guided breast cancer care and challenges to institutionalizing a Breast MGTB, specifically in promoting interdisciplinary contributions and managing limited actionability of genomic test results for patients with advanced disease.
Pan-Cancer Analysis of the Mediator Complex Transcriptome Identifies CDK19 and CDK8 as Therapeutic Targets in Advanced Prostate Cancer.

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Brägelmann, Johannes; Klümper, Niklas; Offermann, Anne; von Mässenhausen, Anne; Böhm, Diana; Deng, Mario; Queisser, Angela; Sanders, Christine; Syring, Isabella; Merseburger, Axel S; Vogel, Wenzel; Sievers, Elisabeth; Vlasic, Ignacija; Carlsson, Jessica; Andrén, Ove; Brossart, Peter; Duensing, Stefan; Svensson, Maria A; Shaikhibrahim, Zaki; Kirfel, Jutta; Perner, Sven

2017-04-01

Purpose: The Mediator complex is a multiprotein assembly, which serves as a hub for diverse signaling pathways to regulate gene expression. Because gene expression is frequently altered in cancer, a systematic understanding of the Mediator complex in malignancies could foster the development of novel targeted therapeutic approaches. Experimental Design: We performed a systematic deconvolution of the Mediator subunit expression profiles across 23 cancer entities ( n = 8,568) using data from The Cancer Genome Atlas (TCGA). Prostate cancer-specific findings were validated in two publicly available gene expression cohorts and a large cohort of primary and advanced prostate cancer ( n = 622) stained by immunohistochemistry. The role of CDK19 and CDK8 was evaluated by siRNA-mediated gene knockdown and inhibitor treatment in prostate cancer cell lines with functional assays and gene expression analysis by RNAseq. Results: Cluster analysis of TCGA expression data segregated tumor entities, indicating tumor-type-specific Mediator complex compositions. Only prostate cancer was marked by high expression of CDK19 In primary prostate cancer, CDK19 was associated with increased aggressiveness and shorter disease-free survival. During cancer progression, highest levels of CDK19 and of its paralog CDK8 were present in metastases. In vitro , inhibition of CDK19 and CDK8 by knockdown or treatment with a selective CDK8/CDK19 inhibitor significantly decreased migration and invasion. Conclusions: Our analysis revealed distinct transcriptional expression profiles of the Mediator complex across cancer entities indicating differential modes of transcriptional regulation. Moreover, it identified CDK19 and CDK8 to be specifically overexpressed during prostate cancer progression, highlighting their potential as novel therapeutic targets in advanced prostate cancer. Clin Cancer Res; 23(7); 1829-40. ©2016 AACR . ©2016 American Association for Cancer Research.
Genome-wide association study with 1000 genomes imputation identifies signals for nine sex hormone-related phenotypes.

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Ruth, Katherine S; Campbell, Purdey J; Chew, Shelby; Lim, Ee Mun; Hadlow, Narelle; Stuckey, Bronwyn G A; Brown, Suzanne J; Feenstra, Bjarke; Joseph, John; Surdulescu, Gabriela L; Zheng, Hou Feng; Richards, J Brent; Murray, Anna; Spector, Tim D; Wilson, Scott G; Perry, John R B

2016-02-01

Genetic factors contribute strongly to sex hormone levels, yet knowledge of the regulatory mechanisms remains incomplete. Genome-wide association studies (GWAS) have identified only a small number of loci associated with sex hormone levels, with several reproductive hormones yet to be assessed. The aim of the study was to identify novel genetic variants contributing to the regulation of sex hormones. We performed GWAS using genotypes imputed from the 1000 Genomes reference panel. The study used genotype and phenotype data from a UK twin register. We included 2913 individuals (up to 294 males) from the Twins UK study, excluding individuals receiving hormone treatment. Phenotypes were standardised for age, sex, BMI, stage of menstrual cycle and menopausal status. We tested 7,879,351 autosomal SNPs for association with levels of dehydroepiandrosterone sulphate (DHEAS), oestradiol, free androgen index (FAI), follicle-stimulating hormone (FSH), luteinizing hormone (LH), prolactin, progesterone, sex hormone-binding globulin and testosterone. Eight independent genetic variants reached genome-wide significance (P<5 × 10(-8)), with minor allele frequencies of 1.3-23.9%. Novel signals included variants for progesterone (P=7.68 × 10(-12)), oestradiol (P=1.63 × 10(-8)) and FAI (P=1.50 × 10(-8)). A genetic variant near the FSHB gene was identified which influenced both FSH (P=1.74 × 10(-8)) and LH (P=3.94 × 10(-9)) levels. A separate locus on chromosome 7 was associated with both DHEAS (P=1.82 × 10(-14)) and progesterone (P=6.09 × 10(-14)). This study highlights loci that are relevant to reproductive function and suggests overlap in the genetic basis of hormone regulation.
kmer-SVM: a web server for identifying predictive regulatory sequence features in genomic data sets

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Fletez-Brant, Christopher; Lee, Dongwon; McCallion, Andrew S.; Beer, Michael A.

2013-01-01

Massively parallel sequencing technologies have made the generation of genomic data sets a routine component of many biological investigations. For example, Chromatin immunoprecipitation followed by sequence assays detect genomic regions bound (directly or indirectly) by specific factors, and DNase-seq identifies regions of open chromatin. A major bottleneck in the interpretation of these data is the identification of the underlying DNA sequence code that defines, and ultimately facilitates prediction of, these transcription factor (TF) bound or open chromatin regions. We have recently developed a novel computational methodology, which uses a support vector machine (SVM) with kmer sequence features (kmer-SVM) to identify predictive combinations of short transcription factor-binding sites, which determine the tissue specificity of these genomic assays (Lee, Karchin and Beer, Discriminative prediction of mammalian enhancers from DNA sequence. Genome Res. 2011; 21:2167–80). This regulatory information can (i) give confidence in genomic experiments by recovering previously known binding sites, and (ii) reveal novel sequence features for subsequent experimental testing of cooperative mechanisms. Here, we describe the development and implementation of a web server to allow the broader research community to independently apply our kmer-SVM to analyze and interpret their genomic datasets. We analyze five recently published data sets and demonstrate how this tool identifies accessory factors and repressive sequence elements. kmer-SVM is available at http://kmersvm.beerlab.org. PMID:23771147
The Candidate Cancer Gene Database: a database of cancer driver genes from forward genetic screens in mice.

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Abbott, Kenneth L; Nyre, Erik T; Abrahante, Juan; Ho, Yen-Yi; Isaksson Vogel, Rachel; Starr, Timothy K

2015-01-01

Identification of cancer driver gene mutations is crucial for advancing cancer therapeutics. Due to the overwhelming number of passenger mutations in the human tumor genome, it is difficult to pinpoint causative driver genes. Using transposon mutagenesis in mice many laboratories have conducted forward genetic screens and identified thousands of candidate driver genes that are highly relevant to human cancer. Unfortunately, this information is difficult to access and utilize because it is scattered across multiple publications using different mouse genome builds and strength metrics. To improve access to these findings and facilitate meta-analyses, we developed the Candidate Cancer Gene Database (CCGD, http://ccgd-starrlab.oit.umn.edu/). The CCGD is a manually curated database containing a unified description of all identified candidate driver genes and the genomic location of transposon common insertion sites (CISs) from all currently published transposon-based screens. To demonstrate relevance to human cancer, we performed a modified gene set enrichment analysis using KEGG pathways and show that human cancer pathways are highly enriched in the database. We also used hierarchical clustering to identify pathways enriched in blood cancers compared to solid cancers. The CCGD is a novel resource available to scientists interested in the identification of genetic drivers of cancer. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.
FISH Oracle 2: a web server for integrative visualization of genomic data in cancer research.

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Mader, Malte; Simon, Ronald; Kurtz, Stefan

2014-03-31

A comprehensive view on all relevant genomic data is instrumental for understanding the complex patterns of molecular alterations typically found in cancer cells. One of the most effective ways to rapidly obtain an overview of genomic alterations in large amounts of genomic data is the integrative visualization of genomic events. We developed FISH Oracle 2, a web server for the interactive visualization of different kinds of downstream processed genomics data typically available in cancer research. A powerful search interface and a fast visualization engine provide a highly interactive visualization for such data. High quality image export enables the life scientist to easily communicate their results. A comprehensive data administration allows to keep track of the available data sets. We applied FISH Oracle 2 to published data and found evidence that, in colorectal cancer cells, the gene TTC28 may be inactivated in two different ways, a fact that has not been published before. The interactive nature of FISH Oracle 2 and the possibility to store, select and visualize large amounts of downstream processed data support life scientists in generating hypotheses. The export of high quality images supports explanatory data visualization, simplifying the communication of new biological findings. A FISH Oracle 2 demo server and the software is available at http://www.zbh.uni-hamburg.de/fishoracle.
The FUN of identifying gene function in bacterial pathogens; insights from Salmonella functional genomics.

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Hammarlöf, Disa L; Canals, Rocío; Hinton, Jay C D

2013-10-01

The availability of thousands of genome sequences of bacterial pathogens poses a particular challenge because each genome contains hundreds of genes of unknown function (FUN). How can we easily discover which FUN genes encode important virulence factors? One solution is to combine two different functional genomic approaches. First, transcriptomics identifies bacterial FUN genes that show differential expression during the process of mammalian infection. Second, global mutagenesis identifies individual FUN genes that the pathogen requires to cause disease. The intersection of these datasets can reveal a small set of candidate genes most likely to encode novel virulence attributes. We demonstrate this approach with the Salmonella infection model, and propose that a similar strategy could be used for other bacterial pathogens. Copyright © 2013 Elsevier Ltd. All rights reserved.
Genome-Wide Association Study Identifies Four Loci Associated with Eruption of Permanent Teeth

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Zhang, Hao; Shaffer, John R.; Hansen, Thomas; Esserlind, Ann-Louise; Boyd, Heather A.; Nohr, Ellen A.; Timpson, Nicholas J.; Fatemifar, Ghazaleh; Paternoster, Lavinia; Evans, David M.; Weyant, Robert J.; Levy, Steven M.; Lathrop, Mark; Smith, George Davey; Murray, Jeffrey C.; Olesen, Jes; Werge, Thomas; Marazita, Mary L.; Sørensen, Thorkild I. A.; Melbye, Mads

2011-01-01

The sequence and timing of permanent tooth eruption is thought to be highly heritable and can have important implications for the risk of malocclusion, crowding, and periodontal disease. We conducted a genome-wide association study of number of permanent teeth erupted between age 6 and 14 years, analyzed as age-adjusted standard deviation score averaged over multiple time points, based on childhood records for 5,104 women from the Danish National Birth Cohort. Four loci showed association at Peruption and were also known to influence height and breast cancer, respectively. The two other loci pointed to genomic regions without any previous significant genome-wide association study results. The intronic SNP rs7924176 in ADK could be linked to gene expression in monocytes. The combined effect of the four genetic variants was most pronounced between age 10 and 12 years, where children with 6 to 8 delayed tooth eruption alleles had on average 3.5 (95% confidence interval: 2.9–4.1) fewer permanent teeth than children with 0 or 1 of these alleles. PMID:21931568
Use of Whole Genome Sequencing for Diagnosis and Discovery in the Cancer Genetics Clinic

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Samantha B. Foley

2015-01-01

Full Text Available Despite the potential of whole-genome sequencing (WGS to improve patient diagnosis and care, the empirical value of WGS in the cancer genetics clinic is unknown. We performed WGS on members of two cohorts of cancer genetics patients: those with BRCA1/2 mutations (n = 176 and those without (n = 82. Initial analysis of potentially pathogenic variants (PPVs, defined as nonsynonymous variants with allele frequency < 1% in ESP6500 in 163 clinically-relevant genes suggested that WGS will provide useful clinical results. This is despite the fact that a majority of PPVs were novel missense variants likely to be classified as variants of unknown significance (VUS. Furthermore, previously reported pathogenic missense variants did not always associate with their predicted diseases in our patients. This suggests that the clinical use of WGS will require large-scale efforts to consolidate WGS and patient data to improve accuracy of interpretation of rare variants. While loss-of-function (LoF variants represented only a small fraction of PPVs, WGS identified additional cancer risk LoF PPVs in patients with known BRCA1/2 mutations and led to cancer risk diagnoses in 21% of non-BRCA cancer genetics patients after expanding our analysis to 3209 ClinVar genes. These data illustrate how WGS can be used to improve our ability to discover patients' cancer genetic risks.
The Art and Science of Thyroid Surgery in the Age of Genomics: 100 years after Theodor Kocher

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Seza Gulec

2017-02-01

Full Text Available Cancer is a disorder of the genome. The thyroid cancer genome is being decoded. Recent studies have identified a mutation or a genetic alteration in 95% of thyroid cancers. The National Cancer Institute initiated the Cancer Genome Atlas project in 2006 to catalogue genetic mutations associated with cancer, using genome sequencing and bioinformatics. The project has expanded to carry out genomic characterization and sequence analysis of thyroid cancer. The concept of risk stratification based on traditional parameters will soon vacate their role for clear molecular markers of non-invasive/focal, invasive/metastatic and systemic stages/phases of neoplastic disorder. A refined classification scheme based on genomics and its phenotypic expressions will accurately reflect the biologic differences between the different morphologic definitions we use today. Tumor differentiation/de-differentiation, and clinical behavior of an individual cancer will be defined by molecular markers, in addition to standard morpho-pathology. Empiricism in science of medicine and surgery has acquired a new method for testing the appropriate treatment for individual patients; that is molecular pathology, governed by genomics. The technology is present and rapidly evolving. The surgeons will determine the extent of interventions with molecular evidence and guidance.
Genetic profiles distinguish different types of hereditary ovarian cancer

DEFF Research Database (Denmark)

Domanska, Katarina; Malander, Susanne; Staaf, Johan

2010-01-01

(HBOC) syndrome and the hereditary non-polyposis colorectal cancer (HNPCC) syndrome. Genome-wide array comparative genomic hybridization was applied to 12 HBOC associated tumors with BRCA1 mutations and 8 HNPCC associated tumors with mismatch repair gene mutations with 24 sporadic ovarian cancers......Heredity represents the strongest risk factor for ovarian cancer with disease predisposing mutations identified in 15% of the tumors. With the aim to identify genetic classifiers for hereditary ovarian cancer, we profiled hereditary ovarian cancers linked to the hereditary breast and ovarian cancer...... that HBOC and HNPCC associated ovarian cancer develop along distinct genetic pathways and genetic profiles can thus be applied to distinguish between different types of hereditary ovarian cancer....

Targeted sequencing identifies genetic alterations that confer primary resistance to EGFR tyrosine kinase inhibitor (Korean Lung Cancer Consortium).

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Lim, Sun Min; Kim, Hye Ryun; Cho, Eun Kyung; Min, Young Joo; Ahn, Jin Seok; Ahn, Myung-Ju; Park, Keunchil; Cho, Byoung Chul; Lee, Ji-Hyun; Jeong, Hye Cheol; Kim, Eun Kyung; Kim, Joo-Hang

2016-06-14

Non-small-cell lung cancer (NSCLC) patients with activating epidermal growth factor receptor (EGFR) mutations may exhibit primary resistance to EGFR tyrosine kinase inhibitor (TKI). We aimed to examine genomic alterations associated with de novo resistance to gefitinib in a prospective study of NSCLC patients. One-hundred and fifty two patients with activating EGFR mutations were included in this study and 136 patients' tumor sample were available for targeted sequencing of genomic alterations in 22 genes using the Colon and Lung Cancer panel (Ampliseq, Life Technologies). All 132 patients with EGFR mutation were treated with gefitinib for their treatment of advanced NSCLC. Twenty patients showed primary resistance to EGFR TKI, and were classified as non-responders. A total of 543 somatic single-nucleotide variants (498 missense, 13 nonsense) and 32 frameshift insertions/deletions, with a median of 3 mutations per sample. TP53 was most commonly mutated (47%) and mutations in SMAD4 was also common (19%), as well as DDR2 (16%), PIK3CA (15%), STK11 (14%), and BRAF (7%). Genomic mutations in the PI3K/Akt/mTOR pathway were commonly found in non-responders (45%) compared to responders (27%), and they had significantly shorter progression-free survival and overall survival compared to patients without mutations (2.1 vs. 12.8 months, P=0.04, 15.7 vs. not reached, PAkt/mTOR pathway were commonly identified in non-responders and may confer resistance to EGFR TKI. Screening lung adenocarcinoma patients with clinical cancer gene test may aid in selecting out those who show primary resistance to EGFR TKI (NCT01697163).
Next-generation Sequencing-based genomic profiling: Fostering innovation in cancer care?

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Gustavo S. Fernandes

Full Text Available OBJECTIVES: With the development of next-generation sequencing (NGS technologies, DNA sequencing has been increasingly utilized in clinical practice. Our goal was to investigate the impact of genomic evaluation on treatment decisions for heavily pretreated patients with metastatic cancer. METHODS: We analyzed metastatic cancer patients from a single institution whose cancers had progressed after all available standard-of-care therapies and whose tumors underwent next-generation sequencing analysis. We determined the percentage of patients who received any therapy directed by the test, and its efficacy. RESULTS: From July 2013 to December 2015, 185 consecutive patients were tested using a commercially available next-generation sequencing-based test, and 157 patients were eligible. Sixty-six patients (42.0% were female, and 91 (58.0% were male. The mean age at diagnosis was 52.2 years, and the mean number of pre-test lines of systemic treatment was 2.7. One hundred and seventy-seven patients (95.6% had at least one identified gene alteration. Twenty-four patients (15.2% underwent systemic treatment directed by the test result. Of these, one patient had a complete response, four (16.7% had partial responses, two (8.3% had stable disease, and 17 (70.8% had disease progression as the best result. The median progression-free survival time with matched therapy was 1.6 months, and the median overall survival was 10 months. CONCLUSION: We identified a high prevalence of gene alterations using an next-generation sequencing test. Although some benefit was associated with the matched therapy, most of the patients had disease progression as the best response, indicating the limited biological potential and unclear clinical relevance of this practice.
A survey of single nucleotide polymorphisms identified from whole-genome sequencing and their functional effect in the porcine genome.

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Keel, B N; Nonneman, D J; Rohrer, G A

2017-08-01

Genetic variants detected from sequence have been used to successfully identify causal variants and map complex traits in several organisms. High and moderate impact variants, those expected to alter or disrupt the protein coded by a gene and those that regulate protein production, likely have a more significant effect on phenotypic variation than do other types of genetic variants. Hence, a comprehensive list of these functional variants would be of considerable interest in swine genomic studies, particularly those targeting fertility and production traits. Whole-genome sequence was obtained from 72 of the founders of an intensely phenotyped experimental swine herd at the U.S. Meat Animal Research Center (USMARC). These animals included all 24 of the founding boars (12 Duroc and 12 Landrace) and 48 Yorkshire-Landrace composite sows. Sequence reads were mapped to the Sscrofa10.2 genome build, resulting in a mean of 6.1 fold (×) coverage per genome. A total of 22 342 915 high confidence SNPs were identified from the sequenced genomes. These included 21 million previously reported SNPs and 79% of the 62 163 SNPs on the PorcineSNP60 BeadChip assay. Variation was detected in the coding sequence or untranslated regions (UTRs) of 87.8% of the genes in the porcine genome: loss-of-function variants were predicted in 504 genes, 10 202 genes contained nonsynonymous variants, 10 773 had variation in UTRs and 13 010 genes contained synonymous variants. Approximately 139 000 SNPs were classified as loss-of-function, nonsynonymous or regulatory, which suggests that over 99% of the variation detected in our pigs could potentially be ignored, allowing us to focus on a much smaller number of functional SNPs during future analyses. Published 2017. This article is a U.S. Government work and is in the public domain in the USA.
Fine-Scale Mapping at 9p22.2 Identifies Candidate Causal Variants That Modify Ovarian Cancer Risk in BRCA1 and BRCA2 Mutation Carriers

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Vigorito, Elena; Kuchenbaecker, Karoline B; Beesley, Jonathan

2016-01-01

Population-based genome wide association studies have identified a locus at 9p22.2 associated with ovarian cancer risk, which also modifies ovarian cancer risk in BRCA1 and BRCA2 mutation carriers. We conducted fine-scale mapping at 9p22.2 to identify potential causal variants in BRCA1 and BRCA2...... mutation carriers. Genotype data were available for 15,252 (2,462 ovarian cancer cases) BRCA1 and 8,211 (631 ovarian cancer cases) BRCA2 mutation carriers. Following genotype imputation, ovarian cancer associations were assessed for 4,873 and 5,020 SNPs in BRCA1 and BRCA 2 mutation carriers respectively...... of BNC2. In BRCA2 mutation carriers one region, up to 45 kb upstream of BNC2, and containing 100 correlated SNPs was identified as candidate causal (top SNP rs62543585, HR: 0.69, 95%CI: 0.59 to 0.80, p-value 1.0 × 10-6). The candidate causal in BRCA1 mutation carriers did not include the strongest...
Overexpression screens identify conserved dosage chromosome instability genes in yeast and human cancer

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Duffy, Supipi; Fam, Hok Khim; Wang, Yi Kan; Styles, Erin B.; Kim, Jung-Hyun; Ang, J. Sidney; Singh, Tejomayee; Larionov, Vladimir; Shah, Sohrab P.; Andrews, Brenda; Boerkoel, Cornelius F.; Hieter, Philip

2016-01-01

Somatic copy number amplification and gene overexpression are common features of many cancers. To determine the role of gene overexpression on chromosome instability (CIN), we performed genome-wide screens in the budding yeast for yeast genes that cause CIN when overexpressed, a phenotype we refer to as dosage CIN (dCIN), and identified 245 dCIN genes. This catalog of genes reveals human orthologs known to be recurrently overexpressed and/or amplified in tumors. We show that two genes, TDP1, a tyrosyl-DNA-phosphdiesterase, and TAF12, an RNA polymerase II TATA-box binding factor, cause CIN when overexpressed in human cells. Rhabdomyosarcoma lines with elevated human Tdp1 levels also exhibit CIN that can be partially rescued by siRNA-mediated knockdown of TDP1. Overexpression of dCIN genes represents a genetic vulnerability that could be leveraged for selective killing of cancer cells through targeting of an unlinked synthetic dosage lethal (SDL) partner. Using SDL screens in yeast, we identified a set of genes that when deleted specifically kill cells with high levels of Tdp1. One gene was the histone deacetylase RPD3, for which there are known inhibitors. Both HT1080 cells overexpressing hTDP1 and rhabdomyosarcoma cells with elevated levels of hTdp1 were more sensitive to histone deacetylase inhibitors valproic acid (VPA) and trichostatin A (TSA), recapitulating the SDL interaction in human cells and suggesting VPA and TSA as potential therapeutic agents for tumors with elevated levels of hTdp1. The catalog of dCIN genes presented here provides a candidate list to identify genes that cause CIN when overexpressed in cancer, which can then be leveraged through SDL to selectively target tumors. PMID:27551064
Cancer in silico drug discovery: a systems biology tool for identifying candidate drugs to target specific molecular tumor subtypes.

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San Lucas, F Anthony; Fowler, Jerry; Chang, Kyle; Kopetz, Scott; Vilar, Eduardo; Scheet, Paul

2014-12-01

Large-scale cancer datasets such as The Cancer Genome Atlas (TCGA) allow researchers to profile tumors based on a wide range of clinical and molecular characteristics. Subsequently, TCGA-derived gene expression profiles can be analyzed with the Connectivity Map (CMap) to find candidate drugs to target tumors with specific clinical phenotypes or molecular characteristics. This represents a powerful computational approach for candidate drug identification, but due to the complexity of TCGA and technology differences between CMap and TCGA experiments, such analyses are challenging to conduct and reproduce. We present Cancer in silico Drug Discovery (CiDD; scheet.org/software), a computational drug discovery platform that addresses these challenges. CiDD integrates data from TCGA, CMap, and Cancer Cell Line Encyclopedia (CCLE) to perform computational drug discovery experiments, generating hypotheses for the following three general problems: (i) determining whether specific clinical phenotypes or molecular characteristics are associated with unique gene expression signatures; (ii) finding candidate drugs to repress these expression signatures; and (iii) identifying cell lines that resemble the tumors being studied for subsequent in vitro experiments. The primary input to CiDD is a clinical or molecular characteristic. The output is a biologically annotated list of candidate drugs and a list of cell lines for in vitro experimentation. We applied CiDD to identify candidate drugs to treat colorectal cancers harboring mutations in BRAF. CiDD identified EGFR and proteasome inhibitors, while proposing five cell lines for in vitro testing. CiDD facilitates phenotype-driven, systematic drug discovery based on clinical and molecular data from TCGA. ©2014 American Association for Cancer Research.
Three new pancreatic cancer susceptibility signals identified on chromosomes 1q32.1, 5p15.33 and 8q24.21

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Zhang, Mingfeng; Wang, Zhaoming; Obazee, Ofure; Jia, Jinping; Childs, Erica J.; Hoskins, Jason; Figlioli, Gisella; Mocci, Evelina; Collins, Irene; Chung, Charles C.; Hautman, Christopher; Arslan, Alan A.; Beane-Freeman, Laura; Bracci, Paige M.; Buring, Julie; Duell, Eric J.; Gallinger, Steven; Giles, Graham G.; Goodman, Gary E.; Goodman, Phyllis J.; Kamineni, Aruna; Kolonel, Laurence N.; Kulke, Matthew H.; Malats, Núria; Olson, Sara H.; Sesso, Howard D.; Visvanathan, Kala; White, Emily; Zheng, Wei; Abnet, Christian C.; Albanes, Demetrius; Andreotti, Gabriella; Brais, Lauren; Bueno-de-Mesquita, H. Bas; Basso, Daniela; Berndt, Sonja I.; Boutron-Ruault, Marie-Christine; Bijlsma, Maarten F.; Brenner, Hermann; Burdette, Laurie; Campa, Daniele; Caporaso, Neil E.; Capurso, Gabriele; Cavestro, Giulia Martina; Cotterchio, Michelle; Costello, Eithne; Elena, Joanne; Boggi, Ugo; Gaziano, J. Michael; Gazouli, Maria; Giovannucci, Edward L.; Goggins, Michael; Gross, Myron; Haiman, Christopher A.; Hassan, Manal; Helzlsouer, Kathy J.; Hu, Nan; Hunter, David J.; Iskierka-Jazdzewska, Elzbieta; Jenab, Mazda; Kaaks, Rudolf; Key, Timothy J.; Khaw, Kay-Tee; Klein, Eric A.; Kogevinas, Manolis; Krogh, Vittorio; Kupcinskas, Juozas; Kurtz, Robert C.; Landi, Maria T.; Landi, Stefano; Marchand, Le Loic; Mambrini, Andrea; Mannisto, Satu; Milne, Roger L.; Neale, Rachel E.; Oberg, Ann L.; Panico, Salvatore; Patel, Alpa V.; Peeters, Petra H. M.; Peters, Ulrike; Pezzilli, Raffaele; Porta, Miquel; Purdue, Mark; Quiros, J. Ramón; Riboli, Elio; Rothman, Nathaniel; Scarpa, Aldo; Scelo, Ghislaine; Shu, Xiao-Ou; Silverman, Debra T.; Soucek, Pavel; Strobel, Oliver; Sund, Malin; Małecka-Panas, Ewa; Taylor, Philip R.; Tavano, Francesca; Travis, Ruth C.; Thornquist, Mark; Tjønneland, Anne; Tobias, Geoffrey S.; Trichopoulos, Dimitrios; Vashist, Yogesh; Vodicka, Pavel; Wactawski-Wende, Jean; Wentzensen, Nicolas; Yu, Herbert; Yu, Kai; Zeleniuch-Jacquotte, Anne; Kooperberg, Charles; Risch, Harvey A.; Jacobs, Eric J.; Li, Donghui; Fuchs, Charles; Hoover, Robert; Hartge, Patricia; Chanock, Stephen J.; Petersen, Gloria M.; Stolzenberg-Solomon, Rachael S.; Wolpin, Brian M.; Kraft, Peter; Klein, Alison P.; Canzian, Federico; Amundadottir, Laufey T.

2016-01-01

Genome-wide association studies (GWAS) have identified common pancreatic cancer susceptibility variants at 13 chromosomal loci in individuals of European descent. To identify new susceptibility variants, we performed imputation based on 1000 Genomes (1000G) Project data and association analysis using 5,107 case and 8,845 control subjects from 27 cohort and case-control studies that participated in the PanScan I-III GWAS. This analysis, in combination with a two-staged replication in an additional 6,076 case and 7,555 control subjects from the PANcreatic Disease ReseArch (PANDoRA) and Pancreatic Cancer Case-Control (PanC4) Consortia uncovered 3 new pancreatic cancer risk signals marked by single nucleotide polymorphisms (SNPs) rs2816938 at chromosome 1q32.1 (per allele odds ratio (OR) = 1.20, P = 4.88×10−15), rs10094872 at 8q24.21 (OR = 1.15, P = 3.22×10−9) and rs35226131 at 5p15.33 (OR = 0.71, P = 1.70×10−8). These SNPs represent independent risk variants at previously identified pancreatic cancer risk loci on chr1q32.1 (NR5A2), chr8q24.21 (MYC) and chr5p15.33 (CLPTM1L-TERT) as per analyses conditioned on previously reported susceptibility variants. We assessed expression of candidate genes at the three risk loci in histologically normal (n = 10) and tumor (n = 8) derived pancreatic tissue samples and observed a marked reduction of NR5A2 expression (chr1q32.1) in the tumors (fold change -7.6, P = 5.7×10−8). This finding was validated in a second set of paired (n = 20) histologically normal and tumor derived pancreatic tissue samples (average fold change for three NR5A2 isoforms -31.3 to -95.7, P = 7.5×10−4-2.0×10−3). Our study has identified new susceptibility variants independently conferring pancreatic cancer risk that merit functional follow-up to identify target genes and explain the underlying biology. PMID:27579533
Prostate cancer risk locus at 8q24 as a regulatory hub by physical interactions with multiple genomic loci across the genome.

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Du, Meijun; Yuan, Tiezheng; Schilter, Kala F; Dittmar, Rachel L; Mackinnon, Alexander; Huang, Xiaoyi; Tschannen, Michael; Worthey, Elizabeth; Jacob, Howard; Xia, Shu; Gao, Jianzhong; Tillmans, Lori; Lu, Yan; Liu, Pengyuan; Thibodeau, Stephen N; Wang, Liang

2015-01-01

Chromosome 8q24 locus contains regulatory variants that modulate genetic risk to various cancers including prostate cancer (PC). However, the biological mechanism underlying this regulation is not well understood. Here, we developed a chromosome conformation capture (3C)-based multi-target sequencing technology and systematically examined three PC risk regions at the 8q24 locus and their potential regulatory targets across human genome in six cell lines. We observed frequent physical contacts of this risk locus with multiple genomic regions, in particular, inter-chromosomal interaction with CD96 at 3q13 and intra-chromosomal interaction with MYC at 8q24. We identified at least five interaction hot spots within the predicted functional regulatory elements at the 8q24 risk locus. We also found intra-chromosomal interaction genes PVT1, FAM84B and GSDMC and inter-chromosomal interaction gene CXorf36 in most of the six cell lines. Other gene regions appeared to be cell line-specific, such as RRP12 in LNCaP, USP14 in DU-145 and SMIN3 in lymphoblastoid cell line. We further found that the 8q24 functional domains more likely interacted with genomic regions containing genes enriched in critical pathways such as Wnt signaling and promoter motifs such as E2F1 and TCF3. This result suggests that the risk locus may function as a regulatory hub by physical interactions with multiple genes important for prostate carcinogenesis. Further understanding genetic effect and biological mechanism of these chromatin interactions will shed light on the newly discovered regulatory role of the risk locus in PC etiology and progression. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.
Genome-Wide Search Identifies 1.9 Mb from the Polar Bear Y Chromosome for Evolutionary Analyses

Science.gov (United States)

Bidon, Tobias; Schreck, Nancy; Hailer, Frank; Nilsson, Maria A.; Janke, Axel

2015-01-01

The male-inherited Y chromosome is the major haploid fraction of the mammalian genome, rendering Y-linked sequences an indispensable resource for evolutionary research. However, despite recent large-scale genome sequencing approaches, only a handful of Y chromosome sequences have been characterized to date, mainly in model organisms. Using polar bear (Ursus maritimus) genomes, we compare two different in silico approaches to identify Y-linked sequences: 1) Similarity to known Y-linked genes and 2) difference in the average read depth of autosomal versus sex chromosomal scaffolds. Specifically, we mapped available genomic sequencing short reads from a male and a female polar bear against the reference genome and identify 112 Y-chromosomal scaffolds with a combined length of 1.9 Mb. We verified the in silico findings for the longer polar bear scaffolds by male-specific in vitro amplification, demonstrating the reliability of the average read depth approach. The obtained Y chromosome sequences contain protein-coding sequences, single nucleotide polymorphisms, microsatellites, and transposable elements that are useful for evolutionary studies. A high-resolution phylogeny of the polar bear patriline shows two highly divergent Y chromosome lineages, obtained from analysis of the identified Y scaffolds in 12 previously published male polar bear genomes. Moreover, we find evidence of gene conversion among ZFX and ZFY sequences in the giant panda lineage and in the ancestor of ursine and tremarctine bears. Thus, the identification of Y-linked scaffold sequences from unordered genome sequences yields valuable data to infer phylogenomic and population-genomic patterns in bears. PMID:26019166
Fine-Mapping of Common Genetic Variants Associated with Colorectal Tumor Risk Identified Potential Functional Variants.

Directory of Open Access Journals (Sweden)

Mengmeng Du

Full Text Available Genome-wide association studies (GWAS have identified many common single nucleotide polymorphisms (SNPs associated with colorectal cancer risk. These SNPs may tag correlated variants with biological importance. Fine-mapping around GWAS loci can facilitate detection of functional candidates and additional independent risk variants. We analyzed 11,900 cases and 14,311 controls in the Genetics and Epidemiology of Colorectal Cancer Consortium and the Colon Cancer Family Registry. To fine-map genomic regions containing all known common risk variants, we imputed high-density genetic data from the 1000 Genomes Project. We tested single-variant associations with colorectal tumor risk for all variants spanning genomic regions 250-kb upstream or downstream of 31 GWAS-identified SNPs (index SNPs. We queried the University of California, Santa Cruz Genome Browser to examine evidence for biological function. Index SNPs did not show the strongest association signals with colorectal tumor risk in their respective genomic regions. Bioinformatics analysis of SNPs showing smaller P-values in each region revealed 21 functional candidates in 12 loci (5q31.1, 8q24, 11q13.4, 11q23, 12p13.32, 12q24.21, 14q22.2, 15q13, 18q21, 19q13.1, 20p12.3, and 20q13.33. We did not observe evidence of additional independent association signals in GWAS-identified regions. Our results support the utility of integrating data from comprehensive fine-mapping with expanding publicly available genomic databases to help clarify GWAS associations and identify functional candidates that warrant more onerous laboratory follow-up. Such efforts may aid the eventual discovery of disease-causing variant(s.
Proteogenomic Analysis Identifies a Novel Human SHANK3 Isoform

Directory of Open Access Journals (Sweden)

Fahad Benthani

2015-05-01

Full Text Available Mutations of the SHANK3 gene have been associated with autism spectrum disorder. Individuals harboring different SHANK3 mutations display considerable heterogeneity in their cognitive impairment, likely due to the high SHANK3 transcriptional diversity. In this study, we report a novel interaction between the Mutated in colorectal cancer (MCC protein and a newly identified SHANK3 protein isoform in human colon cancer cells and mouse brain tissue. Hence, our proteogenomic analysis identifies a new human long isoform of the key synaptic protein SHANK3 that was not predicted by the human reference genome. Taken together, our findings describe a potential new role for MCC in neurons, a new human SHANK3 long isoform and, importantly, highlight the use of proteomic data towards the re-annotation of GC-rich genomic regions.
A computational approach to distinguish somatic vs. germline origin of genomic alterations from deep sequencing of cancer specimens without a matched normal.

Directory of Open Access Journals (Sweden)

James X Sun

2018-02-01

Full Text Available A key constraint in genomic testing in oncology is that matched normal specimens are not commonly obtained in clinical practice. Thus, while well-characterized genomic alterations do not require normal tissue for interpretation, a significant number of alterations will be unknown in whether they are germline or somatic, in the absence of a matched normal control. We introduce SGZ (somatic-germline-zygosity, a computational method for predicting somatic vs. germline origin and homozygous vs. heterozygous or sub-clonal state of variants identified from deep massively parallel sequencing (MPS of cancer specimens. The method does not require a patient matched normal control, enabling broad application in clinical research. SGZ predicts the somatic vs. germline status of each alteration identified by modeling the alteration's allele frequency (AF, taking into account the tumor content, tumor ploidy, and the local copy number. Accuracy of the prediction depends on the depth of sequencing and copy number model fit, which are achieved in our clinical assay by sequencing to high depth (>500x using MPS, covering 394 cancer-related genes and over 3,500 genome-wide single nucleotide polymorphisms (SNPs. Calls are made using a statistic based on read depth and local variability of SNP AF. To validate the method, we first evaluated performance on samples from 30 lung and colon cancer patients, where we sequenced tumors and matched normal tissue. We examined predictions for 17 somatic hotspot mutations and 20 common germline SNPs in 20,182 clinical cancer specimens. To assess the impact of stromal admixture, we examined three cell lines, which were titrated with their matched normal to six levels (10-75%. Overall, predictions were made in 85% of cases, with 95-99% of variants predicted correctly, a significantly superior performance compared to a basic approach based on AF alone. We then applied the SGZ method to the COSMIC database of known somatic variants
Implementing genomics and pharmacogenomics in the clinic: The National Human Genome Research Institute's genomic medicine portfolio.

Science.gov (United States)

Manolio, Teri A

2016-10-01

Increasing knowledge about the influence of genetic variation on human health and growing availability of reliable, cost-effective genetic testing have spurred the implementation of genomic medicine in the clinic. As defined by the National Human Genome Research Institute (NHGRI), genomic medicine uses an individual's genetic information in his or her clinical care, and has begun to be applied effectively in areas such as cancer genomics, pharmacogenomics, and rare and undiagnosed diseases. In 2011 NHGRI published its strategic vision for the future of genomic research, including an ambitious research agenda to facilitate and promote the implementation of genomic medicine. To realize this agenda, NHGRI is consulting and facilitating collaborations with the external research community through a series of "Genomic Medicine Meetings," under the guidance and leadership of the National Advisory Council on Human Genome Research. These meetings have identified and begun to address significant obstacles to implementation, such as lack of evidence of efficacy, limited availability of genomics expertise and testing, lack of standards, and difficulties in integrating genomic results into electronic medical records. The six research and dissemination initiatives comprising NHGRI's genomic research portfolio are designed to speed the evaluation and incorporation, where appropriate, of genomic technologies and findings into routine clinical care. Actual adoption of successful approaches in clinical care will depend upon the willingness, interest, and energy of professional societies, practitioners, patients, and payers to promote their responsible use and share their experiences in doing so. Published by Elsevier Ireland Ltd.
Digestive tumor bank protocol: from surgical specimens to genomic studies of digestive cancers.

Science.gov (United States)

Popescu, I; Stroescu, C; Dumitrascu, T; Herlea, V; Paslaru, Liliana; Lazar, V; Boissin, H; Taieb, J; Horeanga, Ionela

2006-01-01

Cancer is a complex polygenic and multifactorial disease, resulting from successive dynamic changes in the genome of somatic cells and from the accumulation of molecular alterations in both tumour cells and host cells. For the majority of cancers, including many malignancies of the gastrointestinal tract, our current means of diagnosis and treatment of the tumors are grossly insufficient. In recent years the development of several gene expression profiling methods such as comparative genomic hybridization (CGH), differential display, serial analysis of gene expression (SAGE) and DNA arrays, together with the sequencing of the human genome, has provided an opportunity to monitor and investigate the complete cascade of molecular events leading to tumor development and progression. Given the central role played by surgeons in the current management of patients with solid cancers, it is of paramount importance for them to know the principles characterizing this laboratory tools to critically assess the results originating from this biotechnology. We describe in this article the scientific partnership between Fundeni Clinical Institute Bucharest, Romania and RNtech Company, Paris, France for the development of a center of biological resources (Biobank) as well as the standardized protocol of working with the biological samples, the ongoing projects and the future perspectives.
Gastric cancers of Western European and African patients show different patterns of genomic instability

Directory of Open Access Journals (Sweden)

Mulder Chris JJ

2011-01-01

Full Text Available Abstract Background Infection with H. pylori is important in the etiology of gastric cancer. Gastric cancer is infrequent in Africa, despite high frequencies of H. pylori infection, referred to as the African enigma. Variation in environmental and host factors influencing gastric cancer risk between different populations have been reported but little is known about the biological differences between gastric cancers from different geographic locations. We aim to study genomic instability patterns of gastric cancers obtained from patients from United Kingdom (UK and South Africa (SA, in an attempt to support the African enigma hypothesis at the biological level. Methods DNA was isolated from 67 gastric adenocarcinomas, 33 UK patients, 9 Caucasian SA patients and 25 native SA patients. Microsatellite instability and chromosomal instability were analyzed by PCR and microarray comparative genomic hybridization, respectively. Data was analyzed by supervised univariate and multivariate analyses as well as unsupervised hierarchical cluster analysis. Results Tumors from Caucasian and native SA patients showed significantly more microsatellite instable tumors (p Conclusions Gastric cancers from SA and UK patients show differences in genetic instability patterns, indicating possible different biological mechanisms in patients from different geographical origin. This is of future clinical relevance for stratification of gastric cancer therapy.
Integrative Genomics Reveals Mechanisms of Copy Number Alterations Responsible for Transcriptional Deregulation in Colorectal Cancer

Science.gov (United States)

Camps, Jordi; Nguyen, Quang Tri; Padilla-Nash, Hesed M.; Knutsen, Turid; McNeil, Nicole E.; Wangsa, Danny; Hummon, Amanda B.; Grade, Marian; Ried, Thomas; Difilippantonio, Michael J.

2016-01-01

To evaluate the mechanisms and consequences of chromosomal aberrations in colorectal cancer (CRC), we used a combination of spectral karyotyping, array comparative genomic hybridization (aCGH), and array-based global gene expression profiling on 31 primary carcinomas and 15 established cell lines. Importantly, aCGH showed that the genomic profiles of primary tumors are recapitulated in the cell lines. We revealed a preponderance of chromosome breakpoints at sites of copy number variants (CNVs) in the CRC cell lines, a novel mechanism of DNA breakage in cancer. The integration of gene expression and aCGH led to the identification of 157 genes localized within high-level copy number changes whose transcriptional deregulation was significantly affected across all of the samples, thereby suggesting that these genes play a functional role in CRC. Genomic amplification at 8q24 was the most recurrent event and led to the overexpression of MYC and FAM84B. Copy number dependent gene expression resulted in deregulation of known cancer genes such as APC, FGFR2, and ERBB2. The identification of only 36 genes whose localization near a breakpoint could account for their observed deregulated expression demonstrates that the major mechanism for transcriptional deregulation in CRC is genomic copy number changes resulting from chromosomal aberrations. PMID:19691111
In vivo CRISPR screening identifies Ptpn2 as a cancer immunotherapy target.

Science.gov (United States)

Manguso, Robert T; Pope, Hans W; Zimmer, Margaret D; Brown, Flavian D; Yates, Kathleen B; Miller, Brian C; Collins, Natalie B; Bi, Kevin; LaFleur, Martin W; Juneja, Vikram R; Weiss, Sarah A; Lo, Jennifer; Fisher, David E; Miao, Diana; Van Allen, Eliezer; Root, David E; Sharpe, Arlene H; Doench, John G; Haining, W Nicholas

2017-07-27

Immunotherapy with PD-1 checkpoint blockade is effective in only a minority of patients with cancer, suggesting that additional treatment strategies are needed. Here we use a pooled in vivo genetic screening approach using CRISPR-Cas9 genome editing in transplantable tumours in mice treated with immunotherapy to discover previously undescribed immunotherapy targets. We tested 2,368 genes expressed by melanoma cells to identify those that synergize with or cause resistance to checkpoint blockade. We recovered the known immune evasion molecules PD-L1 and CD47, and confirmed that defects in interferon-γ signalling caused resistance to immunotherapy. Tumours were sensitized to immunotherapy by deletion of genes involved in several diverse pathways, including NF-κB signalling, antigen presentation and the unfolded protein response. In addition, deletion of the protein tyrosine phosphatase PTPN2 in tumour cells increased the efficacy of immunotherapy by enhancing interferon-γ-mediated effects on antigen presentation and growth suppression. In vivo genetic screens in tumour models can identify new immunotherapy targets in unanticipated pathways.
Whole-Genome Sequencing of Sordaria macrospora Mutants Identifies Developmental Genes.

Science.gov (United States)

Nowrousian, Minou; Teichert, Ines; Masloff, Sandra; Kück, Ulrich

2012-02-01

The study of mutants to elucidate gene functions has a long and successful history; however, to discover causative mutations in mutants that were generated by random mutagenesis often takes years of laboratory work and requires previously generated genetic and/or physical markers, or resources like DNA libraries for complementation. Here, we present an alternative method to identify defective genes in developmental mutants of the filamentous fungus Sordaria macrospora through Illumina/Solexa whole-genome sequencing. We sequenced pooled DNA from progeny of crosses of three mutants and the wild type and were able to pinpoint the causative mutations in the mutant strains through bioinformatics analysis. One mutant is a spore color mutant, and the mutated gene encodes a melanin biosynthesis enzyme. The causative mutation is a G to A change in the first base of an intron, leading to a splice defect. The second mutant carries an allelic mutation in the pro41 gene encoding a protein essential for sexual development. In the mutant, we detected a complex pattern of deletion/rearrangements at the pro41 locus. In the third mutant, a point mutation in the stop codon of a transcription factor-encoding gene leads to the production of immature fruiting bodies. For all mutants, transformation with a wild type-copy of the affected gene restored the wild-type phenotype. Our data demonstrate that whole-genome sequencing of mutant strains is a rapid method to identify developmental genes in an organism that can be genetically crossed and where a reference genome sequence is available, even without prior mapping information.
Identification of a breast cancer susceptibility locus at 4q31.22 using a genome-wide association study paradigm.

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Yadav Sapkota

Full Text Available More than 40 single nucleotide polymorphisms (SNPs for breast cancer susceptibility were identified by genome-wide association studies (GWASs. However, additional SNPs likely contribute to breast cancer susceptibility and overall genetic risk, prompting this investigation for additional variants. Six putative breast cancer susceptibility SNPs identified in a two-stage GWAS that we reported earlier were replicated in a follow-up stage 3 study using an independent set of breast cancer cases and controls from Canada, with an overall cumulative sample size of 7,219 subjects across all three stages. The study design also encompassed the 11 variants from GWASs previously reported by various consortia between the years 2007-2009 to (i enable comparisons of effect sizes, and (ii identify putative prognostic variants across studies. All SNP associations reported with breast cancer were also adjusted for body mass index (BMI. We report a strong association with 4q31.22-rs1429142 (combined per allele odds ratio and 95% confidence interval = 1.28 [1.17-1.41] and P combined = 1.5×10(-7, when adjusted for BMI. Ten of the 11 breast cancer susceptibility loci reported by consortia also showed associations in our predominantly Caucasian study population, and the associations were independent of BMI; four FGFR2 SNPs and TNRC9-rs3803662 were among the most notable associations. Since the original report by Garcia-Closas et al. 2008, this is the second study to confirm the association of 8q24.21-rs13281615 with breast cancer outcomes.
Genomes2Drugs: identifies target proteins and lead drugs from proteome data.

LENUS (Irish Health Repository)

Toomey, David

2009-01-01

BACKGROUND: Genome sequencing and bioinformatics have provided the full hypothetical proteome of many pathogenic organisms. Advances in microarray and mass spectrometry have also yielded large output datasets of possible target proteins\\/genes. However, the challenge remains to identify new targets for drug discovery from this wealth of information. Further analysis includes bioinformatics and\\/or molecular biology tools to validate the findings. This is time consuming and expensive, and could fail to yield novel drugs if protein purification and crystallography is impossible. To pre-empt this, a researcher may want to rapidly filter the output datasets for proteins that show good homology to proteins that have already been structurally characterised or proteins that are already targets for known drugs. Critically, those researchers developing novel antibiotics need to select out the proteins that show close homology to any human proteins, as future inhibitors are likely to cross-react with the host protein, causing off-target toxicity effects later in clinical trials. METHODOLOGY\\/PRINCIPAL FINDINGS: To solve many of these issues, we have developed a free online resource called Genomes2Drugs which ranks sequences to identify proteins that are (i) homologous to previously crystallized proteins or (ii) targets of known drugs, but are (iii) not homologous to human proteins. When tested using the Plasmodium falciparum malarial genome the program correctly enriched the ranked list of proteins with known drug target proteins. CONCLUSIONS\\/SIGNIFICANCE: Genomes2Drugs rapidly identifies proteins that are likely to succeed in drug discovery pipelines. This free online resource helps in the identification of potential drug targets. Importantly, the program further highlights proteins that are likely to be inhibited by FDA-approved drugs. These drugs can then be rapidly moved into Phase IV clinical studies under \\'change-of-application\\' patents.

Genomes2Drugs: identifies target proteins and lead drugs from proteome data.

Directory of Open Access Journals (Sweden)

David Toomey

Full Text Available BACKGROUND: Genome sequencing and bioinformatics have provided the full hypothetical proteome of many pathogenic organisms. Advances in microarray and mass spectrometry have also yielded large output datasets of possible target proteins/genes. However, the challenge remains to identify new targets for drug discovery from this wealth of information. Further analysis includes bioinformatics and/or molecular biology tools to validate the findings. This is time consuming and expensive, and could fail to yield novel drugs if protein purification and crystallography is impossible. To pre-empt this, a researcher may want to rapidly filter the output datasets for proteins that show good homology to proteins that have already been structurally characterised or proteins that are already targets for known drugs. Critically, those researchers developing novel antibiotics need to select out the proteins that show close homology to any human proteins, as future inhibitors are likely to cross-react with the host protein, causing off-target toxicity effects later in clinical trials. METHODOLOGY/PRINCIPAL FINDINGS: To solve many of these issues, we have developed a free online resource called Genomes2Drugs which ranks sequences to identify proteins that are (i homologous to previously crystallized proteins or (ii targets of known drugs, but are (iii not homologous to human proteins. When tested using the Plasmodium falciparum malarial genome the program correctly enriched the ranked list of proteins with known drug target proteins. CONCLUSIONS/SIGNIFICANCE: Genomes2Drugs rapidly identifies proteins that are likely to succeed in drug discovery pipelines. This free online resource helps in the identification of potential drug targets. Importantly, the program further highlights proteins that are likely to be inhibited by FDA-approved drugs. These drugs can then be rapidly moved into Phase IV clinical studies under 'change-of-application' patents.
Genome-Wide Search Identifies 1.9 Mb from the Polar Bear Y Chromosome for Evolutionary Analyses.

Science.gov (United States)

Bidon, Tobias; Schreck, Nancy; Hailer, Frank; Nilsson, Maria A; Janke, Axel

2015-05-27

The male-inherited Y chromosome is the major haploid fraction of the mammalian genome, rendering Y-linked sequences an indispensable resource for evolutionary research. However, despite recent large-scale genome sequencing approaches, only a handful of Y chromosome sequences have been characterized to date, mainly in model organisms. Using polar bear (Ursus maritimus) genomes, we compare two different in silico approaches to identify Y-linked sequences: 1) Similarity to known Y-linked genes and 2) difference in the average read depth of autosomal versus sex chromosomal scaffolds. Specifically, we mapped available genomic sequencing short reads from a male and a female polar bear against the reference genome and identify 112 Y-chromosomal scaffolds with a combined length of 1.9 Mb. We verified the in silico findings for the longer polar bear scaffolds by male-specific in vitro amplification, demonstrating the reliability of the average read depth approach. The obtained Y chromosome sequences contain protein-coding sequences, single nucleotide polymorphisms, microsatellites, and transposable elements that are useful for evolutionary studies. A high-resolution phylogeny of the polar bear patriline shows two highly divergent Y chromosome lineages, obtained from analysis of the identified Y scaffolds in 12 previously published male polar bear genomes. Moreover, we find evidence of gene conversion among ZFX and ZFY sequences in the giant panda lineage and in the ancestor of ursine and tremarctine bears. Thus, the identification of Y-linked scaffold sequences from unordered genome sequences yields valuable data to infer phylogenomic and population-genomic patterns in bears. © The Author(s) 2015. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.
A Novel Yeast Genomics Method for Identifying New Breast Cancer Susceptibility Genes

National Research Council Canada - National Science Library

Brown, J. M; Brown, James A

2007-01-01

...) a hallmark of most breast cancers when deleted. Using a collection of yeast strains carrying the deletion of a unique open reading frame, we have transfected a yeast artificial chromosome (YAC...
BAC CGH-array identified specific small-scale genomic imbalances in diploid DMBA-induced rat mammary tumors

International Nuclear Information System (INIS)

Samuelson, Emma; Karlsson, Sara; Partheen, Karolina; Nilsson, Staffan; Szpirer, Claude; Behboudi, Afrouz

2012-01-01

Development of breast cancer is a multistage process influenced by hormonal and environmental factors as well as by genetic background. The search for genes underlying this malignancy has recently been highly productive, but the etiology behind this complex disease is still not understood. In studies using animal cancer models, heterogeneity of the genetic background and environmental factors is reduced and thus analysis and identification of genetic aberrations in tumors may become easier. To identify chromosomal regions potentially involved in the initiation and progression of mammary cancer, in the present work we subjected a subset of experimental mammary tumors to cytogenetic and molecular genetic analysis. Mammary tumors were induced with DMBA (7,12-dimethylbenz[a]anthrazene) in female rats from the susceptible SPRD-Cu3 strain and from crosses and backcrosses between this strain and the resistant WKY strain. We first produced a general overview of chromosomal aberrations in the tumors using conventional kartyotyping (G-banding) and Comparative Genome Hybridization (CGH) analyses. Particular chromosomal changes were then analyzed in more details using an in-house developed BAC (bacterial artificial chromosome) CGH-array platform. Tumors appeared to be diploid by conventional karyotyping, however several sub-microscopic chromosome gains or losses in the tumor material were identified by BAC CGH-array analysis. An oncogenetic tree analysis based on the BAC CGH-array data suggested gain of rat chromosome (RNO) band 12q11, loss of RNO5q32 or RNO6q21 as the earliest events in the development of these mammary tumors. Some of the identified changes appear to be more specific for DMBA-induced mammary tumors and some are similar to those previously reported in ACI rat model for estradiol-induced mammary tumors. The later group of changes is more interesting, since they may represent anomalies that involve genes with a critical role in mammary tumor development. Genetic
Implementing genomics and pharmacogenomics in the clinic: The National Human Genome Research Institute’s genomic medicine portfolio

Science.gov (United States)

Manolio, Teri A.

2016-01-01

Increasing knowledge about the influence of genetic variation on human health and growing availability of reliable, cost-effective genetic testing have spurred the implementation of genomic medicine in the clinic. As defined by the National Human Genome Research Institute (NHGRI), genomic medicine uses an individual’s genetic information in his or her clinical care, and has begun to be applied effectively in areas such as cancer genomics, pharmacogenomics, and rare and undiagnosed diseases. In 2011 NHGRI published its strategic vision for the future of genomic research, including an ambitious research agenda to facilitate and promote the implementation of genomic medicine. To realize this agenda, NHGRI is consulting and facilitating collaborations with the external research community through a series of “Genomic Medicine Meetings,” under the guidance and leadership of the National Advisory Council on Human Genome Research. These meetings have identified and begun to address significant obstacles to implementation, such as lack of evidence of efficacy, limited availability of genomics expertise and testing, lack of standards, and diffficulties in integrating genomic results into electronic medical records. The six research and dissemination initiatives comprising NHGRI’s genomic research portfolio are designed to speed the evaluation and incorporation, where appropriate, of genomic technologies and findings into routine clinical care. Actual adoption of successful approaches in clinical care will depend upon the willingness, interest, and energy of professional societies, practitioners, patients, and payers to promote their responsible use and share their experiences in doing so. PMID:27612677
Whole genome association study identifies regions of the bovine genome and biological pathways involved in carcass trait performance in Holstein-Friesian cattle.

Science.gov (United States)

Doran, Anthony G; Berry, Donagh P; Creevey, Christopher J

2014-10-01

Four traits related to carcass performance have been identified as economically important in beef production: carcass weight, carcass fat, carcass conformation of progeny and cull cow carcass weight. Although Holstein-Friesian cattle are primarily utilized for milk production, they are also an important source of meat for beef production and export. Because of this, there is great interest in understanding the underlying genomic structure influencing these traits. Several genome-wide association studies have identified regions of the bovine genome associated with growth or carcass traits, however, little is known about the mechanisms or underlying biological pathways involved. This study aims to detect regions of the bovine genome associated with carcass performance traits (employing a panel of 54,001 SNPs) using measures of genetic merit (as predicted transmitting abilities) for 5,705 Irish Holstein-Friesian animals. Candidate genes and biological pathways were then identified for each trait under investigation. Following adjustment for false discovery (q-value carcass traits using a single SNP regression approach. Using a Bayesian approach, 46 QTL were associated (posterior probability > 0.5) with at least one of the four traits. In total, 557 unique bovine genes, which mapped to 426 human orthologs, were within 500kbs of QTL found associated with a trait using the Bayesian approach. Using this information, 24 significantly over-represented pathways were identified across all traits. The most significantly over-represented biological pathway was the peroxisome proliferator-activated receptor (PPAR) signaling pathway. A large number of genomic regions putatively associated with bovine carcass traits were detected using two different statistical approaches. Notably, several significant associations were detected in close proximity to genes with a known role in animal growth such as glucagon and leptin. Several biological pathways, including PPAR signaling, were
The compact Selaginella genome identifies changes in gene content associated with the evolution of vascular plants

Energy Technology Data Exchange (ETDEWEB)

Grigoriev, Igor V.; Banks, Jo Ann; Nishiyama, Tomoaki; Hasebe, Mitsuyasu; Bowman, John L.; Gribskov, Michael; dePamphilis, Claude; Albert, Victor A.; Aono, Naoki; Aoyama, Tsuyoshi; Ambrose, Barbara A.; Ashton, Neil W.; Axtell, Michael J.; Barker, Elizabeth; Barker, Michael S.; Bennetzen, Jeffrey L.; Bonawitz, Nicholas D.; Chapple, Clint; Cheng, Chaoyang; Correa, Luiz Gustavo Guedes; Dacre, Michael; DeBarry, Jeremy; Dreyer, Ingo; Elias, Marek; Engstrom, Eric M.; Estelle, Mark; Feng, Liang; Finet, Cedric; Floyd, Sandra K.; Frommer, Wolf B.; Fujita, Tomomichi; Gramzow, Lydia; Gutensohn, Michael; Harholt, Jesper; Hattori, Mitsuru; Heyl, Alexander; Hirai, Tadayoshi; Hiwatashi, Yuji; Ishikawa, Masaki; Iwata, Mineko; Karol, Kenneth G.; Koehler, Barbara; Kolukisaoglu, Uener; Kubo, Minoru; Kurata, Tetsuya; Lalonde, Sylvie; Li, Kejie; Li, Ying; Litt, Amy; Lyons, Eric; Manning, Gerard; Maruyama, Takeshi; Michael, Todd P.; Mikami, Koji; Miyazaki, Saori; Morinaga, Shin-ichi; Murata, Takashi; Mueller-Roeber, Bernd; Nelson, David R.; Obara, Mari; Oguri, Yasuko; Olmstead, Richard G.; Onodera, Naoko; Petersen, Bent Larsen; Pils, Birgit; Prigge, Michael; Rensing, Stefan A.; Riano-Pachon, Diego Mauricio; Roberts, Alison W.; Sato, Yoshikatsu; Scheller, Henrik Vibe; Schulz, Burkhard; Schulz, Christian; Shakirov, Eugene V.; Shibagaki, Nakako; Shinohara, Naoki; Shippen, Dorothy E.; Sorensen, Iben; Sotooka, Ryo; Sugimoto, Nagisa; Sugita, Mamoru; Sumikawa, Naomi; Tanurdzic, Milos; Theilsen, Gunter; Ulvskov, Peter; Wakazuki, Sachiko; Weng, Jing-Ke; Willats, William W.G.T.; Wipf, Daniel; Wolf, Paul G.; Yang, Lixing; Zimmer, Andreas D.; Zhu, Qihui; Mitros, Therese; Hellsten, Uffe; Loque, Dominique; Otillar, Robert; Salamov, Asaf; Schmutz, Jeremy; Shapiro, Harris; Lindquist, Erika; Lucas, Susan; Rokhsar, Daniel

2011-04-28

We report the genome sequence of the nonseed vascular plant, Selaginella moellendorffii, and by comparative genomics identify genes that likely played important roles in the early evolution of vascular plants and their subsequent evolution
CHEK2 c.1100delC allele is rarely identified in Greek breast cancer cases.

Science.gov (United States)

Apostolou, Paraskevi; Fostira, Florentia; Papamentzelopoulou, Myrto; Michelli, Maria; Panopoulos, Christos; Fountzilas, George; Konstantopoulou, Irene; Voutsinas, Gerassimos E; Yannoukakos, Drakoulis

2015-04-01

The CHEK2 gene encodes a protein kinase that plays a crucial role in maintenance of genomic integrity and the DNA repair mechanism. CHEK2 germline mutations are associated with increased risk of breast cancer and other malignancies. From a clinical perspective, the most significant mutation identified is the c.1100delC mutation, which is associated with an approximately 25% lifetime breast cancer risk. The distribution of this mutation shows wide geographical variation; it is more prevalent in the Northern European countries and less common, or even absent, in Southern Europe. In order to estimate the frequency of the CHEK2 c.1100delC mutation in Greek breast cancer patients, we genotyped 2,449 patients (2,408 females and 41 males), which was the largest series ever tested for c.1100delC. The mean age of female and male breast cancer diagnosis was 49 and 59 years, respectively. All patients had previously tested negative for the Greek BRCA1 founder and recurrent mutations. The CHEK2 c.1100delC mutation was detected in 0.16% (4 of 2,408) of females, all of whom were diagnosed with breast cancer before the age of 50 years. Only one c.1100delC carrier was reported with breast cancer family history. The present study indicates that the CHEK2 c.1100delC mutation does not contribute substantially to hereditary breast cancer in patients of Greek descent. Copyright © 2015 Elsevier Inc. All rights reserved.
Finding cancer driver mutations in the era of big data research.

Science.gov (United States)

Poulos, Rebecca C; Wong, Jason W H

2018-04-02

In the last decade, the costs of genome sequencing have decreased considerably. The commencement of large-scale cancer sequencing projects has enabled cancer genomics to join the big data revolution. One of the challenges still facing cancer genomics research is determining which are the driver mutations in an individual cancer, as these contribute only a small subset of the overall mutation profile of a tumour. Focusing primarily on somatic single nucleotide mutations in this review, we consider both coding and non-coding driver mutations, and discuss how such mutations might be identified from cancer sequencing datasets. We describe some of the tools and database that are available for the annotation of somatic variants and the identification of cancer driver genes. We also address the use of genome-wide variation in mutation load to establish background mutation rates from which to identify driver mutations under positive selection. Finally, we describe the ways in which mutational signatures can act as clues for the identification of cancer drivers, as these mutations may cause, or arise from, certain mutational processes. By defining the molecular changes responsible for driving cancer development, new cancer treatment strategies may be developed or novel preventative measures proposed.
9q31.2-rs865686 as a susceptibility locus for estrogen receptor-positive breast cancer

DEFF Research Database (Denmark)

Warren, Helen; Dudbridge, Frank; Fletcher, Olivia

2012-01-01

Our recent genome-wide association study identified a novel breast cancer susceptibility locus at 9q31.2 (rs865686).......Our recent genome-wide association study identified a novel breast cancer susceptibility locus at 9q31.2 (rs865686)....
Warburg effect and translocation-induced genomic instability: two yeast models for cancer cells

International Nuclear Information System (INIS)

Tosato, Valentina; Grüning, Nana-Maria; Breitenbach, Michael; Arnak, Remigiusz; Ralser, Markus; Bruschi, Carlo V.

2013-01-01

Yeast has been established as an efficient model system to study biological principles underpinning human health. In this review we focus on yeast models covering two aspects of cancer formation and progression (i) the activity of pyruvate kinase (PK), which recapitulates metabolic features of cancer cells, including the Warburg effect, and (ii) chromosome bridge-induced translocation (BIT) mimiking genome instability in cancer. Saccharomyces cerevisiae is an excellent model to study cancer cell metabolism, as exponentially growing yeast cells exhibit many metabolic similarities with rapidly proliferating cancer cells. The metabolic reconfiguration includes an increase in glucose uptake and fermentation, at the expense of respiration and oxidative phosphorylation (the Warburg effect), and involves a broad reconfiguration of nucleotide and amino acid metabolism. Both in yeast and humans, the regulation of this process seems to have a central player, PK, which is up-regulated in cancer, and to occur mostly on a post-transcriptional and post-translational basis. Furthermore, BIT allows to generate selectable translocation-derived recombinants (“translocants”), between any two desired chromosomal locations, in wild-type yeast strains transformed with a linear DNA cassette carrying a selectable marker flanked by two DNA sequences homologous to different chromosomes. Using the BIT system, targeted non-reciprocal translocations in mitosis are easily inducible. An extensive collection of different yeast translocants exhibiting genome instability and aberrant phenotypes similar to cancer cells has been produced and subjected to analysis. In this review, we hence provide an overview upon two yeast cancer models, and extrapolate general principles for mimicking human disease mechanisms in yeast.
Warburg effect and translocation-induced genomic instability: two yeast models for cancer cells

Energy Technology Data Exchange (ETDEWEB)

Tosato, Valentina [International Centre for Genetic Engineering and Biotechnology, Trieste (Italy); Grüning, Nana-Maria [Cambridge System Biology Center, Department of Biochemistry, University of Cambridge, Cambridge (United Kingdom); Breitenbach, Michael [Division of Genetics, Department of Cell Biology, University of Salzburg, Salzburg (Austria); Arnak, Remigiusz [International Centre for Genetic Engineering and Biotechnology, Trieste (Italy); Ralser, Markus [Cambridge System Biology Center, Department of Biochemistry, University of Cambridge, Cambridge (United Kingdom); Bruschi, Carlo V., E-mail: bruschi@icgeb.org [International Centre for Genetic Engineering and Biotechnology, Trieste (Italy)

2013-01-18

Yeast has been established as an efficient model system to study biological principles underpinning human health. In this review we focus on yeast models covering two aspects of cancer formation and progression (i) the activity of pyruvate kinase (PK), which recapitulates metabolic features of cancer cells, including the Warburg effect, and (ii) chromosome bridge-induced translocation (BIT) mimiking genome instability in cancer. Saccharomyces cerevisiae is an excellent model to study cancer cell metabolism, as exponentially growing yeast cells exhibit many metabolic similarities with rapidly proliferating cancer cells. The metabolic reconfiguration includes an increase in glucose uptake and fermentation, at the expense of respiration and oxidative phosphorylation (the Warburg effect), and involves a broad reconfiguration of nucleotide and amino acid metabolism. Both in yeast and humans, the regulation of this process seems to have a central player, PK, which is up-regulated in cancer, and to occur mostly on a post-transcriptional and post-translational basis. Furthermore, BIT allows to generate selectable translocation-derived recombinants (“translocants”), between any two desired chromosomal locations, in wild-type yeast strains transformed with a linear DNA cassette carrying a selectable marker flanked by two DNA sequences homologous to different chromosomes. Using the BIT system, targeted non-reciprocal translocations in mitosis are easily inducible. An extensive collection of different yeast translocants exhibiting genome instability and aberrant phenotypes similar to cancer cells has been produced and subjected to analysis. In this review, we hence provide an overview upon two yeast cancer models, and extrapolate general principles for mimicking human disease mechanisms in yeast.
WARBURG EFFECT AND TRANSLOCATION-INDUCED GENOMIC INSTABILITY: TWO YEAST MODELS FOR CANCER CELLS

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Valentina eTosato

2013-01-01

Full Text Available Yeast has been established as an efficient model system to study biological principles underpinning human health. In this review we focus on yeast models covering two aspects of cancer formation and progression i the activity of pyruvate kinase (PK, which recapitulates metabolic features of cancer cells, including the Warburg effect, and ii Bridge-Induced chromosome Translocation (BIT mimicking genome instability in cancer. Saccharomyces cerevisiae is an excellent model to study cancer cell metabolism, as exponentially growing yeast cells exhibit many metabolic similarities with rapidly proliferating cancer cells. The metabolic reconfiguration includes an increase in glucose uptake and fermentation, at the expense of respiration and oxidative phosphorylation (the Warburg effect, and involves a broad reconfiguration of nucleotide and amino acid metabolism. Both in yeast and humans, the regulation of this process seems to have a central player, pyruvate kinase, which is up-regulated in cancer, and to occur mostly on a post-transcriptional and posttranslational basis. Furthermore, BIT allows to generate selectable translocation-derived recombinants (translocants, between any two desired chromosomal locations, in wild-type yeast strains transformed with a linear DNA cassette carrying a selectable marker flanked by two DNA sequences homologous to different chromosomes. Using the Bridge-Induced Translocation system, targeted non-reciprocal translocations in mitosis are easily inducible. An extensive collection of different yeast translocants exhibiting genome instability and aberrant phenotypes similar to cancer cells has been produced and subjected to analysis. In this review, we hence provide an overview upon two yeast cancer models, and extrapolate general principles for mimicking human disease mechanisms in yeast.
Evaluation of K-ras and p53 expression in pancreatic adenocarcinoma using the cancer genome atlas.

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Liming Lu

Full Text Available Genetic alterations in K-ras and p53 are thought to be critical in pancreatic cancer development and progression. However, K-ras and p53 expression in pancreatic adenocarcinoma have not been systematically examined in The Cancer Genome Atlas (TCGA Data Portal. Information regarding K-ras and p53 alterations, mRNA expression data, and protein/protein phosphorylation abundance was retrieved from The Cancer Genome Atlas (TCGA databases, and analyses were performed by the cBioPortal for Cancer Genomics. The mutual exclusivity analysis showed that events in K-ras and p53 were likely to co-occur in pancreatic adenocarcinoma (Log odds ratio = 1.599, P = 0.006. The graphical summary of the mutations showed that there were hotspots for protein activation. In the network analysis, no solid association between K-ras and p53 was observed in pancreatic adenocarcinoma. In the survival analysis, neither K-ras nor p53 were associated with both survival events. As in the data mining study in the TCGA databases, our study provides a new perspective to understand the genetic features of K-ras and p53 in pancreatic adenocarcinoma.
Deciphering cancer heterogeneity: the biological space

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Stephanie eRoessler

2014-04-01

Full Text Available Most lethal solid tumors including hepatocellular carcinoma (HCC are considered incurable due to extensive heterogeneity in clinical presentation and tumor biology. Tumor heterogeneity may result from different cells of origin, patient ethnicity, etiology, underlying disease and diversity of genomic and epigenomic changes which drive tumor development. Cancer genomic heterogeneity thereby impedes treatment options and poses a significant challenge to cancer management. Studies of the HCC genome have revealed that although various genomic signatures identified in different HCC subgroups share a common prognosis, each carries unique molecular changes which are linked to different sets of cancer hallmarks whose misregulation has been proposed by Hanahan and Weinberg to be essential for tumorigenesis. We hypothesize that these specific sets of cancer hallmarks collectively occupy different tumor biological space representing the misregulation of different biological processes. In principle, a combination of different cancer hallmarks can result in new convergent molecular networks that are unique to each tumor subgroup and represent ideal druggable targets. Due to the ability of the tumor to adapt to external factors such as treatment or changes in the tumor microenvironment, the tumor biological space is elastic. Our ability to identify distinct groups of cancer patients with similar tumor biology who are most likely to respond to a specific therapy would have a significant impact on improving patient outcome. It is currently a challenge to identify a particular hallmark or a newly emerged convergent molecular network for a particular tumor. Thus, it is anticipated that the integration of multiple levels of data such as genomic mutations, somatic copy number aberration, gene expression, proteomics, and metabolomics, may help us grasp the tumor biological space occupied by each individual, leading to improved therapeutic intervention and outcome.
Associations between circulating carotenoids, genomic instability and the risk of high-grade prostate cancer.

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Nordström, Tobias; Van Blarigan, Erin L; Ngo, Vy; Roy, Ritu; Weinberg, Vivian; Song, Xiaoling; Simko, Jeffry; Carroll, Peter R; Chan, June M; Paris, Pamela L

2016-03-01

Carotenoids are a class of nutrients with antioxidant properties that have been purported to protect against cancer. However, the reported associations between carotenoids and prostate cancer have been heterogeneous and lacking data on interactions with nucleotide sequence variations and genomic biomarkers. To examine the associations between carotenoid levels and the risk of high-grade prostate cancer, also considering antioxidant-related genes and tumor instability. We measured plasma levels of carotenoids and genotyped 20 single nucleotide polymorphisms (SNP) in SOD1, SOD2, SOD3, XRCC1, and OGG1 among 559 men with non-metastatic prostate cancer undergoing radical prostatectomy. We performed copy number analysis in a subset of these men (n = 67) to study tumor instability assessed as Fraction of the Genome Altered (FGA). We examined associations between carotenoids, genotypes, tumor instability and risk of high-grade prostate cancer (Gleason grade ≥ 4 + 3) using logistic and linear regression. Circulating carotenoid levels were inversely associated with the risk of high-grade prostate cancer; odds ratios (OR) and 95% confidence intervals (CI) comparing highest versus lowest quartiles were: 0.34 (95% CI: 0.18-0.66) for α-carotene, 0.31 (95% CI: 0.15-0.63) for β-carotene, 0.55 (0.28-1.08) for lycopene and 0.37 (0.18-0.75) for total carotenoids. SNPs rs25489 in XRCC1, rs699473 in SOD3 and rs1052133 in OGG1 modified these associations for α-carotene, β-carotene and lycopene, respectively (P ≤ 0.05). The proportion of men with a high degree of FGA increased with Gleason Score (P carotenoids at diagnosis, particularly among men carrying specific somatic variations, were inversely associated with risk of high-grade prostate cancer. In exploratory analyses, higher lycopene level was associated with less genomic instability among men with low-grade disease which is novel and supports the hypothesis that lycopene may inhibit progression of
Alternative splicing enriched cDNA libraries identify breast cancer-associated transcripts

Science.gov (United States)

2010-01-01

Background Alternative splicing (AS) is a central mechanism in the generation of genomic complexity and is a major contributor to transcriptome and proteome diversity. Alterations of the splicing process can lead to deregulation of crucial cellular processes and have been associated with a large spectrum of human diseases. Cancer-associated transcripts are potential molecular markers and may contribute to the development of more accurate diagnostic and prognostic methods and also serve as therapeutic targets. Alternative splicing-enriched cDNA libraries have been used to explore the variability generated by alternative splicing. In this study, by combining the use of trapping heteroduplexes and RNA amplification, we developed a powerful approach that enables transcriptome-wide exploration of the AS repertoire for identifying AS variants associated with breast tumor cells modulated by ERBB2 (HER-2/neu) oncogene expression. Results The human breast cell line (C5.2) and a pool of 5 ERBB2 over-expressing breast tumor samples were used independently for the construction of two AS-enriched libraries. In total, 2,048 partial cDNA sequences were obtained, revealing 214 alternative splicing sequence-enriched tags (ASSETs). A subset with 79 multiple exon ASSETs was compared to public databases and reported 138 different AS events. A high success rate of RT-PCR validation (94.5%) was obtained, and 2 novel AS events were identified. The influence of ERBB2-mediated expression on AS regulation was evaluated by capillary electrophoresis and probe-ligation approaches in two mammary cell lines (Hb4a and C5.2) expressing different levels of ERBB2. The relative expression balance between AS variants from 3 genes was differentially modulated by ERBB2 in this model system. Conclusions In this study, we presented a method for exploring AS from any RNA source in a transcriptome-wide format, which can be directly easily adapted to next generation sequencers. We identified AS transcripts
Genomic Analysis of Uterine Lavage Fluid Detects Early Endometrial Cancers and Reveals a Prevalent Landscape of Driver Mutations in Women without Histopathologic Evidence of Cancer: A Prospective Cross-Sectional Study.

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Navya Nair

2016-12-01

Full Text Available Endometrial cancer is the most common gynecologic malignancy, and its incidence and associated mortality are increasing. Despite the immediate need to detect these cancers at an earlier stage, there is no effective screening methodology or protocol for endometrial cancer. The comprehensive, genomics-based analysis of endometrial cancer by The Cancer Genome Atlas (TCGA revealed many of the molecular defects that define this cancer. Based on these cancer genome results, and in a prospective study, we hypothesized that the use of ultra-deep, targeted gene sequencing could detect somatic mutations in uterine lavage fluid obtained from women undergoing hysteroscopy as a means of molecular screening and diagnosis.Uterine lavage and paired blood samples were collected and analyzed from 107 consecutive patients who were undergoing hysteroscopy and curettage for diagnostic evaluation from this single-institution study. The lavage fluid was separated into cellular and acellular fractions by centrifugation. Cellular and cell-free DNA (cfDNA were isolated from each lavage. Two targeted next-generation sequencing (NGS gene panels, one composed of 56 genes and the other of 12 genes, were used for ultra-deep sequencing. To rule out potential NGS-based errors, orthogonal mutation validation was performed using digital PCR and Sanger sequencing. Seven patients were diagnosed with endometrial cancer based on classic histopathologic analysis. Six of these patients had stage IA cancer, and one of these cancers was only detectable as a microscopic focus within a polyp. All seven patients were found to have significant cancer-associated gene mutations in both cell pellet and cfDNA fractions. In the four patients in whom adequate tumor sample was available, all tumor mutations above a specific allele fraction were present in the uterine lavage DNA samples. Mutations originally only detected in lavage fluid fractions were later confirmed to be present in tumor but at
A web server for mining Comparative Genomic Hybridization (CGH) data

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Liu, Jun; Ranka, Sanjay; Kahveci, Tamer

2007-11-01

Advances in cytogenetics and molecular biology has established that chromosomal alterations are critical in the pathogenesis of human cancer. Recurrent chromosomal alterations provide cytological and molecular markers for the diagnosis and prognosis of disease. They also facilitate the identification of genes that are important in carcinogenesis, which in the future may help in the development of targeted therapy. A large amount of publicly available cancer genetic data is now available and it is growing. There is a need for public domain tools that allow users to analyze their data and visualize the results. This chapter describes a web based software tool that will allow researchers to analyze and visualize Comparative Genomic Hybridization (CGH) datasets. It employs novel data mining methodologies for clustering and classification of CGH datasets as well as algorithms for identifying important markers (small set of genomic intervals with aberrations) that are potentially cancer signatures. The developed software will help in understanding the relationships between genomic aberrations and cancer types.
New families of human regulatory RNA structures identified by comparative analysis of vertebrate genomes.

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Parker, Brian J; Moltke, Ida; Roth, Adam; Washietl, Stefan; Wen, Jiayu; Kellis, Manolis; Breaker, Ronald; Pedersen, Jakob Skou

2011-11-01

Regulatory RNA structures are often members of families with multiple paralogous instances across the genome. Family members share functional and structural properties, which allow them to be studied as a whole, facilitating both bioinformatic and experimental characterization. We have developed a comparative method, EvoFam, for genome-wide identification of families of regulatory RNA structures, based on primary sequence and secondary structure similarity. We apply EvoFam to a 41-way genomic vertebrate alignment. Genome-wide, we identify 220 human, high-confidence families outside protein-coding regions comprising 725 individual structures, including 48 families with known structural RNA elements. Known families identified include both noncoding RNAs, e.g., miRNAs and the recently identified MALAT1/MEN β lincRNA family; and cis-regulatory structures, e.g., iron-responsive elements. We also identify tens of new families supported by strong evolutionary evidence and other statistical evidence, such as GO term enrichments. For some of these, detailed analysis has led to the formulation of specific functional hypotheses. Examples include two hypothesized auto-regulatory feedback mechanisms: one involving six long hairpins in the 3'-UTR of MAT2A, a key metabolic gene that produces the primary human methyl donor S-adenosylmethionine; the other involving a tRNA-like structure in the intron of the tRNA maturation gene POP1. We experimentally validate the predicted MAT2A structures. Finally, we identify potential new regulatory networks, including large families of short hairpins enriched in immunity-related genes, e.g., TNF, FOS, and CTLA4, which include known transcript destabilizing elements. Our findings exemplify the diversity of post-transcriptional regulation and provide a resource for further characterization of new regulatory mechanisms and families of noncoding RNAs.

Omics Approaches for Identifying Physiological Adaptations to Genome Instability in Aging.

Science.gov (United States)

Edifizi, Diletta; Schumacher, Björn

2017-11-04

DNA damage causally contributes to aging and age-related diseases. The declining functioning of tissues and organs during aging can lead to the increased risk of succumbing to aging-associated diseases. Congenital syndromes that are caused by heritable mutations in DNA repair pathways lead to cancer susceptibility and accelerated aging, thus underlining the importance of genome maintenance for withstanding aging. High-throughput mass-spectrometry-based approaches have recently contributed to identifying signalling response networks and gaining a more comprehensive understanding of the physiological adaptations occurring upon unrepaired DNA damage. The insulin-like signalling pathway has been implicated in a DNA damage response (DDR) network that includes epidermal growth factor (EGF)-, AMP-activated protein kinases (AMPK)- and the target of rapamycin (TOR)-like signalling pathways, which are known regulators of growth, metabolism, and stress responses. The same pathways, together with the autophagy-mediated proteostatic response and the decline in energy metabolism have also been found to be similarly regulated during natural aging, suggesting striking parallels in the physiological adaptation upon persistent DNA damage due to DNA repair defects and long-term low-level DNA damage accumulation occurring during natural aging. These insights will be an important starting point to study the interplay between signalling networks involved in progeroid syndromes that are caused by DNA repair deficiencies and to gain new understanding of the consequences of DNA damage in the aging process.
Characterization of canine osteosarcoma by array comparative genomic hybridization and RT-qPCR: signatures of genomic imbalance in canine osteosarcoma parallel the human counterpart.

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Angstadt, Andrea Y; Motsinger-Reif, Alison; Thomas, Rachael; Kisseberth, William C; Guillermo Couto, C; Duval, Dawn L; Nielsen, Dahlia M; Modiano, Jaime F; Breen, Matthew

2011-11-01

Osteosarcoma (OS) is the most commonly diagnosed malignant bone tumor in humans and dogs, characterized in both species by extremely complex karyotypes exhibiting high frequencies of genomic imbalance. Evaluation of genomic signatures in human OS using array comparative genomic hybridization (aCGH) has assisted in uncovering genetic mechanisms that result in disease phenotype. Previous low-resolution (10-20 Mb) aCGH analysis of canine OS identified a wide range of recurrent DNA copy number aberrations, indicating extensive genomic instability. In this study, we profiled 123 canine OS tumors by 1 Mb-resolution aCGH to generate a dataset for direct comparison with current data for human OS, concluding that several high frequency aberrations in canine and human OS are orthologous. To ensure complete coverage of gene annotation, we identified the human refseq genes that map to these orthologous aberrant dog regions and found several candidate genes warranting evaluation for OS involvement. Specifically, subsequenct FISH and qRT-PCR analysis of RUNX2, TUSC3, and PTEN indicated that expression levels correlated with genomic copy number status, showcasing RUNX2 as an OS associated gene and TUSC3 as a possible tumor suppressor candidate. Together these data demonstrate the ability of genomic comparative oncology to identify genetic abberations which may be important for OS progression. Large scale screening of genomic imbalance in canine OS further validates the use of the dog as a suitable model for human cancers, supporting the idea that dysregulation discovered in canine cancers will provide an avenue for complementary study in human counterparts. Copyright © 2011 Wiley-Liss, Inc.
Genomic agonism and phenotypic antagonism between estrogen and progesterone receptors in breast cancer

OpenAIRE

Singhal, Hari; Greene, Marianne E.; Tarulli, Gerard; Zarnke, Allison L.; Bourgo, Ryan J.; Laine, Muriel; Chang, Ya-Fang; Ma, Shihong; Dembo, Anna G.; Raj, Ganesh V.; Hickey, Theresa E.; Tilley, Wayne D.; Greene, Geoffrey L.

2016-01-01

The functional role of progesterone receptor (PR) and its impact on estrogen signaling in breast cancer remain controversial. In primary ER+ (estrogen receptor?positive)/PR+ human tumors, we report that PR reprograms estrogen signaling as a genomic agonist and a phenotypic antagonist. In isolation, estrogen and progestin act as genomic agonists by regulating the expression of common target genes in similar directions, but at different levels. Similarly, in isolation, progestin is also a weak ...
Somatic mutation load of estrogen receptor-positive breast tumors predicts overall survival: an analysis of genome sequence data.

Science.gov (United States)

Haricharan, Svasti; Bainbridge, Matthew N; Scheet, Paul; Brown, Powel H

2014-07-01

Breast cancer is one of the most commonly diagnosed cancers in women. While there are several effective therapies for breast cancer and important single gene prognostic/predictive markers, more than 40,000 women die from this disease every year. The increasing availability of large-scale genomic datasets provides opportunities for identifying factors that influence breast cancer survival in smaller, well-defined subsets. The purpose of this study was to investigate the genomic landscape of various breast cancer subtypes and its potential associations with clinical outcomes. We used statistical analysis of sequence data generated by the Cancer Genome Atlas initiative including somatic mutation load (SML) analysis, Kaplan-Meier survival curves, gene mutational frequency, and mutational enrichment evaluation to study the genomic landscape of breast cancer. We show that ER(+), but not ER(-), tumors with high SML associate with poor overall survival (HR = 2.02). Further, these high mutation load tumors are enriched for coincident mutations in both DNA damage repair and ER signature genes. While it is known that somatic mutations in specific genes affect breast cancer survival, this study is the first to identify that SML may constitute an important global signature for a subset of ER(+) tumors prone to high mortality. Moreover, although somatic mutations in individual DNA damage genes affect clinical outcome, our results indicate that coincident mutations in DNA damage response and signature ER genes may prove more informative for ER(+) breast cancer survival. Next generation sequencing may prove an essential tool for identifying pathways underlying poor outcomes and for tailoring therapeutic strategies.
Systematic identification of combinatorial drivers and targets in cancer cell lines.

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Adel Tabchy

Full Text Available There is an urgent need to elicit and validate highly efficacious targets for combinatorial intervention from large scale ongoing molecular characterization efforts of tumors. We established an in silico bioinformatic platform in concert with a high throughput screening platform evaluating 37 novel targeted agents in 669 extensively characterized cancer cell lines reflecting the genomic and tissue-type diversity of human cancers, to systematically identify combinatorial biomarkers of response and co-actionable targets in cancer. Genomic biomarkers discovered in a 141 cell line training set were validated in an independent 359 cell line test set. We identified co-occurring and mutually exclusive genomic events that represent potential drivers and combinatorial targets in cancer. We demonstrate multiple cooperating genomic events that predict sensitivity to drug intervention independent of tumor lineage. The coupling of scalable in silico and biologic high throughput cancer cell line platforms for the identification of co-events in cancer delivers rational combinatorial targets for synthetic lethal approaches with a high potential to pre-empt the emergence of resistance.
Systematic identification of combinatorial drivers and targets in cancer cell lines.

Science.gov (United States)

Tabchy, Adel; Eltonsy, Nevine; Housman, David E; Mills, Gordon B

2013-01-01

There is an urgent need to elicit and validate highly efficacious targets for combinatorial intervention from large scale ongoing molecular characterization efforts of tumors. We established an in silico bioinformatic platform in concert with a high throughput screening platform evaluating 37 novel targeted agents in 669 extensively characterized cancer cell lines reflecting the genomic and tissue-type diversity of human cancers, to systematically identify combinatorial biomarkers of response and co-actionable targets in cancer. Genomic biomarkers discovered in a 141 cell line training set were validated in an independent 359 cell line test set. We identified co-occurring and mutually exclusive genomic events that represent potential drivers and combinatorial targets in cancer. We demonstrate multiple cooperating genomic events that predict sensitivity to drug intervention independent of tumor lineage. The coupling of scalable in silico and biologic high throughput cancer cell line platforms for the identification of co-events in cancer delivers rational combinatorial targets for synthetic lethal approaches with a high potential to pre-empt the emergence of resistance.
High throughput sequencing and proteomics to identify immunogenic proteins of a new pathogen: the dirty genome approach.

Science.gov (United States)

Greub, Gilbert; Kebbi-Beghdadi, Carole; Bertelli, Claire; Collyn, François; Riederer, Beat M; Yersin, Camille; Croxatto, Antony; Raoult, Didier

2009-12-23

With the availability of new generation sequencing technologies, bacterial genome projects have undergone a major boost. Still, chromosome completion needs a costly and time-consuming gap closure, especially when containing highly repetitive elements. However, incomplete genome data may be sufficiently informative to derive the pursued information. For emerging pathogens, i.e. newly identified pathogens, lack of release of genome data during gap closure stage is clearly medically counterproductive. We thus investigated the feasibility of a dirty genome approach, i.e. the release of unfinished genome sequences to develop serological diagnostic tools. We showed that almost the whole genome sequence of the emerging pathogen Parachlamydia acanthamoebae was retrieved even with relatively short reads from Genome Sequencer 20 and Solexa. The bacterial proteome was analyzed to select immunogenic proteins, which were then expressed and used to elaborate the first steps of an ELISA. This work constitutes the proof of principle for a dirty genome approach, i.e. the use of unfinished genome sequences of pathogenic bacteria, coupled with proteomics to rapidly identify new immunogenic proteins useful to develop in the future specific diagnostic tests such as ELISA, immunohistochemistry and direct antigen detection. Although applied here to an emerging pathogen, this combined dirty genome sequencing/proteomic approach may be used for any pathogen for which better diagnostics are needed. These genome sequences may also be very useful to develop DNA based diagnostic tests. All these diagnostic tools will allow further evaluations of the pathogenic potential of this obligate intracellular bacterium.
A genome-wide map of aberrantly expressed chromosomal islands in colorectal cancer

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Castanos-Velez Esmeralda

2006-09-01

Full Text Available Abstract Background Cancer development is accompanied by genetic phenomena like deletion and amplification of chromosome parts or alterations of chromatin structure. It is expected that these mechanisms have a strong effect on regional gene expression. Results We investigated genome-wide gene expression in colorectal carcinoma (CRC and normal epithelial tissues from 25 patients using oligonucleotide arrays. This allowed us to identify 81 distinct chromosomal islands with aberrant gene expression. Of these, 38 islands show a gain in expression and 43 a loss of expression. In total, 7.892 genes (25.3% of all human genes are located in aberrantly expressed islands. Many chromosomal regions that are linked to hereditary colorectal cancer show deregulated expression. Also, many known tumor genes localize to chromosomal islands of misregulated expression in CRC. Conclusion An extensive comparison with published CGH data suggests that chromosomal regions known for frequent deletions in colon cancer tend to show reduced expression. In contrast, regions that are often amplified in colorectal tumors exhibit heterogeneous expression patterns: even show a decrease of mRNA expression. Because for several islands of deregulated expression chromosomal aberrations have never been observed, we speculate that additional mechanisms (like abnormal states of regional chromatin also have a substantial impact on the formation of co-expression islands in colorectal carcinoma.
Genome-wide siRNA-based functional genomics of pigmentation identifies novel genes and pathways that impact melanogenesis in human cells.

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Anand K Ganesan

2008-12-01

Full Text Available Melanin protects the skin and eyes from the harmful effects of UV irradiation, protects neural cells from toxic insults, and is required for sound conduction in the inner ear. Aberrant regulation of melanogenesis underlies skin disorders (melasma and vitiligo, neurologic disorders (Parkinson's disease, auditory disorders (Waardenburg's syndrome, and opthalmologic disorders (age related macular degeneration. Much of the core synthetic machinery driving melanin production has been identified; however, the spectrum of gene products participating in melanogenesis in different physiological niches is poorly understood. Functional genomics based on RNA-mediated interference (RNAi provides the opportunity to derive unbiased comprehensive collections of pharmaceutically tractable single gene targets supporting melanin production. In this study, we have combined a high-throughput, cell-based, one-well/one-gene screening platform with a genome-wide arrayed synthetic library of chemically synthesized, small interfering RNAs to identify novel biological pathways that govern melanin biogenesis in human melanocytes. Ninety-two novel genes that support pigment production were identified with a low false discovery rate. Secondary validation and preliminary mechanistic studies identified a large panel of targets that converge on tyrosinase expression and stability. Small molecule inhibition of a family of gene products in this class was sufficient to impair chronic tyrosinase expression in pigmented melanoma cells and UV-induced tyrosinase expression in primary melanocytes. Isolation of molecular machinery known to support autophagosome biosynthesis from this screen, together with in vitro and in vivo validation, exposed a close functional relationship between melanogenesis and autophagy. In summary, these studies illustrate the power of RNAi-based functional genomics to identify novel genes, pathways, and pharmacologic agents that impact a biological phenotype
A novel genomic alteration of LSAMP associates with aggressive prostate cancer in African American men

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Gyorgy Petrovics

2015-12-01

Full Text Available Evaluation of cancer genomes in global context is of great interest in light of changing ethnic distribution of the world population. We focused our study on men of African ancestry because of their disproportionately higher rate of prostate cancer (CaP incidence and mortality. We present a systematic whole genome analyses, revealing alterations that differentiate African American (AA and Caucasian American (CA CaP genomes. We discovered a recurrent deletion on chromosome 3q13.31 centering on the LSAMP locus that was prevalent in tumors from AA men (cumulative analyses of 435 patients: whole genome sequence, 14; FISH evaluations, 101; and SNP array, 320 patients. Notably, carriers of this deletion experienced more rapid disease progression. In contrast, PTEN and ERG common driver alterations in CaP were significantly lower in AA prostate tumors compared to prostate tumors from CA. Moreover, the frequency of inter-chromosomal rearrangements was significantly higher in AA than CA tumors. These findings reveal differentially distributed somatic mutations in CaP across ancestral groups, which have implications for precision medicine strategies.
Benchmark data for identifying N6-methyladenosine sites in the Saccharomyces cerevisiae genome

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Wei Chen

2015-12-01

Full Text Available This data article contains the benchmark dataset for training and testing iRNA-Methyl, a web-server predictor for identifying N6-methyladenosine sites in RNA (Chen et al., 2015 [15]. It can also be used to develop other predictors for identifying N6-methyladenosine sites in the Saccharomyces cerevisiae genome.
Hybrid Capture-Based Comprehensive Genomic Profiling Identifies Lung Cancer Patients with Well-Characterized Sensitizing Epidermal Growth Factor Receptor Point Mutations That Were Not Detected by Standard of Care Testing.

Science.gov (United States)

Suh, James H; Schrock, Alexa B; Johnson, Adrienne; Lipson, Doron; Gay, Laurie M; Ramkissoon, Shakti; Vergilio, Jo-Anne; Elvin, Julia A; Shakir, Abdur; Ruehlman, Peter; Reckamp, Karen L; Ou, Sai-Hong Ignatius; Ross, Jeffrey S; Stephens, Philip J; Miller, Vincent A; Ali, Siraj M

2018-03-14

In our recent study, of cases positive for epidermal growth factor receptor ( EGFR ) exon 19 deletions using comprehensive genomic profiling (CGP), 17/77 (22%) patients with prior standard of care (SOC) EGFR testing results available were previously negative for exon 19 deletion. Our aim was to compare the detection rates of CGP versus SOC testing for well-characterized sensitizing EGFR point mutations (pm) in our 6,832-patient cohort. DNA was extracted from 40 microns of formalin-fixed paraffin-embedded sections from 6,832 consecutive cases of non-small cell lung cancer (NSCLC) of various histologies (2012-2015). CGP was performed using a hybrid capture, adaptor ligation-based next-generation sequencing assay to a mean coverage depth of 576×. Genomic alterations (pm, small indels, copy number changes and rearrangements) involving EGFR were recorded for each case and compared with prior testing results if available. Overall, there were 482 instances of EGFR exon 21 L858R (359) and L861Q (20), exon 18 G719X (73) and exon 20 S768I (30) pm, of which 103 unique cases had prior EGFR testing results that were available for review. Of these 103 cases, CGP identified 22 patients (21%) with sensitizing EGFR pm that were not detected by SOC testing, including 9/75 (12%) patients with L858R, 4/7 (57%) patients with L861Q, 8/20 (40%) patients with G719X, and 4/7 (57%) patients with S768I pm (some patients had multiple EGFR pm). In cases with available clinical data, benefit from small molecule inhibitor therapy was observed. CGP, even when applied to low tumor purity clinical-grade specimens, can detect well-known EGFR pm in NSCLC patients that would otherwise not be detected by SOC testing. Taken together with EGFR exon 19 deletions, over 20% of patients who are positive for EGFR -activating mutations using CGP are previously negative by SOC EGFR mutation testing, suggesting that thousands of such patients per year in the U.S. alone could experience improved clinical
[Utility of chromosome banding with ALU I enzyme for identifying methylated areas in breast cancer].

Science.gov (United States)

Rojas-Atencio, Alicia; Yamarte, Leonard; Urdaneta, Karelis; Soto-Alvarez, Marisol; Alvarez Nava, Francisco; Cañizalez, Jenny; Quintero, Maribel; Atencio, Raquel; González, Richard

2012-12-01

Cancer is a group of disorders characterized by uncontrolled cell growth which is produced by two successive events: increased cell proliferation (tumor or neoplasia) and the invasive capacity of these cells (metastasis). DNA methylation is an epigenetic process which has been involved as an important pathogenic factor of cancer. DNA methylation participates in the regulation of gene expression, directly, by preventing the union of transcription factors, and indirectly, by promoting the "closed" structure of the chromatine. The objectives of this study were to identify hypermethyled chromosomal regions through the use of restriction Alu I endonuclease, and to relate cytogenetically these regions with tumor suppressive gene loci. Sixty peripheral blood samples of females with breast cancer were analyzed. Cell cultures were performed and cytogenetic spreads, previously digested with Alu I enzyme, were stained with Giemsa. Chromosomal centromeric and not centromeric regions were stained in 37% of cases. About 96% of stained hypermethyled chromosomal regions (1q, 2q, 6q) were linked with methylated genes associated with breast cancer. In addition, centromeric regions in chromosomes 3, 4, 8, 13, 14, 15 and 17, usually unstained, were found positive to digestion with Alu I enzime and Giemsa staining. We suggest the importance of this technique for the global visualization of the genome which can find methylated genes related to breast cancer, and thus lead to a specific therapy, and therefore a better therapeutic response.
A genome editing approach to study cancer stem cells in human tumors.

Science.gov (United States)

Cortina, Carme; Turon, Gemma; Stork, Diana; Hernando-Momblona, Xavier; Sevillano, Marta; Aguilera, Mònica; Tosi, Sébastien; Merlos-Suárez, Anna; Stephan-Otto Attolini, Camille; Sancho, Elena; Batlle, Eduard

2017-07-01

The analysis of stem cell hierarchies in human cancers has been hampered by the impossibility of identifying or tracking tumor cell populations in an intact environment. To overcome this limitation, we devised a strategy based on editing the genomes of patient-derived tumor organoids using CRISPR/Cas9 technology to integrate reporter cassettes at desired marker genes. As proof of concept, we engineered human colorectal cancer (CRC) organoids that carry EGFP and lineage-tracing cassettes knocked in the LGR5 locus. Analysis of LGR5-EGFP + cells isolated from organoid-derived xenografts demonstrated that these cells express a gene program similar to that of normal intestinal stem cells and that they propagate the disease to recipient mice very efficiently. Lineage-tracing experiments showed that LGR5 + CRC cells self-renew and generate progeny over long time periods that undergo differentiation toward mucosecreting- and absorptive-like phenotypes. These genetic experiments confirm that human CRCs adopt a hierarchical organization reminiscent of that of the normal colonic epithelium. The strategy described herein may have broad applications to study cell heterogeneity in human tumors. © 2017 The Authors. Published under the terms of the CC BY 4.0 license.
Genome-wide association study identifies multiple risk loci for chronic lymphocytic leukemia

OpenAIRE

Berndt, S.I.; Skibola, C.F.; Joseph, V.; Camp, N.J.; Nieters, A.; Wang, Z.; Cozen, W.; Monnereau, A.; Wang, S.S.; Kelly, R.S.; Lan, Q.; Teras, L.R.; Chatterjee, N.; Chung, C.C.; Yeager, M.

2013-01-01

Genome-wide association studies (GWAS) have previously identified 13 loci associated with risk of chronic lymphocytic leukemia or small lymphocytic lymphoma (CLL). To identify additional CLL susceptibility loci, we conducted the largest meta-analysis for CLL thus far, including four GWAS with a total of 3,100 individuals with CLL (cases) and 7,667 controls. In the meta-analysis, we identified ten independent associated SNPs in nine new loci at 10q23.31 (ACTA2 or FAS (ACTA2/FAS), P = 1.22 × 10...
Genomic alterations in neuroendocrine cancers of the ovary.

Science.gov (United States)

Yaghmour, George; Prouet, Philippe; Wiedower, Eric; Jamy, Omer Hassan; Feldman, Rebecca; Chandler, Jason C; Pandey, Manjari; Martin, Mike G

2016-08-26

As we have previously reported, small cell carcinoma of the ovary (SCCO) is a rare, aggressive form of ovarian cancer associated with poor outcomes. In an effort to identify new treatment options, we utilized comprehensive genomic profiling to assess the potential for novel therapies in SCCO. Patients with SCCO, SCCO-HT (hypercalcemic type), neuroendocrine tumors of the ovary (NET-O), and small cell carcinoma of the lung (SCLC) profiled by Caris Life Sciences between 2007-2015 were identified. Tumors were assessed with up to 21 IHC stains, in situ hybridization of cMET, EGFR, HER2 and PIK3CA, and next-generation sequencing (NGS) as well as Sanger sequencing of selected genes. Forty-six patients with SCCO (10 SCCO, 18 SCCO-HT, 18 NET-O) were identified as well as 58 patients with SCLC for comparison. Patients with SCCO and SCCO-HT were younger (median 42 years [range 12-75] and 26 years [range 8-40], respectively) than patients with NET-O 62 [range 13-76] or SCLC 66 [range 36-86]. SCCO patients were more likely to be metastatic (70 %) than SCCO-HT (50 %) or NET-O (33 %) patients, but at a similar rate to SCLC patients (65 %). PD1 expression varied across tumor type with SCCO (100 %), SCCO-HT (60 %), NET-O (33 %) vs SCLC (42 %). PDL1 expression also varied with SCCO (50 %), SCCO-HT (20 %), NET-O (33 %) and SCLC (0 %). No amplifications were identified in cMET, EGFR, or HER2 and only 1 was found in PIK3CA (NET-O). Actionable mutations were rare with 1 patient with SCCO having a BRCA2 mutation and 1 patient with NET-O having a PIK3CA mutation. No other actionable mutations were identified. No recurrent actionable mutations or rearrangements were identified using this platform in SCCO. IHC patterns may help guide the use of chemotherapy in these rare tumors.
Biomarkers for bladder cancer management: present and future

Science.gov (United States)

Ye, Fei; Wang, Li; Castillo-Martin, Mireia; McBride, Russell; Galsky, Matthew D; Zhu, Jun; Boffetta, Paolo; Zhang, David Y; Cordon-Cardo, Carlos

2014-01-01

Accurate and sensitive detection of bladder cancer is critical to diagnose this deadly disease at an early stage, estimate prognosis, predict response to treatment, and monitor recurrence. In past years, laboratory diagnosis and surveillance of urinary bladder cancer have improved significantly. Although urine cytology remains the gold standard test, many new urinary biomarkers have been identified. Furthermore, recent advances in genomic studies of bladder cancer have helped to refine our understanding of the pathogenesis of the disease, the biological basis for outcome disparities, and to inform more efficient treatment and surveillance strategies. In this article, the established diagnostic tests, newly identified biomarkers and genomic landscape of bladder cancer will be reviewed. PMID:25374904
Identification of a Genomic Signature Predicting for Recurrence in Early Stage Ovarian Cancer

Science.gov (United States)

2015-12-01

do it. Thus, instead of simply sequencing all the FFPE samples, we used 10 tumor samples (5 recurrent and 5 non recurrent ) to test sequencing and...Award Number: W81XWH-12-1-0521 TITLE: Identification of a Genomic Signature Predicting for Recurrence in Early-Stage Ovarian Cancer PRINCIPAL...4. TITLE AND SUBTITLE 5a. CONTRACT NUMBER 5b. GRANT NUMBER W81XWH-12-1-0521 Identification of a Genomic Signature Predicting for Recurrence in
Genetic susceptibility markers for a breast-colorectal cancer phenotype: Exploratory results from genome-wide association studies

Science.gov (United States)

Joon, Aron; Brewster, Abenaa M.; Chen, Wei V.; Eng, Cathy; Shete, Sanjay; Casey, Graham; Schumacher, Fredrick; Lin, Yi; Harrison, Tabitha A.; White, Emily; Ahsan, Habibul; Andrulis, Irene L.; Whittemore, Alice S.; Ko Win, Aung; Schmidt, Daniel F.; Kapuscinski, Miroslaw K.; Ochs-Balcom, Heather M.; Gallinger, Steven; Jenkins, Mark A.; Newcomb, Polly A.; Lindor, Noralane M.; Peters, Ulrike; Amos, Christopher I.; Lynch, Patrick M.

2018-01-01

Background Clustering of breast and colorectal cancer has been observed within some families and cannot be explained by chance or known high-risk mutations in major susceptibility genes. Potential shared genetic susceptibility between breast and colorectal cancer, not explained by high-penetrance genes, has been postulated. We hypothesized that yet undiscovered genetic variants predispose to a breast-colorectal cancer phenotype. Methods To identify variants associated with a breast-colorectal cancer phenotype, we analyzed genome-wide association study (GWAS) data from cases and controls that met the following criteria: cases (n = 985) were women with breast cancer who had one or more first- or second-degree relatives with colorectal cancer, men/women with colorectal cancer who had one or more first- or second-degree relatives with breast cancer, and women diagnosed with both breast and colorectal cancer. Controls (n = 1769), were unrelated, breast and colorectal cancer-free, and age- and sex- frequency-matched to cases. After imputation, 6,220,060 variants were analyzed using the discovery set and variants associated with the breast-colorectal cancer phenotype at Pcolorectal cancer phenotype in the discovery and replication data (most significant; rs7430339, Pdiscovery = 1.2E-04; rs7429100, Preplication = 2.8E-03). In meta-analysis of the discovery and replication data, the most significant association remained at rs7429100 (P = 1.84E-06). Conclusion The results of this exploratory analysis did not find clear evidence for a susceptibility locus with a pleiotropic effect on hereditary breast and colorectal cancer risk, although the suggestive association of genetic variation in the region of ROBO1, a potential tumor suppressor gene, merits further investigation. PMID:29698419
Transcriptomic profiling of curcumin-treated human breast stem cells identifies a role for stearoyl-coa desaturase in breast cancer prevention.

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Colacino, Justin A; McDermott, Sean P; Sartor, Maureen A; Wicha, Max S; Rozek, Laura S

2016-07-01

Curcumin is a potential agent for both the prevention and treatment of cancers. Curcumin treatment alone, or in combination with piperine, limits breast stem cell self-renewal, while remaining non-toxic to normal differentiated cells. We paired fluorescence-activated cell sorting with RNA sequencing to characterize the genome-wide changes induced specifically in normal breast stem cells following treatment with these compounds. We generated genome-wide maps of the transcriptional changes that occur in epithelial-like (ALDH+) and mesenchymal-like (ALDH-/CD44+/CD24-) normal breast stem/progenitor cells following treatment with curcumin and piperine. We show that curcumin targets both stem cell populations by down-regulating expression of breast stem cell genes including ALDH1A3, CD49f, PROM1, and TP63. We also identified novel genes and pathways targeted by curcumin, including downregulation of SCD. Transient siRNA knockdown of SCD in MCF10A cells significantly inhibited mammosphere formation and the mean proportion of CD44+/CD24- cells, suggesting that SCD is a regulator of breast stemness and a target of curcumin in breast stem cells. These findings extend previous reports of curcumin targeting stem cells, here in two phenotypically distinct stem/progenitor populations isolated from normal human breast tissue. We identified novel mechanisms by which curcumin and piperine target breast stem cell self-renewal, such as by targeting lipid metabolism, providing a mechanistic link between curcumin treatment and stem cell self-renewal. These results elucidate the mechanisms by which curcumin may act as a cancer-preventive compound and provide novel targets for cancer prevention and treatment.

Developing Cancer Informatics Applications and Tools Using the NCI Genomic Data Commons API.

Science.gov (United States)

Wilson, Shane; Fitzsimons, Michael; Ferguson, Martin; Heath, Allison; Jensen, Mark; Miller, Josh; Murphy, Mark W; Porter, James; Sahni, Himanso; Staudt, Louis; Tang, Yajing; Wang, Zhining; Yu, Christine; Zhang, Junjun; Ferretti, Vincent; Grossman, Robert L

2017-11-01

The NCI Genomic Data Commons (GDC) was launched in 2016 and makes available over 4 petabytes (PB) of cancer genomic and associated clinical data to the research community. This dataset continues to grow and currently includes over 14,500 patients. The GDC is an example of a biomedical data commons, which collocates biomedical data with storage and computing infrastructure and commonly used web services, software applications, and tools to create a secure, interoperable, and extensible resource for researchers. The GDC is (i) a data repository for downloading data that have been submitted to it, and also a system that (ii) applies a common set of bioinformatics pipelines to submitted data; (iii) reanalyzes existing data when new pipelines are developed; and (iv) allows users to build their own applications and systems that interoperate with the GDC using the GDC Application Programming Interface (API). We describe the GDC API and how it has been used both by the GDC itself and by third parties. Cancer Res; 77(21); e15-18. ©2017 AACR . ©2017 American Association for Cancer Research.
Genome-wide association study identifies 74 loci associated with educational attainment

DEFF Research Database (Denmark)

Okbay, Aysu; P. Beauchamp, Jonathan; Alan Fontana, Mark

2016-01-01

-nucleotide polymorphisms associated with educational attainment are disproportionately found in genomic regions regulating gene expression in the fetal brain. Candidate genes are preferentially expressed in neural tissue, especially during the prenatal period, and enriched for biological pathways involved in neural......Educational attainment is strongly influenced by social and other environmental factors, but genetic factors are estimated to account for at least 20% of the variation across individuals1. Here we report the results of a genome-wide association study (GWAS) for educational attainment that extends...... development. Our findings demonstrate that, even for a behavioural phenotype that is mostly environmentally determined, a well-powered GWAS identifies replicable associated genetic variants that suggest biologically relevant pathways. Because educational attainment is measured in large numbers of individuals...
The Genomic Grade Assay Compared With Ki67 to Determine Risk of Distant Breast Cancer Recurrence

DEFF Research Database (Denmark)

Ignatiadis, Michail; Azim, Hatem A; Desmedt, Christine

2016-01-01

Importance: The Genomic Grade Index (GGI) was previously developed, evaluated on frozen tissue, and shown to be prognostic in early breast cancer. To test the GGI in formalin-fixed, paraffin-embedded breast cancer tumors, a quantitative reverse transcriptase polymerase chain reaction assay...
TMEPAI genome editing in triple negative breast cancer cells

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Bantari W.K. Wardhani

2017-05-01

Full Text Available Background: Clustered regularly interspaced short palindromic repeats/CRISPR-associated 9 (CRISPR/Cas9 is a powerful genome editing technique. It consists of RNA-guided DNA endonuclease Cas9 and single guide RNA (gRNA. By combining their expressions, high efficiency cleavage of the target gene can be achieved, leading to the formation of DNA double-strand break (DSB at the genomic locus of interest which will be repaired via NHEJ (non-homologous end joining or HDR (homology-directed repair and mediate DNA alteration. We aimed to apply the CRISPR/Cas9 technique to knock-out the transmembrane prostate androgen-induced protein (TMEPAI gene in the triple negative breast cancer cell line.Methods: Designed gRNA which targets the TMEPAI gene was synthesized, annealed, and cloned into gRNA expression vector. It was co-transfected into the TNBC cell line using polyethylenimine (PEI together with Cas9-GFP and puromycin resistant gene vector. At 24-hours post-transfection, cells were selected by puromycin for 3 days before they were cloned. Selected knock-out clones were subsequently checked on their protein levels by western blotting.Results: CRISPR/Cas9, a genome engineering technique successfully knocked-out TMEPAI in the Hs578T TNBC cell line. Sequencing shows a frameshift mutation in TMEPAI. Western blot shows the absence of TMEPAI band on Hs578T KO cells.Conclusion: TMEPAI gene was deleted in the TNBC cell line using the genomic editing technique CRISPR/Cas9. The deletion was confirmed by genome and protein analysis.
Genomic, Epigenomic, and Transcriptomic Profiling towards Identifying Omics Features and Specific Biomarkers That Distinguish Uterine Leiomyosarcoma and Leiomyoma at Molecular Levels

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Tomoko Miyata

2015-01-01

Full Text Available Uterine leiomyosarcoma (LMS is the worst malignancy among the gynecologic cancers. Uterine leiomyoma (LM, a benign tumor of myometrial origin, is the most common among women of childbearing age. Because of their similar symptoms, it is difficult to preoperatively distinguish the two conditions only by ultrasound and pelvic MRI. While histopathological diagnosis is currently the main approach used to distinguish them postoperatively, unusual histologic variants of LM tend to be misdiagnosed as LMS. Therefore, development of molecular diagnosis as an alternative or confirmatory means will help to diagnose LMS more accurately. We adopted omics-based technologies to identify genome-wide features to distinguish LMS from LM and revealed that copy number, gene expression, and DNA methylation profiles successfully distinguished these tumors. LMS was found to possess features typically observed in malignant solid tumors, such as extensive chromosomal abnormalities, overexpression of cell cycle-related genes, hypomethylation spreading through large genomic regions, and frequent hypermethylation at the polycomb group target genes and protocadherin genes. We also identified candidate expression and DNA methylation markers, which will facilitate establishing postoperative molecular diagnostic tests based on conventional quantitative assays. Our results demonstrate the feasibility of establishing such tests and the possibility of developing preoperative and noninvasive methods.
High throughput sequencing and proteomics to identify immunogenic proteins of a new pathogen: the dirty genome approach.

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Gilbert Greub

Full Text Available BACKGROUND: With the availability of new generation sequencing technologies, bacterial genome projects have undergone a major boost. Still, chromosome completion needs a costly and time-consuming gap closure, especially when containing highly repetitive elements. However, incomplete genome data may be sufficiently informative to derive the pursued information. For emerging pathogens, i.e. newly identified pathogens, lack of release of genome data during gap closure stage is clearly medically counterproductive. METHODS/PRINCIPAL FINDINGS: We thus investigated the feasibility of a dirty genome approach, i.e. the release of unfinished genome sequences to develop serological diagnostic tools. We showed that almost the whole genome sequence of the emerging pathogen Parachlamydia acanthamoebae was retrieved even with relatively short reads from Genome Sequencer 20 and Solexa. The bacterial proteome was analyzed to select immunogenic proteins, which were then expressed and used to elaborate the first steps of an ELISA. CONCLUSIONS/SIGNIFICANCE: This work constitutes the proof of principle for a dirty genome approach, i.e. the use of unfinished genome sequences of pathogenic bacteria, coupled with proteomics to rapidly identify new immunogenic proteins useful to develop in the future specific diagnostic tests such as ELISA, immunohistochemistry and direct antigen detection. Although applied here to an emerging pathogen, this combined dirty genome sequencing/proteomic approach may be used for any pathogen for which better diagnostics are needed. These genome sequences may also be very useful to develop DNA based diagnostic tests. All these diagnostic tools will allow further evaluations of the pathogenic potential of this obligate intracellular bacterium.
An integrative -omics approach to identify functional sub-networks in human colorectal cancer.

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Rod K Nibbe

2010-01-01

Full Text Available Emerging evidence indicates that gene products implicated in human cancers often cluster together in "hot spots" in protein-protein interaction (PPI networks. Additionally, small sub-networks within PPI networks that demonstrate synergistic differential expression with respect to tumorigenic phenotypes were recently shown to be more accurate classifiers of disease progression when compared to single targets identified by traditional approaches. However, many of these studies rely exclusively on mRNA expression data, a useful but limited measure of cellular activity. Proteomic profiling experiments provide information at the post-translational level, yet they generally screen only a limited fraction of the proteome. Here, we demonstrate that integration of these complementary data sources with a "proteomics-first" approach can enhance the discovery of candidate sub-networks in cancer that are well-suited for mechanistic validation in disease. We propose that small changes in the mRNA expression of multiple genes in the neighborhood of a protein-hub can be synergistically associated with significant changes in the activity of that protein and its network neighbors. Further, we hypothesize that proteomic targets with significant fold change between phenotype and control may be used to "seed" a search for small PPI sub-networks that are functionally associated with these targets. To test this hypothesis, we select proteomic targets having significant expression changes in human colorectal cancer (CRC from two independent 2-D gel-based screens. Then, we use random walk based models of network crosstalk and develop novel reference models to identify sub-networks that are statistically significant in terms of their functional association with these proteomic targets. Subsequently, using an information-theoretic measure, we evaluate synergistic changes in the activity of identified sub-networks based on genome-wide screens of mRNA expression in CRC
Using sheep genomes from diverse U.S. breeds to identify missense variants in genes affecting fecundity

Science.gov (United States)

Background: Access to sheep genome sequences significantly improves the chances of identifying genes that may influence the health, welfare, and productivity of these animals. Methods: A public, searchable DNA sequence resource for U.S. sheep was created with whole genome sequence (WGS) of 96 rams. ...
Large BRCA1 and BRCA2 genomic rearrangements in Danish high risk breast-ovarian cancer families

DEFF Research Database (Denmark)

Hansen, Thomas v O; Jønson, Lars; Albrechtsen, Anders

2009-01-01

BRCA1 and BRCA2 germ-line mutations predispose to breast and ovarian cancer. Large genomic rearrangements of BRCA1 account for 0-36% of all disease causing mutations in various populations, while large genomic rearrangements in BRCA2 are more rare. We examined 642 East Danish breast and/or ovaria...
Genomic and epigenomic analysis of high-risk prostate cancer reveals changes in hydroxymethylation and TET1.

Science.gov (United States)

Spans, Lien; Van den Broeck, Thomas; Smeets, Elien; Prekovic, Stefan; Thienpont, Bernard; Lambrechts, Diether; Karnes, R Jeffrey; Erho, Nicholas; Alshalalfa, Mohammed; Davicioni, Elai; Helsen, Christine; Gevaert, Thomas; Tosco, Lorenzo; Haustermans, Karin; Lerut, Evelyne; Joniau, Steven; Claessens, Frank

2016-04-26

The clinical heterogeneity of prostate cancer (PCa) makes it difficult to identify those patients that could benefit from more aggressive treatments. As a contribution to a better understanding of the genomic changes in the primary tumor that are associated with the development of high-risk disease, we performed exome sequencing and copy number determination of a clinically homogeneous cohort of 47 high-risk PCas. We confirmed recurrent mutations in SPOP, PTEN and TP53 among the 850 point mutations we detected. In seven cases, we discovered genomic aberrations in the TET1 (Ten-Eleven Translocation 1) gene which encodes a DNA hydroxymethylase than can modify methylated cytosines in genomic DNA and thus is linked with gene expression changes. TET1 protein levels were reduced in tumor versus non-tumor prostate tissue in 39 of 40 cases. The clinical relevance of changes in TET1 levels was demonstrated in an independent PCa cohort, in which low TET1 mRNA levels were significantly associated with worse metastases-free survival. We also demonstrate a strong reduction in hydroxymethylated DNA in tumor tissue in 27 of 41 cases. Furthermore, we report the first exploratory (h)MeDIP-Seq analyses of eight high-risk PCa samples. This reveals a large heterogeneity in hydroxymethylation changes in tumor versus non-tumor genomes which can be linked with cell polarity.
Identification of Driving ALK Fusion Genes and Genomic Landscape of Medullary Thyroid Cancer.

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Jun Ho Ji

2015-08-01

Full Text Available The genetic landscape of medullary thyroid cancer (MTC is not yet fully understood, although some oncogenic mutations have been identified. To explore genetic profiles of MTCs, formalin-fixed, paraffin-embedded tumor tissues from MTC patients were assayed on the Ion AmpliSeq Cancer Panel v2. Eighty-four sporadic MTC samples and 36 paired normal thyroid tissues were successfully sequenced. We discovered 101 hotspot mutations in 18 genes in the 84 MTC tissue samples. The most common mutation was in the ret proto-oncogene, which occurred in 47 cases followed by mutations in genes encoding Harvey rat sarcoma viral oncogene homolog (N = 14, serine/threonine kinase 11 (N = 11, v-kit Hardy-Zuckerman 4 feline sarcoma viral oncogene homolog (N = 6, mutL homolog 1 (N = 4, Kiesten rat sarcoma viral oncogene homolog (N = 3 and MET proto-oncogene (N = 3. We also evaluated anaplastic lymphoma kinase (ALK rearrangement by immunohistochemistry and break-apart fluorescence in situ hybridization (FISH. Two of 98 screened cases were positive for ALK FISH. To identify the genomic breakpoint and 5' fusion partner of ALK, customized targeted cancer panel sequencing was performed using DNA from tumor samples of the two patients. Glutamine:fructose-6-phosphate transaminase 1 (GFPT1-ALK and echinoderm microtubule-associated protein-like 4 (EML4-ALK fusions were identified. Additional PCR analysis, followed by Sanger sequencing, confirmed the GFPT1-ALK fusion, indicating that the fusion is a result of intra-chromosomal translocation or deletion. Notably, a metastatic MTC case harboring the EML4-ALK fusion showed a dramatic response to an ALK inhibitor, crizotinib. In conclusion, we found several genetic mutations in MTC and are the first to identify ALK fusions in MTC. Our results suggest that the EML4-ALK fusion in MTC may be a potential driver mutation and a valid target of ALK inhibitors. Furthermore, the GFPT1-ALK fusion may be a potential candidate for molecular
Integrated proteomic and genomic analysis of colorectal cancer

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Investigators who analyzed 95 human colorectal tumor samples have determined how gene alterations identified in previous analyses of the same samples are expressed at the protein level. The integration of proteomic and genomic data, or proteogenomics, pro
Genome-wide association study identified CNP12587 region underlying height variation in Chinese females.

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Yin-Ping Zhang

Full Text Available Human height is a highly heritable trait considered as an important factor for health. There has been limited success in identifying the genetic factors underlying height variation. We aim to identify sequence variants associated with adult height by a genome-wide association study of copy number variants (CNVs in Chinese.Genome-wide CNV association analyses were conducted in 1,625 unrelated Chinese adults and sex specific subgroup for height variation, respectively. Height was measured with a stadiometer. Affymetrix SNP6.0 genotyping platform was used to identify copy number polymorphisms (CNPs. We constructed a genomic map containing 1,009 CNPs in Chinese individuals and performed a genome-wide association study of CNPs with height.We detected 10 significant association signals for height (p<0.05 in the whole population, 9 and 11 association signals for Chinese female and male population, respectively. A copy number polymorphism (CNP12587, chr18:54081842-54086942, p = 2.41 × 10(-4 was found to be significantly associated with height variation in Chinese females even after strict Bonferroni correction (p = 0.048. Confirmatory real time PCR experiments lent further support for CNV validation. Compared to female subjects with two copies of the CNP, carriers of three copies had an average of 8.1% decrease in height. An important candidate gene, ubiquitin-protein ligase NEDD4-like (NEDD4L, was detected at this region, which plays important roles in bone metabolism by binding to bone formation regulators.Our findings suggest the important genetic variants underlying height variation in Chinese.
High-resolution characterization of a hepatocellular carcinoma genome.

Science.gov (United States)

Totoki, Yasushi; Tatsuno, Kenji; Yamamoto, Shogo; Arai, Yasuhito; Hosoda, Fumie; Ishikawa, Shumpei; Tsutsumi, Shuichi; Sonoda, Kohtaro; Totsuka, Hirohiko; Shirakihara, Takuya; Sakamoto, Hiromi; Wang, Linghua; Ojima, Hidenori; Shimada, Kazuaki; Kosuge, Tomoo; Okusaka, Takuji; Kato, Kazuto; Kusuda, Jun; Yoshida, Teruhiko; Aburatani, Hiroyuki; Shibata, Tatsuhiro

2011-05-01

Hepatocellular carcinoma, one of the most common virus-associated cancers, is the third most frequent cause of cancer-related death worldwide. By massively parallel sequencing of a primary hepatitis C virus-positive hepatocellular carcinoma (36× coverage) and matched lymphocytes (>28× coverage) from the same individual, we identified more than 11,000 somatic substitutions of the tumor genome that showed predominance of T>C/A>G transition and a decrease of the T>C substitution on the transcribed strand, suggesting preferential DNA repair. Gene annotation enrichment analysis of 63 validated non-synonymous substitutions revealed enrichment of phosphoproteins. We further validated 22 chromosomal rearrangements, generating four fusion transcripts that had altered transcriptional regulation (BCORL1-ELF4) or promoter activity. Whole-exome sequencing at a higher sequence depth (>76× coverage) revealed a TSC1 nonsense substitution in a subpopulation of the tumor cells. This first high-resolution characterization of a virus-associated cancer genome identified previously uncharacterized mutation patterns, intra-chromosomal rearrangements and fusion genes, as well as genetic heterogeneity within the tumor.
Cancer Epidemiology Data Repository (CEDR)

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In an effort to broaden access and facilitate efficient data sharing, the Epidemiology and Genomics Research Program (EGRP) has created the Cancer Epidemiology Data Repository (CEDR), a centralized, controlled-access database, where Investigators can deposit individual-level de-identified observational cancer datasets.
The Front Line of Genomic Translation

International Nuclear Information System (INIS)

O'Neill, C. S.; McBride, C. M.; Koehly, L. M.; Bryan, A. D.; Wideroff, L.

2012-01-01

Cancer prevention, detection, and treatment represent the front line of genomic translation. Increasingly, new genomic knowledge is being used to inform personalized cancer prevention recommendations and treatment [1-3]. Genomic applications proposed and realized span the full cancer continuum, from cancer prevention and early detection vis a vis genomic risk profiles to motivate behavioral risk reduction and adherence [4] to screening and prophylactic prevention recommendations for high-risk families [5-7], to enhancing cancer survivorship by using genomic tumor profiles to inform treatment decisions and targeted cancer therapies [8, 9]. Yet the utility for many of these applications is as yet unclear and will be influenced heavily by the public’s, patients’, and health care providers’ responses and in numerous other factors, such as health care delivery models [3]. The contributors to this special issue consider various target groups’ responses and contextual factors. To reflect the cancer continuum, the special issue is divided into three broad, overlapping themes-primary prevention, high risk families and family communication and clinical translation.
Genome-wide Analyses Identify KIF5A as a Novel ALS Gene

NARCIS (Netherlands)

Nicolas, Aude; Kenna, Kevin P.; Renton, Alan E.; Ticozzi, Nicola; Faghri, Faraz; Chia, Ruth; Dominov, Janice A.; Kenna, Brendan J.; Nalls, Mike A.; Keagle, Pamela; Rivera, Alberto M.; van Rheenen, Wouter; Murphy, Natalie A.; van Vugt, Joke J.F.A.; Geiger, Joshua T.; van der Spek, Rick; Pliner, Hannah A.; Smith, Bradley N.; Marangi, Giuseppe; Topp, Simon D.; Abramzon, Yevgeniya; Gkazi, Athina Soragia; Eicher, John D.; Kenna, Aoife; Logullo, Francesco O.; Simone, Isabella L.; Logroscino, Giancarlo; Salvi, Fabrizio; Bartolomei, Ilaria; Borghero, Giuseppe; Murru, Maria Rita; Costantino, Emanuela; Pani, Carla; Puddu, Roberta; Caredda, Carla; Piras, Valeria; Tranquilli, Stefania; Cuccu, Stefania; Corongiu, Daniela; Melis, Maurizio; Milia, Antonio; Marrosu, Francesco; Marrosu, Maria Giovanna; Floris, Gianluca; Cannas, Antonino; Capasso, Margherita; Caponnetto, Claudia; Mancardi, Gianluigi; Origone, Paola; Mandich, Paola; Conforti, Francesca L.; Cavallaro, Sebastiano; Mora, Gabriele; Marinou, Kalliopi; Sideri, Riccardo; Penco, Silvana; Mosca, Lorena; Lunetta, Christian; Pinter, Giuseppe Lauria; Corbo, Massimo; Riva, Nilo; Carrera, Paola; Volanti, Paolo; Mandrioli, Jessica; Fini, Nicola; Fasano, Antonio; Tremolizzo, Lucio; Arosio, Alessandro; Ferrarese, Carlo; Trojsi, Francesca; Tedeschi, Gioacchino; Monsurrò, Maria Rosaria; Piccirillo, Giovanni; Femiano, Cinzia; Ticca, Anna; Ortu, Enzo; La Bella, Vincenzo; Spataro, Rossella; Colletti, Tiziana; Sabatelli, Mario; Zollino, Marcella; Conte, Amelia; Luigetti, Marco; Lattante, Serena; Marangi, Giuseppe; Santarelli, Marialuisa; Petrucci, Antonio; Pugliatti, Maura; Pirisi, Angelo; Parish, Leslie D.; Occhineri, Patrizia; Giannini, Fabio; Battistini, Stefania; Ricci, Claudia; Benigni, Michele; Cau, Tea B.; Loi, Daniela; Calvo, Andrea; Moglia, Cristina; Brunetti, Maura; Barberis, Marco; Restagno, Gabriella; Casale, Federico; Marrali, Giuseppe; Fuda, Giuseppe; Ossola, Irene; Cammarosano, Stefania; Canosa, Antonio; Ilardi, Antonio; Manera, Umberto; Grassano, Maurizio; Tanel, Raffaella; Pisano, Fabrizio; Mora, Gabriele; Calvo, Andrea; Mazzini, Letizia; Riva, Nilo; Mandrioli, Jessica; Caponnetto, Claudia; Battistini, Stefania; Volanti, Paolo; La Bella, Vincenzo; Conforti, Francesca L.; Borghero, Giuseppe; Messina, Sonia; Simone, Isabella L.; Trojsi, Francesca; Salvi, Fabrizio; Logullo, Francesco O.; D'Alfonso, Sandra; Corrado, Lucia; Capasso, Margherita; Ferrucci, Luigi; Harms, Matthew B.; Goldstein, David B.; Shneider, Neil A.; Goutman, Stephen A.; Simmons, Zachary; Miller, Timothy M.; Chandran, Siddharthan; Pal, Suvankar; Manousakis, George; Appel, Stanley H.; Simpson, Ericka; Wang, Leo; Baloh, Robert H.; Gibson, Summer B.; Bedlack, Richard; Lacomis, David; Sareen, Dhruv; Sherman, Alexander; Bruijn, Lucie; Penny, Michelle; Moreno, Cristiane de Araujo Martins; Kamalakaran, Sitharthan; Goldstein, David B.; Allen, Andrew S.; Appel, Stanley; Baloh, Robert H.; Bedlack, Richard S.; Boone, Braden E.; Brown, Robert; Carulli, John P.; Chesi, Alessandra; Chung, Wendy K.; Cirulli, Elizabeth T.; Cooper, Gregory M.; Couthouis, Julien; Day-Williams, Aaron G.; Dion, Patrick A.; Gibson, Summer B.; Gitler, Aaron D.; Glass, Jonathan D.; Goldstein, David B.; Han, Yujun; Harms, Matthew B.; Harris, Tim; Hayes, Sebastian D.; Jones, Angela L.; Keebler, Jonathan; Krueger, Brian J.; Lasseigne, Brittany N.; Levy, Shawn E.; Lu, Yi Fan; Maniatis, Tom; McKenna-Yasek, Diane; Miller, Timothy M.; Myers, Richard M.; Petrovski, Slavé; Pulst, Stefan M.; Raphael, Alya R.; Ravits, John M.; Ren, Zhong; Rouleau, Guy A.; Sapp, Peter C.; Shneider, Neil A.; Simpson, Ericka; Sims, Katherine B.; Staropoli, John F.; Waite, Lindsay L.; Wang, Quanli; Wimbish, Jack R.; Xin, Winnie W.; Gitler, Aaron D.; Harris, Tim; Myers, Richard M.; Phatnani, Hemali; Kwan, Justin; Sareen, Dhruv; Broach, James R.; Simmons, Zachary; Arcila-Londono, Ximena; Lee, Edward B.; Van Deerlin, Vivianna M.; Shneider, Neil A.; Fraenkel, Ernest; Ostrow, Lyle W.; Baas, Frank; Zaitlen, Noah; Berry, James D.; Malaspina, Andrea; Fratta, Pietro; Cox, Gregory A.; Thompson, Leslie M.; Finkbeiner, Steve; Dardiotis, Efthimios; Miller, Timothy M.; Chandran, Siddharthan; Pal, Suvankar; Hornstein, Eran; MacGowan, Daniel J.L.; Heiman-Patterson, Terry D.; Hammell, Molly G.; Patsopoulos, Nikolaos A.; Dubnau, Joshua; Nath, Avindra; Phatnani, Hemali; Musunuri, Rajeeva Lochan; Evani, Uday Shankar; Abhyankar, Avinash; Zody, Michael C.; Kaye, Julia; Finkbeiner, Steven; Wyman, Stacia K.; LeNail, Alexander; Lima, Leandro; Fraenkel, Ernest; Rothstein, Jeffrey D.; Svendsen, Clive N.; Thompson, Leslie M.; Van Eyk, Jenny; Maragakis, Nicholas J.; Berry, James D.; Glass, Jonathan D.; Miller, Timothy M.; Kolb, Stephen J.; Baloh, Robert H.; Cudkowicz, Merit; Baxi, Emily; Kaye, Julia; Finkbeiner, Steven; Wyman, Stacia K.; Finkbeiner, Steven; LeNail, Alex; Lima, Leandro; Fraenkel, Ernest; Fraenkel, Ernest; Svendsen, Clive N.; Svendsen, Clive N.; Thompson, Leslie M.; Thompson, Leslie M.; Van Eyk, Jennifer E.; Berry, James D.; Berry, James D.; Miller, Timothy M.; Kolb, Stephen J.; Cudkowicz, Merit; Cudkowicz, Merit; Baxi, Emily; Benatar, Michael; Taylor, J. Paul; Wu, Gang; Rampersaud, Evadnie; Wuu, Joanne; Rademakers, Rosa; Züchner, Stephan; Schule, Rebecca; McCauley, Jacob; Hussain, Sumaira; Cooley, Anne; Wallace, Marielle; Clayman, Christine; Barohn, Richard; Statland, Jeffrey; Ravits, John M.; Swenson, Andrea; Jackson, Carlayne; Trivedi, Jaya; Khan, Shaida; Katz, Jonathan; Jenkins, Liberty; Burns, Ted; Gwathmey, Kelly; Caress, James; McMillan, Corey; Elman, Lauren; Pioro, Erik P.; Heckmann, Jeannine; So, Yuen; Walk, David; Maiser, Samuel; Zhang, Jinghui; Benatar, Michael; Taylor, J. Paul; Taylor, J. Paul; Rampersaud, Evadnie; Wu, Gang; Wuu, Joanne; Silani, Vincenzo; Ticozzi, Nicola; Gellera, Cinzia; Ratti, Antonia; Taroni, Franco; Lauria, Giuseppe; Verde, Federico; Fogh, Isabella; Tiloca, Cinzia; Comi, Giacomo P.; Sorarù, Gianni; Cereda, Cristina; D'Alfonso, Sandra; Corrado, Lucia; De Marchi, Fabiola; Corti, Stefania; Ceroni, Mauro; Mazzini, Letizia; Siciliano, Gabriele; Filosto, Massimiliano; Inghilleri, Maurizio; Peverelli, Silvia; Colombrita, Claudia; Poletti, Barbara; Maderna, Luca; Del Bo, Roberto; Gagliardi, Stella; Querin, Giorgia; Bertolin, Cinzia; Pensato, Viviana; Castellotti, Barbara; Lauria, Giuseppe; Verde, Federico; Fogh, Isabella; Tiloca, Cinzia; Fogh, Isabella; Comi, Giacomo P.; Sorarù, Gianni; Cereda, Cristina; Camu, William; Mouzat, Kevin; Lumbroso, Serge; Corcia, Philippe; Meininger, Vincent; Besson, Gérard; Lagrange, Emmeline; Clavelou, Pierre; Guy, Nathalie; Couratier, Philippe; Vourch, Patrick; Danel, Véronique; Bernard, Emilien; Lemasson, Gwendal; Corcia, Philippe; Laaksovirta, Hannu; Myllykangas, Liisa; Jansson, Lilja; Valori, Miko; Ealing, John; Hamdalla, Hisham; Rollinson, Sara; Pickering-Brown, Stuart; Orrell, Richard W.; Sidle, Katie C.; Malaspina, Andrea; Hardy, John; Singleton, Andrew B.; Johnson, Janel O.; Arepalli, Sampath; Sapp, Peter C.; McKenna-Yasek, Diane; Polak, Meraida; Asress, Seneshaw; Al-Sarraj, Safa; King, Andrew; Troakes, Claire; Vance, Caroline; de Belleroche, Jacqueline; Baas, Frank; ten Asbroek, Anneloor L.M.A.; Muñoz-Blanco, José Luis; Hernandez, Dena G.; Ding, Jinhui; Gibbs, J. Raphael; Scholz, Sonja W.; Scholz, Sonja W.; Floeter, Mary Kay; Campbell, Roy H.; Landi, Francesco; Bowser, Robert; Pulst, Stefan M.; Ravits, John M.; MacGowan, Daniel J.L.; Kirby, Janine; Pioro, Erik P.; Pamphlett, Roger; Broach, James; Gerhard, Glenn; Dunckley, Travis L.; Brady, Christopher B.; Brady, Christopher B.; Kowall, Neil W.; Troncoso, Juan C.; Le Ber, Isabelle; Mouzat, Kevin; Lumbroso, Serge; Mouzat, Kevin; Lumbroso, Serge; Heiman-Patterson, Terry D.; Heiman-Patterson, Terry D.; Kamel, Freya; Van Den Bosch, Ludo; Van Den Bosch, Ludo; Baloh, Robert H.; Strom, Tim M.; Meitinger, Thomas; Strom, Tim M.; Shatunov, Aleksey; Van Eijk, Kristel R.; de Carvalho, Mamede; de Carvalho, Mamede; Kooyman, Maarten; Middelkoop, Bas; Moisse, Matthieu; McLaughlin, Russell; Van Es, Michael A.; Weber, Markus; Boylan, Kevin B.; Van Blitterswijk, Marka; Rademakers, Rosa; Morrison, Karen; Basak, A. Nazli; Mora, Jesús S.; Drory, Vivian; Shaw, Pamela; Turner, Martin R.; Talbot, Kevin; Hardiman, Orla; Williams, Kelly L.; Fifita, Jennifer A.; Nicholson, Garth A.; Blair, Ian P.; Nicholson, Garth A.; Rouleau, Guy A.; Esteban-Pérez, Jesús; García-Redondo, Alberto; Al-Chalabi, Ammar; Al Kheifat, Ahmad; Al-Chalabi, Ammar; Andersen, Peter M.; Basak, A. Nazli; Blair, Ian P.; Chio, Adriano; Cooper-Knock, Jonathan; Corcia, Philippe; Couratier, Philippe; de Carvalho, Mamede; Dekker, Annelot; Drory, Vivian; Redondo, Alberto Garcia; Gotkine, Marc; Hardiman, Orla; Hide, Winston; Iacoangeli, Alfredo; Glass, Jonathan D.; Kenna, Kevin P.; Kiernan, Matthew; Kooyman, Maarten; Landers, John E.; McLaughlin, Russell; Middelkoop, Bas; Mill, Jonathan; Neto, Miguel Mitne; Moisse, Matthieu; Pardina, Jesus Mora; Morrison, Karen; Newhouse, Stephen; Pinto, Susana; Pulit, Sara; Robberecht, Wim; Shatunov, Aleksey; Shaw, Pamela; Shaw, Chris; Silani, Vincenzo; Sproviero, William; Tazelaar, Gijs; Ticozzi, Nicola; Van Damme, Philip; van den Berg, Leonard; van der Spek, Rick; Van Eijk, Kristel R.; Van Es, Michael A.; van Rheenen, Wouter; van Vugt, Joke J.F.A.; Veldink, Jan H.; Weber, Markus; Williams, Kelly L.; Van Damme, Philip; Robberecht, Wim; Zatz, Mayana; Robberecht, Wim; Bauer, Denis C.; Twine, Natalie A.; Rogaeva, Ekaterina; Zinman, Lorne; Ostrow, Lyle W.; Maragakis, Nicholas J.; Rothstein, Jeffrey D.; Simmons, Zachary; Cooper-Knock, Johnathan; Brice, Alexis; Goutman, Stephen A.; Feldman, Eva L.; Gibson, Summer B.; Taroni, Franco; Ratti, Antonia; Ratti, Antonia; Gellera, Cinzia; Van Damme, Philip; Robberecht, Wim; Fratta, Pietro; Sabatelli, Mario; Lunetta, Christian; Ludolph, Albert C.; Andersen, Peter M.; Weishaupt, Jochen H.; Camu, William; Trojanowski, John Q.; Van Deerlin, Vivianna M.; Brown, Robert H.; van den Berg, Leonard; Veldink, Jan H.; Harms, Matthew B.; Glass, Jonathan D.; Stone, David J.; Tienari, Pentti; Silani, Vincenzo; Silani, Vincenzo; Chiò, Adriano; Shaw, Christopher E.; Chiò, Adriano; Traynor, Bryan J.; Landers, John E.; Traynor, Bryan J.

2018-01-01

To identify novel genes associated with ALS, we undertook two lines of investigation. We carried out a genome-wide association study comparing 20,806 ALS cases and 59,804 controls. Independently, we performed a rare variant burden analysis comparing 1,138 index familial ALS cases and 19,494
A colorectal cancer susceptibility new variant at 4q26 in the Spanish population identified by genome-wide association analysis.

Directory of Open Access Journals (Sweden)

Luis M Real

Full Text Available BACKGROUND: Non-hereditary colorectal cancer (CRC is a complex disorder resulting from the combination of genetic and non-genetic factors. Genome-wide association studies (GWAS are useful for identifying such genetic susceptibility factors. However, the single loci so far associated with CRC only represent a fraction of the genetic risk for CRC development in the general population. Therefore, many other genetic risk variants alone and in combination must still remain to be discovered. The aim of this work was to search for genetic risk factors for CRC, by performing single-locus and two-locus GWAS in the Spanish population. RESULTS: A total of 801 controls and 500 CRC cases were included in the discovery GWAS dataset. 77 single nucleotide polymorphisms (SNPs from single-locus and 243 SNPs from two-locus association analyses were selected for replication in 423 additional CRC cases and 1382 controls. In the meta-analysis, one SNP, rs3987 at 4q26, reached GWAS significant p-value (p = 4.02×10(-8, and one SNP pair, rs1100508 CG and rs8111948 AA, showed a trend for two-locus association (p = 4.35×10(-11. Additionally, our GWAS confirmed the previously reported association with CRC of five SNPs located at 3q36.2 (rs10936599, 8q24 (rs10505477, 8q24.21(rs6983267, 11q13.4 (rs3824999 and 14q22.2 (rs4444235. CONCLUSIONS: Our GWAS for CRC patients from Spain confirmed some previously reported associations for CRC and yielded a novel candidate risk SNP, located at 4q26. Epistasis analyses also yielded several novel candidate susceptibility pairs that need to be validated in independent analyses.
Genetic differences in transcript responses to low-dose ionizing radiation identify tissue functions associated with breast cancer susceptibility.

Science.gov (United States)

Snijders, Antoine M; Marchetti, Francesco; Bhatnagar, Sandhya; Duru, Nadire; Han, Ju; Hu, Zhi; Mao, Jian-Hua; Gray, Joe W; Wyrobek, Andrew J

2012-01-01

High dose ionizing radiation (IR) is a well-known risk factor for breast cancer but the health effects after low-dose (LD, differences in their sensitivity to radiation-induced mammary cancer (BALB/c and C57BL/6) for the purpose of identifying mechanisms of mammary cancer susceptibility. Unirradiated mammary and blood tissues of these strains differed significantly in baseline expressions of DNA repair, tumor suppressor, and stress response genes. LD exposures of 7.5 cGy (weekly for 4 weeks) did not induce detectable genomic instability in either strain. However, the mammary glands of the sensitive strain but not the resistant strain showed early transcriptional responses involving: (a) diminished immune response, (b) increased cellular stress, (c) altered TGFβ-signaling, and (d) inappropriate expression of developmental genes. One month after LD exposure, the two strains showed opposing responses in transcriptional signatures linked to proliferation, senescence, and microenvironment functions. We also discovered a pre-exposure expression signature in both blood and mammary tissues that is predictive for poor survival among human cancer patients (p = 0.0001), and a post-LD-exposure signature also predictive for poor patient survival (pidentify genetic features that predispose or protect individuals from LD-induced breast cancer.
Racial and Ethnic Differences in the Epidemiology and Genomics of Lung Cancer.

Science.gov (United States)

Schabath, Matthew B; Cress, Douglas; Munoz-Antonia, Teresita

2016-10-01

Lung cancer is the most common cancer in the world. In addition to the geographical and sex-specific differences in the incidence, mortality, and survival rates of lung cancer, growing evidence suggests that racial and ethnic differences exist. We reviewed published data related to racial and ethnic differences in lung cancer. Current knowledge and substantive findings related to racial and ethnic differences in lung cancer were summarized, focusing on incidence, mortality, survival, cigarette smoking, prevention and early detection, and genomics. Systems-level and health care professional-related issues likely to contribute to specific racial and ethnic health disparities were also reviewed to provide possible suggestions for future strategies to reduce the disproportionate burden of lung cancer. Although lung carcinogenesis is a multifactorial process driven by exogenous exposures, genetic variations, and an accumulation of somatic genetic events, it appears to have racial and ethnic differences that in turn impact the observed epidemiological differences in rates of incidence, mortality, and survival.

Genome-wide Association Study for Ovarian Cancer Susceptibility using Pooled DNA

Science.gov (United States)

Lu, Yi; Chen, Xiaoqing; Beesley, Jonathan; Johnatty, Sharon E.; deFazio, Anna; Lambrechts, Sandrina; Lambrechts, Diether; Despierre, Evelyn; Vergotes, Ignace; Chang-Claude, Jenny; Hein, Rebecca; Nickels, Stefan; Wang-Gohrke, Shan; Dörk, Thilo; Dürst, Matthias; Antonenkova, Natalia; Bogdanova, Natalia; Goodman, Marc T.; Lurie, Galina; Wilkens, Lynne R.; Carney, Michael E.; Butzow, Ralf; Nevanlinna, Heli; Heikkinen, Tuomas; Leminen, Arto; Kiemeney, Lambertus A.; Massuger, Leon F.A.G.; van Altena, Anne M.; Aben, Katja K.; Kjaer, Susanne Krüger; Høgdall, Estrid; Jensen, Allan; Brooks-Wilson, Angela; Le, Nhu; Cook, Linda; Earp, Madalene; Kelemen, Linda; Easton, Douglas; Pharoah, Paul; Song, Honglin; Tyrer, Jonathan; Ramus, Susan; Menon, Usha; Gentry-Maharaj, Alexandra; Gayther, Simon A.; Bandera, Elisa V.; Olson, Sara H.; Orlow, Irene; Rodriguez-Rodriguez, Lorna

2013-01-01

Recent genome-wide association studies (GWAS) have identified four low-penetrance ovarian cancer susceptibility loci. We hypothesized that further moderate or low penetrance variants exist among the subset of SNPs not well tagged by the genotyping arrays used in the previous studies which would account for some of the remaining risk. We therefore conducted a time- and cost-effective stage 1 GWAS on 342 invasive serous cases and 643 controls genotyped on pooled DNA using the high density Illumina 1M-Duo array. We followed up 20 of the most significantly associated SNPs, which are not well tagged by the lower density arrays used by the published GWAS, and genotyping them on individual DNA. Most of the top 20 SNPs were clearly validated by individually genotyping the samples used in the pools. However, none of the 20 SNPs replicated when tested for association in a much larger stage 2 set of 4,651 cases and 6,966 controls from the Ovarian Cancer Association Consortium. Given that most of the top 20 SNPs from pooling were validated in the same samples by individual genotyping, the lack of replication is likely to be due to the relatively small sample size in our stage 1 GWAS rather than due to problems with the pooling approach. We conclude that there are unlikely to be any moderate or large effects on ovarian cancer risk untagged by the less dense arrays. However our study lacked power to make clear statements on the existence of hitherto untagged small effect variants. PMID:22794196
Omics Approaches for Identifying Physiological Adaptations to Genome Instability in Aging

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Diletta Edifizi

2017-11-01

Full Text Available DNA damage causally contributes to aging and age-related diseases. The declining functioning of tissues and organs during aging can lead to the increased risk of succumbing to aging-associated diseases. Congenital syndromes that are caused by heritable mutations in DNA repair pathways lead to cancer susceptibility and accelerated aging, thus underlining the importance of genome maintenance for withstanding aging. High-throughput mass-spectrometry-based approaches have recently contributed to identifying signalling response networks and gaining a more comprehensive understanding of the physiological adaptations occurring upon unrepaired DNA damage. The insulin-like signalling pathway has been implicated in a DNA damage response (DDR network that includes epidermal growth factor (EGF-, AMP-activated protein kinases (AMPK- and the target of rapamycin (TOR-like signalling pathways, which are known regulators of growth, metabolism, and stress responses. The same pathways, together with the autophagy-mediated proteostatic response and the decline in energy metabolism have also been found to be similarly regulated during natural aging, suggesting striking parallels in the physiological adaptation upon persistent DNA damage due to DNA repair defects and long-term low-level DNA damage accumulation occurring during natural aging. These insights will be an important starting point to study the interplay between signalling networks involved in progeroid syndromes that are caused by DNA repair deficiencies and to gain new understanding of the consequences of DNA damage in the aging process.
A prospective pilot study of genome-wide exome and transcriptome profiling in patients with small cell lung cancer progressing after first-line therapy.

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Glen J Weiss

Full Text Available Small cell lung cancer (SCLC that has progressed after first-line therapy is an aggressive disease with few effective therapeutic strategies. In this prospective study, we employed next-generation sequencing (NGS to identify therapeutically actionable alterations to guide treatment for advanced SCLC patients.Twelve patients with SCLC were enrolled after failing platinum-based chemotherapy. Following informed consent, genome-wide exome and RNA-sequencing was performed in a CLIA-certified, CAP-accredited environment. Actionable targets were identified and therapeutic recommendations made from a pharmacopeia of FDA-approved drugs. Clinical response to genomically-guided treatment was evaluated by Response Evaluation Criteria in Solid Tumors (RECIST 1.1.The study completed its accrual goal of 12 evaluable patients. The minimum tumor content for successful NGS was 20%, with a median turnaround time from sample collection to genomics-based treatment recommendation of 27 days. At least two clinically actionable targets were identified in each patient, and six patients (50% received treatment identified by NGS. Two had partial responses by RECIST 1.1 on a clinical trial involving a PD-1 inhibitor + irinotecan (indicated by MLH1 alteration. The remaining patients had clinical deterioration before NGS recommended therapy could be initiated.Comprehensive genomic profiling using NGS identified clinically-actionable alterations in SCLC patients who progressed on initial therapy. Recommended PD-1 therapy generated partial responses in two patients. Earlier access to NGS guided therapy, along with improved understanding of those SCLC patients likely to respond to immune-based therapies, should help to extend survival in these cases with poor outcomes.
A prospective pilot study of genome-wide exome and transcriptome profiling in patients with small cell lung cancer progressing after first-line therapy.

Science.gov (United States)

Weiss, Glen J; Byron, Sara A; Aldrich, Jessica; Sangal, Ashish; Barilla, Heather; Kiefer, Jeffrey A; Carpten, John D; Craig, David W; Whitsett, Timothy G

2017-01-01

Small cell lung cancer (SCLC) that has progressed after first-line therapy is an aggressive disease with few effective therapeutic strategies. In this prospective study, we employed next-generation sequencing (NGS) to identify therapeutically actionable alterations to guide treatment for advanced SCLC patients. Twelve patients with SCLC were enrolled after failing platinum-based chemotherapy. Following informed consent, genome-wide exome and RNA-sequencing was performed in a CLIA-certified, CAP-accredited environment. Actionable targets were identified and therapeutic recommendations made from a pharmacopeia of FDA-approved drugs. Clinical response to genomically-guided treatment was evaluated by Response Evaluation Criteria in Solid Tumors (RECIST) 1.1. The study completed its accrual goal of 12 evaluable patients. The minimum tumor content for successful NGS was 20%, with a median turnaround time from sample collection to genomics-based treatment recommendation of 27 days. At least two clinically actionable targets were identified in each patient, and six patients (50%) received treatment identified by NGS. Two had partial responses by RECIST 1.1 on a clinical trial involving a PD-1 inhibitor + irinotecan (indicated by MLH1 alteration). The remaining patients had clinical deterioration before NGS recommended therapy could be initiated. Comprehensive genomic profiling using NGS identified clinically-actionable alterations in SCLC patients who progressed on initial therapy. Recommended PD-1 therapy generated partial responses in two patients. Earlier access to NGS guided therapy, along with improved understanding of those SCLC patients likely to respond to immune-based therapies, should help to extend survival in these cases with poor outcomes.
Single-molecule optical genome mapping of a human HapMap and a colorectal cancer cell line.

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Teo, Audrey S M; Verzotto, Davide; Yao, Fei; Nagarajan, Niranjan; Hillmer, Axel M

2015-01-01

Next-generation sequencing (NGS) technologies have changed our understanding of the variability of the human genome. However, the identification of genome structural variations based on NGS approaches with read lengths of 35-300 bases remains a challenge. Single-molecule optical mapping technologies allow the analysis of DNA molecules of up to 2 Mb and as such are suitable for the identification of large-scale genome structural variations, and for de novo genome assemblies when combined with short-read NGS data. Here we present optical mapping data for two human genomes: the HapMap cell line GM12878 and the colorectal cancer cell line HCT116. High molecular weight DNA was obtained by embedding GM12878 and HCT116 cells, respectively, in agarose plugs, followed by DNA extraction under mild conditions. Genomic DNA was digested with KpnI and 310,000 and 296,000 DNA molecules (≥ 150 kb and 10 restriction fragments), respectively, were analyzed per cell line using the Argus optical mapping system. Maps were aligned to the human reference by OPTIMA, a new glocal alignment method. Genome coverage of 6.8× and 5.7× was obtained, respectively; 2.9× and 1.7× more than the coverage obtained with previously available software. Optical mapping allows the resolution of large-scale structural variations of the genome, and the scaffold extension of NGS-based de novo assemblies. OPTIMA is an efficient new alignment method; our optical mapping data provide a resource for genome structure analyses of the human HapMap reference cell line GM12878, and the colorectal cancer cell line HCT116.
Providing guidance for genomics-based cancer treatment decisions: insights from stakeholder engagement for post-prostatectomy radiation therapy.

Science.gov (United States)

Abe, James; Lobo, Jennifer M; Trifiletti, Daniel M; Showalter, Timothy N

2017-08-24

Despite the emergence of genomics-based risk prediction tools in oncology, there is not yet an established framework for communication of test results to cancer patients to support shared decision-making. We report findings from a stakeholder engagement program that aimed to develop a framework for using Markov models with individualized model inputs, including genomics-based estimates of cancer recurrence probability, to generate personalized decision aids for prostate cancer patients faced with radiation therapy treatment decisions after prostatectomy. We engaged a total of 22 stakeholders, including: prostate cancer patients, urological surgeons, radiation oncologists, genomic testing industry representatives, and biomedical informatics faculty. Slides were at each meeting to provide background information regarding the analytical framework. Participants were invited to provide feedback during the meeting, including revising the overall project aims. Stakeholder meeting content was reviewed and summarized by stakeholder group and by theme. The majority of stakeholder suggestions focused on aspects of decision aid design and formatting. Stakeholders were enthusiastic about the potential value of using decision analysis modeling with personalized model inputs for cancer recurrence risk, as well as competing risks from age and comorbidities, to generate a patient-centered tool to assist decision-making. Stakeholders did not view privacy considerations as a major barrier to the proposed decision aid program. A common theme was that decision aids should be portable across multiple platforms (electronic and paper), should allow for interaction by the user to adjust model inputs iteratively, and available to patients both before and during consult appointments. Emphasis was placed on the challenge of explaining the model's composite result of quality-adjusted life years. A range of stakeholders provided valuable insights regarding the design of a personalized decision
A genome-wide association study identifies a new ovarian cancer susceptibility locus on 9p22.2

DEFF Research Database (Denmark)

Song, Honglin; Ramus, Susan J; Tyrer, Jonathan

2009-01-01

,817 cases and 2,353 controls from the UK and approximately 2 million imputed SNPs. We genotyped the 22,790 top ranked SNPs in 4,274 cases and 4,809 controls of European ancestry from Europe, USA and Australia. We identified 12 SNPs at 9p22 associated with disease risk (P ... (rs3814113; P = 2.5 x 10(-17)) was genotyped in a further 2,670 ovarian cancer cases and 4,668 controls, confirming its association (combined data odds ratio (OR) = 0.82, 95% confidence interval (CI) 0.79-0.86, P(trend) = 5.1 x 10(-19)). The association differs by histological subtype, being strongest...
Pan-Genome Analysis of Human Gastric Pathogen H. pylori: Comparative Genomics and Pathogenomics Approaches to Identify Regions Associated with Pathogenicity and Prediction of Potential Core Therapeutic Targets

DEFF Research Database (Denmark)

Ali, Amjad; Naz, Anam; Soares, Siomar C.

2015-01-01

-genome approach; the predicted conserved gene families (1,193) constitute similar to 77% of the average H. pylori genome and 45% of the global gene repertoire of the species. Reverse vaccinology strategies have been adopted to identify and narrow down the potential core-immunogenic candidates. Total of 28 nonhost....... Pan-genome analyses of the global representative H. pylori isolates consisting of 39 complete genomes are presented in this paper. Phylogenetic analyses have revealed close relationships among geographically diverse strains of H. pylori. The conservation among these genomes was further analyzed by pan...
Comparing sequencing assays and human-machine analyses in actionable genomics for glioblastoma.

Science.gov (United States)

Wrzeszczynski, Kazimierz O; Frank, Mayu O; Koyama, Takahiko; Rhrissorrakrai, Kahn; Robine, Nicolas; Utro, Filippo; Emde, Anne-Katrin; Chen, Bo-Juen; Arora, Kanika; Shah, Minita; Vacic, Vladimir; Norel, Raquel; Bilal, Erhan; Bergmann, Ewa A; Moore Vogel, Julia L; Bruce, Jeffrey N; Lassman, Andrew B; Canoll, Peter; Grommes, Christian; Harvey, Steve; Parida, Laxmi; Michelini, Vanessa V; Zody, Michael C; Jobanputra, Vaidehi; Royyuru, Ajay K; Darnell, Robert B

2017-08-01

To analyze a glioblastoma tumor specimen with 3 different platforms and compare potentially actionable calls from each. Tumor DNA was analyzed by a commercial targeted panel. In addition, tumor-normal DNA was analyzed by whole-genome sequencing (WGS) and tumor RNA was analyzed by RNA sequencing (RNA-seq). The WGS and RNA-seq data were analyzed by a team of bioinformaticians and cancer oncologists, and separately by IBM Watson Genomic Analytics (WGA), an automated system for prioritizing somatic variants and identifying drugs. More variants were identified by WGS/RNA analysis than by targeted panels. WGA completed a comparable analysis in a fraction of the time required by the human analysts. The development of an effective human-machine interface in the analysis of deep cancer genomic datasets may provide potentially clinically actionable calls for individual patients in a more timely and efficient manner than currently possible. NCT02725684.
A meta-analysis of genome-wide association studies identifies novel variants associated with osteoarthritis of the hip

DEFF Research Database (Denmark)

Evangelou, Evangelos; Kerkhof, Hanneke J; Styrkarsdottir, Unnur

2014-01-01

Osteoarthritis (OA) is the most common form of arthritis with a clear genetic component. To identify novel loci associated with hip OA we performed a meta-analysis of genome-wide association studies (GWAS) on European subjects.......Osteoarthritis (OA) is the most common form of arthritis with a clear genetic component. To identify novel loci associated with hip OA we performed a meta-analysis of genome-wide association studies (GWAS) on European subjects....
Genomewide high-density SNP linkage analysis of non-BRCA1/2 breast cancer families identifies various candidate regions and has greater power than microsatellite studies

Directory of Open Access Journals (Sweden)

Gonzalez-Neira Anna

2007-08-01

Full Text Available Abstract Background The recent development of new high-throughput technologies for SNP genotyping has opened the possibility of taking a genome-wide linkage approach to the search for new candidate genes involved in heredity diseases. The two major breast cancer susceptibility genes BRCA1 and BRCA2 are involved in 30% of hereditary breast cancer cases, but the discovery of additional breast cancer predisposition genes for the non-BRCA1/2 breast cancer families has so far been unsuccessful. Results In order to evaluate the power improvement provided by using SNP markers in a real situation, we have performed a whole genome screen of 19 non-BRCA1/2 breast cancer families using 4720 genomewide SNPs with Illumina technology (Illumina's Linkage III Panel, with an average distance of 615 Kb/SNP. We identified six regions on chromosomes 2, 3, 4, 7, 11 and 14 as candidates to contain genes involved in breast cancer susceptibility, and additional fine mapping genotyping using microsatellite markers around linkage peaks confirmed five of them, excluding the region on chromosome 3. These results were consistent in analyses that excluded SNPs in high linkage disequilibrium. The results were compared with those obtained previously using a 10 cM microsatellite scan (STR-GWS and we found lower or not significant linkage signals with STR-GWS data compared to SNP data in all cases. Conclusion Our results show the power increase that SNPs can supply in linkage studies.
Fine-scale mapping of the 4q24 locus identifies two independent loci associated with breast cancer risk

DEFF Research Database (Denmark)

Guo, Xingyi; Long, Jirong; Zeng, Chenjie

2015-01-01

or enhancer, respectively, of the nearest gene, TET2. Both variants are located in DNase I hypersensitivity and transcription factor-binding sites. Using data from both The Cancer Genome Atlas (TCGA) and Molecular Taxonomy of Breast Cancer International Consortium (METABRIC), we showed that rs62331150...
Leveraging Comparative Genomics to Identify and Functionally Characterize Genes Associated with Sperm Phenotypes in Python bivittatus (Burmese Python

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Kristopher J. L. Irizarry

2016-01-01

Full Text Available Comparative genomics approaches provide a means of leveraging functional genomics information from a highly annotated model organism’s genome (such as the mouse genome in order to make physiological inferences about the role of genes and proteins in a less characterized organism’s genome (such as the Burmese python. We employed a comparative genomics approach to produce the functional annotation of Python bivittatus genes encoding proteins associated with sperm phenotypes. We identify 129 gene-phenotype relationships in the python which are implicated in 10 specific sperm phenotypes. Results obtained through our systematic analysis identified subsets of python genes exhibiting associations with gene ontology annotation terms. Functional annotation data was represented in a semantic scatter plot. Together, these newly annotated Python bivittatus genome resources provide a high resolution framework from which the biology relating to reptile spermatogenesis, fertility, and reproduction can be further investigated. Applications of our research include (1 production of genetic diagnostics for assessing fertility in domestic and wild reptiles; (2 enhanced assisted reproduction technology for endangered and captive reptiles; and (3 novel molecular targets for biotechnology-based approaches aimed at reducing fertility and reproduction of invasive reptiles. Additional enhancements to reptile genomic resources will further enhance their value.
Identification of nine genomic regions of amplification in urothelial carcinoma, correlation with stage, and potential prognostic and therapeutic value.

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Yvonne Chekaluk

Full Text Available We performed a genome wide analysis of 164 urothelial carcinoma samples and 27 bladder cancer cell lines to identify copy number changes associated with disease characteristics, and examined the association of amplification events with stage and grade of disease. Multiplex inversion probe (MIP analysis, a recently developed genomic technique, was used to study 80 urothelial carcinomas to identify mutations and copy number changes. Selected amplification events were then analyzed in a validation cohort of 84 bladder cancers by multiplex ligation-dependent probe assay (MLPA. In the MIP analysis, 44 regions of significant copy number change were identified using GISTIC. Nine gene-containing regions of amplification were selected for validation in the second cohort by MLPA. Amplification events at these 9 genomic regions were found to correlate strongly with stage, being seen in only 2 of 23 (9% Ta grade 1 or 1-2 cancers, in contrast to 31 of 61 (51% Ta grade 3 and T2 grade 2 cancers, p<0.001. These observations suggest that analysis of genomic amplification of these 9 regions might help distinguish non-invasive from invasive urothelial carcinoma, although further study is required. Both MIP and MLPA methods perform well on formalin-fixed paraffin-embedded DNA, enhancing their potential clinical use. Furthermore several of the amplified genes identified here (ERBB2, MDM2, CCND1 are potential therapeutic targets.
Genome-wide association study identifies three novel loci for type 2 diabetes

DEFF Research Database (Denmark)

Hara, Kazuo; Fujita, Hayato; Johnson, Todd A

2014-01-01

Although over 60 loci for type 2 diabetes (T2D) have been identified, there still remains a large genetic component to be clarified. To explore unidentified loci for T2D, we performed a genome-wide association study (GWAS) of 6 209 637 single-nucleotide polymorphisms (SNPs), which were directly g...
4C-ker: A Method to Reproducibly Identify Genome-Wide Interactions Captured by 4C-Seq Experiments.

Science.gov (United States)

Raviram, Ramya; Rocha, Pedro P; Müller, Christian L; Miraldi, Emily R; Badri, Sana; Fu, Yi; Swanzey, Emily; Proudhon, Charlotte; Snetkova, Valentina; Bonneau, Richard; Skok, Jane A

2016-03-01

4C-Seq has proven to be a powerful technique to identify genome-wide interactions with a single locus of interest (or "bait") that can be important for gene regulation. However, analysis of 4C-Seq data is complicated by the many biases inherent to the technique. An important consideration when dealing with 4C-Seq data is the differences in resolution of signal across the genome that result from differences in 3D distance separation from the bait. This leads to the highest signal in the region immediately surrounding the bait and increasingly lower signals in far-cis and trans. Another important aspect of 4C-Seq experiments is the resolution, which is greatly influenced by the choice of restriction enzyme and the frequency at which it can cut the genome. Thus, it is important that a 4C-Seq analysis method is flexible enough to analyze data generated using different enzymes and to identify interactions across the entire genome. Current methods for 4C-Seq analysis only identify interactions in regions near the bait or in regions located in far-cis and trans, but no method comprehensively analyzes 4C signals of different length scales. In addition, some methods also fail in experiments where chromatin fragments are generated using frequent cutter restriction enzymes. Here, we describe 4C-ker, a Hidden-Markov Model based pipeline that identifies regions throughout the genome that interact with the 4C bait locus. In addition, we incorporate methods for the identification of differential interactions in multiple 4C-seq datasets collected from different genotypes or experimental conditions. Adaptive window sizes are used to correct for differences in signal coverage in near-bait regions, far-cis and trans chromosomes. Using several datasets, we demonstrate that 4C-ker outperforms all existing 4C-Seq pipelines in its ability to reproducibly identify interaction domains at all genomic ranges with different resolution enzymes.
4C-ker: A Method to Reproducibly Identify Genome-Wide Interactions Captured by 4C-Seq Experiments.

Directory of Open Access Journals (Sweden)

Ramya Raviram

2016-03-01

Full Text Available 4C-Seq has proven to be a powerful technique to identify genome-wide interactions with a single locus of interest (or "bait" that can be important for gene regulation. However, analysis of 4C-Seq data is complicated by the many biases inherent to the technique. An important consideration when dealing with 4C-Seq data is the differences in resolution of signal across the genome that result from differences in 3D distance separation from the bait. This leads to the highest signal in the region immediately surrounding the bait and increasingly lower signals in far-cis and trans. Another important aspect of 4C-Seq experiments is the resolution, which is greatly influenced by the choice of restriction enzyme and the frequency at which it can cut the genome. Thus, it is important that a 4C-Seq analysis method is flexible enough to analyze data generated using different enzymes and to identify interactions across the entire genome. Current methods for 4C-Seq analysis only identify interactions in regions near the bait or in regions located in far-cis and trans, but no method comprehensively analyzes 4C signals of different length scales. In addition, some methods also fail in experiments where chromatin fragments are generated using frequent cutter restriction enzymes. Here, we describe 4C-ker, a Hidden-Markov Model based pipeline that identifies regions throughout the genome that interact with the 4C bait locus. In addition, we incorporate methods for the identification of differential interactions in multiple 4C-seq datasets collected from different genotypes or experimental conditions. Adaptive window sizes are used to correct for differences in signal coverage in near-bait regions, far-cis and trans chromosomes. Using several datasets, we demonstrate that 4C-ker outperforms all existing 4C-Seq pipelines in its ability to reproducibly identify interaction domains at all genomic ranges with different resolution enzymes.
Investigating core genetic-and-epigenetic cell cycle networks for stemness and carcinogenic mechanisms, and cancer drug design using big database mining and genome-wide next-generation sequencing data.

Science.gov (United States)

Li, Cheng-Wei; Chen, Bor-Sen

2016-10-01

Recent studies have demonstrated that cell cycle plays a central role in development and carcinogenesis. Thus, the use of big databases and genome-wide high-throughput data to unravel the genetic and epigenetic mechanisms underlying cell cycle progression in stem cells and cancer cells is a matter of considerable interest. Real genetic-and-epigenetic cell cycle networks (GECNs) of embryonic stem cells (ESCs) and HeLa cancer cells were constructed by applying system modeling, system identification, and big database mining to genome-wide next-generation sequencing data. Real GECNs were then reduced to core GECNs of HeLa cells and ESCs by applying principal genome-wide network projection. In this study, we investigated potential carcinogenic and stemness mechanisms for systems cancer drug design by identifying common core and specific GECNs between HeLa cells and ESCs. Integrating drug database information with the specific GECNs of HeLa cells could lead to identification of multiple drugs for cervical cancer treatment with minimal side-effects on the genes in the common core. We found that dysregulation of miR-29C, miR-34A, miR-98, and miR-215; and methylation of ANKRD1, ARID5B, CDCA2, PIF1, STAMBPL1, TROAP, ZNF165, and HIST1H2AJ in HeLa cells could result in cell proliferation and anti-apoptosis through NFκB, TGF-β, and PI3K pathways. We also identified 3 drugs, methotrexate, quercetin, and mimosine, which repressed the activated cell cycle genes, ARID5B, STK17B, and CCL2, in HeLa cells with minimal side-effects.
Identifying tagging SNPs for African specific genetic variation from the African Diaspora Genome.

Science.gov (United States)

Johnston, Henry Richard; Hu, Yi-Juan; Gao, Jingjing; O'Connor, Timothy D; Abecasis, Gonçalo R; Wojcik, Genevieve L; Gignoux, Christopher R; Gourraud, Pierre-Antoine; Lizee, Antoine; Hansen, Mark; Genuario, Rob; Bullis, Dave; Lawley, Cindy; Kenny, Eimear E; Bustamante, Carlos; Beaty, Terri H; Mathias, Rasika A; Barnes, Kathleen C; Qin, Zhaohui S

2017-04-21

A primary goal of The Consortium on Asthma among African-ancestry Populations in the Americas (CAAPA) is to develop an 'African Diaspora Power Chip' (ADPC), a genotyping array consisting of tagging SNPs, useful in comprehensively identifying African specific genetic variation. This array is designed based on the novel variation identified in 642 CAAPA samples of African ancestry with high coverage whole genome sequence data (~30× depth). This novel variation extends the pattern of variation catalogued in the 1000 Genomes and Exome Sequencing Projects to a spectrum of populations representing the wide range of West African genomic diversity. These individuals from CAAPA also comprise a large swath of the African Diaspora population and incorporate historical genetic diversity covering nearly the entire Atlantic coast of the Americas. Here we show the results of designing and producing such a microchip array. This novel array covers African specific variation far better than other commercially available arrays, and will enable better GWAS analyses for researchers with individuals of African descent in their study populations. A recent study cataloging variation in continental African populations suggests this type of African-specific genotyping array is both necessary and valuable for facilitating large-scale GWAS in populations of African ancestry.
Exploiting genomic data to identify proteins involved in abalone reproduction.

Science.gov (United States)

Mendoza-Porras, Omar; Botwright, Natasha A; McWilliam, Sean M; Cook, Mathew T; Harris, James O; Wijffels, Gene; Colgrave, Michelle L

2014-08-28

Aside from their critical role in reproduction, abalone gonads serve as an indicator of sexual maturity and energy balance, two key considerations for effective abalone culture. Temperate abalone farmers face issues with tank restocking with highly marketable abalone owing to inefficient spawning induction methods. The identification of key proteins in sexually mature abalone will serve as the foundation for a greater understanding of reproductive biology. Addressing this knowledge gap is the first step towards improving abalone aquaculture methods. Proteomic profiling of female and male gonads of greenlip abalone, Haliotis laevigata, was undertaken using liquid chromatography-mass spectrometry. Owing to the incomplete nature of abalone protein databases, in addition to searching against two publicly available databases, a custom database comprising genomic data was used. Overall, 162 and 110 proteins were identified in females and males respectively with 40 proteins common to both sexes. For proteins involved in sexual maturation, sperm and egg structure, motility, acrosomal reaction and fertilization, 23 were identified only in females, 18 only in males and 6 were common. Gene ontology analysis revealed clear differences between the female and male protein profiles reflecting a higher rate of protein synthesis in the ovary and higher metabolic activity in the testis. A comprehensive mass spectrometry-based analysis was performed to profile the abalone gonad proteome providing the foundation for future studies of reproduction in abalone. Key proteins involved in both reproduction and energy balance were identified. Genomic resources were utilised to build a database of molluscan proteins yielding >60% more protein identifications than in a standard workflow employing public protein databases. Copyright © 2014 Elsevier B.V. All rights reserved.

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