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...

Fenton reaction induced cancer in wild type rats recapitulates genomic alterations observed in human cancer.

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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.

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

Genome-wide DNA Methylation Profiling of Cell-Free Serum DNA in Esophageal Adenocarcinoma and Barrett Esophagus

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Rihong Zhai

2012-01-01

Full Text Available Aberrant DNA methylation (DNAm is a feature of most types of cancers. Genome-wide DNAm profiling has been performed successfully on tumor tissue DNA samples. However, the invasive procedure limits the utility of tumor tissue for epidemiological studies. While recent data indicate that cell-free circulating DNAm (cfDNAm profiles reflect DNAm status in corresponding tumor tissues, no studies have examined the association of cfDNAm with cancer or precursors on a genome-wide scale. The objective of this pilot study was to evaluate the putative significance of genome-wide cfDNAm profiles in esophageal adenocarcinoma (EA and Barrett esophagus (BE, EA precursor. We performed genome-wide DNAm profiling in EA tissue DNA (n = 8 and matched serum DNA (n = 8, in serum DNA of BE (n = 10, and in healthy controls (n = 10 using the Infinium HumanMethylation27 BeadChip that covers 27,578 CpG loci in 14,495 genes. We found that cfDNAm profiles were highly correlated to DNAm profiles in matched tumor tissue DNA (r = 0.92 in patients with EA. We selected the most differentially methylated loci to perform hierarchical clustering analysis. We found that 911 loci can discriminate perfectly between EA and control samples, 554 loci can separate EA from BE samples, and 46 loci can distinguish BE from control samples. These results suggest that genome-wide cfDNAm profiles are highly consistent with DNAm profiles detected in corresponding tumor tissues. Differential cfDNAm profiling may be a useful approach for the noninvasive screening of EA and EA premalignant lesions.

Oncogenomic portals for the visualization and analysis of genome-wide cancer data.

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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 Stability Pathways in Head and Neck Cancers

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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

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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

Association between genomic recurrence risk and well-being among breast cancer patients

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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

Functional genomic mRNA profiling of a large cancer data base demonstrates mesothelin overexpression in a broad range of tumor types.

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Lamberts, Laetitia E; de Groot, Derk Jan A; Bense, Rico D; de Vries, Elisabeth G E; Fehrmann, Rudolf S N

2015-09-29

The membrane bound glycoprotein mesothelin (MSLN) is a highly specific tumor marker, which is currently exploited as target for drugs. There are only limited data available on MSLN expression by human tumors. Therefore we determined overexpression of MSLN across different tumor types with Functional Genomic mRNA (FGM) profiling of a large cancer database. Results were compared with data in articles reporting immunohistochemical (IHC) MSLN tumor expression. FGM profiling is a technique that allows prediction of biologically relevant overexpression of proteins from a robust data set of mRNA microarrays. This technique was used in a database comprising 19,746 tumors to identify for 41 tumor types the percentage of samples with an overexpression of MSLN compared to a normal background. A literature search was performed to compare the FGM profiling data with studies reporting IHC MSLN tumor expression. FGM profiling showed MSLN overexpression in gastrointestinal (12-36%) and gynecological tumors (20-66%), non-small cell lung cancer (21%) and synovial sarcomas (30%). The overexpression found in thyroid cancers (5%) and renal cell cancers (10%) was not yet reported with IHC analyses. We observed that MSLN amplification rate within esophageal cancer depends on the histotype (31% for adenocarcinomas versus 3% for squamous-cell carcinomas). Subset analysis in breast cancer showed MSLN amplification rates of 28% in triple-negative breast cancer (TNBC) and 33% in basal-like breast cancer. Further subtype analysis of TNBCs showed the highest amplification rate (42%) in the basal-like 1 subtype and the lowest amplification rate (9%) in the luminal androgen receptor subtype.

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

Genomic profiling of CHEK2*1100delC-mutated breast carcinomas

International Nuclear Information System (INIS)

Massink, Maarten P. G.; Kooi, Irsan E.; Martens, John W. M.; Waisfisz, Quinten; Meijers-Heijboer, Hanne

2015-01-01

CHEK2*1100delC is a moderate-risk breast cancer susceptibility allele with a high prevalence in the Netherlands. We performed copy number and gene expression profiling to investigate whether CHEK2*1100delC breast cancers harbor characteristic genomic aberrations, as seen for BRCA1 mutated breast cancers. We performed high-resolution SNP array and gene expression profiling of 120 familial breast carcinomas selected from a larger cohort of 155 familial breast tumors, including BRCA1, BRCA2, and CHEK2 mutant tumors. Gene expression analyses based on a mRNA immune signature was used to identify samples with relative low amounts of tumor infiltrating lymphocytes (TILs), which were previously found to disturb tumor copy number and LOH (loss of heterozygosity) profiling. We specifically compared the genomic and gene expression profiles of CHEK2*1100delC breast cancers (n = 14) with BRCAX (familial non-BRCA1/BRCA2/CHEK2*1100delC mutated) breast cancers (n = 34) of the luminal intrinsic subtypes for which both SNP-array and gene expression data is available. High amounts of TILs were found in a relatively small number of luminal breast cancers as compared to breast cancers of the basal-like subtype. As expected, these samples mostly have very few copy number aberrations and no detectable regions of LOH. By unsupervised hierarchical clustering of copy number data we observed a great degree of heterogeneity amongst the CHEK2*1100delC breast cancers, comparable to the BRCAX breast cancers. Furthermore, copy number aberrations were mostly seen at low frequencies in both the CHEK2*1100delC and BRCAX group of breast cancers. However, supervised class comparison identified copy number loss of chromosomal arm 1p to be associated with CHEK2*1100delC status. In conclusion, in contrast to basal-like BRCA1 mutated breast cancers, no apparent specific somatic copy number aberration (CNA) profile for CHEK2*1100delC breast cancers was found. With the possible exception of copy number loss

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

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

Genomic profiling toward precision medicine in non-small cell lung cancer: getting beyond EGFR

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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

Genomic Profiling of Prostate Cancers from African American Men

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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.

Profiles of Genomic Instability in High-Grade Serous Ovarian Cancer Predict Treatment Outcome

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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...

Multi-region and single-cell sequencing reveal variable genomic heterogeneity in rectal cancer.

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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

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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.

Microenvironmental Heterogeneity Parallels Breast Cancer Progression: A Histology-Genomic Integration Analysis.

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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

Distinct gene expression profiles in ovarian cancer linked to Lynch syndrome

DEFF Research Database (Denmark)

Jönsson, Jenny-Maria; Bartuma, Katarina; Dominguez-Valentin, Mev

2014-01-01

Ovarian cancer linked to Lynch syndrome represents a rare subset that typically presents at young age as early-stage tumors with an overrepresentation of endometrioid and clear cell histologies. We investigated the molecular profiles of Lynch syndrome-associated and sporadic ovarian cancer...... with the aim to identify key discriminators and central tumorigenic mechanisms in hereditary ovarian cancer. Global gene expression profiling using whole-genome c-DNA-mediated Annealing, Selection, extension, and Ligation was applied to 48 histopathologically matched Lynch syndrome-associated and sporadic...... ovarian cancers. Lynch syndrome-associated and sporadic ovarian cancers differed by 349 significantly deregulated genes, including PTPRH, BIRC3, SHH and TNFRSF6B. The genes involved were predominantly linked to cell growth, proliferation, and cell-to-cell signaling and interaction. When stratified...

PBX1 Genomic Pioneer Function Drives ERα Signaling Underlying Progression in Breast Cancer

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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

Conditional Selection of Genomic Alterations Dictates Cancer Evolution and Oncogenic Dependencies.

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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.

Profiling cancer

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Ciro, Marco; Bracken, Adrian P; Helin, Kristian

2003-01-01

In the past couple of years, several very exciting studies have demonstrated the enormous power of gene-expression profiling for cancer classification and prediction of patient survival. In addition to promising a more accurate classification of cancer and therefore better treatment of patients......, gene-expression profiling can result in the identification of novel potential targets for cancer therapy and a better understanding of the molecular mechanisms leading to cancer....

Genome Wide Expression Profiling of Cancer Cell Lines Cultured in Microgravity Reveals Significant Dysregulation of Cell Cycle and MicroRNA Gene Networks.

Directory of Open Access Journals (Sweden)

Prasanna Vidyasekar

Full Text Available Zero gravity causes several changes in metabolic and functional aspects of the human body and experiments in space flight have demonstrated alterations in cancer growth and progression. This study reports the genome wide expression profiling of a colorectal cancer cell line-DLD-1, and a lymphoblast leukemic cell line-MOLT-4, under simulated microgravity in an effort to understand central processes and cellular functions that are dysregulated among both cell lines. Altered cell morphology, reduced cell viability and an aberrant cell cycle profile in comparison to their static controls were observed in both cell lines under microgravity. The process of cell cycle in DLD-1 cells was markedly affected with reduced viability, reduced colony forming ability, an apoptotic population and dysregulation of cell cycle genes, oncogenes, and cancer progression and prognostic markers. DNA microarray analysis revealed 1801 (upregulated and 2542 (downregulated genes (>2 fold in DLD-1 cultures under microgravity while MOLT-4 cultures differentially expressed 349 (upregulated and 444 (downregulated genes (>2 fold under microgravity. The loss in cell proliferative capacity was corroborated with the downregulation of the cell cycle process as demonstrated by functional clustering of DNA microarray data using gene ontology terms. The genome wide expression profile also showed significant dysregulation of post transcriptional gene silencing machinery and multiple microRNA host genes that are potential tumor suppressors and proto-oncogenes including MIR22HG, MIR17HG and MIR21HG. The MIR22HG, a tumor-suppressor gene was one of the highest upregulated genes in the microarray data showing a 4.4 log fold upregulation under microgravity. Real time PCR validated the dysregulation in the host gene by demonstrating a 4.18 log fold upregulation of the miR-22 microRNA. Microarray data also showed dysregulation of direct targets of miR-22, SP1, CDK6 and CCNA2.

Glycosyltransferase Gene Expression Profiles Classify Cancer Types and Propose Prognostic Subtypes

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Ashkani, Jahanshah; Naidoo, Kevin J.

2016-05-01

Aberrant glycosylation in tumours stem from altered glycosyltransferase (GT) gene expression but can the expression profiles of these signature genes be used to classify cancer types and lead to cancer subtype discovery? The differential structural changes to cellular glycan structures are predominantly regulated by the expression patterns of GT genes and are a hallmark of neoplastic cell metamorphoses. We found that the expression of 210 GT genes taken from 1893 cancer patient samples in The Cancer Genome Atlas (TCGA) microarray data are able to classify six cancers; breast, ovarian, glioblastoma, kidney, colon and lung. The GT gene expression profiles are used to develop cancer classifiers and propose subtypes. The subclassification of breast cancer solid tumour samples illustrates the discovery of subgroups from GT genes that match well against basal-like and HER2-enriched subtypes and correlates to clinical, mutation and survival data. This cancer type glycosyltransferase gene signature finding provides foundational evidence for the centrality of glycosylation in cancer.

Specific genomic regions are differentially affected by copy number alterations across distinct cancer types, in aggregated cytogenetic data.

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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.

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

Population-based statistical inference for temporal sequence of somatic mutations in cancer genomes.

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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.

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.

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

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

Directory of Open Access Journals (Sweden)

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.

Identifying anti-growth factors for human cancer cell lines through genome-scale metabolic modeling

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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....

MTAP deletion confers enhanced dependency on the PRMT5 arginine methyltransferase in cancer cells | Office of Cancer Genomics

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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.

Initiative for Molecular Profiling and Advanced Cancer Therapy and challenges in the implementation of precision medicine.

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Tsimberidou, Apostolia-Maria

In the last decade, breakthroughs in technology have improved our understanding of genomic, transcriptional, proteomic, epigenetic aberrations and immune mechanisms in carcinogenesis. Genomics and model systems have enabled the validation of novel therapeutic strategies. Based on these developments, in 2007, we initiated the IMPACT (Initiative for Molecular Profiling and Advanced Cancer Therapy) study, the first personalized medicine program for patients with advanced cancer at The University of Texas MD Anderson Cancer Center. We demonstrated that in patients referred for Phase I clinical trials, the use of tumor molecular profiling and treatment with matched targeted therapy was associated with encouraging rates of response, progression-free survival and overall survival compared to non-matched therapy. We are currently conducting IMPACT2, a randomized study evaluating molecular profiling and targeted agents in patients with metastatic cancer. Optimization of innovative biomarker-driven clinical trials that include targeted therapy and/or immunotherapeutic approaches for carefully selected patients will accelerate the development of novel drugs and the implementation of precision medicine. Copyright © 2017 Elsevier Inc. All rights reserved.

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

Integrative Genomics Reveals Mechanisms of Copy Number Alterations Responsible for Transcriptional Deregulation in Colorectal Cancer

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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

Prediction of metastasis from low-malignant breast cancer by gene expression profiling

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Thomassen, Mads; Tan, Qihua; Eiriksdottir, Freyja

2007-01-01

examined in these studies is the low-risk patients for whom outcome is very difficult to predict with currently used methods. These patients do not receive adjuvant treatment according to the guidelines of the Danish Breast Cancer Cooperative Group (DBCG). In this study, 26 tumors from low-risk patients...... with different characteristics and risk, expression-based classification specifically developed in low-risk patients have higher predictive power in this group.......Promising results for prediction of outcome in breast cancer have been obtained by genome wide gene expression profiling. Some studies have suggested that an extensive overtreatment of breast cancer patients might be reduced by risk assessment with gene expression profiling. A patient group hardly...

Molecular profile and copy number analysis of sporadic colorectal cancer in Taiwan

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Li Ling-Hui

2011-06-01

Full Text Available Abstract Background Colorectal cancer (CRC is a major health concern worldwide, and recently becomes the most common cancer in Asia. The case collection of this study is one of the largest sets of CRC in Asia, and serves as representative data for investigating genomic differences between ethnic populations. We took comprehensive and high-resolution approaches to compare the clinicopathologic and genomic profiles of microsatellite instability (MSI vs. microsatellite stability (MSS in Taiwanese sporadic CRCs. Methods 1,173 CRC tumors were collected from the Taiwan population, and sequencing-based microsatellite typing assay was used to determine MSI and MSS. Genome-wide SNP array was used to detect CN alterations in 16 MSI-H and 13 MSS CRCs and CN variations in 424 general controls. Gene expression array was used to evaluate the effects of CN alterations, and quantitative PCR methods were used to replicate the findings in independent clinical samples. Results These 1,173 CRC tumors can be classified into 75 high-frequency MSI (MSI-H (6.4%, 96 low-frequency MSI (8.2% and 1,002 MSS (85.4%. Of the 75 MSI-H tumors, 22 had a BRAF mutation and 51 showed MLH1 promoter hypermethylation. There were distinctive differences in the extent of CN alterations between CRC MSS and MSI-H subtypes (300 Mb vs. 42 Mb per genome, p-value Conclusions Sporadic CRCs with MSI-H displayed distinguishable clinicopathologic features, which differ from those of MSS. Genomic profiling of the two types of sporadic CRCs revealed significant differences in the extent and distribution of CN alterations in the cancer genome. More than half of expressed genes showing CN differences can directly contribute to their expressional diversities, and the biological functions of the genes associated with CN changes in sporadic CRCs warrant further investigation to establish their possible clinical implications.

In vitro analysis of integrated global high-resolution DNA methylation profiling with genomic imbalance and gene expression in osteosarcoma.

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Bekim Sadikovic

Full Text Available Genetic and epigenetic changes contribute to deregulation of gene expression and development of human cancer. Changes in DNA methylation are key epigenetic factors regulating gene expression and genomic stability. Recent progress in microarray technologies resulted in developments of high resolution platforms for profiling of genetic, epigenetic and gene expression changes. OS is a pediatric bone tumor with characteristically high level of numerical and structural chromosomal changes. Furthermore, little is known about DNA methylation changes in OS. Our objective was to develop an integrative approach for analysis of high-resolution epigenomic, genomic, and gene expression profiles in order to identify functional epi/genomic differences between OS cell lines and normal human osteoblasts. A combination of Affymetrix Promoter Tilling Arrays for DNA methylation, Agilent array-CGH platform for genomic imbalance and Affymetrix Gene 1.0 platform for gene expression analysis was used. As a result, an integrative high-resolution approach for interrogation of genome-wide tumour-specific changes in DNA methylation was developed. This approach was used to provide the first genomic DNA methylation maps, and to identify and validate genes with aberrant DNA methylation in OS cell lines. This first integrative analysis of global cancer-related changes in DNA methylation, genomic imbalance, and gene expression has provided comprehensive evidence of the cumulative roles of epigenetic and genetic mechanisms in deregulation of gene expression networks.

The Front Line of Genomic Translation

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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.

CHESS (CgHExpreSS): a comprehensive analysis tool for the analysis of genomic alterations and their effects on the expression profile of the genome.

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Lee, Mikyung; Kim, Yangseok

2009-12-16

Genomic alterations frequently occur in many cancer patients and play important mechanistic roles in the pathogenesis of cancer. Furthermore, they can modify the expression level of genes due to altered copy number in the corresponding region of the chromosome. An accumulating body of evidence supports the possibility that strong genome-wide correlation exists between DNA content and gene expression. Therefore, more comprehensive analysis is needed to quantify the relationship between genomic alteration and gene expression. A well-designed bioinformatics tool is essential to perform this kind of integrative analysis. A few programs have already been introduced for integrative analysis. However, there are many limitations in their performance of comprehensive integrated analysis using published software because of limitations in implemented algorithms and visualization modules. To address this issue, we have implemented the Java-based program CHESS to allow integrative analysis of two experimental data sets: genomic alteration and genome-wide expression profile. CHESS is composed of a genomic alteration analysis module and an integrative analysis module. The genomic alteration analysis module detects genomic alteration by applying a threshold based method or SW-ARRAY algorithm and investigates whether the detected alteration is phenotype specific or not. On the other hand, the integrative analysis module measures the genomic alteration's influence on gene expression. It is divided into two separate parts. The first part calculates overall correlation between comparative genomic hybridization ratio and gene expression level by applying following three statistical methods: simple linear regression, Spearman rank correlation and Pearson's correlation. In the second part, CHESS detects the genes that are differentially expressed according to the genomic alteration pattern with three alternative statistical approaches: Student's t-test, Fisher's exact test and Chi square

Genomic instability--an evolving hallmark of cancer.

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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.

Network analysis of genomic alteration profiles reveals co-altered functional modules and driver genes for glioblastoma.

Science.gov (United States)

Gu, Yunyan; Wang, Hongwei; Qin, Yao; Zhang, Yujing; Zhao, Wenyuan; Qi, Lishuang; Zhang, Yuannv; Wang, Chenguang; Guo, Zheng

2013-03-01

The heterogeneity of genetic alterations in human cancer genomes presents a major challenge to advancing our understanding of cancer mechanisms and identifying cancer driver genes. To tackle this heterogeneity problem, many approaches have been proposed to investigate genetic alterations and predict driver genes at the individual pathway level. However, most of these approaches ignore the correlation of alteration events between pathways and miss many genes with rare alterations collectively contributing to carcinogenesis. Here, we devise a network-based approach to capture the cooperative functional modules hidden in genome-wide somatic mutation and copy number alteration profiles of glioblastoma (GBM) from The Cancer Genome Atlas (TCGA), where a module is a set of altered genes with dense interactions in the protein interaction network. We identify 7 pairs of significantly co-altered modules that involve the main pathways known to be altered in GBM (TP53, RB and RTK signaling pathways) and highlight the striking co-occurring alterations among these GBM pathways. By taking into account the non-random correlation of gene alterations, the property of co-alteration could distinguish oncogenic modules that contain driver genes involved in the progression of GBM. The collaboration among cancer pathways suggests that the redundant models and aggravating models could shed new light on the potential mechanisms during carcinogenesis and provide new indications for the design of cancer therapeutic strategies.

Comparative mRNA and microRNA expression profiling of three genitourinary cancers reveals common hallmarks and cancer-specific molecular events.

Directory of Open Access Journals (Sweden)

Xianxin Li

Full Text Available Genome-wide gene expression profile using deep sequencing technologies can drive the discovery of cancer biomarkers and therapeutic targets. Such efforts are often limited to profiling the expression signature of either mRNA or microRNA (miRNA in a single type of cancer.Here we provided an integrated analysis of the genome-wide mRNA and miRNA expression profiles of three different genitourinary cancers: carcinomas of the bladder, kidney and testis.Our results highlight the general or cancer-specific roles of several genes and miRNAs that may serve as candidate oncogenes or suppressors of tumor development. Further comparative analyses at the systems level revealed that significant aberrations of the cell adhesion process, p53 signaling, calcium signaling, the ECM-receptor and cell cycle pathways, the DNA repair and replication processes and the immune and inflammatory response processes were the common hallmarks of human cancers. Gene sets showing testicular cancer-specific deregulation patterns were mainly implicated in processes related to male reproductive function, and general disruptions of multiple metabolic pathways and processes related to cell migration were the characteristic molecular events for renal and bladder cancer, respectively. Furthermore, we also demonstrated that tumors with the same histological origins and genes with similar functions tended to group together in a clustering analysis. By assessing the correlation between the expression of each miRNA and its targets, we determined that deregulation of 'key' miRNAs may result in the global aberration of one or more pathways or processes as a whole.This systematic analysis deciphered the molecular phenotypes of three genitourinary cancers and investigated their variations at the miRNA level simultaneously. Our results provided a valuable source for future studies and highlighted some promising genes, miRNAs, pathways and processes that may be useful for diagnostic or

Random Subspace Aggregation for Cancer Prediction with Gene Expression Profiles

Directory of Open Access Journals (Sweden)

Liying Yang

2016-01-01

Full Text Available Background. Precisely predicting cancer is crucial for cancer treatment. Gene expression profiles make it possible to analyze patterns between genes and cancers on the genome-wide scale. Gene expression data analysis, however, is confronted with enormous challenges for its characteristics, such as high dimensionality, small sample size, and low Signal-to-Noise Ratio. Results. This paper proposes a method, termed RS_SVM, to predict gene expression profiles via aggregating SVM trained on random subspaces. After choosing gene features through statistical analysis, RS_SVM randomly selects feature subsets to yield random subspaces and training SVM classifiers accordingly and then aggregates SVM classifiers to capture the advantage of ensemble learning. Experiments on eight real gene expression datasets are performed to validate the RS_SVM method. Experimental results show that RS_SVM achieved better classification accuracy and generalization performance in contrast with single SVM, K-nearest neighbor, decision tree, Bagging, AdaBoost, and the state-of-the-art methods. Experiments also explored the effect of subspace size on prediction performance. Conclusions. The proposed RS_SVM method yielded superior performance in analyzing gene expression profiles, which demonstrates that RS_SVM provides a good channel for such biological data.

Quantitative image analysis of cellular heterogeneity in breast tumors complements genomic profiling.

Science.gov (United States)

Yuan, Yinyin; Failmezger, Henrik; Rueda, Oscar M; Ali, H Raza; Gräf, Stefan; Chin, Suet-Feung; Schwarz, Roland F; Curtis, Christina; Dunning, Mark J; Bardwell, Helen; Johnson, Nicola; Doyle, Sarah; Turashvili, Gulisa; Provenzano, Elena; Aparicio, Sam; Caldas, Carlos; Markowetz, Florian

2012-10-24

Solid tumors are heterogeneous tissues composed of a mixture of cancer and normal cells, which complicates the interpretation of their molecular profiles. Furthermore, tissue architecture is generally not reflected in molecular assays, rendering this rich information underused. To address these challenges, we developed a computational approach based on standard hematoxylin and eosin-stained tissue sections and demonstrated its power in a discovery and validation cohort of 323 and 241 breast tumors, respectively. To deconvolute cellular heterogeneity and detect subtle genomic aberrations, we introduced an algorithm based on tumor cellularity to increase the comparability of copy number profiles between samples. We next devised a predictor for survival in estrogen receptor-negative breast cancer that integrated both image-based and gene expression analyses and significantly outperformed classifiers that use single data types, such as microarray expression signatures. Image processing also allowed us to describe and validate an independent prognostic factor based on quantitative analysis of spatial patterns between stromal cells, which are not detectable by molecular assays. Our quantitative, image-based method could benefit any large-scale cancer study by refining and complementing molecular assays of tumor samples.

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

Endometrial and acute myeloid leukemia cancer genomes characterized

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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.

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.

Genomic profiling of oral squamous cell carcinoma by array-based comparative genomic hybridization.

Directory of Open Access Journals (Sweden)

Shunichi Yoshioka

Full Text Available We designed a study to investigate genetic relationships between primary tumors of oral squamous cell carcinoma (OSCC and their lymph node metastases, and to identify genomic copy number aberrations (CNAs related to lymph node metastasis. For this purpose, we collected a total of 42 tumor samples from 25 patients and analyzed their genomic profiles by array-based comparative genomic hybridization. We then compared the genetic profiles of metastatic primary tumors (MPTs with their paired lymph node metastases (LNMs, and also those of LNMs with non-metastatic primary tumors (NMPTs. Firstly, we found that although there were some distinctive differences in the patterns of genomic profiles between MPTs and their paired LNMs, the paired samples shared similar genomic aberration patterns in each case. Unsupervised hierarchical clustering analysis grouped together 12 of the 15 MPT-LNM pairs. Furthermore, similarity scores between paired samples were significantly higher than those between non-paired samples. These results suggested that MPTs and their paired LNMs are composed predominantly of genetically clonal tumor cells, while minor populations with different CNAs may also exist in metastatic OSCCs. Secondly, to identify CNAs related to lymph node metastasis, we compared CNAs between grouped samples of MPTs and LNMs, but were unable to find any CNAs that were more common in LNMs. Finally, we hypothesized that subpopulations carrying metastasis-related CNAs might be present in both the MPT and LNM. Accordingly, we compared CNAs between NMPTs and LNMs, and found that gains of 7p, 8q and 17q were more common in the latter than in the former, suggesting that these CNAs may be involved in lymph node metastasis of OSCC. In conclusion, our data suggest that in OSCCs showing metastasis, the primary and metastatic tumors share similar genomic profiles, and that cells in the primary tumor may tend to metastasize after acquiring metastasis-associated CNAs.

Comprehensive genomic profiling reveals inactivating SMARCA4 mutations and low tumor mutational burden in small cell carcinoma of the ovary, hypercalcemic-type.

Science.gov (United States)

Lin, Douglas I; Chudnovsky, Yakov; Duggan, Bridget; Zajchowski, Deborah; Greenbowe, Joel; Ross, Jeffrey S; Gay, Laurie M; Ali, Siraj M; Elvin, Julia A

2017-12-01

Small cell carcinoma of the ovary, hypercalcemic-type (SCCOHT) is a rare, extremely aggressive neoplasm that usually occurs in young women and is characterized by deleterious germline or somatic SMARCA4 mutations. We performed comprehensive genomic profiling (CGP) to potentially identify additional clinically and pathophysiologically relevant genomic alterations in SCCOHT. CGP assessment of all classes of coding alterations in up to 406 genes commonly altered in cancer and intronic regions for up to 31 genes commonly rearranged in cancer was performed on 18 SCCOHT cases (16 exhibiting classic morphology and 2 cases exhibiting exclusive a large cell variant morphology). In addition, a retrospective database search for clinically advanced ovarian tumors with genomic profiles similar to SCCOHT yielded 3 additional cases originally diagnosed as non-SCCOHT. CGP revealed inactivating SMARCA4 alterations and low tumor mutational burden (TMB) (<6mutations/Mb) in 94% (15/16) of SCCOHT with classic morphology. In contrast, both (2/2) cases exhibiting only large cell variant morphology were hypermutated (TMB scores of 90 and 360mut/Mb) and were wildtype for SMARCA4. In our retrospective search, an index ovarian cancer patient harboring inactivating SMARCA4 alterations, initially diagnosed as endometrioid carcinoma, was re-classified as SCCOHT and responded to an SCCOHT chemotherapy regimen. The vast majority of SCCOHT demonstrate genomic SMARCA4 loss with only rare co-occurring alterations. Our data support a role for CGP in the diagnosis and management of SCCOHT and of other lesions with overlapping histological and clinical features, since identifying the former by genomic profile suggests benefit from an appropriate regimen and treatment decisions, as illustrated by an index patient. Copyright © 2017 Elsevier Inc. All rights reserved.

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.

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

Genomic and Molecular Landscape of DNA Damage Repair Deficiency across The Cancer Genome Atlas

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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

Translating the cancer genome: Going beyond p values

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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.

MicroRNA expression profiles of cancer stem cells in head and neck squamous cell carcinoma

OpenAIRE

YATA, KAZUYA; BEDER, LEVENT BEKIR; TAMAGAWA, SHUNJI; HOTOMI, MUNEKI; HIROHASHI, YOSHIHIKO; GRENMAN, REIDAR; YAMANAKA, NOBORU

2015-01-01

Increasing evidence indicates that cancer stem cells have essential roles in tumor initiation, progression, metastasis and resistance to chemo-radiation. Recent research has pointed out biological importance of microRNAs in cancer stem cell dysregulation. Total number of mature microRNAs in human genome increased to more than 2,500 with the recent up-date of the database. However, currently no information is available regarding microRNA expression profiles of cancer stem cells in head and nec...

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 profiling of the PIWI-interacting RNA-mRNA regulatory networks in epithelial ovarian cancers.

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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).

Genome scale metabolic modeling of cancer

DEFF Research Database (Denmark)

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...

Genomic outlier profile analysis: mixture models, null hypotheses, and nonparametric estimation.

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Ghosh, Debashis; Chinnaiyan, Arul M

2009-01-01

In most analyses of large-scale genomic data sets, differential expression analysis is typically assessed by testing for differences in the mean of the distributions between 2 groups. A recent finding by Tomlins and others (2005) is of a different type of pattern of differential expression in which a fraction of samples in one group have overexpression relative to samples in the other group. In this work, we describe a general mixture model framework for the assessment of this type of expression, called outlier profile analysis. We start by considering the single-gene situation and establishing results on identifiability. We propose 2 nonparametric estimation procedures that have natural links to familiar multiple testing procedures. We then develop multivariate extensions of this methodology to handle genome-wide measurements. The proposed methodologies are compared using simulation studies as well as data from a prostate cancer gene expression study.

Pathway and network analysis of cancer genomes

DEFF Research Database (Denmark)

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...

Computational approaches to identify functional genetic variants in cancer genomes

DEFF Research Database (Denmark)

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....

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.

Global copy number profiling of cancer genomes | Office of Cancer Genomics

Science.gov (United States)

In this article, we introduce a robust and efficient strategy for deriving global and allele-specific copy number alternations (CNA) from cancer whole exome sequencing data based on Log R ratios and B-allele frequencies. Applying the approach to the analysis of over 200 skin cancer samples, we demonstrate its utility for discovering distinct CNA events and for deriving ancillary information such as tumor purity. Availability and implementation: https://github.com/xfwang/CLOSE CONTACT: xuefeng.wang@stonybrook.edu or michael.krauthammer@yale.edu. (Publication Abstract)

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.

Whole genome expression array profiling highlights differences in mucosal defense genes in Barrett's esophagus and esophageal adenocarcinoma.

Directory of Open Access Journals (Sweden)

Derek J Nancarrow

Full Text Available Esophageal adenocarcinoma (EAC has become a major concern in Western countries due to rapid rises in incidence coupled with very poor survival rates. One of the key risk factors for the development of this cancer is the presence of Barrett's esophagus (BE, which is believed to form in response to repeated gastro-esophageal reflux. In this study we performed comparative, genome-wide expression profiling (using Illumina whole-genome Beadarrays on total RNA extracted from esophageal biopsy tissues from individuals with EAC, BE (in the absence of EAC and those with normal squamous epithelium. We combined these data with publically accessible raw data from three similar studies to investigate key gene and ontology differences between these three tissue states. The results support the deduction that BE is a tissue with enhanced glycoprotein synthesis machinery (DPP4, ATP2A3, AGR2 designed to provide strong mucosal defenses aimed at resisting gastro-esophageal reflux. EAC exhibits the enhanced extracellular matrix remodeling (collagens, IGFBP7, PLAU effects expected in an aggressive form of cancer, as well as evidence of reduced expression of genes associated with mucosal (MUC6, CA2, TFF1 and xenobiotic (AKR1C2, AKR1B10 defenses. When our results are compared to previous whole-genome expression profiling studies keratin, mucin, annexin and trefoil factor gene groups are the most frequently represented differentially expressed gene families. Eleven genes identified here are also represented in at least 3 other profiling studies. We used these genes to discriminate between squamous epithelium, BE and EAC within the two largest cohorts using a support vector machine leave one out cross validation (LOOCV analysis. While this method was satisfactory for discriminating squamous epithelium and BE, it demonstrates the need for more detailed investigations into profiling changes between BE and EAC.

Clinical utility of gene expression profiling data for clinical decision-making regarding adjuvant therapy in early stage, node-negative breast cancer: a case report.

Science.gov (United States)

Schuster, Steven R; Pockaj, Barbara A; Bothe, Mary R; David, Paru S; Northfelt, Donald W

2012-09-10

Breast cancer is the most common malignancy among women in the United States with the second highest incidence of cancer-related death following lung cancer. The decision-making process regarding adjuvant therapy is a time intensive dialogue between the patient and her oncologist. There are multiple tools that help individualize the treatment options for a patient. Population-based analysis with Adjuvant! Online and genomic profiling with Oncotype DX are two commonly used tools in patients with early stage, node-negative breast cancer. This case report illustrates a situation in which the population-based prognostic and predictive information differed dramatically from that obtained from genomic profiling and affected the patient's decision. In light of this case, we discuss the benefits and limitations of these tools.

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.

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

Applications of Support Vector Machine (SVM) Learning in Cancer Genomics.

Science.gov (United States)

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.

A Breast Tissue Protein Expression Profile Contributing to Early Parity-Induced Protection Against Breast Cancer

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Christina Marie Gutierrez

2015-11-01

Full Text Available Background/Aims: Early parity reduces breast cancer risk, whereas, late parity and nulliparity increase breast cancer risk. Despite substantial efforts to understand the protective effects of early parity, the precise molecular circuitry responsible for these changes is not yet fully defined. Methods: Here, we have conducted the first study assessing protein expression profiles in normal breast tissue of healthy early parous, late parous, and nulliparous women. Breast tissue biopsies were obtained from 132 healthy parous and nulliparous volunteers. These samples were subjected to global protein expression profiling and immunohistochemistry. GeneSpring and MetaCore bioinformatics analysis software were used to identify protein expression profiles associated with early parity (low risk versus late/nulliparity (high risk. Results: Early parity reduces expression of key proteins involved in mitogenic signaling pathways in breast tissue through down regulation of EGFR1/3, ESR1, AKT1, ATF, Fos, and SRC. Early parity is also characterized by greater genomic stability and reduced tissue inflammation based on differential expression of aurora kinases, p53, RAD52, BRCA1, MAPKAPK-2, ATF-1, ICAM1, and NF-kappaB compared to late and nulli parity. Conclusions: Early parity reduces basal cell proliferation in breast tissue, which translates to enhanced genomic stability, reduced cellular stress/inflammation, and thus reduced breast cancer risk.

TCGA study identifies genomic features of cervical cancer

Science.gov (United States)

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.

Intra-tumor heterogeneity in breast cancer has limited impact on transcriptomic-based molecular profiling.

Science.gov (United States)

Karthik, Govindasamy-Muralidharan; Rantalainen, Mattias; Stålhammar, Gustav; Lövrot, John; Ullah, Ikram; Alkodsi, Amjad; Ma, Ran; Wedlund, Lena; Lindberg, Johan; Frisell, Jan; Bergh, Jonas; Hartman, Johan

2017-11-29

Transcriptomic profiling of breast tumors provides opportunity for subtyping and molecular-based patient stratification. In diagnostic applications the specimen profiled should be representative of the expression profile of the whole tumor and ideally capture properties of the most aggressive part of the tumor. However, breast cancers commonly exhibit intra-tumor heterogeneity at molecular, genomic and in phenotypic level, which can arise during tumor evolution. Currently it is not established to what extent a random sampling approach may influence molecular breast cancer diagnostics. In this study we applied RNA-sequencing to quantify gene expression in 43 pieces (2-5 pieces per tumor) from 12 breast tumors (Cohort 1). We determined molecular subtype and transcriptomic grade for all tumor pieces and analysed to what extent pieces originating from the same tumors are concordant or discordant with each other. Additionally, we validated our finding in an independent cohort consisting of 19 pieces (2-6 pieces per tumor) from 6 breast tumors (Cohort 2) profiled using microarray technique. Exome sequencing was also performed on this cohort, to investigate the extent of intra-tumor genomic heterogeneity versus the intra-tumor molecular subtype classifications. Molecular subtyping was consistent in 11 out of 12 tumors and transcriptomic grade assignments were consistent in 11 out of 12 tumors as well. Molecular subtype predictions revealed consistent subtypes in four out of six patients in this cohort 2. Interestingly, we observed extensive intra-tumor genomic heterogeneity in these tumor pieces but not in their molecular subtype classifications. Our results suggest that macroscopic intra-tumoral transcriptomic heterogeneity is limited and unlikely to have an impact on molecular diagnostics for most patients.

The NCI Genomic Data Commons as an engine for precision medicine.

Science.gov (United States)

Jensen, Mark A; Ferretti, Vincent; Grossman, Robert L; Staudt, Louis M

2017-07-27

The National Cancer Institute Genomic Data Commons (GDC) is an information system for storing, analyzing, and sharing genomic and clinical data from patients with cancer. The recent high-throughput sequencing of cancer genomes and transcriptomes has produced a big data problem that precludes many cancer biologists and oncologists from gleaning knowledge from these data regarding the nature of malignant processes and the relationship between tumor genomic profiles and treatment response. The GDC aims to democratize access to cancer genomic data and to foster the sharing of these data to promote precision medicine approaches to the diagnosis and treatment of cancer.

Human Cancer Models Initiative | Office of Cancer Genomics

Science.gov (United States)

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...

Characterization of genomic alterations in radiation-associated breast cancer among childhood cancer survivors, using comparative genomic hybridization (CGH arrays.

Directory of Open Access Journals (Sweden)

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.

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.

Identification of coding and non-coding mutational hotspots in cancer genomes.

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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

Digestive tumor bank protocol: from surgical specimens to genomic studies of digestive cancers.

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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.

Classification of breast cancer patients using somatic mutation profiles and machine learning approaches.

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Vural, Suleyman; Wang, Xiaosheng; Guda, Chittibabu

2016-08-26

The high degree of heterogeneity observed in breast cancers makes it very difficult to classify the cancer patients into distinct clinical subgroups and consequently limits the ability to devise effective therapeutic strategies. Several classification strategies based on ER/PR/HER2 expression or the expression profiles of a panel of genes have helped, but such methods often produce misleading results due to their dynamic nature. In contrast, somatic DNA mutations are relatively stable and lead to initiation and progression of many sporadic cancers. Hence in this study, we explore the use of gene mutation profiles to classify, characterize and predict the subgroups of breast cancers. We analyzed the whole exome sequencing data from 358 ethnically similar breast cancer patients in The Cancer Genome Atlas (TCGA) project. Somatic and non-synonymous single nucleotide variants identified from each patient were assigned a quantitative score (C-score) that represents the extent of negative impact on the gene function. Using these scores with non-negative matrix factorization method, we clustered the patients into three subgroups. By comparing the clinical stage of patients, we identified an early-stage-enriched and a late-stage-enriched subgroup. Comparison of the mutation scores of early and late-stage-enriched subgroups identified 358 genes that carry significantly higher mutations rates in the late stage subgroup. Functional characterization of these genes revealed important functional gene families that carry a heavy mutational load in the late state rich subgroup of patients. Finally, using the identified subgroups, we also developed a supervised classification model to predict the stage of the patients. This study demonstrates that gene mutation profiles can be effectively used with unsupervised machine-learning methods to identify clinically distinguishable breast cancer subgroups. The classification model developed in this method could provide a reasonable

Cancer Genomics: Diversity and Disparity Across Ethnicity and Geography.

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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.

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.

Comprehensive Genomic Profiling of 282 Pediatric Low- and High-Grade Gliomas Reveals Genomic Drivers, Tumor Mutational Burden, and Hypermutation Signatures.

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Johnson, Adrienne; Severson, Eric; Gay, Laurie; Vergilio, Jo-Anne; Elvin, Julia; Suh, James; Daniel, Sugganth; Covert, Mandy; Frampton, Garrett M; Hsu, Sigmund; Lesser, Glenn J; Stogner-Underwood, Kimberly; Mott, Ryan T; Rush, Sarah Z; Stanke, Jennifer J; Dahiya, Sonika; Sun, James; Reddy, Prasanth; Chalmers, Zachary R; Erlich, Rachel; Chudnovsky, Yakov; Fabrizio, David; Schrock, Alexa B; Ali, Siraj; Miller, Vincent; Stephens, Philip J; Ross, Jeffrey; Crawford, John R; Ramkissoon, Shakti H

2017-12-01

Pediatric brain tumors are the leading cause of death for children with cancer in the U.S. Incorporating next-generation sequencing data for both pediatric low-grade (pLGGs) and high-grade gliomas (pHGGs) can inform diagnostic, prognostic, and therapeutic decision-making. We performed comprehensive genomic profiling on 282 pediatric gliomas (157 pHGGs, 125 pLGGs), sequencing 315 cancer-related genes and calculating the tumor mutational burden (TMB; mutations per megabase [Mb]). In pLGGs, we detected genomic alterations (GA) in 95.2% (119/125) of tumors. BRAF was most frequently altered (48%; 60/125), and FGFR1 missense (17.6%; 22/125), NF1 loss of function (8.8%; 11/125), and TP53 (5.6%; 7/125) mutations were also detected. Rearrangements were identified in 35% of pLGGs, including KIAA1549-BRAF , QKI-RAF1 , FGFR3-TACC3 , CEP85L-ROS1 , and GOPC-ROS1 fusions. Among pHGGs, GA were identified in 96.8% (152/157). The genes most frequently mutated were TP53 (49%; 77/157), H3F3A (37.6%; 59/157), ATRX (24.2%; 38/157), NF1 (22.2%; 35/157), and PDGFRA (21.7%; 34/157). Interestingly, most H3F3A mutations (81.4%; 35/43) were the variant K28M. Midline tumor analysis revealed H3F3A mutations (40%; 40/100) consisted solely of the K28M variant. Pediatric high-grade gliomas harbored oncogenic EML4-ALK , DGKB-ETV1 , ATG7-RAF1 , and EWSR1-PATZ1 fusions. Six percent (9/157) of pHGGs were hypermutated (TMB >20 mutations per Mb; range 43-581 mutations per Mb), harboring mutations deleterious for DNA repair in MSH6, MSH2, MLH1, PMS2, POLE , and POLD1 genes (78% of cases). Comprehensive genomic profiling of pediatric gliomas provides objective data that promote diagnostic accuracy and enhance clinical decision-making. Additionally, TMB could be a biomarker to identify pediatric glioblastoma (GBM) patients who may benefit from immunotherapy. By providing objective data to support diagnostic, prognostic, and therapeutic decision-making, comprehensive genomic profiling is necessary for

Genome-wide alterations of the DNA replication program during tumor progression

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Arneodo, A.; Goldar, A.; Argoul, F.; Hyrien, O.; Audit, B.

2016-08-01

Oncogenic stress is a major driving force in the early stages of cancer development. Recent experimental findings reveal that, in precancerous lesions and cancers, activated oncogenes may induce stalling and dissociation of DNA replication forks resulting in DNA damage. Replication timing is emerging as an important epigenetic feature that recapitulates several genomic, epigenetic and functional specificities of even closely related cell types. There is increasing evidence that chromosome rearrangements, the hallmark of many cancer genomes, are intimately associated with the DNA replication program and that epigenetic replication timing changes often precede chromosomic rearrangements. The recent development of a novel methodology to map replication fork polarity using deep sequencing of Okazaki fragments has provided new and complementary genome-wide replication profiling data. We review the results of a wavelet-based multi-scale analysis of genomic and epigenetic data including replication profiles along human chromosomes. These results provide new insight into the spatio-temporal replication program and its dynamics during differentiation. Here our goal is to bring to cancer research, the experimental protocols and computational methodologies for replication program profiling, and also the modeling of the spatio-temporal replication program. To illustrate our purpose, we report very preliminary results obtained for the chronic myelogeneous leukemia, the archetype model of cancer. Finally, we discuss promising perspectives on using genome-wide DNA replication profiling as a novel efficient tool for cancer diagnosis, prognosis and personalized treatment.

Different Array CGH profiles within hereditary breast cancer tumors associated to BRCA1 expression and overall survival

International Nuclear Information System (INIS)

Alvarez, Carolina; Aravena, Andrés; Tapia, Teresa; Rozenblum, Ester; Solís, Luisa; Corvalán, Alejandro; Camus, Mauricio; Alvarez, Manuel; Munroe, David; Maass, Alejandro; Carvallo, Pilar

2016-01-01

Array CGH analysis of breast tumors has contributed to the identification of different genomic profiles in these tumors. Loss of DNA repair by BRCA1 functional deficiency in breast cancer has been proposed as a relevant contribution to breast cancer progression for tumors with no germline mutation. Identifying the genomic alterations taking place in BRCA1 not expressing tumors will lead us to a better understanding of the cellular functions affected in this heterogeneous disease. Moreover, specific genomic alterations may contribute to the identification of potential therapeutic targets and offer a more personalized treatment to breast cancer patients. Forty seven tumors from hereditary breast cancer cases, previously analyzed for BRCA1 expression, and screened for germline BRCA1 and 2 mutations, were analyzed by Array based Comparative Genomic Hybridization (aCGH) using Agilent 4x44K arrays. Overall survival was established for tumors in different clusters using Log-rank (Mantel-Cox) Test. Gene lists obtained from aCGH analysis were analyzed for Gene Ontology enrichment using GOrilla and DAVID tools. Genomic profiling of the tumors showed specific alterations associated to BRCA1 or 2 mutation status, and BRCA1 expression in the tumors, affecting relevant cellular processes. Similar cellular functions were found affected in BRCA1 not expressing and BRCA1 or 2 mutated tumors. Hierarchical clustering classified hereditary breast tumors in four major, groups according to the type and amount of genomic alterations, showing one group with a significantly poor overall survival (p = 0.0221). Within this cluster, deletion of PLEKHO1, GDF11, DARC, DAG1 and CD63 may be associated to the worse outcome of the patients. These results support the fact that BRCA1 lack of expression in tumors should be used as a marker for BRCAness and to select these patients for synthetic lethality approaches such as treatment with PARP inhibitors. In addition, the identification of specific

Simultaneous genomic identification and profiling of a single cell using semiconductor-based next generation sequencing

Directory of Open Access Journals (Sweden)

Manabu Watanabe

2014-09-01

Full Text Available Combining single-cell methods and next-generation sequencing should provide a powerful means to understand single-cell biology and obviate the effects of sample heterogeneity. Here we report a single-cell identification method and seamless cancer gene profiling using semiconductor-based massively parallel sequencing. A549 cells (adenocarcinomic human alveolar basal epithelial cell line were used as a model. Single-cell capture was performed using laser capture microdissection (LCM with an Arcturus® XT system, and a captured single cell and a bulk population of A549 cells (≈106 cells were subjected to whole genome amplification (WGA. For cell identification, a multiplex PCR method (AmpliSeq™ SNP HID panel was used to enrich 136 highly discriminatory SNPs with a genotype concordance probability of 1031–35. For cancer gene profiling, we used mutation profiling that was performed in parallel using a hotspot panel for 50 cancer-related genes. Sequencing was performed using a semiconductor-based bench top sequencer. The distribution of sequence reads for both HID and Cancer panel amplicons was consistent across these samples. For the bulk population of cells, the percentages of sequence covered at coverage of more than 100× were 99.04% for the HID panel and 98.83% for the Cancer panel, while for the single cell percentages of sequence covered at coverage of more than 100× were 55.93% for the HID panel and 65.96% for the Cancer panel. Partial amplification failure or randomly distributed non-amplified regions across samples from single cells during the WGA procedures or random allele drop out probably caused these differences. However, comparative analyses showed that this method successfully discriminated a single A549 cancer cell from a bulk population of A549 cells. Thus, our approach provides a powerful means to overcome tumor sample heterogeneity when searching for somatic mutations.

Value-based genomics.

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Gong, Jun; Pan, Kathy; Fakih, Marwan; Pal, Sumanta; Salgia, Ravi

2018-03-20

Advancements in next-generation sequencing have greatly enhanced the development of biomarker-driven cancer therapies. The affordability and availability of next-generation sequencers have allowed for the commercialization of next-generation sequencing platforms that have found widespread use for clinical-decision making and research purposes. Despite the greater availability of tumor molecular profiling by next-generation sequencing at our doorsteps, the achievement of value-based care, or improving patient outcomes while reducing overall costs or risks, in the era of precision oncology remains a looming challenge. In this review, we highlight available data through a pre-established and conceptualized framework for evaluating value-based medicine to assess the cost (efficiency), clinical benefit (effectiveness), and toxicity (safety) of genomic profiling in cancer care. We also provide perspectives on future directions of next-generation sequencing from targeted panels to whole-exome or whole-genome sequencing and describe potential strategies needed to attain value-based genomics.

Radiogenomics of High-Grade Serous Ovarian Cancer: Multireader Multi-Institutional Study from the Cancer Genome Atlas Ovarian Cancer Imaging Research Group.

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Vargas, Hebert Alberto; Huang, Erich P; Lakhman, Yulia; Ippolito, Joseph E; Bhosale, Priya; Mellnick, Vincent; Shinagare, Atul B; Anello, Maria; Kirby, Justin; Fevrier-Sullivan, Brenda; Freymann, John; Jaffe, C Carl; Sala, Evis

2017-11-01

Purpose To evaluate interradiologist agreement on assessments of computed tomography (CT) imaging features of high-grade serous ovarian cancer (HGSOC), to assess their associations with time-to-disease progression (TTP) and HGSOC transcriptomic profiles (Classification of Ovarian Cancer [CLOVAR]), and to develop an imaging-based risk score system to predict TTP and CLOVAR profiles. Materials and Methods This study was a multireader, multi-institutional, institutional review board-approved, HIPAA-compliant retrospective analysis of 92 patients with HGSOC (median age, 61 years) with abdominopelvic CT before primary cytoreductive surgery available through the Cancer Imaging Archive. Eight radiologists from the Cancer Genome Atlas Ovarian Cancer Imaging Research Group developed and independently recorded the following CT features: characteristics of primary ovarian mass(es), presence of definable mesenteric implants and infiltration, presence of other implants, presence and distribution of peritoneal spread, presence and size of pleural effusions and ascites, lymphadenopathy, and distant metastases. Interobserver agreement for CT features was assessed, as were univariate and multivariate associations with TTP and CLOVAR mesenchymal profile (worst prognosis). Results Interobserver agreement for some features was strong (eg, α = .78 for pleural effusion and ascites) but was lower for others (eg, α = .08 for intraparenchymal splenic metastases). Presence of peritoneal disease in the right upper quadrant (P = .0003), supradiaphragmatic lymphadenopathy (P = .0004), more peritoneal disease sites (P = .0006), and nonvisualization of a discrete ovarian mass (P = .0037) were associated with shorter TTP. More peritoneal disease sites (P = .0025) and presence of pouch of Douglas implants (P = .0045) were associated with CLOVAR mesenchymal profile. Combinations of imaging features contained predictive signal for TTP (concordance index = 0.658; P = .0006) and CLOVAR profile (mean

Comprehensive Genomic Profiling of Esthesioneuroblastoma Reveals Additional Treatment Options.

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Gay, Laurie M; Kim, Sungeun; Fedorchak, Kyle; Kundranda, Madappa; Odia, Yazmin; Nangia, Chaitali; Battiste, James; Colon-Otero, Gerardo; Powell, Steven; Russell, Jeffery; Elvin, Julia A; Vergilio, Jo-Anne; Suh, James; Ali, Siraj M; Stephens, Philip J; Miller, Vincent A; Ross, Jeffrey S

2017-07-01

Esthesioneuroblastoma (ENB), also known as olfactory neuroblastoma, is a rare malignant neoplasm of the olfactory mucosa. Despite surgical resection combined with radiotherapy and adjuvant chemotherapy, ENB often relapses with rapid progression. Current multimodality, nontargeted therapy for relapsed ENB is of limited clinical benefit. We queried whether comprehensive genomic profiling (CGP) of relapsed or refractory ENB can uncover genomic alterations (GA) that could identify potential targeted therapies for these patients. CGP was performed on formalin-fixed, paraffin-embedded sections from 41 consecutive clinical cases of ENBs using a hybrid-capture, adaptor ligation based next-generation sequencing assay to a mean coverage depth of 593X. The results were analyzed for base substitutions, insertions and deletions, select rearrangements, and copy number changes (amplifications and homozygous deletions). Clinically relevant GA (CRGA) were defined as GA linked to drugs on the market or under evaluation in clinical trials. A total of 28 ENBs harbored GA, with a mean of 1.5 GA per sample. Approximately half of the ENBs (21, 51%) featured at least one CRGA, with an average of 1 CRGA per sample. The most commonly altered gene was TP53 (17%), with GA in PIK3CA , NF1 , CDKN2A , and CDKN2C occurring in 7% of samples. We report comprehensive genomic profiles for 41 ENB tumors. CGP revealed potential new therapeutic targets, including targetable GA in the mTOR, CDK and growth factor signaling pathways, highlighting the clinical value of genomic profiling in ENB. Comprehensive genomic profiling of 41 relapsed or refractory ENBs reveals recurrent alterations or classes of mutation, including amplification of tyrosine kinases encoded on chromosome 5q and mutations affecting genes in the mTOR/PI3K pathway. Approximately half of the ENBs (21, 51%) featured at least one clinically relevant genomic alteration (CRGA), with an average of 1 CRGA per sample. The most commonly altered

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...

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

Unique DNA methylome profiles in CpG island methylator phenotype colon cancers

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Xu, Yaomin; Hu, Bo; Choi, Ae-Jin; Gopalan, Banu; Lee, Byron H.; Kalady, Matthew F.; Church, James M.; Ting, Angela H.

2012-01-01

A subset of colorectal cancers was postulated to have the CpG island methylator phenotype (CIMP), a higher propensity for CpG island DNA methylation. The validity of CIMP, its molecular basis, and its prognostic value remain highly controversial. Using MBD-isolated genome sequencing, we mapped and compared genome-wide DNA methylation profiles of normal, non-CIMP, and CIMP colon specimens. Multidimensional scaling analysis revealed that each specimen could be clearly classified as normal, non-CIMP, and CIMP, thus signifying that these three groups have distinctly different global methylation patterns. We discovered 3780 sites in various genomic contexts that were hypermethylated in both non-CIMP and CIMP colon cancers when compared with normal colon. An additional 2026 sites were found to be hypermethylated in CIMP tumors only; and importantly, 80% of these sites were located in CpG islands. These data demonstrate on a genome-wide level that the additional hypermethylation seen in CIMP tumors occurs almost exclusively at CpG islands and support definitively that these tumors were appropriately named. When these sites were examined more closely, we found that 25% were adjacent to sites that were also hypermethylated in non-CIMP tumors. Thus, CIMP is also characterized by more extensive methylation of sites that are already prone to be hypermethylated in colon cancer. These observations indicate that CIMP tumors have specific defects in controlling both DNA methylation seeding and spreading and serve as an important first step in delineating molecular mechanisms that control these processes. PMID:21990380

Transcript Profiling Distinguishes Complete Treatment Responders With Locally Advanced Cervical Cancer

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Jorge Fernandez-Retana

2015-04-01

Full Text Available Cervical cancer (CC mortality is a major public health concern since it is the second cause of cancer-related deaths among women. Patients diagnosed with locally advanced CC (LACC have an important rate of recurrence and treatment failure. Conventional treatment for LACC is based on chemotherapy and radiotherapy; however, up to 40% of patients will not respond to conventional treatment; hence, we searched for a prognostic gene signature able to discriminate patients who do not respond to the conventional treatment employed to treat LACC. Tumor biopsies were profiled with genome-wide high-density expression microarrays. Class prediction was performed in tumor tissues and the resultant gene signature was validated by quantitative reverse transcription–polymerase chain reaction. A 27-predictive gene profile was identified through its association with pathologic response. The 27-gene profile was validated in an independent set of patients and was able to distinguish between patients diagnosed as no response versus complete response. Gene expression analysis revealed two distinct groups of tumors diagnosed as LACC. Our findings could provide a strategy to select patients who would benefit from neoadjuvant radiochemotherapy-based treatment.

Childhood Cancer Genomics (PDQ®)—Health Professional Version

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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.

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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.

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.

Genomic and Expression Profiling of Benign and Malignant Nerve Sheath Profiling of Benign and Malignant Nerve Sheath

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2007-05-01

Benign and Malignant Nerve Sheath Tumors in Neurofibromatosis Patients PRINCIPAL INVESTIGATOR: Matt van de Rijn, M.D., Ph.D. Torsten...Annual 3. DATES COVERED 1 May 2006 –30 Apr 2007 4. TITLE AND SUBTITLE 5a. CONTRACT NUMBER Genomic and Expression Profiling of Benign and Malignant Nerve...Award Number: DAMD17-03-1-0297 Title: Genomic and Expression Profiling of Benign and Malignant Nerve Sheath Tumors in Neurofibromatosis

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

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...

Tiling array-CGH for the assessment of genomic similarities among synchronous unilateral and bilateral invasive breast cancer tumor pairs

Directory of Open Access Journals (Sweden)

Ringnér Markus

2008-07-01

Full Text Available Abstract Background Today, no objective criteria exist to differentiate between individual primary tumors and intra- or intermammary dissemination respectively, in patients diagnosed with two or more synchronous breast cancers. To elucidate whether these tumors most likely arise through clonal expansion, or whether they represent individual primary tumors is of tumor biological interest and may have clinical implications. In this respect, high resolution genomic profiling may provide a more reliable approach than conventional histopathological and tumor biological factors. Methods 32 K tiling microarray-based comparative genomic hybridization (aCGH was used to explore the genomic similarities among synchronous unilateral and bilateral invasive breast cancer tumor pairs, and was compared with histopathological and tumor biological parameters. Results Based on global copy number profiles and unsupervised hierarchical clustering, five of ten (p = 1.9 × 10-5 unilateral tumor pairs displayed similar genomic profiles within the pair, while only one of eight bilateral tumor pairs (p = 0.29 displayed pair-wise genomic similarities. DNA index, histological type and presence of vessel invasion correlated with the genomic analyses. Conclusion Synchronous unilateral tumor pairs are often genomically similar, while synchronous bilateral tumors most often represent individual primary tumors. However, two independent unilateral primary tumors can develop synchronously and contralateral tumor spread can occur. The presence of an intraductal component is not informative when establishing the independence of two tumors, while vessel invasion, the presence of which was found in clustering tumor pairs but not in tumor pairs that did not cluster together, supports the clustering outcome. Our data suggest that genomically similar unilateral tumor pairs may represent a more aggressive disease that requires the addition of more severe treatment modalities, and

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.

PanCoreGen - Profiling, detecting, annotating protein-coding genes in microbial genomes.

Science.gov (United States)

Paul, Sandip; Bhardwaj, Archana; Bag, Sumit K; Sokurenko, Evgeni V; Chattopadhyay, Sujay

2015-12-01

A large amount of genomic data, especially from multiple isolates of a single species, has opened new vistas for microbial genomics analysis. Analyzing the pan-genome (i.e. the sum of genetic repertoire) of microbial species is crucial in understanding the dynamics of molecular evolution, where virulence evolution is of major interest. Here we present PanCoreGen - a standalone application for pan- and core-genomic profiling of microbial protein-coding genes. PanCoreGen overcomes key limitations of the existing pan-genomic analysis tools, and develops an integrated annotation-structure for a species-specific pan-genomic profile. It provides important new features for annotating draft genomes/contigs and detecting unidentified genes in annotated genomes. It also generates user-defined group-specific datasets within the pan-genome. Interestingly, analyzing an example-set of Salmonella genomes, we detect potential footprints of adaptive convergence of horizontally transferred genes in two human-restricted pathogenic serovars - Typhi and Paratyphi A. Overall, PanCoreGen represents a state-of-the-art tool for microbial phylogenomics and pathogenomics study. Copyright © 2015 Elsevier Inc. All rights reserved.

Methyl-Analyzer--whole genome DNA methylation profiling.

Science.gov (United States)

Xin, Yurong; Ge, Yongchao; Haghighi, Fatemeh G

2011-08-15

Methyl-Analyzer is a python package that analyzes genome-wide DNA methylation data produced by the Methyl-MAPS (methylation mapping analysis by paired-end sequencing) method. Methyl-MAPS is an enzymatic-based method that uses both methylation-sensitive and -dependent enzymes covering >80% of CpG dinucleotides within mammalian genomes. It combines enzymatic-based approaches with high-throughput next-generation sequencing technology to provide whole genome DNA methylation profiles. Methyl-Analyzer processes and integrates sequencing reads from methylated and unmethylated compartments and estimates CpG methylation probabilities at single base resolution. Methyl-Analyzer is available at http://github.com/epigenomics/methylmaps. Sample dataset is available for download at http://epigenomicspub.columbia.edu/methylanalyzer_data.html. fgh3@columbia.edu Supplementary data are available at Bioinformatics online.

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.

Functional profiling of cyanobacterial genomes and its role in ecological adaptations

Directory of Open Access Journals (Sweden)

Ratna Prabha

2016-09-01

Full Text Available With the availability of complete genome sequences of many cyanobacterial species, it is becoming feasible to study the broad prospective of the environmental adaptation and the overall changes at transcriptional and translational level in these organisms. In the evolutionary phase, niche-specific competitive forces have resulted in specific features of the cyanobacterial genomes. In this study, functional composition of the 84 different cyanobacterial genomes and their adaptations to different environments was examined by identifying the genomic composition for specific cellular processes, which reflect their genomic functional profile and ecological adaptation. It was identified that among cyanobacterial genomes, metabolic genes have major share over other categories and differentiation of genomic functional profile was observed for the species inhabiting different habitats. The cyanobacteria of freshwater and other habitats accumulate large number of poorly characterized genes. Strain specific functions were also reported in many cyanobacterial members, of which an important feature was the occurrence of phage-related sequences. From this study, it can be speculated that habitat is one of the major factors in giving the shape of functional composition of cyanobacterial genomes towards their ecological adaptations.

Genome-wide identification of key modulators of gene-gene interaction networks in breast cancer.

Science.gov (United States)

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.

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.

A prospective pilot study of genome-wide exome and transcriptome profiling in patients with small cell lung cancer progressing after first-line therapy.

Directory of Open Access Journals (Sweden)

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.

TEGS-CN: A Statistical Method for Pathway Analysis of Genome-wide Copy Number Profile.

Science.gov (United States)

Huang, Yen-Tsung; Hsu, Thomas; Christiani, David C

2014-01-01

The effects of copy number alterations make up a significant part of the tumor genome profile, but pathway analyses of these alterations are still not well established. We proposed a novel method to analyze multiple copy numbers of genes within a pathway, termed Test for the Effect of a Gene Set with Copy Number data (TEGS-CN). TEGS-CN was adapted from TEGS, a method that we previously developed for gene expression data using a variance component score test. With additional development, we extend the method to analyze DNA copy number data, accounting for different sizes and thus various numbers of copy number probes in genes. The test statistic follows a mixture of X (2) distributions that can be obtained using permutation with scaled X (2) approximation. We conducted simulation studies to evaluate the size and the power of TEGS-CN and to compare its performance with TEGS. We analyzed a genome-wide copy number data from 264 patients of non-small-cell lung cancer. With the Molecular Signatures Database (MSigDB) pathway database, the genome-wide copy number data can be classified into 1814 biological pathways or gene sets. We investigated associations of the copy number profile of the 1814 gene sets with pack-years of cigarette smoking. Our analysis revealed five pathways with significant P values after Bonferroni adjustment (number data, and causal mechanisms of the five pathways require further study.

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

Profiling Invasiveness in Head and Neck Cancer: Recent Contributions of Genomic and Transcriptomic Approaches

International Nuclear Information System (INIS)

Nisa, Lluís; Aebersold, Daniel Matthias; Giger, Roland; Caversaccio, Marco Domenico; Borner, Urs; Medová, Michaela; Zimmer, Yitzhak

2015-01-01

High-throughput molecular profiling approaches have emerged as precious research tools in the field of head and neck translational oncology. Such approaches have identified and/or confirmed the role of several genes or pathways in the acquisition/maintenance of an invasive phenotype and the execution of cellular programs related to cell invasion. Recently published new-generation sequencing studies in head and neck squamous cell carcinoma (HNSCC) have unveiled prominent roles in carcinogenesis and cell invasion of mutations involving NOTCH1 and PI3K-patwhay components. Gene-expression profiling studies combined with systems biology approaches have allowed identifying and gaining further mechanistic understanding into pathways commonly enriched in invasive HNSCC. These pathways include antigen-presenting and leucocyte adhesion molecules, as well as genes involved in cell-extracellular matrix interactions. Here we review the major insights into invasiveness in head and neck cancer provided by high-throughput molecular profiling approaches

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 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.

Genetic variability in MCF-7 sublines: evidence of rapid genomic and RNA expression profile modifications

International Nuclear Information System (INIS)

Nugoli, Mélanie; Theillet, Charles; Chuchana, Paul; Vendrell, Julie; Orsetti, Béatrice; Ursule, Lisa; Nguyen, Catherine; Birnbaum, Daniel; Douzery, Emmanuel JP; Cohen, Pascale

2003-01-01

Both phenotypic and cytogenetic variability have been reported for clones of breast carcinoma cell lines but have not been comprehensively studied. Despite this, cell lines such as MCF-7 cells are extensively used as model systems. In this work we documented, using CGH and RNA expression profiles, the genetic variability at the genomic and RNA expression levels of MCF-7 cells of different origins. Eight MCF-7 sublines collected from different sources were studied as well as 3 subclones isolated from one of the sublines by limit dilution. MCF-7 sublines showed important differences in copy number alteration (CNA) profiles. Overall numbers of events ranged from 28 to 41. Involved chromosomal regions varied greatly from a subline to another. A total of 62 chromosomal regions were affected by either gains or losses in the 11 sublines studied. We performed a phylogenetic analysis of CGH profiles using maximum parsimony in order to reconstruct the putative filiation of the 11 MCF-7 sublines. The phylogenetic tree obtained showed that the MCF-7 clade was characterized by a restricted set of 8 CNAs and that the most divergent subline occupied the position closest to the common ancestor. Expression profiles of 8 MCF-7 sublines were analyzed along with those of 19 unrelated breast cancer cell lines using home made cDNA arrays comprising 720 genes. Hierarchical clustering analysis of the expression data showed that 7/8 MCF-7 sublines were grouped forming a cluster while the remaining subline clustered with unrelated breast cancer cell lines. These data thus showed that MCF-7 sublines differed at both the genomic and phenotypic levels. The analysis of CGH profiles of the parent subline and its three subclones supported the heteroclonal nature of MCF-7 cells. This strongly suggested that the genetic plasticity of MCF-7 cells was related to their intrinsic capacity to generate clonal heterogeneity. We propose that MCF-7, and possibly the breast tumor it was derived from, evolved

Profiling Invasiveness in Head and Neck Cancer: Recent Contributions of Genomic and Transcriptomic Approaches

Directory of Open Access Journals (Sweden)

Lluís Nisa

2015-03-01

Full Text Available High-throughput molecular profiling approaches have emerged as precious research tools in the field of head and neck translational oncology. Such approaches have identified and/or confirmed the role of several genes or pathways in the acquisition/maintenance of an invasive phenotype and the execution of cellular programs related to cell invasion. Recently published new-generation sequencing studies in head and neck squamous cell carcinoma (HNSCC have unveiled prominent roles in carcinogenesis and cell invasion of mutations involving NOTCH1 and PI3K-patwhay components. Gene-expression profiling studies combined with systems biology approaches have allowed identifying and gaining further mechanistic understanding into pathways commonly enriched in invasive HNSCC. These pathways include antigen-presenting and leucocyte adhesion molecules, as well as genes involved in cell-extracellular matrix interactions. Here we review the major insights into invasiveness in head and neck cancer provided by high-throughput molecular profiling approaches.

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

PanCoreGen – profiling, detecting, annotating protein-coding genes in microbial genomes

Science.gov (United States)

Bhardwaj, Archana; Bag, Sumit K; Sokurenko, Evgeni V.

2015-01-01

A large amount of genomic data, especially from multiple isolates of a single species, has opened new vistas for microbial genomics analysis. Analyzing pan-genome (i.e. the sum of genetic repertoire) of microbial species is crucial in understanding the dynamics of molecular evolution, where virulence evolution is of major interest. Here we present PanCoreGen – a standalone application for pan- and core-genomic profiling of microbial protein-coding genes. PanCoreGen overcomes key limitations of the existing pan-genomic analysis tools, and develops an integrated annotation-structure for species-specific pan-genomic profile. It provides important new features for annotating draft genomes/contigs and detecting unidentified genes in annotated genomes. It also generates user-defined group-specific datasets within the pan-genome. Interestingly, analyzing an example-set of Salmonella genomes, we detect potential footprints of adaptive convergence of horizontally transferred genes in two human-restricted pathogenic serovars – Typhi and Paratyphi A. Overall, PanCoreGen represents a state-of-the-art tool for microbial phylogenomics and pathogenomics study. PMID:26456591

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)

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.

State Cancer Profiles Web site

Data.gov (United States)

U.S. Department of Health & Human Services — The State Cancer Profiles (SCP) web site provides statistics to help guide and prioritize cancer control activities at the state and local levels. SCP is a...

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 ...

Profiling cancer gene mutations in clinical formalin-fixed, paraffin-embedded colorectal tumor specimens using targeted next-generation sequencing.

Science.gov (United States)

Zhang, Liangxuan; Chen, Liangjing; Sah, Sachin; Latham, Gary J; Patel, Rajesh; Song, Qinghua; Koeppen, Hartmut; Tam, Rachel; Schleifman, Erica; Mashhedi, Haider; Chalasani, Sreedevi; Fu, Ling; Sumiyoshi, Teiko; Raja, Rajiv; Forrest, William; Hampton, Garret M; Lackner, Mark R; Hegde, Priti; Jia, Shidong

2014-04-01

The success of precision oncology relies on accurate and sensitive molecular profiling. The Ion AmpliSeq Cancer Panel, a targeted enrichment method for next-generation sequencing (NGS) using the Ion Torrent platform, provides a fast, easy, and cost-effective sequencing workflow for detecting genomic "hotspot" regions that are frequently mutated in human cancer genes. Most recently, the U.K. has launched the AmpliSeq sequencing test in its National Health Service. This study aimed to evaluate the clinical application of the AmpliSeq methodology. We used 10 ng of genomic DNA from formalin-fixed, paraffin-embedded human colorectal cancer (CRC) tumor specimens to sequence 46 cancer genes using the AmpliSeq platform. In a validation study, we developed an orthogonal NGS-based resequencing approach (SimpliSeq) to assess the AmpliSeq variant calls. Validated mutational analyses revealed that AmpliSeq was effective in profiling gene mutations, and that the method correctly pinpointed "true-positive" gene mutations with variant frequency >5% and demonstrated high-level molecular heterogeneity in CRC. However, AmpliSeq enrichment and NGS also produced several recurrent "false-positive" calls in clinically druggable oncogenes such as PIK3CA. AmpliSeq provided highly sensitive and quantitative mutation detection for most of the genes on its cancer panel using limited DNA quantities from formalin-fixed, paraffin-embedded samples. For those genes with recurrent "false-positive" variant calls, caution should be used in data interpretation, and orthogonal verification of mutations is recommended for clinical decision making.

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.

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

MiRNA Profiles in Lymphoblastoid Cell Lines of Finnish Prostate Cancer Families.

Directory of Open Access Journals (Sweden)

Daniel Fischer

Full Text Available Heritable factors are evidently involved in prostate cancer (PrCa carcinogenesis, but currently, genetic markers are not routinely used in screening or diagnostics of the disease. More precise information is needed for making treatment decisions to distinguish aggressive cases from indolent disease, for which heritable factors could be a useful tool. The genetic makeup of PrCa has only recently begun to be unravelled through large-scale genome-wide association studies (GWAS. The thus far identified Single Nucleotide Polymorphisms (SNPs explain, however, only a fraction of familial clustering. Moreover, the known risk SNPs are not associated with the clinical outcome of the disease, such as aggressive or metastasised disease, and therefore cannot be used to predict the prognosis. Annotating the SNPs with deep clinical data together with miRNA expression profiles can improve the understanding of the underlying mechanisms of different phenotypes of prostate cancer.In this study microRNA (miRNA profiles were studied as potential biomarkers to predict the disease outcome. The study subjects were from Finnish high risk prostate cancer families. To identify potential biomarkers we combined a novel non-parametrical test with an importance measure provided from a Random Forest classifier. This combination delivered a set of nine miRNAs that was able to separate cases from controls. The detected miRNA expression profiles could predict the development of the disease years before the actual PrCa diagnosis or detect the existence of other cancers in the studied individuals. Furthermore, using an expression Quantitative Trait Loci (eQTL analysis, regulatory SNPs for miRNA miR-483-3p that were also directly associated with PrCa were found.Based on our findings, we suggest that blood-based miRNA expression profiling can be used in the diagnosis and maybe even prognosis of the disease. In the future, miRNA profiling could possibly be used in targeted screening

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.

Whole-genome sequencing of asian lung cancers: second-hand smoke unlikely to be responsible for higher incidence of lung cancer among Asian never-smokers.

Science.gov (United States)

Krishnan, Vidhya G; Ebert, Philip J; Ting, Jason C; Lim, Elaine; Wong, Swee-Seong; Teo, Audrey S M; Yue, Yong G; Chua, Hui-Hoon; Ma, Xiwen; Loh, Gary S L; Lin, Yuhao; Tan, Joanna H J; Yu, Kun; Zhang, Shenli; Reinhard, Christoph; Tan, Daniel S W; Peters, Brock A; Lincoln, Stephen E; Ballinger, Dennis G; Laramie, Jason M; Nilsen, Geoffrey B; Barber, Thomas D; Tan, Patrick; Hillmer, Axel M; Ng, Pauline C

2014-11-01

Asian nonsmoking populations have a higher incidence of lung cancer compared with their European counterparts. There is a long-standing hypothesis that the increase of lung cancer in Asian never-smokers is due to environmental factors such as second-hand smoke. We analyzed whole-genome sequencing of 30 Asian lung cancers. Unsupervised clustering of mutational signatures separated the patients into two categories of either all the never-smokers or all the smokers or ex-smokers. In addition, nearly one third of the ex-smokers and smokers classified with the never-smoker-like cluster. The somatic variant profiles of Asian lung cancers were similar to that of European origin with G.C>T.A being predominant in smokers. We found EGFR and TP53 to be the most frequently mutated genes with mutations in 50% and 27% of individuals, respectively. Among the 16 never-smokers, 69% had an EGFR mutation compared with 29% of 14 smokers/ex-smokers. Asian never-smokers had lung cancer signatures distinct from the smoker signature and their mutation profiles were similar to European never-smokers. The profiles of Asian and European smokers are also similar. Taken together, these results suggested that the same mutational mechanisms underlie the etiology for both ethnic groups. Thus, the high incidence of lung cancer in Asian never-smokers seems unlikely to be due to second-hand smoke or other carcinogens that cause oxidative DNA damage, implying that routine EGFR testing is warranted in the Asian population regardless of smoking status. ©2014 American Association for Cancer Research.

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.

Genome-wide methylation analysis identifies a core set of hypermethylated genes in CIMP-H colorectal cancer.

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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

UFO: a web server for ultra-fast functional profiling of whole genome protein sequences.

Science.gov (United States)

Meinicke, Peter

2009-09-02

Functional profiling is a key technique to characterize and compare the functional potential of entire genomes. The estimation of profiles according to an assignment of sequences to functional categories is a computationally expensive task because it requires the comparison of all protein sequences from a genome with a usually large database of annotated sequences or sequence families. Based on machine learning techniques for Pfam domain detection, the UFO web server for ultra-fast functional profiling allows researchers to process large protein sequence collections instantaneously. Besides the frequencies of Pfam and GO categories, the user also obtains the sequence specific assignments to Pfam domain families. In addition, a comparison with existing genomes provides dissimilarity scores with respect to 821 reference proteomes. Considering the underlying UFO domain detection, the results on 206 test genomes indicate a high sensitivity of the approach. In comparison with current state-of-the-art HMMs, the runtime measurements show a considerable speed up in the range of four orders of magnitude. For an average size prokaryotic genome, the computation of a functional profile together with its comparison typically requires about 10 seconds of processing time. For the first time the UFO web server makes it possible to get a quick overview on the functional inventory of newly sequenced organisms. The genome scale comparison with a large number of precomputed profiles allows a first guess about functionally related organisms. The service is freely available and does not require user registration or specification of a valid email address.

UFO: a web server for ultra-fast functional profiling of whole genome protein sequences

Directory of Open Access Journals (Sweden)

Meinicke Peter

2009-09-01

Full Text Available Abstract Background Functional profiling is a key technique to characterize and compare the functional potential of entire genomes. The estimation of profiles according to an assignment of sequences to functional categories is a computationally expensive task because it requires the comparison of all protein sequences from a genome with a usually large database of annotated sequences or sequence families. Description Based on machine learning techniques for Pfam domain detection, the UFO web server for ultra-fast functional profiling allows researchers to process large protein sequence collections instantaneously. Besides the frequencies of Pfam and GO categories, the user also obtains the sequence specific assignments to Pfam domain families. In addition, a comparison with existing genomes provides dissimilarity scores with respect to 821 reference proteomes. Considering the underlying UFO domain detection, the results on 206 test genomes indicate a high sensitivity of the approach. In comparison with current state-of-the-art HMMs, the runtime measurements show a considerable speed up in the range of four orders of magnitude. For an average size prokaryotic genome, the computation of a functional profile together with its comparison typically requires about 10 seconds of processing time. Conclusion For the first time the UFO web server makes it possible to get a quick overview on the functional inventory of newly sequenced organisms. The genome scale comparison with a large number of precomputed profiles allows a first guess about functionally related organisms. The service is freely available and does not require user registration or specification of a valid email address.

Prostate cancer molecular profiling: the Achilles heel for the implementation of precision medicine.

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Oliveira-Barros, Eliane Gouvêa; Nicolau-Neto, Pedro; Da Costa, Nathalia Meireles; Pinto, Luís Felipe Ribeiro; Palumbo, Antonio; Nasciutti, Luiz Eurico

2017-11-01

Cancer has been mainly treated by traditional therapeutic approaches which do not consider the human genetic diversity and present limitations, probably as a consequence of a poor knowledge of both patient's genetic background and tumor biology. Due to genome project conclusion and large-scale gene analyses emergence, the therapeutic management of several prevalent and aggressive tumors has dramatically improved and represents the closest examples of a precision medicine intervention in this field. Nonetheless, prostate cancer (PCa) remains as a challenge to personalized medicine implementation, probably due to its notorious heterogeneous molecular profile. Cancer treatment personalized approaches rely on the premise that a well-defined panorama of tumor molecular alterations can help selecting new and specific therapeutic targets for its treatment and potentially discriminate tumors which behave differentially. Lately, molecular and genetic studies have been investigating PCa basis, revealing multiple recurrent genomic alterations that include mutations, DNA copy-number variations, rearrangements, and gene fusions, among others. In addition to the increment on PCa molecular biology knowledge, mapping the molecular alterations pattern of this neoplasia, especially the differences existent between tumors displaying distinct behaviors, could represent a great improvement concerning the identification of new targets, personalized medicine, and patients' management and prognosis. © 2017 International Federation for Cell Biology.

Network Biomarkers of Bladder Cancer Based on a Genome-Wide Genetic and Epigenetic Network Derived from Next-Generation Sequencing Data.

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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.

Breast Cancer in Africa: Limitations and Opportunities for Application of Genomic Medicine

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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.

Soybean (Glycine max) SWEET gene family: insights through comparative genomics, transcriptome profiling and whole genome re-sequence analysis.

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Patil, Gunvant; Valliyodan, Babu; Deshmukh, Rupesh; Prince, Silvas; Nicander, Bjorn; Zhao, Mingzhe; Sonah, Humira; Song, Li; Lin, Li; Chaudhary, Juhi; Liu, Yang; Joshi, Trupti; Xu, Dong; Nguyen, Henry T

2015-07-11

SWEET (MtN3_saliva) domain proteins, a recently identified group of efflux transporters, play an indispensable role in sugar efflux, phloem loading, plant-pathogen interaction and reproductive tissue development. The SWEET gene family is predominantly studied in Arabidopsis and members of the family are being investigated in rice. To date, no transcriptome or genomics analysis of soybean SWEET genes has been reported. In the present investigation, we explored the evolutionary aspect of the SWEET gene family in diverse plant species including primitive single cell algae to angiosperms with a major emphasis on Glycine max. Evolutionary features showed expansion and duplication of the SWEET gene family in land plants. Homology searches with BLAST tools and Hidden Markov Model-directed sequence alignments identified 52 SWEET genes that were mapped to 15 chromosomes in the soybean genome as tandem duplication events. Soybean SWEET (GmSWEET) genes showed a wide range of expression profiles in different tissues and developmental stages. Analysis of public transcriptome data and expression profiling using quantitative real time PCR (qRT-PCR) showed that a majority of the GmSWEET genes were confined to reproductive tissue development. Several natural genetic variants (non-synonymous SNPs, premature stop codons and haplotype) were identified in the GmSWEET genes using whole genome re-sequencing data analysis of 106 soybean genotypes. A significant association was observed between SNP-haplogroup and seed sucrose content in three gene clusters on chromosome 6. Present investigation utilized comparative genomics, transcriptome profiling and whole genome re-sequencing approaches and provided a systematic description of soybean SWEET genes and identified putative candidates with probable roles in the reproductive tissue development. Gene expression profiling at different developmental stages and genomic variation data will aid as an important resource for the soybean research

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

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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.

Mitochondrial mutations drive prostate cancer aggression

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Hopkins, Julia F.; Sabelnykova, Veronica Y.; Weischenfeldt, Joachim

2017-01-01

Nuclear mutations are well known to drive tumor incidence, aggression and response to therapy. By contrast, the frequency and roles of mutations in the maternally inherited mitochondrial genome are poorly understood. Here we sequence the mitochondrial genomes of 384 localized prostate cancer...... in prostate cancer, and suggest interplay between nuclear and mitochondrial mutational profiles in prostate cancer....

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....

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

Clinically Applicable Inhibitors Impacting Genome Stability.

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Prakash, Anu; Garcia-Moreno, Juan F; Brown, James A L; Bourke, Emer

2018-05-13

Advances in technology have facilitated the molecular profiling (genomic and transcriptomic) of tumours, and has led to improved stratification of patients and the individualisation of treatment regimes. To fully realize the potential of truly personalised treatment options, we need targeted therapies that precisely disrupt the compensatory pathways identified by profiling which allow tumours to survive or gain resistance to treatments. Here, we discuss recent advances in novel therapies that impact the genome (chromosomes and chromatin), pathways targeted and the stage of the pathways targeted. The current state of research will be discussed, with a focus on compounds that have advanced into trials (clinical and pre-clinical). We will discuss inhibitors of specific DNA damage responses and other genome stability pathways, including those in development, which are likely to synergistically combine with current therapeutic options. Tumour profiling data, combined with the knowledge of new treatments that affect the regulation of essential tumour signalling pathways, is revealing fundamental insights into cancer progression and resistance mechanisms. This is the forefront of the next evolution of advanced oncology medicine that will ultimately lead to improved survival and may, one day, result in many cancers becoming chronic conditions, rather than fatal diseases.

Profiling of circulating microRNAs for prostate cancer biomarker discovery

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Haldrup, Christa; Kosaka, Nobuyoshi; Ochiya, Takahiro

2014-01-01

Prostate cancer (PC) is the most frequent cancer in men in the Western world. Currently, serum prostate-specific antigen levels and digital rectal examinations are used to indicate the need for diagnostic prostate biopsy, but lack in specificity and sensitivity. Thus, many men undergo unnecessary...... performed genome-wide miRNA profiling of serum samples from 13 benign prostatic hyperplasia (BPH) control patients and 31 PC patients. Furthermore, we carefully reviewed the literature on circulating miRNA biomarkers for PC. Our results confirmed the de-regulation of miR-141 and miR-375, two of the most...... well-documented candidate miRNA markers for PC. Moreover, we identified several new potential serum miRNA markers for PC and developed three novel and highly specific (100 %) miRNA candidate marker panels able to identify 84 % of all PC patients (miR-562/miR-210/miR-501-3p/miR-375/miR-551b), 80...

Real-World Evidence In Support Of Precision Medicine: Clinico-Genomic Cancer Data As A Case Study.

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Agarwala, Vineeta; Khozin, Sean; Singal, Gaurav; O'Connell, Claire; Kuk, Deborah; Li, Gerald; Gossai, Anala; Miller, Vincent; Abernethy, Amy P

2018-05-01

The majority of US adult cancer patients today are diagnosed and treated outside the context of any clinical trial (that is, in the real world). Although these patients are not part of a research study, their clinical data are still recorded. Indeed, data captured in electronic health records form an ever-growing, rich digital repository of longitudinal patient experiences, treatments, and outcomes. Likewise, genomic data from tumor molecular profiling are increasingly guiding oncology care. Linking real-world clinical and genomic data, as well as information from other co-occurring data sets, could create study populations that provide generalizable evidence for precision medicine interventions. However, the infrastructure required to link, ensure quality, and rapidly learn from such composite data is complex. We outline the challenges and describe a novel approach to building a real-world clinico-genomic database of patients with cancer. This work represents a case study in how data collected during routine patient care can inform precision medicine efforts for the population at large. We suggest that health policies can promote innovation by defining appropriate uses of real-world evidence, establishing data standards, and incentivizing data sharing.

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

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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. 

Comprehensive genomic profiling of 295 cases of clinically advanced urothelial carcinoma of the urinary bladder reveals a high frequency of clinically relevant genomic alterations.

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Ross, Jeffrey S; Wang, Kai; Khaira, Depinder; Ali, Siraj M; Fisher, Huge A G; Mian, Badar; Nazeer, Tipu; Elvin, Julia A; Palma, Norma; Yelensky, Roman; Lipson, Doron; Miller, Vincent A; Stephens, Philip J; Subbiah, Vivek; Pal, Sumanta K

2016-03-01

In the current study, the authors present a comprehensive genomic profile (CGP)-based study of advanced urothelial carcinoma (UC) designed to detect clinically relevant genomic alterations (CRGAs). DNA was extracted from 40 µm of formalin-fixed, paraffin-embedded sections from 295 consecutive cases of recurrent/metastatic UC. CGP was performed on hybridization-captured, adaptor ligation-based libraries to a mean coverage depth of 688X for all coding exons of 236 cancer-related genes plus 47 introns from 19 genes frequently rearranged in cancer, using process-matched normal control samples as a reference. CRGAs were defined as GAs linked to drugs on the market or currently under evaluation in mechanism-driven clinical trials. All 295 patients assessed were classified with high-grade (International Society of Urological Pathology classification) and advanced stage (stage III/IV American Joint Committee on Cancer) disease, and 294 of 295 patients (99.7%) had at least 1 GA on CGP with a mean of 6.4 GAs per UC (61% substitutions/insertions/deletions, 37% copy number alterations, and 2% fusions). Furthermore, 275 patients (93%) had at least 1 CRGA involving 75 individual genes with a mean of 2.6 CRGAs per UC. The most common CRGAs involved cyclin-dependent kinase inhibitor 2A (CDKN2A) (34%), fibroblast growth factor receptor 3 (FGFR3) (21%), phosphatidylinositol 3-kinase catalytic subunit alpha (PIK3CA) (20%), and ERBB2 (17%). FGFR3 GAs were diverse types and included 10% fusions. ERBB2 GAs were equally divided between amplifications and substitutions. ERBB2 substitutions were predominantly within the extracellular domain and were highly enriched in patients with micropapillary UC (38% of 32 cases vs 5% of 263 nonmicropapillary UC cases; PCancer 2016;122:702-711. © 2015 American Cancer Society. © 2015 American Cancer Society.

Epigenomic profiling of DNA methylation in paired prostate cancer versus adjacent benign tissue.

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Geybels, Milan S; Zhao, Shanshan; Wong, Chao-Jen; Bibikova, Marina; Klotzle, Brandy; Wu, Michael; Ostrander, Elaine A; Fan, Jian-Bing; Feng, Ziding; Stanford, Janet L

2015-12-01

Aberrant DNA methylation may promote prostate carcinogenesis. We investigated epigenome-wide DNA methylation profiles in prostate cancer (PCa) compared to adjacent benign tissue to identify differentially methylated CpG sites. The study included paired PCa and adjacent benign tissue samples from 20 radical prostatectomy patients. Epigenetic profiling was done using the Infinium HumanMethylation450 BeadChip. Linear models that accounted for the paired study design and False Discovery Rate Q-values were used to evaluate differential CpG methylation. mRNA expression levels of the genes with the most differentially methylated CpG sites were analyzed. In total, 2,040 differentially methylated CpG sites were identified in PCa versus adjacent benign tissue (Q-value Cancer Genome Atlas (TCGA) data provided confirmatory evidence for our findings. This study of PCa versus adjacent benign tissue showed many differentially methylated CpGs and regions in and outside gene promoter regions, which may potentially be used for the development of future epigenetic-based diagnostic tests or as therapeutic targets. © 2015 Wiley Periodicals, Inc.

The mediator complex in genomic and non-genomic signaling in cancer.

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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.

Gene Expression Profiling of Peripheral Blood From Kidney Transplant Recipients for the Early Detection of Digestive System Cancer.

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Kusaka, M; Okamoto, M; Takenaka, M; Sasaki, H; Fukami, N; Kataoka, K; Ito, T; Kenmochi, T; Hoshinaga, K; Shiroki, R

2017-06-01

Kidney transplant recipients are at increased risk of developing cancer in comparison with the general population. To effectively manage post-transplantation malignancies, it is essential to proactively monitor patients. A long-term intensive screening program was associated with a reduced incidence of cancer after transplantation. This study evaluated the usefulness of the gene expression profiling of peripheral blood samples obtained from kidney transplant patients and adopted a screening test for detecting cancer of the digestive system (gastric, colon, pancreas, and biliary tract). Nineteen patients were included in this study and a total of 53 gene expression screening tests were performed. The gene expression profiles of blood-delivered total RNA and whole genome human gene expression profiles were obtained. We investigated the expression levels of 2665 genes associated with digestive cancers and counted the number of genes in which expression was altered. A hierarchical clustering analysis was also performed. The final prediction of the cancer possibility was determined according to an algorithm. The number of genes in which expression was altered was significantly increased in the kidney transplant recipients in comparison with the general population (1091 ± 63 vs 823 ± 94; P = .0024). The number of genes with altered expression decreased after the induction of mechanistic target of rapamycin (mTOR) inhibitor (1484 ± 227 vs 883 ± 154; P = .0439). No cases of possible digestive cancer were detected in this study period. The gene expression profiling of peripheral blood samples may be a useful and noninvasive diagnostic tool that allows for the early detection of cancer of the digestive system. Copyright © 2017 Elsevier Inc. All rights reserved.

Carcinogen susceptibility is regulated by genome architecture and predicts cancer mutagenesis.

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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.

Genomic Heterogeneity as a Barrier to Precision Medicine in Gastroesophageal Adenocarcinoma.

Science.gov (United States)

Pectasides, Eirini; Stachler, Matthew D; Derks, Sarah; Liu, Yang; Maron, Steven; Islam, Mirazul; Alpert, Lindsay; Kwak, Heewon; Kindler, Hedy; Polite, Blase; Sharma, Manish R; Allen, Kenisha; O'Day, Emily; Lomnicki, Samantha; Maranto, Melissa; Kanteti, Rajani; Fitzpatrick, Carrie; Weber, Christopher; Setia, Namrata; Xiao, Shu-Yuan; Hart, John; Nagy, Rebecca J; Kim, Kyoung-Mee; Choi, Min-Gew; Min, Byung-Hoon; Nason, Katie S; O'Keefe, Lea; Watanabe, Masayuki; Baba, Hideo; Lanman, Rick; Agoston, Agoston T; Oh, David J; Dunford, Andrew; Thorner, Aaron R; Ducar, Matthew D; Wollison, Bruce M; Coleman, Haley A; Ji, Yuan; Posner, Mitchell C; Roggin, Kevin; Turaga, Kiran; Chang, Paul; Hogarth, Kyle; Siddiqui, Uzma; Gelrud, Andres; Ha, Gavin; Freeman, Samuel S; Rhoades, Justin; Reed, Sarah; Gydush, Greg; Rotem, Denisse; Davison, Jon; Imamura, Yu; Adalsteinsson, Viktor; Lee, Jeeyun; Bass, Adam J; Catenacci, Daniel V

2018-01-01

Gastroesophageal adenocarcinoma (GEA) is a lethal disease where targeted therapies, even when guided by genomic biomarkers, have had limited efficacy. A potential reason for the failure of such therapies is that genomic profiling results could commonly differ between the primary and metastatic tumors. To evaluate genomic heterogeneity, we sequenced paired primary GEA and synchronous metastatic lesions across multiple cohorts, finding extensive differences in genomic alterations, including discrepancies in potentially clinically relevant alterations. Multiregion sequencing showed significant discrepancy within the primary tumor (PT) and between the PT and disseminated disease, with oncogene amplification profiles commonly discordant. In addition, a pilot analysis of cell-free DNA (cfDNA) sequencing demonstrated the feasibility of detecting genomic amplifications not detected in PT sampling. Lastly, we profiled paired primary tumors, metastatic tumors, and cfDNA from patients enrolled in the personalized antibodies for GEA (PANGEA) trial of targeted therapies in GEA and found that genomic biomarkers were recurrently discrepant between the PT and untreated metastases. Divergent primary and metastatic tissue profiling led to treatment reassignment in 32% (9/28) of patients. In discordant primary and metastatic lesions, we found 87.5% concordance for targetable alterations in metastatic tissue and cfDNA, suggesting the potential for cfDNA profiling to enhance selection of therapy. Significance: We demonstrate frequent baseline heterogeneity in targetable genomic alterations in GEA, indicating that current tissue sampling practices for biomarker testing do not effectively guide precision medicine in this disease and that routine profiling of metastatic lesions and/or cfDNA should be systematically evaluated. Cancer Discov; 8(1); 37-48. ©2017 AACR. See related commentary by Sundar and Tan, p. 14 See related article by Janjigian et al., p. 49 This article is highlighted

Systematic Identification and Assessment of Therapeutic Targets for Breast Cancer Based on Genome-Wide RNA Interference Transcriptomes

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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 Genome-Wide Analysis of Carcinoembryonic Antigen Signaling by Colorectal Cancer Cells Using RNA Sequencing.

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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.

Ectopic Expression of Testis Germ Cell Proteins in Cancer and Its Potential Role in Genomic Instability

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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.

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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.

Crossing the LINE toward genomic instability: LINE-1 retrotransposition in cancer

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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.

Dana-Farber Cancer Institute: Identification of Therapeutic Targets Across Cancer Types | Office of Cancer Genomics

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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.

Genome-wide nucleosome occupancy and DNA methylation profiling of four human cell lines

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Aaron L. Statham

2015-03-01

Full Text Available DNA methylation and nucleosome positioning are two key mechanisms that contribute to the epigenetic control of gene expression. During carcinogenesis, the expression of many genes is altered alongside extensive changes in the epigenome, with repressed genes often being associated with local DNA hypermethylation and gain of nucleosomes at their promoters. However the spectrum of alterations that occur at distal regulatory regions has not been extensively studied. To address this we used Nucleosome Occupancy and Methylation sequencing (NOMe-seq to compare the genome-wide DNA methylation and nucleosome occupancy profiles between normal and cancer cell line models of the breast and prostate. Here we describe the bioinformatic pipeline and methods that we developed for the processing and analysis of the NOMe-seq data published by (Taberlay et al., 2014 [1] and deposited in the Gene Expression Omnibus with accession GSE57498.

The functional genomic studies of curcumin.

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Huminiecki, Lukasz; Horbańczuk, Jarosław; Atanasov, Atanas G

2017-10-01

Curcumin is a natural plant-derived compound that has attracted a lot of attention for its anti-cancer activities. Curcumin can slow proliferation of and induce apoptosis in cancer cell lines, but the precise mechanisms of these effects are not fully understood. However, many lines of evidence suggested that curcumin has a potent impact on gene expression profiles; thus, functional genomics should be the key to understanding how curcumin exerts its anti-cancer activities. Here, we review the published functional genomic studies of curcumin focusing on cancer. Typically, a cancer cell line or a grafted tumor were exposed to curcumin and profiled with microarrays, methylation assays, or RNA-seq. Crucially, these studies are in agreement that curcumin has a powerful effect on gene expression. In the majority of the studies, among differentially expressed genes we found genes involved in cell signaling, apoptosis, and the control of cell cycle. Curcumin can also induce specific methylation changes, and is a powerful regulator of the expression of microRNAs which control oncogenesis. We also reflect on how the broader technological progress in transcriptomics has been reflected on the field of curcumin. We conclude by discussing the areas where more functional genomic studies are highly desirable. Integrated OMICS approaches will clearly be the key to understanding curcumin's anticancer and chemopreventive effects. Such strategies may become a template for elucidating the mode of action of other natural products; many natural products have pleiotropic effects that are well suited for a systems-level analysis. Copyright © 2017 Elsevier Ltd. All rights reserved.

Break Breast Cancer Addiction by CRISPR/Cas9 Genome Editing

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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...

Biosemiotic Entropy of the Genome: Mutations and Epigenetic Imbalances Resulting in Cancer

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Samuel S. Shepard

2013-01-01

Full Text Available Biosemiotic entropy involves the deterioration of biological sign systems. The genome is a coded sign system that is connected to phenotypic outputs through the interpretive functions of the tRNA/ribosome machinery. This symbolic sign system (semiosis at the core of all biology has been termed “biosemiosis”. Layers of biosemiosis and cellular information management are analogous in varying degrees to the semiotics of computer programming, spoken, and written human languages. Biosemiotic entropy — an error or deviation from a healthy state — results from errors in copying functional information (mutations and errors in the appropriate context or quantity of gene expression (epigenetic imbalance. The concept of biosemiotic entropy is a deeply imbedded assumption in the study of cancer biology. Cells have a homeostatic, preprogrammed, ideal or healthy state that is rooted in genomics, strictly orchestrated by epigenetic regulation, and maintained by DNA repair mechanisms. Cancer is an eminent illustration of biosemiotic entropy, in which the corrosion of genetic information via substitutions, deletions, insertions, fusions, and aberrant regulation results in malignant phenotypes. However, little attention has been given to explicitly outlining the paradigm of biosemiotic entropy in the context of cancer. Herein we distill semiotic theory (from the familiar and well understood spheres of human language and computer code to draw analogies useful for understanding the operation of biological semiosis at the genetic level. We propose that the myriad checkpoints, error correcting mechanisms, and immunities are all systems whose primary role is to defend against the constant pressure of biosemiotic entropy, which malignancy must shut down in order to achieve advanced stages. In lieu of the narrower tumor suppressor/oncogene model, characterization of oncogenesis into the biosemiotic framework of sign, index, or object entropy may allow for more

Genome-wide association scan for variants associated with early-onset prostate cancer.

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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.

Investigating a multigene prognostic assay based on significant pathways for Luminal A breast cancer through gene expression profile analysis.

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Gao, Haiyan; Yang, Mei; Zhang, Xiaolan

2018-04-01

The present study aimed to investigate potential recurrence-risk biomarkers based on significant pathways for Luminal A breast cancer through gene expression profile analysis. Initially, the gene expression profiles of Luminal A breast cancer patients were downloaded from The Cancer Genome Atlas database. The differentially expressed genes (DEGs) were identified using a Limma package and the hierarchical clustering analysis was conducted for the DEGs. In addition, the functional pathways were screened using Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses and rank ratio calculation. The multigene prognostic assay was exploited based on the statistically significant pathways and its prognostic function was tested using train set and verified using the gene expression data and survival data of Luminal A breast cancer patients downloaded from the Gene Expression Omnibus. A total of 300 DEGs were identified between good and poor outcome groups, including 176 upregulated genes and 124 downregulated genes. The DEGs may be used to effectively distinguish Luminal A samples with different prognoses verified by hierarchical clustering analysis. There were 9 pathways screened as significant pathways and a total of 18 DEGs involved in these 9 pathways were identified as prognostic biomarkers. According to the survival analysis and receiver operating characteristic curve, the obtained 18-gene prognostic assay exhibited good prognostic function with high sensitivity and specificity to both the train and test samples. In conclusion the 18-gene prognostic assay including the key genes, transcription factor 7-like 2, anterior parietal cortex and lymphocyte enhancer factor-1 may provide a new method for predicting outcomes and may be conducive to the promotion of precision medicine for Luminal A breast cancer.

A new generation of cancer genome diagnostics for routine clinical use: overcoming the roadblocks to personalized cancer medicine.

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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.

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...

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.

Quantitative high-resolution genomic analysis of single cancer cells.

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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)

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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.

Genome-Wide Expression Profiling of Complex Regional Pain Syndrome

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Jin, Eun-Heui; Zhang, Enji; Ko, Youngkwon; Sim, Woo Seog; Moon, Dong Eon; Yoon, Keon Jung; Hong, Jang Hee; Lee, Won Hyung

2013-01-01

Complex regional pain syndrome (CRPS) is a chronic, progressive, and devastating pain syndrome characterized by spontaneous pain, hyperalgesia, allodynia, altered skin temperature, and motor dysfunction. Although previous gene expression profiling studies have been conducted in animal pain models, there genome-wide expression profiling in the whole blood of CRPS patients has not been reported yet. Here, we successfully identified certain pain-related genes through genome-wide expression profiling in the blood from CRPS patients. We found that 80 genes were differentially expressed between 4 CRPS patients (2 CRPS I and 2 CRPS II) and 5 controls (cut-off value: 1.5-fold change and pCRPS patients and 18 controls by quantitative reverse transcription-polymerase chain reaction (qRT-PCR). We focused on the MMP9 gene that, by qRT-PCR, showed a statistically significant difference in expression in CRPS patients compared to controls with the highest relative fold change (4.0±1.23 times and p = 1.4×10−4). The up-regulation of MMP9 gene in the blood may be related to the pain progression in CRPS patients. Our findings, which offer a valuable contribution to the understanding of the differential gene expression in CRPS may help in the understanding of the pathophysiology of CRPS pain progression. PMID:24244504

Integrative Genomic Analysis of Coincident Cancer Foci Implicates CTNNB1 and PTEN Alterations in Ductal Prostate Cancer.

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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

Human miRNome profiling in colorectal cancer and liver metastasis development

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Lisa Perilli

2014-12-01

Full Text Available Qualitative alterations or abnormal expression of microRNAs (miRNAs in colorectal cancer has mainly been demonstrated in primary tumors. The miRNA expression profiles in 78 samples from 46 patients were analyzed to identify changes in miRNA expression level among normal colon mucosa, primary tumor and liver metastasis samples. Using this dataset, we describe the interplay of miRNA groups in regulating pathways that are important for tumor development. Here we describe in details the contents and quality controls for the miRNA expression and clinical data associated with the study published by Pizzini and colleagues in the BMC Genomics in 2013 (Pizzini et al., 2013. Data are deposited in GEO database as GSE35834 series.

Human miRNome profiling in colorectal cancer and liver metastasis development

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Perilli, Lisa; Pizzini, Silvia; Bisognin, Andrea; Mandruzzato, Susanna; Biasiolo, Marta; Facciolli, Arianna; Rossi, Elisabetta; Esposito, Giovanni; Rugge, Massimo; Pilati, Pierluigi; Mocellin, Simone; Nitti, Donato; Bortoluzzi, Stefania; Zanovello, Paola

2014-01-01

Qualitative alterations or abnormal expression of microRNAs (miRNAs) in colorectal cancer has mainly been demonstrated in primary tumors. The miRNA expression profiles in 78 samples from 46 patients were analyzed to identify changes in miRNA expression level among normal colon mucosa, primary tumor and liver metastasis samples. Using this dataset, we describe the interplay of miRNA groups in regulating pathways that are important for tumor development. Here we describe in details the contents and quality controls for the miRNA expression and clinical data associated with the study published by Pizzini and colleagues in the BMC Genomics in 2013 (Pizzini et al., 2013). Data are deposited in GEO database as GSE35834 series. PMID:26484092

Human Papillomavirus Genome Integration and Head and Neck Cancer.

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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.

Luminal B tumors are the most frequent molecular subtype in breast cancer of North African women: an immunohistochemical profile study from Morocco

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El Fatemi Hinde

2012-12-01

Full Text Available Abstract Background Breast cancer may be classified into luminal A, luminal B, HER2+/ER-, basal-like and normal-like subtypes based on gene expression profiling or immunohistochemical (IHC characteristics. The aim of our study is to show the molecular profile characteristic of breast cancer in the North African population of Morocco. This work showed preliminary results and correlations with clinicopathological and histological parameters. Three hundred and ninety primary breast carcinomas tumor tissues were immunostained for ER, PR, HER2, CK5/6, CK8/18 and Ki67 using paraffin tissue. Methods We reviewed 390 cases of breast cancer diagnosed on January 2008 to December 2011 at the Department of pathology, Hassan II teaching hospital, Fez, Morocco. Age, size tumor, metastatic profile, node involvement profile, histological type and immunohistochemical profile were studied. Results The average age was 46 years; our patients were diagnosed late with a high average tumor size. Luminal B subtype was more prevalent (41.8%, followed by luminal A (30.5%, basal-like (13, 6%, Her2-overexpressing (9, 2%, and unclassified subtype (4.9%. Conclusion This study showed that molecular classification and biological profile may be different according to geographical distribution, to encourage further studies to know the genomic profile of tumors and the environment. Virtual slide http://www.diagnosticpathology.diagnomx.eu/vs/1675272504826544

The discovery of putative urine markers for the specific detection of prostate tumor by integrative mining of public genomic profiles.

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Min Chen

Full Text Available Urine has emerged as an attractive biofluid for the noninvasive detection of prostate cancer (PCa. There is a strong imperative to discover candidate urinary markers for the clinical diagnosis and prognosis of PCa. The rising flood of various omics profiles presents immense opportunities for the identification of prospective biomarkers. Here we present a simple and efficient strategy to derive candidate urine markers for prostate tumor by mining cancer genomic profiles from public databases. Prostate, bladder and kidney are three major tissues from which cellular matters could be released into urine. To identify urinary markers specific for PCa, upregulated entities that might be shed in exosomes of bladder cancer and kidney cancer are first excluded. Through the ontology-based filtering and further assessment, a reduced list of 19 entities encoding urinary proteins was derived as putative PCa markers. Among them, we have found 10 entities closely associated with the process of tumor cell growth and development by pathway enrichment analysis. Further, using the 10 entities as seeds, we have constructed a protein-protein interaction (PPI subnetwork and suggested a few urine markers as preferred prognostic markers to monitor the invasion and progression of PCa. Our approach is amenable to discover and prioritize potential markers present in a variety of body fluids for a spectrum of human diseases.

Noncoding Genomics in Gastric Cancer and the Gastric Precancerous Cascade: Pathogenesis and Biomarkers

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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.

Early Onset Malignancies - Genomic Study of Cancer Disparities

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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.

Genome-wide association study of susceptibility loci for breast cancer in Sardinian population.

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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

Xenopatients 2.0: reprogramming the epigenetic landscapes of patient-derived cancer genomes.

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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

Hormone-replacement therapy influences gene expression profiles and is associated with breast-cancer prognosis: a cohort study

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Skoog Lambert

2006-06-01

Full Text Available Abstract Background Postmenopausal hormone-replacement therapy (HRT increases breast-cancer risk. The influence of HRT on the biology of the primary tumor, however, is not well understood. Methods We obtained breast-cancer gene expression profiles using Affymetrix human genome U133A arrays. We examined the relationship between HRT-regulated gene profiles, tumor characteristics, and recurrence-free survival in 72 postmenopausal women. Results HRT use in patients with estrogen receptor (ER protein positive tumors (n = 72 was associated with an altered regulation of 276 genes. Expression profiles based on these genes clustered ER-positive tumors into two molecular subclasses, one of which was associated with HRT use and had significantly better recurrence free survival despite lower ER levels. A comparison with external data suggested that gene regulation in tumors associated with HRT was negatively correlated with gene regulation induced by short-term estrogen exposure, but positively correlated with the effect of tamoxifen. Conclusion Our findings suggest that post-menopausal HRT use is associated with a distinct gene expression profile related to better recurrence-free survival and lower ER protein levels. Tentatively, HRT-associated gene expression in tumors resembles the effect of tamoxifen exposure on MCF-7 cells.

Early experience with formalin-fixed paraffin-embedded (FFPE) based commercial clinical genomic profiling of gliomas-robust and informative with caveats.

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Movassaghi, Masoud; Shabihkhani, Maryam; Hojat, Seyed A; Williams, Ryan R; Chung, Lawrance K; Im, Kyuseok; Lucey, Gregory M; Wei, Bowen; Mareninov, Sergey; Wang, Michael W; Ng, Denise W; Tashjian, Randy S; Magaki, Shino; Perez-Rosendahl, Mari; Yang, Isaac; Khanlou, Negar; Vinters, Harry V; Liau, Linda M; Nghiemphu, Phioanh L; Lai, Albert; Cloughesy, Timothy F; Yong, William H

2017-08-01

Commercial targeted genomic profiling with next generation sequencing using formalin-fixed paraffin embedded (FFPE) tissue has recently entered into clinical use for diagnosis and for the guiding of therapy. However, there is limited independent data regarding the accuracy or robustness of commercial genomic profiling in gliomas. As part of patient care, FFPE samples of gliomas from 71 patients were submitted for targeted genomic profiling to one commonly used commercial vendor, Foundation Medicine. Genomic alterations were determined for the following grades or groups of gliomas; Grade I/II, Grade III, primary glioblastomas (GBMs), recurrent primary GBMs, and secondary GBMs. In addition, FFPE samples from the same patients were independently assessed with conventional methods such as immunohistochemistry (IHC), Quantitative real-time PCR (qRT-PCR), or Fluorescence in situ hybridization (FISH) for three genetic alterations: IDH1 mutations, EGFR amplification, and EGFRvIII expression. A total of 100 altered genes were detected by the aforementioned targeted genomic profiling assay. The number of different genomic alterations was significantly different between the five groups of gliomas and consistent with the literature. CDKN2A/B, TP53, and TERT were the most common genomic alterations seen in primary GBMs, whereas IDH1, TP53, and PIK3CA were the most common in secondary GBMs. Targeted genomic profiling demonstrated 92.3%-100% concordance with conventional methods. The targeted genomic profiling report provided an average of 5.5 drugs, and listed an average of 8.4 clinical trials for the 71 glioma patients studied but only a third of the trials were appropriate for glioma patients. In this limited comparison study, this commercial next generation sequencing based-targeted genomic profiling showed a high concordance rate with conventional methods for the 3 genetic alterations and identified mutations expected for the type of glioma. While it may not be feasible to

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 association analysis identifies three new breast cancer susceptibility loci

DEFF Research Database (Denmark)

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...

MicroRNA Expression Profile in Penile Cancer Revealed by Next-Generation Small RNA Sequencing.

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Li Zhang

Full Text Available Penile cancer (PeCa is a relatively rare tumor entity but possesses higher morbidity and mortality rates especially in developing countries. To date, the concrete pathogenic signaling pathways and core machineries involved in tumorigenesis and progression of PeCa remain to be elucidated. Several studies suggested miRNAs, which modulate gene expression at posttranscriptional level, were frequently mis-regulated and aberrantly expressed in human cancers. However, the miRNA profile in human PeCa has not been reported before. In this present study, the miRNA profile was obtained from 10 fresh penile cancerous tissues and matched adjacent non-cancerous tissues via next-generation sequencing. As a result, a total of 751 and 806 annotated miRNAs were identified in normal and cancerous penile tissues, respectively. Among which, 56 miRNAs with significantly different expression levels between paired tissues were identified. Subsequently, several annotated miRNAs were selected randomly and validated using quantitative real-time PCR. Compared with the previous publications regarding to the altered miRNAs expression in various cancers and especially genitourinary (prostate, bladder, kidney, testis cancers, the most majority of deregulated miRNAs showed the similar expression pattern in penile cancer. Moreover, the bioinformatics analyses suggested that the putative target genes of differentially expressed miRNAs between cancerous and matched normal penile tissues were tightly associated with cell junction, proliferation, growth as well as genomic instability and so on, by modulating Wnt, MAPK, p53, PI3K-Akt, Notch and TGF-β signaling pathways, which were all well-established to participate in cancer initiation and progression. Our work presents a global view of the differentially expressed miRNAs and potentially regulatory networks of their target genes for clarifying the pathogenic transformation of normal penis to PeCa, which research resource also

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.

Health psychology and translational genomic research: bringing innovation to cancer-related behavioral interventions.

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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.

Integrated analysis of epigenomic and genomic changes by DNA methylation dependent mechanisms provides potential novel biomarkers for prostate cancer.

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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.

Personal Genomic Testing for Cancer Risk: Results From the Impact of Personal Genomics Study.

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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.

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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 .

The molecular landscape of pediatric acute myeloid leukemia reveals recurrent structural alterations and age-specific mutational interactions | Office of Cancer Genomics

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We present the molecular landscape of pediatric acute myeloid leukemia (AML) and characterize nearly 1,000 participants in Children’s Oncology Group (COG) AML trials. The COG–National Cancer Institute (NCI) TARGET AML initiative assessed cases by whole-genome, targeted DNA, mRNA and microRNA sequencing and CpG methylation profiling. Validated DNA variants corresponded to diverse, infrequent mutations, with fewer than 40 genes mutated in >2% of cases.

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

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...

Altered mitochondrial genome content signals worse pathology and prognosis in prostate cancer.

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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.

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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.

Prospective molecular profiling of canine cancers provides a clinically relevant comparative model for evaluating personalized medicine (PMed) trials.

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Paoloni, Melissa; Webb, Craig; Mazcko, Christina; Cherba, David; Hendricks, William; Lana, Susan; Ehrhart, E J; Charles, Brad; Fehling, Heather; Kumar, Leena; Vail, David; Henson, Michael; Childress, Michael; Kitchell, Barbara; Kingsley, Christopher; Kim, Seungchan; Neff, Mark; Davis, Barbara; Khanna, Chand; Trent, Jeffrey

2014-01-01

Molecularly-guided trials (i.e. PMed) now seek to aid clinical decision-making by matching cancer targets with therapeutic options. Progress has been hampered by the lack of cancer models that account for individual-to-individual heterogeneity within and across cancer types. Naturally occurring cancers in pet animals are heterogeneous and thus provide an opportunity to answer questions about these PMed strategies and optimize translation to human patients. In order to realize this opportunity, it is now necessary to demonstrate the feasibility of conducting molecularly-guided analysis of tumors from dogs with naturally occurring cancer in a clinically relevant setting. A proof-of-concept study was conducted by the Comparative Oncology Trials Consortium (COTC) to determine if tumor collection, prospective molecular profiling, and PMed report generation within 1 week was feasible in dogs. Thirty-one dogs with cancers of varying histologies were enrolled. Twenty-four of 31 samples (77%) successfully met all predefined QA/QC criteria and were analyzed via Affymetrix gene expression profiling. A subsequent bioinformatics workflow transformed genomic data into a personalized drug report. Average turnaround from biopsy to report generation was 116 hours (4.8 days). Unsupervised clustering of canine tumor expression data clustered by cancer type, but supervised clustering of tumors based on the personalized drug report clustered by drug class rather than cancer type. Collection and turnaround of high quality canine tumor samples, centralized pathology, analyte generation, array hybridization, and bioinformatic analyses matching gene expression to therapeutic options is achievable in a practical clinical window (strategies may aid cancer drug development.

Dana-Farber Cancer Institute: Identification of Therapeutic Targets in KRAS Driven Lung Cancer | Office of Cancer Genomics

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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.

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.

Lipid Biomarkers Identified for Liver Cancer | Center for Cancer Research

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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

Centrosome Dysfunction Contributes To Chromosome Instability, Chromoanagenesis And Genome Reprograming In Cancer.

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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.

Integrated Genomic Analysis of the Ubiquitin Pathway across Cancer Types

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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

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.

Surface activity, lipid profiles and their implications in cervical cancer.

Directory of Open Access Journals (Sweden)

Preetha A

2005-01-01

Full Text Available Background: The profiles of lipids in normal and cancerous tissues may differ revealing information about cancer development and progression. Lipids being surface active, changes in lipid profiles can manifest as altered surface activity profiles. Langmuir monolayers offer a convenient model for evaluating surface activity of biological membranes. Aims: The aims of this study were to quantify phospholipids and their effects on surface activity of normal and cancerous human cervical tissues as well as to evaluate the role of phosphatidylcholine (PC and sphingomyelin (SM in cervical cancer using Langmuir monolayers. Methods and Materials: Lipid quantification was done using thin layer chromatography and phosphorus assay. Surface activity was evaluated using Langmuir monolayers. Monolayers were formed on the surface of deionized water by spreading tissue organic phase corresponding to 1 mg of tissue and studying their surface pressure-area isotherms at body temperature. The PC and SM contents of cancerous human cervical tissues were higher than those of the normal human cervical tissues. Role of PC and SM were evaluated by adding varying amounts of these lipids to normal cervical pooled organic phase. Statistical analysis: Student′s t-test (p < 0.05 and one-way analysis of variance (ANOVA was used. Results: Our results reveals that the phosphatidylglycerol level in cancerous cervical tissue was nearly five folds higher than that in normal cervical tissue. Also PC and sphingomyelin SM were found to be the major phospholipid components in cancerous and normal cervical tissues respectively. The addition of either 1.5 µg DPPC or 0.5 µg SM /mg of tissue to the normal organic phase changed its surface activity profile to that of the cancerous tissues. Statistically significant surface activity parameters showed that PC and SM have remarkable roles in shifting the normal cervical lipophilic surface activity towards that of cancerous lipophilic

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.

The rectal cancer microRNAome - microRNA expression in rectal cancer and matched normal mucosa

DEFF Research Database (Denmark)

Gaedcke, Jochen; Grade, Marian; Camps, Jordi

2012-01-01

PURPOSE: miRNAs play a prominent role in a variety of physiologic and pathologic biologic processes, including cancer. For rectal cancers, only limited data are available on miRNA expression profiles, whereas the underlying genomic and transcriptomic aberrations have been firmly established. We t...

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

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

Molecular Concordance Between Primary Breast Cancer and Matched Metastases

DEFF Research Database (Denmark)

Krøigård, Anne Bruun; Larsen, Martin Jakob; Thomassen, Mads

2016-01-01

Clinical management of breast cancer is increasingly personalized and based on molecular profiling. Often, primary tumors are used as proxies for systemic disease at the time of recurrence. However, recent studies have revealed substantial discordances between primary tumors and metastases, both....... The purpose of this review is to illuminate the extent of cancer genome evolution through disease progression and the degree of molecular concordance between primary breast cancers and matched metastases. We present an overview of the most prominent studies investigating the expression of endocrine receptors......, transcriptomics, and genome aberrations in primary tumors and metastases. In conclusion, biopsy of metastatic lesions at recurrence of breast cancer is encouraged to provide optimal treatment of the disease. Furthermore, molecular profiling of metastatic tissue provides invaluable mechanistic insight...

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

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...

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).

Common genetic variants associated with disease from genome-wide association studies are mutually exclusive in prostate cancer and rheumatoid arthritis.

Science.gov (United States)

Orozco, Gisela; Goh, Chee L; Al Olama, Ali Amin; Benlloch-Garcia, Sara; Govindasami, Koveela; Guy, Michelle; Muir, Kenneth R; Giles, Graham G; Severi, Gianluca; Neal, David E; Hamdy, Freddie C; Donovan, Jenny L; Kote-Jarai, Zsofia; Easton, Douglas F; Eyre, Steve; Eeles, Rosalind A

2013-06-01

WHAT'S KNOWN ON THE SUBJECT? AND WHAT DOES THE STUDY ADD?: The link between inflammation and cancer has long been reported and inflammation is thought to play a role in the pathogenesis of many cancers, including prostate cancer (PrCa). Over the last 5 years, genome-wide association studies (GWAS) have reported numerous susceptibility loci that predispose individuals to many different traits. The present study aims to ascertain if there are common genetic risk profiles that might predispose individuals to both PrCa and the autoimmune inflammatory condition, rheumatoid arthritis. These results could have potential public heath impact in terms of screening and chemoprevention. To investigate if potential common pathways exist for the pathogenesis of autoimmune disease and prostate cancer (PrCa). To ascertain if the single nucleotide polymorphisms (SNPs) reported by genome-wide association studies (GWAS) as being associated with susceptibility to PrCa are also associated with susceptibility to the autoimmune disease rheumatoid arthritis (RA). The original Wellcome Trust Case Control Consortium (WTCCC) UK RA GWAS study was expanded to include a total of 3221 cases and 5272 controls. In all, 37 germline autosomal SNPs at genome-wide significance associated with PrCa risk were identified from a UK/Australian PrCa GWAS. Allele frequencies were compared for these 37 SNPs between RA cases and controls using a chi-squared trend test and corrected for multiple testing (Bonferroni). In all, 33 SNPs were able to be analysed in the RA dataset. Proxies could not be located for the SNPs in 3q26, 5p15 and for two SNPs in 17q12. After applying a Bonferroni correction for the number of SNPs tested, the SNP mapping to CCHCR1 (rs130067) retained statistically significant evidence for association (P = 6 × 10(-4) ; odds ratio [OR] = 1.15, 95% CI: 1.06-1.24); this has also been associated with psoriasis. However, further analyses showed that the association of this allele was due to

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

Development and psychometric testing of a breast cancer patient-profiling questionnaire

Directory of Open Access Journals (Sweden)

Gorini A

2015-06-01

Full Text Available Alessandra Gorini,1,2 Ketti Mazzocco,1,2 Sara Gandini,2 Elisabetta Munzone,2 Gordon McVie,2 Gabriella Pravettoni1,2 1Department of Health Science, University of Milan, Milan, Italy; 2European Institute of Oncology, Milan, Italy Introduction: The advent of “personalized medicine” has been driven by technological advances in genomics. Concentration at the subcellular level of a patient's cancer cells has meant inevitably that the “person” has been overlooked. For this reason, we think there is an urgent need to develop a truly personalized approach focusing on each patient as an individual, assessing his/her unique mental dimensions and tailoring interventions to his/her individual needs and preferences. The aim of this study was to develop and test the psychometric properties of the ALGA-Breast Cancer (ALGA-BC, a new multidimensional questionnaire that assesses the breast cancer patient's physical and mental characteristics in order to provide physicians, prior to the consultation, with a patient's profile that is supposed to facilitate subsequent communication, interaction, and information delivery between the doctor and the patient. Methods: The specific validation processes used were: content and face validity, construct validity using factor analysis, reliability and internal consistency using test–retest reliability, and Cronbach's alpha correlation coefficient. The exploratory analysis included 100 primary breast cancer patients and 730 healthy subjects. Results: The exploratory factor analysis revealed eight key factors: global self-rated health, perceived physical health, anxiety, self-efficacy, cognitive closure, memory, body image, and sexual life. Test–retest reliability and internal consistency were good. Comparing patients with a sample of healthy subjects, we also observed a general ability of the ALGA-BC questionnaire to discriminate between the two. Conclusion: The ALGA-BC questionnaire with 29 items is a valid

Metabolic profiles are principally different between cancers of the liver, pancreas and breast.

Science.gov (United States)

Budhu, Anuradha; Terunuma, Atsushi; Zhang, Geng; Hussain, S Perwez; Ambs, Stefan; Wang, Xin Wei

2014-01-01

Molecular profiling of primary tumors may facilitate the classification of patients with cancer into more homogenous biological groups to aid clinical management. Metabolomic profiling has been shown to be a powerful tool in characterizing the biological mechanisms underlying a disease but has not been evaluated for its ability to classify cancers by their tissue of origin. Thus, we assessed metabolomic profiling as a novel tool for multiclass cancer characterization. Global metabolic profiling was employed to identify metabolites in paired tumor and non-tumor liver (n=60), breast (n=130) and pancreatic (n=76) tissue specimens. Unsupervised principal component analysis showed that metabolites are principally unique to each tissue and cancer type. Such a difference can also be observed even among early stage cancers, suggesting a significant and unique alteration of global metabolic pathways associated with each cancer type. Our global high-throughput metabolomic profiling study shows that specific biochemical alterations distinguish liver, pancreatic and breast cancer and could be applied as cancer classification tools to differentiate tumors based on tissue of origin.

Renal cell carcinoma primary cultures maintain genomic and phenotypic profile of parental tumor tissues

International Nuclear Information System (INIS)

Cifola, Ingrid; Magni, Fulvio; Signorini, Stefano; Battaglia, Cristina; Perego, Roberto A; Bianchi, Cristina; Mangano, Eleonora; Bombelli, Silvia; Frascati, Fabio; Fasoli, Ester; Ferrero, Stefano; Di Stefano, Vitalba; Zipeto, Maria A

2011-01-01

Clear cell renal cell carcinoma (ccRCC) is characterized by recurrent copy number alterations (CNAs) and loss of heterozygosity (LOH), which may have potential diagnostic and prognostic applications. Here, we explored whether ccRCC primary cultures, established from surgical tumor specimens, maintain the DNA profile of parental tumor tissues allowing a more confident CNAs and LOH discrimination with respect to the original tissues. We established a collection of 9 phenotypically well-characterized ccRCC primary cell cultures. Using the Affymetrix SNP array technology, we performed the genome-wide copy number (CN) profiling of both cultures and corresponding tumor tissues. Global concordance for each culture/tissue pair was assayed evaluating the correlations between whole-genome CN profiles and SNP allelic calls. CN analysis was performed using the two CNAG v3.0 and Partek software, and comparing results returned by two different algorithms (Hidden Markov Model and Genomic Segmentation). A very good overlap between the CNAs of each culture and corresponding tissue was observed. The finding, reinforced by high whole-genome CN correlations and SNP call concordances, provided evidence that each culture was derived from its corresponding tissue and maintained the genomic alterations of parental tumor. In addition, primary culture DNA profile remained stable for at least 3 weeks, till to third passage. These cultures showed a greater cell homogeneity and enrichment in tumor component than original tissues, thus enabling a better discrimination of CNAs and LOH. Especially for hemizygous deletions, primary cultures presented more evident CN losses, typically accompanied by LOH; differently, in original tissues the intensity of these deletions was weaken by normal cell contamination and LOH calls were missed. ccRCC primary cultures are a reliable in vitro model, well-reproducing original tumor genetics and phenotype, potentially useful for future functional approaches

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...

Systematic profiling of alternative splicing signature reveals prognostic predictor for ovarian cancer.

Science.gov (United States)

Zhu, Junyong; Chen, Zuhua; Yong, Lei

2018-02-01

The majority of genes are alternatively spliced and growing evidence suggests that alternative splicing is modified in cancer and is associated with cancer progression. Systematic analysis of alternative splicing signature in ovarian cancer is lacking and greatly needed. We profiled genome-wide alternative splicing events in 408 ovarian serous cystadenocarcinoma (OV) patients in TCGA. Seven types of alternative splicing events were curated and prognostic analyses were performed with predictive models and splicing network built for OV patients. Among 48,049 mRNA splicing events in 10,582 genes, we detected 2,611 alternative splicing events in 2,036 genes which were significant associated with overall survival of OV patients. Exon skip events were the most powerful prognostic factors among the seven types. The area under the curve of the receiver-operator characteristic curve for prognostic predictor, which was built with top significant alternative splicing events, was 0.937 at 2,000 days of overall survival, indicating powerful efficiency in distinguishing patient outcome. Interestingly, splicing correlation network suggested obvious trends in the role of splicing factors in OV. In summary, we built powerful prognostic predictors for OV patients and uncovered interesting splicing networks which could be underlying mechanisms. Copyright © 2017 Elsevier Inc. All rights reserved.

Regulatory variation: an emerging vantage point for cancer biology.

Science.gov (United States)

Li, Luolan; Lorzadeh, Alireza; Hirst, Martin

2014-01-01

Transcriptional regulation involves complex and interdependent interactions of noncoding and coding regions of the genome with proteins that interact and modify them. Genetic variation/mutation in coding and noncoding regions of the genome can drive aberrant transcription and disease. In spite of accounting for nearly 98% of the genome comparatively little is known about the contribution of noncoding DNA elements to disease. Genome-wide association studies of complex human diseases including cancer have revealed enrichment for variants in the noncoding genome. A striking finding of recent cancer genome re-sequencing efforts has been the previously underappreciated frequency of mutations in epigenetic modifiers across a wide range of cancer types. Taken together these results point to the importance of dysregulation in transcriptional regulatory control in genesis of cancer. Powered by recent technological advancements in functional genomic profiling, exploration of normal and transformed regulatory networks will provide novel insight into the initiation and progression of cancer and open new windows to future prognostic and diagnostic tools. © 2013 Wiley Periodicals, Inc.

Comparison of serum lipid profiles between normal controls and breast cancer patients

Directory of Open Access Journals (Sweden)

Pikul Laisupasin

2013-01-01

Full Text Available Background: Researchers have reported association of plasma/serum lipids and lipoproteins with different cancers. Increase levels of circulating lipids and lipoproteins have been associated with breast cancer risk. Aim: The aim of this study is to compare serum lipid profiles: total-cholesterol (T-CHOL, triglyceride (TG, high density lipoprotein-cholesterol (HDL-C, low density lipoprotein-cholesterol (LDL-C and very low density lipoprotein-cholesterol (VLDL-C between breast cancer patients and normal participants. Materials and Methods: A total of 403 women in this study were divided into two groups in the period during May 2006-April 2007. Blood samples were collected from 249 patients with early stage breast cancer and 154 normal controls for serum lipid profiles (T-CHOL, TG, HDL-C, LDL-C and VLDL-C analysis using Hitachi 717 Autoanalyzer (Roche Diagnostic GmbH, Germany. TG, LDL-C and VLDL-C levels in breast cancer group were significantly increased as compared with normal controls group (P < 0.001, whereas HDL-C and T-CHOL levels were not. Results: The results of this study suggest that increased serum lipid profiles may associate with breast cancer risk in Thai women. Further studies to group important factors including, cancer stages, types of cancer, parity, and menopausal status that may affect to lipid profiles in breast cancer patients along with an investigation of new lipid profiles to clarify most lipid factors that may involve in breast cancer development are needed.

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

Prospective molecular profiling of canine cancers provides a clinically relevant comparative model for evaluating personalized medicine (PMed trials.

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Melissa Paoloni

Full Text Available Molecularly-guided trials (i.e. PMed now seek to aid clinical decision-making by matching cancer targets with therapeutic options. Progress has been hampered by the lack of cancer models that account for individual-to-individual heterogeneity within and across cancer types. Naturally occurring cancers in pet animals are heterogeneous and thus provide an opportunity to answer questions about these PMed strategies and optimize translation to human patients. In order to realize this opportunity, it is now necessary to demonstrate the feasibility of conducting molecularly-guided analysis of tumors from dogs with naturally occurring cancer in a clinically relevant setting.A proof-of-concept study was conducted by the Comparative Oncology Trials Consortium (COTC to determine if tumor collection, prospective molecular profiling, and PMed report generation within 1 week was feasible in dogs. Thirty-one dogs with cancers of varying histologies were enrolled. Twenty-four of 31 samples (77% successfully met all predefined QA/QC criteria and were analyzed via Affymetrix gene expression profiling. A subsequent bioinformatics workflow transformed genomic data into a personalized drug report. Average turnaround from biopsy to report generation was 116 hours (4.8 days. Unsupervised clustering of canine tumor expression data clustered by cancer type, but supervised clustering of tumors based on the personalized drug report clustered by drug class rather than cancer type.Collection and turnaround of high quality canine tumor samples, centralized pathology, analyte generation, array hybridization, and bioinformatic analyses matching gene expression to therapeutic options is achievable in a practical clinical window (<1 week. Clustering data show robust signatures by cancer type but also showed patient-to-patient heterogeneity in drug predictions. This lends further support to the inclusion of a heterogeneous population of dogs with cancer into the preclinical

Metabolic Risk Profile and Cancer in Korean Men and Women.

Science.gov (United States)

Ko, Seulki; Yoon, Seok-Jun; Kim, Dongwoo; Kim, A-Rim; Kim, Eun-Jung; Seo, Hye-Young

2016-05-01

Metabolic syndrome is a cluster of risk factors for type 2 diabetes mellitus and cardiovascular disease. Associations between metabolic syndrome and several types of cancer have recently been documented. We analyzed the sample cohort data from the Korean National Health Insurance Service from 2002, with a follow-up period extending to 2013. The cohort data included 99 565 individuals who participated in the health examination program and whose data were therefore present in the cohort database. The metabolic risk profile of each participant was assessed based on obesity, high serum glucose and total cholesterol levels, and high blood pressure. The occurrence of cancer was identified using Korean National Health Insurance claims data. Hazard ratios (HRs) and 95% confidence intervals (CIs) were estimated using Cox proportional hazards models, adjusting for age group, smoking status, alcohol intake, and regular exercise. A total of 5937 cases of cancer occurred during a mean follow-up period of 10.4 years. In men with a high-risk metabolic profile, the risk of colon cancer was elevated (HR, 1.40; 95% CI, 1.14 to 1.71). In women, a high-risk metabolic profile was associated with a significantly increased risk of gallbladder and biliary tract cancer (HR, 2.05; 95% CI, 1.24 to 3.42). Non-significantly increased risks were observed in men for pharynx, larynx, rectum, and kidney cancer, and in women for colon, liver, breast, and ovarian cancer. The findings of this study support the previously suggested association between metabolic syndrome and the risk of several cancers. A high-risk metabolic profile may be an important risk factor for colon cancer in Korean men and gallbladder and biliary tract cancer in Korean women.

cisMEP: an integrated repository of genomic epigenetic profiles and cis-regulatory modules in Drosophila.

Science.gov (United States)

Yang, Tzu-Hsien; Wang, Chung-Ching; Hung, Po-Cheng; Wu, Wei-Sheng

2014-01-01

Cis-regulatory modules (CRMs), or the DNA sequences required for regulating gene expression, play the central role in biological researches on transcriptional regulation in metazoan species. Nowadays, the systematic understanding of CRMs still mainly resorts to computational methods due to the time-consuming and small-scale nature of experimental methods. But the accuracy and reliability of different CRM prediction tools are still unclear. Without comparative cross-analysis of the results and combinatorial consideration with extra experimental information, there is no easy way to assess the confidence of the predicted CRMs. This limits the genome-wide understanding of CRMs. It is known that transcription factor binding and epigenetic profiles tend to determine functions of CRMs in gene transcriptional regulation. Thus integration of the genome-wide epigenetic profiles with systematically predicted CRMs can greatly help researchers evaluate and decipher the prediction confidence and possible transcriptional regulatory functions of these potential CRMs. However, these data are still fragmentary in the literatures. Here we performed the computational genome-wide screening for potential CRMs using different prediction tools and constructed the pioneer database, cisMEP (cis-regulatory module epigenetic profile database), to integrate these computationally identified CRMs with genomic epigenetic profile data. cisMEP collects the literature-curated TFBS location data and nine genres of epigenetic data for assessing the confidence of these potential CRMs and deciphering the possible CRM functionality. cisMEP aims to provide a user-friendly interface for researchers to assess the confidence of different potential CRMs and to understand the functions of CRMs through experimentally-identified epigenetic profiles. The deposited potential CRMs and experimental epigenetic profiles for confidence assessment provide experimentally testable hypotheses for the molecular mechanisms

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

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.

Accurate confidence aware clustering of array CGH tumor profiles.

NARCIS (Netherlands)

van Houte, B.P.P.; Heringa, J.

2010-01-01

Motivation: Chromosomal aberrations tend to be characteristic for given (sub)types of cancer. Such aberrations can be detected with array comparative genomic hybridization (aCGH). Clustering aCGH tumor profiles aids in identifying chromosomal regions of interest and provides useful diagnostic

Deciphering the Correlation between Breast Tumor Samples and Cell Lines by Integrating Copy Number Changes and Gene Expression Profiles

Directory of Open Access Journals (Sweden)

Yi Sun

2015-01-01

Full Text Available Breast cancer is one of the most common cancers with high incident rate and high mortality rate worldwide. Although different breast cancer cell lines were widely used in laboratory investigations, accumulated evidences have indicated that genomic differences exist between cancer cell lines and tissue samples in the past decades. The abundant molecular profiles of cancer cell lines and tumor samples deposited in the Cancer Cell Line Encyclopedia and The Cancer Genome Atlas now allow a systematical comparison of the breast cancer cell lines with breast tumors. We depicted the genomic characteristics of breast primary tumors based on the copy number variation and gene expression profiles and the breast cancer cell lines were compared to different subgroups of breast tumors. We identified that some of the breast cancer cell lines show high correlation with the tumor group that agrees with previous knowledge, while a big part of them do not, including the most used MCF7, MDA-MB-231, and T-47D. We presented a computational framework to identify cell lines that mostly resemble a certain tumor group for the breast tumor study. Our investigation presents a useful guide to bridge the gap between cell lines and tumors and helps to select the most suitable cell line models for personalized cancer studies.

A national study of breast and colorectal cancer patients' decision-making for novel personalized medicine genomic diagnostics.

Science.gov (United States)

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

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

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

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

Cancer genomics

DEFF Research Database (Denmark)

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.

Emerging applications of read profiles towards the functional annotation of the genome

DEFF Research Database (Denmark)

Pundhir, Sachin; Poirazi, Panayiota; Gorodkin, Jan

2015-01-01

is typically a result of the protocol designed to address specific research questions. The sequencing results in reads, which when mapped to a reference genome often leads to the formation of distinct patterns (read profiles). Interpretation of these read profiles is essential for their analysis in relation...... to the research question addressed. Several strategies have been employed at varying levels of abstraction ranging from a somewhat ad hoc to a more systematic analysis of read profiles. These include methods which can compare read profiles, e.g., from direct (non-sequence based) alignments to classification...... of patterns into functional groups. In this review, we highlight the emerging applications of read profiles for the annotation of non-coding RNA and cis-regulatory elements (CREs) such as enhancers and promoters. We also discuss the biological rationale behind their formation....

Funding Opportunity: Genomic Data Centers

Science.gov (United States)

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,

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.

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....

Next-generation sequence analysis of cancer xenograft models.

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Fernando J Rossello

Full Text Available Next-generation sequencing (NGS studies in cancer are limited by the amount, quality and purity of tissue samples. In this situation, primary xenografts have proven useful preclinical models. However, the presence of mouse-derived stromal cells represents a technical challenge to their use in NGS studies. We examined this problem in an established primary xenograft model of small cell lung cancer (SCLC, a malignancy often diagnosed from small biopsy or needle aspirate samples. Using an in silico strategy that assign reads according to species-of-origin, we prospectively compared NGS data from primary xenograft models with matched cell lines and with published datasets. We show here that low-coverage whole-genome analysis demonstrated remarkable concordance between published genome data and internal controls, despite the presence of mouse genomic DNA. Exome capture sequencing revealed that this enrichment procedure was highly species-specific, with less than 4% of reads aligning to the mouse genome. Human-specific expression profiling with RNA-Seq replicated array-based gene expression experiments, whereas mouse-specific transcript profiles correlated with published datasets from human cancer stroma. We conclude that primary xenografts represent a useful platform for complex NGS analysis in cancer research for tumours with limited sample resources, or those with prominent stromal cell populations.

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.

Common genomic signaling among initial DNA damage and radiation-induced apoptosis in peripheral blood lymphocytes from locally advanced breast cancer patients

DEFF Research Database (Denmark)

Henríquez-Hernández, Luis Alberto; Pinar, Beatriz; Carmona-Vigo, Ruth

2013-01-01

PURPOSE: To investigate the genomic signaling that defines sensitive lymphocytes to radiation and if such molecular profiles are consistent with clinical toxicity; trying to disclose the radiobiology mechanisms behind these cellular processes. PATIENTS AND METHODS: Twelve consecutive patients...... suffering from locally advanced breast cancer and treated with high-dose hyperfractionated radiotherapy were recruited. Initial DNA damage was measured by pulsed-field gel electrophoresis and radiation-induced apoptosis was measured by flow cytometry. Gene expression was assessed by DNA microarray. RESULTS...

Rapid Identification of Potential Drugs for Diabetic Nephropathy Using Whole-Genome Expression Profiles of Glomeruli

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Jingsong Shi

2016-01-01

Full Text Available Objective. To investigate potential drugs for diabetic nephropathy (DN using whole-genome expression profiles and the Connectivity Map (CMAP. Methodology. Eighteen Chinese Han DN patients and six normal controls were included in this study. Whole-genome expression profiles of microdissected glomeruli were measured using the Affymetrix human U133 plus 2.0 chip. Differentially expressed genes (DEGs between late stage and early stage DN samples and the CMAP database were used to identify potential drugs for DN using bioinformatics methods. Results. (1 A total of 1065 DEGs (FDR 1.5 were found in late stage DN patients compared with early stage DN patients. (2 Piperlongumine, 15d-PGJ2 (15-delta prostaglandin J2, vorinostat, and trichostatin A were predicted to be the most promising potential drugs for DN, acting as NF-κB inhibitors, histone deacetylase inhibitors (HDACIs, PI3K pathway inhibitors, or PPARγ agonists, respectively. Conclusion. Using whole-genome expression profiles and the CMAP database, we rapidly predicted potential DN drugs, and therapeutic potential was confirmed by previously published studies. Animal experiments and clinical trials are needed to confirm both the safety and efficacy of these drugs in the treatment of DN.

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,...

Genomic Copy Number Dictates a Gene-Independent Cell Response to CRISPR/Cas9 Targeting | Office of Cancer Genomics

Science.gov (United States)

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.

Genome-wide expression profiling of complex regional pain syndrome.

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Eun-Heui Jin

Full Text Available Complex regional pain syndrome (CRPS is a chronic, progressive, and devastating pain syndrome characterized by spontaneous pain, hyperalgesia, allodynia, altered skin temperature, and motor dysfunction. Although previous gene expression profiling studies have been conducted in animal pain models, there genome-wide expression profiling in the whole blood of CRPS patients has not been reported yet. Here, we successfully identified certain pain-related genes through genome-wide expression profiling in the blood from CRPS patients. We found that 80 genes were differentially expressed between 4 CRPS patients (2 CRPS I and 2 CRPS II and 5 controls (cut-off value: 1.5-fold change and p<0.05. Most of those genes were associated with signal transduction, developmental processes, cell structure and motility, and immunity and defense. The expression levels of major histocompatibility complex class I A subtype (HLA-A29.1, matrix metalloproteinase 9 (MMP9, alanine aminopeptidase N (ANPEP, l-histidine decarboxylase (HDC, granulocyte colony-stimulating factor 3 receptor (G-CSF3R, and signal transducer and activator of transcription 3 (STAT3 genes selected from the microarray were confirmed in 24 CRPS patients and 18 controls by quantitative reverse transcription-polymerase chain reaction (qRT-PCR. We focused on the MMP9 gene that, by qRT-PCR, showed a statistically significant difference in expression in CRPS patients compared to controls with the highest relative fold change (4.0±1.23 times and p = 1.4×10(-4. The up-regulation of MMP9 gene in the blood may be related to the pain progression in CRPS patients. Our findings, which offer a valuable contribution to the understanding of the differential gene expression in CRPS may help in the understanding of the pathophysiology of CRPS pain progression.

Renal cell carcinoma primary cultures maintain genomic and phenotypic profile of parental tumor tissues.

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Cifola, Ingrid; Bianchi, Cristina; Mangano, Eleonora; Bombelli, Silvia; Frascati, Fabio; Fasoli, Ester; Ferrero, Stefano; Di Stefano, Vitalba; Zipeto, Maria A; Magni, Fulvio; Signorini, Stefano; Battaglia, Cristina; Perego, Roberto A

2011-06-13

Clear cell renal cell carcinoma (ccRCC) is characterized by recurrent copy number alterations (CNAs) and loss of heterozygosity (LOH), which may have potential diagnostic and prognostic applications. Here, we explored whether ccRCC primary cultures, established from surgical tumor specimens, maintain the DNA profile of parental tumor tissues allowing a more confident CNAs and LOH discrimination with respect to the original tissues. We established a collection of 9 phenotypically well-characterized ccRCC primary cell cultures. Using the Affymetrix SNP array technology, we performed the genome-wide copy number (CN) profiling of both cultures and corresponding tumor tissues. Global concordance for each culture/tissue pair was assayed evaluating the correlations between whole-genome CN profiles and SNP allelic calls. CN analysis was performed using the two CNAG v3.0 and Partek software, and comparing results returned by two different algorithms (Hidden Markov Model and Genomic Segmentation). A very good overlap between the CNAs of each culture and corresponding tissue was observed. The finding, reinforced by high whole-genome CN correlations and SNP call concordances, provided evidence that each culture was derived from its corresponding tissue and maintained the genomic alterations of parental tumor. In addition, primary culture DNA profile remained stable for at least 3 weeks, till to third passage. These cultures showed a greater cell homogeneity and enrichment in tumor component than original tissues, thus enabling a better discrimination of CNAs and LOH. Especially for hemizygous deletions, primary cultures presented more evident CN losses, typically accompanied by LOH; differently, in original tissues the intensity of these deletions was weaken by normal cell contamination and LOH calls were missed. ccRCC primary cultures are a reliable in vitro model, well-reproducing original tumor genetics and phenotype, potentially useful for future functional approaches

Functional Genomics Uncover the Biology behind the Responsiveness of Head and Neck Squamous Cell Cancer Patients to Cetuximab.

Science.gov (United States)

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.

tRNA modification profiles of the fast-proliferating cancer cells

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Dong, Chao; Niu, Leilei; Song, Wei [State Key Laboratory of Natural and Biomimetic Drugs, School of Pharmaceutical Sciences, Department of Obstetrics and Gynecology, Peking University Third Hospital, Peking University, Beijing 100191 (China); Xiong, Xin; Zhang, Xianhua [Departmentof Pharmacy, Peking University Third Hospital, Peking University, Beijing 100191 (China); Zhang, Zhenxi; Yang, Yi; Yi, Fan [State Key Laboratory of Natural and Biomimetic Drugs, School of Pharmaceutical Sciences, Department of Obstetrics and Gynecology, Peking University Third Hospital, Peking University, Beijing 100191 (China); Zhan, Jun; Zhang, Hongquan [Department of Anatomy, Histology and Embryology, Laboratory of Molecular Cell Biology and Tumor Biology, Peking University, Beijing 100191 (China); Yang, Zhenjun; Zhang, Li-He [State Key Laboratory of Natural and Biomimetic Drugs, School of Pharmaceutical Sciences, Department of Obstetrics and Gynecology, Peking University Third Hospital, Peking University, Beijing 100191 (China); Zhai, Suodi [Departmentof Pharmacy, Peking University Third Hospital, Peking University, Beijing 100191 (China); Li, Hua, E-mail: huali88@sina.com [State Key Laboratory of Natural and Biomimetic Drugs, School of Pharmaceutical Sciences, Department of Obstetrics and Gynecology, Peking University Third Hospital, Peking University, Beijing 100191 (China); Ye, Min, E-mail: yemin@bjmu.edu.cn [State Key Laboratory of Natural and Biomimetic Drugs, School of Pharmaceutical Sciences, Department of Obstetrics and Gynecology, Peking University Third Hospital, Peking University, Beijing 100191 (China); Du, Quan, E-mail: quan.du@pku.edu.cn [State Key Laboratory of Natural and Biomimetic Drugs, School of Pharmaceutical Sciences, Department of Obstetrics and Gynecology, Peking University Third Hospital, Peking University, Beijing 100191 (China)

2016-08-05

Despite the recent progress in RNA modification study, a comprehensive modification profile is still lacking for mammalian cells. Using a quantitative HPLC/MS/MS assay, we present here a study where RNA modifications are examined in term of the major RNA species. With paired slow- and fast-proliferating cell lines, distinct RNA modification profiles are first revealed for diverse RNA species. Compared to mRNAs, increased ribose and nucleobase modifications are shown for the highly-structured tRNAs and rRNAs, lending support to their contribution to the formation of high-order structures. This study also reveals a dynamic tRNA modification profile in the fast-proliferating cells. In addition to cultured cells, this unique tRNA profile has been further confirmed with endometrial cancers and their adjacent normal tissues. Taken together, the results indicate that tRNA is a actively regulated RNA species in the fast-proliferating cancer cells, and suggest that they may play a more active role in biological process than expected. -- Highlights: •RNA modifications were first examined in term of the major RNA species. •A dynamic tRNA modifications was characterized for the fast-proliferating cells. •The unique tRNA profile was confirmed with endometrial cancers and their adjacent normal tissues. •tRNA was predicted as an actively regulated RNA species in the fast-proliferating cancer cells.

tRNA modification profiles of the fast-proliferating cancer cells

International Nuclear Information System (INIS)

Dong, Chao; Niu, Leilei; Song, Wei; Xiong, Xin; Zhang, Xianhua; Zhang, Zhenxi; Yang, Yi; Yi, Fan; Zhan, Jun; Zhang, Hongquan; Yang, Zhenjun; Zhang, Li-He; Zhai, Suodi; Li, Hua; Ye, Min; Du, Quan

2016-01-01

Despite the recent progress in RNA modification study, a comprehensive modification profile is still lacking for mammalian cells. Using a quantitative HPLC/MS/MS assay, we present here a study where RNA modifications are examined in term of the major RNA species. With paired slow- and fast-proliferating cell lines, distinct RNA modification profiles are first revealed for diverse RNA species. Compared to mRNAs, increased ribose and nucleobase modifications are shown for the highly-structured tRNAs and rRNAs, lending support to their contribution to the formation of high-order structures. This study also reveals a dynamic tRNA modification profile in the fast-proliferating cells. In addition to cultured cells, this unique tRNA profile has been further confirmed with endometrial cancers and their adjacent normal tissues. Taken together, the results indicate that tRNA is a actively regulated RNA species in the fast-proliferating cancer cells, and suggest that they may play a more active role in biological process than expected. -- Highlights: •RNA modifications were first examined in term of the major RNA species. •A dynamic tRNA modifications was characterized for the fast-proliferating cells. •The unique tRNA profile was confirmed with endometrial cancers and their adjacent normal tissues. •tRNA was predicted as an actively regulated RNA species in the fast-proliferating cancer cells.

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 (...

Personalizing therapy for colorectal cancer.

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Wong, Ashley; Ma, Brigette B Y

2014-01-01

Colorectal cancer (CRC) is the third most commonly diagnosed cancer worldwide. Several important scientific discoveries in the molecular biology of CRC have changed clinical practice in oncology. These included the comprehensive genome-wide profiling of CRC by the Cancer Genome Atlas Network, the discovery of mutations along the RAS-RAF signaling pathway as major determinants of response to antibodies against the epidermal growth factor receptor, the elucidation of new molecular subsets of CRC or gene signatures that may predict clinical outcome after adjuvant chemotherapy, and the innovative targeting of the family of vascular endothelial growth factor and receptors. These new data have allowed oncologists to individualize drug therapy on the basis of a patient's tumor's unique molecular profile, especially in the management of metastatic CRC. This review article will discuss the progress of personalized medicine in the contemporary management of CRC. Copyright © 2014 AGA Institute. Published by Elsevier Inc. All rights reserved.

The Valuable Role of Measuring Serum Lipid Profile in Cancer Progression

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Farahnaz Ghahremanfard

2015-09-01

Full Text Available Objective: Serum lipid levels are not only associated with etiology, but also with prognosis in cancer. To investigate this issue further, we aimed to evaluate the serum levels of lipids in association with the most important prognostic indicators in cancer patients at the start of chemotherapy. Methods: In a retrospective cross-sectional study, using existing medical records obtained from 2009–2014, the data of all incident cancer cases in Iranian patients referred to the Semnan oncology clinic for chemotherapy were analyzed. Data on demographics, cancer type, prognostic indicators (e.g. lymph node involvement, metastasis, and stage of disease, as well as the patient’s lipid profile were collected. We used multiple logistic regression models to show the relationship between prognosis indicators and lipid profile adjusting for age, gender, and type of cancer. Results: The data of 205 patients was gathered. We found a significant difference in the lipid profile between different types of cancers (breast, colon, gastric, and ovarian. With the exception of high-density lipoprotein levels in women, which were higher than in men, the means of other lipid profiles were similar between the genders. There was a significant association between higher levels of low-density lipoprotein (LDL >110mg/dL in the serum and metastasis (adjusted odds ratio=2.4, 95% CI 1.2–3.5. No significant association was reported between lipid profile and lymph nodes involvement and stage of the disease. Conclusion: Our study suggested a benefit of measuring serum levels of lipids for predicting cancer progression. Increased LDL levels can be considered a predictive factor for increasing the risk of metastasis.

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.

Reduced fatalism and increased prevention behavior after two high-profile lung cancer events.

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Portnoy, David B; Leach, Corinne R; Kaufman, Annette R; Moser, Richard P; Alfano, Catherine M

2014-01-01

The positive impact of media coverage of high-profile cancer events on cancer prevention behaviors is well-established. However, less work has focused on potential adverse psychological reactions to such events, such as fatalism. Conducting 3 studies, the authors explored how the lung cancer death of Peter Jennings and diagnosis of Dana Reeve in 2005 related to fatalism. Analysis of a national media sample in Study 1 found that media coverage of these events often focused on reiterating the typical profile of those diagnosed with lung cancer; 38% of the media mentioned at least 1 known risk factor for lung cancer, most often smoking. Data from a nationally representative survey in Study 2 found that respondents reported lower lung cancer fatalism, after, compared with before, the events (OR = 0.16, 95% CI [0.03, 0.93]). A sustained increase in call volume to the national tobacco Quitline after these events was found in Study 3. These results suggest that there is a temporal association between high-profile cancer events, the subsequent media coverage, psychological outcomes, and cancer prevention behaviors. These results suggest that high-profile cancer events could be leveraged as an opportunity for large-scale public heath communication campaigns through the dissemination of cancer prevention messages and services.

TIMP-1 expression in human colorectal cancer is associated with TGF-B1, LOXL2, INHBA1, TNF-AIP6 and TIMP-2 transcript profiles

DEFF Research Database (Denmark)

Offenberg, Hanne Kjær; Brunner, Nils; Mansilla, Francisco

2008-01-01

colorectal cancer (CRC) and the other TIMPs 2-4, which have also been associated with the progression of colorectal cancer. Genome-wide expression profiling of 172 CRC and normal mucosa samples was used to identify transcript changes for the genes under investigation. We found that TIMP-1 was up...... with the synthesis of extracellullar matrix, genes involved in the TGF-beta signalling pathway, and genes that are likely transcribed by the tumour cells. These insights add to the complex picture emerging about the regulation of TIMPs in colorectal cancer....... that colorectal cancer patients have increased plasma levels of the tissue inhibitor of metalloproteinases-1 (TIMP-1), and that high plasma TIMP-1 levels are associated with short colorectal cancer patient survival. However, although TIMP-1 has been extensively studied in cancer, very little is known about how...

Genetics and Genomics: Discovery, Validation, and Utility of Novel Tools for management of Prostate Cancer

Directory of Open Access Journals (Sweden)

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.

Genome-scale analysis of aberrant DNA methylation in colorectal cancer

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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

Understanding the development of human bladder cancer by using a whole-organ genomic mapping strategy.

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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

Comparative genomic analysis of Lactobacillus plantarum ZJ316 reveals its genetic adaptation and potential probiotic profiles.

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Li, Ping; Li, Xuan; Gu, Qing; Lou, Xiu-Yu; Zhang, Xiao-Mei; Song, Da-Feng; Zhang, Chen

2016-08-01

In previous studies, Lactobacillus plantarum ZJ316 showed probiotic properties, such as antimicrobial activity against various pathogens and the capacity to significantly improve pig growth and pork quality. The purpose of this study was to reveal the genes potentially related to its genetic adaptation and probiotic profiles based on comparative genomic analysis. The genome sequence of L. plantarum ZJ316 was compared with those of eight L. plantarum strains deposited in GenBank. BLASTN, Mauve, and MUMmer programs were used for genome alignment and comparison. CRISPRFinder was applied for searching the clustered regularly interspaced short palindromic repeats (CRISPRs). We identified genes that encode proteins related to genetic adaptation and probiotic profiles, including carbohydrate transport and metabolism, proteolytic enzyme systems and amino acid biosynthesis, CRISPR adaptive immunity, stress responses, bile salt resistance, ability to adhere to the host intestinal wall, exopolysaccharide (EPS) biosynthesis, and bacteriocin biosynthesis. Comparative characterization of the L. plantarum ZJ316 genome provided the genetic basis for further elucidating the functional mechanisms of its probiotic properties. ZJ316 could be considered a potential probiotic candidate.

Comparative genomic analysis of Lactobacillus plantarum ZJ316 reveals its genetic adaptation and potential probiotic profiles* #

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Li, Ping; Li, Xuan; Gu, Qing; Lou, Xiu-yu; Zhang, Xiao-mei; Song, Da-feng; Zhang, Chen

2016-01-01

Objective: In previous studies, Lactobacillus plantarum ZJ316 showed probiotic properties, such as antimicrobial activity against various pathogens and the capacity to significantly improve pig growth and pork quality. The purpose of this study was to reveal the genes potentially related to its genetic adaptation and probiotic profiles based on comparative genomic analysis. Methods: The genome sequence of L. plantarum ZJ316 was compared with those of eight L. plantarum strains deposited in GenBank. BLASTN, Mauve, and MUMmer programs were used for genome alignment and comparison. CRISPRFinder was applied for searching the clustered regularly interspaced short palindromic repeats (CRISPRs). Results: We identified genes that encode proteins related to genetic adaptation and probiotic profiles, including carbohydrate transport and metabolism, proteolytic enzyme systems and amino acid biosynthesis, CRISPR adaptive immunity, stress responses, bile salt resistance, ability to adhere to the host intestinal wall, exopolysaccharide (EPS) biosynthesis, and bacteriocin biosynthesis. Conclusions: Comparative characterization of the L. plantarum ZJ316 genome provided the genetic basis for further elucidating the functional mechanisms of its probiotic properties. ZJ316 could be considered a potential probiotic candidate. PMID:27487802

Ezrin and E-cadherin expression profile in cervical cytology: a prognostic marker for tumor progression in cervical cancer.

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Zacapala-Gómez, Ana E; Navarro-Tito, Napoleón; Alarcón-Romero, Luz Del C; Ortuño-Pineda, Carlos; Illades-Aguiar, Berenice; Castañeda-Saucedo, Eduardo; Ortiz-Ortiz, Julio; Garibay-Cerdenares, Olga L; Jiménez-López, Marco A; Mendoza-Catalán, Miguel A

2018-03-27

Cervical cancer (CC) is the fourth cause of mortality by neoplasia in women worldwide. The use of immunomarkers is an alternative tool to complement currently used algorithms for detection of cancer, and to improve selection of therapeutic schemes. Aberrant expression of Ezrin and E-cadherin play an important role in tumor invasion. In this study we analyzed Ezrin and E-cadherin expression in liquid-based cervical cytology samples, and evaluated their potential use as prognostic immunomarkers. Immunocytochemical staining of Ezrin and E-cadherin was performed in cervical samples of 125 patients. The cytological or histological diagnostic was performed by Papanicolaou staining or H&E staining, respectively. HPV genotyping was determined using INNO-LIPA Genotyping Extra kit and the HPV physical status by in situ hybridization. Ezrin expression in HaCaT, HeLa and SiHa cell lines was determined by immunocytochemistry, immunofluorescence and Western blot. High Ezrin expression was observed in cervical cancer samples (70%), samples with multiple infection by HR-HPV (43%), and samples with integrated viral genome (47%). High Ezrin expression was associated with degree of SIL, viral genotype and physical status. In contrast, low E-cadherin expression was found in cervical cancer samples (95%), samples with multiple infection by HR-HPV/LR-HPV (87%) and integrated viral genome (72%). Low E-cadherin expression was associated with degree of SIL and viral genotype. Interestingly, Ezrin nuclear staining was associated with degree of SIL and viral genotype. High Ezrin expression, high percent of nuclear Ezrin and low E-cadherin expression behaved as risk factors for progression to HSIL and cervical cancer. Ezrin and E-cadherin expression profile in cervical cytology samples could be a potential prognostic marker, useful for identifying cervical lesions with a high-risk of progression to cervical cancer.

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.

Cooperation and conflict in cancer: An evolutionary perspective

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Jonathan Featherston

2012-09-01

Full Text Available Evolutionary approaches to carcinogenesis have gained prominence in the literature and enhanced our understanding of cancer. However, an appreciation of neoplasia in the context of evolutionary transitions, particularly the transition from independent genes to a fullyintegrated genome, is largely absent. In the gene–genome evolutionary transition, mobile genetic elements (MGEs can be studied as the extant exemplars of selfish autonomous lowerlevel units that cooperated to form a higher-level, functionally integrated genome. Here,we discuss levels of selection in cancer cells. In particular, we examine the tension between gene and genome units of selection by examining the expression profiles of MGE domains in an array of human cancers. Overall, across diverse cancers, there is an aberrant expression of several families of mobile elements, including the most common MGE in the human genome, retrotransposon LINE 1. These results indicate an alternative life-history strategy for MGEs in the cancers studied. Whether the aberrant expression is the cause or effect oftumourigenesis is unknown, although some evidence suggests that dysregulation of MGEs can play a role in cancer origin and progression. These data are interpreted in combination with phylostratigraphic reports correlating the origin of cancer genes with multicellularity and other potential increases in complexity in cancer cell populations. Cooperation and conflict between individuals at the gene, genome and cell level provide an evolutionary medicineperspective of cancer that enhances our understanding of disease pathogenesis and treatment.

Development of Castration Resistant Prostate Cancer can be Predicted by a DNA Hypermethylation Profile.

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Angulo, Javier C; Andrés, Guillermo; Ashour, Nadia; Sánchez-Chapado, Manuel; López, Jose I; Ropero, Santiago

2016-03-01

Detection of DNA hypermethylation has emerged as a novel molecular biomarker for prostate cancer diagnosis and evaluation of prognosis. We sought to define whether a hypermethylation profile of patients with prostate cancer on androgen deprivation would predict castrate resistant prostate cancer. Genome-wide methylation analysis was performed using a methylation cancer panel in 10 normal prostates and 45 tumor samples from patients placed on androgen deprivation who were followed until castrate resistant disease developed. Castrate resistant disease was defined according to EAU (European Association of Urology) guideline criteria. Two pathologists reviewed the Gleason score, Ki-67 index and neuroendocrine differentiation. Hierarchical clustering analysis was performed and relationships with outcome were investigated by Cox regression and log rank analysis. We found 61 genes that were significantly hypermethylated in greater than 20% of tumors analyzed. Three clusters of patients were characterized by a DNA methylation profile, including 1 at risk for earlier castrate resistant disease (log rank p = 0.019) and specific mortality (log rank p = 0.002). Hypermethylation of ETV1 (HR 3.75) and ZNF215 (HR 2.89) predicted disease progression despite androgen deprivation. Hypermethylation of IRAK3 (HR 13.72), ZNF215 (HR 4.81) and SEPT9 (HR 7.64) were independent markers of prognosis. Prostate specific antigen greater than 25 ng/ml, Gleason pattern 5, Ki-67 index greater than 12% and metastasis at diagnosis also predicted a negative response to androgen deprivation. Study limitations included the retrospective design and limited number of cases. Epigenetic silencing of the mentioned genes could be novel molecular markers for the prognosis of advanced prostate cancer. It might predict castrate resistance during hormone deprivation and, thus, disease specific mortality. Gene hypermethylation is associated with disease progression in patients who receive hormone therapy. It

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.

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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

Survival-related profile, pathways, and transcription factors in ovarian cancer.

Directory of Open Access Journals (Sweden)

Anne P G Crijns

2009-02-01

Full Text Available BACKGROUND: Ovarian cancer has a poor prognosis due to advanced stage at presentation and either intrinsic or acquired resistance to classic cytotoxic drugs such as platinum and taxoids. Recent large clinical trials with different combinations and sequences of classic cytotoxic drugs indicate that further significant improvement in prognosis by this type of drugs is not to be expected. Currently a large number of drugs, targeting dysregulated molecular pathways in cancer cells have been developed and are introduced in the clinic. A major challenge is to identify those patients who will benefit from drugs targeting these specific dysregulated pathways.The aims of our study were (1 to develop a gene expression profile associated with overall survival in advanced stage serous ovarian cancer, (2 to assess the association of pathways and transcription factors with overall survival, and (3 to validate our identified profile and pathways/transcription factors in an independent set of ovarian cancers. METHODS AND FINDINGS: According to a randomized design, profiling of 157 advanced stage serous ovarian cancers was performed in duplicate using approximately 35,000 70-mer oligonucleotide microarrays. A continuous predictor of overall survival was built taking into account well-known issues in microarray analysis, such as multiple testing and overfitting. A functional class scoring analysis was utilized to assess pathways/transcription factors for their association with overall survival. The prognostic value of genes that constitute our overall survival profile was validated on a fully independent, publicly available dataset of 118 well-defined primary serous ovarian cancers. Furthermore, functional class scoring analysis was also performed on this independent dataset to assess the similarities with results from our own dataset. An 86-gene overall survival profile discriminated between patients with unfavorable and favorable prognosis (median survival, 19

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.

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.

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.

Identification of neutral tumor evolution across cancer types

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Barnes, Chris P; Graham, Trevor A; Sottoriva, Andrea

2016-01-01

Despite extraordinary efforts to profile cancer genomes, interpreting the vast amount of genomic data in the light of cancer evolution remains challenging. Here we demonstrate that neutral tumor evolution results in a power-law distribution of the mutant allele frequencies reported by next-generation sequencing of tumor bulk samples. We find that the neutral power-law fits with high precision 323 of 904 cancers from 14 types, selected from different cohorts. In malignancies identified as neutral, all clonal selection occurred prior to the onset of cancer growth and not in later-arising subclones, resulting in numerous passenger mutations that are responsible for intra-tumor heterogeneity. Reanalyzing cancer sequencing data within the neutral framework allowed the measurement, in each patient, of both the in vivo mutation rate and the order and timing of mutations. This result provides a new way to interpret existing cancer genomic data and to discriminate between functional and non-functional intra-tumor heterogeneity. PMID:26780609

Targetable kinase-activating lesions in Ph-like acute lymphoblastic leukemia | Office of Cancer Genomics

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Publication Abstract:  Philadelphia chromosome-like acute lymphoblastic leukemia (Ph-like ALL) is characterized by a gene-expression profile similar to that of BCR-ABL1-positive ALL, alterations of lymphoid transcription factor genes, and a poor outcome. The frequency and spectrum of genetic alterations in Ph-like ALL and its responsiveness to tyrosine kinase inhibition are undefined, especially in adolescents and adults. We performed genomic profiling of 1725 patients with precursor B-cell ALL and detailed genomic analysis of 154 patients with Ph-like ALL.

A Classification Framework Applied to Cancer Gene Expression Profiles

Directory of Open Access Journals (Sweden)

Hussein Hijazi

2013-01-01

Full Text Available Classification of cancer based on gene expression has provided insight into possible treatment strategies. Thus, developing machine learning methods that can successfully distinguish among cancer subtypes or normal versus cancer samples is important. This work discusses supervised learning techniques that have been employed to classify cancers. Furthermore, a two-step feature selection method based on an attribute estimation method (e.g., ReliefF and a genetic algorithm was employed to find a set of genes that can best differentiate between cancer subtypes or normal versus cancer samples. The application of different classification methods (e.g., decision tree, k-nearest neighbor, support vector machine (SVM, bagging, and random forest on 5 cancer datasets shows that no classification method universally outperforms all the others. However, k-nearest neighbor and linear SVM generally improve the classification performance over other classifiers. Finally, incorporating diverse types of genomic data (e.g., protein-protein interaction data and gene expression increase the prediction accuracy as compared to using gene expression alone.

Molecular Imaging and Precision Medicine in Head and Neck Cancer.

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Mena, Esther; Thippsandra, Shwetha; Yanamadala, Anusha; Redy, Siddaling; Pattanayak, Puskar; Subramaniam, Rathan M

2017-01-01

The concept of using tumor genomic profiling information has revolutionized personalized cancer treatment. Head and neck (HN) cancer management is being influenced by recent discoveries of activating mutations in epidermal growth factor receptor and related targeted therapies with tyrosine kinase inhibitors, targeted therapies for Kristen Rat Sarcoma, and MET proto-oncogenes. Molecular imaging using PET plays an important role in assessing the biologic behavior of HN cancer with the goal of delivering individualized cancer treatment. This review summarizes recent genomic discoveries in HN cancer and their implications for functional PET imaging in assessing response to targeted therapies, and drug resistance mechanisms. Copyright © 2016 Elsevier Inc. All rights reserved.

Global Expression Profiling and Pathway Analysis of Mouse Mammary Tumor Reveals Strain and Stage Specific Dysregulated Pathways in Breast Cancer Progression.

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Mei, Yan; Yang, Jun-Ping; Lang, Yan-Hong; Peng, Li-Xia; Yang, Ming-Ming; Liu, Qin; Meng, Dong-Fang; Zheng, Li-Sheng; Qiang, Yuan-Yuan; Xu, Liang; Li, Chang-Zhi; Wei, Wen-Wen; Niu, Ting; Peng, Xing-Si; Yang, Qin; Lin, Fen; Hu, Hao; Xu, Hong-Fa; Huang, Bi-Jun; Wang, Li-Jing; Qian, Chao-Nan

2018-05-01

It is believed that the alteration of tissue microenvironment would affect cancer initiation and progression. However, little is known in terms of the underlying molecular mechanisms that would affect the initiation and progression of breast cancer. In the present study, we use two murine mammary tumor models with different speeds of tumor initiation and progression for whole genome expression profiling to reveal the involved genes and signaling pathways. The pathways regulating PI3K-Akt signaling and Ras signaling were activated in Fvb mice and promoted tumor progression. Contrastingly, the pathways regulating apoptosis and cellular senescence were activated in Fvb.B6 mice and suppressed tumor progression. We identified distinct patterns of oncogenic pathways activation at different stages of breast cancer, and uncovered five oncogenic pathways that were activated in both human and mouse breast cancers. The genes and pathways discovered in our study would be useful information for other researchers and drug development.

Genomic Alterations Observed in Colitis-Associated Cancers Are Distinct From Those Found in Sporadic Colorectal Cancers and Vary by Type of Inflammatory Bowel Disease.

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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.

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

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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

Molecular Profiles for Lung Cancer Pathogenesis and Detection in U.S. Veterans

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2013-10-01

independent survival and growth of cancer cells, including a catalytic subunit of phosphatidylinositol 3- kinase (PIK3CA) (33) and the SH2 -containg...comparative genomic hybridization: implications of the phosphatidylinositol 3- kinase pathway. Cancer Res. 2002;62:3636-40. 28. Massion PP, Zou Y, Uner

Analysis of The Cancer Genome Atlas sequencing data reveals novel properties of the human papillomavirus 16 genome in head and neck squamous cell carcinoma.

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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.

Comprehensive evaluation of genome-wide 5-hydroxymethylcytosine profiling approaches in human DNA.

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Skvortsova, Ksenia; Zotenko, Elena; Luu, Phuc-Loi; Gould, Cathryn M; Nair, Shalima S; Clark, Susan J; Stirzaker, Clare

2017-01-01

The discovery that 5-methylcytosine (5mC) can be oxidized to 5-hydroxymethylcytosine (5hmC) by the ten-eleven translocation (TET) proteins has prompted wide interest in the potential role of 5hmC in reshaping the mammalian DNA methylation landscape. The gold-standard bisulphite conversion technologies to study DNA methylation do not distinguish between 5mC and 5hmC. However, new approaches to mapping 5hmC genome-wide have advanced rapidly, although it is unclear how the different methods compare in accurately calling 5hmC. In this study, we provide a comparative analysis on brain DNA using three 5hmC genome-wide approaches, namely whole-genome bisulphite/oxidative bisulphite sequencing (WG Bis/OxBis-seq), Infinium HumanMethylation450 BeadChip arrays coupled with oxidative bisulphite (HM450K Bis/OxBis) and antibody-based immunoprecipitation and sequencing of hydroxymethylated DNA (hMeDIP-seq). We also perform loci-specific TET-assisted bisulphite sequencing (TAB-seq) for validation of candidate regions. We show that whole-genome single-base resolution approaches are advantaged in providing precise 5hmC values but require high sequencing depth to accurately measure 5hmC, as this modification is commonly in low abundance in mammalian cells. HM450K arrays coupled with oxidative bisulphite provide a cost-effective representation of 5hmC distribution, at CpG sites with 5hmC levels >~10%. However, 5hmC analysis is restricted to the genomic location of the probes, which is an important consideration as 5hmC modification is commonly enriched at enhancer elements. Finally, we show that the widely used hMeDIP-seq method provides an efficient genome-wide profile of 5hmC and shows high correlation with WG Bis/OxBis-seq 5hmC distribution in brain DNA. However, in cell line DNA with low levels of 5hmC, hMeDIP-seq-enriched regions are not detected by WG Bis/OxBis or HM450K, either suggesting misinterpretation of 5hmC calls by hMeDIP or lack of sensitivity of the latter methods. We

Emory University: High-Throughput Protein-Protein Interaction Dataset for Lung Cancer-Associated Genes | Office of Cancer Genomics

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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

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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.

Adjuvant tamoxifen influences the lipid profile in breast cancer patients.

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Lin, Che; Chen, Li-Sheng; Kuo, Shou-Jen; Chen, Dar-Ren

2014-02-01

Currently there is a debate regarding whether tamoxifen used in breast cancer has an impact on lipid profiles. The aim of this study was to determine whether tamoxifen has an impact on the serum lipid profile in Taiwanese women. Data of 109 patients were collected from the routine clinical follow-up for women with hormone receptor-positive breast cancer who were treated between July 2005 and March 2008. These patients were divided into 2 subgroups, based on their tumor grade and lymph node status. Subgroup 1 patients had tumor grade I/II and a negative lymph node status. Those patients with tumor grade III or a positive lymph node status were defined as subgroup 2. In the 109 patients, the mean serum total cholesterol (TC) levels after tamoxifen treatment, as well as the serum low-density lipoprotein cholesterol (LDL-C) levels, were lower than the baseline levels, with statistically significant differences. Treatment with tamoxifen lowered the serum TC and LDL-C levels in both subgroups. The results indicate that tamoxifen has an impact on the serum lipid profile of breast cancer patients in Taiwan. Physicians should follow up the lipid profile in these patients.

Analysis of Epstein-Barr Virus Genomes and Expression Profiles in Gastric Adenocarcinoma.

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Borozan, Ivan; Zapatka, Marc; Frappier, Lori; Ferretti, Vincent

2018-01-15

Epstein-Barr virus (EBV) is a causative agent of a variety of lymphomas, nasopharyngeal carcinoma (NPC), and ∼9% of gastric carcinomas (GCs). An important question is whether particular EBV variants are more oncogenic than others, but conclusions are currently hampered by the lack of sequenced EBV genomes. Here, we contribute to this question by mining whole-genome sequences of 201 GCs to identify 13 EBV-positive GCs and by assembling 13 new EBV genome sequences, almost doubling the number of available GC-derived EBV genome sequences and providing the first non-Asian EBV genome sequences from GC. Whole-genome sequence comparisons of all EBV isolates sequenced to date (85 from tumors and 57 from healthy individuals) showed that most GC and NPC EBV isolates were closely related although American Caucasian GC samples were more distant, suggesting a geographical component. However, EBV GC isolates were found to contain some consistent changes in protein sequences regardless of geographical origin. In addition, transcriptome data available for eight of the EBV-positive GCs were analyzed to determine which EBV genes are expressed in GC. In addition to the expected latency proteins (EBNA1, LMP1, and LMP2A), specific subsets of lytic genes were consistently expressed that did not reflect a typical lytic or abortive lytic infection, suggesting a novel mechanism of EBV gene regulation in the context of GC. These results are consistent with a model in which a combination of specific latent and lytic EBV proteins promotes tumorigenesis. IMPORTANCE Epstein-Barr virus (EBV) is a widespread virus that causes cancer, including gastric carcinoma (GC), in a small subset of individuals. An important question is whether particular EBV variants are more cancer associated than others, but more EBV sequences are required to address this question. Here, we have generated 13 new EBV genome sequences from GC, almost doubling the number of EBV sequences from GC isolates and providing the

Methylation-sensitive amplified polymorphism-based genome-wide analysis of cytosine methylation profiles in Nicotiana tabacum cultivars.

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Jiao, J; Wu, J; Lv, Z; Sun, C; Gao, L; Yan, X; Cui, L; Tang, Z; Yan, B; Jia, Y

2015-11-26

This study aimed to investigate cytosine methylation profiles in different tobacco (Nicotiana tabacum) cultivars grown in China. Methylation-sensitive amplified polymorphism was used to analyze genome-wide global methylation profiles in four tobacco cultivars (Yunyan 85, NC89, K326, and Yunyan 87). Amplicons with methylated C motifs were cloned by reamplified polymerase chain reaction, sequenced, and analyzed. The results show that geographical location had a greater effect on methylation patterns in the tobacco genome than did sampling time. Analysis of the CG dinucleotide distribution in methylation-sensitive polymorphic restriction fragments suggested that a CpG dinucleotide cluster-enriched area is a possible site of cytosine methylation in the tobacco genome. The sequence alignments of the Nia1 gene (that encodes nitrate reductase) in Yunyan 87 in different regions indicate that a C-T transition might be responsible for the tobacco phenotype. T-C nucleotide replacement might also be responsible for the tobacco phenotype and may be influenced by geographical location.

Assessment of DNA methylation profiling and copy number variation as indications of clonal relationship in ipsilateral and contralateral breast cancers to distinguish recurrent breast cancer from a second primary tumour

International Nuclear Information System (INIS)

Huang, Katie T.; Mikeska, Thomas; Li, Jason; Takano, Elena A.; Millar, Ewan K A; Graham, Peter H.; Boyle, Samantha E.; Campbell, Ian G.; Speed, Terence P.; Dobrovic, Alexander; Fox, Stephen B.

2015-01-01

Patients with breast cancer have an increased risk of developing subsequent breast cancers. It is important to distinguish whether these tumours are de novo or recurrences of the primary tumour in order to guide the appropriate therapy. Our aim was to investigate the use of DNA methylation profiling and array comparative genomic hybridization (aCGH) to determine whether the second tumour is clonally related to the first tumour. Methylation-sensitive high-resolution melting was used to screen promoter methylation in a panel of 13 genes reported as methylated in breast cancer (RASSF1A, TWIST1, APC, WIF1, MGMT, MAL, CDH13, RARβ, BRCA1, CDH1, CDKN2A, TP73, and GSTP1) in 29 tumour pairs (16 ipsilateral and 13 contralateral). Using the methylation profile of these genes, we employed a Bayesian and an empirical statistical approach to estimate clonal relationship. Copy number alterations were analysed using aCGH on the same set of tumour pairs. There is a higher probability of the second tumour being recurrent in ipsilateral tumours compared with contralateral tumours (38 % versus 8 %; p <0.05) based on the methylation profile. Using previously reported recurrence rates as Bayesian prior probabilities, we classified 69 % of ipsilateral and 15 % of contralateral tumours as recurrent. The inferred clonal relationship results of the tumour pairs were generally concordant between methylation profiling and aCGH. Our results show that DNA methylation profiling as well as aCGH have potential as diagnostic tools in improving the clinical decisions to differentiate recurrences from a second de novo tumour. The online version of this article (doi:10.1186/s12885-015-1676-0) contains supplementary material, which is available to authorized users

Proteome Profiling Outperforms Transcriptome Profiling for Coexpression Based Gene Function Prediction

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Wang, Jing; Ma, Zihao; Carr, Steven A.; Mertins, Philipp; Zhang, Hui; Zhang, Zhen; Chan, Daniel W.; Ellis, Matthew J. C.; Townsend, R. Reid; Smith, Richard D.; McDermott, Jason E.; Chen, Xian; Paulovich, Amanda G.; Boja, Emily S.; Mesri, Mehdi; Kinsinger, Christopher R.; Rodriguez, Henry; Rodland, Karin D.; Liebler, Daniel C.; Zhang, Bing

2016-11-11

Coexpression of mRNAs under multiple conditions is commonly used to infer cofunctionality of their gene products despite well-known limitations of this “guilt-by-association” (GBA) approach. Recent advancements in mass spectrometry-based proteomic technologies have enabled global expression profiling at the protein level; however, whether proteome profiling data can outperform transcriptome profiling data for coexpression based gene function prediction has not been systematically investigated. Here, we address this question by constructing and analyzing mRNA and protein coexpression networks for three cancer types with matched mRNA and protein profiling data from The Cancer Genome Atlas (TCGA) and the Clinical Proteomic Tumor Analysis Consortium (CPTAC). Our analyses revealed a marked difference in wiring between the mRNA and protein coexpression networks. Whereas protein coexpression was driven primarily by functional similarity between coexpressed genes, mRNA coexpression was driven by both cofunction and chromosomal colocalization of the genes. Functionally coherent mRNA modules were more likely to have their edges preserved in corresponding protein networks than functionally incoherent mRNA modules. Proteomic data strengthened the link between gene expression and function for at least 75% of Gene Ontology (GO) biological processes and 90% of KEGG pathways. A web application Gene2Net (http://cptac.gene2net.org) developed based on the three protein coexpression networks revealed novel gene-function relationships, such as linking ERBB2 (HER2) to lipid biosynthetic process in breast cancer, identifying PLG as a new gene involved in complement activation, and identifying AEBP1 as a new epithelial-mesenchymal transition (EMT) marker. Our results demonstrate that proteome profiling outperforms transcriptome profiling for coexpression based gene function prediction. Proteomics should be integrated if not preferred in gene function and human disease studies

Clinical Trials of Precision Medicine through Molecular Profiling: Focus on Breast Cancer.

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Zardavas, Dimitrios; Piccart-Gebhart, Martine

2015-01-01

High-throughput technologies of molecular profiling in cancer, such as gene-expression profiling and next-generation sequencing, are expanding our knowledge of the molecular landscapes of several cancer types. This increasing knowledge coupled with the development of several molecularly targeted agents hold the promise for personalized cancer medicine to be fully realized. Moreover, an expanding armamentarium of targeted agents has been approved for the treatment of specific molecular cancer subgroups in different diagnoses. According to this paradigm, treatment selection should be dictated by the specific molecular aberrations found in each patient's tumor. The classical clinical trials paradigm of patients' eligibility being based on clinicopathologic parameters is being abandoned, with current clinical trials enrolling patients on the basis of specific molecular aberrations. New, innovative trial designs have been generated to better tackle the multiple challenges induced by the increasing molecular fragmentation of cancer, namely: (1) longitudinal cohort studies with or without downstream trials, (2) studies assessing the clinical utility of molecular profiling, (3) master or umbrella trials, (4) basket trials, (5) N-of-1 trials, and (6) adaptive design trials. This article provides an overview of the challenges for clinical trials in the era of molecular profiling of cancer. Subsequently, innovative trial designs with respective examples and their potential to expedite efficient clinical development of targeted anticancer agents is discussed.

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.

Tissue metabolic profiling of human gastric cancer assessed by 1H NMR

International Nuclear Information System (INIS)

Wang, Huijuan; Zhang, Hailong; Deng, Pengchi; Liu, Chunqi; Li, Dandan; Jie, Hui; Zhang, Hu; Zhou, Zongguang; Zhao, Ying-Lan

2016-01-01

Gastric cancer is the fourth most common cancer and the second most deadly cancer worldwide. Study on molecular mechanisms of carcinogenesis will play a significant role in diagnosing and treating gastric cancer. Metabolic profiling may offer the opportunity to understand the molecular mechanism of carcinogenesis and help to identify the potential biomarkers for the early diagnosis of gastric cancer. In this study, we reported the metabolic profiling of tissue samples on a large cohort of human gastric cancer subjects (n = 125) and normal controls (n = 54) based on 1 H nuclear magnetic resonance ( 1 H NMR) together with multivariate statistical analyses (PCA, PLS-DA, OPLS-DA and ROC curve). The OPLS-DA model showed adequate discrimination between cancer tissues and normal controls, and meanwhile, the model excellently discriminated the stage-related of tissue samples (stage I, 30; stage II, 46; stage III, 37; stage IV, 12) and normal controls. A total of 48 endogenous distinguishing metabolites (VIP > 1 and p < 0.05) were identified, 13 of which were changed with the progression of gastric cancer. These modified metabolites revealed disturbance of glycolysis, glutaminolysis, TCA, amino acids and choline metabolism, which were correlated with the occurrence and development of human gastric cancer. The receiver operating characteristic diagnostic AUC of OPLS-DA model between cancer tissues and normal controls was 0.945. And the ROC curves among different stages cancer subjects and normal controls were gradually improved, the corresponding AUC values were 0.952, 0.994, 0.998 and 0.999, demonstrating the robust diagnostic power of this metabolic profiling approach. As far as we know, the present study firstly identified the differential metabolites in various stages of gastric cancer tissues. And the AUC values were relatively high. So these results suggest that the metabolic profiling of gastric cancer tissues has great potential in detecting this disease and helping

Integrative genome-wide gene expression profiling of clear cell renal cell carcinoma in Czech Republic and in the United States.

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Magdalena B Wozniak

Full Text Available Gene expression microarray and next generation sequencing efforts on conventional, clear cell renal cell carcinoma (ccRCC have been mostly performed in North American and Western European populations, while the highest incidence rates are found in Central/Eastern Europe. We conducted whole-genome expression profiling on 101 pairs of ccRCC tumours and adjacent non-tumour renal tissue from Czech patients recruited within the "K2 Study", using the Illumina HumanHT-12 v4 Expression BeadChips to explore the molecular variations underlying the biological and clinical heterogeneity of this cancer. Differential expression analysis identified 1650 significant probes (fold change ≥2 and false discovery rate <0.05 mapping to 630 up- and 720 down-regulated unique genes. We performed similar statistical analysis on the RNA sequencing data of 65 ccRCC cases from the Cancer Genome Atlas (TCGA project and identified 60% (402 of the downregulated and 74% (469 of the upregulated genes found in the K2 series. The biological characterization of the significantly deregulated genes demonstrated involvement of downregulated genes in metabolic and catabolic processes, excretion, oxidation reduction, ion transport and response to chemical stimulus, while simultaneously upregulated genes were associated with immune and inflammatory responses, response to hypoxia, stress, wounding, vasculature development and cell activation. Furthermore, genome-wide DNA methylation analysis of 317 TCGA ccRCC/adjacent non-tumour renal tissue pairs indicated that deregulation of approximately 7% of genes could be explained by epigenetic changes. Finally, survival analysis conducted on 89 K2 and 464 TCGA cases identified 8 genes associated with differential prognostic outcomes. In conclusion, a large proportion of ccRCC molecular characteristics were common to the two populations and several may have clinical implications when validated further through large clinical cohorts.

Differential DNA methylation profiles in gynecological cancers and correlation with clinico-pathological data

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Tsang Percy CK

2006-08-01

Full Text Available Abstract Background Epigenetic gene silencing is one of the major causes of carcinogenesis. Its widespread occurrence in cancer genome could inactivate many cellular pathways including DNA repair, cell cycle control, apoptosis, cell adherence, and detoxification. The abnormal promoter methylation might be a potential molecular marker for cancer management. Methods For rapid identification of potential targets for aberrant methylation in gynecological cancers, methylation status of the CpG islands of 34 genes was determined using pooled DNA approach and methylation-specific PCR. Pooled DNA mixture from each cancer type (50 cervical cancers, 50 endometrial cancers and 50 ovarian cancers was made to form three test samples. The corresponding normal DNA from the patients of each cancer type was also pooled to form the other three control samples. Methylated alleles detected in tumors, but not in normal controls, were indicative of aberrant methylation in tumors. Having identified potential markers, frequencies of methylation were further analyzed in individual samples. Markers identified are used to correlate with clinico-pathological data of tumors using χ2 or Fisher's exact test. Results APC and p16 were hypermethylated across the three cancers. MINT31 and PTEN were hypermethylated in cervical and ovarian cancers. Specific methylation was found in cervical cancer (including CDH1, DAPK, MGMT and MINT2, endometrial cancer (CASP8, CDH13, hMLH1 and p73, and ovarian cancer (BRCA1, p14, p15, RIZ1 and TMS1. The frequencies of occurrence of hypermethylation in 4 candidate genes in individual samples of each cancer type (DAPK, MGMT, p16 and PTEN in 127 cervical cancers; APC, CDH13, hMLH1 and p16 in 60 endometrial cancers; and BRCA1, p14, p16 and PTEN in 49 ovarian cancers were examined for further confirmation. Incidence varied among different genes and in different cancer types ranging from the lowest 8.2% (PTEN in ovarian cancer to the highest 56

Differential DNA methylation profiles in gynecological cancers and correlation with clinico-pathological data

International Nuclear Information System (INIS)

Yang, Hui-Juan; Liu, Vincent WS; Wang, Yue; Tsang, Percy CK; Ngan, Hextan YS

2006-01-01

Epigenetic gene silencing is one of the major causes of carcinogenesis. Its widespread occurrence in cancer genome could inactivate many cellular pathways including DNA repair, cell cycle control, apoptosis, cell adherence, and detoxification. The abnormal promoter methylation might be a potential molecular marker for cancer management. For rapid identification of potential targets for aberrant methylation in gynecological cancers, methylation status of the CpG islands of 34 genes was determined using pooled DNA approach and methylation-specific PCR. Pooled DNA mixture from each cancer type (50 cervical cancers, 50 endometrial cancers and 50 ovarian cancers) was made to form three test samples. The corresponding normal DNA from the patients of each cancer type was also pooled to form the other three control samples. Methylated alleles detected in tumors, but not in normal controls, were indicative of aberrant methylation in tumors. Having identified potential markers, frequencies of methylation were further analyzed in individual samples. Markers identified are used to correlate with clinico-pathological data of tumors using χ 2 or Fisher's exact test. APC and p16 were hypermethylated across the three cancers. MINT31 and PTEN were hypermethylated in cervical and ovarian cancers. Specific methylation was found in cervical cancer (including CDH1, DAPK, MGMT and MINT2), endometrial cancer (CASP8, CDH13, hMLH1 and p73), and ovarian cancer (BRCA1, p14, p15, RIZ1 and TMS1). The frequencies of occurrence of hypermethylation in 4 candidate genes in individual samples of each cancer type (DAPK, MGMT, p16 and PTEN in 127 cervical cancers; APC, CDH13, hMLH1 and p16 in 60 endometrial cancers; and BRCA1, p14, p16 and PTEN in 49 ovarian cancers) were examined for further confirmation. Incidence varied among different genes and in different cancer types ranging from the lowest 8.2% (PTEN in ovarian cancer) to the highest 56.7% (DAPK in cervical cancer). Aberrant methylation

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...

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.

Whole genomes redefine the mutational landscape of pancreatic cancer.

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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

Exploring the Mechanisms of Gastrointestinal Cancer Development Using Deep Sequencing Analysis

International Nuclear Information System (INIS)

Matsumoto, Tomonori; Shimizu, Takahiro; Takai, Atsushi; Marusawa, Hiroyuki

2015-01-01

Next-generation sequencing (NGS) technologies have revolutionized cancer genomics due to their high throughput sequencing capacity. Reports of the gene mutation profiles of various cancers by many researchers, including international cancer genome research consortia, have increased over recent years. In addition to detecting somatic mutations in tumor cells, NGS technologies enable us to approach the subject of carcinogenic mechanisms from new perspectives. Deep sequencing, a method of optimizing the high throughput capacity of NGS technologies, allows for the detection of genetic aberrations in small subsets of premalignant and/or tumor cells in noncancerous chronically inflamed tissues. Genome-wide NGS data also make it possible to clarify the mutational signatures of each cancer tissue by identifying the precise pattern of nucleotide alterations in the cancer genome, providing new information regarding the mechanisms of tumorigenesis. In this review, we highlight these new methods taking advantage of NGS technologies, and discuss our current understanding of carcinogenic mechanisms elucidated from such approaches

Exploring the Mechanisms of Gastrointestinal Cancer Development Using Deep Sequencing Analysis

Energy Technology Data Exchange (ETDEWEB)

Matsumoto, Tomonori; Shimizu, Takahiro; Takai, Atsushi; Marusawa, Hiroyuki, E-mail: maru@kuhp.kyoto-u.ac.jp [Department of Gastroenterology and Hepatology, Graduate School of Medicine, Kyoto University, 54 Shogoin-Kawahara-cho, Sakyo-ku, Kyoto 606-8507 (Japan)

2015-06-15

Next-generation sequencing (NGS) technologies have revolutionized cancer genomics due to their high throughput sequencing capacity. Reports of the gene mutation profiles of various cancers by many researchers, including international cancer genome research consortia, have increased over recent years. In addition to detecting somatic mutations in tumor cells, NGS technologies enable us to approach the subject of carcinogenic mechanisms from new perspectives. Deep sequencing, a method of optimizing the high throughput capacity of NGS technologies, allows for the detection of genetic aberrations in small subsets of premalignant and/or tumor cells in noncancerous chronically inflamed tissues. Genome-wide NGS data also make it possible to clarify the mutational signatures of each cancer tissue by identifying the precise pattern of nucleotide alterations in the cancer genome, providing new information regarding the mechanisms of tumorigenesis. In this review, we highlight these new methods taking advantage of NGS technologies, and discuss our current understanding of carcinogenic mechanisms elucidated from such approaches.

Pathway index models for construction of patient-specific risk profiles.

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Eng, Kevin H; Wang, Sijian; Bradley, William H; Rader, Janet S; Kendziorski, Christina

2013-04-30

Statistical methods for variable selection, prediction, and classification have proven extremely useful in moving personalized genomics medicine forward, in particular, leading to a number of genomic-based assays now in clinical use for predicting cancer recurrence. Although invaluable in individual cases, the information provided by these assays is limited. Most often, a patient is classified into one of very few groups (e.g., recur or not), limiting the potential for truly personalized treatment. Furthermore, although these assays provide information on which individuals are at most risk (e.g., those for which recurrence is predicted), they provide no information on the aberrant biological pathways that give rise to the increased risk. We have developed an approach to address these limitations. The approach models a time-to-event outcome as a function of known biological pathways, identifies important genomic aberrations, and provides pathway-based patient-specific assessments of risk. As we demonstrate in a study of ovarian cancer from The Cancer Genome Atlas project, the patient-specific risk profiles are powerful and efficient characterizations useful in addressing a number of questions related to identifying informative patient subtypes and predicting survival. Copyright © 2012 John Wiley & Sons, Ltd.

Transcription Restores DNA Repair to Heterochromatin, Determining Regional Mutation Rates in Cancer Genomes

Directory of Open Access Journals (Sweden)

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.

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....

Profile of lung cancer in kuwait.

Science.gov (United States)

El-Basmy, Amani

2013-01-01

Lung cancer is the most frequent cancer in males and the fourth most frequent site in females, worldwide. This study is the first to explore the profile of lung cancer in Kuwait. Cases of primary lung cancer (Kuwaiti) in Kuwait cancer Registry (KCR) were grouped in 4 periods (10 years each) from 1970-2009. Epidemiological measures; age standardized incidence rate (ASIR) with 95% confidence intervals (CI), Standardized rate ratio (SRR) and Cumulative risk and Forecasting to year 2020-2029 used for analysis. Between years, 2000-2009 lung cancer ranked the 4th and the 9th most frequent cancer in males and females respectively. M:F ratio 1:3. Mean age at diagnosis (95%CI) was 65.2 (63.9-66.4) years. The estimated risk of developing lung cancer before the age of 75 years in males is 1.8% (1/56), and 0.6 (1/167) in females. The ASIR for male cases was 11.7, 17.1, 17.0, 14.0 cases/100,000 population in the seventies, eighties, nineties and in 2000-2009 respectively. Female ASIR was 2.3, 8.4, 5.1, 4.4 cases/100,000 population in the same duration. Lung cancer is the leading cause cancer death in males 168 (14.2%) and the fifth cause of death due to cancer in females accounting for 6.1% of all cancer deaths. The ASMR (95%CI) was 8.1 (6.6-10.0) deaths/100,000 population and 2.8 (1.3-4.3) deaths/100,000 population in males and females respectively. The estimated Mortality to incidence Ratio was 0.6. The incidence of lung cancer between years 2000-2009 is not different from that reported in the seventies. KCR is expecting the number of lung cancer cases to increase.

Molecular profiling of ADAM12 in human bladder cancer

DEFF Research Database (Denmark)

Albrechtsen, Reidar; Dyrskjøt, Lars; Rudkjaer, Lise

2006-01-01

PURPOSE: We have previously found ADAM12, a disintegrin and metalloprotease, to be an interesting biomarker for breast cancer. The purpose of this study was to determine the gene and protein expression profiles of ADAM12 in different grades and stages of bladder cancer. EXPERIMENTAL DESIGN: ADAM12...... gene expression was evaluated in tumors from 96 patients with bladder cancer using a customized Affymetrix GeneChip. Gene expression in bladder cancer was validated using reverse transcription-PCR, quantitative PCR, and in situ hybridization. Protein expression was evaluated by immunohistochemical...

“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.

Finding cancer driver mutations in the era of big data research.

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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.

NetNorM: Capturing cancer-relevant information in somatic exome mutation data with gene networks for cancer stratification and prognosis.

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Le Morvan, Marine; Zinovyev, Andrei; Vert, Jean-Philippe

2017-06-01

Genome-wide somatic mutation profiles of tumours can now be assessed efficiently and promise to move precision medicine forward. Statistical analysis of mutation profiles is however challenging due to the low frequency of most mutations, the varying mutation rates across tumours, and the presence of a majority of passenger events that hide the contribution of driver events. Here we propose a method, NetNorM, to represent whole-exome somatic mutation data in a form that enhances cancer-relevant information using a gene network as background knowledge. We evaluate its relevance for two tasks: survival prediction and unsupervised patient stratification. Using data from 8 cancer types from The Cancer Genome Atlas (TCGA), we show that it improves over the raw binary mutation data and network diffusion for these two tasks. In doing so, we also provide a thorough assessment of somatic mutations prognostic power which has been overlooked by previous studies because of the sparse and binary nature of mutations.

Prognostic Gene Expression Profiles in Breast Cancer

DEFF Research Database (Denmark)

Sørensen, Kristina Pilekær

Each year approximately 4,800 Danish women are diagnosed with breast cancer. Several clinical and pathological factors are used as prognostic and predictive markers to categorize the patients into groups of high or low risk. Around 90% of all patients are allocated to the high risk group...... clinical courses, and they may be useful as novel prognostic biomarkers in breast cancer. The aim of the present project was to predict the development of metastasis in lymph node negative breast cancer patients by RNA profiling. We collected and analyzed 82 primary breast tumors from patients who...... and the time of event. Previous findings have shown that high expression of the lncRNA HOTAIR is correlated with poor survival in breast cancer. We validated this finding by demonstrating that high HOTAIR expression in our primary tumors was significantly associated with worse prognosis independent...

Genome profiling of sterol synthesis shows convergent evolution in parasites and guides chemotherapeutic attack.

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Fügi, Matthias A; Gunasekera, Kapila; Ochsenreiter, Torsten; Guan, Xueli; Wenk, Markus R; Mäser, Pascal

2014-05-01

Sterols are an essential class of lipids in eukaryotes, where they serve as structural components of membranes and play important roles as signaling molecules. Sterols are also of high pharmacological significance: cholesterol-lowering drugs are blockbusters in human health, and inhibitors of ergosterol biosynthesis are widely used as antifungals. Inhibitors of ergosterol synthesis are also being developed for Chagas's disease, caused by Trypanosoma cruzi. Here we develop an in silico pipeline to globally evaluate sterol metabolism and perform comparative genomics. We generate a library of hidden Markov model-based profiles for 42 sterol biosynthetic enzymes, which allows expressing the genomic makeup of a given species as a numerical vector. Hierarchical clustering of these vectors functionally groups eukaryote proteomes and reveals convergent evolution, in particular metabolic reduction in obligate endoparasites. We experimentally explore sterol metabolism by testing a set of sterol biosynthesis inhibitors against trypanosomatids, Plasmodium falciparum, Giardia, and mammalian cells, and by quantifying the expression levels of sterol biosynthetic genes during the different life stages of T. cruzi and Trypanosoma brucei. The phenotypic data correlate with genomic makeup for simvastatin, which showed activity against trypanosomatids. Other findings, such as the activity of terbinafine against Giardia, are not in agreement with the genotypic profile.

Potential Impact on Clinical Decision Making via a Genome-Wide Expression Profiling: A Case Report

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Hyun Kim

2016-11-01

Full Text Available Management of men with prostate cancer is fraught with uncertainty as physicians and patients balance efficacy with potential toxicity and diminished quality of life. Utilization of genomics as a prognostic biomarker has improved the informed decision-making process by enabling more rationale treatment choices. Recently investigations have begun to determine whether genomic information from tumor transcriptome data can be used to impact clinical decision-making beyond prognosis. Here we discuss the potential of genomics to alter management of a patient who presented with high-risk prostate adenocarcinoma. We suggest that this information help selecting patients for advanced imaging, chemotherapies, or clinical trial.

Whole-genome gene expression profiling of formalin-fixed, paraffin-embedded tissue samples.

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Craig April

2009-12-01

Full Text Available We have developed a gene expression assay (Whole-Genome DASL, capable of generating whole-genome gene expression profiles from degraded samples such as formalin-fixed, paraffin-embedded (FFPE specimens.We demonstrated a similar level of sensitivity in gene detection between matched fresh-frozen (FF and FFPE samples, with the number and overlap of probes detected in the FFPE samples being approximately 88% and 95% of that in the corresponding FF samples, respectively; 74% of the differentially expressed probes overlapped between the FF and FFPE pairs. The WG-DASL assay is also able to detect 1.3-1.5 and 1.5-2 -fold changes in intact and FFPE samples, respectively. The dynamic range for the assay is approximately 3 logs. Comparing the WG-DASL assay with an in vitro transcription-based labeling method yielded fold-change correlations of R(2 approximately 0.83, while fold-change comparisons with quantitative RT-PCR assays yielded R(2 approximately 0.86 and R(2 approximately 0.55 for intact and FFPE samples, respectively. Additionally, the WG-DASL assay yielded high self-correlations (R(2>0.98 with low intact RNA inputs ranging from 1 ng to 100 ng; reproducible expression profiles were also obtained with 250 pg total RNA (R(2 approximately 0.92, with approximately 71% of the probes detected in 100 ng total RNA also detected at the 250 pg level. When FFPE samples were assayed, 1 ng total RNA yielded self-correlations of R(2 approximately 0.80, while still maintaining a correlation of R(2 approximately 0.75 with standard FFPE inputs (200 ng.Taken together, these results show that WG-DASL assay provides a reliable platform for genome-wide expression profiling in archived materials. It also possesses utility within clinical settings where only limited quantities of samples may be available (e.g. microdissected material or when minimally invasive procedures are performed (e.g. biopsied specimens.

A transcriptome anatomy of human colorectal cancers

International Nuclear Information System (INIS)

Lü, Bingjian; Xu, Jing; Lai, Maode; Zhang, Hao; Chen, Jian

2006-01-01

Accumulating databases in human genome research have enabled integrated genome-wide study on complicated diseases such as cancers. A practical approach is to mine a global transcriptome profile of disease from public database. New concepts of these diseases might emerge by landscaping this profile. In this study, we clustered human colorectal normal mucosa (N), inflammatory bowel disease (IBD), adenoma (A) and cancer (T) related expression sequence tags (EST) into UniGenes via an in-house GetUni software package and analyzed the transcriptome overview of these libraries by GOTree Machine (GOTM). Additionally, we downloaded UniGene based cDNA libraries of colon and analyzed them by Xprofiler to cross validate the efficiency of GetUni. Semi-quantitative RT-PCR was used to validate the expression of β-catenin and. 7 novel genes in colorectal cancers. The efficiency of GetUni was successfully validated by Xprofiler and RT-PCR. Genes in library N, IBD and A were all found in library T. A total of 14,879 genes were identified with 2,355 of them having at least 2 transcripts. Differences in gene enrichment among these libraries were statistically significant in 50 signal transduction pathways and Pfam protein domains by GOTM analysis P < 0.01 Hypergeometric Test). Genes in two metabolic pathways, ribosome and glycolysis, were more enriched in the expression profiles of A and IBD than in N and T. Seven transmembrane receptor superfamily genes were typically abundant in cancers. Colorectal cancers are genetically heterogeneous. Transcription variants are common in them. Aberrations of ribosome and glycolysis pathway might be early indicators of precursor lesions in colon cancers. The electronic gene expression profile could be used to highlight the integral molecular events in colorectal cancers

Gene expression profile and genomic alterations in colonic tumours induced by 1,2-dimethylhydrazine (DMH) in rats

International Nuclear Information System (INIS)

Femia, Angelo Pietro; Luceri, Cristina; Toti, Simona; Giannini, Augusto; Dolara, Piero; Caderni, Giovanna

2010-01-01

Azoxymethane (AOM) or 1,2-dimethylhydrazine (DMH)-induced colon carcinogenesis in rats shares many phenotypical similarities with human sporadic colon cancer and is a reliable model for identifying chemopreventive agents. Genetic mutations relevant to human colon cancer have been described in this model, but comprehensive gene expression and genomic analysis have not been reported so far. Therefore, we applied genome-wide technologies to study variations in gene expression and genomic alterations in DMH-induced colon cancer in F344 rats. For gene expression analysis, 9 tumours (TUM) and their paired normal mucosa (NM) were hybridized on 4 × 44K Whole rat arrays (Agilent) and selected genes were validated by semi-quantitative RT-PCR. Functional analysis on microarray data was performed by GenMAPP/MappFinder analysis. Array-comparative genomic hybridization (a-CGH) was performed on 10 paired TUM-NM samples hybridized on Rat genome arrays 2 × 105K (Agilent) and the results were analyzed by CGH Analytics (Agilent). Microarray gene expression analysis showed that Defcr4, Igfbp5, Mmp7, Nos2, S100A8 and S100A9 were among the most up-regulated genes in tumours (Fold Change (FC) compared with NM: 183, 48, 39, 38, 36 and 32, respectively), while Slc26a3, Mptx, Retlna and Muc2 were strongly down-regulated (FC: -500; -376, -167, -79, respectively). Functional analysis showed that pathways controlling cell cycle, protein synthesis, matrix metalloproteinases, TNFα/NFkB, and inflammatory responses were up-regulated in tumours, while Krebs cycle, the electron transport chain, and fatty acid beta oxidation were down-regulated. a-CGH analysis showed that four TUM out of ten had one or two chromosomal aberrations. Importantly, one sample showed a deletion on chromosome 18 including Apc. The results showed complex gene expression alterations in adenocarcinomas encompassing many altered pathways. While a-CGH analysis showed a low degree of genomic imbalance, it is interesting to

Deciphering Phosphotyrosine-Dependent Signaling Networks in Cancer by SH2 Profiling

Science.gov (United States)

Machida, Kazuya; Khenkhar, Malik

2012-01-01

It has been a decade since the introduction of SH2 profiling, a modular domain-based molecular diagnostics tool. This review covers the original concept of SH2 profiling, different analytical platforms, and their applications, from the detailed analysis of single proteins to broad screening in translational research. Illustrated by practical examples, we discuss the uniqueness and advantages of the approach as well as its limitations and challenges. We provide guidance for basic researchers and oncologists who may consider SH2 profiling in their respective cancer research, especially for those focusing on tyrosine phosphoproteomics. SH2 profiling can serve as an alternative phosphoproteomics tool to dissect aberrant tyrosine kinase pathways responsible for individual malignancies, with the goal of facilitating personalized diagnostics for the treatment of cancer. PMID:23226573

FISH Oracle 2: a web server for integrative visualization of genomic data in cancer research.

Science.gov (United States)

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.

¹H NMR-based metabolic profiling of human rectal cancer tissue

Science.gov (United States)

2013-01-01

Background Rectal cancer is one of the most prevalent tumor types. Understanding the metabolic profile of rectal cancer is important for developing therapeutic approaches and molecular diagnosis. Methods Here, we report a metabonomics profiling of tissue samples on a large cohort of human rectal cancer subjects (n = 127) and normal controls (n = 43) using 1H nuclear magnetic resonance (1H NMR) based metabonomics assay, which is a highly sensitive and non-destructive method for the biomarker identification in biological systems. Principal component analysis (PCA), partial least squares discriminant analysis (PLS-DA) and orthogonal projection to latent structure with discriminant analysis (OPLS-DA) were applied to analyze the 1H-NMR profiling data to identify the distinguishing metabolites of rectal cancer. Results Excellent separation was obtained and distinguishing metabolites were observed among the different stages of rectal cancer tissues (stage I = 35; stage II = 37; stage III = 37 and stage IV = 18) and normal controls. A total of 38 differential metabolites were identified, 16 of which were closely correlated with the stage of rectal cancer. The up-regulation of 10 metabolites, including lactate, threonine, acetate, glutathione, uracil, succinate, serine, formate, lysine and tyrosine, were detected in the cancer tissues. On the other hand, 6 metabolites, including myo-inositol, taurine, phosphocreatine, creatine, betaine and dimethylglycine were decreased in cancer tissues. These modified metabolites revealed disturbance of energy, amino acids, ketone body and choline metabolism, which may be correlated with the progression of human rectal cancer. Conclusion Our findings firstly identify the distinguishing metabolites in different stages of rectal cancer tissues, indicating possibility of the attribution of metabolites disturbance to the progression of rectal cancer. The altered metabolites may be as potential biomarkers, which would

Versatile Gene-Specific Sequence Tags for Arabidopsis Functional Genomics: Transcript Profiling and Reverse Genetics Applications

Science.gov (United States)

Hilson, Pierre; Allemeersch, Joke; Altmann, Thomas; Aubourg, Sébastien; Avon, Alexandra; Beynon, Jim; Bhalerao, Rishikesh P.; Bitton, Frédérique; Caboche, Michel; Cannoot, Bernard; Chardakov, Vasil; Cognet-Holliger, Cécile; Colot, Vincent; Crowe, Mark; Darimont, Caroline; Durinck, Steffen; Eickhoff, Holger; de Longevialle, Andéol Falcon; Farmer, Edward E.; Grant, Murray; Kuiper, Martin T.R.; Lehrach, Hans; Léon, Céline; Leyva, Antonio; Lundeberg, Joakim; Lurin, Claire; Moreau, Yves; Nietfeld, Wilfried; Paz-Ares, Javier; Reymond, Philippe; Rouzé, Pierre; Sandberg, Goran; Segura, Maria Dolores; Serizet, Carine; Tabrett, Alexandra; Taconnat, Ludivine; Thareau, Vincent; Van Hummelen, Paul; Vercruysse, Steven; Vuylsteke, Marnik; Weingartner, Magdalena; Weisbeek, Peter J.; Wirta, Valtteri; Wittink, Floyd R.A.; Zabeau, Marc; Small, Ian

2004-01-01

Microarray transcript profiling and RNA interference are two new technologies crucial for large-scale gene function studies in multicellular eukaryotes. Both rely on sequence-specific hybridization between complementary nucleic acid strands, inciting us to create a collection of gene-specific sequence tags (GSTs) representing at least 21,500 Arabidopsis genes and which are compatible with both approaches. The GSTs were carefully selected to ensure that each of them shared no significant similarity with any other region in the Arabidopsis genome. They were synthesized by PCR amplification from genomic DNA. Spotted microarrays fabricated from the GSTs show good dynamic range, specificity, and sensitivity in transcript profiling experiments. The GSTs have also been transferred to bacterial plasmid vectors via recombinational cloning protocols. These cloned GSTs constitute the ideal starting point for a variety of functional approaches, including reverse genetics. We have subcloned GSTs on a large scale into vectors designed for gene silencing in plant cells. We show that in planta expression of GST hairpin RNA results in the expected phenotypes in silenced Arabidopsis lines. These versatile GST resources provide novel and powerful tools for functional genomics. PMID:15489341

CGDM: collaborative genomic data model for molecular profiling data using NoSQL.

Science.gov (United States)

Wang, Shicai; Mares, Mihaela A; Guo, Yi-Ke

2016-12-01

High-throughput molecular profiling has greatly improved patient stratification and mechanistic understanding of diseases. With the increasing amount of data used in translational medicine studies in recent years, there is a need to improve the performance of data warehouses in terms of data retrieval and statistical processing. Both relational and Key Value models have been used for managing molecular profiling data. Key Value models such as SeqWare have been shown to be particularly advantageous in terms of query processing speed for large datasets. However, more improvement can be achieved, particularly through better indexing techniques of the Key Value models, taking advantage of the types of queries which are specific for the high-throughput molecular profiling data. In this article, we introduce a Collaborative Genomic Data Model (CGDM), aimed at significantly increasing the query processing speed for the main classes of queries on genomic databases. CGDM creates three Collaborative Global Clustering Index Tables (CGCITs) to solve the velocity and variety issues at the cost of limited extra volume. Several benchmarking experiments were carried out, comparing CGDM implemented on HBase to the traditional SQL data model (TDM) implemented on both HBase and MySQL Cluster, using large publicly available molecular profiling datasets taken from NCBI and HapMap. In the microarray case, CGDM on HBase performed up to 246 times faster than TDM on HBase and 7 times faster than TDM on MySQL Cluster. In single nucleotide polymorphism case, CGDM on HBase outperformed TDM on HBase by up to 351 times and TDM on MySQL Cluster by up to 9 times. The CGDM source code is available at https://github.com/evanswang/CGDM. y.guo@imperial.ac.uk. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Functionally Assessing Candidate Drivers Advances Precision Cancer Medicine.

Science.gov (United States)

Scott, Kenneth L; Powers, Scott

2016-08-08

The complexity of genomic alterations in cancer has made it difficult to identify oncogenic drivers for the development of targeted therapies. The study by Berger et al. in this issue of Cancer Cell demonstrates that high-throughput functional profiling can uncover impactful mutations and oncogenic driver alleles. Copyright © 2016 Elsevier Inc. All rights reserved.

Distinct choline metabolic profiles are associated with differences in gene expression for basal-like and luminal-like breast cancer xenograft models

International Nuclear Information System (INIS)

Moestue, Siver A; Borgan, Eldrid; Huuse, Else M; Lindholm, Evita M; Sitter, Beathe; Børresen-Dale, Anne-Lise; Engebraaten, Olav; Mælandsmo, Gunhild M; Gribbestad, Ingrid S

2010-01-01

Increased concentrations of choline-containing compounds are frequently observed in breast carcinomas, and may serve as biomarkers for both diagnostic and treatment monitoring purposes. However, underlying mechanisms for the abnormal choline metabolism are poorly understood. The concentrations of choline-derived metabolites were determined in xenografted primary human breast carcinomas, representing basal-like and luminal-like subtypes. Quantification of metabolites in fresh frozen tissue was performed using high-resolution magic angle spinning magnetic resonance spectroscopy (HR MAS MRS). The expression of genes involved in phosphatidylcholine (PtdCho) metabolism was retrieved from whole genome expression microarray analyses. The metabolite profiles from xenografts were compared with profiles from human breast cancer, sampled from patients with estrogen/progesterone receptor positive (ER+/PgR+) or triple negative (ER-/PgR-/HER2-) breast cancer. In basal-like xenografts, glycerophosphocholine (GPC) concentrations were higher than phosphocholine (PCho) concentrations, whereas this pattern was reversed in luminal-like xenografts. These differences may be explained by lower choline kinase (CHKA, CHKB) expression as well as higher PtdCho degradation mediated by higher expression of phospholipase A2 group 4A (PLA2G4A) and phospholipase B1 (PLB1) in the basal-like model. The glycine concentration was higher in the basal-like model. Although glycine could be derived from energy metabolism pathways, the gene expression data suggested a metabolic shift from PtdCho synthesis to glycine formation in basal-like xenografts. In agreement with results from the xenograft models, tissue samples from triple negative breast carcinomas had higher GPC/PCho ratio than samples from ER+/PgR+ carcinomas, suggesting that the choline metabolism in the experimental models is representative for luminal-like and basal-like human breast cancer. The differences in choline metabolite

Molecular profiling of ADAM12 in human bladder cancer

DEFF Research Database (Denmark)

Albrechtsen, Reidar; Dyrskjøt, Lars; Rudkjaer, Lise

2006-01-01

PURPOSE: We have previously found ADAM12, a disintegrin and metalloprotease, to be an interesting biomarker for breast cancer. The purpose of this study was to determine the gene and protein expression profiles of ADAM12 in different grades and stages of bladder cancer. EXPERIMENTAL DESIGN: ADAM12...... gene expression was evaluated in tumors from 96 patients with bladder cancer using a customized Affymetrix GeneChip. Gene expression in bladder cancer was validated using reverse transcription-PCR, quantitative PCR, and in situ hybridization. Protein expression was evaluated by immunohistochemical...... staining on tissue arrays of bladder cancers. The presence and relative amount of ADAM12 in the urine of cancer patients were determined by Western blotting and densitometric measurements, respectively. RESULTS: ADAM12 mRNA expression was significantly up-regulated in bladder cancer, as determined...

Epigenomics of Total Acute Sleep Deprivation in Relation to Genome-Wide DNA Methylation Profiles and RNA Expression.

Science.gov (United States)

Nilsson, Emil K; Boström, Adrian E; Mwinyi, Jessica; Schiöth, Helgi B

2016-06-01

Despite an established link between sleep deprivation and epigenetic processes in humans, it remains unclear to what extent sleep deprivation modulates DNA methylation. We performed a within-subject randomized blinded study with 16 healthy subjects to examine the effect of one night of total sleep deprivation (TSD) on the genome-wide methylation profile in blood compared with that in normal sleep. Genome-wide differences in methylation between both conditions were assessed by applying a paired regression model that corrected for monocyte subpopulations. In addition, the correlations between the methylation of genes detected to be modulated by TSD and gene expression were examined in a separate, publicly available cohort of 10 healthy male donors (E-GEOD-49065). Sleep deprivation significantly affected the DNA methylation profile both independently and in dependency of shifts in monocyte composition. Our study detected differential methylation of 269 probes. Notably, one CpG site was located 69 bp upstream of ING5, which has been shown to be differentially expressed after sleep deprivation. Gene set enrichment analysis detected the Notch and Wnt signaling pathways to be enriched among the differentially methylated genes. These results provide evidence that total acute sleep deprivation alters the methylation profile in healthy human subjects. This is, to our knowledge, the first study that systematically investigated the impact of total acute sleep deprivation on genome-wide DNA methylation profiles in blood and related the epigenomic findings to the expression data.

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.

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

Use of deep whole-genome sequencing data to identify structure risk variants in breast cancer susceptibility genes.

Science.gov (United States)

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.

BarleyBase—an expression profiling database for plant genomics

Science.gov (United States)

Shen, Lishuang; Gong, Jian; Caldo, Rico A.; Nettleton, Dan; Cook, Dianne; Wise, Roger P.; Dickerson, Julie A.

2005-01-01

BarleyBase (BB) (www.barleybase.org) is an online database for plant microarrays with integrated tools for data visualization and statistical analysis. BB houses raw and normalized expression data from the two publicly available Affymetrix genome arrays, Barley1 and Arabidopsis ATH1 with plans to include the new Affymetrix 61K wheat, maize, soybean and rice arrays, as they become available. BB contains a broad set of query and display options at all data levels, ranging from experiments to individual hybridizations to probe sets down to individual probes. Users can perform cross-experiment queries on probe sets based on observed expression profiles and/or based on known biological information. Probe set queries are integrated with visualization and analysis tools such as the R statistical toolbox, data filters and a large variety of plot types. Controlled vocabularies for gene and plant ontologies, as well as interconnecting links to physical or genetic map and other genomic data in PlantGDB, Gramene and GrainGenes, allow users to perform EST alignments and gene function prediction using Barley1 exemplar sequences, thus, enhancing cross-species comparison. PMID:15608273

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.

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.

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

A systems approach to predict oncometabolites via context-specific genome-scale metabolic networks.

Directory of Open Access Journals (Sweden)

Hojung Nam

2014-09-01

Full Text Available Altered metabolism in cancer cells has been viewed as a passive response required for a malignant transformation. However, this view has changed through the recently described metabolic oncogenic factors: mutated isocitrate dehydrogenases (IDH, succinate dehydrogenase (SDH, and fumarate hydratase (FH that produce oncometabolites that competitively inhibit epigenetic regulation. In this study, we demonstrate in silico predictions of oncometabolites that have the potential to dysregulate epigenetic controls in nine types of cancer by incorporating massive scale genetic mutation information (collected from more than 1,700 cancer genomes, expression profiling data, and deploying Recon 2 to reconstruct context-specific genome-scale metabolic models. Our analysis predicted 15 compounds and 24 substructures of potential oncometabolites that could result from the loss-of-function and gain-of-function mutations of metabolic enzymes, respectively. These results suggest a substantial potential for discovering unidentified oncometabolites in various forms of 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.

Effects of high hydrostatic pressure on genomic expression profiling of porcine parthenogenetic activated and cloned embryos