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Sample records for cancer models genomic

  1. A Gene Gravity Model for the Evolution of Cancer Genomes: A Study of 3,000 Cancer Genomes across 9 Cancer Types.

    Directory of Open Access Journals (Sweden)

    Feixiong Cheng

    2015-09-01

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

  2. Cancer models, genomic instability and somatic cellular Darwinian evolution

    Directory of Open Access Journals (Sweden)

    Little Mark P

    2010-04-01

    Full Text Available Abstract The biology of cancer is critically reviewed and evidence adduced that its development can be modelled as a somatic cellular Darwinian evolutionary process. The evidence for involvement of genomic instability (GI is also reviewed. A variety of quasi-mechanistic models of carcinogenesis are reviewed, all based on this somatic Darwinian evolutionary hypothesis; in particular, the multi-stage model of Armitage and Doll (Br. J. Cancer 1954:8;1-12, the two-mutation model of Moolgavkar, Venzon, and Knudson (MVK (Math. Biosci. 1979:47;55-77, the generalized MVK model of Little (Biometrics 1995:51;1278-1291 and various generalizations of these incorporating effects of GI (Little and Wright Math. Biosci. 2003:183;111-134; Little et al. J. Theoret. Biol. 2008:254;229-238. Reviewers This article was reviewed by RA Gatenby and M Kimmel.

  3. An Integrative Pathway-based Clinical-genomic Model for Cancer Survival Prediction.

    Science.gov (United States)

    Chen, Xi; Wang, Lily; Ishwaran, Hemant

    2010-09-01

    Prediction models that use gene expression levels are now being proposed for personalized treatment of cancer, but building accurate models that are easy to interpret remains a challenge. In this paper, we describe an integrative clinical-genomic approach that combines both genomic pathway and clinical information. First, we summarize information from genes in each pathway using Supervised Principal Components (SPCA) to obtain pathway-based genomic predictors. Next, we build a prediction model based on clinical variables and pathway-based genomic predictors using Random Survival Forests (RSF). Our rationale for this two-stage procedure is that the underlying disease process may be influenced by environmental exposure (measured by clinical variables) and perturbations in different pathways (measured by pathway-based genomic variables), as well as their interactions. Using two cancer microarray datasets, we show that the pathway-based clinical-genomic model outperforms gene-based clinical-genomic models, with improved prediction accuracy and interpretability.

  4. Integrating microarray gene expression object model and clinical document architecture for cancer genomics research.

    Science.gov (United States)

    Park, Yu Rang; Lee, Hye Won; Kim, Ju Han

    2005-01-01

    Systematic integration of genomic-scale expression profiles with clinical information may facilitate cancer genomics research. MAGE-OM (Microarray Gene Expression Object Model) defines standard objects for genomic but not for clinical data. HL7 CDA (Clinical Document Architecture) is a document model for clinical information, describing syntax (generic structure) but not semantics. We designed a document template in XML Schema with additional constraints for CDA to define content semantics, enabling data model-level integration of MAGE-OM and CDA for cancer genomics research. PMID:16779360

  5. 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...

  6. Organoids as Models for Neoplastic Transformation | Office of Cancer Genomics

    Science.gov (United States)

    Cancer models strive to recapitulate the incredible diversity inherent in human tumors. A key challenge in accurate tumor modeling lies in capturing the panoply of homo- and heterotypic cellular interactions within the context of a three-dimensional tissue microenvironment. To address this challenge, researchers have developed organotypic cancer models (organoids) that combine the 3D architecture of in vivo tissues with the experimental facility of 2D cell lines.

  7. Genomic distance entrained clustering and regression modelling highlights interacting genomic regions contributing to proliferation in breast cancer

    Directory of Open Access Journals (Sweden)

    Dexter Tim J

    2010-09-01

    Full Text Available Abstract Background Genomic copy number changes and regional alterations in epigenetic states have been linked to grade in breast cancer. However, the relative contribution of specific alterations to the pathology of different breast cancer subtypes remains unclear. The heterogeneity and interplay of genomic and epigenetic variations means that large datasets and statistical data mining methods are required to uncover recurrent patterns that are likely to be important in cancer progression. Results We employed ridge regression to model the relationship between regional changes in gene expression and proliferation. Regional features were extracted from tumour gene expression data using a novel clustering method, called genomic distance entrained agglomerative (GDEC clustering. Using gene expression data in this way provides a simple means of integrating the phenotypic effects of both copy number aberrations and alterations in chromatin state. We show that regional metagenes derived from GDEC clustering are representative of recurrent regions of epigenetic regulation or copy number aberrations in breast cancer. Furthermore, detected patterns of genomic alterations are conserved across independent oestrogen receptor positive breast cancer datasets. Sequential competitive metagene selection was used to reveal the relative importance of genomic regions in predicting proliferation rate. The predictive model suggested additive interactions between the most informative regions such as 8p22-12 and 8q13-22. Conclusions Data-mining of large-scale microarray gene expression datasets can reveal regional clusters of co-ordinate gene expression, independent of cause. By correlating these clusters with tumour proliferation we have identified a number of genomic regions that act together to promote proliferation in ER+ breast cancer. Identification of such regions should enable prioritisation of genomic regions for combinatorial functional studies to pinpoint

  8. Integrating Microarray Gene Expression Object Model and Clinical Document Architecture for Cancer Genomics Research

    OpenAIRE

    Park, Yu Rang; Lee, Hye Won; Kim, Ju Han

    2005-01-01

    Systematic integration of gene expression profiling with clinical information may facilitate cancer genomics research. MAGE-OM (MicroArray Gene Expression Object Model) defines standard objects for genomic but not for clinical data. HL7 CDA (Clinical Document Architecture) is a document model for clinical information, describing syntax but not semantics. We designed a document template and common data elements in XML Schema with additional constraints for CDA to define conte...

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

    DEFF Research Database (Denmark)

    Ghaffari, Pouyan; Mardinoglu, Adil; Asplund, Anna;

    2015-01-01

    85 antimetabolites that can inhibit growth of, or even kill, any of the cell lines, while at the same time not being toxic for 83 different healthy human cell types. 60 of these antimetabolites were found to inhibit growth in all cell lines. Finally, we experimentally validated one of the predicted...... for inhibition of cell growth may provide leads for the development of efficient cancer treatment strategies.......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...

  10. Center for Cancer Genomics | Office of Cancer Genomics

    Science.gov (United States)

    The Center for Cancer Genomics (CCG) was established to unify the National Cancer Institute's activities in cancer genomics, with the goal of advancing genomics research and translating findings into the clinic to improve the precise diagnosis and treatment of cancers. In addition to promoting genomic sequencing approach

  11. Methods in Mammary Gland Development and Cancer: the second ENDBC meeting - intravital imaging, genomics, modeling and metastasis

    OpenAIRE

    Stingl, John; Matthew J Smalley; Glukhova, Marina A.; Bentires-Alj, Mohamed

    2010-01-01

    The second meeting of the European Network for Breast Development and Cancer (ENBDC) on 'Methods in Mammary Gland Development and Cancer' was held in April 2010 in Weggis, Switzerland. The focus was on genomics and bioinformatics, extracellular matrix and stroma-epithelial cell interactions, intravital imaging, the search for metastasis founder cells and mouse models of breast cancer.

  12. Genomic analysis to define molecular basis of aggressiveness in a mouse model of oral cancer

    OpenAIRE

    Varun Chalivendra; Krishna Latha Kanchi; Onken, Michael D.; Ashley E. Winkler; Elaine Mardis; Ravindra Uppaluri

    2014-01-01

    To investigate the molecular basis underlying aggressive behavior in oral squamous cell carcinoma (OSCC), our laboratory developed a carcinogen-induced mouse oral cancer (MOC) cell line model that encompasses the growth and metastasis spectrum of its human counterpart. We performed next-generation sequencing (NGS) and gene expression microarray profiles to explore the genomic and transcriptional backgrounds of the differential MOC line phenotypes, as well as, the cross-species relevance of th...

  13. Genomic Data Commons | Office of Cancer Genomics

    Science.gov (United States)

    The NCI’s Center for Cancer Genomics launches the Genomic Data Commons (GDC), a unified data sharing platform for the cancer research community. The mission of the GDC is to enable data sharing across the entire cancer research community, to ultimately support precision medicine in oncology.

  14. My Cancer Genome: Evaluating an Educational Model to Introduce Patients and Caregivers to Precision Medicine Information.

    Science.gov (United States)

    Kusnoor, Sheila V; Koonce, Taneya Y; Levy, Mia A; Lovly, Christine M; Naylor, Helen M; Anderson, Ingrid A; Micheel, Christine M; Chen, Sheau-Chiann; Ye, Fei; Giuse, Nunzia B

    2016-01-01

    This study tested an innovative model for creating consumer-level content about precision medicine based on health literacy and learning style principles. "Knowledge pearl" videos, incorporating multiple learning modalities, were created to explain genetic and cancer medicine concepts. Cancer patients and caregivers (n=117) were randomized to view professional-level content directly from the My Cancer Genome (MCG) website (Group A; control), content from MCG with knowledge pearls embedded (Group B), or a consumer translation, targeted at the sixth grade level, with knowledge pearls embedded (Group C). A multivariate analysis showed that Group C, but not Group B, showed greater knowledge gains immediately after viewing the educational material than Group A. Statistically significant group differences in test performance were no longer observed three weeks later. These findings suggest that adherence to health literacy and learning style principles facilitates comprehension of precision medicine concepts and that ongoing review of the educational information is necessary. PMID:27570660

  15. Collaborators | Office of Cancer Genomics

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    The TARGET initiative is jointly managed within the National Cancer Institute (NCI) by the Office of Cancer Genomics (OCG)Opens in a New Tab and the Cancer Therapy Evaluation Program (CTEP)Opens in a New Tab.

  16. Genomic analysis to define molecular basis of aggressiveness in a mouse model of oral cancer

    Directory of Open Access Journals (Sweden)

    Varun Chalivendra

    2015-03-01

    Full Text Available To investigate the molecular basis underlying aggressive behavior in oral squamous cell carcinoma (OSCC, our laboratory developed a carcinogen-induced mouse oral cancer (MOC cell line model that encompasses the growth and metastasis spectrum of its human counterpart. We performed next-generation sequencing (NGS and gene expression microarray profiles to explore the genomic and transcriptional backgrounds of the differential MOC line phenotypes, as well as, the cross-species relevance of the model. Here we describe the comparative analysis of NGS (www.ncbi.nlm.nih.gov/biosample?LinkName=bioproject_biosample_all&from_uid=247825 and expression microarray (www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE50041 data from the MOC lines and corresponding human data, as described in our recent publication [1].

  17. Programs | Office of Cancer Genomics

    Science.gov (United States)

    OCG facilitates cancer genomics research through a series of highly-focused programs. These programs generate and disseminate genomic data for use by the cancer research community. OCG programs also promote advances in technology-based infrastructure and create valuable experimental reagents and tools. OCG programs encourage collaboration by interconnecting with other genomics and cancer projects in order to accelerate translation of findings into the clinic. Below are OCG’s current, completed, and initiated programs:

  18. Genomic Datasets for Cancer Research

    Science.gov (United States)

    A variety of datasets from genome-wide association studies of cancer and other genotype-phenotype studies, including sequencing and molecular diagnostic assays, are available to approved investigators through the Extramural National Cancer Institute Data Access Committee.

  19. Contact | Office of Cancer Genomics

    Science.gov (United States)

    For more information about the Office of Cancer Genomics, please contact: Office of Cancer Genomics National Cancer Institute 31 Center Drive, 10A07 Bethesda, Maryland 20892-2580 Phone: (301) 451-8027 Fax: (301) 480-4368 Email: ocg@mail.nih.gov *Please note that this site will not function properly in Internet Explorer unless you completely turn off the Compatibility View*

  20. Predicting survival within the lung cancer histopathological hierarchy using a multi-scale genomic model of development.

    Directory of Open Access Journals (Sweden)

    Hongye Liu

    2006-07-01

    Full Text Available BACKGROUND: The histopathologic heterogeneity of lung cancer remains a significant confounding factor in its diagnosis and prognosis-spurring numerous recent efforts to find a molecular classification of the disease that has clinical relevance. METHODS AND FINDINGS: Molecular profiles of tumors from 186 patients representing four different lung cancer subtypes (and 17 normal lung tissue samples were compared with a mouse lung development model using principal component analysis in both temporal and genomic domains. An algorithm for the classification of lung cancers using a multi-scale developmental framework was developed. Kaplan-Meier survival analysis was conducted for lung adenocarcinoma patient subgroups identified via their developmental association. We found multi-scale genomic similarities between four human lung cancer subtypes and the developing mouse lung that are prognostically meaningful. Significant association was observed between the localization of human lung cancer cases along the principal mouse lung development trajectory and the corresponding patient survival rate at three distinct levels of classical histopathologic resolution: among different lung cancer subtypes, among patients within the adenocarcinoma subtype, and within the stage I adenocarcinoma subclass. The earlier the genomic association between a human tumor profile and the mouse lung development sequence, the poorer the patient's prognosis. Furthermore, decomposing this principal lung development trajectory identified a gene set that was significantly enriched for pyrimidine metabolism and cell-adhesion functions specific to lung development and oncogenesis. CONCLUSIONS: From a multi-scale disease modeling perspective, the molecular dynamics of murine lung development provide an effective framework that is not only data driven but also informed by the biology of development for elucidating the mechanisms of human lung cancer biology and its clinical outcome.

  1. International network of cancer genome projects

    NARCIS (Netherlands)

    Hudson, Thomas J.; Anderson, Warwick; Aretz, Axel; Barker, Anna D.; Bell, Cindy; Bernabe, Rosa R.; Bhan, M. K.; Calvo, Fabien; Eerola, Iiro; Gerhard, Daniela S.; Guttmacher, Alan; Guyer, Mark; Hemsley, Fiona M.; Jennings, Jennifer L.; Kerr, David; Klatt, Peter; Kolar, Patrik; Kusuda, Jun; Lane, David P.; Laplace, Frank; Lu, Youyong; Nettekoven, Gerd; Ozenberger, Brad; Peterson, Jane; Rao, T. S.; Remacle, Jacques; Schafer, Alan J.; Shibata, Tatsuhiro; Stratton, Michael R.; Vockley, Joseph G.; Watanabe, Koichi; Yang, Huanming; Yuen, Matthew M. F.; Knoppers, M.; Bobrow, Martin; Cambon-Thomsen, Anne; Dressler, Lynn G.; Dyke, Stephanie O. M.; Joly, Yann; Kato, Kazuto; Kennedy, Karen L.; Nicolas, Pilar; Parker, Michael J.; Rial-Sebbag, Emmanuelle; Romeo-Casabona, Carlos M.; Shaw, Kenna M.; Wallace, Susan; Wiesner, Georgia L.; Zeps, Nikolajs; Lichter, Peter; Biankin, Andrew V.; Chabannon, Christian; Chin, Lynda; Clement, Bruno; de Alava, Enrique; Degos, Francoise; Ferguson, Martin L.; Geary, Peter; Hayes, D. Neil; Johns, Amber L.; Nakagawa, Hidewaki; Penny, Robert; Piris, Miguel A.; Sarin, Rajiv; Scarpa, Aldo; Shibata, Tatsuhiro; van de Vijver, Marc; Futreal, P. Andrew; Aburatani, Hiroyuki; Bayes, Monica; Bowtell, David D. L.; Campbell, Peter J.; Estivill, Xavier; Grimmond, Sean M.; Gut, Ivo; Hirst, Martin; Lopez-Otin, Carlos; Majumder, Partha; Marra, Marco; Nakagawa, Hidewaki; Ning, Zemin; Puente, Xose S.; Ruan, Yijun; Shibata, Tatsuhiro; Stratton, Michael R.; Stunnenberg, Hendrik G.; Swerdlow, Harold; Velculescu, Victor E.; Wilson, Richard K.; Xue, Hong H.; Yang, Liu; Spellman, Paul T.; Bader, Gary D.; Boutros, Paul C.; Campbell, Peter J.; Flicek, Paul; Getz, Gad; Guigo, Roderic; Guo, Guangwu; Haussler, David; Heath, Simon; Hubbard, Tim J.; Jiang, Tao; Jones, Steven M.; Li, Qibin; Lopez-Bigas, Nuria; Luo, Ruibang; Pearson, John V.; Puente, Xose S.; Quesada, Victor; Raphael, Benjamin J.; Sander, Chris; Shibata, Tatsuhiro; Speed, Terence P.; Stuart, Joshua M.; Teague, Jon W.; Totoki, Yasushi; Tsunoda, Tatsuhiko; Valencia, Alfonso; Wheeler, David A.; Wu, Honglong; Zhao, Shancen; Zhou, Guangyu; Stein, Lincoln D.; Guigo, Roderic; Hubbard, Tim J.; Joly, Yann; Jones, Steven M.; Lathrop, Mark; Lopez-Bigas, Nuria; Ouellette, B. F. Francis; Spellman, Paul T.; Teague, Jon W.; Thomas, Gilles; Valencia, Alfonso; Yoshida, Teruhiko; Kennedy, Karen L.; Axton, Myles; Dyke, Stephanie O. M.; Futreal, P. Andrew; Gunter, Chris; Guyer, Mark; McPherson, John D.; Miller, Linda J.; Ozenberger, Brad; Kasprzyk, Arek; Zhang, Junjun; Haider, Syed A.; Wang, Jianxin; Yung, Christina K.; Cross, Anthony; Liang, Yong; Gnaneshan, Saravanamuttu; Guberman, Jonathan; Hsu, Jack; Bobrow, Martin; Chalmers, Don R. C.; Hasel, Karl W.; Joly, Yann; Kaan, Terry S. H.; Kennedy, Karen L.; Knoppers, Bartha M.; Lowrance, William W.; Masui, Tohru; Nicolas, Pilar; Rial-Sebbag, Emmanuelle; Rodriguez, Laura Lyman; Vergely, Catherine; Yoshida, Teruhiko; Grimmond, Sean M.; Biankin, Andrew V.; Bowtell, David D. L.; Cloonan, Nicole; Defazio, Anna; Eshleman, James R.; Etemadmoghadam, Dariush; Gardiner, Brooke A.; Kench, James G.; Scarpa, Aldo; Sutherland, Robert L.; Tempero, Margaret A.; Waddell, Nicola J.; Wilson, Peter J.; Gallinger, Steve; Tsao, Ming-Sound; Shaw, Patricia A.; Petersen, Gloria M.; Mukhopadhyay, Debabrata; Chin, Lynda; DePinho, Ronald A.; Thayer, Sarah; Muthuswamy, Lakshmi; Shazand, Kamran; Beck, Timothy; Sam, Michelle; Timms, Lee; Ballin, Vanessa; Lu, Youyong; Ji, Jiafu; Zhang, Xiuqing; Chen, Feng; Hu, Xueda; Zhou, Guangyu; Yang, Qi; Tian, Geng; Zhang, Lianhai; Xing, Xiaofang; Li, Xianghong; Zhu, Zhenggang; Yu, Yingyan; Yu, Jun; Yang, Huanming; Lathrop, Mark; Tost, Joerg; Brennan, Paul; Holcatova, Ivana; Zaridze, David; Brazma, Alvis; Egevad, Lars; Prokhortchouk, Egor; Banks, Rosamonde Elizabeth; Uhlen, Mathias; Cambon-Thomsen, Anne; Viksna, Juris; Ponten, Fredrik; Skryabin, Konstantin; Stratton, Michael R.; Futreal, P. Andrew; Birney, Ewan; Borg, Ake; Borresen-Dale, Anne-Lise; Caldas, Carlos; Foekens, John A.; Martin, Sancha; Reis-Filho, Jorge S.; Richardson, Andrea L.; Sotiriou, Christos; Stunnenberg, Hendrik G.; Thomas, Gilles; van de Vijver, Marc; van't Veer, Laura; Birnbaum, Daniel; Blanche, Helene; Boucher, Pascal; Boyault, Sandrine; Chabannon, Christian; Gut, Ivo; Masson-Jacquemier, Jocelyne D.; Lathrop, Mark; Pauporte, Iris; Pivot, Xavier; Vincent-Salomon, Anne; Tabone, Eric; Theillet, Charles; Thomas, Gilles; Tost, Joerg; Treilleux, Isabelle; Bioulac-Sage, Paulette; Clement, Bruno; Decaens, Thomas; Degos, Francoise; Franco, Dominique; Gut, Ivo; Gut, Marta; Heath, Simon

    2010-01-01

    The International Cancer Genome Consortium (ICGC) was launched to coordinate large-scale cancer genome studies in tumours from 50 different cancer types and/or subtypes that are of clinical and societal importance across the globe. Systematic studies of more than 25,000 cancer genomes at the genomic

  2. 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.

  3. Cancer Genome Anatomy Project | Office of Cancer Genomics

    Science.gov (United States)

    The National Cancer Institute (NCI) Cancer Genome Anatomy Project (CGAP) is an online resource designed to provide the research community access to biological tissue characterization data. Request a free copy of the CGAP Website Virtual Tour CD from ocg@mail.nih.gov.

  4. Genomic determinants of cancer immunotherapy.

    Science.gov (United States)

    Miao, Diana; Van Allen, Eliezer M

    2016-08-01

    Cancer immunotherapies - including therapeutic vaccines, adoptive cell transfer, oncolytic viruses, and immune checkpoint blockade - yield durable responses in many cancer types, but understanding of predictors of response is incomplete. Genomic characterization of human cancers has already contributed to the success of targeted therapies; in cancer immunotherapy, identification of tumor-specific antigens through whole-exome sequencing may be key to designing individualized, highly immunogenic therapeutic vaccines. Additionally, pre-treatment tumor mutational and gene expression signatures can predict which patients are most likely to benefit from cancer immunotherapy. Continued work in harnessing genomic, transcriptomic, and immunological data from clinical cohorts of immunotherapy-treated patients will bring the promises of precision medicine to immuno-oncology.

  5. Genomic profiling of breast cancer.

    Science.gov (United States)

    Pandey, Anjita; Singh, Alok Kumar; Maurya, Sanjeev Kumar; Rai, Rajani; Tewari, Mallika; Kumar, Mohan; Shukla, Hari S

    2009-05-01

    Genome study provides significant changes in the advancement of molecular diagnosis and treatment in Breast cancer. Several recent critical advances and high-throughput techniques identified the genomic trouble and dramatically accelerated the pace of research in preventing and curing this malignancy. Tumor-suppressor genes, proto-oncogenes, DNA-repair genes, carcinogen-metabolism genes are critically involved in progression of breast cancer. We reviewed imperative finding in breast genetics, ongoing work to segregate further susceptible genes, and preliminary studies on molecular profiling.

  6. Cancer Genome Anatomy Project (CGAP) | Office of Cancer Genomics

    Science.gov (United States)

    CGAP generated a wide range of genomics data on cancerous cells that are accessible through easy-to-use online tools. Researchers, educators, and students can find "in silico" answers to biological questions through the CGAP website. Request a free copy of the CGAP Website Virtual Tour CD from ocg@mail.nih.gov to learn how to navigate the website.

  7. Dana-Farber Cancer Institute | Office of Cancer Genomics

    Science.gov (United States)

    Functional Annotation of Cancer Genomes Principal Investigator: William C. Hahn, M.D., Ph.D. The comprehensive characterization of cancer genomes has and will continue to provide an increasingly complete catalog of genetic alterations in specific cancers. However, most epithelial cancers harbor hundreds of genetic alterations as a consequence of genomic instability. Therefore, the functional consequences of the majority of mutations remain unclear.

  8. International network of cancer genome projects.

    OpenAIRE

    Aretz, Axel; Bernabé, Rosa R.; Eerola, Iiro; Hemsley, Fiona M.; Jennings, Jennifer L.; Kerr, David; Klatt, Peter; Kolar, Patrik; Lane, David P; Laplace, Frank; Nettekoven, Gerd; Remacle, Jacques; WATANABE, Koichi; Yuen, Matthew M. F.; Knoppers, Bartha M.

    2010-01-01

    The International Cancer Genome Consortium (ICGC) was launched to coordinate large-scale cancer genome studies in tumours from 50 different cancer types and/or subtypes that are of clinical and societal importance across the globe. Systematic studies of more than 25,000 cancer genomes at the genomic, epigenomic and transcriptomic levels will reveal the repertoire of oncogenic mutations, uncover traces of the mutagenic influences, define clinically relevant subtypes for prognosis and therapeut...

  9. Mouse p53-Deficient Cancer Models as Platforms for Obtaining Genomic Predictors of Human Cancer Clinical Outcomes

    Science.gov (United States)

    Dueñas, Marta; Santos, Mirentxu; Aranda, Juan F.; Bielza, Concha; Martínez-Cruz, Ana B.; Lorz, Corina; Taron, Miquel; Ciruelos, Eva M.; Rodríguez-Peralto, José L.; Martín, Miguel; Larrañaga, Pedro; Dahabreh, Jubrail; Stathopoulos, George P.; Rosell, Rafael; Paramio, Jesús M.; García-Escudero, Ramón

    2012-01-01

    Mutations in the TP53 gene are very common in human cancers, and are associated with poor clinical outcome. Transgenic mouse models lacking the Trp53 gene or that express mutant Trp53 transgenes produce tumours with malignant features in many organs. We previously showed the transcriptome of a p53-deficient mouse skin carcinoma model to be similar to those of human cancers with TP53 mutations and associated with poor clinical outcomes. This report shows that much of the 682-gene signature of this murine skin carcinoma transcriptome is also present in breast and lung cancer mouse models in which p53 is inhibited. Further, we report validated gene-expression-based tests for predicting the clinical outcome of human breast and lung adenocarcinoma. It was found that human patients with cancer could be stratified based on the similarity of their transcriptome with the mouse skin carcinoma 682-gene signature. The results also provide new targets for the treatment of p53-defective tumours. PMID:22880004

  10. Genetic and genomic analysis modeling of germline c-MYC overexpression and cancer susceptibility

    Directory of Open Access Journals (Sweden)

    Nunes Virginia

    2008-01-01

    Full Text Available Abstract Background Germline genetic variation is associated with the differential expression of many human genes. The phenotypic effects of this type of variation may be important when considering susceptibility to common genetic diseases. Three regions at 8q24 have recently been identified to independently confer risk of prostate cancer. Variation at 8q24 has also recently been associated with risk of breast and colorectal cancer. However, none of the risk variants map at or relatively close to known genes, with c-MYC mapping a few hundred kilobases distally. Results This study identifies cis-regulators of germline c-MYC expression in immortalized lymphocytes of HapMap individuals. Quantitative analysis of c-MYC expression in normal prostate tissues suggests an association between overexpression and variants in Region 1 of prostate cancer risk. Somatic c-MYC overexpression correlates with prostate cancer progression and more aggressive tumor forms, which was also a pathological variable associated with Region 1. Expression profiling analysis and modeling of transcriptional regulatory networks predicts a functional association between MYC and the prostate tumor suppressor KLF6. Analysis of MYC/Myc-driven cell transformation and tumorigenesis substantiates a model in which MYC overexpression promotes transformation by down-regulating KLF6. In this model, a feedback loop through E-cadherin down-regulation causes further transactivation of c-MYC. Conclusion This study proposes that variation at putative 8q24 cis-regulator(s of transcription can significantly alter germline c-MYC expression levels and, thus, contribute to prostate cancer susceptibility by down-regulating the prostate tumor suppressor KLF6 gene.

  11. Implications of using whole genome sequencing to test unselected populations for high risk breast cancer genes: a modelling study

    OpenAIRE

    Warren-Gash, Charlotte; Kroese, Mark; Burton, Hilary; Pharoah, Paul

    2016-01-01

    Background The decision to test for high risk breast cancer gene mutations is traditionally based on risk scores derived from age, family and personal cancer history. Next generation sequencing technologies such as whole genome sequencing (WGS) make wider population testing more feasible. In the UK’s 100,000 Genomes Project, mutations in 16 genes including BRCA1 and BRCA2 are to be actively sought regardless of clinical presentation. The implications of deploying this approach at scale for pa...

  12. Translating genomics in cancer care.

    Science.gov (United States)

    Bombard, Yvonne; Bach, Peter B; Offit, Kenneth

    2013-11-01

    There is increasing enthusiasm for genomics and its promise in advancing personalized medicine. Genomic information has been used to personalize health care for decades, spanning the fields of cardiovascular disease, infectious disease, endocrinology, metabolic medicine, and hematology. However, oncology has often been the first test bed for the clinical translation of genomics for diagnostic, prognostic, and therapeutic applications. Notable hereditary cancer examples include testing for mutations in BRCA1 or BRCA2 in unaffected women to identify those at significantly elevated risk for developing breast and ovarian cancers, and screening patients with newly diagnosed colorectal cancer for mutations in 4 mismatch repair genes to reduce morbidity and mortality in their relatives. Somatic genomic testing is also increasingly used in oncology, with gene expression profiling of breast tumors and EGFR testing to predict treatment response representing commonly used examples. Health technology assessment provides a rigorous means to inform clinical and policy decision-making through systematic assessment of the evidentiary base, along with precepts of clinical effectiveness, cost-effectiveness, and consideration of risks and benefits for health care delivery and society. Although this evaluation is a fundamental step in the translation of any new therapeutic, procedure, or diagnostic test into clinical care, emerging developments may threaten this standard. These include "direct to consumer" genomic risk assessment services and the challenges posed by incidental results generated from next-generation sequencing (NGS) technologies. This article presents a review of the evidentiary standards and knowledge base supporting the translation of key cancer genomic technologies along the continuum of validity, utility, cost-effectiveness, health service impacts, and ethical and societal issues, and offers future research considerations to guide the responsible introduction of

  13. Clinical Implications of the Cancer Genome

    OpenAIRE

    MacConaill, Laura E; Garraway, Levi A

    2010-01-01

    Cancer is a disease of the genome. Most tumors harbor a constellation of structural genomic alterations that may dictate their clinical behavior and treatment response. Whereas elucidating the nature and importance of these genomic alterations has been the goal of cancer biologists for several decades, ongoing global genome characterization efforts are revolutionizing both tumor biology and the optimal paradigm for cancer treatment at an unprecedented scope. The pace of advance has been empow...

  14. Genome-Scale Models

    DEFF Research Database (Denmark)

    Bergdahl, Basti; Sonnenschein, Nikolaus; Machado, Daniel;

    2016-01-01

    An introduction to genome-scale models, how to build and use them, will be given in this chapter. Genome-scale models have become an important part of systems biology and metabolic engineering, and are increasingly used in research, both in academica and in industry, both for modeling chemical...

  15. Integration of genomics in cancer care

    DEFF Research Database (Denmark)

    Santos, Erika Maria Monteiro; Edwards, Quannetta T; Floria-Santos, Milena;

    2013-01-01

    PURPOSE: The article aims to introduce nurses to how genetics-genomics is currently integrated into cancer care from prevention to treatment and influencing oncology nursing practice. ORGANIZING CONSTRUCT: An overview of genetics-genomics is described as it relates to cancer etiology, hereditary...... cancer syndromes, epigenetics factors, and management of care considerations. METHODS: Peer-reviewed literature and expert professional guidelines were reviewed to address concepts of genetics-genomics in cancer care. FINDINGS: Cancer is now known to be heterogeneous at the molecular level, with genetic......: Rapidly developing advances in genetics-genomics are changing all aspects of cancer care, with implications for nursing practice. CLINICAL RELEVANCE: Nurses can educate cancer patients and their families about genetic-genomic advances and advocate for use of evidence-based genetic-genomic practice...

  16. Genomic instability and cancer: an introduction

    Institute of Scientific and Technical Information of China (English)

    Zhiyuan Shen

    2011-01-01

    @@ Genomic instability as a major driving force of tumorigenesis.The ultimate goal of cell division for most non-cancerous somatic cells is to accurately duplicate the genome and then evenly divide the duplicated genome into the two daughter cells.This ensures that the daughter cells will have exactly the same genetic material as their parent cell.

  17. Genomic tumor evolution of breast cancer.

    Science.gov (United States)

    Sato, Fumiaki; Saji, Shigehira; Toi, Masakazu

    2016-01-01

    Owing to recent technical development of comprehensive genome-wide analysis such as next generation sequencing, deep biological insights of breast cancer have been revealed. Information of genomic mutations and rearrangements in patients' tumors is indispensable to understand the mechanism in carcinogenesis, progression, metastasis, and resistance to systemic treatment of breast cancer. To date, comprehensive genomic analyses illustrate not only base substitution patterns and lists of driver mutations and key rearrangements, but also a manner of tumor evolution. Breast cancer genome is dynamically changing and evolving during cancer development course from non-invasive disease via invasive primary tumor to metastatic tumor, and during treatment exposure. The accumulation pattern of base substitution and genomic rearrangement looks gradual and punctuated, respectively, in analogy with contrasting theories for evolution manner of species, Darwin's phyletic gradualism, and Eldredge and Gould's "punctuated equilibrium". Liquid biopsy is a non-invasive method to detect the genomic evolution of breast cancer. Genomic mutation patterns in circulating tumor cells and circulating cell-free tumor DNA represent those of tumors existing in patient body. Liquid biopsy methods are now under development for future application to clinical practice of cancer treatment. In this article, latest knowledge regarding breast cancer genome, especially in terms of 'tumor evolution', is summarized. PMID:25998191

  18. ChromoHub V2: cancer genomics

    OpenAIRE

    Shah, Muhammad A; Denton, Emily L; Liu, Lihua; Schapira, Matthieu

    2013-01-01

    Summary: Cancer genomics data produced by next-generation sequencing support the notion that epigenetic mechanisms play a central role in cancer. We have previously developed Chromohub, an open access online interface where users can map chemical, structural and biological data from public repositories on phylogenetic trees of protein families involved in chromatin mediated-signaling. Here, we describe a cancer genomics interface that was recently added to Chromohub; the frequency of mutation...

  19. Genomic Copy Number Variations in the Genomes of Leukocytes Predict Prostate Cancer Clinical Outcomes.

    Directory of Open Access Journals (Sweden)

    Yan P Yu

    Full Text Available Accurate prediction of prostate cancer clinical courses remains elusive. In this study, we performed whole genome copy number analysis on leukocytes of 273 prostate cancer patients using Affymetrix SNP6.0 chip. Copy number variations (CNV were found across all chromosomes of the human genome. An average of 152 CNV fragments per genome was identified in the leukocytes from prostate cancer patients. The size distributions of CNV in the genome of leukocytes were highly correlative with prostate cancer aggressiveness. A prostate cancer outcome prediction model was developed based on large size ratio of CNV from the leukocyte genomes. This prediction model generated an average prediction rate of 75.2%, with sensitivity of 77.3% and specificity of 69.0% for prostate cancer recurrence. When combined with Nomogram and the status of fusion transcripts, the average prediction rate was improved to 82.5% with sensitivity of 84.8% and specificity of 78.2%. In addition, the leukocyte prediction model was 62.6% accurate in predicting short prostate specific antigen doubling time. When combined with Gleason's grade, Nomogram and the status of fusion transcripts, the prediction model generated a correct prediction rate of 77.5% with 73.7% sensitivity and 80.1% specificity. To our knowledge, this is the first study showing that CNVs in leukocyte genomes are predictive of clinical outcomes of a human malignancy.

  20. Genomic Feature Models

    DEFF Research Database (Denmark)

    Sørensen, Peter; Edwards, Stefan McKinnon; Rohde, Palle Duun

    Whole-genome sequences and multiple trait phenotypes from large numbers of individuals will soon be available in many populations. Well established statistical modeling approaches enable the genetic analyses of complex trait phenotypes while accounting for a variety of additive and non-additive g...... regions and gene ontologies) that provide better model fit and increase predictive ability of the statistical model for this trait....

  1. 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...... large interest in developing pathway and network analysis methods that group genes and illuminate the processes involved. We provide an overview of these analysis techniques and show where they guide mechanistic and translational investigations....

  2. Prostate Cancer Genomics: Toward a New Understanding

    OpenAIRE

    John S Witte

    2008-01-01

    Recent genetics and genomics studies of prostate cancer help clarify the genetic basis of this common but complex disease. Genome-wide studies have detected numerous variants associated with disease as well as common gene fusions and expression ‘signatures’ in prostate tumors. Based on these results, some advocate gene-based individualized screening for prostate cancer, although such testing may only be worthwhile to distinguish disease aggressiveness. Lessons learned here provide strategies ...

  3. Characterizing the cancer genome in lung adenocarcinoma

    OpenAIRE

    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

    2007-01-01

    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 ...

  4. The genomic landscape of prostate cancer

    Directory of Open Access Journals (Sweden)

    Sylvan eBaca

    2012-05-01

    Full Text Available Prostate cancer is a common malignancy in men, with a markedly variable clinical course. Somatic alterations in DNA drive the growth of prostate cancers and may underlie the behavior of aggressive versus indolent tumors. The accelerating application of genomic technologies over the last two decades has identified mutations that drive prostate cancer formation, progression, and therapeutic resistance. Here, we discuss exemplary somatic mutations in prostate cancer, and highlight mutated cellular pathways with biological and possible therapeutic importance. Examples include mutated genes involved in androgen signaling, cell cycle regulation, signal transduction and development. Some genetic alterations may also predict the clinical course of disease or response to therapy, although the molecular heterogeneity of prostate tumors poses challenges to genomic biomarker identification. The widespread application of massively parallel sequencing technology to the analysis of prostate cancer genomes should continue to advance both discovery-oriented and diagnostic avenues.

  5. Novel patterns of cancer genome evolution

    Institute of Scientific and Technical Information of China (English)

    Xia Zhang; Xiaodi Deng; Yu Zhang; Zhiguang Li

    2015-01-01

    Cells usually undergo a long journey of evolution during the progression from normal to precancerous cells and finally to full-fledged cancer cells. Multiple genomic aberrations are acquired during this journey that could either act as drivers to confer significant growth advantages or act as passengers with little effect on the tumor growth. Recent advances in sequencing technology have made it feasible to decipher the evolutionary course of a cancer cell on a genome-wide level by evaluating the relative number of mutated alleles. Novel terms such as chromothripsis and chromoplexy have been introduced to describe the newly identified patterns of cancer genome evolution. These new insights have greatly expanded our understanding of the initiation and progression of cancers, which should aid in improving the efficiency of cancer management and treatment.

  6. Cancer Genome Sequencing and Its Implications for Personalized Cancer Vaccines

    International Nuclear Information System (INIS)

    New DNA sequencing platforms have revolutionized human genome sequencing. The dramatic advances in genome sequencing technologies predict that the $1,000 genome will become a reality within the next few years. Applied to cancer, the availability of cancer genome sequences permits real-time decision-making with the potential to affect diagnosis, prognosis, and treatment, and has opened the door towards personalized medicine. A promising strategy is the identification of mutated tumor antigens, and the design of personalized cancer vaccines. Supporting this notion are preliminary analyses of the epitope landscape in breast cancer suggesting that individual tumors express significant numbers of novel antigens to the immune system that can be specifically targeted through cancer vaccines

  7. Genome Modeling System: A Knowledge Management Platform for Genomics.

    Directory of Open Access Journals (Sweden)

    Malachi Griffith

    2015-07-01

    Full Text Available In this work, we present the Genome Modeling System (GMS, an analysis information management system capable of executing automated genome analysis pipelines at a massive scale. The GMS framework provides detailed tracking of samples and data coupled with reliable and repeatable analysis pipelines. The GMS also serves as a platform for bioinformatics development, allowing a large team to collaborate on data analysis, or an individual researcher to leverage the work of others effectively within its data management system. Rather than separating ad-hoc analysis from rigorous, reproducible pipelines, the GMS promotes systematic integration between the two. As a demonstration of the GMS, we performed an integrated analysis of whole genome, exome and transcriptome sequencing data from a breast cancer cell line (HCC1395 and matched lymphoblastoid line (HCC1395BL. These data are available for users to test the software, complete tutorials and develop novel GMS pipeline configurations. The GMS is available at https://github.com/genome/gms.

  8. Cancer Genome Atlas Pan-cancer Analysis Project

    OpenAIRE

    Zhang, Kun; Wang, Hong

    2015-01-01

    Cancer can exhibit different forms depending on the site of origin, cell types, the different forms of genetic mutations which also affect cancer therapeutic effect. Although many genes have been demonstrated to change a direct result of the change in phenotype, however, many cancers lineage complex molecular mechanisms are still not fully elucidated. Therefore, The Cancer Genome Atlas (TCGA) Research Network analyzed a large human tumors, in order to find the molecular changes in DNA, RNA, p...

  9. Genomic rearrangements of PTEN in prostate cancer

    Directory of Open Access Journals (Sweden)

    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.

  10. Cancer Genome Atlas Pan-cancer Analysis Project

    Directory of Open Access Journals (Sweden)

    Kun ZHANG

    2015-04-01

    Full Text Available Cancer can exhibit different forms depending on the site of origin, cell types, the different forms of genetic mutations which also affect cancer therapeutic effect. Although many genes have been demonstrated to change a direct result of the change in phenotype, however, many cancers lineage complex molecular mechanisms are still not fully elucidated. Therefore, The Cancer Genome Atlas (TCGA Research Network analyzed a large human tumors, in order to find the molecular changes in DNA, RNA, protein and epigenetic level, The results contain a wealth of data provides us with an opportunity for common, personality and new ideas throughout the cancer lineages form a whole description. Pan-cancer genome program first compares the 12 kinds of cancer types. Analysis of different tumor molecular changes and their functions, will tell us how effective treatment method is applied to a similar phenotype of the tumor.

  11. [Cancer Genome Atlas Pan-cancer Analysis Project].

    Science.gov (United States)

    Zhang, Kun; Wang, Hong

    2015-04-01

    Cancer can exhibit different forms depending on the site of origin, cell types, the different forms of genetic mutations which also affect cancer therapeutic effect. Although many genes have been demonstrated to change a direct result of the change in phenotype, however, many cancers lineage complex molecular mechanisms are still not fully elucidated. Therefore, The Cancer Genome Atlas (TCGA) Research Network analyzed a large human tumors, in order to find the molecular changes in DNA, RNA, protein and epigenetic level, The results contain a wealth of data provides us with an opportunity for common, personality and new ideas throughout the cancer lineages form a whole description. Pan-cancer genome program first compares the 12 kinds of cancer types. Analysis of different tumor molecular changes and their functions, will tell us how effective treatment method is applied to a similar phenotype of the tumor. PMID:25936886

  12. Characterizing genomic alterations in cancer by complementary functional associations | Office of Cancer Genomics

    Science.gov (United States)

    Systematic efforts to sequence the cancer genome have identified large numbers of mutations and copy number alterations in human cancers. However, elucidating the functional consequences of these variants, and their interactions to drive or maintain oncogenic states, remains a challenge in cancer research. We developed REVEALER, a computational method that identifies combinations of mutually exclusive genomic alterations correlated with functional phenotypes, such as the activation or gene dependency of oncogenic pathways or sensitivity to a drug treatment.

  13. 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).

  14. Open-Access Cancer Genomics - Office of Cancer Clinical Proteomics Research

    Science.gov (United States)

    The completion of the Human Genome Project sparked a revolution in high-throughput genomics applied towards deciphering genetically complex diseases, like cancer. Now, almost 10 years later, we have a mountain of genomics data on many different cancer type

  15. 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.

  16. Genome organization, instabilities, stem cells, and cancer

    Directory of Open Access Journals (Sweden)

    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.

  17. Exploring TCGA Pan-Cancer Data at the UCSC Cancer Genomics Browser

    OpenAIRE

    Cline, Melissa S.; Brian Craft; Teresa Swatloski; Mary Goldman; Singer Ma; David Haussler; Jingchun Zhu

    2013-01-01

    The UCSC Cancer Genomics Browser (https://genome-cancer.ucsc.edu) offers interactive visualization and exploration of TCGA genomic, phenotypic, and clinical data, as produced by the Cancer Genome Atlas Research Network. Researchers can explore the impact of genomic alterations on phenotypes by visualizing gene and protein expression, copy number, DNA methylation, somatic mutation and pathway inference data alongside clinical features, Pan-Cancer subtype classifications and genomic biomarkers....

  18. Overview | Office of Cancer Genomics

    Science.gov (United States)

    The Therapeutically Applicable Research to Generate Effective Treatments (TARGET) initiative uses comprehensive molecular characterization to determine the genetic changes that drive the initiation and progression of hard-to-treat childhood cancers. TARGET aims to identify therapeutic targets and prognostic markers so that new, more effective treatment strategies can be developed and applied. Novel pediatric cancer treatments are needed because:

  19. Genomic analysis of epithelial ovarian cancer

    Institute of Scientific and Technical Information of China (English)

    John Farley; Laurent L Ozbun; Michael J Birrer

    2008-01-01

    Ovarian cancer is a major health problem for women in the United States.Despite evidence of considerable heterogeneity,most cases of ovarian cancer are treated in a similar fashion.The molecular basis for the clinicopathologic characteristics of these tumors remains poorly defined.Whole genome expression profiling is a genomic tool,which can identify dysregulated genes and uncover unique sub-classes of tumors.The application of this technology to ovarian cancer has provided a solid molecular basis for differences in histology and grade of ovarian tumors.Differentially expressed genes identified pathways implicated in cell proliferation,invasion,motility,chromosomal instability,and gene silencing and provided new insights into the origin and potential treatment of these cancers.The added knowledge provided by global gene expression profiling should allow for a more rational treatment of ovarian cancers.These techniques are leading to a paradigm shift from empirical treatment to an individually tailored approach.This review summarizes the new genomic data on epithelial ovarian cancers of different histology and grade and the impact it will have on our understanding and treatment of this disease.

  20. 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.

  1. 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

  2. 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

  3. Glossary | Office of Cancer Genomics

    Science.gov (United States)

    A   B   C   D   E   F   G   H   I   J   K   L   M   N   O   P   Q   R   S   T   U   V   W   X   Y   Z     B Bioinformatics The use of computing tools to manage and analyze genomic and molecular biological data.

  4. ScreenBEAM: a novel meta-analysis algorithm for functional genomics screens via Bayesian hierarchical modeling | Office of Cancer Genomics

    Science.gov (United States)

    Functional genomics (FG) screens, using RNAi or CRISPR technology, have become a standard tool for systematic, genome-wide loss-of-function studies for therapeutic target discovery. As in many large-scale assays, however, off-target effects, variable reagents' potency and experimental noise must be accounted for appropriately control for false positives.

  5. Resources | Office of Cancer Genomics

    Science.gov (United States)

    OCG provides a variety of scientific and educational resources for both cancer researchers and members of the general public. These resources are divided into the following types: OCG-Supported Resources: Tools, databases, and reagents generated by initiated and completed OCG programs for researchers, educators, and students. (Note: Databases for current OCG programs are available through program-specific data matrices)

  6. Childhood Cancer Genomics (PDQ®)—Health Professional Version

    Science.gov (United States)

    Expert-reviewed information summary about the genomics of childhood cancer. The summary describes the molecular subtypes for specific pediatric cancers and their associated clinical characteristics, the recurring genomic alterations that characterize each subtype at diagnosis or relapse, and the therapeutic and prognostic significance of the genomic alterations. The genomic alterations associated with brain tumors, kidney tumors, leukemias, lymphomas, sarcomas, and other cancers are discussed.

  7. Review of State Comprehensive Cancer Control Plans for Genomics Content

    OpenAIRE

    Robert C. Millikan, DVM, PhD; Tejinder Rakhra-Burris, MA; Erin Shaughnessy Zuiker, MPH; Debra E. Irwin, PhD, MSPH

    2005-01-01

    Introduction The goals of this study were to determine U.S. states with Comprehensive Cancer Control plans that include genomics in some capacity and to review successes with and barriers to implementation of genomics-related cancer control initiatives. Methods This study was conducted in two phases. Phase one included a content analysis of written state Comprehensive Cancer Control plans (n = 30) for terms related to genomics, or genomic components (n = 18). The second phase involved te...

  8. Predicting human genetic interactions from cancer genome evolution.

    Directory of Open Access Journals (Sweden)

    Xiaowen Lu

    Full Text Available Synthetic Lethal (SL genetic interactions play a key role in various types of biological research, ranging from understanding genotype-phenotype relationships to identifying drug-targets against cancer. Despite recent advances in empirical measuring SL interactions in human cells, the human genetic interaction map is far from complete. Here, we present a novel approach to predict this map by exploiting patterns in cancer genome evolution. First, we show that empirically determined SL interactions are reflected in various gene presence, absence, and duplication patterns in hundreds of cancer genomes. The most evident pattern that we discovered is that when one member of an SL interaction gene pair is lost, the other gene tends not to be lost, i.e. the absence of co-loss. This observation is in line with expectation, because the loss of an SL interacting pair will be lethal to the cancer cell. SL interactions are also reflected in gene expression profiles, such as an under representation of cases where the genes in an SL pair are both under expressed, and an over representation of cases where one gene of an SL pair is under expressed, while the other one is over expressed. We integrated the various previously unknown cancer genome patterns and the gene expression patterns into a computational model to identify SL pairs. This simple, genome-wide model achieves a high prediction power (AUC = 0.75 for known genetic interactions. It allows us to present for the first time a comprehensive genome-wide list of SL interactions with a high estimated prediction precision, covering up to 591,000 gene pairs. This unique list can potentially be used in various application areas ranging from biotechnology to medical genetics.

  9. Identifying driver mutations in sequenced cancer genomes

    DEFF Research Database (Denmark)

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

    2014-01-01

    High-throughput DNA sequencing is revolutionizing the study of cancer and enabling the measurement of the somatic mutations that drive cancer development. However, the resulting sequencing datasets are large and complex, obscuring the clinically important mutations in a background of errors, noise......, and random mutations. Here, we review computational approaches to identify somatic mutations in cancer genome sequences and to distinguish the driver mutations that are responsible for cancer from random, passenger mutations. First, we describe approaches to detect somatic mutations from high-throughput DNA...... sequencing data, particularly for tumor samples that comprise heterogeneous populations of cells. Next, we review computational approaches that aim to predict driver mutations according to their frequency of occurrence in a cohort of samples, or according to their predicted functional impact on protein...

  10. Using large-scale genome variation cohorts to decipher the molecular mechanism of cancer.

    Science.gov (United States)

    Habermann, Nina; Mardin, Balca R; Yakneen, Sergei; Korbel, Jan O

    2016-01-01

    Characterizing genomic structural variations (SVs) in the human genome remains challenging, and there is a growing interest to understand somatic SVs occurring in cancer, a disease of the genome. A havoc-causing SV process known as chromothripsis scars the genome when localized chromosome shattering and repair occur in a one-off catastrophe. Recent efforts led to the development of a set of conceptual criteria for the inference of chromothripsis events in cancer genomes and to the development of experimental model systems for studying this striking DNA alteration process in vitro. We discuss these approaches, and additionally touch upon current "Big Data" efforts that employ hybrid cloud computing to enable studies of numerous cancer genomes in an effort to search for commonalities and differences in molecular DNA alteration processes in cancer. PMID:27342254

  11. Using large-scale genome variation cohorts to decipher the molecular mechanism of cancer.

    Science.gov (United States)

    Habermann, Nina; Mardin, Balca R; Yakneen, Sergei; Korbel, Jan O

    2016-01-01

    Characterizing genomic structural variations (SVs) in the human genome remains challenging, and there is a growing interest to understand somatic SVs occurring in cancer, a disease of the genome. A havoc-causing SV process known as chromothripsis scars the genome when localized chromosome shattering and repair occur in a one-off catastrophe. Recent efforts led to the development of a set of conceptual criteria for the inference of chromothripsis events in cancer genomes and to the development of experimental model systems for studying this striking DNA alteration process in vitro. We discuss these approaches, and additionally touch upon current "Big Data" efforts that employ hybrid cloud computing to enable studies of numerous cancer genomes in an effort to search for commonalities and differences in molecular DNA alteration processes in cancer.

  12. Comprehensive genomic profiles of small cell lung cancer.

    Science.gov (United States)

    George, Julie; Lim, Jing Shan; Jang, Se Jin; Cun, Yupeng; Ozretić, Luka; Kong, Gu; Leenders, Frauke; Lu, Xin; Fernández-Cuesta, Lynnette; Bosco, Graziella; Müller, Christian; Dahmen, Ilona; Jahchan, Nadine S; Park, Kwon-Sik; Yang, Dian; Karnezis, Anthony N; Vaka, Dedeepya; Torres, Angela; Wang, Maia Segura; Korbel, Jan O; Menon, Roopika; Chun, Sung-Min; Kim, Deokhoon; Wilkerson, Matt; Hayes, Neil; Engelmann, David; Pützer, Brigitte; Bos, Marc; Michels, Sebastian; Vlasic, Ignacija; Seidel, Danila; Pinther, Berit; Schaub, Philipp; Becker, Christian; Altmüller, Janine; Yokota, Jun; Kohno, Takashi; Iwakawa, Reika; Tsuta, Koji; Noguchi, Masayuki; Muley, Thomas; Hoffmann, Hans; Schnabel, Philipp A; Petersen, Iver; Chen, Yuan; Soltermann, Alex; Tischler, Verena; Choi, Chang-min; Kim, Yong-Hee; Massion, Pierre P; Zou, Yong; Jovanovic, Dragana; Kontic, Milica; Wright, Gavin M; Russell, Prudence A; Solomon, Benjamin; Koch, Ina; Lindner, Michael; Muscarella, Lucia A; la Torre, Annamaria; Field, John K; Jakopovic, Marko; Knezevic, Jelena; Castaños-Vélez, Esmeralda; Roz, Luca; Pastorino, Ugo; Brustugun, Odd-Terje; Lund-Iversen, Marius; Thunnissen, Erik; Köhler, Jens; Schuler, Martin; Botling, Johan; Sandelin, Martin; Sanchez-Cespedes, Montserrat; Salvesen, Helga B; Achter, Viktor; Lang, Ulrich; Bogus, Magdalena; Schneider, Peter M; Zander, Thomas; Ansén, Sascha; Hallek, Michael; Wolf, Jürgen; Vingron, Martin; Yatabe, Yasushi; Travis, William D; Nürnberg, Peter; Reinhardt, Christian; Perner, Sven; Heukamp, Lukas; Büttner, Reinhard; Haas, Stefan A; Brambilla, Elisabeth; Peifer, Martin; Sage, Julien; Thomas, Roman K

    2015-08-01

    We have sequenced the genomes of 110 small cell lung cancers (SCLC), one of the deadliest human cancers. In nearly all the tumours analysed we found bi-allelic inactivation of TP53 and RB1, sometimes by complex genomic rearrangements. Two tumours with wild-type RB1 had evidence of chromothripsis leading to overexpression of cyclin D1 (encoded by the CCND1 gene), revealing an alternative mechanism of Rb1 deregulation. Thus, loss of the tumour suppressors TP53 and RB1 is obligatory in SCLC. We discovered somatic genomic rearrangements of TP73 that create an oncogenic version of this gene, TP73Δex2/3. In rare cases, SCLC tumours exhibited kinase gene mutations, providing a possible therapeutic opportunity for individual patients. Finally, we observed inactivating mutations in NOTCH family genes in 25% of human SCLC. Accordingly, activation of Notch signalling in a pre-clinical SCLC mouse model strikingly reduced the number of tumours and extended the survival of the mutant mice. Furthermore, neuroendocrine gene expression was abrogated by Notch activity in SCLC cells. This first comprehensive study of somatic genome alterations in SCLC uncovers several key biological processes and identifies candidate therapeutic targets in this highly lethal form of cancer. PMID:26168399

  13. Comprehensive genomic profiles of small cell lung cancer

    Science.gov (United States)

    George, Julie; Lim, Jing Shan; Jang, Se Jin; Cun, Yupeng; Ozretić, Luka; Kong, Gu; Leenders, Frauke; Lu, Xin; Fernández-Cuesta, Lynnette; Bosco, Graziella; Müller, Christian; Dahmen, Ilona; Jahchan, Nadine S.; Park, Kwon-Sik; Yang, Dian; Karnezis, Anthony N.; Vaka, Dedeepya; Torres, Angela; Wang, Maia Segura; Korbel, Jan O.; Menon, Roopika; Chun, Sung-Min; Kim, Deokhoon; Wilkerson, Matt; Hayes, Neil; Engelmann, David; Pützer, Brigitte; Bos, Marc; Michels, Sebastian; Vlasic, Ignacija; Seidel, Danila; Pinther, Berit; Schaub, Philipp; Becker, Christian; Altmüller, Janine; Yokota, Jun; Kohno, Takashi; Iwakawa, Reika; Tsuta, Koji; Noguchi, Masayuki; Muley, Thomas; Hoffmann, Hans; Schnabel, Philipp A.; Petersen, Iver; Chen, Yuan; Soltermann, Alex; Tischler, Verena; Choi, Chang-min; Kim, Yong-Hee; Massion, Pierre P.; Zou, Yong; Jovanovic, Dragana; Kontic, Milica; Wright, Gavin M.; Russell, Prudence A.; Solomon, Benjamin; Koch, Ina; Lindner, Michael; Muscarella, Lucia A.; la Torre, Annamaria; Field, John K.; Jakopovic, Marko; Knezevic, Jelena; Castaños-Vélez, Esmeralda; Roz, Luca; Pastorino, Ugo; Brustugun, Odd-Terje; Lund-Iversen, Marius; Thunnissen, Erik; Köhler, Jens; Schuler, Martin; Botling, Johan; Sandelin, Martin; Sanchez-Cespedes, Montserrat; Salvesen, Helga B.; Achter, Viktor; Lang, Ulrich; Bogus, Magdalena; Schneider, Peter M.; Zander, Thomas; Ansén, Sascha; Hallek, Michael; Wolf, Jürgen; Vingron, Martin; Yatabe, Yasushi; Travis, William D.; Nürnberg, Peter; Reinhardt, Christian; Perner, Sven; Heukamp, Lukas; Büttner, Reinhard; Haas, Stefan A.; Brambilla, Elisabeth; Peifer, Martin; Sage, Julien; Thomas, Roman K.

    2016-01-01

    We have sequenced the genomes of 110 small cell lung cancers (SCLC), one of the deadliest human cancers. In nearly all the tumours analysed we found bi-allelic inactivation of TP53 and RB1, sometimes by complex genomic rearrangements. Two tumours with wild-type RB1 had evidence of chromothripsis leading to overexpression of cyclin D1 (encoded by the CCND1 gene), revealing an alternative mechanism of Rb1 deregulation. Thus, loss of the tumour suppressors TP53 and RB1 is obligatory in SCLC. We discovered somatic genomic rearrangements of TP73 that create an oncogenic version of this gene, TP73Δex2/3. In rare cases, SCLC tumours exhibited kinase gene mutations, providing a possible therapeutic opportunity for individual patients. Finally, we observed inactivating mutations in NOTCH family genes in 25% of human SCLC. Accordingly, activation of Notch signalling in a pre-clinical SCLC mouse model strikingly reduced the number of tumours and extended the survival of the mutant mice. Furthermore, neuroendocrine gene expression was abrogated by Notch activity in SCLC cells. This first comprehensive study of somatic genome alterations in SCLC uncovers several key biological processes and identifies candidate therapeutic targets in this highly lethal form of cancer. PMID:26168399

  14. International Cancer Genome Consortium Data Portal--a one-stop shop for cancer genomics data.

    Science.gov (United States)

    Zhang, Junjun; Baran, Joachim; Cros, A; Guberman, Jonathan M; Haider, Syed; Hsu, Jack; Liang, Yong; Rivkin, Elena; Wang, Jianxin; Whitty, Brett; Wong-Erasmus, Marie; Yao, Long; Kasprzyk, Arek

    2011-01-01

    The International Cancer Genome Consortium (ICGC) is a collaborative effort to characterize genomic abnormalities in 50 different cancer types. To make this data available, the ICGC has created the ICGC Data Portal. Powered by the BioMart software, the Data Portal allows each ICGC member institution to manage and maintain its own databases locally, while seamlessly presenting all the data in a single access point for users. The Data Portal currently contains data from 24 cancer projects, including ICGC, The Cancer Genome Atlas (TCGA), Johns Hopkins University, and the Tumor Sequencing Project. It consists of 3478 genomes and 13 cancer types and subtypes. Available open access data types include simple somatic mutations, copy number alterations, structural rearrangements, gene expression, microRNAs, DNA methylation and exon junctions. Additionally, simple germline variations are available as controlled access data. The Data Portal uses a web-based graphical user interface (GUI) to offer researchers multiple ways to quickly and easily search and analyze the available data. The web interface can assist in constructing complicated queries across multiple data sets. Several application programming interfaces are also available for programmatic access. Here we describe the organization, functionality, and capabilities of the ICGC Data Portal. PMID:21930502

  15. Review of State Comprehensive Cancer Control Plans for Genomics Content

    Directory of Open Access Journals (Sweden)

    Robert C. Millikan, DVM, PhD

    2005-03-01

    Full Text Available Introduction The goals of this study were to determine U.S. states with Comprehensive Cancer Control plans that include genomics in some capacity and to review successes with and barriers to implementation of genomics-related cancer control initiatives. Methods This study was conducted in two phases. Phase one included a content analysis of written state Comprehensive Cancer Control plans (n = 30 for terms related to genomics, or “genomic components” (n = 18. The second phase involved telephone interviews with the Comprehensive Cancer Control plan coordinators in states with plans that contained genomic components (n = 16. The interview was designed to gather more detailed information about the genomics-related initiatives within the state’s Comprehensive Cancer Control plan and the successes with and barriers to plan implementation, as defined by each state. Results Eighteen of the 30 Comprehensive Cancer Control plans analyzed contained genomics components. We noted a large variability among these 18 plans in the types of genomics components included. Nine (56% of the 16 states interviewed had begun to implement the genomics components in their plan. Most states emphasized educating health care providers and the public about the role of genomics in cancer control. Many states consider awareness of family history to be an important aspect of their Comprehensive Cancer Control plan. Approximately 67% of states with family history components in their plans had begun to implement these goals. Virtually all states reported they would benefit from additional training in cancer genetics and general public health genomics. Conclusion The number of states incorporating genomics into their Comprehensive Cancer Control plans is increasing. Family history is a public health application of genomics that could be implemented more fully into Comprehensive Cancer Control plans.

  16. Computational approaches to identify functional genetic variants in cancer genomes

    Science.gov (United States)

    Gonzalez-Perez, Abel; Mustonen, Ville; Reva, Boris; Ritchie, Graham R.S.; Creixell, Pau; Karchin, Rachel; Vazquez, Miguel; Fink, J. Lynn; Kassahn, Karin S.; Pearson, John V.; Bader, Gary; Boutros, Paul C.; Muthuswamy, Lakshmi; Ouellette, B.F. Francis; Reimand, Jüri; Linding, Rune; Shibata, Tatsuhiro; Valencia, Alfonso; Butler, Adam; Dronov, Serge; Flicek, Paul; Shannon, Nick B.; Carter, Hannah; Ding, Li; Sander, Chris; Stuart, Josh M.; Stein, Lincoln D.; Lopez-Bigas, Nuria

    2014-01-01

    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 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. PMID:23900255

  17. Genomic and epigenomic alterations in prostate cancer

    Directory of Open Access Journals (Sweden)

    Anna Maria eAschelter

    2012-11-01

    Full Text Available Prostate cancer (PC is the second most frequently diagnosed cancer and the second leading cause of cancer deaths in man. The treatment of localized PC includes surgery or radiation therapy. In case of relapse after a definitive treatment or in patients with locally advanced or metastatic disease, the standard treatment includes the androgen-deprivation therapy (ADT. By reducing the levels of Testosterone and dihydrotestosterone (DHT under the castration threshold, the ADT acts on the androgen receptor (AR, even if indirectly. The effects of the ADT are usually temporary and nearly all patients, initially sensitive to the androgen ablation therapy, have a disease progression after a 18-24 months medium term. This is probably due to the selection of the cancer cell clones and to their acquisition of critical somatic genome and epigenomic changes. This review aims to provide an overview about the genetic and epigenetic alterations having a crucial role in the carcinogenesis and in the disease progression toward the castration resistant prostate cancer (CRPC. We focused on the role of the androgen receptor, on its signaling cascade and on the clinical implications that the knowledge of these aspects would have on hormonal therapy, on its failure and its toxicity.

  18. Perspectives of integrative cancer genomics in next generation sequencing era.

    Science.gov (United States)

    Kwon, So Mee; Cho, Hyunwoo; Choi, Ji Hye; Jee, Byul A; Jo, Yuna; Woo, Hyun Goo

    2012-06-01

    The explosive development of genomics technologies including microarrays and next generation sequencing (NGS) has provided comprehensive maps of cancer genomes, including the expression of mRNAs and microRNAs, DNA copy numbers, sequence variations, and epigenetic changes. These genome-wide profiles of the genetic aberrations could reveal the candidates for diagnostic and/or prognostic biomarkers as well as mechanistic insights into tumor development and progression. Recent efforts to establish the huge cancer genome compendium and integrative omics analyses, so-called "integromics", have extended our understanding on the cancer genome, showing its daunting complexity and heterogeneity. However, the challenges of the structured integration, sharing, and interpretation of the big omics data still remain to be resolved. Here, we review several issues raised in cancer omics data analysis, including NGS, focusing particularly on the study design and analysis strategies. This might be helpful to understand the current trends and strategies of the rapidly evolving cancer genomics research. PMID:23105932

  19. KRAS Genomic Status Predicts the Sensitivity of Ovarian Cancer Cells to Decitabine | Office of Cancer Genomics

    Science.gov (United States)

    Decitabine, a cancer therapeutic that inhibits DNA methylation, produces variable antitumor response rates in patients with solid tumors that might be leveraged clinically with identification of a predictive biomarker. In this study, we profiled the response of human ovarian, melanoma, and breast cancer cells treated with decitabine, finding that RAS/MEK/ERK pathway activation and DNMT1 expression correlated with cytotoxic activity. Further, we showed that KRAS genomic status predicted decitabine sensitivity in low-grade and high-grade serous ovarian cancer cells.

  20. Genome-wide network analysis of Wnt signaling in three pediatric cancers

    Science.gov (United States)

    Bao, Ju; Lee, Ho-Jin; Zheng, Jie J.

    2013-10-01

    Genomic structural alteration is common in pediatric cancers, and analysis of data generated by the Pediatric Cancer Genome Project reveals such tumor-related alterations in many Wnt signaling-associated genes. Most pediatric cancers are thought to arise within developing tissues that undergo substantial expansion during early organ formation, growth and maturation, and Wnt signaling plays an important role in this development. We examined three pediatric tumors--medullobastoma, early T-cell precursor acute lymphoblastic leukemia, and retinoblastoma--that show multiple genomic structural variations within Wnt signaling pathways. We mathematically modeled this pathway to investigate the effects of cancer-related structural variations on Wnt signaling. Surprisingly, we found that an outcome measure of canonical Wnt signaling was consistently similar in matched cancer cells and normal cells, even in the context of different cancers, different mutations, and different Wnt-related genes. Our results suggest that the cancer cells maintain a normal level of Wnt signaling by developing multiple mutations.

  1. Genome Wide Methylome Alterations in Lung Cancer.

    Science.gov (United States)

    Mullapudi, Nandita; Ye, Bin; Suzuki, Masako; Fazzari, Melissa; Han, Weiguo; Shi, Miao K; Marquardt, Gaby; Lin, Juan; Wang, Tao; Keller, Steven; Zhu, Changcheng; Locker, Joseph D; Spivack, Simon D

    2015-01-01

    Aberrant cytosine 5-methylation underlies many deregulated elements of cancer. Among paired non-small cell lung cancers (NSCLC), we sought to profile DNA 5-methyl-cytosine features which may underlie genome-wide deregulation. In one of the more dense interrogations of the methylome, we sampled 1.2 million CpG sites from twenty-four NSCLC tumor (T)-non-tumor (NT) pairs using a methylation-sensitive restriction enzyme- based HELP-microarray assay. We found 225,350 differentially methylated (DM) sites in adenocarcinomas versus adjacent non-tumor tissue that vary in frequency across genomic compartment, particularly notable in gene bodies (GB; pLAMA3, AR]. The unique findings from this study include the discovery of numerous candidate The unique findings from this study include the discovery of numerous candidate methylation sites in both PR and GB regions not previously identified in NSCLC, and many non-canonical relationships to gene expression. These DNA methylation features could potentially be developed as risk or diagnostic biomarkers, or as candidate targets for newer methylation locus-targeted preventive or therapeutic agents. PMID:26683690

  2. Genetics and genomics of prostate cancer

    Institute of Scientific and Technical Information of China (English)

    Michael Dean; Hong Lou

    2013-01-01

    Prostate cancer (PCa) is one of the most common malignancies in the world with over 890 000 cases and over 258 000 deaths worldwide each year.Nearly all mortalities from PCa are due to metastatic disease,typically through tumors that evolve to be hormone-refractory or castrate-resistant.Despite intensive epidemiological study,there are few known environmental risk factors,and age and family history are the major determinants.However,there is extreme heterogeneity in PCa incidence worldwide,suggesting that major determining factors have not been described.Genome-wide association studies have been performed and a considerable number of significant,but low-risk loci have been identified.In addition,several groups have analyzed PCa by determination of genomic copy number,fusion gene generation and targeted resequencing of candidate genes,as well as exome and whole genome sequencing.These initial studies have examined both primary and metastatic tumors as well as murine xenografts and identified somatic alterations in TP53 and other potential driver genes,and the disturbance of androgen response and cell cycle pathways.It is hoped that continued characterization of risk factors as well as gene mutation and misregulation in tumors will aid in understanding,diagnosing and better treating PCa.

  3. Genomic alterations in pancreatic cancer and their relevance to therapy

    Institute of Scientific and Technical Information of China (English)

    Erina; Takai; Shinichi; Yachida

    2015-01-01

    Pancreatic cancer is a highly lethal cancer type, for which there are few viable therapeutic options. But, with the advance of sequencing technologies for global genomic analysis, the landscape of genomic alterations in pancreatic cancer is becoming increasingly well understood. In this review, we summarize current knowledge of genomic alterations in 12 core signaling pathways or cellular processes in pancreatic ductal adenocarcinoma, which is the most common type of malignancy in the pancreas, including four commonly mutated genes and many other genes that are mutated at low frequencies. We also describe the potential implications of these genomic alterations for development of novel therapeutic approaches in the context of personalized medicine.

  4. Genome Wide Methylome Alterations in Lung Cancer.

    Directory of Open Access Journals (Sweden)

    Nandita Mullapudi

    Full Text Available Aberrant cytosine 5-methylation underlies many deregulated elements of cancer. Among paired non-small cell lung cancers (NSCLC, we sought to profile DNA 5-methyl-cytosine features which may underlie genome-wide deregulation. In one of the more dense interrogations of the methylome, we sampled 1.2 million CpG sites from twenty-four NSCLC tumor (T-non-tumor (NT pairs using a methylation-sensitive restriction enzyme- based HELP-microarray assay. We found 225,350 differentially methylated (DM sites in adenocarcinomas versus adjacent non-tumor tissue that vary in frequency across genomic compartment, particularly notable in gene bodies (GB; p<2.2E-16. Further, when DM was coupled to differential transcriptome (DE in the same samples, 37,056 differential loci in adenocarcinoma emerged. Approximately 90% of the DM-DE relationships were non-canonical; for example, promoter DM associated with DE in the same direction. Of the canonical changes noted, promoter (PR DM loci with reciprocal changes in expression in adenocarcinomas included HBEGF, AGER, PTPRM, DPT, CST1, MELK; DM GB loci with concordant changes in expression included FOXM1, FERMT1, SLC7A5, and FAP genes. IPA analyses showed adenocarcinoma-specific promoter DMxDE overlay identified familiar lung cancer nodes [tP53, Akt] as well as less familiar nodes [HBEGF, NQO1, GRK5, VWF, HPGD, CDH5, CTNNAL1, PTPN13, DACH1, SMAD6, LAMA3, AR]. The unique findings from this study include the discovery of numerous candidate The unique findings from this study include the discovery of numerous candidate methylation sites in both PR and GB regions not previously identified in NSCLC, and many non-canonical relationships to gene expression. These DNA methylation features could potentially be developed as risk or diagnostic biomarkers, or as candidate targets for newer methylation locus-targeted preventive or therapeutic agents.

  5. Translating the cancer genome: Going beyond p values

    Energy Technology Data Exchange (ETDEWEB)

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

    2008-04-03

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

  6. Cancer genetic association studies in the genome-wide age

    OpenAIRE

    Savage, Sharon A

    2008-01-01

    Genome-wide association studies of hundreds of thousands of SNPs have led to a deluge of studies of genetic variation in cancer and other common diseases. Large case–control and cohort studies have identified novel SNPs as markers of cancer risk. Genome-wide association study SNP data have also advanced understanding of population-specific genetic variation. While studies of risk profiles, combinations of SNPs that may increase cancer risk, are not yet clinically applicable, future, large-sca...

  7. The breast cancer genome - a key for better oncology

    OpenAIRE

    Vollan Hans; Caldas Carlos

    2011-01-01

    Abstract Molecular classification has added important knowledge to breast cancer biology, but has yet to be implemented as a clinical standard. Full sequencing of breast cancer genomes could potentially refine classification and give a more complete picture of the mutational profile of cancer and thus aid therapy decisions. Future treatment guidelines must be based on the knowledge derived from histopathological sub-classification of tumors, but with added information from genomic signatures ...

  8. Collaborative Research to Advance Precision Medicine in the Post-Genomic World | Office of Cancer Genomics

    Science.gov (United States)

    My name is Subhashini Jagu, and I am the Scientific Program Manager for the Cancer Target Discovery and Development (CTD2) Network at the Office of Cancer Genomics (OCG). In my new role, I help CTD2 work toward its mission, which is to develop new scientific approaches to accelerate the translation of genomic discoveries into new treatments. Collaborative efforts that bring together a variety of expertise and infrastructure are needed to understand and successfully treat cancer, a highly complex disease.

  9. 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...... 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....

  10. Modeling the Human Genome Maintenance network

    Science.gov (United States)

    Simão, Éder M.; Cabral, Heleno B.; Castro, Mauro A. A.; Sinigaglia, Marialva; Mombach, José C. M.; Librelotto, Giovani R.

    2010-10-01

    We present the Ontocancro Database ( www.ontocancro.org) illustrated with applications to network modeling and pathway functional analysis. The database compiles information on gene pathways involved in Human Genome Maintenance Mechanisms (GMM) whose dysfunction accounts for cancer and several genetic syndromes. Ontocancro is the most complete, manually curated information resource available providing genomics and interatomics data on 120 GMM pathways (comprising a total of 1435 genes) obtained from curated databases and the literature. It was developed to facilitate the GMM network and functional modeling for the integration of genomic, transcriptomic and interatomic data. The database’s main contribution is the Ontocancro pathways that are expanded versions of standard GMM pathways for including additional genes with evidences of functional involvement in GMM. Using these pathways we find the largest cluster of interacting proteins involving GMM and on it we project a microarray study of adenoma to identify the regions of the network that are highly altered. In the last application we present the dynamical alterations of the pathways in a study of the effect of Cadmium, a known carcinogenic substance, on prostate cells to find that it produces a strong decrease of the pathway activity.

  11. Translational genomics in cancer research:converting proifles into personalized cancer medicine

    Institute of Scientific and Technical Information of China (English)

    Lalit Patel; Brittany Parker; Da Yang; Wei Zhang

    2013-01-01

    Cancer genomics is a rapidly growing discipline in which the genetic molecular basis of malignancy is studied at the scale of whole genomes. While the discipline has been successful with respect to identifying specific oncogenes and tumor suppressors involved in oncogenesis, it is also challenging our approach to managing patients suffering from this deadly disease. Speciifcally cancer genomics is driving clinical oncology to take a more molecular approach to diagnosis, prognostication, and treatment selection. We review here recent work undertaken in cancer genomics with an emphasis on translation of genomic ifndings. Finally, we discuss scientiifc challenges and research opportunities emerging from ifndings derived through analysis of tumors with high-depth sequencing.

  12. Cancer Genomics: Diversity and Disparity Across Ethnicity and Geography.

    Science.gov (United States)

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

    2016-01-01

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

  13. Contributions to Cancer Research: Finding a Niche in Communication | Office of Cancer Genomics

    Science.gov (United States)

    This past July, I started a journey into the fields of communications and cancer research when I joined the Office of Cancer Genomics (OCG) as a fellow in the National Cancer Institute (NCI) Health Communications Internship Program (HCIP). Cancer genomics and working in an office were new and uncharted territory for me: before I came to OCG, I was finishing a Ph.D. in cell biology at Vanderbilt University in Dr. Matthew Tyska’s laboratory.

  14. A microscopic landscape of the invasive breast cancer genome

    OpenAIRE

    Zheng Ping; Yuchao Xia; Tiansheng Shen; Vishwas Parekh; Siegal, Gene P; Isam-Eldin Eltoum; Jianbo He; Dongquan Chen; Minghua Deng; Ruibin Xi; Dejun Shen

    2016-01-01

    Histologic grade is one of the most important microscopic features used to predict the prognosis of invasive breast cancer and may serve as a marker for studying cancer driving genomic abnormalities in vivo. We analyzed whole genome sequencing data from 680 cases of TCGA invasive ductal carcinomas of the breast and correlated them to corresponding pathology information. Ten genetic abnormalities were found to be statistically associated with histologic grade, including three most prevalent ca...

  15. CRISPR-Cas9: A Revolutionary Tool for Cancer Modelling

    OpenAIRE

    Raul Torres-Ruiz; Sandra Rodriguez-Perales

    2015-01-01

    The cancer-modelling field is now experiencing a conversion with the recent emergence of the RNA-programmable CRISPR-Cas9 system, a flexible methodology to produce essentially any desired modification in the genome. Cancer is a multistep process that involves many genetic mutations and other genome rearrangements. Despite their importance, it is difficult to recapitulate the degree of genetic complexity found in patient tumors. The CRISPR-Cas9 system for genome editing has been proven as a ...

  16. Comprehensive genomic characterization of squamous cell lung cancers

    NARCIS (Netherlands)

    Hammerman, Peter S.; Lawrence, Michael S.; Voet, Douglas; Jing, Rui; Cibulskis, Kristian; Sivachenko, Andrey; Stojanov, Petar; McKenna, Aaron; Lander, Eric S.; Gabriel, Stacey; Getz, Gad; Sougnez, Carrie; Imielinski, Marcin; Helman, Elena; Hernandez, Bryan; Pho, Nam H.; Meyerson, Matthew; Chu, Andy; Chun, Hye-Jung E.; Mungall, Andrew J.; Pleasance, Erin; Robertson, A. Gordon; Sipahimalani, Payal; Stoll, Dominik; Balasundaram, Miruna; Birol, Inanc; Butterfield, Yaron S. N.; Chuah, Eric; Coope, Robin J. N.; Corbett, Richard; Dhalla, Noreen; Guin, Ranabir; Hirst, Anhe Carrie; Hirst, Martin; Holt, Robert A.; Lee, Darlene; Li, Haiyan I.; Mayo, Michael; Moore, Richard A.; Mungall, Karen; Nip, Ka Ming; Olshen, Adam; Schein, Jacqueline E.; Slobodan, Jared R.; Tam, Angela; Thiessen, Nina; Varhol, Richard; Zeng, Thomas; Zhao, Yongjun; Jones, Steven J. M.; Marra, Marco A.; Saksena, Gordon; Cherniack, Andrew D.; Schumacher, Stephen E.; Tabak, Barbara; Carter, Scott L.; Pho, Nam H.; Nguyen, Huy; Onofrio, Robert C.; Crenshaw, Andrew; Ardlie, Kristin; Beroukhim, Rameen; Winckler, Wendy; Hammerman, Peter S.; Getz, Gad; Meyerson, Matthew; Protopopov, Alexei; Zhang, Jianhua; Hadjipanayis, Angela; Lee, Semin; Xi, Ruibin; Yang, Lixing; Ren, Xiaojia; Zhang, Hailei; Shukla, Sachet; Chen, Peng-Chieh; Haseley, Psalm; Lee, Eunjung; Chin, Lynda; Park, Peter J.; Kucherlapati, Raju; Socci, Nicholas D.; Liang, Yupu; Schultz, Nikolaus; Borsu, Laetitia; Lash, Alex E.; Viale, Agnes; Sander, Chris; Ladanyi, Marc; Auman, J. Todd; Hoadley, Katherine A.; Wilkerson, Matthew D.; Shi, Yan; Liquori, Christina; Meng, Shaowu; Li, Ling; Turman, Yidi J.; Topal, Michael D.; Tan, Donghui; Waring, Scot; Buda, Elizabeth; Walsh, Jesse; Jones, Corbin D.; Mieczkowski, Piotr A.; Singh, Darshan; Wu, Junyuan; Gulabani, Anisha; Dolina, Peter; Bodenheimer, Tom; Hoyle, Alan P.; Simons, Janae V.; Soloway, Matthew G.; Mose, Lisle E.; Jefferys, Stuart R.; Balu, Saianand; O'Connor, Brian D.; Prins, Jan F.; Liu, Jinze; Chiang, Derek Y.; Hayes, D. Neil; Perou, Charles M.; Cope, Leslie; Danilova, Ludmila; Weisenberger, Daniel J.; Maglinte, Dennis T.; Pan, Fei; Van den Berg, David J.; Triche, Timothy; Herman, James G.; Baylin, Stephen B.; Laird, Peter W.; Getz, Gad; Noble, Michael; Voet, Doug; Saksena, Gordon; Gehlenborg, Nils; DiCara, Daniel; Zhang, Jinhua; Zhang, Hailei; Wu, Chang-Jiun; Liu, Spring Yingchun; Lawrence, Michael S.; Zou, Lihua; Sivachenko, Andrey; Lin, Pei; Stojanov, Petar; Jing, Rui; Cho, Juok; Nazaire, Marc-Danie; Robinson, Jim; Thorvaldsdottir, Helga; Mesirov, Jill; Park, Peter J.; Chin, Lynda; Schultz, Nikolaus; Sinha, Rileen; Ciriello, Giovanni; Cerami, Ethan; Gross, Benjamin; Jacobsen, Anders; Gao, Jianjiong; Aksoy, B. Arman; Weinhold, Nils; Ramirez, Ricardo; Taylor, Barry S.; Antipin, Yevgeniy; Reva, Boris; Shen, Ronglai; Mo, Qianxing; Seshan, Venkatraman; Paik, Paul K.; Ladanyi, Marc; Sander, Chris; Akbani, Rehan; Zhang, Nianxiang; Broom, Bradley M.; Casasent, Tod; Unruh, Anna; Wakefield, Chris; Cason, R. Craig; Baggerly, Keith A.; Weinstein, John N.; Haussler, David; Benz, Christopher C.; Stuart, Joshua M.; Zhu, Jingchun; Szeto, Christopher; Scott, Gary K.; Yau, Christina; Ng, Sam; Goldstein, Ted; Waltman, Peter; Sokolov, Artem; Ellrott, Kyle; Collisson, Eric A.; Zerbino, Daniel; Wilks, Christopher; Ma, Singer; Craft, Brian; Wilkerson, Matthew D.; Auman, J. Todd; Hoadley, Katherine A.; Du, Ying; Cabanski, Christopher; Walter, Vonn; Singh, Darshan; Wu, Junyuan; Gulabani, Anisha; Bodenheimer, Tom; Hoyle, Alan P.; Simons, Janae V.; Soloway, Matthew G.; Mose, Lisle E.; Jefferys, Stuart R.; Balu, Saianand; Marron, J. S.; Liu, Yufeng; Wang, Kai; Liu, Jinze; Prins, Jan F.; Hayes, D. Neil; Perou, Charles M.; Creighton, Chad J.; Zhang, Yiqun; Travis, William D.; Rekhtman, Natasha; Yi, Joanne; Aubry, Marie C.; Cheney, Richard; Dacic, Sanja; Flieder, Douglas; Funkhouser, William; Illei, Peter; Myers, Jerome; Tsao, Ming-Sound; Penny, Robert; Mallery, David; Shelton, Troy; Hatfield, Martha; Morris, Scott; Yena, Peggy; Shelton, Candace; Sherman, Mark; Paulauskis, Joseph; Meyerson, Matthew; Baylin, Stephen B.; Govindan, Ramaswamy; Akbani, Rehan; Azodo, Ijeoma; Beer, David; Bose, Ron; Byers, Lauren A.; Carbone, David; Chang, Li-Wei; Chiang, Derek; Chu, Andy; Chun, Elizabeth; Collisson, Eric; Cope, Leslie; Creighton, Chad J.; Danilova, Ludmila; Ding, Li; Getz, Gad; Hammerman, Peter S.; Hayes, D. Neil; Hernandez, Bryan; Herman, James G.; Heymach, John; Ida, Cristiane; Imielinski, Marcin; Johnson, Bruce; Jurisica, Igor; Kaufman, Jacob; Kosari, Farhad; Kucherlapati, Raju; Kwiatkowski, David; Ladanyi, Marc; Lawrence, Michael S.; Maher, Christopher A.; Mungall, Andy; Ng, Sam; Pao, William; Peifer, Martin; Penny, Robert; Robertson, Gordon; Rusch, Valerie; Sander, Chris; Schultz, Nikolaus; Shen, Ronglai; Siegfried, Jill; Sinha, Rileen; Sivachenko, Andrey; Sougnez, Carrie; Stoll, Dominik; Stuart, Joshua; Thomas, Roman K.; Tomaszek, Sandra; Tsao, Ming-Sound; Travis, William D.; Vaske, Charles; Weinstein, John N.; Weisenberger, Daniel; Wheeler, David; Wigle, Dennis A.; Wilkerson, Matthew D.; Wilks, Christopher; Yang, Ping; Zhang, Jianjua John; Jensen, Mark A.; Sfeir, Robert; Kahn, Ari B.; Chu, Anna L.; Kothiyal, Prachi; Wang, Zhining; Snyder, Eric E.; Pontius, Joan; Pihl, Todd D.; Ayala, Brenda; Backus, Mark; Walton, Jessica; Baboud, Julien; Berton, Dominique L.; Nicholls, Matthew C.; Srinivasan, Deepak; Raman, Rohini; Girshik, Stanley; Kigonya, Peter A.; Alonso, Shelley; Sanbhadti, Rashmi N.; Barletta, Sean P.; Greene, John M.; Pot, David A.; Tsao, Ming-Sound; Bandarchi-Chamkhaleh, Bizhan; Boyd, Jeff; Weaver, JoEllen; Wigle, Dennis A.; Azodo, Ijeoma A.; Tomaszek, Sandra C.; Aubry, Marie Christine; Ida, Christiane M.; Yang, Ping; Kosari, Farhad; Brock, Malcolm V.; Rogers, Kristen; Rutledge, Marian; Brown, Travis; Lee, Beverly; Shin, James; Trusty, Dante; Dhir, Rajiv; Siegfried, Jill M.; Potapova, Olga; Fedosenko, Konstantin V.; Nemirovich-Danchenko, Elena; Rusch, Valerie; Zakowski, Maureen; Iacocca, Mary V.; Brown, Jennifer; Rabeno, Brenda; Czerwinski, Christine; Petrelli, Nicholas; Fan, Zhen; Todaro, Nicole; Eckman, John; Myers, Jerome; Rathmell, W. Kimryn; Thorne, Leigh B.; Huang, Mei; Boice, Lori; Hill, Ashley; Penny, Robert; Mallery, David; Curley, Erin; Shelton, Candace; Yena, Peggy; Morrison, Carl; Gaudioso, Carmelo; Bartlett, Johnm. S.; Kodeeswaran, Sugy; Zanke, Brent; Sekhon, Harman; David, Kerstin; Juhl, Hartmut; Van Le, Xuan; Kohl, Bernard; Thorp, Richard; Tien, Nguyen Viet; Van Bang, Nguyen; Sussman, Howard; Phu, Bui Duc; Hajek, Richard; PhiHung, Nguyen; Khan, Khurram Z.; Muley, Thomas; Shaw, Kenna R. Mills; Sheth, Margi; Yang, Liming; Buetow, Ken; Davidsen, Tanja; Demchok, John A.; Eley, Greg; Ferguson, Martin; Dillon, Laura A. L.; Schaefer, Carl; Guyer, Mark S.; Ozenberger, Bradley A.; Palchik, Jacqueline D.; Peterson, Jane; Sofia, Heidi J.; Thomson, Elizabeth; Meyerson, Matthew

    2012-01-01

    Lung squamous cell carcinoma is a common type of lung cancer, causing approximately 400,000 deaths per year worldwide. Genomic alterations in squamous cell lung cancers have not been comprehensively characterized, and no molecularly targeted agents have been specifically developed for its treatment.

  17. ENDOCRINE TUMOURS: Advances in the molecular pathogenesis of thyroid cancer: lessons from the cancer genome.

    Science.gov (United States)

    Riesco-Eizaguirre, Garcilaso; Santisteban, Pilar

    2016-11-01

    Thyroid cancer is the most common endocrine malignancy giving rise to one of the most indolent solid cancers, but also one of the most lethal. In recent years, systematic studies of the cancer genome, most importantly those derived from The Cancer Genome Altas (TCGA), have catalogued aberrations in the DNA, chromatin, and RNA of the genomes of thousands of tumors relative to matched normal cellular genomes and have analyzed their epigenetic and protein consequences. Cancer genomics is therefore providing new information on cancer development and behavior, as well as new insights into genetic alterations and molecular pathways. From this genomic perspective, we will review the main advances concerning some essential aspects of the molecular pathogenesis of thyroid cancer such as mutational mechanisms, new cancer genes implicated in tumor initiation and progression, the role of non-coding RNA, and the advent of new susceptibility genes in thyroid cancer predisposition. This look across these genomic and cellular alterations results in the reshaping of the multistep development of thyroid tumors and offers new tools and opportunities for further research and clinical development of novel treatment strategies. PMID:27666535

  18. Minimal model for genome evolution and growth

    OpenAIRE

    Hsieh, L. C.; Luo, L. F.; Ji, F. M.; Lee, H C

    2002-01-01

    Textual analysis of typical microbial genomes reveals that they have the statistical characteristics of a DNA sequence of a much shorter length. This peculiar property supports an evolutionary model in which a genome evolves by random mutation but primarily grows by random segmental self-copying. That genomes grew mostly by self-copying is consistent with the observation that repeat sequences in all genomes are widespread and intragenomic and intergenomic homologous genes are preponderance ac...

  19. Exploring Cancer's Fractured Genomic Landscape: Searching for Cancer Drivers and Vulnerabilities in Somatic Copy Number Alterations

    OpenAIRE

    Zack, Travis Ian

    2014-01-01

    Somatic copy number alterations (SCNAs) are a class of alterations that lead to deviations from diploidy in developing and established tumors. A feature that distinguishes SCNAs from other alterations is their genomic footprint. The large genomic footprint of SCNAs in a typical cancer's genome presents both a challenge and an opportunity to find targetable vulnerabilities in cancer. Because a single event affects many genes, it is often challenging to identify the tumorigenic targets of SCNAs...

  20. The breast cancer genome - a key for better oncology

    Directory of Open Access Journals (Sweden)

    Vollan Hans

    2011-11-01

    Full Text Available Abstract Molecular classification has added important knowledge to breast cancer biology, but has yet to be implemented as a clinical standard. Full sequencing of breast cancer genomes could potentially refine classification and give a more complete picture of the mutational profile of cancer and thus aid therapy decisions. Future treatment guidelines must be based on the knowledge derived from histopathological sub-classification of tumors, but with added information from genomic signatures when properly clinically validated. The objective of this article is to give some background on molecular classification, the potential of next generation sequencing, and to outline how this information could be implemented in the clinic.

  1. Databases and Web Tools for Cancer Genomics Study

    Institute of Scientific and Technical Information of China (English)

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

    2015-01-01

    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 com-prehensiveness, 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.

  2. Genomics Study of Gastric Cancer and Its Molecular Subtypes.

    Science.gov (United States)

    Yuen, Siu Tsan; Leung, Suet Yi

    2016-01-01

    Gastric cancer is a heterogeneous disease encompassing diverse morphological (intestinal versus diffuse) and molecular subtypes (MSI, EBV, TP53 mutation). Recent advances in genomic technology have led to an improved understanding of the driver gene mutational profile, gene expression, and epigenetic alterations that underlie each of the subgroups, with therapeutic implications in some of these alterations. There have been attempts to classify gastric cancers based on these genomic features, with an aim to improve prognostication and predict responsiveness to specific drug therapy. The eventual aims of these genomic studies are to develop deep biological insights into the carcinogenic pathway in each of these subtypes. Future large-scale drug screening strategies may then be able to link these genomic features to drug responsiveness, eventually leading to genome-guided personalized medicine with improved cure rates. PMID:27573784

  3. Genome Science and Personalized Cancer Treatment (LBNL Summer Lecture Series)

    Energy Technology Data Exchange (ETDEWEB)

    Gray, Joe

    2009-08-04

    Summer Lecture Series 2009: Results from the Human Genome Project are enabling scientists to understand how individual cancers form and progress. This information, when combined with newly developed drugs, can optimize the treatment of individual cancers. Joe Gray, director of Berkeley Labs Life Sciences Division and Associate Laboratory Director for Life and Environmental Sciences, will focus on this approach, its promise, and its current roadblocks — particularly with regard to breast cancer.

  4. Methods for detection of subtle mutations in cancer genomes

    DEFF Research Database (Denmark)

    Dahl, Christina; Ralfkiaer, Ulrik; Guldberg, Per

    2006-01-01

    With the realization that cancer is a genetic disease, detection of mutations in genomic DNA has become an important discipline in many areas of cancer research. Although the publication of the human genome sequence and the immense technological advancements have facilitated the analysis of cancer...... genomes, detection of mutations in tumor specimens may still be challenging and fraught with technical problems. In this review, we describe current technologies for detection of small DNA mutations, including mutation scanning techniques to search for unknown mutations, and diagnostic techniques...... to detect known cancer mutations. We outline the principles of the different techniques and discuss their advantages and limitations. We also discuss critical issues that must be considered before choosing methodology, including sensitivity, specificity, limit of detection, throughput and cost, quantity...

  5. An emerging place for lung cancer genomics in 2013.

    Science.gov (United States)

    Daniels, Marissa G; Bowman, Rayleen V; Yang, Ian A; Govindan, Ramaswamy; Fong, Kwun M

    2013-10-01

    Lung cancer is a disease with a dismal prognosis and is the biggest cause of cancer deaths in many countries. Nonetheless, rapid technological developments in genome science promise more effective prevention and treatment strategies. Since the Human Genome Project, scientific advances have revolutionized the diagnosis and treatment of human cancers, including thoracic cancers. The latest, massively parallel, next generation sequencing (NGS) technologies offer much greater sequencing capacity than traditional, capillary-based Sanger sequencing. These modern but costly technologies have been applied to whole genome-, and whole exome sequencing (WGS and WES) for the discovery of mutations and polymorphisms, transcriptome sequencing for quantification of gene expression, small ribonucleic acid (RNA) sequencing for microRNA profiling, large scale analysis of deoxyribonucleic acid (DNA) methylation and chromatin immunoprecipitation mapping of DNA-protein interaction. With the rise of personalized cancer care, based on the premise of precision medicine, sequencing technologies are constantly changing. To date, the genomic landscape of lung cancer has been captured in several WGS projects. Such work has not only contributed to our understanding of cancer biology, but has also provided impetus for technical advances that may improve our ability to accurately capture the cancer genome. Issues such as short read lengths contribute to sequenced libraries that contain challenging gaps in the aligned genome. Emerging platforms promise longer reads as well as the ability to capture a range of epigenomic signals. In addition, ongoing optimization of bioinformatics strategies for data analysis and interpretation are critical, especially for the differentiation between driver and passenger mutations. Moreover, broader deployment of these and future generations of platforms, coupled with an increasing bioinformatics workforce with access to highly sophisticated technologies, could

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

    Directory of Open Access Journals (Sweden)

    Davies Jonathan J

    2006-12-01

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

  7. The Genomic Landscape and Clinical Relevance of A-to-I RNA Editing in Human Cancers | Office of Cancer Genomics

    Science.gov (United States)

    Adenosine-to-inosine (A-to-I) RNA editing is a widespread post-transcriptional mechanism, but its genomic landscape and clinical relevance in cancer have not been investigated systematically. We characterized the global A-to-I RNA editing profiles of 6,236 patient samples of 17 cancer types from The Cancer Genome Atlas and revealed a striking diversity of altered RNA-editing patterns in tumors relative to normal tissues. We identified an appreciable number of clinically relevant editing events, many of which are in noncoding regions.

  8. Cancer Therapy Evaluation Program | Office of Cancer Genomics

    Science.gov (United States)

    The Cancer Therapy Evaluation Program (CTEP) seeks to improve the lives of cancer patients by finding better treatments, control mechanisms, and cures for cancer. CTEP funds a national program of cancer research, sponsoring clinical trials to evaluate new anti-cancer agents.

  9. Plantagora: modeling whole genome sequencing and assembly of plant genomes.

    Directory of Open Access Journals (Sweden)

    Roger Barthelson

    Full Text Available BACKGROUND: Genomics studies are being revolutionized by the next generation sequencing technologies, which have made whole genome sequencing much more accessible to the average researcher. Whole genome sequencing with the new technologies is a developing art that, despite the large volumes of data that can be produced, may still fail to provide a clear and thorough map of a genome. The Plantagora project was conceived to address specifically the gap between having the technical tools for genome sequencing and knowing precisely the best way to use them. METHODOLOGY/PRINCIPAL FINDINGS: For Plantagora, a platform was created for generating simulated reads from several different plant genomes of different sizes. The resulting read files mimicked either 454 or Illumina reads, with varying paired end spacing. Thousands of datasets of reads were created, most derived from our primary model genome, rice chromosome one. All reads were assembled with different software assemblers, including Newbler, Abyss, and SOAPdenovo, and the resulting assemblies were evaluated by an extensive battery of metrics chosen for these studies. The metrics included both statistics of the assembly sequences and fidelity-related measures derived by alignment of the assemblies to the original genome source for the reads. The results were presented in a website, which includes a data graphing tool, all created to help the user compare rapidly the feasibility and effectiveness of different sequencing and assembly strategies prior to testing an approach in the lab. Some of our own conclusions regarding the different strategies were also recorded on the website. CONCLUSIONS/SIGNIFICANCE: Plantagora provides a substantial body of information for comparing different approaches to sequencing a plant genome, and some conclusions regarding some of the specific approaches. Plantagora also provides a platform of metrics and tools for studying the process of sequencing and assembly

  10. 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.

  11. Endoplasmic Reticulum Stress, Genome Damage, and Cancer

    OpenAIRE

    Dicks, Naomi; Gutierrez, Karina; Michalak, Marek; Bordignon, Vilceu; Agellon, Luis B.

    2015-01-01

    Endoplasmic reticulum (ER) stress has been linked to many diseases, including cancer. A large body of work has focused on the activation of the ER stress response in cancer cells to facilitate their survival and tumor growth; however, there are some studies suggesting that the ER stress response can also mitigate cancer progression. Despite these contradictions, it is clear that the ER stress response is closely associated with cancer biology. The ER stress response classically encompasses ac...

  12. Endoplasmic reticulum stress, genome damage and cancer

    OpenAIRE

    Naomi eDicks; Karina eGutierrez; Marek eMichalak; Vilceu eBordignon; Agellon, Luis B.

    2015-01-01

    Endoplasmic reticulum (ER) stress has been linked to many diseases, including cancer. A large body of work has focused on the activation of the ER stress response in cancer cells to facilitate their survival and tumor growth, however, there are some studies suggesting that the ER stress response can also mitigate cancer progression. Despite these contradictions, it is clear that the ER stress response is closely associated with cancer biology. The ER stress response classically encompasses ...

  13. The evolving role of cancer cell line-based screens to define the impact of cancer genomes on drug response ?

    OpenAIRE

    Garnett, Mathew J.; McDermott, Ultan

    2014-01-01

    Over the last decade we have witnessed the convergence of two powerful experimental designs toward a common goal of defining the molecular subtypes that underpin the likelihood of a cancer patient responding to treatment in the clinic. The first of these ‘experiments’ has been the systematic sequencing of large numbers of cancer genomes through the International Cancer Genome Consortium and The Cancer Genome Atlas. This endeavour is beginning to yield a complete catalogue of the cancer genes ...

  14. Pancreatic cancer genomes reveal aberrations in axon guidance pathway genes.

    Science.gov (United States)

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

    2012-11-15

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

  15. Minimal model for genome evolution and growth

    CERN Document Server

    Hsieh, L C; Ji, F M; Lee, H C

    2002-01-01

    Textual analysis of typical microbial genomes reveals that they have the statistical characteristics of a DNA sequence of a much shorter length. This peculiar property supports an evolutionary model in which a genome evolves by random mutation but primarily grows by random segmental self-copying. That genomes grew mostly by self-copying is consistent with the observation that repeat sequences in all genomes are widespread and intragenomic and intergenomic homologous genes are preponderance across all life forms. The model predicates the coexistence of the two competing modes of evolution: the gradual changes of classical Darwinism and the stochastic spurts envisioned in ``punctuated equilibrium''.

  16. Genomic diversity of colorectal cancer: Changing landscape and emerging targets.

    Science.gov (United States)

    Ahn, Daniel H; Ciombor, Kristen K; Mikhail, Sameh; Bekaii-Saab, Tanios

    2016-07-01

    Improvements in screening and preventive measures have led to an increased detection of early stage colorectal cancers (CRC) where patients undergo treatment with a curative intent. Despite these efforts, a high proportion of patients are diagnosed with advanced stage disease that is associated with poor outcomes, as CRC remains one of the leading causes of cancer-related deaths in the world. The development of next generation sequencing and collaborative multi-institutional efforts to characterize the cancer genome has afforded us with a comprehensive assessment of the genomic makeup present in CRC. This knowledge has translated into understanding the prognostic role of various tumor somatic variants in this disease. Additionally, the awareness of the genomic alterations present in CRC has resulted in an improvement in patient outcomes, largely due to better selection of personalized therapies based on an individual's tumor genomic makeup. The benefit of various treatments is often limited, where recent studies assessing the genomic diversity in CRC have identified the development of secondary tumor somatic variants that likely contribute to acquired treatment resistance. These studies have begun to alter the landscape of treatment for CRC that include investigating novel targeted therapies, assessing the role of immunotherapy and prospective, dynamic assessment of changes in tumor genomic alterations that occur during the treatment of CRC. PMID:27433082

  17. Genomic diversity of colorectal cancer: Changing landscape and emerging targets

    Science.gov (United States)

    Ahn, Daniel H; Ciombor, Kristen K; Mikhail, Sameh; Bekaii-Saab, Tanios

    2016-01-01

    Improvements in screening and preventive measures have led to an increased detection of early stage colorectal cancers (CRC) where patients undergo treatment with a curative intent. Despite these efforts, a high proportion of patients are diagnosed with advanced stage disease that is associated with poor outcomes, as CRC remains one of the leading causes of cancer-related deaths in the world. The development of next generation sequencing and collaborative multi-institutional efforts to characterize the cancer genome has afforded us with a comprehensive assessment of the genomic makeup present in CRC. This knowledge has translated into understanding the prognostic role of various tumor somatic variants in this disease. Additionally, the awareness of the genomic alterations present in CRC has resulted in an improvement in patient outcomes, largely due to better selection of personalized therapies based on an individual’s tumor genomic makeup. The benefit of various treatments is often limited, where recent studies assessing the genomic diversity in CRC have identified the development of secondary tumor somatic variants that likely contribute to acquired treatment resistance. These studies have begun to alter the landscape of treatment for CRC that include investigating novel targeted therapies, assessing the role of immunotherapy and prospective, dynamic assessment of changes in tumor genomic alterations that occur during the treatment of CRC. PMID:27433082

  18. Genomic diversity of colorectal cancer: Changing landscape and emerging targets.

    Science.gov (United States)

    Ahn, Daniel H; Ciombor, Kristen K; Mikhail, Sameh; Bekaii-Saab, Tanios

    2016-07-01

    Improvements in screening and preventive measures have led to an increased detection of early stage colorectal cancers (CRC) where patients undergo treatment with a curative intent. Despite these efforts, a high proportion of patients are diagnosed with advanced stage disease that is associated with poor outcomes, as CRC remains one of the leading causes of cancer-related deaths in the world. The development of next generation sequencing and collaborative multi-institutional efforts to characterize the cancer genome has afforded us with a comprehensive assessment of the genomic makeup present in CRC. This knowledge has translated into understanding the prognostic role of various tumor somatic variants in this disease. Additionally, the awareness of the genomic alterations present in CRC has resulted in an improvement in patient outcomes, largely due to better selection of personalized therapies based on an individual's tumor genomic makeup. The benefit of various treatments is often limited, where recent studies assessing the genomic diversity in CRC have identified the development of secondary tumor somatic variants that likely contribute to acquired treatment resistance. These studies have begun to alter the landscape of treatment for CRC that include investigating novel targeted therapies, assessing the role of immunotherapy and prospective, dynamic assessment of changes in tumor genomic alterations that occur during the treatment of CRC.

  19. Comprehensive genomic profiles of small cell lung cancer

    OpenAIRE

    George, J.; Lim, J; JANG, S.; Cun, Y.; Ozretic, L.; Kong, G.; Leenders, F.; Lu, X.; Fernandez-Cuesta, L.; Bosco, G.; Müller, C.(Dr. Remeis-Sternwarte and ECAP, Universität Erlangen-Nürnberg, Sternwartstr. 7, 96049 , Bamberg, Germany); Dahmen, I.; Jahchan, N.; K. Park; D. Yang

    2015-01-01

    We have sequenced the genomes of 110 small cell lung cancers (SCLC), one of the deadliest human cancers. In nearly all the tumours analysed we found bi-allelic inactivation of TP53 and RB1, sometimes by complex genomic rearrangements. Two tumours with wild-type RB1 had evidence of chromothripsis leading to overexpression of cyclin D1 (encoded by the CCND1 gene), revealing an alternative mechanism of Rb1 deregulation. Thus, loss of the tumour suppressors TP53 and RB1 is obligatory in SCLC. We ...

  20. Genomic analysis and selected molecular pathways in rare cancers

    International Nuclear Information System (INIS)

    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)

  1. Modeling the Aneuploidy Control of Cancer

    Directory of Open Access Journals (Sweden)

    Wang Zhong

    2010-07-01

    Full Text Available Abstract Background Aneuploidy has long been recognized to be associated with cancer. A growing body of evidence suggests that tumorigenesis, the formation of new tumors, can be attributed to some extent to errors occurring at the mitotic checkpoint, a major cell cycle control mechanism that acts to prevent chromosome missegregation. However, so far no statistical model has been available quantify the role aneuploidy plays in determining cancer. Methods We develop a statistical model for testing the association between aneuploidy loci and cancer risk in a genome-wide association study. The model incorporates quantitative genetic principles into a mixture-model framework in which various genetic effects, including additive, dominant, imprinting, and their interactions, are estimated by implementing the EM algorithm. Results Under the new model, a series of hypotheses tests are formulated to explain the pattern of the genetic control of cancer through aneuploid loci. Simulation studies were performed to investigate the statistical behavior of the model. Conclusions The model will provide a tool for estimating the effects of genetic loci on aneuploidy abnormality in genome-wide studies of cancer cells.

  2. Whole-genome sequencing identifies genomic heterogeneity at a nucleotide and chromosomal level in bladder cancer

    Science.gov (United States)

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

    2014-01-01

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

  3. A Health Services Research Agenda for Cellular, Molecular and Genomic Technologies in Cancer Care

    Science.gov (United States)

    Wideroff, Louise; Phillips, Kathryn A.; Randhawa, Gurvaneet; Ambs, Anita; Armstrong, Katrina; Bennett, Charles L.; Brown, Martin L.; Donaldson, Molla S.; Follen, Michele; Goldie, Sue J.; Hiatt, Robert A.; Khoury, Muin J.; Lewis, Graham; McLeod, Howard L.; Piper, Margaret; Powell, Isaac; Schrag, Deborah; Schulman, Kevin A.; Scott, Joan

    2009-01-01

    Background In recent decades, extensive resources have been invested to develop cellular, molecular and genomic technologies with clinical applications that span the continuum of cancer care. Methods In December 2006, the National Cancer Institute sponsored the first workshop to uniquely examine the state of health services research on cancer-related cellular, molecular and genomic technologies and identify challenges and priorities for expanding the evidence base on their effectiveness in routine care. Results This article summarizes the workshop outcomes, which included development of a comprehensive research agenda that incorporates health and safety endpoints, utilization patterns, patient and provider preferences, quality of care and access, disparities, economics and decision modeling, trends in cancer outcomes, and health-related quality of life among target populations. Conclusions Ultimately, the successful adoption of useful technologies will depend on understanding and influencing the patient, provider, health care system and societal factors that contribute to their uptake and effectiveness in ‘real-world’ settings. PMID:19367091

  4. Cancer in Children and Adolescents | Office of Cancer Genomics

    Science.gov (United States)

    View a fact sheet that has statistics as well as information about types, causes, and treatments of cancers in children and adolescents in the United States.  http://www.cancer.gov/cancertopics/factsheet/Sites-Types/childhood

  5. Multiscale modeling of three-dimensional genome

    Science.gov (United States)

    Zhang, Bin; Wolynes, Peter

    The genome, the blueprint of life, contains nearly all the information needed to build and maintain an entire organism. A comprehensive understanding of the genome is of paramount interest to human health and will advance progress in many areas, including life sciences, medicine, and biotechnology. The overarching goal of my research is to understand the structure-dynamics-function relationships of the human genome. In this talk, I will be presenting our efforts in moving towards that goal, with a particular emphasis on studying the three-dimensional organization, the structure of the genome with multi-scale approaches. Specifically, I will discuss the reconstruction of genome structures at both interphase and metaphase by making use of data from chromosome conformation capture experiments. Computationally modeling of chromatin fiber at atomistic level from first principles will also be presented as our effort for studying the genome structure from bottom up.

  6. Genome-wide sequencing to identify the cause of hereditary cancer syndromes: with examples from familial pancreatic cancer

    OpenAIRE

    Roberts, Nicholas J.; Klein, Alison P.

    2012-01-01

    Advances in our understanding of the human genome and next-generation technologies have facilitated the use of genome-wide sequencing to decipher the genetic basis of Mendelian disease and hereditary cancer syndromes. The application of genome-wide sequencing in hereditary cancer syndromes has had mixed success, in part, due to complex nature of the underlying genetic architecture. In this review we discuss the use of genome-wide sequencing in both Mendelian diseases and hereditary cancer syn...

  7. Context Sensitive Modeling of Cancer Drug Sensitivity

    Science.gov (United States)

    Chen, Bo-Juen; Litvin, Oren; Ungar, Lyle; Pe’er, Dana

    2015-01-01

    Recent screening of drug sensitivity in large panels of cancer cell lines provides a valuable resource towards developing algorithms that predict drug response. Since more samples provide increased statistical power, most approaches to prediction of drug sensitivity pool multiple cancer types together without distinction. However, pan-cancer results can be misleading due to the confounding effects of tissues or cancer subtypes. On the other hand, independent analysis for each cancer-type is hampered by small sample size. To balance this trade-off, we present CHER (Contextual Heterogeneity Enabled Regression), an algorithm that builds predictive models for drug sensitivity by selecting predictive genomic features and deciding which ones should—and should not—be shared across different cancers, tissues and drugs. CHER provides significantly more accurate models of drug sensitivity than comparable elastic-net-based models. Moreover, CHER provides better insight into the underlying biological processes by finding a sparse set of shared and type-specific genomic features. PMID:26274927

  8. Context Sensitive Modeling of Cancer Drug Sensitivity.

    Directory of Open Access Journals (Sweden)

    Bo-Juen Chen

    Full Text Available Recent screening of drug sensitivity in large panels of cancer cell lines provides a valuable resource towards developing algorithms that predict drug response. Since more samples provide increased statistical power, most approaches to prediction of drug sensitivity pool multiple cancer types together without distinction. However, pan-cancer results can be misleading due to the confounding effects of tissues or cancer subtypes. On the other hand, independent analysis for each cancer-type is hampered by small sample size. To balance this trade-off, we present CHER (Contextual Heterogeneity Enabled Regression, an algorithm that builds predictive models for drug sensitivity by selecting predictive genomic features and deciding which ones should-and should not-be shared across different cancers, tissues and drugs. CHER provides significantly more accurate models of drug sensitivity than comparable elastic-net-based models. Moreover, CHER provides better insight into the underlying biological processes by finding a sparse set of shared and type-specific genomic features.

  9. National Cancer Moonshot Initiative platform | Office of Cancer Genomics

    Science.gov (United States)

    As part of the Vice President’s National Cancer Moonshot Initiative, the National Cancer Institute has launched an online engagement platform to enable the research community and the public to submit cancer research ideas to a Blue Ribbon Panel of scientific experts. Any member of the public is encouraged to submit his or her ideas for reducing the incidence of cancer and developing better ways to prevent, treat, and cure all types of cancer. Research ideas may be submitted in the following areas:

  10. Cancer genomics: why rare is valuable.

    Science.gov (United States)

    Jamshidi, Farzad; Nielsen, Torsten O; Huntsman, David G

    2015-04-01

    Rare conditions are sometimes ignored in biomedical research because of difficulties in obtaining specimens and limited interest from fund raisers. However, the study of rare diseases such as unusual cancers has again and again led to breakthroughs in our understanding of more common diseases. It is therefore unsurprising that with the development and accessibility of next-generation sequencing, much has been learnt from studying cancers that are rare and in particular those with uniform biological and clinical behavior. Herein, we describe how shotgun sequencing of cancers such as granulosa cell tumor, endometrial stromal sarcoma, epithelioid hemangioendothelioma, ameloblastoma, small-cell carcinoma of the ovary, clear-cell carcinoma of the ovary, nonepithelial ovarian tumors, chondroblastoma, and giant cell tumor of the bone has led to rapidly translatable discoveries in diagnostics and tumor taxonomies, as well as providing insights into cancer biology. PMID:25676695

  11. Highlights from the prostate cancer genome report

    Institute of Scientific and Technical Information of China (English)

    Shyh-Han Tan; Gyorgy Petrovics; Shiv Srivastava

    2011-01-01

    @@ Prostate cancer (Cap) is the second most frequently diagnosed cancer of men worldwide (899 000 new cases,13.6% of the total),with nearly 75% of the registered cases occurring in developed countries (644000 cases).1 Blood prostate-specific antigen test has revolutionized the early detection of Cap and organ-confined Cap is effectively managed by state-of-the-art treatments including radical prostatectomy or radiation therapy.2 In the past decade,tremendous progress has also been made in our understanding of the biology and common genomicalterations in Cap 3.4 New molecular marker assays have promise in improving CaP diagnosis.Despite these advances,major challenges remain with our ability to distinguish indolent cancers from the more aggressive cancers detected early due to widely used prostate-specific antigen test.Furthermore,development of molecular stratification of CaP for targeted and more effective therapies is critically needed.

  12. Genomic Predictors of Outcome in Prostate Cancer

    NARCIS (Netherlands)

    Bostrom, P.J.; Bjartell, A.S.; Catto, J.W.; Eggener, S.E.; Lilja, H.; Loeb, S.; Schalken, J.A.; Schlomm, T.; Cooperberg, M.R.

    2015-01-01

    CONTEXT: Given the highly variable behavior and clinical course of prostate cancer (PCa) and the multiple available treatment options, a personalized approach to oncologic risk stratification is important. Novel genetic approaches offer additional information to improve clinical decision making. OBJ

  13. 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.

  14. Significance of duon mutations in cancer genomes

    OpenAIRE

    Vinod Kumar Yadav; Smith, Kyle S.; Colin Flinders; Mumenthaler, Shannon M.; De, Subhajyoti

    2016-01-01

    Functional mutations in coding regions not only affect the structure and function of the protein products, but may also modulate their expression in some cases. This class of mutations, recently dubbed “duon mutations” due to their dual roles, can potentially have major impacts on downstream pathways. However their significance in diseases such as cancer remain unclear. In a survey covering 4606 samples from 19 cancer types, and integrating allelic expression, overall mRNA expression, regulat...

  15. 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.

  16. In situ quantification of genomic instability in breast cancer progression

    Energy Technology Data Exchange (ETDEWEB)

    Ortiz de Solorzano, Carlos; Chin, Koei; Gray, Joe W.; Lockett, Stephen J.

    2003-05-15

    Genomic instability is a hallmark of breast and other solid cancers. Presumably caused by critical telomere reduction, GI is responsible for providing the genetic diversity required in the multi-step progression of the disease. We have used multicolor fluorescence in situ hybridization and 3D image analysis to quantify genomic instability cell-by-cell in thick, intact tissue sections of normal breast epithelium, preneoplastic lesions (usual ductal hyperplasia), ductal carcinona is situ or invasive carcinoma of the breast. Our in situ-cell by cell-analysis of genomic instability shows an important increase of genomic instability in the transition from hyperplasia to in situ carcinoma, followed by a reduction of instability in invasive carcinoma. This pattern suggests that the transition from hyperplasia to in situ carcinoma corresponds to telomere crisis and invasive carcinoma is a consequence of telomerase reactivation afertelomere crisis.

  17. Targeted or whole genome sequencing of formalin fixed tissue samples: potential applications in cancer genomics.

    Science.gov (United States)

    Munchel, Sarah; Hoang, Yen; Zhao, Yue; Cottrell, Joseph; Klotzle, Brandy; Godwin, Andrew K; Koestler, Devin; Beyerlein, Peter; Fan, Jian-Bing; Bibikova, Marina; Chien, Jeremy

    2015-09-22

    Current genomic studies are limited by the poor availability of fresh-frozen tissue samples. Although formalin-fixed diagnostic samples are in abundance, they are seldom used in current genomic studies because of the concern of formalin-fixation artifacts. Better characterization of these artifacts will allow the use of archived clinical specimens in translational and clinical research studies. To provide a systematic analysis of formalin-fixation artifacts on Illumina sequencing, we generated 26 DNA sequencing data sets from 13 pairs of matched formalin-fixed paraffin-embedded (FFPE) and fresh-frozen (FF) tissue samples. The results indicate high rate of concordant calls between matched FF/FFPE pairs at reference and variant positions in three commonly used sequencing approaches (whole genome, whole exome, and targeted exon sequencing). Global mismatch rates and C · G > T · A substitutions were comparable between matched FF/FFPE samples, and discordant rates were low (<0.26%) in all samples. Finally, low-pass whole genome sequencing produces similar pattern of copy number alterations between FF/FFPE pairs. The results from our studies suggest the potential use of diagnostic FFPE samples for cancer genomic studies to characterize and catalog variations in cancer genomes. PMID:26305677

  18. Mouse models of colorectal cancer

    Institute of Scientific and Technical Information of China (English)

    Yunguang Tong; Wancai Yang; H. Phillip Koeffler

    2011-01-01

    Colorectal cancer is one of the most common malignancies in the world. Many mouse models have been developed to evaluate features of colorectal cancer in humans. These can be grouped into genetically-engineered, chemically-induced, and inoculated models. However, none recapitulates all of the characteristics of human colorectal cancer. It is critical to use a specific mouse model to address a particular research question. Here, we review commonly used mouse models for human colorectal cancer.

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

    Directory of Open Access Journals (Sweden)

    Shinya Akatsuka

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

  20. Significance of duon mutations in cancer genomes

    Science.gov (United States)

    Yadav, Vinod Kumar; Smith, Kyle S.; Flinders, Colin; Mumenthaler, Shannon M.; de, Subhajyoti

    2016-06-01

    Functional mutations in coding regions not only affect the structure and function of the protein products, but may also modulate their expression in some cases. This class of mutations, recently dubbed “duon mutations” due to their dual roles, can potentially have major impacts on downstream pathways. However their significance in diseases such as cancer remain unclear. In a survey covering 4606 samples from 19 cancer types, and integrating allelic expression, overall mRNA expression, regulatory motif perturbation, and chromatin signatures in one composite index called REDACT score, we identified potential duon mutations. Several such mutations are detected in known cancer genes in multiple cancer types. For instance a potential duon mutation in TP53 is associated with increased expression of the mutant allelic gene copy, thereby possibly amplifying the functional effects on the downstream pathways. Another potential duon mutation in SF3B1 is associated with abnormal splicing and changes in angiogenesis and matrix degradation related pathways. Our findings emphasize the need to interrogate the mutations in coding regions beyond their obvious effects on protein structures.

  1. Integrated genomic analysis of breast cancers.

    Science.gov (United States)

    Addou-Klouche, L; Adélaïde, J; Cornen, S; Bekhouche, I; Finetti, P; Guille, A; Sircoulomb, F; Raynaud, S; Bertucci, F; Birnbaum, D; Chaffanet, M

    2012-12-01

    Breast cancer is the most frequent and the most deadly cancer in women in Western countries. Different classifications of disease (anatomoclinical, pathological, prognostic, genetic) are used for guiding the management of patients. Unfortunately, they fail to reflect the whole clinical heterogeneity of the disease. Consequently, molecularly distinct diseases are grouped in similar clinical classes, likely explaining the different clinical outcome between patients in a given class, and the fact that selection of the most appropriate diagnostic or therapeutic strategy for each patient is not done accurately. Today, treatment is efficient in only 70.0-75.0% of cases overall. Our repertoire of efficient drugs is limited but is being expanded with the discovery of new molecular targets for new drugs, based on the identification of candidate oncogenes and tumor suppressor genes (TSG) functionally relevant in disease. Development of new drugs makes therapeutical decisions even more demanding of reliable classifiers and prognostic/predictive tests. Breast cancer is a complex, heterogeneous disease at the molecular level. The combinatorial molecular origin and the heterogeneity of malignant cells, and the variability of the host background, create distinct subgroups of tumors endowed with different phenotypic features such as response to therapy and clinical outcome. Cellular and molecular analyses can identify new classes biologically and clinically relevant, as well as provide new clinically relevant markers and targets. The various stages of mammary tumorigenesis are not clearly defined and the genetic and epigenetic events critical to the development and aggressiveness of breast cancer are not precisely known. Because the phenotype of tumors is dependent on many genes, a large-scale and integrated molecular characterization of the genetic and epigenetic alterations and gene expression deregulation should allow the identification of new molecular classes clinically

  2. Median Approximations for Genomes Modeled as Matrices.

    Science.gov (United States)

    Zanetti, Joao Paulo Pereira; Biller, Priscila; Meidanis, Joao

    2016-04-01

    The genome median problem is an important problem in phylogenetic reconstruction under rearrangement models. It can be stated as follows: Given three genomes, find a fourth that minimizes the sum of the pairwise rearrangement distances between it and the three input genomes. In this paper, we model genomes as matrices and study the matrix median problem using the rank distance. It is known that, for any metric distance, at least one of the corners is a [Formula: see text]-approximation of the median. Our results allow us to compute up to three additional matrix median candidates, all of them with approximation ratios at least as good as the best corner, when the input matrices come from genomes. We also show a class of instances where our candidates are optimal. From the application point of view, it is usually more interesting to locate medians farther from the corners, and therefore, these new candidates are potentially more useful. In addition to the approximation algorithm, we suggest a heuristic to get a genome from an arbitrary square matrix. This is useful to translate the results of our median approximation algorithm back to genomes, and it has good results in our tests. To assess the relevance of our approach in the biological context, we ran simulated evolution tests and compared our solutions to those of an exact DCJ median solver. The results show that our method is capable of producing very good candidates. PMID:27072561

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

    OpenAIRE

    Silverstein, Allison; Sood, Rachita; Costas-Chavarri, Ainhoa

    2016-01-01

    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 ...

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

    Directory of Open Access Journals (Sweden)

    Rachael Natrajan

    2016-02-01

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

  5. New frontiers in translational control of the cancer genome.

    Science.gov (United States)

    Truitt, Morgan L; Ruggero, Davide

    2016-04-26

    The past several years have seen dramatic leaps in our understanding of how gene expression is rewired at the translation level during tumorigenesis to support the transformed phenotype. This work has been driven by an explosion in technological advances and is revealing previously unimagined regulatory mechanisms that dictate functional expression of the cancer genome. In this Review we discuss emerging trends and exciting new discoveries that reveal how this translational circuitry contributes to specific aspects of tumorigenesis and cancer cell function, with a particular focus on recent insights into the role of translational control in the adaptive response to oncogenic stress conditions. PMID:27112207

  6. Animal Models of Colorectal Cancer

    Science.gov (United States)

    Johnson, Robert L.; Fleet, James C.

    2012-01-01

    Colorectal cancer is a heterogeneous disease that afflicts a large number of people in the United States. The use of animal models has the potential to increase our understanding of carcinogenesis, tumor biology, and the impact of specific molecular events on colon biology. In addition, animal models with features of specific human colorectal cancers can be used to test strategies for cancer prevention and treatment. In this review we provide an overview of the mechanisms driving human cancer, we discuss the approaches one can take to model colon cancer in animals, and we describe a number of specific animal models that have been developed for the study of colon cancer. We believe that there are many valuable animal models to study various aspects of human colorectal cancer. However, opportunities for improving upon these models exist. PMID:23076650

  7. Advances in Swine Biomedical Model Genomics

    Directory of Open Access Journals (Sweden)

    Joan K. Lunney

    2007-01-01

    Full Text Available This review is a short update on the diversity of swine biomedical models and the importance of genomics in their continued development. The swine has been used as a major mammalian model for human studies because of the similarity in size and physiology, and in organ development and disease progression. The pig model allows for deliberately timed studies, imaging of internal vessels and organs using standard human technologies, and collection of repeated peripheral samples and, at kill, detailed mucosal tissues. The ability to use pigs from the same litter, or cloned or transgenic pigs, facilitates comparative analyses and genetic mapping. The availability of numerous well defined cell lines, representing a broad range of tissues, further facilitates testing of gene expression, drug susceptibility, etc. Thus the pig is an excellent biomedical model for humans. For genomic applications it is an asset that the pig genome has high sequence and chromosome structure homology with humans. With the swine genome sequence now well advanced there are improving genetic and proteomic tools for these comparative analyses. The review will discuss some of the genomic approaches used to probe these models. The review will highlight genomic studies of melanoma and of infectious disease resistance, discussing issues to consider in designing such studies. It will end with a short discussion of the potential for genomic approaches to develop new alternatives for control of the most economically important disease of pigs, porcine reproductive and respiratory syndrome (PRRS, and the potential for applying knowledge gained with this virus for human viral infectious disease studies.

  8. Genome-wide sequencing to identify the cause of hereditary cancer syndromes: with examples from familial pancreatic cancer.

    Science.gov (United States)

    Roberts, Nicholas J; Klein, Alison P

    2013-11-01

    Advances in our understanding of the human genome and next-generation technologies have facilitated the use of genome-wide sequencing to decipher the genetic basis of Mendelian disease and hereditary cancer syndromes. However, the application of genome-wide sequencing in hereditary cancer syndromes has had mixed success, in part, due to complex nature of the underlying genetic architecture. In this review we discuss the use of genome-wide sequencing in both Mendelian diseases and hereditary cancer syndromes, highlighting the potential and challenges of this approach using familial pancreatic cancer as an example. PMID:23196058

  9. Advances in Swine biomedical Model Genomics

    Science.gov (United States)

    This manuscript is a short update on the diversity of swine biomedical models and the importance of genomics in their continued development. The swine has been used as a major mammalian model for human studies because of the similarity in size and physiology, and in organ development and disease pro...

  10. Contributing to Tumor Molecular Characterization Projects with a Global Impact | Office of Cancer Genomics

    Science.gov (United States)

    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.

  11. Cancer Metabolism: A Modeling Perspective

    DEFF Research Database (Denmark)

    Ghaffari, Pouyan; Mardinoglu, Adil; Nielsen, Jens

    2015-01-01

    requires both the advancement of experimental technologies for more comprehensive measurement of omics as well as the advancement of robust computational methods for accurate analysis of the generated data. Here, we review cancer-associated reprogramming of metabolism and highlight the capability of genome...... suggest that utilization of amino acids and lipids contributes significantly to cancer cell metabolism. Also recent progresses in our understanding of carcinogenesis have revealed that cancer is a complex disease and cannot be understood through simple investigation of genetic mutations of cancerous cells....... Cancer cells present in complex tumor tissues communicate with the surrounding microenvironment and develop traits which promote their growth, survival, and metastasis. Decoding the full scope and targeting dysregulated metabolic pathways that support neoplastic transformations and their preservation...

  12. Genome rearrangement affects RNA virus adaptability on prostate cancer cells

    Directory of Open Access Journals (Sweden)

    Kendra ePesko

    2015-04-01

    Full Text Available Gene order is often highly conserved within taxonomic groups, such that organisms with rearranged genomes tend to be less fit than wildtype gene orders, and suggesting natural selection favors genome architectures that maximize fitness. But it is unclear whether rearranged genomes hinder adaptability: capacity to evolutionarily improve in a new environment. Negative-sense nonsegmented RNA viruses (order Mononegavirales have specific genome architecture: 3′ UTR – core protein genes – envelope protein genes – RNA-dependent RNA-polymerase gene – 5′ UTR. To test how genome architecture affects RNA virus evolution, we examined vesicular stomatitis virus (VSV variants with the nucleocapsid (N gene moved sequentially downstream in the genome. Because RNA polymerase stuttering in VSV replication causes greater mRNA production in upstream genes, N-gene translocation towards the 5’ end leads to stepwise decreases in N transcription, viral replication and progeny production, and also impacts the activation of type 1 interferon mediated antiviral responses. We evolved VSV gene-order variants in two prostate cancer cell lines: LNCap cells deficient in innate immune response to viral infection, and PC3 cells that mount an IFN stimulated anti-viral response to infection. We observed that gene order affects phenotypic adaptability (reproductive growth; viral suppression of immune function, especially on PC3 cells that strongly select against virus infection. Overall, populations derived from the least-fit ancestor (most-altered N position architecture adapted fastest, consistent with theory predicting populations with low initial fitness should improve faster in evolutionary time. Also, we observed correlated responses to selection, where viruses improved across both hosts, rather than suffer fitness trade-offs on unselected hosts. Whole genomics revealed multiple mutations in evolved variants, some of which were conserved across selective

  13. Identification of genomic alterations in pancreatic cancer using array-based comparative genomic hybridization.

    Directory of Open Access Journals (Sweden)

    Jian-Wei Liang

    Full Text Available BACKGROUND: Genomic aberration is a common feature of human cancers and also is one of the basic mechanisms that lead to overexpression of oncogenes and underexpression of tumor suppressor genes. Our study aims to identify frequent genomic changes in pancreatic cancer. MATERIALS AND METHODS: We used array comparative genomic hybridization (array CGH to identify recurrent genomic alterations and validated the protein expression of selected genes by immunohistochemistry. RESULTS: Sixteen gains and thirty-two losses occurred in more than 30% and 60% of the tumors, respectively. High-level amplifications at 7q21.3-q22.1 and 19q13.2 and homozygous deletions at 1p33-p32.3, 1p22.1, 1q22, 3q27.2, 6p22.3, 6p21.31, 12q13.2, 17p13.2, 17q21.31 and 22q13.1 were identified. Especially, amplification of AKT2 was detected in two carcinomas and homozygous deletion of CDKN2C in other two cases. In 15 independent validation samples, we found that AKT2 (19q13.2 and MCM7 (7q22.1 were amplified in 6 and 9 cases, and CAMTA2 (17p13.2 and PFN1 (17p13.2 were homozygously deleted in 3 and 1 cases. AKT2 and MCM7 were overexpressed, and CAMTA2 and PFN1 were underexpressed in pancreatic cancer tissues than in morphologically normal operative margin tissues. Both GISTIC and Genomic Workbench software identified 22q13.1 containing APOBEC3A and APOBEC3B as the only homozygous deletion region. And the expression levels of APOBEC3A and APOBEC3B were significantly lower in tumor tissues than in morphologically normal operative margin tissues. Further validation showed that overexpression of PSCA was significantly associated with lymph node metastasis, and overexpression of HMGA2 was significantly associated with invasive depth of pancreatic cancer. CONCLUSION: These recurrent genomic changes may be useful for revealing the mechanism of pancreatic carcinogenesis and providing candidate biomarkers.

  14. Engineered Swine Models of Cancer

    Directory of Open Access Journals (Sweden)

    Adrienne L. Watson

    2016-05-01

    Full Text Available Over the past decade, the technology to engineer genetically modified swine has seen many advancements, and because their physiology is remarkably similar to that of humans, swine models of cancer may be extremely valuable for preclinical safety studies as well as toxicity testing of pharmaceuticals prior to the start of human clinical trials. Hence, the benefits of using swine as a large animal model in cancer research and the potential applications and future opportunities of utilizing pigs in cancer modeling are immense. In this review, we discuss how pigs have been and can be used as a biomedical models for cancer research, with an emphasis on current technologies. We have focused on applications of precision genetics that can provide models that mimic human cancer predisposition syndromes. In particular, we describe the advantages of targeted gene-editing using custom endonucleases, specifically TALENs and CRISPRs, and transposon systems, to make novel pig models of cancer with broad preclinical applications.

  15. Engineered Swine Models of Cancer.

    Science.gov (United States)

    Watson, Adrienne L; Carlson, Daniel F; Largaespada, David A; Hackett, Perry B; Fahrenkrug, Scott C

    2016-01-01

    Over the past decade, the technology to engineer genetically modified swine has seen many advancements, and because their physiology is remarkably similar to that of humans, swine models of cancer may be extremely valuable for preclinical safety studies as well as toxicity testing of pharmaceuticals prior to the start of human clinical trials. Hence, the benefits of using swine as a large animal model in cancer research and the potential applications and future opportunities of utilizing pigs in cancer modeling are immense. In this review, we discuss how pigs have been and can be used as a biomedical models for cancer research, with an emphasis on current technologies. We have focused on applications of precision genetics that can provide models that mimic human cancer predisposition syndromes. In particular, we describe the advantages of targeted gene-editing using custom endonucleases, specifically TALENs and CRISPRs, and transposon systems, to make novel pig models of cancer with broad preclinical applications. PMID:27242889

  16. Comparison of genomic abnormalities between BRCAX and sporadic breast cancers studied by comparative genomic hybridization.

    Science.gov (United States)

    Gronwald, Jacek; Jauch, Anna; Cybulski, Cezary; Schoell, Brigitte; Böhm-Steuer, Barbara; Lener, Marcin; Grabowska, Ewa; Górski, Bohdan; Jakubowska, Anna; Domagała, Wenancjusz; Chosia, Maria; Scott, Rodney J; Lubiński, Jan

    2005-03-20

    Very little is known about the chromosomal regions harbouring genes involved in initiation and progression of BRCAX-associated breast cancers. We applied comparative genomic hybridization (CGH) to identify the most frequent genomic imbalances in 18 BRCAX hereditary breast cancers and compared them to chromosomal aberrations detected in a group of 27 sporadic breast cancers. The aberrations observed most frequently in BRCAX tumours were gains of 8q (83%), 19q (67%), 19p (61%), 20q (61%), 1q (56%), 17q (56%) and losses of 8p (56%), 11q (44%) and 13q (33%). The sporadic cases most frequently showed gains of 1q (67%), 8q (48%), 17q (37%), 16p (33%), 19q (33%) and losses of 11q (26%), 8p (22%) and 16q (19%). Losses of 8p and gains 8q, 19 as well as gains of 20q (with respect to ductal tumours only) were detected significantly more often in BRCAX than in sporadic breast cancers. Analysis of 8p-losses and 8q-gains showed that these aberrations are early events in the tumorigenesis of BRCAX tumors. The findings of this report indicate similarities between BRCAX and BRCA2 tumours, possibly suggesting a common pathway of disease. These findings need confirmation by more extensive studies because only a limited number of cases were analysed and there are relatively few reports published. PMID:15540206

  17. Integration of Genomic Data Enables Selective Discovery of Breast Cancer Drivers

    Science.gov (United States)

    Sanchez-Garcia, Félix; Villagrasa, Patricia; Matsui, Junji; Kotliar, Dylan; Castro, Verónica; Akavia, Uri-David; Chen, Bo-Juen; Saucedo-Cuevas, Laura; Barrueco, Ruth Rodriguez; Llobet-Navas, David; Silva, Jose M.; Pe’er, Dana

    2014-01-01

    Identifying driver genes in cancer remains a crucial bottleneck in therapeutic development and basic understanding of the disease. We developed Helios, a novel algorithm that integrates genomic data from primary tumors with data from functional RNAi screens to pinpoint driver genes within large recurrently amplified regions of DNA. Applying Helios to breast cancer data identified a set of candidate drivers highly enriched with known drivers (p-value < e−14). 9/10 top scoring Helios genes are known drivers of breast cancer and in vitro validation of 12 novel candidates predicted by Helios found 10 conferred enhanced anchorage independent growth, demonstrating Helios’s exquisite sensitivity and specificity. We extensively characterized RSF-1, a driver identified by Helios whose amplification correlates with poor prognosis, and found increased tumorigenesis and metastasis in mouse models. We have demonstrated a powerful approach for identifying novel driver genes and how it can yield important insights into cancer. PMID:25433701

  18. Advances in Swine Biomedical Model Genomics

    OpenAIRE

    Lunney, Joan K.

    2007-01-01

    This review is a short update on the diversity of swine biomedical models and the importance of genomics in their continued development. The swine has been used as a major mammalian model for human studies because of the similarity in size and physiology, and in organ development and disease progression. The pig model allows for deliberately timed studies, imaging of internal vessels and organs using standard human technologies, and collection of repeated peripheral samples and, at kill, deta...

  19. Genomic landscape of DNA repair genes in cancer

    Science.gov (United States)

    Carneiro, Benedito A.; Chandra, Sunandana; Kaplan, Jason; Kalyan, Aparna; Santa-Maria, Cesar A.; Platanias, Leonidas C.; Giles, Francis J.

    2016-01-01

    DNA repair genes are frequently mutated in cancer, yet limited data exist regarding the overall genomic landscape and functional implications of these alterations in their entirety.  We created comprehensive lists of DNA repair genes and indirect caretakers.  Mutation, copy number variation (CNV), and expression frequencies of these genes were analyzed in COSMIC. Mutation co-occurrence, clinical outcomes, and mutation burden were analyzed in TCGA. We report the 20 genes most frequently with mutations (n > 19,689 tumor samples for each gene), CNVs (n > 1,556), or up- or down-regulated (n = 7,998).  Mutual exclusivity was observed as no genes displayed both high CNV gain and loss or high up- and down-regulation, and CNV gain and loss positively correlated with up- and down-regulation, respectively. Co-occurrence of mutations differed between cancers, and mutations in many DNA repair genes were associated with higher total mutation burden. Mutation and CNV frequencies offer insights into which genes may play tumor suppressive or oncogenic roles, such as NEIL2 and RRM2B, respectively.  Mutual exclusivities within CNV and expression frequencies, and correlations between CNV and expression, support the functionality of these genomic alterations. This study provides comprehensive lists of candidate genes as potential biomarkers for genomic instability, novel therapeutic targets, or predictors of immunotherapy efficacy. PMID:27004405

  20. Mouse models for cancer research

    Institute of Scientific and Technical Information of China (English)

    Wei Zhang; Lynette Moore; Ping Ji

    2011-01-01

    Mouse models of cancer enable researchers to leamn about tumor biology in complicated and dynamic physiological systems. Since the development of gene targeting in mice, cancer biologists have been among the most frequent users of transgenic mouse models, which have dramatically increased knowledge about how cancers form and grow. The Chinese Joumnal of Cancer will publish a series of papers reporting the use of mouse models in studying genetic events in cancer cases. This editorial is an overview of the development and applications of mouse models of cancer and directs the reader to upcoming papers describing the use of these models to be published in coming issues, beginning with three articles in the current issue.

  1. Passage relevance models for genomics search

    Directory of Open Access Journals (Sweden)

    Frieder Ophir

    2009-03-01

    Full Text Available Abstract We present a passage relevance model for integrating syntactic and semantic evidence of biomedical concepts and topics using a probabilistic graphical model. Component models of topics, concepts, terms, and document are represented as potential functions within a Markov Random Field. The probability of a passage being relevant to a biologist's information need is represented as the joint distribution across all potential functions. Relevance model feedback of top ranked passages is used to improve distributional estimates of query concepts and topics in context, and a dimensional indexing strategy is used for efficient aggregation of concept and term statistics. By integrating multiple sources of evidence including dependencies between topics, concepts, and terms, we seek to improve genomics literature passage retrieval precision. Using this model, we are able to demonstrate statistically significant improvements in retrieval precision using a large genomics literature corpus.

  2. CRISPR-Cas9: A Revolutionary Tool for Cancer Modelling

    Directory of Open Access Journals (Sweden)

    Raul Torres-Ruiz

    2015-09-01

    Full Text Available The cancer-modelling field is now experiencing a conversion with the recent emergence of the RNA-programmable CRISPR-Cas9 system, a flexible methodology to produce essentially any desired modification in the genome. Cancer is a multistep process that involves many genetic mutations and other genome rearrangements. Despite their importance, it is difficult to recapitulate the degree of genetic complexity found in patient tumors. The CRISPR-Cas9 system for genome editing has been proven as a robust technology that makes it possible to generate cellular and animal models that recapitulate those cooperative alterations rapidly and at low cost. In this review, we will discuss the innovative applications of the CRISPR-Cas9 system to generate new models, providing a new way to interrogate the development and progression of cancers.

  3. Cancer and aging: The importance of telomeres in genome maintenance

    Energy Technology Data Exchange (ETDEWEB)

    Rodier, Francis; Kim, Sahn-ho; Nijjar, Tarlochan; Yaswen, Paul; Campisi, Judith

    2004-10-01

    Telomeres are the specialized DNA-protein structures that cap the ends of linear chromosomes, thereby protecting them from degradation and fusion by cellular DNA repair processes. In vertebrate cells, telomeres consist of several kilobase pairs of DNA having the sequence TTAGGG, a few hundred base pairs of single-stranded DNA at the 3' end of the telomeric DNA tract, and a host of proteins that organize the telomeric double and single stranded DNA into a protective structure. Functional telomeres are essential for maintaining the integrity and stability of genomes. When combined with loss of cell cycle checkpoint controls, telomere dysfunction can lead to genomic instability, a common cause and hallmark of cancer. Consequently, normal mammalian cells respond to dysfunctional telomeres by undergoing apoptosis (programmed cell death) or cellular senescence (permanent cell cycle arrest), two cellular tumor suppressor mechanisms. These tumor suppressor mechanisms are potent suppressors of cancer, but recent evidence suggests that they can antagonistically also contribute to aging phenotypes. Here, we review what is known about the structure and function of telomeres in mammalian cells, particularly human cells, and how telomere dysfunction may arise and contribute to cancer and aging phenotypes.

  4. Understanding the Genetic Mechanisms of Cancer Drug Resistance Using Genomic Approaches.

    Science.gov (United States)

    Hu, Xueda; Zhang, Zemin

    2016-02-01

    A major obstacle in precision cancer medicine is the inevitable resistance to targeted therapies. Tremendous effort and progress has been made over the past few years to understand the biochemical and genetic mechanisms underlying drug resistance, with the goal to eventually overcome such daunting challenges. Diverse mechanisms, such as secondary mutations, oncogene bypass, and epigenetic alterations, can all lead to drug resistance, and the number of known involved genes is growing rapidly, thus providing many possibilities to overcome resistance. The finding of these mechanisms and genes invariably requires the application of genomic and functional genomic approaches to tumors or cancer models. In this review, we briefly highlight the major drug-resistance mechanisms known today, and then focus primarily on the technological approaches leading to the advancement of this field.

  5. Understanding the Genetic Mechanisms of Cancer Drug Resistance Using Genomic Approaches.

    Science.gov (United States)

    Hu, Xueda; Zhang, Zemin

    2016-02-01

    A major obstacle in precision cancer medicine is the inevitable resistance to targeted therapies. Tremendous effort and progress has been made over the past few years to understand the biochemical and genetic mechanisms underlying drug resistance, with the goal to eventually overcome such daunting challenges. Diverse mechanisms, such as secondary mutations, oncogene bypass, and epigenetic alterations, can all lead to drug resistance, and the number of known involved genes is growing rapidly, thus providing many possibilities to overcome resistance. The finding of these mechanisms and genes invariably requires the application of genomic and functional genomic approaches to tumors or cancer models. In this review, we briefly highlight the major drug-resistance mechanisms known today, and then focus primarily on the technological approaches leading to the advancement of this field. PMID:26689126

  6. Proteomics Data on UCSC Genome Browser - Office of Cancer Clinical Proteomics Research

    Science.gov (United States)

    The National Cancer Institute's Clinical Proteomic Tumor Analysis Consortium scientists are working together with the University of California, Santa Cruz (UCSC) Genomics Institute to provide public access to cancer proteomics data.

  7. Genome profiling of ERBB2-amplified breast cancers

    International Nuclear Information System (INIS)

    Around 20% of breast cancers (BC) show ERBB2 gene amplification and overexpression of the ERBB2 tyrosine kinase receptor. They are associated with a poor prognosis but can benefit from targeted therapy. A better knowledge of these BCs, genomically and biologically heterogeneous, may help understand their behavior and design new therapeutic strategies. We defined the high resolution genome and gene expression profiles of 54 ERBB2-amplified BCs using 244K oligonucleotide array-comparative genomic hybridization and whole-genome DNA microarrays. Expression of ERBB2, phosphorylated ERBB2, EGFR, IGF1R and FOXA1 proteins was assessed by immunohistochemistry to evaluate the functional ERBB2 status and identify co-expressions. First, we identified the ERBB2-C17orf37-GRB7 genomic segment as the minimal common 17q12-q21 amplicon, and CRKRS and IKZF3 as the most frequent centromeric and telomeric amplicon borders, respectively. Second, GISTIC analysis identified 17 other genome regions affected by copy number aberration (CNA) (amplifications, gains, losses). The expression of 37 genes of these regions was deregulated. Third, two types of heterogeneity were observed in ERBB2-amplified BCs. The genomic profiles of estrogen receptor-postive (ER+) and negative (ER-) ERBB2-amplified BCs were different. The WNT/β-catenin signaling pathway was involved in ER- ERBB2-amplified BCs, and PVT1 and TRPS1 were candidate oncogenes associated with ER+ ERBB2-amplified BCs. The size of the ERBB2 amplicon was different in inflammatory (IBC) and non-inflammatory BCs. ERBB2-amplified IBCs were characterized by the downregulated and upregulated mRNA expression of ten and two genes in proportion to CNA, respectively. IHC results showed (i) a linear relationship between ERBB2 gene amplification and its gene and protein expressions with a good correlation between ERBB2 expression and phosphorylation status; (ii) a potential signaling cross-talk between EGFR or IGF1R and ERBB2, which could influence

  8. 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.

  9. Disentangling Pleiotropy along the Genome using Sparse Latent Variable Models

    DEFF Research Database (Denmark)

    Janss, Luc

    Bayesian models are described that use atent variables to model covariances. These models are flexible, scale up linearly in the number of traits, and allow separating covariance structures in different components at the trait level and at the genomic level. Multi-trait version of the BayesA (MT......-BA) and Bayesian LASSO (MT-BL) are described that model heterogeneous variance and covariance over the genome, and a model that directly models multiple genomic breeding values (MT-MG), representing different genomic covariance structures. The models are demonstrated on a mouse data set to model the genomic...

  10. Breast cancer risk among Swedish hemangioma patients and possible consequences of radiation-induced genomic instability

    Energy Technology Data Exchange (ETDEWEB)

    Eidemueller, Markus, E-mail: markus.eidemueller@helmholtz-muenchen.de [Helmholtz Zentrum Muenchen, Institute of Radiation Protection, 85764 Neuherberg (Germany); Holmberg, Erik [Department of Oncology, Sahlgrenska University Hospital, SE-413 45 Goeteborg (Sweden); Jacob, Peter [Helmholtz Zentrum Muenchen, Institute of Radiation Protection, 85764 Neuherberg (Germany); Lundell, Marie [Department of Medical Physics, Radiumhemmet, Karolinska University Hospital, SE-171 76 Stockholm (Sweden); Karlsson, Per [Department of Oncology, Sahlgrenska University Hospital, SE-413 45 Goeteborg (Sweden)

    2009-10-02

    Breast cancer incidence among 17,158 female Swedish hemangioma patients was analyzed with empirical excess relative risk models and with a biologically-based model of carcinogenesis. The patients were treated in infancy mainly by external application of radium-226. The mean and median absorbed doses to the breast were 0.29 and 0.04 Gy, and a total of 678 breast cancer cases have been observed. Both models agree very well in the risk estimates with an excess relative risk and excess absolute risk at the age of 50 years, about the mean age of breast cancer incidence, of 0.25 Gy{sup -1}(95% CI 0.14; 0.37) and 30.7 (10{sup 5}BYRGy){sup -1} (95% CI 16.9; 42.8), respectively. Models incorporating effects of radiation-induced genomic instability were developed and applied to the hemangioma cohort. The biologically-based description of the radiation risk was significantly improved with a model of genomic instability at an early stage of carcinogenesis.

  11. The impact of vitamin D in breast cancer: genomics, pathways, metabolism

    Directory of Open Access Journals (Sweden)

    Carmen Judith Narvaez

    2014-06-01

    Full Text Available Nuclear receptors exert profound effects on mammary gland physiology and have complex roles in the etiology of breast cancer. In addition to receptors for classic steroid hormones such as estrogen and progesterone, the nuclear vitamin D receptor (VDR interacts with its ligand 1α,25(OH2D3 to modulate the normal mammary epithelial cell genome and subsequent phenotype. Observational studies suggest that vitamin D deficiency is common in breast cancer patients and that low vitamin D status enhances the risk for disease development or progression. Genomic profiling has characterized many 1α,25(OH2D3 responsive targets in normal mammary cells and in breast cancers, providing insight into the molecular actions of 1α,25(OH2D3 and the VDR in regulation of cell cycle, apoptosis and differentiation. New areas of emphasis include regulation of tumor metabolism and innate immune responses. However, the role of VDR in individual cell types (ie epithelial, adipose, fibroblast, endotelial, immune of normal and tumor tissues remains to be clarified. Furthermore, the mechanisms by which VDR integrates signaling between diverse cell types and controls soluble signals and paracrine pathways in the tissue/tumor microenvironment remain to be defined. Model systems of carcinogenesis have provided evidence that both VDR expression and 1α,25(OH2D3 actions change with transformation but clinical data regarding vitamin D responsiveness of established tumors is limited and inconclusive. Because breast cancer is heterogeneous, analysis of VDR actions in specific molecular subtypes of the disease may help to clarify the conflicting data. The expanded use of genomic, proteomic and metabolomic approaches on a diverse array of in vitro and in vivo model systems is clearly warranted to comprehensively understand the nework of vitamin D regulated pathways in the context of breast cancer.

  12. 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.

  13. 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

  14. Identifying common prognostic factors in genomic cancer studies: A novel index for censored outcomes

    Directory of Open Access Journals (Sweden)

    Moreau Thierry

    2010-03-01

    Full Text Available Abstract Background With the growing number of public repositories for high-throughput genomic data, it is of great interest to combine the results produced by independent research groups. Such a combination allows the identification of common genomic factors across multiple cancer types and provides new insights into the disease process. In the framework of the proportional hazards model, classical procedures, which consist of ranking genes according to the estimated hazard ratio or the p-value obtained from a test statistic of no association between survival and gene expression level, are not suitable for gene selection across multiple genomic datasets with different sample sizes. We propose a novel index for identifying genes with a common effect across heterogeneous genomic studies designed to remain stable whatever the sample size and which has a straightforward interpretation in terms of the percentage of separability between patients according to their survival times and gene expression measurements. Results The simulations results show that the proposed index is not substantially affected by the sample size of the study and the censoring. They also show that its separability performance is higher than indices of predictive accuracy relying on the likelihood function. A simulated example illustrates the good operating characteristics of our index. In addition, we demonstrate that it is linked to the score statistic and possesses a biologically relevant interpretation. The practical use of the index is illustrated for identifying genes with common effects across eight independent genomic cancer studies of different sample sizes. The meta-selection allows the identification of four genes (ESPL1, KIF4A, HJURP, LRIG1 that are biologically relevant to the carcinogenesis process and have a prognostic impact on survival outcome across various solid tumors. Conclusion The proposed index is a promising tool for identifying factors having a

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

    Science.gov (United States)

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

    2016-01-01

    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. PMID:26484415

  16. DO CANCER CLINICAL TRIAL POPULATIONS TRULY REPRESENT CANCER PATIENTS? A COMPARISON OF OPEN CLINICAL TRIALS TO THE CANCER GENOME ATLAS

    Science.gov (United States)

    Geifman, Nophar; Butte, Atul J.

    2016-01-01

    Open clinical trial data offer many opportunities for the scientific community to independently verify published results, evaluate new hypotheses and conduct meta-analyses. These data provide a springboard for scientific advances in precision medicine but the question arises as to how representative clinical trials data are of cancer patients overall. Here we present the integrative analysis of data from several cancer clinical trials and compare these to patient-level data from The Cancer Genome Atlas (TCGA). Comparison of cancer type-specific survival rates reveals that these are overall lower in trial subjects. This effect, at least to some extent, can be explained by the more advanced stages of cancer of trial subjects. This analysis also reveals that for stage IV cancer, colorectal cancer patients have a better chance of survival than breast cancer patients. On the other hand, for all other stages, breast cancer patients have better survival than colorectal cancer patients. Comparison of survival in different stages of disease between the two datasets reveals that subjects with stage IV cancer from the trials dataset have a lower chance of survival than matching stage IV subjects from TCGA. One likely explanation for this observation is that stage IV trial subjects have lower survival rates since their cancer is less likely to respond to treatment. To conclude, we present here a newly available clinical trials dataset which allowed for the integration of patient-level data from many cancer clinical trials. Our comprehensive analysis reveals that cancer-related clinical trials are not representative of general cancer patient populations, mostly due to their focus on the more advanced stages of the disease. These and other limitations of clinical trials data should, perhaps, be taken into consideration in medical research and in the field of precision medicine. PMID:26776196

  17. DO CANCER CLINICAL TRIAL POPULATIONS TRULY REPRESENT CANCER PATIENTS? A COMPARISON OF OPEN CLINICAL TRIALS TO THE CANCER GENOME ATLAS.

    Science.gov (United States)

    Geifman, Nophar; Butte, Atul J

    2016-01-01

    Open clinical trial data offer many opportunities for the scientific community to independently verify published results, evaluate new hypotheses and conduct meta-analyses. These data provide a springboard for scientific advances in precision medicine but the question arises as to how representative clinical trials data are of cancer patients overall. Here we present the integrative analysis of data from several cancer clinical trials and compare these to patient-level data from The Cancer Genome Atlas (TCGA). Comparison of cancer type-specific survival rates reveals that these are overall lower in trial subjects. This effect, at least to some extent, can be explained by the more advanced stages of cancer of trial subjects. This analysis also reveals that for stage IV cancer, colorectal cancer patients have a better chance of survival than breast cancer patients. On the other hand, for all other stages, breast cancer patients have better survival than colorectal cancer patients. Comparison of survival in different stages of disease between the two datasets reveals that subjects with stage IV cancer from the trials dataset have a lower chance of survival than matching stage IV subjects from TCGA. One likely explanation for this observation is that stage IV trial subjects have lower survival rates since their cancer is less likely to respond to treatment. To conclude, we present here a newly available clinical trials dataset which allowed for the integration of patient-level data from many cancer clinical trials. Our comprehensive analysis reveals that cancer-related clinical trials are not representative of general cancer patient populations, mostly due to their focus on the more advanced stages of the disease. These and other limitations of clinical trials data should, perhaps, be taken into consideration in medical research and in the field of precision medicine.

  18. Connecting Genomic Alterations to Cancer Biology with Proteomics: The NCI Clinical Proteomic Tumor Analysis Consortium

    Energy Technology Data Exchange (ETDEWEB)

    Ellis, Matthew; Gillette, Michael; Carr, Steven A.; Paulovich, Amanda G.; Smith, Richard D.; Rodland, Karin D.; Townsend, Reid; Kinsinger, Christopher; Mesri, Mehdi; Rodriguez, Henry; Liebler, Daniel

    2013-10-03

    The National Cancer Institute (NCI) Clinical Proteomic Tumor Analysis Consortium is applying the latest generation of proteomic technologies to genomically annotated tumors from The Cancer Genome Atlas (TCGA) program, a joint initiative of the NCI and the National Human Genome Research Institute. By providing a fully integrated accounting of DNA, RNA, and protein abnormalities in individual tumors, these datasets will illuminate the complex relationship between genomic abnormalities and cancer phenotypes, thus producing biologic insights as well as a wave of novel candidate biomarkers and therapeutic targets amenable to verifi cation using targeted mass spectrometry methods.

  19. [The application of CRISPR/Cas9 genome editing technology in cancer research].

    Science.gov (United States)

    Wang, Dayong; Ma, Ning; Hui, Yang; Gao, Xu

    2016-01-01

    The CRISPR/Cas9 (clustered regularly interspaced short palindromic repeats/CRISPR-associated protein-9 nuclease) genome editing technology has become more and more popular in gene editing because of its simple design and easy operation. Using the CRISPR/Cas9 system, researchers can perform site-directed genome modification at the base level. Moreover, it has been widely used in genome editing in multiple species and related cancer research. In this review, we summarize the application of the CRISPR/Cas9 system in cancer research based on the latest research progresses as well as our understanding of cancer research and genome editing techniques.

  20. 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...

  1. Bayesian predictive modeling for genomic based personalized treatment selection.

    Science.gov (United States)

    Ma, Junsheng; Stingo, Francesco C; Hobbs, Brian P

    2016-06-01

    Efforts to personalize medicine in oncology have been limited by reductive characterizations of the intrinsically complex underlying biological phenomena. Future advances in personalized medicine will rely on molecular signatures that derive from synthesis of multifarious interdependent molecular quantities requiring robust quantitative methods. However, highly parameterized statistical models when applied in these settings often require a prohibitively large database and are sensitive to proper characterizations of the treatment-by-covariate interactions, which in practice are difficult to specify and may be limited by generalized linear models. In this article, we present a Bayesian predictive framework that enables the integration of a high-dimensional set of genomic features with clinical responses and treatment histories of historical patients, providing a probabilistic basis for using the clinical and molecular information to personalize therapy for future patients. Our work represents one of the first attempts to define personalized treatment assignment rules based on large-scale genomic data. We use actual gene expression data acquired from The Cancer Genome Atlas in the settings of leukemia and glioma to explore the statistical properties of our proposed Bayesian approach for personalizing treatment selection. The method is shown to yield considerable improvements in predictive accuracy when compared to penalized regression approaches. PMID:26575856

  2. Integrated Bioinformatics, Environmental Epidemiologic and Genomic Approaches to Identify Environmental and Molecular Links between Endometriosis and Breast Cancer

    OpenAIRE

    Deodutta Roy; Marisa Morgan; Changwon Yoo; Alok Deoraj; Sandhya Roy; Vijay Kumar Yadav; Mohannad Garoub; Hamza Assaggaf; Mayur Doke

    2015-01-01

    We present a combined environmental epidemiologic, genomic, and bioinformatics approach to identify: exposure of environmental chemicals with estrogenic activity; epidemiologic association between endocrine disrupting chemical (EDC) and health effects, such as, breast cancer or endometriosis; and gene-EDC interactions and disease associations. Human exposure measurement and modeling confirmed estrogenic activity of three selected class of environmental chemicals, polychlorinated biphenyls (PC...

  3. The Impact of dUTPase on Ribonucleotide Reductase-Induced Genome Instability in Cancer Cells

    Directory of Open Access Journals (Sweden)

    Chih-Wei Chen

    2016-08-01

    Full Text Available The appropriate supply of dNTPs is critical for cell growth and genome integrity. Here, we investigated the interrelationship between dUTP pyrophosphatase (dUTPase and ribonucleotide reductase (RNR in the regulation of genome stability. Our results demonstrate that reducing the expression of dUTPase increases genome stress in cancer. Analysis of clinical samples reveals a significant correlation between the combination of low dUTPase and high R2, a subunit of RNR, and a poor prognosis in colorectal and breast cancer patients. Furthermore, overexpression of R2 in non-tumorigenic cells progressively increases genome stress, promoting transformation. These cells display alterations in replication fork progression, elevated genomic uracil, and breaks at AT-rich common fragile sites. Consistently, overexpression of dUTPase abolishes R2-induced genome instability. Thus, the expression level of dUTPase determines the role of high R2 in driving genome instability in cancer cells.

  4. Merging Marine Ecosystem Models and Genomics

    Science.gov (United States)

    Coles, V.; Hood, R. R.; Stukel, M. R.; Moran, M. A.; Paul, J. H.; Satinsky, B.; Zielinski, B.; Yager, P. L.

    2015-12-01

    oceanography. One of the grand challenges of oceanography is to develop model techniques to more effectively incorporate genomic information. As one approach, we developed an ecosystem model whose community is determined by randomly assigning functional genes to build each organism's "DNA". Microbes are assigned a size that sets their baseline environmental responses using allometric response cuves. These responses are modified by the costs and benefits conferred by each gene in an organism's genome. The microbes are embedded in a general circulation model where environmental conditions shape the emergent population. This model is used to explore whether organisms constructed from randomized combinations of metabolic capability alone can self-organize to create realistic oceanic biogeochemical gradients. Realistic community size spectra and chlorophyll-a concentrations emerge in the model. The model is run repeatedly with randomly-generated microbial communities and each time realistic gradients in community size spectra, chlorophyll-a, and forms of nitrogen develop. This supports the hypothesis that the metabolic potential of a community rather than the realized species composition is the primary factor setting vertical and horizontal environmental gradients. Vertical distributions of nitrogen and transcripts for genes involved in nitrification are broadly consistent with observations. Modeled gene and transcript abundance for nitrogen cycling and processing of land-derived organic material match observations along the extreme gradients in the Amazon River plume, and they help to explain the factors controlling observed variability.

  5. Clinic-Genomic Association Mining for Colorectal Cancer Using Publicly Available Datasets

    OpenAIRE

    Fang Liu; Yaning Feng; Zhenye Li; Chao Pan; Yuncong Su; Rui Yang; Liying Song; Huilong Duan; Ning Deng

    2014-01-01

    In recent years, a growing number of researchers began to focus on how to establish associations between clinical and genomic data. However, up to now, there is lack of research mining clinic-genomic associations by comprehensively analysing available gene expression data for a single disease. Colorectal cancer is one of the malignant tumours. A number of genetic syndromes have been proven to be associated with colorectal cancer. This paper presents our research on mining clinic-genomic assoc...

  6. Pan-cancer analysis of the extent and consequences of intratumor heterogeneity | Office of Cancer Genomics

    Science.gov (United States)

    Intratumor heterogeneity (ITH) drives neoplastic progression and therapeutic resistance. We used the bioinformatics tools 'expanding ploidy and allele frequency on nested subpopulations' (EXPANDS) and PyClone to detect clones that are present at a ≥10% frequency in 1,165 exome sequences from tumors in The Cancer Genome Atlas. 86% of tumors across 12 cancer types had at least two clones. ITH in the morphology of nuclei was associated with genetic ITH (Spearman's correlation coefficient, ρ = 0.24-0.41; P < 0.001).

  7. Systematic Functional Interrogation of Rare Cancer Variants Identifies Oncogenic Alleles | Office of Cancer Genomics

    Science.gov (United States)

    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.

  8. Liver Cancer Risk Prediction Models

    Science.gov (United States)

    Developing statistical models that estimate the probability of developing liver cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  9. Breast Cancer Risk Prediction Models

    Science.gov (United States)

    Developing statistical models that estimate the probability of developing breast cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  10. Prostate Cancer Risk Prediction Models

    Science.gov (United States)

    Developing statistical models that estimate the probability of developing prostate cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  11. Pancreatic Cancer Risk Prediction Models

    Science.gov (United States)

    Developing statistical models that estimate the probability of developing pancreatic cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  12. Colorectal Cancer Risk Prediction Models

    Science.gov (United States)

    Developing statistical models that estimate the probability of developing colorectal cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  13. Bladder Cancer Risk Prediction Models

    Science.gov (United States)

    Developing statistical models that estimate the probability of developing bladder cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  14. Esophageal Cancer Risk Prediction Models

    Science.gov (United States)

    Developing statistical models that estimate the probability of developing esophageal cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  15. Cervical Cancer Risk Prediction Models

    Science.gov (United States)

    Developing statistical models that estimate the probability of developing cervical cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  16. Testicular Cancer Risk Prediction Models

    Science.gov (United States)

    Developing statistical models that estimate the probability of testicular cervical cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  17. Ovarian Cancer Risk Prediction Models

    Science.gov (United States)

    Developing statistical models that estimate the probability of developing ovarian cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  18. Lung Cancer Risk Prediction Models

    Science.gov (United States)

    Developing statistical models that estimate the probability of developing lung cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  19. The Cancer Cell Line Encyclopedia enables predictive modeling of anticancer drug sensitivity

    OpenAIRE

    Barretina, Jordi; Caponigro, Giordano; Stransky, Nicolas; Venkatesan, Kavitha; Margolin, Adam A.; Kim, Sungjoon; Wilson, Christopher J.; Lehár, Joseph; Kryukov, Gregory V; Sonkin, Dmitriy; Reddy, Anupama; Liu, Manway; Murray, Lauren; Berger, Michael F; Monahan, John E.

    2012-01-01

    The systematic translation of cancer genomic data into knowledge of tumor biology and therapeutic avenues remains challenging. Such efforts should be greatly aided by robust preclinical model systems that reflect the genomic diversity of human cancers and for which detailed genetic and pharmacologic annotation is available 1 . Here we describe the Cancer Cell Line Encyclopedia (CCLE): a compilation of gene expression, chromosomal copy number, and massively parallel sequencing data from 947 hu...

  20. BreCAN-DB: a repository cum browser of personalized DNA breakpoint profiles of cancer genomes.

    Science.gov (United States)

    Narang, Pankaj; Dhapola, Parashar; Chowdhury, Shantanu

    2016-01-01

    BreCAN-DB (http://brecandb.igib.res.in) is a repository cum browser of whole genome somatic DNA breakpoint profiles of cancer genomes, mapped at single nucleotide resolution using deep sequencing data. These breakpoints are associated with deletions, insertions, inversions, tandem duplications, translocations and a combination of these structural genomic alterations. The current release of BreCAN-DB features breakpoint profiles from 99 cancer-normal pairs, comprising five cancer types. We identified DNA breakpoints across genomes using high-coverage next-generation sequencing data obtained from TCGA and dbGaP. Further, in these cancer genomes, we methodically identified breakpoint hotspots which were significantly enriched with somatic structural alterations. To visualize the breakpoint profiles, a next-generation genome browser was integrated with BreCAN-DB. Moreover, we also included previously reported breakpoint profiles from 138 cancer-normal pairs, spanning 10 cancer types into the browser. Additionally, BreCAN-DB allows one to identify breakpoint hotspots in user uploaded data set. We have also included a functionality to query overlap of any breakpoint profile with regions of user's interest. Users can download breakpoint profiles from the database or may submit their data to be integrated in BreCAN-DB. We believe that BreCAN-DB will be useful resource for genomics scientific community and is a step towards personalized cancer genomics. PMID:26586806

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

    OpenAIRE

    Aaraby Yoheswaran Nielsen; Morten Frier Gjerstorff

    2016-01-01

    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 ...

  2. Engineered Swine Models of Cancer

    OpenAIRE

    Watson, Adrienne L; Carlson, Daniel F.; Largaespada, David A; Hackett, Perry B; Fahrenkrug, Scott C.

    2016-01-01

    Over the past decade, the technology to engineer genetically modified swine has seen many advancements, and because their physiology is remarkably similar to that of humans, swine models of cancer may be extremely valuable for preclinical safety studies as well as toxicity testing of pharmaceuticals prior to the start of human clinical trials. Hence, the benefits of using swine as a large animal model in cancer research and the potential applications and future opportunities of utilizing pigs...

  3. Whole-genome characterization of chemoresistant ovarian cancer.

    Science.gov (United States)

    Patch, Ann-Marie; Christie, Elizabeth L; Etemadmoghadam, Dariush; Garsed, Dale W; George, Joshy; Fereday, Sian; Nones, Katia; Cowin, Prue; Alsop, Kathryn; Bailey, Peter J; Kassahn, Karin S; Newell, Felicity; Quinn, Michael C J; Kazakoff, Stephen; Quek, Kelly; Wilhelm-Benartzi, Charlotte; Curry, Ed; Leong, Huei San; Hamilton, Anne; Mileshkin, Linda; Au-Yeung, George; Kennedy, Catherine; Hung, Jillian; Chiew, Yoke-Eng; Harnett, Paul; Friedlander, Michael; Quinn, Michael; Pyman, Jan; Cordner, Stephen; O'Brien, Patricia; Leditschke, Jodie; Young, Greg; Strachan, Kate; Waring, Paul; Azar, Walid; Mitchell, Chris; Traficante, Nadia; Hendley, Joy; Thorne, Heather; Shackleton, Mark; Miller, David K; Arnau, Gisela Mir; Tothill, Richard W; Holloway, Timothy P; Semple, Timothy; Harliwong, Ivon; Nourse, Craig; Nourbakhsh, Ehsan; Manning, Suzanne; Idrisoglu, Senel; Bruxner, Timothy J C; Christ, Angelika N; Poudel, Barsha; Holmes, Oliver; Anderson, Matthew; Leonard, Conrad; Lonie, Andrew; Hall, Nathan; Wood, Scott; Taylor, Darrin F; Xu, Qinying; Fink, J Lynn; Waddell, Nick; Drapkin, Ronny; Stronach, Euan; Gabra, Hani; Brown, Robert; Jewell, Andrea; Nagaraj, Shivashankar H; Markham, Emma; Wilson, Peter J; Ellul, Jason; McNally, Orla; Doyle, Maria A; Vedururu, Ravikiran; Stewart, Collin; Lengyel, Ernst; Pearson, John V; Waddell, Nicola; deFazio, Anna; Grimmond, Sean M; Bowtell, David D L

    2015-05-28

    Patients with high-grade serous ovarian cancer (HGSC) have experienced little improvement in overall survival, and standard treatment has not advanced beyond platinum-based combination chemotherapy, during the past 30 years. To understand the drivers of clinical phenotypes better, here we use whole-genome sequencing of tumour and germline DNA samples from 92 patients with primary refractory, resistant, sensitive and matched acquired resistant disease. We show that gene breakage commonly inactivates the tumour suppressors RB1, NF1, RAD51B and PTEN in HGSC, and contributes to acquired chemotherapy resistance. CCNE1 amplification was common in primary resistant and refractory disease. We observed several molecular events associated with acquired resistance, including multiple independent reversions of germline BRCA1 or BRCA2 mutations in individual patients, loss of BRCA1 promoter methylation, an alteration in molecular subtype, and recurrent promoter fusion associated with overexpression of the drug efflux pump MDR1. PMID:26017449

  4. The national cancer institute (NCI) and cancer biology in a 'post genome world'

    International Nuclear Information System (INIS)

    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

  5. 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) in ...

  6. Genome-wide association analysis identifies three new breast cancer susceptibility loci

    NARCIS (Netherlands)

    Ghoussaini, M.; Fletcher, O.; Michailidou, K.; Turnbull, C.; Schmidt, M.K.; Dicks, E.; Dennis, J.; Wang, Q.; Humphreys, M.K.; Luccarini, C.; Baynes, C.; Conroy, D.; Maranian, M.; Ahmed, S.; Driver, K.; Johnson, N.; Orr, N.; dos Santos Silva, I.; Waisfisz, Q.; Meijers-Heijboer, H.; Uitterlinden, A.G.; Rivadeneira, F.; Hall, P.; Czene, K.; Irwanto, A.; Liu, J.; Nevanlinna, H.; Aittomaki, K.; Blomqvist, C.; Meindl, A.; Schmutzler, R.K.; Muller-Myhsok, B.; Lichtner, P.; Chang-Claude, J.; Hein, R.; Nickels, S.; Flesch-Janys, D.; Tsimiklis, H.; Makalic, E.; Schmidt, D.; Bui, M.; Hopper, J.L.; Apicella, C.; Park, D.J.; Southey, M.; Hunter, D.J.; Chanock, S.J.; Broeks, A.; Verhoef, S.; Hogervorst, F.B.; Fasching, P.A.; Lux, M.P.; Beckmann, M.W.; Ekici, A.B.; Sawyer, E.; Tomlinson, I.; Kerin, M.; Marme, F.; Schneeweiss, A.; Sohn, C.; Burwinkel, B.; Guenel, P.; Truong, T.; Cordina-Duverger, E.; Menegaux, F.; Bojesen, S.E.; Nordestgaard, B.G.; Nielsen, S.F.; Flyger, H.; Milne, R.L.; Alonso, M.R.; Gonzalez-Neira, A.; Benitez, J.; Anton-Culver, H.; Ziogas, A.; Bernstein, L.; Dur, C.C.; Brenner, H.; Muller, H.; Arndt, V.; Stegmaier, C.; Justenhoven, C.; Brauch, H.; Bruning, T.; Wang-Gohrke, S.; Eilber, U.; Dork, T.; Schurmann, P.; Bremer, M.; Hillemanns, P.; Bogdanova, N.V.; Antonenkova, N.N.; Rogov, Y.I.; Karstens, J.H.; Bermisheva, M.; Prokofieva, D.; Ligtenberg, M.J.

    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 approximately 8% of the heritability of the disease. We attempted to replicate 72 promising associations from two independent genome-wide association studies

  7. Genome-wide association study identifies new prostate cancer susceptibility loci

    DEFF Research Database (Denmark)

    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...

  8. Large-scale profiling of microRNAs for The Cancer Genome Atlas.

    Science.gov (United States)

    Chu, Andy; Robertson, Gordon; Brooks, Denise; Mungall, Andrew J; Birol, Inanc; Coope, Robin; Ma, Yussanne; Jones, Steven; Marra, Marco A

    2016-01-01

    The comprehensive multiplatform genomics data generated by The Cancer Genome Atlas (TCGA) Research Network is an enabling resource for cancer research. It includes an unprecedented amount of microRNA sequence data: ~11 000 libraries across 33 cancer types. Combined with initiatives like the National Cancer Institute Genomics Cloud Pilots, such data resources will make intensive analysis of large-scale cancer genomics data widely accessible. To support such initiatives, and to enable comparison of TCGA microRNA data to data from other projects, we describe the process that we developed and used to generate the microRNA sequence data, from library construction through to submission of data to repositories. In the context of this process, we describe the computational pipeline that we used to characterize microRNA expression across large patient cohorts.

  9. Interpreting cancer genomes using systematic host network perturbations by tumour virus proteins.

    Science.gov (United States)

    Rozenblatt-Rosen, Orit; Deo, Rahul C; Padi, Megha; Adelmant, Guillaume; Calderwood, Michael A; Rolland, Thomas; Grace, Miranda; Dricot, Amélie; Askenazi, Manor; Tavares, Maria; Pevzner, Samuel J; Abderazzaq, Fieda; Byrdsong, Danielle; Carvunis, Anne-Ruxandra; Chen, Alyce A; Cheng, Jingwei; Correll, Mick; Duarte, Melissa; Fan, Changyu; Feltkamp, Mariet C; Ficarro, Scott B; Franchi, Rachel; Garg, Brijesh K; Gulbahce, Natali; Hao, Tong; Holthaus, Amy M; James, Robert; Korkhin, Anna; Litovchick, Larisa; Mar, Jessica C; Pak, Theodore R; Rabello, Sabrina; Rubio, Renee; Shen, Yun; Singh, Saurav; Spangle, Jennifer M; Tasan, Murat; Wanamaker, Shelly; Webber, James T; Roecklein-Canfield, Jennifer; Johannsen, Eric; Barabási, Albert-László; Beroukhim, Rameen; Kieff, Elliott; Cusick, Michael E; Hill, David E; Münger, Karl; Marto, Jarrod A; Quackenbush, John; Roth, Frederick P; DeCaprio, James A; Vidal, Marc

    2012-07-26

    Genotypic differences greatly influence susceptibility and resistance to disease. Understanding genotype-phenotype relationships requires that phenotypes be viewed as manifestations of network properties, rather than simply as the result of individual genomic variations. Genome sequencing efforts have identified numerous germline mutations, and large numbers of somatic genomic alterations, associated with a predisposition to cancer. However, it remains difficult to distinguish background, or 'passenger', cancer mutations from causal, or 'driver', mutations in these data sets. Human viruses intrinsically depend on their host cell during the course of infection and can elicit pathological phenotypes similar to those arising from mutations. Here we test the hypothesis that genomic variations and tumour viruses may cause cancer through related mechanisms, by systematically examining host interactome and transcriptome network perturbations caused by DNA tumour virus proteins. The resulting integrated viral perturbation data reflects rewiring of the host cell networks, and highlights pathways, such as Notch signalling and apoptosis, that go awry in cancer. We show that systematic analyses of host targets of viral proteins can identify cancer genes with a success rate on a par with their identification through functional genomics and large-scale cataloguing of tumour mutations. Together, these complementary approaches increase the specificity of cancer gene identification. Combining systems-level studies of pathogen-encoded gene products with genomic approaches will facilitate the prioritization of cancer-causing driver genes to advance the understanding of the genetic basis of human cancer. PMID:22810586

  10. Interpreting cancer genomes using systematic host perturbations by tumour virus proteins

    Science.gov (United States)

    Rozenblatt-Rosen, Orit; Deo, Rahul C.; Padi, Megha; Adelmant, Guillaume; Calderwood, Michael A.; Rolland, Thomas; Grace, Miranda; Dricot, Amélie; Askenazi, Manor; Tavares, Maria; Pevzner, Sam; Abderazzaq, Fieda; Byrdsong, Danielle; Carvunis, Anne-Ruxandra; Chen, Alyce A.; Cheng, Jingwei; Correll, Mick; Duarte, Melissa; Fan, Changyu; Feltkamp, Mariet C.; Ficarro, Scott B.; Franchi, Rachel; Garg, Brijesh K.; Gulbahce, Natali; Hao, Tong; Holthaus, Amy M.; James, Robert; Korkhin, Anna; Litovchick, Larisa; Mar, Jessica C.; Pak, Theodore R.; Rabello, Sabrina; Rubio, Renee; Shen, Yun; Singh, Saurav; Spangle, Jennifer M.; Tasan, Murat; Wanamaker, Shelly; Webber, James T.; Roecklein-Canfield, Jennifer; Johannsen, Eric; Barabási, Albert-László; Beroukhim, Rameen; Kieff, Elliott; Cusick, Michael E.; Hill, David E.; Münger, Karl; Marto, Jarrod A.; Quackenbush, John; Roth, Frederick P.; DeCaprio, James A.; Vidal, Marc

    2012-01-01

    Genotypic differences greatly influence susceptibility and resistance to disease. Understanding genotype-phenotype relationships requires that phenotypes be viewed as manifestations of network properties, rather than simply as the result of individual genomic variations1. Genome sequencing efforts have identified numerous germline mutations associated with cancer predisposition and large numbers of somatic genomic alterations2. However, it remains challenging to distinguish between background, or “passenger” and causal, or “driver” cancer mutations in these datasets. Human viruses intrinsically depend on their host cell during the course of infection and can elicit pathological phenotypes similar to those arising from mutations3. To test the hypothesis that genomic variations and tumour viruses may cause cancer via related mechanisms, we systematically examined host interactome and transcriptome network perturbations caused by DNA tumour virus proteins. The resulting integrated viral perturbation data reflects rewiring of the host cell networks, and highlights pathways that go awry in cancer, such as Notch signalling and apoptosis. We show that systematic analyses of host targets of viral proteins can identify cancer genes with a success rate on par with their identification through functional genomics and large-scale cataloguing of tumour mutations. Together, these complementary approaches result in increased specificity for cancer gene identification. Combining systems-level studies of pathogen-encoded gene products with genomic approaches will facilitate prioritization of cancer-causing driver genes so as to advance understanding of the genetic basis of human cancer. PMID:22810586

  11. Genome instability in blood cells of a BRCA1+ breast cancer family

    International Nuclear Information System (INIS)

    BRCA1 plays an essential role in maintaining genome stability. Inherited BRCA1 germline mutation (BRCA1+) is a determined genetic predisposition leading to high risk of breast cancer. While BRCA1+ induces breast cancer by causing genome instability, most of the knowledge is known about somatic genome instability in breast cancer cells but not germline genome instability. Using the exome-sequencing method, we analyzed the genomes of blood cells in a typical BRCA1+ breast cancer family with an exon 13-duplicated founder mutation, including six breast cancer-affected and two breast cancer unaffected members. We identified 23 deleterious mutations in the breast cancer-affected family members, which are absent in the unaffected members. Multiple mutations damaged functionally important and breast cancer-related genes, including transcriptional factor BPTF and FOXP1, ubiquitin ligase CUL4B, phosphorylase kinase PHKG2, and nuclear receptor activator SRA1. Analysis of the mutations between the mothers and daughters shows that most mutations were germline mutation inherited from the ancestor(s) while only a few were somatic mutation generated de novo. Our study indicates that BRCA1+ can cause genome instability with both germline and somatic mutations in non-breast cells

  12. 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.

  13. Mouse models of pancreatic cancer

    Institute of Scientific and Technical Information of China (English)

    Marta Herreros-Villanueva; Elizabeth Hijona; Angel Cosme; Luis Bujanda

    2012-01-01

    Pancreatic cancer is one of the most lethal of human malignancies ranking 4th among cancer-related death in the western world and in the United States,and potent therapeutic options are lacking.Although during the last few years there have been important advances in the understanding of the molecular events responsible for the development of pancreatic cancer,currently specific mechanisms of treatment resistance remain poorly understood and new effective systemic drugs need to be developed and probed.In vivo models to study pancreatic cancer and approach this issue remain limited and present different molecular features that must be considered in the studies depending on the purpose to fit special research themes.In the last few years,several genetically engineered mouse models of pancreatic exocrine neoplasia have been developed.These models mimic the disease as they reproduce genetic alterations implicated in the progression of pancreatic cancer.Genetic alterations such as activating mutations in KRas,or TGFb and/or inactivation of tumoral suppressors such as p53,INK4A/ARF BRCA2 and Smad4 are the most common drivers to pancreatic carcinogenesis and have been used to create transgenic mice.These mouse models have a spectrum of pathologic changes,from pancreatic intraepithelial neoplasia to lesions that progress histologically culminating in fully invasive and metastatic disease and represent the most useful preclinical model system.These models can characterize the cellular and molecular pathology of pancreatic neoplasia and cancer and constitute the best tool to investigate new therapeutic approaches,chemopreventive and/or anticancer treatments.Here,we review and update the current mouse models that reproduce different stages of human pancreatic ductal adenocarcinoma and will have clinical relevance in future pancreatic cancer developments.

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

    Directory of Open Access Journals (Sweden)

    Aaraby Yoheswaran Nielsen

    2016-06-01

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

  15. Targeting the Human Cancer Pathway Protein Interaction Network by Structural Genomics*

    OpenAIRE

    Huang, Yuanpeng Janet; Hang, Dehua; Lu, Long Jason; Tong, Liang; Gerstein, Mark B; Montelione, Gaetano T.

    2008-01-01

    Structural genomics provides an important approach for characterizing and understanding systems biology. As a step toward better integrating protein three-dimensional (3D) structural information in cancer systems biology, we have constructed a Human Cancer Pathway Protein Interaction Network (HCPIN) by analysis of several classical cancer-associated signaling pathways and their physical protein-protein interactions. Many well known cancer-associated proteins play central roles as “hubs” or “b...

  16. 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.; 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; Muller-Myhsok, Bertram; Muranen, Taru A.; Nevanlinna, Heli; Peeters, Petra H.; Peto, Julian; Prentice, Ross L.; Rahman, Nazneen; Sanchez, Maria Jose; Schmidt, Daniel F.; Schmutzler, Rita K.; Southey, Melissa C.; Tamimi, Rulla; Travis, Ruth C.; Turnbull, Clare; Uitterlinden, Andre G.; Wang, Zhaoming; Whittemore, Alice S.; Yang, Xiaohong R.; Zheng, Wei; Buchanan, Daniel D.; Casey, Graham; Conti, David V.; Edlund, Christopher K.; Gallinger, Steven; Haile, Robert W.; Jenkins, Mark; Le Marchand, Loic; 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; Bosse, 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 c

  17. 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 P; Eeles, Rosalind A; Chatterjee, Nilanjan; Schumacher, Fredrick R; Schildkraut, Joellen M; Lindstrom, Sara; Brennan, Paul; Bickeböller, Heike; Houlston, Richard S; Landi, Maria Teresa; Caporaso, Neil E; Risch, Angela; Amin Al Olama, Ali; Berndt, Sonja I; Giovannucci, Edward; 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, Stéphane; Brenner, Hermann; Chan, Andrew T; Chang-Claude, Jenny; Hudson, Thomas J; Kocarnik, Jonathan; 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; 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, Jian Jun; 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 M; Travis, Ruth C; Turnbull, Clare; Uitterlinden, Andre G; Wang, Zhaoming; Whittemore, Alice S; Yang, Xiaohong R; Zheng, Wei; Rafnar, Thorunn; Gudmundsson, Julius; Stacey, Simon N; Stefansson, Kari; Sulem, Patrick; Chen, Y Ann; Tyrer, Jonathan P; Christiani, David C; Wei, Yongyue; Shen, Hongbing; Hu, Zhibin; Shu, Xiao-Ou; Shiraishi, Kouya; Takahashi, Atsushi; Bossé, Yohan; Obeidat, Ma'en; Nickle, David; Timens, Wim; Freedman, Matthew L; Li, Qiyuan; Seminara, Daniela; Chanock, Stephen J; Gong, Jian; Peters, Ulrike; Gruber, Stephen B; Amos, Christopher I; Sellers, Thomas A; Easton, Douglas F; Hunter, David J; Haiman, Christopher A; Henderson, Brian E; Hung, Rayjean J

    2016-01-01

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

  18. 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 a...

  19. Multi-OMICs and Genome Editing Perspectives on Liver Cancer Signaling Networks

    Science.gov (United States)

    Lin, Shengda; Yin, Yi A.; Jiang, Xiaoqian; Sahni, Nidhi; Yi, Song

    2016-01-01

    The advent of the human genome sequence and the resulting ~20,000 genes provide a crucial framework for a transition from traditional biology to an integrative “OMICs” arena (Lander et al., 2001; Venter et al., 2001; Kitano, 2002). This brings in a revolution for cancer research, which now enters a big data era. In the past decade, with the facilitation by next-generation sequencing, there have been a huge number of large-scale sequencing efforts, such as The Cancer Genome Atlas (TCGA), the HapMap, and the 1000 genomes project. As a result, a deluge of genomic information becomes available from patients stricken by a variety of cancer types. The list of cancer-associated genes is ever expanding. New discoveries are made on how frequent and highly penetrant mutations, such as those in the telomerase reverse transcriptase (TERT) and TP53, function in cancer initiation, progression, and metastasis. Most genes with relatively frequent but weakly penetrant cancer mutations still remain to be characterized. In addition, genes that harbor rare but highly penetrant cancer-associated mutations continue to emerge. Here, we review recent advances related to cancer genomics, proteomics, and systems biology and suggest new perspectives in targeted therapy and precision medicine. PMID:27403431

  20. The genomic landscape of breast cancer and its interaction with host immunity.

    Science.gov (United States)

    Luen, Stephen; Virassamy, Balaji; Savas, Peter; Salgado, Roberto; Loi, Sherene

    2016-10-01

    Molecular profiling of thousands of primary breast cancers has uncovered remarkable genomic diversity between breast cancer subtypes, and even within subtypes. Only a few driver genes are recurrently altered at high frequency highlighting great challenges for precision medicine. Considerable evidence also confirms the role of host immunosurveillance in influencing response to therapy and prognosis in HER2+ and triple negative breast cancer. The role of immunosurveillance in ER + disease remains unclear. Advances in both these fields have lead to intensified interest in the interaction between genomic landscapes and host anti-tumour immune responses in breast cancer. In this review, we discuss the potential genomic determinants of host anti-tumour immunity - mutational load, driver alterations, mutational processes and neoantigens - and their relationship with immunity in breast cancer. Significant differences exist in both the genomic and immune characteristics amongst breast cancer subtypes. While ER + disease appears to be less immunogenic than HER2+ and triple negative breast cancer, it displays the greatest degree of heterogeneity. Mutational and neoantigen load appears to incompletely explains immune responses in breast cancer. Driver alterations do not appear to increase immunogenicity. Instead, they could contribute to immune-evasion or an immunosuppressive microenvironment, and therefore represent potential therapeutic targets. Finally, we also discuss the tailoring of immunotherapeutic strategies by genomic alterations, with possible multimodal combination approaches to maximise clinical benefits.

  1. The genomic landscape of breast cancer and its interaction with host immunity.

    Science.gov (United States)

    Luen, Stephen; Virassamy, Balaji; Savas, Peter; Salgado, Roberto; Loi, Sherene

    2016-10-01

    Molecular profiling of thousands of primary breast cancers has uncovered remarkable genomic diversity between breast cancer subtypes, and even within subtypes. Only a few driver genes are recurrently altered at high frequency highlighting great challenges for precision medicine. Considerable evidence also confirms the role of host immunosurveillance in influencing response to therapy and prognosis in HER2+ and triple negative breast cancer. The role of immunosurveillance in ER + disease remains unclear. Advances in both these fields have lead to intensified interest in the interaction between genomic landscapes and host anti-tumour immune responses in breast cancer. In this review, we discuss the potential genomic determinants of host anti-tumour immunity - mutational load, driver alterations, mutational processes and neoantigens - and their relationship with immunity in breast cancer. Significant differences exist in both the genomic and immune characteristics amongst breast cancer subtypes. While ER + disease appears to be less immunogenic than HER2+ and triple negative breast cancer, it displays the greatest degree of heterogeneity. Mutational and neoantigen load appears to incompletely explains immune responses in breast cancer. Driver alterations do not appear to increase immunogenicity. Instead, they could contribute to immune-evasion or an immunosuppressive microenvironment, and therefore represent potential therapeutic targets. Finally, we also discuss the tailoring of immunotherapeutic strategies by genomic alterations, with possible multimodal combination approaches to maximise clinical benefits. PMID:27481651

  2. Mutational and structural analysis of diffuse large B-cell lymphoma using whole genome sequencing | Office of Cancer Genomics

    Science.gov (United States)

    Abstract: Diffuse large B-cell lymphoma (DLBCL) is a genetically heterogeneous cancer comprising at least two molecular subtypes that differ in gene expression and distribution of mutations. Recently, application of genome/exome sequencing and RNA-seq to DLBCL has revealed numerous genes that are recurrent targets of somatic point mutation in this disease.

  3. BiGG Models: A platform for integrating, standardizing and sharing genome-scale models

    DEFF Research Database (Denmark)

    2016-01-01

    redesigned Biochemical, Genetic and Genomic knowledge base. BiGG Models contains more than 75 high-quality, manually-curated genome-scale metabolic models. On the website, users can browse, search and visualize models. BiGG Models connects genome-scale models to genome annotations and external databases...... for highly curated, standardized and accessible models of metabolism, BiGG Models will facilitate diverse systems biology studies and support knowledge-based analysis of diverse experimental data....

  4. Computational discovery of pathway-level genetic vulnerabilities in non-small-cell lung cancer | Office of Cancer Genomics

    Science.gov (United States)

    Novel approaches are needed for discovery of targeted therapies for non-small-cell lung cancer (NSCLC) that are specific to certain patients. Whole genome RNAi screening of lung cancer cell lines provides an ideal source for determining candidate drug targets. Unsupervised learning algorithms uncovered patterns of differential vulnerability across lung cancer cell lines to loss of functionally related genes. Such genetic vulnerabilities represent candidate targets for therapy and are found to be involved in splicing, translation and protein folding.

  5. Clinical implications of genomic alterations in the tumour and circulation of pancreatic cancer patients

    DEFF Research Database (Denmark)

    Sausen, Mark; Phallen, Jillian; Adleff, Vilmos;

    2015-01-01

    Pancreatic adenocarcinoma has the worst mortality of any solid cancer. In this study, to evaluate the clinical implications of genomic alterations in this tumour type, we perform whole-exome analyses of 24 tumours, targeted genomic analyses of 77 tumours, and use non-invasive approaches to examine...... imaging. These observations provide genetic predictors of outcome in pancreatic cancer and have implications for new avenues of therapeutic intervention....

  6. Pre-Diagnostic Leukocyte Genomic DNA Methylation and the Risk of Colorectal Cancer in Women

    OpenAIRE

    Hongmei Nan; Giovannucci, Edward L; Kana Wu; Jacob Selhub; Ligi Paul; Bernard Rosner; Fuchs, Charles S; Eunyoung Cho

    2013-01-01

    BACKGROUND: Abnormal one-carbon metabolism may lead to general genomic (global) hypomethylation, which may predispose an individual to the development of colorectal neoplasia. METHODS: We evaluated the association between pre-diagnostic leukocyte genomic DNA methylation level and the risk of colorectal cancer in a nested case-control study of 358 colorectal cancer cases and 661 matched controls within the all-female cohort of the Nurses' Health Study (NHS). Among control subjects, we further ...

  7. Whole genome sequencing defines the genetic heterogeneity of familial pancreatic cancer

    Science.gov (United States)

    Roberts, Nicholas J.; Norris, Alexis L.; Petersen, Gloria M.; Bondy, Melissa L.; Brand, Randall; Gallinger, Steven; Kurtz, Robert C.; Olson, Sara H.; Rustgi, Anil K.; Schwartz, Ann G.; Stoffel, Elena; Syngal, Sapna; Zogopoulos, George; Ali, Syed Z.; Axilbund, Jennifer; Chaffee, Kari G.; Chen, Yun-Ching; Cote, Michele L.; Childs, Erica J.; Douville, Christopher; Goes, Fernando S.; Herman, Joseph M.; Iacobuzio-Donahue, Christine; Kramer, Melissa; Makohon-Moore, Alvin; McCombie, Richard W.; McMahon, K. Wyatt; Niknafs, Noushin; Parla, Jennifer; Pirooznia, Mehdi; Potash, James B.; Rhim, Andrew D.; Smith, Alyssa L.; Wang, Yuxuan; Wolfgang, Christopher L.; Wood, Laura D.; Zandi, Peter P.; Goggins, Michael; Karchin, Rachel; Eshleman, James R.; Papadopoulos, Nickolas; Kinzler, Kenneth W.; Vogelstein, Bert; Hruban, Ralph H.; Klein, Alison P.

    2015-01-01

    Pancreatic cancer is projected to become the second leading cause of cancer-related death in the United States by 2020. A familial aggregation of pancreatic cancer has been established, but the cause of this aggregation in most families is unknown. To determine the genetic basis of susceptibility in these families, we sequenced the germline genome of 638 familial pancreatic cancer patients. We also sequenced the exomes of 39 familial pancreatic adenocarcinomas. Our analyses support the role of previously identified familial pancreatic cancer susceptibility genes such as BRCA2, CDKN2A and ATM, and identify novel candidate genes harboring rare, deleterious germline variants for further characterization. We also show how somatic point mutations that occur during hematopoiesis can affect the interpretation of genome-wide studies of hereditary traits. Our observations have important implications for the etiology of pancreatic cancer and for the identification of susceptibility genes in other common cancer types. PMID:26658419

  8. Inferences of drug responses in cancer cells from cancer genomic features and compound chemical and therapeutic properties

    Science.gov (United States)

    Wang, Yongcui; Fang, Jianwen; Chen, Shilong

    2016-01-01

    Accurately predicting the response of a cancer patient to a therapeutic agent is a core goal of precision medicine. Existing approaches were mainly relied primarily on genomic alterations in cancer cells that have been treated with different drugs. Here we focus on predicting drug response based on integration of the heterogeneously pharmacogenomics data from both cell and drug sides. Through a systematical approach, named as PDRCC (Predict Drug Response in Cancer Cells), the cancer genomic alterations and compound chemical and therapeutic properties were incorporated to determine the chemotherapeutic response in cancer patients. Using the Cancer Cell Line Encyclopedia (CCLE) study as the benchmark dataset, all pharmacogenomics data exhibited their roles in inferring the relationships between cancer cells and drugs. When integrating both genomic resources and compound information, the prediction coverage was significantly increased. The validity of PDRCC was also supported by its effective in uncovering the unknown cell-drug associations with database and literature evidences. It set the stage for clinical testing of novel therapeutic strategies, such as the sensitive association between cancer cell ‘A549_LUNG’ and compound ‘Topotecan’. In conclusion, PDRCC offers the possibility for faster, safer, and cheaper the development of novel anti-cancer therapeutics in the early-stage clinical trails. PMID:27645580

  9. The Cancer Genome Anatomy Project: EST Sequencing and the Genetics of Cancer Progression

    Directory of Open Access Journals (Sweden)

    David B. Krizman

    1999-06-01

    Full Text Available As the process of tumor progression proceeds from the normal cellular state to a preneoplastic condition and finally to the fully invasive form, the molecular characteristics of the cell change as well. These characteristics can be considered a molecular fingerprint of the cell at each stage of progression and, analogous to fingerprinting a criminal, can be used as markers of the progression process. Based on this premise, the Cancer Genome Anatomy Project was initiated with the broad goal of determining the comprehensive molecular characterization of normal, premalignant, and malignant tumor cells, thus making a reality the identification of all major cellular mechanisms leading to tumor initiation and progression ([Strausberg, R.L., Dahl, C.A., and Klausner, R.D. (1997. “New opportunities for uncovering the molecular basis of cancer.” Nat. Genet., 16: 415-516.], www.ncbi.nlm.nih.gov/ncicgap/. The expectation of determining the genetic fingerprints of cancer progression will allow for 1 correlation of disease progression with therapeutic outcome; 2 improved evaluation of disease treatment; 3 stimulation of novel approaches to prevention, detection, and therapy; and 4 enhanced diagnostic tools for clinical applications. Whereas acquiring the comprehensive molecular analysis of cancer progression may take years, results from initial, short-term goals are currently being realized and are proving very fruitful.

  10. Genome-scale models of bacterial metabolism: reconstruction and applications

    OpenAIRE

    Durot, Maxime; Bourguignon, Pierre-Yves; Schachter, Vincent

    2008-01-01

    Genome-scale metabolic models bridge the gap between genome-derived biochemical information and metabolic phenotypes in a principled manner, providing a solid interpretative framework for experimental data related to metabolic states, and enabling simple in silico experiments with whole-cell metabolism. Models have been reconstructed for almost 20 bacterial species, so far mainly through expert curation efforts integrating information from the literature with genome annotation. A wide variety...

  11. Sequence modelling and an extensible data model for genomic database

    Energy Technology Data Exchange (ETDEWEB)

    Li, Peter Wei-Der (California Univ., San Francisco, CA (United States) Lawrence Berkeley Lab., CA (United States))

    1992-01-01

    The Human Genome Project (HGP) plans to sequence the human genome by the beginning of the next century. It will generate DNA sequences of more than 10 billion bases and complex marker sequences (maps) of more than 100 million markers. All of these information will be stored in database management systems (DBMSs). However, existing data models do not have the abstraction mechanism for modelling sequences and existing DBMS's do not have operations for complex sequences. This work addresses the problem of sequence modelling in the context of the HGP and the more general problem of an extensible object data model that can incorporate the sequence model as well as existing and future data constructs and operators. First, we proposed a general sequence model that is application and implementation independent. This model is used to capture the sequence information found in the HGP at the conceptual level. In addition, abstract and biological sequence operators are defined for manipulating the modelled sequences. Second, we combined many features of semantic and object oriented data models into an extensible framework, which we called the Extensible Object Model'', to address the need of a modelling framework for incorporating the sequence data model with other types of data constructs and operators. This framework is based on the conceptual separation between constructors and constraints. We then used this modelling framework to integrate the constructs for the conceptual sequence model. The Extensible Object Model is also defined with a graphical representation, which is useful as a tool for database designers. Finally, we defined a query language to support this model and implement the query processor to demonstrate the feasibility of the extensible framework and the usefulness of the conceptual sequence model.

  12. Sequence modelling and an extensible data model for genomic database

    Energy Technology Data Exchange (ETDEWEB)

    Li, Peter Wei-Der [California Univ., San Francisco, CA (United States)]|[Lawrence Berkeley Lab., CA (United States)

    1992-01-01

    The Human Genome Project (HGP) plans to sequence the human genome by the beginning of the next century. It will generate DNA sequences of more than 10 billion bases and complex marker sequences (maps) of more than 100 million markers. All of these information will be stored in database management systems (DBMSs). However, existing data models do not have the abstraction mechanism for modelling sequences and existing DBMS`s do not have operations for complex sequences. This work addresses the problem of sequence modelling in the context of the HGP and the more general problem of an extensible object data model that can incorporate the sequence model as well as existing and future data constructs and operators. First, we proposed a general sequence model that is application and implementation independent. This model is used to capture the sequence information found in the HGP at the conceptual level. In addition, abstract and biological sequence operators are defined for manipulating the modelled sequences. Second, we combined many features of semantic and object oriented data models into an extensible framework, which we called the ``Extensible Object Model``, to address the need of a modelling framework for incorporating the sequence data model with other types of data constructs and operators. This framework is based on the conceptual separation between constructors and constraints. We then used this modelling framework to integrate the constructs for the conceptual sequence model. The Extensible Object Model is also defined with a graphical representation, which is useful as a tool for database designers. Finally, we defined a query language to support this model and implement the query processor to demonstrate the feasibility of the extensible framework and the usefulness of the conceptual sequence model.

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

    Directory of Open Access Journals (Sweden)

    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

  14. Genomic analyses identify molecular subtypes of pancreatic cancer.

    Science.gov (United States)

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

    2016-03-01

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

  15. Using the canine genome to cure cancer and other diseases.

    Science.gov (United States)

    Olson, P N

    2007-08-01

    A high-quality draft genome sequence of the domestic dog (Canis familiaris), together with a dense map of single nucleotide polymorphisms, has been reported. Such new tools offer scientists amazing opportunities to define genetic, nutritional, environmental, and other risk factors for various canine diseases. Because many of the diseases that affect man's best friend also affect us, understanding a dog's disease may lead to new preventions and therapies for diseases that affect both dogs and people. Since a dog's life span is shorter than that for a human, monitoring potential risk factors in a well-controlled population of dogs is possible. Such a population should be one where dogs live in close relationship with their owners. Although longitudinal studies have been previously conducted on animals housed in laboratory environments, the natural environment offers a chance to study dogs in environments shared by their owners. If dogs are carefully monitored, and select exposures defined, considerable information could be collected in a dog's lifetime--the next 10-20 years. Such information could hold the clues for important discoveries, including causes and cures for cancer. PMID:17498794

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

    Science.gov (United States)

    Silverstein, Allison; Sood, Rachita; Costas-Chavarri, Ainhoa

    2016-01-01

    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. PMID:27413551

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

    Directory of Open Access Journals (Sweden)

    Allison Silverstein

    2016-01-01

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

  18. Colon Cancer-associated DNA Polymerase β Variant Induces Genomic Instability and Cellular Transformation*

    Science.gov (United States)

    Nemec, Antonia A.; Donigan, Katherine A.; Murphy, Drew L.; Jaeger, Joachim; Sweasy, Joann B.

    2012-01-01

    Rapidly advancing technology has resulted in the generation of the genomic sequences of several human tumors. We have identified several mutations of the DNA polymerase β (pol β) gene in human colorectal cancer. We have demonstrated that the expression of the pol β G231D variant increased chromosomal aberrations and induced cellular transformation. The transformed phenotype persisted in the cells even once the expression of G231D was extinguished, suggesting that it resulted as a consequence of genomic instability. Biochemical analysis revealed that its catalytic rate was 140-fold slower than WT pol β, and this was a result of the decreased binding affinity of nucleotides by G231D. Residue 231 of pol β lies in close proximity to the template strand of the DNA. Molecular modeling demonstrated that the change from a small and nonpolar glycine to a negatively charged aspartate resulted in a repulsion between the template and residue 231 leading to the distortion of the dNTP binding pocket. In addition, expression of G231D was insufficient to rescue pol β-deficient cells treated with chemotherapeutic agents suggesting that these agents may be effectively used to treat tumors harboring this mutation. More importantly, this suggests that the G231D variant has impaired base excision repair. Together, these data indicate that the G231D variant plays a role in driving cancer. PMID:22573322

  19. An Integrative Breakage Model of genome architecture, reshuffling and evolution: The Integrative Breakage Model of genome evolution, a novel multidisciplinary hypothesis for the study of genome plasticity.

    Science.gov (United States)

    Farré, Marta; Robinson, Terence J; Ruiz-Herrera, Aurora

    2015-05-01

    Our understanding of genomic reorganization, the mechanics of genomic transmission to offspring during germ line formation, and how these structural changes contribute to the speciation process, and genetic disease is far from complete. Earlier attempts to understand the mechanism(s) and constraints that govern genome remodeling suffered from being too narrowly focused, and failed to provide a unified and encompassing view of how genomes are organized and regulated inside cells. Here, we propose a new multidisciplinary Integrative Breakage Model for the study of genome evolution. The analysis of the high-level structural organization of genomes (nucleome), together with the functional constrains that accompany genome reshuffling, provide insights into the origin and plasticity of genome organization that may assist with the detection and isolation of therapeutic targets for the treatment of complex human disorders.

  20. Public stated preferences and predicted uptake for genome-based colorectal cancer screening

    NARCIS (Netherlands)

    Groothuis-Oudshoorn, Catharina G.M.; Fermont, Jilles M.; Til, van Janine A.; IJzerman, Maarten J.

    2014-01-01

    Background Emerging developments in nanomedicine allow the development of genome-based technologies for non-invasive and individualised screening for diseases such as colorectal cancer. The main objective of this study was to measure user preferences for colorectal cancer screening using a nanopill.

  1. BYSTANDERS, ADAPTIVE RESPONSES AND GENOMIC INSTABILITY - POTENTIAL MODIFIERS OF LOW-DOSE CANCER RESPONSES.

    Science.gov (United States)

    Bystanders, Adaptive Responses and Genomic Instability -Potential Modifiers ofLow-DoseCancer Responses.There has been a concerted effort in the field of radiation biology to better understand cellularresponses that could have an impact on the estin1ation of cancer...

  2. DNA copy number aberrations in breast cancer by array comparative genomic hybridization

    DEFF Research Database (Denmark)

    Li, J.; Wang, K.; Li, S.;

    2009-01-01

    Array comparative genomic hybridization (CGH) has been popularly used for analyzing DNA copy number variations in diseases like cancer. In this study, we investigated 82 sporadic samples from 49 breast cancer patients using 1-Mb resolution bacterial artificial chromosome CGH arrays. A number...

  3. Seven prostate cancer susceptibility loci identified by a multi-stage genome-wide association study

    DEFF Research Database (Denmark)

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

    2011-01-01

    Prostate cancer (PrCa) is the most frequently diagnosed male cancer in developed countries. We conducted a multi-stage genome-wide association study for PrCa and previously reported the results of the first two stages, which identified 16 PrCa susceptibility loci. We report here the results...

  4. Seven prostate cancer susceptibility loci identified by a multi-stage genome-wide association study

    DEFF Research Database (Denmark)

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

    2011-01-01

    Prostate cancer (PrCa) is the most frequently diagnosed male cancer in developed countries. We conducted a multi-stage genome-wide association study for PrCa and previously reported the results of the first two stages, which identified 16 PrCa susceptibility loci. We report here the results of st...

  5. Genome Informed Trait-Based Models

    Science.gov (United States)

    Karaoz, U.; Cheng, Y.; Bouskill, N.; Tang, J.; Beller, H. R.; Brodie, E.; Riley, W. J.

    2013-12-01

    Trait-based approaches are powerful tools for representing microbial communities across both spatial and temporal scales within ecosystem models. Trait-based models (TBMs) represent the diversity of microbial taxa as stochastic assemblages with a distribution of traits constrained by trade-offs between these traits. Such representation with its built-in stochasticity allows the elucidation of the interactions between the microbes and their environment by reducing the complexity of microbial community diversity into a limited number of functional ';guilds' and letting them emerge across spatio-temporal scales. From the biogeochemical/ecosystem modeling perspective, the emergent properties of the microbial community could be directly translated into predictions of biogeochemical reaction rates and microbial biomass. The accuracy of TBMs depends on the identification of key traits of the microbial community members and on the parameterization of these traits. Current approaches to inform TBM parameterization are empirical (i.e., based on literature surveys). Advances in omic technologies (such as genomics, metagenomics, metatranscriptomics, and metaproteomics) pave the way to better-initialize models that can be constrained in a generic or site-specific fashion. Here we describe the coupling of metagenomic data to the development of a TBM representing the dynamics of metabolic guilds from an organic carbon stimulated groundwater microbial community. Illumina paired-end metagenomic data were collected from the community as it transitioned successively through electron-accepting conditions (nitrate-, sulfate-, and Fe(III)-reducing), and used to inform estimates of growth rates and the distribution of metabolic pathways (i.e., aerobic and anaerobic oxidation, fermentation) across a spatially resolved TBM. We use this model to evaluate the emergence of different metabolisms and predict rates of biogeochemical processes over time. We compare our results to observational

  6. Possible role of the WDR3 gene on genome stability in thyroid cancer patients.

    Directory of Open Access Journals (Sweden)

    Wilser Andrés García-Quispes

    Full Text Available The role of the WDR3 gene on genomic instability has been evaluated in a group of 115 differentiated thyroid cancer (DTC patients. Genomic instability has been measured according to the response of peripheral blood lymphocytes to ionizing radiation (0.5 Gy. The response has been measured with the micronucleus (MN test evaluating the frequency of binucleated cells with MN (BNMN, both before and after the irradiation. No differences between genotypes, for the BNMN frequencies previous the irradiation, were observed. Nevertheless significant decreases in DNA damage after irradiation were observed in individuals carrying the variant alleles for each of the three genotyped SNPs: rs3754127 [-8.85 (-15.01 to -2.70, P<0.01]; rs3765501 [-8.98 (-15.61 to -2.36, P<0.01]; rs4658973 [-8.70 (-14.94 to -2.46, P<0.01]. These values correspond to those obtained assuming a dominant model. This study shows for the first time that WDR3 can modulate genome stability.

  7. ANIMAL MODELS OF CANCER: A REVIEW

    OpenAIRE

    Archana M Navale

    2013-01-01

    Cancer is the second leading cause of death worldwide. In USA three persons out of five will develop some type of cancer. Beyond these statistics of mortality, the morbidity due to cancer presents a real scary picture. Last 50 years of research has rendered some types of cancer curable, but still the major fear factor associated with this disease is unchanged. Animal models are classified according to the method of induction of cancer in the animal. Spontaneous tumor models are the most primi...

  8. Facilitating a Culture of Responsible and Effective Sharing of Cancer Genome Data

    Science.gov (United States)

    Siu, Lillian L.; Lawler, Mark; Haussler, David; Knoppers, Bartha Maria; Lewin, Jeremy; Vis, Daniel J.; Liao, Rachel G.; Andre, Fabrice; Banks, Ian; Barrett, J. Carl; Caldas, Carlos; Camargo, Anamaria Aranha; Fitzgerald, Rebecca C.; Mao, Mao; Mattison, John E.; Pao, William; Sellers, William R.; Sullivan, Patrick; Teh, Bin Tean; Ward, Robyn; ZenKlusen, Jean Claude; Sawyers, Charles L; Voest, Emile E.

    2016-01-01

    Rapid and affordable tumor molecular profiling has led to an explosion of clinical and genomic data poised to enhance diagnosis, prognostication and treatment of cancer. A critical point has now been reached where analysis and storage of annotated clinical and genomic information in unconnected silos will stall the advancement of precision cancer care. Information systems must be harmonized to overcome the multiple technical and logistical barriers for data sharing. Against this backdrop, the Global Alliance for Genomic Health (GA4GH) was established in 2013 to create a common framework that enables responsible, voluntary, and secure sharing of clinical and genomic data. This Perspective from the GA4GH Clinical Working Group Cancer Task Team highlights the data aggregation challenges faced by the field, suggests potential collaborative solutions, and describes how GA4GH can catalyze a harmonized data sharing culture. PMID:27149219

  9. Cancer core modules identification through genomic and transcriptomic changes correlation detection at network level

    Directory of Open Access Journals (Sweden)

    Li Wenting

    2012-06-01

    Full Text Available Abstract Background Identification of driver mutations among numerous genomic alternations remains a critical challenge to the elucidation of the underlying mechanisms of cancer. Because driver mutations by definition are associated with a greater number of cancer phenotypes compared to other mutations, we hypothesized that driver mutations could more easily be identified once the genotype-phenotype correlations are detected across tumor samples. Results In this study, we describe a novel network analysis to identify the driver mutation through integrating both cancer genomes and transcriptomes. Our method successfully identified a significant genotype-phenotype change correlation in all six solid tumor types and revealed core modules that contain both significantly enriched somatic mutations and aberrant expression changes specific to tumor development. Moreover, we found that the majority of these core modules contained well known cancer driver mutations, and that their mutated genes tended to occur at hub genes with central regulatory roles. In these mutated genes, the majority were cancer-type specific and exhibited a closer relationship within the same cancer type rather than across cancer types. The remaining mutated genes that exist in multiple cancer types led to two cancer type clusters, one cluster consisted of three neural derived or related cancer types, and the other cluster consisted of two adenoma cancer types. Conclusions Our approach can successfully identify the candidate drivers from the core modules. Comprehensive network analysis on the core modules potentially provides critical insights into convergent cancer development in different organs.

  10. DNA Copy Number Aberrations in Breast Cancer by Array Comparative Genomic Hybridization

    Institute of Scientific and Technical Information of China (English)

    Jian Li; Kai Wang; Shengting Li; Vera Timmermans-Wielenga; Fritz Rank; Carsten Wiuf; Xiuqing Zhang; Huanming Yang; Lars Bolund

    2009-01-01

    Array comparative genomic hybridization (CGH) has been popularly used for an-alyzing DNA copy number variations in diseases like cancer. In this study, we investigated 82 sporadic samples from 49 breast cancer patients using 1-Mb reso-lution bacterial artificial chromosome CGH arrays. A number of highly frequent genomic aberrations were discovered, which may act as "drivers" of tumor pro-gression. Meanwhile, the genomic profiles of four "normal" breast tissue samples taken at least 2 cm away from the primary tumor sites were also found to have some genomic aberrations that recurred with high frequency in the primary tu-mors, which may have important implications for clinical therapy. Additionally, we performed class comparison and class prediction for various clinicopathological pa-rameters, and a list of characteristic genomic aberrations associated with different clinicopathological phenotypes was compiled. Our study provides clues for further investigations of the underlying mechanisms of breast carcinogenesis.

  11. Characterization of HPV and host genome interactions in primary head and neck cancers

    Science.gov (United States)

    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

  12. Colorectal cancer and the human gut microbiome: reproducibility with whole-genome shotgun sequencing

    OpenAIRE

    Emily Vogtmann; Xing Hua; Georg Zeller; Shinichi Sunagawa; Voigt, Anita Y.; Rajna Hercog; Goedert, James J.; Jianxin Shi; Peer Bork; Rashmi Sinha

    2016-01-01

    Accumulating evidence indicates that the gut microbiota affects colorectal cancer development, but previous studies have varied in population, technical methods, and associations with cancer. Understanding these variations is needed for comparisons and for potential pooling across studies. Therefore, we performed whole-genome shotgun sequencing on fecal samples from 52 pre-treatment colorectal cancer cases and 52 matched controls from Washington, DC. We compared findings from a previously pub...

  13. Genomic profiling identifies TITF1 as a lineage-specific oncogene amplified in lung cancer

    OpenAIRE

    Kwei, KA; Kim, YH; Girard, L; Kao, J; Pacyna-Gengelbach, M; Salari, K; Lee, J.; Choi, Y-L; Sato, M.; Wang, P.; Hernandez-Boussard, T; Gazdar, AF; Petersen, I. (Inga); Minna, JD; Pollack, JR

    2008-01-01

    Lung cancer is a leading cause of cancer death, where the amplification of oncogenes contributes to tumorigenesis. Genomic profiling of 128 lung cancer cell lines and tumors revealed frequent focal DNA amplification at cytoband 14q13.3, a locus not amplified in other tumor types. The smallest region of recurrent amplification spanned the homeobox transcription factor TITF1 (thyroid transcription factor 1; also called NKX2-1), previously linked to normal lung development and function. When amp...

  14. High-Resolution Comparative Genomic Hybridization of Inflammatory Breast Cancer and Identification of Candidate Genes

    OpenAIRE

    Bekhouche, Ismahane; Finetti, Pascal; Adelaïde, José; Ferrari, Anthony; Tarpin, Carole; Charafe-Jauffret, Emmanuelle; Charpin, Colette; Houvenaeghel, Gilles; Jacquemier, Jocelyne; Bidaut, Ghislain; Birnbaum, Daniel; Viens, Patrice; Chaffanet, Max; Bertucci, François

    2011-01-01

    Background Inflammatory breast cancer (IBC) is an aggressive form of BC poorly defined at the molecular level. We compared the molecular portraits of 63 IBC and 134 non-IBC (nIBC) clinical samples. Methodology/Findings Genomic imbalances of 49 IBCs and 124 nIBCs were determined using high-resolution array-comparative genomic hybridization, and mRNA expression profiles of 197 samples using whole-genome microarrays. Genomic profiles of IBCs were as heterogeneous as those of nIBCs, and globally ...

  15. 13A. Integrative Cancer Care: The Life Over Cancer Model

    OpenAIRE

    Block, Keith; Block, Penny; Gyllenhaal, Charlotte; Shoham, Jacob

    2013-01-01

    Focus Areas: Integrative Algorithms of Care Integrative cancer treatment fully blends conventional cancer treatment with integrative therapies such as diet, supplements, exercise and biobehavioral approaches. The Life Over Cancer model comprises three spheres of intervention: improving lifestyle, improving biochemical environment (terrain), and improving tolerance of conventional treatment. These levels are applied within the context of a life-affirming approach to cancer patients and treatme...

  16. Mathematical and Statistical Modeling in Cancer Systems Biology

    Directory of Open Access Journals (Sweden)

    Rachael eHageman Blair

    2012-06-01

    Full Text Available Cancer is a major health problem with high mortality rates. In the post-genome era, investigators have access to massive amounts of rapidly accumulating high-throughput data in publicly available databases, some of which are exclusively devoted to housing Cancer data. However, data interpretation efforts have not kept pace with data collection, and gained knowledge is not necessarily translating into better diagnoses and treatments. A fundamental problem is to integrate and interpret data to further our understanding in Cancer Systems Biology. Viewing cancer as a network provides insights into the complex mechanisms underlying the disease. Mathematical and statistical models provide an avenue for cancer network modeling. In this article, we review two widely used modeling paradigms: deterministic metabolic models and statistical graphical models. The strength of these approaches lies in their flexibility and predictive power. Once a model has been validated, it can be used to make predictions and generate hypotheses. We describe a number of diverse applications to Cancer Biology, including, the system-wide effects of drug-treatments, disease prognosis, tumor classification, forecasting treatment outcomes, and survival predictions.

  17. Modeling Lactococcus lactis using a genome-scale flux model

    Directory of Open Access Journals (Sweden)

    Nielsen Jens

    2005-06-01

    Full Text Available Abstract Background Genome-scale flux models are useful tools to represent and analyze microbial metabolism. In this work we reconstructed the metabolic network of the lactic acid bacteria Lactococcus lactis and developed a genome-scale flux model able to simulate and analyze network capabilities and whole-cell function under aerobic and anaerobic continuous cultures. Flux balance analysis (FBA and minimization of metabolic adjustment (MOMA were used as modeling frameworks. Results The metabolic network was reconstructed using the annotated genome sequence from L. lactis ssp. lactis IL1403 together with physiological and biochemical information. The established network comprised a total of 621 reactions and 509 metabolites, representing the overall metabolism of L. lactis. Experimental data reported in the literature was used to fit the model to phenotypic observations. Regulatory constraints had to be included to simulate certain metabolic features, such as the shift from homo to heterolactic fermentation. A minimal medium for in silico growth was identified, indicating the requirement of four amino acids in addition to a sugar. Remarkably, de novo biosynthesis of four other amino acids was observed even when all amino acids were supplied, which is in good agreement with experimental observations. Additionally, enhanced metabolic engineering strategies for improved diacetyl producing strains were designed. Conclusion The L. lactis metabolic network can now be used for a better understanding of lactococcal metabolic capabilities and potential, for the design of enhanced metabolic engineering strategies and for integration with other types of 'omic' data, to assist in finding new information on cellular organization and function.

  18. The Role of Genomic Profiling in Advanced Breast Cancer: The Two Faces of Janus

    Science.gov (United States)

    Eralp, Yesim

    2016-01-01

    Recent advances in genomic technology have led to considerable improvement in our understanding of the molecular basis that underpins breast cancer biology. Through the use of comprehensive whole genome genomic profiling by next-generation sequencing, an unprecedented bulk of data on driver mutations, key genomic rearrangements, and mechanisms on tumor evolution has been generated. These developments have marked the beginning of a new era in oncology called “personalized or precision medicine.” Elucidation of biologic mechanisms that underpin carcinogenetic potential and metastatic behavior has led to an inevitable explosion in the development of effective targeted agents, many of which have gained approval over the past decade. Despite energetic efforts and the enormous support gained within the oncology community, there are many obstacles in the clinical implementation of precision medicine. Other than the well-known biologic markers, such as ER and Her-2/neu, no proven predictive marker exists to determine the responsiveness to a certain biologic agent. One of the major issues in this regard is teasing driver mutations among the background noise within the bulk of coexisting passenger mutations. Improving bioinformatics tools through electronic models, enhanced by improved insight into pathway dependency may be the step forward to overcome this problem. Next, is the puzzle on spatial and temporal tumoral heterogeneity, which remains to be solved by ultra-deep sequencing and optimizing liquid biopsy techniques. Finally, there are multiple logistical and financial issues that have to be meticulously tackled in order to optimize the use of “precision medicine” in the real-life setting. PMID:27547031

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

    International Nuclear Information System (INIS)

    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

  20. Genome sequence analysis of the model grass Brachypodium distachyon: insights into grass genome evolution

    Energy Technology Data Exchange (ETDEWEB)

    Schulman, Al

    2009-08-09

    Three subfamilies of grasses, the Erhardtoideae (rice), the Panicoideae (maize, sorghum, sugar cane and millet), and the Pooideae (wheat, barley and cool season forage grasses) provide the basis of human nutrition and are poised to become major sources of renewable energy. Here we describe the complete genome sequence of the wild grass Brachypodium distachyon (Brachypodium), the first member of the Pooideae subfamily to be completely sequenced. Comparison of the Brachypodium, rice and sorghum genomes reveals a precise sequence- based history of genome evolution across a broad diversity of the grass family and identifies nested insertions of whole chromosomes into centromeric regions as a predominant mechanism driving chromosome evolution in the grasses. The relatively compact genome of Brachypodium is maintained by a balance of retroelement replication and loss. The complete genome sequence of Brachypodium, coupled to its exceptional promise as a model system for grass research, will support the development of new energy and food crops

  1. Are sites with multiple single nucleotide variants in cancer genomes a consequence of drivers, hypermutable sites or sequencing errors?

    Science.gov (United States)

    Carr, Antony M.

    2016-01-01

    Across independent cancer genomes it has been observed that some sites have been recurrently hit by single nucleotide variants (SNVs). Such recurrently hit sites might be either (i) drivers of cancer that are postively selected during oncogenesis, (ii) due to mutation rate variation, or (iii) due to sequencing and assembly errors. We have investigated the cause of recurrently hit sites in a dataset of >3 million SNVs from 507 complete cancer genome sequences. We find evidence that many sites have been hit significantly more often than one would expect by chance, even taking into account the effect of the adjacent nucleotides on the rate of mutation. We find that the density of these recurrently hit sites is higher in non-coding than coding DNA and hence conclude that most of them are unlikely to be drivers. We also find that most of them are found in parts of the genome that are not uniquely mappable and hence are likely to be due to mapping errors. In support of the error hypothesis, we find that recurently hit sites are not randomly distributed across sequences from different laboratories. We fit a model to the data in which the rate of mutation is constant across sites but the rate of error varies. This model suggests that ∼4% of all SNVs are errors in this dataset, but that the rate of error varies by thousands-of-fold between sites.

  2. Genome Editing of Structural Variations: Modeling and Gene Correction.

    Science.gov (United States)

    Park, Chul-Yong; Sung, Jin Jea; Kim, Dong-Wook

    2016-07-01

    The analysis of chromosomal structural variations (SVs), such as inversions and translocations, was made possible by the completion of the human genome project and the development of genome-wide sequencing technologies. SVs contribute to genetic diversity and evolution, although some SVs can cause diseases such as hemophilia A in humans. Genome engineering technology using programmable nucleases (e.g., ZFNs, TALENs, and CRISPR/Cas9) has been rapidly developed, enabling precise and efficient genome editing for SV research. Here, we review advances in modeling and gene correction of SVs, focusing on inversion, translocation, and nucleotide repeat expansion. PMID:27016031

  3. A Probabilistic Genome-Wide Gene Reading Frame Sequence Model

    DEFF Research Database (Denmark)

    Have, Christian Theil; Mørk, Søren

    using the probabilistic logic programming language and machine learning system PRISM - a fast and efficient model prototyping environment, using bacterial gene finding performance as a benchmark of signal strength. The model is used to prune a set of gene predictions from an underlying gene finder...... and are evaluated by the effect on prediction performance. Since bacterial gene finding to a large extent is a solved problem it forms an ideal proving ground for evaluating the explicit modeling of larger scale gene sequence composition of genomes. We conclude that the sequential composition of gene reading frames......We introduce a new type of probabilistic sequence model, that model the sequential composition of reading frames of genes in a genome. Our approach extends gene finders with a model of the sequential composition of genes at the genome-level -- effectively producing a sequential genome annotation...

  4. Microbial comparative pan-genomics using binomial mixture models

    DEFF Research Database (Denmark)

    Ussery, David; Snipen, L; Almøy, T

    2009-01-01

    The size of the core- and pan-genome of bacterial species is a topic of increasing interest due to the growing number of sequenced prokaryote genomes, many from the same species. Attempts to estimate these quantities have been made, using regression methods or mixture models. We extend the latter...

  5. Development of cancer-initiating cells and immortalized cells with genomic instability.

    Science.gov (United States)

    Yoshioka, Ken-Ichi; Atsumi, Yuko; Nakagama, Hitoshi; Teraoka, Hirobumi

    2015-03-26

    Cancers that develop after middle age usually exhibit genomic instability and multiple mutations. This is in direct contrast to pediatric tumors that usually develop as a result of specific chromosomal translocations and epigenetic aberrations. The development of genomic instability is associated with mutations that contribute to cellular immortalization and transformation. Cancer occurs when cancer-initiating cells (CICs), also called cancer stem cells, develop as a result of these mutations. In this paper, we explore how CICs develop as a result of genomic instability, including looking at which cancer suppression mechanisms are abrogated. A recent in vitro study revealed the existence of a CIC induction pathway in differentiating stem cells. Under aberrant differentiation conditions, cells become senescent and develop genomic instabilities that lead to the development of CICs. The resulting CICs contain a mutation in the alternative reading frame of CDKN2A (ARF)/p53 module, i.e., in either ARF or p53. We summarize recently established knowledge of CIC development and cellular immortality, explore the role of the ARF/p53 module in protecting cells from transformation, and describe a risk factor for genomic destabilization that increases during the process of normal cell growth and differentiation and is associated with the downregulation of histone H2AX to levels representative of growth arrest in normal cells. PMID:25815132

  6. Building a model: developing genomic resources for common milkweed (Asclepias syriaca with low coverage genome sequencing

    Directory of Open Access Journals (Sweden)

    Weitemier Kevin

    2011-05-01

    Full Text Available Abstract Background Milkweeds (Asclepias L. have been extensively investigated in diverse areas of evolutionary biology and ecology; however, there are few genetic resources available to facilitate and compliment these studies. This study explored how low coverage genome sequencing of the common milkweed (Asclepias syriaca L. could be useful in characterizing the genome of a plant without prior genomic information and for development of genomic resources as a step toward further developing A. syriaca as a model in ecology and evolution. Results A 0.5× genome of A. syriaca was produced using Illumina sequencing. A virtually complete chloroplast genome of 158,598 bp was assembled, revealing few repeats and loss of three genes: accD, clpP, and ycf1. A nearly complete rDNA cistron (18S-5.8S-26S; 7,541 bp and 5S rDNA (120 bp sequence were obtained. Assessment of polymorphism revealed that the rDNA cistron and 5S rDNA had 0.3% and 26.7% polymorphic sites, respectively. A partial mitochondrial genome sequence (130,764 bp, with identical gene content to tobacco, was also assembled. An initial characterization of repeat content indicated that Ty1/copia-like retroelements are the most common repeat type in the milkweed genome. At least one A. syriaca microread hit 88% of Catharanthus roseus (Apocynaceae unigenes (median coverage of 0.29× and 66% of single copy orthologs (COSII in asterids (median coverage of 0.14×. From this partial characterization of the A. syriaca genome, markers for population genetics (microsatellites and phylogenetics (low-copy nuclear genes studies were developed. Conclusions The results highlight the promise of next generation sequencing for development of genomic resources for any organism. Low coverage genome sequencing allows characterization of the high copy fraction of the genome and exploration of the low copy fraction of the genome, which facilitate the development of molecular tools for further study of a target species

  7. 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,

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

    Directory of Open Access Journals (Sweden)

    Richer AL

    2015-02-01

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

  9. Genomic instability influences the transcriptome and proteome in endometrial cancer subtypes

    Directory of Open Access Journals (Sweden)

    Habermann Jens K

    2011-10-01

    Full Text Available Abstract Background In addition to clinical characteristics, DNA aneuploidy has been identified as a prognostic factor in epithelial malignancies in general and in endometrial cancers in particular. We mapped ploidy-associated chromosomal aberrations and identified corresponding gene and protein expression changes in endometrial cancers of different prognostic subgroups. Methods DNA image cytometry classified 25 endometrioid cancers to be either diploid (n = 16 or aneuploid (n = 9, and all uterine papillary serous cancers (UPSC to be aneuploid (n = 8. All samples were subjected to comparative genomic hybridization and gene expression profiling. Identified genes were subjected to Ingenuity pathway analysis (IPA and were correlated to protein expression changes. Results Comparative genomic hybridization revealed ploidy-associated specific, recurrent genomic imbalances. Gene expression analysis identified 54 genes between diploid and aneuploid endometrioid carcinomas, 39 genes between aneuploid endometrioid cancer and UPSC, and 76 genes between diploid endometrioid and aneuploid UPSC to be differentially expressed. Protein profiling identified AKR7A2 and ANXA2 to show translational alterations consistent with the transcriptional changes. The majority of differentially expressed genes and proteins belonged to identical molecular functions, foremost Cancer, Cell Death, and Cellular Assembly and Organization. Conclusions We conclude that the grade of genomic instability rather than the histopathological subtype correlates with specific gene and protein expression changes. The identified genes and proteins might be useful as molecular targets for improved diagnostic and therapeutic intervention and merit prospective validation.

  10. Molecular targets in urothelial cancer: detection, treatment, and animal models of bladder cancer

    Science.gov (United States)

    Smolensky, Dmitriy; Rathore, Kusum; Cekanova, Maria

    2016-01-01

    Bladder cancer remains one of the most expensive cancers to treat in the United States due to the length of required treatment and degree of recurrence. In order to treat bladder cancer more effectively, targeted therapies are being investigated. In order to use targeted therapy in a patient, it is important to provide a genetic background of the patient. Recent advances in genome sequencing, as well as transcriptome analysis, have identified major pathway components altered in bladder cancer. The purpose of this review is to provide a broad background on bladder cancer, including its causes, diagnosis, stages, treatments, animal models, as well as signaling pathways in bladder cancer. The major focus is given to the PI3K/AKT pathway, p53/pRb signaling pathways, and the histone modification machinery. Because several promising immunological therapies are also emerging in the treatment of bladder cancer, focus is also given on general activation of the immune system for the treatment of bladder cancer. PMID:27784990

  11. A study based on whole-genome sequencing yields a rare variant at 8q24 associated with prostate cancer

    NARCIS (Netherlands)

    Gudmundsson, J.; Sulem, P.; Gudbjartsson, D.F.; Masson, G.; Agnarsson, B.A.; Benediktsdottir, K.R.; Sigurdsson, A.; Magnusson, O.T.; Gudjonsson, S.A.; Magnusdottir, D.N.; Johannsdottir, H.; Helgadottir, H.T.; Stacey, S.N.; Jonasdottir, A.; Olafsdottir, S.B.; Thorleifsson, G.; Jonasson, J.G.; Tryggvadottir, L.; Navarrete, S.; Fuertes, F.; Helfand, B.T.; Hu, Q.; Csiki, I.E.; Mates, I.N.; Jinga, V.; Aben, K.K.H.; Oort, I.M. van; Vermeulen, S.; Donovan, J.L.; Hamdy, F.C.; Ng, C.F.; Chiu, P.K.; Lau, K.M.; Ng, M.C.; Gulcher, J.R.; Kong, A.; Catalona, W.J.; Mayordomo, J.I.; Einarsson, G.V.; Barkardottir, R.B.; Jonsson, E.; Mates, D.; Neal, D.E.; Kiemeney, L.A.L.M.; Thorsteinsdottir, U.; Rafnar, T.; Stefansson, K.

    2012-01-01

    In Western countries, prostate cancer is the most prevalent cancer of men and one of the leading causes of cancer-related death in men. Several genome-wide association studies have yielded numerous common variants conferring risk of prostate cancer. Here, we analyzed 32.5 million variants discovered

  12. A genome-wide association study identifies susceptibility loci for ovarian cancer at 2q31 and 8q24

    DEFF Research Database (Denmark)

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

    2010-01-01

    Ovarian cancer accounts for more deaths than all other gynecological cancers combined. To identify common low-penetrance ovarian cancer susceptibility genes, we conducted a genome-wide association study of 507,094 SNPs in 1,768 individuals with ovarian cancer (cases) and 2,354 controls, with foll...

  13. Association analysis of a chemo-response signature identified within The Cancer Genome Atlas aimed at predicting genetic risk for chemo-response in ovarian cancer

    Science.gov (United States)

    Salinas, Erin A; Newtson, Andreea M; Leslie, Kimberly K; Gonzalez-Bosquet, Jesus

    2016-01-01

    Background: A gene signature associated with chemo-response in ovarian cancer was created through integration of biological data in The Cancer Genome Atlas (TCGA) and validated in five independent microarray experiments. Our study aimed to determine if single nucleotide polymorphisms (SNPs) within the 422-gene signature were associated with a genetic predisposition to platinum-based chemotherapy response in serous ovarian cancer. Methods: An association analysis between SNPs within the 422-gene signature and chemo-response in serous ovarian cancer was performed under the log-additive genetic model using the ‘SNPassoc’ package within the R environment (p<0.0001). Subsequent validation of statistically significant SNPs was done in the Ovarian Cancer Association Consortium (OCAC) database. Results: 19 SNPs were found to be associated with chemo-response with statistical significance. None of the SNPs found significant in TCGA were validated within OCAC for the outcome of interest, chemo-response. Conclusions: SNPs associated with chemo-response in ovarian cancer within TGCA database were not validated in a larger database of patients and controls from OCAC. New strategies integrating somatic and germline information may help to characterize genetic predictors for treatment response in ovarian cancer. PMID:27186327

  14. CRISPRi and CRISPRa: New Functional Genomics Tools Provide Complementary Insights into Cancer Biology and Therapeutic Strategies | Office of Cancer Genomics

    Science.gov (United States)

    A central goal of research for targeted cancer therapy, or precision oncology, is to reveal the intrinsic vulnerabilities of cancer cells and exploit them as therapeutic targets. Examples of cancer cell vulnerabilities include driver oncogenes that are essential for the initiation and progression of cancer, or non-oncogene addictions resulting from the cancerous state of the cell. To identify vulnerabilities, scientists perform genetic “loss-of-function” and “gain-of-function” studies to better understand the roles of specific genes in cancer cells.

  15. A comprehensive assessment of somatic mutation detection in cancer using whole-genome sequencing

    Science.gov (United States)

    Alioto, Tyler S.; Buchhalter, Ivo; Derdak, Sophia; Hutter, Barbara; Eldridge, Matthew D.; Hovig, Eivind; Heisler, Lawrence E.; Beck, Timothy A.; Simpson, Jared T.; Tonon, Laurie; Sertier, Anne-Sophie; Patch, Ann-Marie; Jäger, Natalie; Ginsbach, Philip; Drews, Ruben; Paramasivam, Nagarajan; Kabbe, Rolf; Chotewutmontri, Sasithorn; Diessl, Nicolle; Previti, Christopher; Schmidt, Sabine; Brors, Benedikt; Feuerbach, Lars; Heinold, Michael; Gröbner, Susanne; Korshunov, Andrey; Tarpey, Patrick S.; Butler, Adam P.; Hinton, Jonathan; Jones, David; Menzies, Andrew; Raine, Keiran; Shepherd, Rebecca; Stebbings, Lucy; Teague, Jon W.; Ribeca, Paolo; Giner, Francesc Castro; Beltran, Sergi; Raineri, Emanuele; Dabad, Marc; Heath, Simon C.; Gut, Marta; Denroche, Robert E.; Harding, Nicholas J.; Yamaguchi, Takafumi N.; Fujimoto, Akihiro; Nakagawa, Hidewaki; Quesada, Víctor; Valdés-Mas, Rafael; Nakken, Sigve; Vodák, Daniel; Bower, Lawrence; Lynch, Andrew G.; Anderson, Charlotte L.; Waddell, Nicola; Pearson, John V.; Grimmond, Sean M.; Peto, Myron; Spellman, Paul; He, Minghui; Kandoth, Cyriac; Lee, Semin; Zhang, John; Létourneau, Louis; Ma, Singer; Seth, Sahil; Torrents, David; Xi, Liu; Wheeler, David A.; López-Otín, Carlos; Campo, Elías; Campbell, Peter J.; Boutros, Paul C.; Puente, Xose S.; Gerhard, Daniela S.; Pfister, Stefan M.; McPherson, John D.; Hudson, Thomas J.; Schlesner, Matthias; Lichter, Peter; Eils, Roland; Jones, David T. W.; Gut, Ivo G.

    2015-01-01

    As whole-genome sequencing for cancer genome analysis becomes a clinical tool, a full understanding of the variables affecting sequencing analysis output is required. Here using tumour-normal sample pairs from two different types of cancer, chronic lymphocytic leukaemia and medulloblastoma, we conduct a benchmarking exercise within the context of the International Cancer Genome Consortium. We compare sequencing methods, analysis pipelines and validation methods. We show that using PCR-free methods and increasing sequencing depth to ∼100 × shows benefits, as long as the tumour:control coverage ratio remains balanced. We observe widely varying mutation call rates and low concordance among analysis pipelines, reflecting the artefact-prone nature of the raw data and lack of standards for dealing with the artefacts. However, we show that, using the benchmark mutation set we have created, many issues are in fact easy to remedy and have an immediate positive impact on mutation detection accuracy. PMID:26647970

  16. Alternate Service Delivery Models in Cancer Genetic Counseling: A Mini-Review

    OpenAIRE

    Buchanan, Adam Hudson; Rahm, Alanna Kulchak; Williams, Janet L.

    2016-01-01

    Demand for cancer genetic counseling has grown rapidly in recent years as germline genomic information has become increasingly incorporated into cancer care, and the field has entered the public consciousness through high-profile celebrity publications. Increased demand and existing variability in the availability of trained cancer genetics clinicians place a priority on developing and evaluating alternate service delivery models for genetic counseling. This mini-review summarizes the state o...

  17. How Darwinian models inform therapeutic failure initiated by clonal heterogeneity in cancer medicine

    OpenAIRE

    Gerlinger, M; Swanton, C.

    2010-01-01

    Carcinogenesis is an evolutionary process that establishes the ‘hallmarks of cancer' by natural selection of cell clones that have acquired advantageous heritable characteristics. Evolutionary adaptation has also been proposed as a mechanism that promotes drug resistance during systemic cancer therapy. This review summarises the evidence for the evolution of resistance to cytotoxic and targeted anti-cancer drugs according to Darwinian models and highlights the roles of genomic instability and...

  18. Combined HSP90 and kinase inhibitor therapy: Insights from The Cancer Genome Atlas.

    Science.gov (United States)

    Schwartz, Harvey; Scroggins, Brad; Zuehlke, Abbey; Kijima, Toshiki; Beebe, Kristin; Mishra, Alok; Neckers, Len; Prince, Thomas

    2015-09-01

    The merging of knowledge from genomics, cellular signal transduction and molecular evolution is producing new paradigms of cancer analysis. Protein kinases have long been understood to initiate and promote malignant cell growth and targeting kinases to fight cancer has been a major strategy within the pharmaceutical industry for over two decades. Despite the initial success of kinase inhibitors (KIs), the ability of cancer to evolve resistance and reprogram oncogenic signaling networks has reduced the efficacy of kinase targeting. The molecular chaperone HSP90 physically supports global kinase function while also acting as an evolutionary capacitor. The Cancer Genome Atlas (TCGA) has compiled a trove of data indicating that a large percentage of tumors overexpress or possess mutant kinases that depend on the HSP90 molecular chaperone complex. Moreover, the overexpression or mutation of parallel activators of kinase activity (PAKA) increases the number of components that promote malignancy and indirectly associate with HSP90. Therefore, targeting HSP90 is predicted to complement kinase inhibitors by inhibiting oncogenic reprogramming and cancer evolution. Based on this hypothesis, consideration should be given by both the research and clinical communities towards combining kinase inhibitors and HSP90 inhibitors (H90Ins) in combating cancer. The purpose of this perspective is to reflect on the current understanding of HSP90 and kinase biology as well as promote the exploration of potential synergistic molecular therapy combinations through the utilization of The Cancer Genome Atlas. PMID:26070366

  19. Genomic and expression array profiling of chromosome 20q amplicon in human colon cancer cells

    Directory of Open Access Journals (Sweden)

    Carter Jennifer

    2005-01-01

    Full Text Available Background: Gain of the q arm of chromosome 20 in human colorectal cancer has been associated with poorer survival time and has been reported to increase in frequency from adenomas to metastasis. The increasing frequency of chromosome 20q amplification during colorectal cancer progression and the presence of this amplification in carcinomas of other tissue origin has lead us to hypothesize that 20q11-13 harbors one or more genes which, when over expressed promote tumor invasion and metastasis. Aims: Generate genomic and expression profiles of the 20q amplicon in human cancer cell lines in order to identify genes with increased copy number and expression. Materials and Methods: Utilizing genomic sequencing clones and amplification mapping data from our lab and other previous studies, BAC/ PAC tiling paths spanning the 20q amplicon and genomic microarrays were generated. Array-CGH on the custom array with human cancer cell line DNAs was performed to generate genomic profiles of the amplicon. Expression array analysis with RNA from these cell lines using commercial oligo microarrays generated expression profiles of the amplicon. The data were then combined in order to identify genes with increased copy number and expression. Results: Over expressed genes in regions of increased copy number were identified and a list of potential novel genetic tumor markers was assembled based on biological functions of these genes Conclusions: Performing high-resolution genomic microarray profiling in conjunction with expression analysis is an effective approach to identify potential tumor markers.

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

    Science.gov (United States)

    Kemp, Jacqueline; Longworth, Michelle

    2015-12-01

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

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

    Directory of Open Access Journals (Sweden)

    Jacqueline R. Kemp

    2015-12-01

    Full Text Available 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.

  2. Can metabolomics in addition to genomics add to prognostic and predictive information in breast cancer?

    Science.gov (United States)

    Howell, Anthony

    2010-11-16

    Genomic data from breast cancers provide additional prognostic and predictive information that is beginning to be used for patient management. The question arises whether additional information derived from other 'omic' approaches such as metabolomics can provide additional information. In an article published this month in BMC Cancer, Borgan et al. add metabolomic information to genomic measures in breast tumours and demonstrate, for the first time, that it may be possible to further define subgroups of patients which could be of value clinically. See research article: http://www.biomedcentral.com/1471-2407/10/628.

  3. Integrated proteomic and genomic analysis of colorectal cancer

    Science.gov (United States)

    Investigators who analyzed 95 human colorectal tumor samples have determined how gene alterations identified in previous analyses of the same samples are expressed at the protein level. The integration of proteomic and genomic data, or proteogenomics, pro

  4. Genomically Driven Tumors and Actionability across Histologies: BRAF-Mutant Cancers as a Paradigm.

    Science.gov (United States)

    Turski, Michelle L; Vidwans, Smruti J; Janku, Filip; Garrido-Laguna, Ignacio; Munoz, Javier; Schwab, Richard; Subbiah, Vivek; Rodon, Jordi; Kurzrock, Razelle

    2016-04-01

    The diagnosis, classification, and management of cancer are traditionally dictated by the site of tumor origin, for example, breast or lung, and by specific histologic subtypes of site-of-origin cancers (e.g., non-small cell versus small cell lung cancer). However, with the advent of sequencing technologies allowing for rapid, low cost, and accurate sequencing of clinical samples, new observations suggest an expanded or different approach to the diagnosis and treatment of cancer-one driven by the unique molecular features of the tumor. We discuss a genomically driven strategy for cancer treatment using BRAF as an example. Several key points are highlighted: (i) molecular aberrations can be shared across cancers; (ii) approximately 15% of all cancers harbor BRAF mutations; and (iii) BRAF inhibitors, while approved only for melanoma, have reported activity across numerous cancers and related disease types bearing BRAF aberrations. However, BRAF-mutated colorectal cancer has shown poor response rate to BRAF inhibitor monotherapy, striking a cautionary note. Yet, even in this case, emerging data suggest BRAF-mutated colorectal cancers can respond well to BRAF inhibitors, albeit when administered in combination with other agents that impact resistance pathways. Taken together, these data suggest that molecular aberrations may be the basis for a new nosology for cancer. Mol Cancer Ther; 15(4); 533-47. ©2016 AACR. PMID:27009213

  5. Detecting the somatic mutations spectrum of Chinese lung cancer by analyzing the whole mitochondrial DNA genomes.

    Science.gov (United States)

    Fang, Yu; Huang, Jie; Zhang, Jing; Wang, Jun; Qiao, Fei; Chen, Hua-Mei; Hong, Zhi-Peng

    2015-02-01

    To detect the somatic mutations and character its spectrum in Chinese lung cancer patients. In this study, we sequenced the whole mitochondrial DNA (mtDNA) genomes for 10 lung cancer patients including the primary cancerous, matched paracancerous normal and distant normal tissues. By analyzing the 30 whole mtDNA genomes, eight somatic mutations were identified from five patients investigated, which were confirmed with the cloning and sequencing of the somatic mutations. Five of the somatic mutations were detected among control region and the rests were found at the coding region. Heterogeneity was the main character of the somatic mutations in Chinese lung cancer patients. Further potential disease-related screening showed that, except the C deletion at position 309 showed AD-weakly associated, most of them were not disease-related. Although the role of aforementioned somatic mutations was unknown, however, considering the relative higher frequency of somatic mutations among the whole mtDNA genomes, it hints that detecting the somatic mutation(s) from the whole mtDNA genomes can serve as a useful tool for the Chinese lung cancer diagnostic to some extent.

  6. The Impact of dUTPase on Ribonucleotide Reductase-Induced Genome Instability in Cancer Cells

    OpenAIRE

    Chih-Wei Chen; Ning Tsao; Lin-Yi Huang; Yun Yen; Xiyong Liu; Christine Lehman; Yuh-Hwa Wang; Mei-Chun Tseng; Yu-Ju Chen; Yi-Chi Ho; Chian-Feng Chen; Zee-Fen Chang

    2016-01-01

    The appropriate supply of dNTPs is critical for cell growth and genome integrity. Here, we investigated the interrelationship between dUTP pyrophosphatase (dUTPase) and ribonucleotide reductase (RNR) in the regulation of genome stability. Our results demonstrate that reducing the expression of dUTPase increases genome stress in cancer. Analysis of clinical samples reveals a significant correlation between the combination of low dUTPase and high R2, a subunit of RNR, and a poor prognosis in co...

  7. The Genomic Grade Assay Compared With Ki67 to Determine Risk of Distant Breast Cancer Recurrence

    DEFF Research Database (Denmark)

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

    2016-01-01

    Importance: The Genomic Grade Index (GGI) was previously developed, evaluated on frozen tissue, and shown to be prognostic in early breast cancer. To test the GGI in formalin-fixed, paraffin-embedded breast cancer tumors, a quantitative reverse transcriptase polymerase chain reaction assay...... was developed and named the Genomic Grade (GG). The GG assay has the potential to increase the clinical application of the GGI, but robust demonstration of the clinical validity of the GG assay is required. Objective: To evaluate the prognostic ability of the GG assay to detect breast cancer recurrence compared...... cancer. Patients included in this study had available formalin-fixed, paraffin-embedded samples of their primary tumors and were randomized to either a 5-year tamoxifen monotherapy arm or a 5-year letrozole monotherapy arm. Associations between either GG assay results or log2-transformed Ki67 data...

  8. Azolla—A Model Organism for Plant Genomic Studies

    Institute of Scientific and Technical Information of China (English)

    Yin-LongQiu; JunYu

    2003-01-01

    The aquatic ferns of the genus Azolla are nitrogen-fixing plants that have great potentials in agricultural production and environmental conservation.Azolla in many aspects is qualified to serve as a model organism for genomic studies because of its importance in agriculture,its unique position in plant evolution,its symbiotic relationship with the N2-fixing cyanobacterium,Anabaena azollae,and its moderate-sized genome.The goals of this genome project are not only to understand the biology of the Azolla genome to promote its applications in biological research and agriculture practice but also to gain critical insights about evolution of plant genomes.Together with the strategic and technical improvement as well as cost reduction of DNA sequencing,the deciphering of their genetic code is imminent.

  9. Azolla - A Model Organism for Plant Genomic Studies

    Institute of Scientific and Technical Information of China (English)

    Yin-Long Qiu; Jun Yu

    2003-01-01

    The aquatic ferns of the genus Azolla are nitrogen-fixing plants that have great potentials in agricultural production and environmental conservation. Azolla in many aspects is qualified to serve as a model organism for genomic studies because of its importance in agriculture, its unique position in plant evolution, its symbiotic relationship with the N2-fixing cyanobacterium, Anabaena azollae, and its moderate-sized genome. The goals of this genome project are not only to understand the biology of the Azolla genome to promote its applications in biological research and agriculture practice but also to gain critical insights about evolution of plant genomes. Together with the strategic and technical improvement as well as cost reduction of DNA sequencing, the deciphering of their genetic code is imminent.

  10. Exploiting linkage disequilibrium in statistical modelling in quantitative genomics

    DEFF Research Database (Denmark)

    Wang, Lei

    the recently proposed antedependence models, which treat neighbouring marker effects as correlated; another approach involves use of haplotype block information derived using the program Beagle. The overall conclusion is that taking LD information into account in genomic prediction models potentially......Alleles at two loci are said to be in linkage disequilibrium (LD) when they are correlated or statistically dependent. Genomic prediction and gene mapping rely on the existence of LD between gentic markers and causul variants of complex traits. In the first part of the thesis, a novel method to...... quantify and visualize local variation in LD along chromosomes in describet, and applied to characterize LD patters at the local and genome-wide scale in three Danish pig breeds. In the second part, different ways of taking LD into account in genomic prediction models are studied. One approach is to use...

  11. Development of A Mouse Model of Menopausal Ovarian Cancer

    Directory of Open Access Journals (Sweden)

    Elizabeth R. Smith

    2014-02-01

    Full Text Available Despite significant understanding of the genetic mutations involved in ovarian epithelial cancer and advances in genomic approaches for expression and mutation profiling of tumor tissues, several key questions in ovarian cancer biology remain enigmatic: the mechanism for the well-established impact of reproductive factors on ovarian cancer risk remains obscure; questions of the cell of origin of ovarian cancer continue to be debated; and the precursor lesion, sequence, or events in progression remain to be defined. Suitable mouse models should complement the analysis of human tumor tissues and may provide clues to these questions currently perplexing ovarian cancer biology.A potentially useful model is the germ cell-deficient Wv (white spotting variant mutant mouse line, which may be used to study the impact of menopausal physiology on the increased risk of ovarian cancer. The Wv mice harbor a point mutation in c-Kit that reduces the receptor tyrosine kinase activity to about 1-5% (it is not a null mutation. Homozygous Wv mutant females have a reduced ovarian germ cell reservoir at birth and the follicles are rapidly depleted upon reaching reproductive maturity, but other biological phenotypes are minimal and the mice have a normal life span. The loss of ovarian function precipitates changes in hormonal and metabolic activity that model features of menopause in humans. As a consequence of follicle depletion, the Wv ovaries develop ovarian tubular adenomas, a benign epithelial tumor corresponding to surface epithelial invaginations and papillomatosis that mark human ovarian aging. Ongoing work will test the possibility of converting the benign epithelial tubular adenomas into neoplastic tumors by addition of an oncogenic mutation, such as of Tp53, to model the genotype and biology of serous ovarian cancer.Model based on the Wv mice may have the potential to gain biological and etiological insights into ovarian cancer development and prevention.

  12. Bystander effects, genomic instability, adaptive response, and cancer risk assessment for radiation and chemical exposures

    International Nuclear Information System (INIS)

    There is an increased interest in utilizing mechanistic data in support of the cancer risk assessment process for ionizing radiation and environmental chemical exposures. In this regard, the use of biologically based dose-response models is particularly advocated. The aim is to provide an enhanced basis for describing the nature of the dose-response curve for induced tumors at low levels of exposure. Cellular responses that might influence the nature of the dose-response curve at low exposures are understandably receiving attention. These responses (bystander effects, genomic instability, and adaptive responses) have been studied most extensively for radiation exposures. The former two could result in an enhancement of the tumor response at low doses and the latter could lead to a reduced response compared to that predicted by a linear extrapolation from high dose responses. Bystander responses, whereby cells other than those directly traversed by radiation tracks are damaged, can alter the concept of target cell population per unit dose. Similarly, induced genomic instability can alter the concept of total response to an exposure. There appears to be a role for oxidative damage and cellular signaling in the etiology of these cellular responses. The adaptive response appears to be inducible at very low doses of radiation or of some chemicals and reduces the cellular response to a larger challenge dose. It is currently unclear how these cellular toxic responses might be involved in tumor formation, if indeed they are. In addition, it is not known how widespread they are as regards inducing agents. Thus, their impact on low dose cancer risk remains to be established

  13. Genomic hallmarks of genes involved in chromosomal translocations in hematological cancer.

    Directory of Open Access Journals (Sweden)

    Mikhail Shugay

    Full Text Available Reciprocal chromosomal translocations (RCTs leading to the formation of fusion genes are important drivers of hematological cancers. Although the general requirements for breakage and fusion are fairly well understood, quantitative support for a general mechanism of RCT formation is still lacking. The aim of this paper is to analyze available high-throughput datasets with computational and robust statistical methods, in order to identify genomic hallmarks of translocation partner genes (TPGs. Our results show that fusion genes are generally overexpressed due to increased promoter activity of 5' TPGs and to more stable 3'-UTR regions of 3' TPGs. Furthermore, expression profiling of 5' TPGs and of interaction partners of 3' TPGs indicates that these features can help to explain tissue specificity of hematological translocations. Analysis of protein domains retained in fusion proteins shows that the co-occurrence of specific domain combinations is non-random and that distinct functional classes of fusion proteins tend to be associated with different components of the gene fusion network. This indicates that the configuration of fusion proteins plays an important role in determining which 5' and 3' TPGs will combine in specific fusion genes. It is generally accepted that chromosomal proximity in the nucleus can explain the specific pairing of 5' and 3' TPGS and the recurrence of hematological translocations. Using recently available data for chromosomal contact probabilities (Hi-C we show that TPGs are preferentially located in early replicated regions and occupy distinct clusters in the nucleus. However, our data suggest that, in general, nuclear position of TPGs in hematological cancers explains neither TPG pairing nor clinical frequency. Taken together, our results support a model in which genomic features related to regulation of expression and replication timing determine the set of candidate genes more likely to be translocated in

  14. In Remembrance of Robert J. Arceci, M.D., Ph.D. | Office of Cancer Genomics

    Science.gov (United States)

    It is with great sadness and a profound sense of loss that OCG recognizes the untimely passing of Dr. Robert J. Arceci. Dr. Arceci was a co-Principal Investigator for the Acute Myeloid Leukemia (AML) project within the TARGET initiative, which aims to discover novel, more effective treatments for childhood cancers. Dr. Arceci was passionate about the use of cancer genomics to both inform therapeutic approaches in the clinic and expand the field of precision medicine.

  15. Genomic and functional characterizations of phosphodiesterase subtype 4D in human cancers

    OpenAIRE

    Lin, De-Chen; Xu, Liang; Ding, Ling-Wen; Sharma, Arjun; Liu, Li-Zhen; Yang, Henry; Tan, Patrick; Vadgama, Jay; Karlan, Beth Y.; Lester, Jenny; Urban, Nicole; Schummer, Michèl; Doan, Ngan; Said, Jonathan W.; Sun, Hongmao

    2013-01-01

    Discovery of cancer genes through interrogation of genomic dosage is one of the major approaches in cancer research. In this study, we report that phosphodiesterase subtype 4D (PDE4D) gene was homozygously deleted in 198 cases of 5,569 primary solid tumors (3.56%), with most being internal microdeletions. Unexpectedly, the microdeletions did not result in loss of their gene products. Screening PDE4D expression in 11 different types of primary tumor samples (n = 165) with immunohistochemistry ...

  16. Integrating Genomics with Proteomics - Office of Cancer Clinical Proteomics Research

    Science.gov (United States)

    Approximately 60 percent of patients diagnosed with cancer present as early stage disease (Stage I and II). Despite the favorable prognosis associated with treatment intervention of such early stage disease (typically surgical excision), there are a small, but significant, fraction of these cancers that appear to be hardwired for aggressive metastatic behavior and ultimately lethal outcome.

  17. Genomic profiling identifies GATA6 as a candidate oncogene amplified in pancreatobiliary cancer.

    Directory of Open Access Journals (Sweden)

    Kevin A Kwei

    2008-05-01

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

  18. The mathematics of cancer: integrating quantitative models.

    Science.gov (United States)

    Altrock, Philipp M; Liu, Lin L; Michor, Franziska

    2015-12-01

    Mathematical modelling approaches have become increasingly abundant in cancer research. The complexity of cancer is well suited to quantitative approaches as it provides challenges and opportunities for new developments. In turn, mathematical modelling contributes to cancer research by helping to elucidate mechanisms and by providing quantitative predictions that can be validated. The recent expansion of quantitative models addresses many questions regarding tumour initiation, progression and metastases as well as intra-tumour heterogeneity, treatment responses and resistance. Mathematical models can complement experimental and clinical studies, but also challenge current paradigms, redefine our understanding of mechanisms driving tumorigenesis and shape future research in cancer biology.

  19. Significance of genomic instability in breast cancer in atomic bomb survivors: analysis of microarray-comparative genomic hybridization

    International Nuclear Information System (INIS)

    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

  20. Significance of genomic instability in breast cancer in atomic bomb survivors: analysis of microarray-comparative genomic hybridization

    Directory of Open Access Journals (Sweden)

    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

  1. Genomic and genetic alterations influence the progression of gastric cancer

    Institute of Scientific and Technical Information of China (English)

    Stefania Nobili; Lorenzo Bruno; Ida Landini; Cristina Napoli; Paolo Bechi; Francesco Tonelli; Carlos A Rubio; Enrico Mini; Gabriella Nesi

    2011-01-01

    Gastric cancer is one of the leading causes of cancerrelated deaths worldwide, although the incidence has gradually decreased in many Western countries. Twomain gastric cancer histotypes, intestinal and diffuse, are recognised. Although most of the described genetic alterations have been observed in both types, different genetic pathways have been hypothesized. Genetic and epigenetic events, including 1q loss of heterozygosity (LOH), microsatellite instability and hypermethylation, have mostly been reported in intestinal-type gastric carcinoma and its precursor lesions, whereas 17p LOH, mutation or loss of E-cadherin are more often implicated in the development of diffuse-type gastric cancer.

  2. Specialized Hidden Markov Model Databases for Microbial Genomics

    OpenAIRE

    Martin Gollery

    2003-01-01

    As hidden Markov models (HMMs) become increasingly more important in the analysis of biological sequences, so too have databases of HMMs expanded in size, number and importance. While the standard paradigm a short while ago was the analysis of one or a few sequences at a time, it has now become standard procedure to submit an entire microbial genome. In the future, it will be common to submit large groups of completed genomes to run simultaneously against a dozen public databas...

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

    Directory of Open Access Journals (Sweden)

    Alejandra Sandoval-Bórquez

    2015-01-01

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

  4. Breast cancer genome and transcriptome integration implicates specific mutational signatures with immune cell infiltration

    NARCIS (Netherlands)

    M. Smid (Marcel); F.G. Rodriguez-Gonzalez (F. German); A.M. Sieuwerts (Anieta); R. Salgado (Roberto); W.J.C. Prager-van der Smissen (Wendy); Vlugt-Daane, M.V.D. (Michelle Van Der); A. van Galen (Anne); S. Nik-Zainal (Serena); J. Staaf (Johan); A.B. Brinkman (Arie B.); M.J. Vijver (Marc ); A.L. Richardson (Andrea); A. Fatima (Aquila); Berentsen, K. (Kim); A. Butler (Adam); S. Martin (Sandra); H. Davies (Helen); J.E.M.A. Debets (Reno); M.E.M.-V. Gelder (Marion E. Meijer-Van); C.H.M. van Deurzen (Carolien); Macgrogan, G. (Gaëtan); Van Den Eynden, G.G.G.M. (Gert G. G. M.); C.A. Purdie (Colin A.); A.M. Thompson (Alastair M.); C. Caldas (Carlos); P.N. Span (Paul); Simpson, P.T. (Peter T.); S. Lakhani (Sunil); S.J. van Laere (Steven); C. Desmedt (Christine); Ringnér, M. (Markus); Tommasi, S. (Stefania); Eyford, J. (Jorunn); A. Broeks (Annegien); A. Vincent-Salomon (Anne); Futreal, P.A. (P. Andrew); S. Knappskog (Stian); King, T. (Tari); G. Thomas (Gilles); Viari, A. (Alain); Langerød, A. (Anita); A.-L. Borresen-Dale (Anne-Lise); E. Birney (Ewan); H. Stunnenberg (Henk); M.R. Stratton (Michael); J.A. Foekens (John); J.W.M. Martens (John)

    2016-01-01

    textabstractA recent comprehensive whole genome analysis of a large breast cancer cohort was used to link known and novel drivers and substitution signatures to the transcriptome of 266 cases. Here, we validate that subtype-specific aberrations show concordant expression changes for, for example, TP

  5. Genome-wide association study for ovarian cancer susceptibility using pooled DNA

    DEFF Research Database (Denmark)

    Lu, Yi; Chen, Xiaoqing; Beesley, Jonathan;

    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...

  6. Integrative genome analyses identify key somatic driver mutations of small-cell lung cancer

    NARCIS (Netherlands)

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

    2012-01-01

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

  7. Mitochondrial Genome Deletion for Detection of Prostate Cancer — EDRN Public Portal

    Science.gov (United States)

    The Prostate Core Mitomic Test™ is based upon a 3.4 kb mitochondrial genome deletion (3.4 mtdelta) that was identified through PCR analysis of frozen prostate cancer samples. In cancer research it has been found that deletions in mitochondrial DNA can correlate with cellular changes that indicate development of cancer. This deletion includes the terminal 22 bases of MT-ND4L, all of MT-ND4, 3 tRNAs (histidine, serine 2, and leucine 2), and all except the terminal 24 bases of MT-ND5.

  8. Data Mining Approaches for Genomic Biomarker Development: Applications Using Drug Screening Data from the Cancer Genome Project and the Cancer Cell Line Encyclopedia.

    Directory of Open Access Journals (Sweden)

    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.

  9. Data Mining Approaches for Genomic Biomarker Development: Applications Using Drug Screening Data from the Cancer Genome Project and the Cancer Cell Line Encyclopedia.

    Science.gov (United States)

    Covell, David G

    2015-01-01

    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.

  10. Modelling human regulatory variation in mouse: finding the function in genome-wide association studies and whole-genome sequencing.

    Directory of Open Access Journals (Sweden)

    Jean-François Schmouth

    Full Text Available An increasing body of literature from genome-wide association studies and human whole-genome sequencing highlights the identification of large numbers of candidate regulatory variants of potential therapeutic interest in numerous diseases. Our relatively poor understanding of the functions of non-coding genomic sequence, and the slow and laborious process of experimental validation of the functional significance of human regulatory variants, limits our ability to fully benefit from this information in our efforts to comprehend human disease. Humanized mouse models (HuMMs, in which human genes are introduced into the mouse, suggest an approach to this problem. In the past, HuMMs have been used successfully to study human disease variants; e.g., the complex genetic condition arising from Down syndrome, common monogenic disorders such as Huntington disease and β-thalassemia, and cancer susceptibility genes such as BRCA1. In this commentary, we highlight a novel method for high-throughput single-copy site-specific generation of HuMMs entitled High-throughput Human Genes on the X Chromosome (HuGX. This method can be applied to most human genes for which a bacterial artificial chromosome (BAC construct can be derived and a mouse-null allele exists. This strategy comprises (1 the use of recombineering technology to create a human variant-harbouring BAC, (2 knock-in of this BAC into the mouse genome using Hprt docking technology, and (3 allele comparison by interspecies complementation. We demonstrate the throughput of the HuGX method by generating a series of seven different alleles for the human NR2E1 gene at Hprt. In future challenges, we consider the current limitations of experimental approaches and call for a concerted effort by the genetics community, for both human and mouse, to solve the challenge of the functional analysis of human regulatory variation.

  11. Ensemble Modeling of Cancer Metabolism

    Directory of Open Access Journals (Sweden)

    Tahmineh eKhazaei

    2012-05-01

    Full Text Available The metabolic behaviour of cancer cells is adapted to meet their proliferative needs, with notable changes such as enhanced lactate secretion and glucose uptake rates. In this work, we use the Ensemble Modeling (EM framework to gain insight and predict potential drug targets for tumour cells. EM generates a set of models which span the space of kinetic parameters that are constrained by thermodynamics. Perturbation data based on known targets are used to screen the entire ensemble of models to obtain a sub-set, which is increasingly predictive. EM allows for incorporation of regulatory information and captures the behaviour of enzymatic reactions at the molecular level by representing reactions in the elementary reaction form. In this study, a metabolic network consisting of 58 reactions is considered and accounts for glycolysis, the pentose phosphate pathway, lipid metabolism, amino acid metabolism, and includes allosteric regulation of key enzymes. Experimentally measured intracellular and extracellular metabolite concentrations are used for developing the ensemble of models along with information on established drug targets. The resulting models predicted transaldolase (TALA and succinyl-CoA ligase (SUCOAS1m to cause a significant reduction in growth rate when repressed, relative to currently known drug targets. Furthermore, the results suggest that the synergetic repression of transaldolase and glycine hydroxymethyltransferase (GHMT2r will lead to a three-fold decrease in growth rate compared to the repression of single enzyme targets.

  12. [Genomic Tests as Predictors of Breast Cancer Patients Prognosis].

    Science.gov (United States)

    Bielčiková, Z; Petruželka, L

    2016-01-01

    Hormonal dependent breast cancer is a heterogeneous disease from a molecular and clinical perspective. The relapse risk of early breast cancer patients treated with adjuvant hormonal therapy varies. Validated predictive markers concerning adjuvant cytotoxic treatment are still lacking in ER+/ HER2-  breast cancer, which has a good prognosis in general. This can lead to the inefficient chemotherapy indication. Molecular classification of breast cancer reports evidence about the heterogeneity of hormonal dependent breast cancer and its stratification to different groups with different characteristics. Multigene assays work on the molecular level, and their aim is to provide patients risk stratification and therapy efficacy prediction. The position of multigene assays in clinical practice is not stabile yet. Non uniform level of evidence connected to patients prognosis interpretations and difficult comparison of tests are the key problems, which prevent their wide clinical use. The article is a summary of some of the most important multigene assays in breast cancer and their current position in oncology practice. PMID:26879059

  13. Gastric cancers of Western European and African patients show different patterns of genomic instability

    Directory of Open Access Journals (Sweden)

    Mulder Chris JJ

    2011-01-01

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

  14. Cancer progression modeling using static sample data.

    Science.gov (United States)

    Sun, Yijun; Yao, Jin; Nowak, Norma J; Goodison, Steve

    2014-01-01

    As molecular profiling data continues to accumulate, the design of integrative computational analyses that can provide insights into the dynamic aspects of cancer progression becomes feasible. Here, we present a novel computational method for the construction of cancer progression models based on the analysis of static tumor samples. We demonstrate the reliability of the method with simulated data, and describe the application to breast cancer data. Our findings support a linear, branching model for breast cancer progression. An interactive model facilitates the identification of key molecular events in the advance of disease to malignancy.

  15. Identification of mutated driver pathways in cancer using a multi-objective optimization model.

    Science.gov (United States)

    Zheng, Chun-Hou; Yang, Wu; Chong, Yan-Wen; Xia, Jun-Feng

    2016-05-01

    New-generation high-throughput technologies, including next-generation sequencing technology, have been extensively applied to solve biological problems. As a result, large cancer genomics projects such as the Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium are producing large amount of rich and diverse data in multiple cancer types. The identification of mutated driver genes and driver pathways from these data is a significant challenge. Genome aberrations in cancer cells can be divided into two types: random 'passenger mutation' and functional 'driver mutation'. In this paper, we introduced a Multi-objective Optimization model based on a Genetic Algorithm (MOGA) to solve the maximum weight submatrix problem, which can be employed to identify driver genes and driver pathways promoting cancer proliferation. The maximum weight submatrix problem defined to find mutated driver pathways is based on two specific properties, i.e., high coverage and high exclusivity. The multi-objective optimization model can adjust the trade-off between high coverage and high exclusivity. We proposed an integrative model by combining gene expression data and mutation data to improve the performance of the MOGA algorithm in a biological context. PMID:26995027

  16. Acetylation Reader Proteins: Linking Acetylation Signaling to Genome Maintenance and Cancer.

    Science.gov (United States)

    Gong, Fade; Chiu, Li-Ya; Miller, Kyle M

    2016-09-01

    Chromatin-based DNA damage response (DDR) pathways are fundamental for preventing genome and epigenome instability, which are prevalent in cancer. Histone acetyltransferases (HATs) and histone deacetylases (HDACs) catalyze the addition and removal of acetyl groups on lysine residues, a post-translational modification important for the DDR. Acetylation can alter chromatin structure as well as function by providing binding signals for reader proteins containing acetyl-lysine recognition domains, including the bromodomain (BRD). Acetylation dynamics occur upon DNA damage in part to regulate chromatin and BRD protein interactions that mediate key DDR activities. In cancer, DDR and acetylation pathways are often mutated or abnormally expressed. DNA damaging agents and drugs targeting epigenetic regulators, including HATs, HDACs, and BRD proteins, are used or are being developed to treat cancer. Here, we discuss how histone acetylation pathways, with a focus on acetylation reader proteins, promote genome stability and the DDR. We analyze how acetylation signaling impacts the DDR in the context of cancer and its treatments. Understanding the relationship between epigenetic regulators, the DDR, and chromatin is integral for obtaining a mechanistic understanding of genome and epigenome maintenance pathways, information that can be leveraged for targeting acetylation signaling, and/or the DDR to treat diseases, including cancer.

  17. Understanding Cancer Prognosis

    Medline Plus

    Full Text Available ... Renal Cell) Cancer Leukemia Lung Cancer Lymphoma Pancreatic Cancer Prostate Cancer Skin Cancer Thyroid Cancer Uterine Cancer All ... Cancer Biology Cancer Genomics Causes of Cancer Diagnosis Prevention Screening & Early Detection Treatment Cancer & Public Health Cancer ...

  18. Integrated analysis of copy number variation and genome-wide expression profiling in colorectal cancer tissues.

    Directory of Open Access Journals (Sweden)

    Nur Zarina Ali Hassan

    Full Text Available Integrative analyses of multiple genomic datasets for selected samples can provide better insight into the overall data and can enhance our knowledge of cancer. The objective of this study was to elucidate the association between copy number variation (CNV and gene expression in colorectal cancer (CRC samples and their corresponding non-cancerous tissues. Sixty-four paired CRC samples from the same patients were subjected to CNV profiling using the Illumina HumanOmni1-Quad assay, and validation was performed using multiplex ligation probe amplification method. Genome-wide expression profiling was performed on 15 paired samples from the same group of patients using the Affymetrix Human Gene 1.0 ST array. Significant genes obtained from both array results were then overlapped. To identify molecular pathways, the data were mapped to the KEGG database. Whole genome CNV analysis that compared primary tumor and non-cancerous epithelium revealed gains in 1638 genes and losses in 36 genes. Significant gains were mostly found in chromosome 20 at position 20q12 with a frequency of 45.31% in tumor samples. Examples of genes that were associated at this cytoband were PTPRT, EMILIN3 and CHD6. The highest number of losses was detected at chromosome 8, position 8p23.2 with 17.19% occurrence in all tumor samples. Among the genes found at this cytoband were CSMD1 and DLC1. Genome-wide expression profiling showed 709 genes to be up-regulated and 699 genes to be down-regulated in CRC compared to non-cancerous samples. Integration of these two datasets identified 56 overlapping genes, which were located in chromosomes 8, 20 and 22. MLPA confirmed that the CRC samples had the highest gains in chromosome 20 compared to the reference samples. Interpretation of the CNV data in the context of the transcriptome via integrative analyses may provide more in-depth knowledge of the genomic landscape of CRC.

  19. Genome-wide association analysis identifies new lung cancer susceptibility loci in never-smoking women in Asia.

    NARCIS (Netherlands)

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

    2012-01-01

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

  20. Identification of Variant-Specific Functions of PIK3CA by Rapid Phenotyping of Rare Mutations | Office of Cancer Genomics

    Science.gov (United States)

    Large-scale sequencing efforts are uncovering the complexity of cancer genomes, which are composed of causal "driver" mutations that promote tumor progression along with many more pathologically neutral "passenger" events. The majority of mutations, both in known cancer drivers and uncharacterized genes, are generally of low occurrence, highlighting the need to functionally annotate the long tail of infrequent mutations present in heterogeneous cancers.

  1. Network regularised Cox regression and multiplex network models to predict disease comorbidities and survival of cancer.

    Science.gov (United States)

    Xu, Haoming; Moni, Mohammad Ali; Liò, Pietro

    2015-12-01

    In cancer genomics, gene expression levels provide important molecular signatures for all types of cancer, and this could be very useful for predicting the survival of cancer patients. However, the main challenge of gene expression data analysis is high dimensionality, and microarray is characterised by few number of samples with large number of genes. To overcome this problem, a variety of penalised Cox proportional hazard models have been proposed. We introduce a novel network regularised Cox proportional hazard model and a novel multiplex network model to measure the disease comorbidities and to predict survival of the cancer patient. Our methods are applied to analyse seven microarray cancer gene expression datasets: breast cancer, ovarian cancer, lung cancer, liver cancer, renal cancer and osteosarcoma. Firstly, we applied a principal component analysis to reduce the dimensionality of original gene expression data. Secondly, we applied a network regularised Cox regression model on the reduced gene expression datasets. By using normalised mutual information method and multiplex network model, we predict the comorbidities for the liver cancer based on the integration of diverse set of omics and clinical data, and we find the diseasome associations (disease-gene association) among different cancers based on the identified common significant genes. Finally, we evaluated the precision of the approach with respect to the accuracy of survival prediction using ROC curves. We report that colon cancer, liver cancer and renal cancer share the CXCL5 gene, and breast cancer, ovarian cancer and renal cancer share the CCND2 gene. Our methods are useful to predict survival of the patient and disease comorbidities more accurately and helpful for improvement of the care of patients with comorbidity. Software in Matlab and R is available on our GitHub page: https://github.com/ssnhcom/NetworkRegularisedCox.git. PMID:26611766

  2. Animal models of ovarian cancer

    OpenAIRE

    Shaw Tanya J; Vanderhyden Barbara C; Ethier Jean-François

    2003-01-01

    Abstract Ovarian cancer is the most lethal of all of the gynecological cancers and can arise from any cell type of the ovary, including germ cells, granulosa or stromal cells. However, the majority of ovarian cancers arise from the surface epithelium, a single layer of cells that covers the surface of the ovary. The lack of a reliable and specific method for the early detection of epithelial ovarian cancer results in diagnosis occurring most commonly at late clinical stages, when treatment is...

  3. Practical implications for genetic modeling in the genomics era.

    Science.gov (United States)

    VanRaden, P M

    2016-03-01

    Genetic models convert data into estimated breeding values and other information useful to breeders. The goal is to provide accurate and timely predictions of the future performance for each animal (or embryo). Modeling involves defining traits, editing raw data, removing environmental effects, including genetic by environmental interactions and correlations among traits, and accounting for nonadditive inheritance or nonnormal distributions. Data include phenotypes and pedigrees during the last century and genotypes within the last decade. The genomic data can include single nucleotide polymorphisms, quantitative trait loci, insertions, deletions, and haplotypes. Subsets must be selected to reduce computation because total numbers of variants that can be imputed have increased rapidly from thousands to millions. Current computation using 60,671 markers takes just a few days. Nonlinear models can account for the nonnormal distribution of genomic effects, but reliability is usually better than that of linear models only for traits influenced by major genes. Numbers of genotyped animals have also increased rapidly in the joint North American database from a few thousand in 2009 to over 1 million in 2015. Most are young females and will contribute to estimating allele effects in the future, but only about 150,000 have phenotypes so far. Genomic preselection can bias traditional animal models because Mendelian sampling of phenotyped progeny and mates is no longer expected to average zero; however, estimates of bias are small in current US data. Single-step models that combine pedigree and genomic relationships can account for preselection, but approximations are required for affordable computation. Traditional animal models may include all breeds and crossbreds, but most genomic evaluations are still computed within breed. Models that include inbreeding, heterosis, dominance, and interactions can improve predictions for individual matings. Multitrait genomic models may

  4. Microbial comparative pan-genomics using binomial mixture models

    Directory of Open Access Journals (Sweden)

    Ussery David W

    2009-08-01

    Full Text Available Abstract Background The size of the core- and pan-genome of bacterial species is a topic of increasing interest due to the growing number of sequenced prokaryote genomes, many from the same species. Attempts to estimate these quantities have been made, using regression methods or mixture models. We extend the latter approach by using statistical ideas developed for capture-recapture problems in ecology and epidemiology. Results We estimate core- and pan-genome sizes for 16 different bacterial species. The results reveal a complex dependency structure for most species, manifested as heterogeneous detection probabilities. Estimated pan-genome sizes range from small (around 2600 gene families in Buchnera aphidicola to large (around 43000 gene families in Escherichia coli. Results for Echerichia coli show that as more data become available, a larger diversity is estimated, indicating an extensive pool of rarely occurring genes in the population. Conclusion Analyzing pan-genomics data with binomial mixture models is a way to handle dependencies between genomes, which we find is always present. A bottleneck in the estimation procedure is the annotation of rarely occurring genes.

  5. MEMOSys: Bioinformatics platform for genome-scale metabolic models

    Directory of Open Access Journals (Sweden)

    Agren Rasmus

    2011-01-01

    Full Text Available Abstract Background Recent advances in genomic sequencing have enabled the use of genome sequencing in standard biological and biotechnological research projects. The challenge is how to integrate the large amount of data in order to gain novel biological insights. One way to leverage sequence data is to use genome-scale metabolic models. We have therefore designed and implemented a bioinformatics platform which supports the development of such metabolic models. Results MEMOSys (MEtabolic MOdel research and development System is a versatile platform for the management, storage, and development of genome-scale metabolic models. It supports the development of new models by providing a built-in version control system which offers access to the complete developmental history. Moreover, the integrated web board, the authorization system, and the definition of user roles allow collaborations across departments and institutions. Research on existing models is facilitated by a search system, references to external databases, and a feature-rich comparison mechanism. MEMOSys provides customizable data exchange mechanisms using the SBML format to enable analysis in external tools. The web application is based on the Java EE framework and offers an intuitive user interface. It currently contains six annotated microbial metabolic models. Conclusions We have developed a web-based system designed to provide researchers a novel application facilitating the management and development of metabolic models. The system is freely available at http://www.icbi.at/MEMOSys.

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

    Directory of Open Access Journals (Sweden)

    German A Pihan

    2013-11-01

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

  7. Figure 4 from Integrative Genomics Viewer: Visualizing Big Data | Office of Cancer Genomics

    Science.gov (United States)

    Gene-list view of genomic data. The gene-list view allows users to compare data across a set of loci. The data in this figure includes copy number, mutation, and clinical data from 202 glioblastoma samples from TCGA. Adapted from Figure 7; Thorvaldsdottir H et al. 2012

  8. Figure 5 from Integrative Genomics Viewer: Visualizing Big Data | Office of Cancer Genomics

    Science.gov (United States)

    Split-Screen View. The split-screen view is useful for exploring relationships of genomic features that are independent of chromosomal location. Color is used here to indicate mate pairs that map to different chromosomes, chromosomes 1 and 6, suggesting a translocation event. Adapted from Figure 8; Thorvaldsdottir H et al. 2012

  9. Figure 2 from Integrative Genomics Viewer: Visualizing Big Data | Office of Cancer Genomics

    Science.gov (United States)

    Grouping and sorting genomic data in IGV. The IGV user interface displaying 202 glioblastoma samples from TCGA. Samples are grouped by tumor subtype (second annotation column) and data type (first annotation column) and sorted by copy number of the EGFR locus (middle column). Adapted from Figure 1; Robinson et al. 2011

  10. Emerging Technologies to Create Inducible and Genetically Defined Porcine Cancer Models.

    Science.gov (United States)

    Schook, Lawrence B; Rund, Laurie; Begnini, Karine R; Remião, Mariana H; Seixas, Fabiana K; Collares, Tiago

    2016-01-01

    There is an emerging need for new animal models that address unmet translational cancer research requirements. Transgenic porcine models provide an exceptional opportunity due to their genetic, anatomic, and physiological similarities with humans. Due to recent advances in the sequencing of domestic animal genomes and the development of new organism cloning technologies, it is now very feasible to utilize pigs as a malleable species, with similar anatomic and physiological features with humans, in which to develop cancer models. In this review, we discuss genetic modification technologies successfully used to produce porcine biomedical models, in particular the Cre-loxP System as well as major advances and perspectives the CRISPR/Cas9 System. Recent advancements in porcine tumor modeling and genome editing will bring porcine models to the forefront of translational cancer research. PMID:26973698

  11. Emerging technologies to create inducible and genetically defined porcine cancer models

    Directory of Open Access Journals (Sweden)

    Lawrence B Schook

    2016-02-01

    Full Text Available There is an emerging need for new animal models that address unmet translational cancer research requirements. Transgenic porcine models provide an exceptional opportunity due to their genetic, anatomic and physiological similarities with humans. Due to recent advances in the sequencing of domestic animal genomes and the development of new organism cloning technologies, it is now very feasible to utilize pigs as a malleable species, with similar anatomic and physiological features with humans, in which to develop cancer models. In this review, we discuss genetic modification technologies successfully used to produce porcine biomedical models, in particular the Cre-loxP System as well as major advances and perspectives the CRISPR/Cas9 System. Recent advancements in porcine tumor modeling and genome editing will bring porcine models to the forefront of translational cancer research.

  12. Role of oxidative DNA damage in genome instability and cancer

    International Nuclear Information System (INIS)

    Inactivation of mismatch repair (MMR) is associated with a dramatic genomic instability that is observed experimentally as a mutator phenotype and micro satellite instability (MSI). It has been implicit that the massive genetic instability in MMR defective cells simply reflects the accumulation of spontaneous DNA polymerase errors during DNA replication. We recently identified oxidation damage, a common threat to DNA integrity to which purines are very susceptible, as an important cofactor in this genetic instability

  13. Impulsive Neural Networks Algorithm Based on the Artificial Genome Model

    Directory of Open Access Journals (Sweden)

    Yuan Gao

    2014-05-01

    Full Text Available To describe gene regulatory networks, this article takes the framework of the artificial genome model and proposes impulsive neural networks algorithm based on the artificial genome model. Firstly, the gene expression and the cell division tree are applied to generate spiking neurons with specific attributes, neural network structure, connection weights and specific learning rules of each neuron. Next, the gene segment duplications and divergence model are applied to design the evolutionary algorithm of impulsive neural networks at the level of the artificial genome. The dynamic changes of developmental gene regulatory networks are controlled during the whole evolutionary process. Finally, the behavior of collecting food for autonomous intelligent agent is simulated, which is driven by nerves. Experimental results demonstrate that the algorithm in this article has the evolutionary ability on large-scale impulsive neural networks

  14. Liver cancer mortality rate model in Thailand

    Science.gov (United States)

    Sriwattanapongse, Wattanavadee; Prasitwattanaseree, Sukon

    2013-09-01

    Liver Cancer has been a leading cause of death in Thailand. The purpose of this study was to model and forecast liver cancer mortality rate in Thailand using death certificate reports. A retrospective analysis of the liver cancer mortality rate was conducted. Numbering of 123,280 liver cancer causes of death cases were obtained from the national vital registration database for the 10-year period from 2000 to 2009, provided by the Ministry of Interior and coded as cause-of-death using ICD-10 by the Ministry of Public Health. Multivariate regression model was used for modeling and forecasting age-specific liver cancer mortality rates in Thailand. Liver cancer mortality increased with increasing age for each sex and was also higher in the North East provinces. The trends of liver cancer mortality remained stable in most age groups with increases during ten-year period (2000 to 2009) in the Northern and Southern. Liver cancer mortality was higher in males and increase with increasing age. There is need of liver cancer control measures to remain on a sustained and long-term basis for the high liver cancer burden rate of Thailand.

  15. The tandem duplicator phenotype as a distinct genomic configuration in cancer.

    Science.gov (United States)

    Menghi, Francesca; Inaki, Koichiro; Woo, XingYi; Kumar, Pooja A; Grzeda, Krzysztof R; Malhotra, Ankit; Yadav, Vinod; Kim, Hyunsoo; Marquez, Eladio J; Ucar, Duygu; Shreckengast, Phung T; Wagner, Joel P; MacIntyre, George; Murthy Karuturi, Krishna R; Scully, Ralph; Keck, James; Chuang, Jeffrey H; Liu, Edison T

    2016-04-26

    Next-generation sequencing studies have revealed genome-wide structural variation patterns in cancer, such as chromothripsis and chromoplexy, that do not engage a single discernable driver mutation, and whose clinical relevance is unclear. We devised a robust genomic metric able to identify cancers with a chromotype called tandem duplicator phenotype (TDP) characterized by frequent and distributed tandem duplications (TDs). Enriched only in triple-negative breast cancer (TNBC) and in ovarian, endometrial, and liver cancers, TDP tumors conjointly exhibit tumor protein p53 (TP53) mutations, disruption of breast cancer 1 (BRCA1), and increased expression of DNA replication genes pointing at rereplication in a defective checkpoint environment as a plausible causal mechanism. The resultant TDs in TDP augment global oncogene expression and disrupt tumor suppressor genes. Importantly, the TDP strongly correlates with cisplatin sensitivity in both TNBC cell lines and primary patient-derived xenografts. We conclude that the TDP is a common cancer chromotype that coordinately alters oncogene/tumor suppressor expression with potential as a marker for chemotherapeutic response. PMID:27071093

  16. The tandem duplicator phenotype as a distinct genomic configuration in cancer

    Science.gov (United States)

    Menghi, Francesca; Inaki, Koichiro; Woo, XingYi; Kumar, Pooja A.; Grzeda, Krzysztof R.; Malhotra, Ankit; Yadav, Vinod; Kim, Hyunsoo; Marquez, Eladio J.; Ucar, Duygu; Shreckengast, Phung T.; Wagner, Joel P.; MacIntyre, George; Murthy Karuturi, Krishna R.; Scully, Ralph; Keck, James; Chuang, Jeffrey H.; Liu, Edison T.

    2016-01-01

    Next-generation sequencing studies have revealed genome-wide structural variation patterns in cancer, such as chromothripsis and chromoplexy, that do not engage a single discernable driver mutation, and whose clinical relevance is unclear. We devised a robust genomic metric able to identify cancers with a chromotype called tandem duplicator phenotype (TDP) characterized by frequent and distributed tandem duplications (TDs). Enriched only in triple-negative breast cancer (TNBC) and in ovarian, endometrial, and liver cancers, TDP tumors conjointly exhibit tumor protein p53 (TP53) mutations, disruption of breast cancer 1 (BRCA1), and increased expression of DNA replication genes pointing at rereplication in a defective checkpoint environment as a plausible causal mechanism. The resultant TDs in TDP augment global oncogene expression and disrupt tumor suppressor genes. Importantly, the TDP strongly correlates with cisplatin sensitivity in both TNBC cell lines and primary patient-derived xenografts. We conclude that the TDP is a common cancer chromotype that coordinately alters oncogene/tumor suppressor expression with potential as a marker for chemotherapeutic response. PMID:27071093

  17. Integrated functional, gene expression and genomic analysis for the identification of cancer targets.

    Directory of Open Access Journals (Sweden)

    Elizabeth Iorns

    Full Text Available The majority of new drug approvals for cancer are based on existing therapeutic targets. One approach to the identification of novel targets is to perform high-throughput RNA interference (RNAi cellular viability screens. We describe a novel approach combining RNAi screening in multiple cell lines with gene expression and genomic profiling to identify novel cancer targets. We performed parallel RNAi screens in multiple cancer cell lines to identify genes that are essential for viability in some cell lines but not others, suggesting that these genes constitute key drivers of cellular survival in specific cancer cells. This approach was verified by the identification of PIK3CA, silencing of which was selectively lethal to the MCF7 cell line, which harbours an activating oncogenic PIK3CA mutation. We combined our functional RNAi approach with gene expression and genomic analysis, allowing the identification of several novel kinases, including WEE1, that are essential for viability only in cell lines that have an elevated level of expression of this kinase. Furthermore, we identified a subset of breast tumours that highly express WEE1 suggesting that WEE1 could be a novel therapeutic target in breast cancer. In conclusion, this strategy represents a novel and effective strategy for the identification of functionally important therapeutic targets in cancer.

  18. Integrated Bioinformatics, Environmental Epidemiologic and Genomic Approaches to Identify Environmental and Molecular Links between Endometriosis and Breast Cancer

    Directory of Open Access Journals (Sweden)

    Deodutta Roy

    2015-10-01

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

  19. Dysfunctional telomeres promote genomic instability and metastasis in the absence of telomerase activity in oncogene induced mammary cancer.

    Science.gov (United States)

    Bojovic, Bojana; Crowe, David L

    2013-02-01

    Telomerase is a ribonucleoprotein that maintains the ends of chromosomes (telomeres). In normal cells lacking telomerase activity, telomeres shorten with each cell division because of the inability to completely synthesize the lagging strand. Critically shortened telomeres elicit DNA damage responses and limit cellular division and lifespan, providing an important tumor suppressor function. Most human cancer cells express telomerase which contributes significantly to the tumor phenotype. In human breast cancer, telomerase expression is predictive of clinical outcomes such as lymph node metastasis and survival. In mouse models of mammary cancer, telomerase expression is also upregulated. Telomerase overexpression resulted in spontaneous mammary tumor development in aged female mice. Increased mammary cancer also was observed when telomerase deficient mice were crossed with p53 null mutant animals. However, the effects of telomerase and telomere length on oncogene driven mammary cancer have not been completely characterized. To address these issues we characterized neu proto-oncogene driven mammary tumor formation in G1 Terc-/- (telomerase deficient with long telomeres), G3 Terc-/- (telomerase deficient with short telomeres), and Terc+/+ mice. Telomerase deficiency reduced the number of mammary tumors and increased tumor latency regardless of telomere length. Decreased tumor formation correlated with increased apoptosis in Terc deficient tumors. Short telomeres dramatically increased lung metastasis which correlated with increased genomic instability, and specific alterations in DNA copy number and gene expression. We concluded that short telomeres promote metastasis in the absence of telomerase activity in neu oncogene driven mammary tumors.

  20. MuSiC: identifying mutational significance in cancer genomes.

    Science.gov (United States)

    Dees, Nathan D; Zhang, Qunyuan; Kandoth, Cyriac; Wendl, Michael C; Schierding, William; Koboldt, Daniel C; Mooney, Thomas B; Callaway, Matthew B; Dooling, David; Mardis, Elaine R; Wilson, Richard K; Ding, Li

    2012-08-01

    Massively parallel sequencing technology and the associated rapidly decreasing sequencing costs have enabled systemic analyses of somatic mutations in large cohorts of cancer cases. Here we introduce a comprehensive mutational analysis pipeline that uses standardized sequence-based inputs along with multiple types of clinical data to establish correlations among mutation sites, affected genes and pathways, and to ultimately separate the commonly abundant passenger mutations from the truly significant events. In other words, we aim to determine the Mutational Significance in Cancer (MuSiC) for these large data sets. The integration of analytical operations in the MuSiC framework is widely applicable to a broad set of tumor types and offers the benefits of automation as well as standardization. Herein, we describe the computational structure and statistical underpinnings of the MuSiC pipeline and demonstrate its performance using 316 ovarian cancer samples from the TCGA ovarian cancer project. MuSiC correctly confirms many expected results, and identifies several potentially novel avenues for discovery.

  1. Genomic Alterations in Liquid Biopsies from Patients with Bladder Cancer

    DEFF Research Database (Denmark)

    Birkenkamp-Demtröder, Karin; Nordentoft, Iver Kristiansen; Christensen, Emil;

    2016-01-01

    Background: At least half of the patients diagnosed with non–muscle-invasive bladder cancer (NMIBC) experience recurrence and approximately 15% will develop progression to muscle invasive or metastatic disease. Biomarkers for disease surveillance are urgently needed. Objective: Development of ass...

  2. Synthetic Genetic Targeting of Genome Instability in Cancer

    Energy Technology Data Exchange (ETDEWEB)

    Sajesh, Babu V.; Guppy, Brent J.; McManus, Kirk J., E-mail: mcmanusk@cc.umanitoba.ca [Manitoba Institute of Cell Biology, Department of Biochemistry and Medical Genetics, University of Manitoba, Winnipeg, Manitoba R3E 0V9 (Canada)

    2013-06-24

    Cancer is a leading cause of death throughout the World. A limitation of many current chemotherapeutic approaches is that their cytotoxic effects are not restricted to cancer cells, and adverse side effects can occur within normal tissues. Consequently, novel strategies are urgently needed to better target cancer cells. As we approach the era of personalized medicine, targeting the specific molecular defect(s) within a given patient’s tumor will become a more effective treatment strategy than traditional approaches that often target a given cancer type or sub-type. Synthetic genetic interactions are now being examined for their therapeutic potential and are designed to target the specific genetic and epigenetic phenomena associated with tumor formation, and thus are predicted to be highly selective. In general, two complementary approaches have been employed, including synthetic lethality and synthetic dosage lethality, to target aberrant expression and/or function associated with tumor suppressor genes and oncogenes, respectively. Here we discuss the concepts of synthetic lethality and synthetic dosage lethality, and explain three general experimental approaches designed to identify novel genetic interactors. We present examples and discuss the merits and caveats of each approach. Finally, we provide insight into the subsequent pre-clinical work required to validate novel candidate drug targets.

  3. Genomic aberrations relate early and advanced stage ovarian cancer

    NARCIS (Netherlands)

    A. Zaal; W.J. Peyrot (Wouter ); P.M.J.J. Berns (Els); M.E.L. van der Burg (Maria); J.H.W. Veerbeek (Jan ); J.B. Trimbos; I. Cadron (Isabelle); P.J. van Diest (Paul); W.N. Wieringen (Wessel); O. Krijgsman (Oscar); G.A. Meijer (Gerrit); J.M.J. Piek (Jurgen ); P.J. Timmers (Petra); I. Vergote (Ignace); R.H.M. Verheijen (René); B. Ylstra (Bauke); R.P. Zweemer (Ronald )

    2012-01-01

    textabstractBackground Because of the distinct clinical presentation of early and advanced stage ovarian cancer, we aim to clarify whether these disease entities are solely separated by time of diagnosis or whether they arise from distinct molecular events. Methods Sixteen early and sixteen advanced

  4. Synthetic Genetic Targeting of Genome Instability in Cancer

    International Nuclear Information System (INIS)

    Cancer is a leading cause of death throughout the World. A limitation of many current chemotherapeutic approaches is that their cytotoxic effects are not restricted to cancer cells, and adverse side effects can occur within normal tissues. Consequently, novel strategies are urgently needed to better target cancer cells. As we approach the era of personalized medicine, targeting the specific molecular defect(s) within a given patient’s tumor will become a more effective treatment strategy than traditional approaches that often target a given cancer type or sub-type. Synthetic genetic interactions are now being examined for their therapeutic potential and are designed to target the specific genetic and epigenetic phenomena associated with tumor formation, and thus are predicted to be highly selective. In general, two complementary approaches have been employed, including synthetic lethality and synthetic dosage lethality, to target aberrant expression and/or function associated with tumor suppressor genes and oncogenes, respectively. Here we discuss the concepts of synthetic lethality and synthetic dosage lethality, and explain three general experimental approaches designed to identify novel genetic interactors. We present examples and discuss the merits and caveats of each approach. Finally, we provide insight into the subsequent pre-clinical work required to validate novel candidate drug targets

  5. MuSiC: Identifying mutational significance in cancer genomes

    Science.gov (United States)

    Dees, Nathan D.; Zhang, Qunyuan; Kandoth, Cyriac; Wendl, Michael C.; Schierding, William; Koboldt, Daniel C.; Mooney, Thomas B.; Callaway, Matthew B.; Dooling, David; Mardis, Elaine R.; Wilson, Richard K.; Ding, Li

    2012-01-01

    Massively parallel sequencing technology and the associated rapidly decreasing sequencing costs have enabled systemic analyses of somatic mutations in large cohorts of cancer cases. Here we introduce a comprehensive mutational analysis pipeline that uses standardized sequence-based inputs along with multiple types of clinical data to establish correlations among mutation sites, affected genes and pathways, and to ultimately separate the commonly abundant passenger mutations from the truly significant events. In other words, we aim to determine the Mutational Significance in Cancer (MuSiC) for these large data sets. The integration of analytical operations in the MuSiC framework is widely applicable to a broad set of tumor types and offers the benefits of automation as well as standardization. Herein, we describe the computational structure and statistical underpinnings of the MuSiC pipeline and demonstrate its performance using 316 ovarian cancer samples from the TCGA ovarian cancer project. MuSiC correctly confirms many expected results, and identifies several potentially novel avenues for discovery. PMID:22759861

  6. An Inherited Efficiencies Model of Non-Genomic Evolution

    Science.gov (United States)

    New, Michael H.; Pohorille, Andrew

    1999-01-01

    A model for the evolution of biological systems in the absence of a nucleic acid-like genome is proposed and applied to model the earliest living organisms -- protocells composed of membrane encapsulated peptides. Assuming that the peptides can make and break bonds between amino acids, and bonds in non-functional peptides are more likely to be destroyed than in functional peptides, it is demonstrated that the catalytic capabilities of the system as a whole can increase. This increase is defined to be non-genomic evolution. The relationship between the proposed mechanism for evolution and recent experiments on self-replicating peptides is discussed.

  7. Evolutionary and ecological genomics of non-model plants

    Institute of Scientific and Technical Information of China (English)

    Bao-Hua SONG; Thomas MITCHELL-OLDS

    2011-01-01

    Dissecting evolutionary dynamics of ecologically important traits is a long-term challenge for biologists.Attempts to understand natural variation and molecular mechanisms have motivated a move from laboratory model systems to non-model systems in diverse natural environments.Next generation sequencing methods,along with an expansion of genomic resources and tools,have fostered new links between diverse disciplines,including molecular biology,evolution,ecology,and genomics.Great progress has been made in a few non-model wild plants,such as Arabidopsis relatives,monkey flowers,and wild sunflowers.Until recently,the lack of comprehensive genomic information has limited evolutionary and ecological studies to larger QTL (quantitative trait locus) regions rather than single gene resolution,and has hindered recognition of general patterns of natural variation and local adaptation.Further efforts in accumulating genomic data and developing bioinformatic and biostatistical tools are now poised to move this field forward.Integrative national and international collaborations and research communities are needed to facilitate development in the field of evolutionary and ecological genomics.

  8. Mouse models of anemia of cancer.

    Directory of Open Access Journals (Sweden)

    Airie Kim

    Full Text Available Anemia of cancer (AC may contribute to cancer-related fatigue and impair quality of life. Improved understanding of the pathogenesis of AC could facilitate better treatment, but animal models to study AC are lacking. We characterized four syngeneic C57BL/6 mouse cancers that cause AC. Mice with two different rapidly-growing metastatic lung cancers developed the characteristic findings of anemia of inflammation (AI, with dramatically different degrees of anemia. Mice with rapidly-growing metastatic melanoma also developed a severe anemia by 14 days, with hematologic and inflammatory parameters similar to AI. Mice with a slow-growing peritoneal ovarian cancer developed an iron-deficiency anemia, likely secondary to chronically impaired nutrition and bleeding into the peritoneal cavity. Of the four models, hepcidin mRNA levels were increased only in the milder lung cancer model. Unlike in our model of systemic inflammation induced by heat-killed Brucella abortus, ablation of hepcidin in the ovarian cancer and the milder lung cancer mouse models did not affect the severity of anemia. Hepcidin-independent mechanisms play an important role in these murine models of AC.

  9. Pathway-based analysis using genome-wide association data from a Korean non-small cell lung cancer study.

    Directory of Open Access Journals (Sweden)

    Donghoon Lee

    Full Text Available Pathway-based analysis, used in conjunction with genome-wide association study (GWAS techniques, is a powerful tool to detect subtle but systematic patterns in genome that can help elucidate complex diseases, like cancers. Here, we stepped back from genetic polymorphisms at a single locus and examined how multiple association signals can be orchestrated to find pathways related to lung cancer susceptibility. We used single-nucleotide polymorphism (SNP array data from 869 non-small cell lung cancer (NSCLC cases from a previous GWAS at the National Cancer Center and 1,533 controls from the Korean Association Resource project for the pathway-based analysis. After mapping single-nucleotide polymorphisms to genes, considering their coding region and regulatory elements (±20 kbp, multivariate logistic regression of additive and dominant genetic models were fitted against disease status, with adjustments for age, gender, and smoking status. Pathway statistics were evaluated using Gene Set Enrichment Analysis (GSEA and Adaptive Rank Truncated Product (ARTP methods. Among 880 pathways, 11 showed relatively significant statistics compared to our positive controls (PGSEA≤0.025, false discovery rate≤0.25. Candidate pathways were validated using the ARTP method and similarities between pathways were computed against each other. The top-ranked pathways were ABC Transporters (PGSEA<0.001, PARTP = 0.001, VEGF Signaling Pathway (PGSEA<0.001, PARTP = 0.008, G1/S Check Point (PGSEA = 0.004, PARTP = 0.013, and NRAGE Signals Death through JNK (PGSEA = 0.006, PARTP = 0.001. Our results demonstrate that pathway analysis can shed light on post-GWAS research and help identify potential targets for cancer susceptibility.

  10. A whole-genome sequence and transcriptome perspective on HER2-positive breast cancers.

    Science.gov (United States)

    Ferrari, Anthony; Vincent-Salomon, Anne; Pivot, Xavier; Sertier, Anne-Sophie; Thomas, Emilie; Tonon, Laurie; Boyault, Sandrine; Mulugeta, Eskeatnaf; Treilleux, Isabelle; MacGrogan, Gaëtan; Arnould, Laurent; Kielbassa, Janice; Le Texier, Vincent; Blanché, Hélène; Deleuze, Jean-François; Jacquemier, Jocelyne; Mathieu, Marie-Christine; Penault-Llorca, Frédérique; Bibeau, Frédéric; Mariani, Odette; Mannina, Cécile; Pierga, Jean-Yves; Trédan, Olivier; Bachelot, Thomas; Bonnefoi, Hervé; Romieu, Gilles; Fumoleau, Pierre; Delaloge, Suzette; Rios, Maria; Ferrero, Jean-Marc; Tarpin, Carole; Bouteille, Catherine; Calvo, Fabien; Gut, Ivo Glynne; Gut, Marta; Martin, Sancha; Nik-Zainal, Serena; Stratton, Michael R; Pauporté, Iris; Saintigny, Pierre; Birnbaum, Daniel; Viari, Alain; Thomas, Gilles

    2016-01-01

    HER2-positive breast cancer has long proven to be a clinically distinct class of breast cancers for which several targeted therapies are now available. However, resistance to the treatment associated with specific gene expressions or mutations has been observed, revealing the underlying diversity of these cancers. Therefore, understanding the full extent of the HER2-positive disease heterogeneity still remains challenging. Here we carry out an in-depth genomic characterization of 64 HER2-positive breast tumour genomes that exhibit four subgroups, based on the expression data, with distinctive genomic features in terms of somatic mutations, copy-number changes or structural variations. The results suggest that, despite being clinically defined by a specific gene amplification, HER2-positive tumours melt into the whole luminal-basal breast cancer spectrum rather than standing apart. The results also lead to a refined ERBB2 amplicon of 106 kb and show that several cases of amplifications are compatible with a breakage-fusion-bridge mechanism. PMID:27406316

  11. Five endometrial cancer risk loci identified through genome-wide association analysis.

    Science.gov (United States)

    Cheng, Timothy H T; Thompson, Deborah J; O'Mara, Tracy A; Painter, Jodie N; Glubb, Dylan M; Flach, Susanne; Lewis, Annabelle; French, Juliet D; Freeman-Mills, Luke; Church, David; Gorman, Maggie; Martin, Lynn; Hodgson, Shirley; Webb, Penelope M; Attia, John; Holliday, Elizabeth G; McEvoy, Mark; Scott, Rodney J; Henders, Anjali K; Martin, Nicholas G; Montgomery, Grant W; Nyholt, Dale R; Ahmed, Shahana; Healey, Catherine S; Shah, Mitul; Dennis, Joe; Fasching, Peter A; Beckmann, Matthias W; Hein, Alexander; Ekici, Arif B; Hall, Per; Czene, Kamila; Darabi, Hatef; Li, Jingmei; Dörk, Thilo; Dürst, Matthias; Hillemanns, Peter; Runnebaum, Ingo; Amant, Frederic; Schrauwen, Stefanie; Zhao, Hui; Lambrechts, Diether; Depreeuw, Jeroen; Dowdy, Sean C; Goode, Ellen L; Fridley, Brooke L; Winham, Stacey J; Njølstad, Tormund S; Salvesen, Helga B; Trovik, Jone; Werner, Henrica M J; Ashton, Katie; Otton, Geoffrey; Proietto, Tony; Liu, Tao; Mints, Miriam; Tham, Emma; Li, Mulin Jun; Yip, Shun H; Wang, Junwen; Bolla, Manjeet K; Michailidou, Kyriaki; Wang, Qin; Tyrer, Jonathan P; Dunlop, Malcolm; Houlston, Richard; Palles, Claire; Hopper, John L; Peto, Julian; Swerdlow, Anthony J; Burwinkel, Barbara; Brenner, Hermann; Meindl, Alfons; Brauch, Hiltrud; Lindblom, Annika; Chang-Claude, Jenny; Couch, Fergus J; Giles, Graham G; Kristensen, Vessela N; Cox, Angela; Cunningham, Julie M; Pharoah, Paul D P; Dunning, Alison M; Edwards, Stacey L; Easton, Douglas F; Tomlinson, Ian; Spurdle, Amanda B

    2016-06-01

    We conducted a meta-analysis of three endometrial cancer genome-wide association studies (GWAS) and two follow-up phases totaling 7,737 endometrial cancer cases and 37,144 controls of European ancestry. Genome-wide imputation and meta-analysis identified five new risk loci of genome-wide significance at likely regulatory regions on chromosomes 13q22.1 (rs11841589, near KLF5), 6q22.31 (rs13328298, in LOC643623 and near HEY2 and NCOA7), 8q24.21 (rs4733613, telomeric to MYC), 15q15.1 (rs937213, in EIF2AK4, near BMF) and 14q32.33 (rs2498796, in AKT1, near SIVA1). We also found a second independent 8q24.21 signal (rs17232730). Functional studies of the 13q22.1 locus showed that rs9600103 (pairwise r(2) = 0.98 with rs11841589) is located in a region of active chromatin that interacts with the KLF5 promoter region. The rs9600103[T] allele that is protective in endometrial cancer suppressed gene expression in vitro, suggesting that regulation of the expression of KLF5, a gene linked to uterine development, is implicated in tumorigenesis. These findings provide enhanced insight into the genetic and biological basis of endometrial cancer. PMID:27135401

  12. Genomic DNA copy-number alterations of the let-7 family in human cancers.

    Directory of Open Access Journals (Sweden)

    Yanling Wang

    Full Text Available In human cancer, expression of the let-7 family is significantly reduced, and this is associated with shorter survival times in patients. However, the mechanisms leading to let-7 downregulation in cancer are still largely unclear. Since an alteration in copy-number is one of the causes of gene deregulation in cancer, we examined copy number alterations of the let-7 family in 2,969 cancer specimens from a high-resolution SNP array dataset. We found that there was a reduction in the copy number of let-7 genes in a cancer-type specific manner. Importantly, focal deletion of four let-7 family members was found in three cancer types: medulloblastoma (let-7a-2 and let-7e, breast cancer (let-7a-2, and ovarian cancer (let-7a-3/let-7b. For example, the genomic locus harboring let-7a-3/let-7b was deleted in 44% of the specimens from ovarian cancer patients. We also found a positive correlation between the copy number of let-7b and mature let-7b expression in ovarian cancer. Finally, we showed that restoration of let-7b expression dramatically reduced ovarian tumor growth in vitro and in vivo. Our results indicate that copy number deletion is an important mechanism leading to the downregulation of expression of specific let-7 family members in medulloblastoma, breast, and ovarian cancers. Restoration of let-7 expression in tumor cells could provide a novel therapeutic strategy for the treatment of cancer.

  13. Genome-wide association study of coronary and aortic calcification in lung cancer screening CT

    Science.gov (United States)

    de Vos, Bob D.; van Setten, Jessica; de Jong, Pim A.; Mali, Willem P.; Oudkerk, Matthijs; Viergever, Max A.; Išgum, Ivana

    2016-03-01

    Arterial calcification has been related to cardiovascular disease (CVD) and osteoporosis. However, little is known about the role of genetics and exact pathways leading to arterial calcification and its relation to bone density changes indicating osteoporosis. In this study, we conducted a genome-wide association study of arterial calcification burden, followed by a look-up of known single nucleotide polymorphisms (SNPs) for coronary artery disease (CAD) and myocardial infarction (MI), and bone mineral density (BMD) to test for a shared genetic basis between the traits. The study included a subcohort of the Dutch-Belgian lung cancer screening trial comprised of 2,561 participants. Participants underwent baseline CT screening in one of two hospitals participating in the trial. Low-dose chest CT images were acquired without contrast enhancement and without ECG-synchronization. In these images coronary and aortic calcifications were identified automatically. Subsequently, the detected calcifications were quantified using coronary artery calcium Agatston and volume scores. Genotype data was available for these participants. A genome-wide association study was conducted on 10,220,814 SNPs using a linear regression model. To reduce multiple testing burden, known CAD/MI and BMD SNPs were specifically tested (45 SNPs from the CARDIoGRAMplusC4D consortium and 60 SNPS from the GEFOS consortium). No novel significant SNPs were found. Significant enrichment for CAD/MI SNPs was observed in testing Agatston and coronary artery calcium volume scores. Moreover, a significant enrichment of BMD SNPs was shown in aortic calcium volume scores. This may indicate genetic relation of BMD SNPs and arterial calcification burden.

  14. Animal Models of Cancer Pain

    OpenAIRE

    Pacharinsak, Cholawat; Beitz, Alvin

    2008-01-01

    Modern cancer therapies have significantly increased patient survival rates in both human and veterinary medicine. Since cancer patients live longer they now face new challenges resulting from severe, chronic tumor-induced pain. Unrelieved cancer pain significantly decreases the quality of life of such patients; thus the goal of pain management is to not only to alleviate pain, but also to maintain the patient's physiological and psychological well-being. The major impediment for developing n...

  15. MuSiC: Identifying mutational significance in cancer genomes

    OpenAIRE

    Dees, Nathan D.; Zhang, Qunyuan; Kandoth, Cyriac; Wendl, Michael C.; Schierding, William; Koboldt, Daniel C.; Mooney, Thomas B.; Matthew B Callaway; Dooling, David; Elaine R Mardis; Wilson, Richard K.; Ding, Li

    2012-01-01

    Massively parallel sequencing technology and the associated rapidly decreasing sequencing costs have enabled systemic analyses of somatic mutations in large cohorts of cancer cases. Here we introduce a comprehensive mutational analysis pipeline that uses standardized sequence-based inputs along with multiple types of clinical data to establish correlations among mutation sites, affected genes and pathways, and to ultimately separate the commonly abundant passenger mutations from the truly sig...

  16. ANIMAL MODELS OF CANCER: A REVIEW

    Directory of Open Access Journals (Sweden)

    Archana M. Navale

    2013-01-01

    Full Text Available Cancer is the second leading cause of death worldwide. In USA three persons out of five will develop some type of cancer. Beyond these statistics of mortality, the morbidity due to cancer presents a real scary picture. Last 50 years of research has rendered some types of cancer curable, but still the major fear factor associated with this disease is unchanged. Animal models are classified according to the method of induction of cancer in the animal. Spontaneous tumor models are the most primitive models. Although these models show good resemblance to the natural disease in humans, they were not capable of keeping pace with developing experimental therapeutics programs. It has therefore been necessary to take a further step towards artificiality, away from the clinical problem in the search for satisfactory testing method. From this step, the journey of artificially induced tumor models started. It is possible to induce cancer reproducibly in animals by exposing them to various agents and now, by transplanting tumor cells or tissue. The development of Genetically Engineered Animal models has provided a great help in knowing the disease. This article takes a review of present animal models used in anti-cancer drug discovery.

  17. 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......,023 prostate cancer patients (3,513 disease-specific deaths) from the PRACTICAL and BPC3 consortia. Top findings were assessed for replication in a Norwegian cohort (CONOR). RESULTS: We observed no significant association between genetic variants and prostate cancer survival. CONCLUSIONS: Common genetic...... variants with large impact on prostate cancer survival were not observed in this study. IMPACT: Future studies should be designed for identification of rare variants with large effect sizes or common variants with small effect sizes....

  18. Insights into pancreatic cancer etiology from pathway analysis of genome-wide association study data.

    Directory of Open Access Journals (Sweden)

    Peng Wei

    Full Text Available Pancreatic cancer is the fourth leading cause of cancer death in the U.S. and the etiology of this highly lethal disease has not been well defined. To identify genetic susceptibility factors for pancreatic cancer, we conducted pathway analysis of genome-wide association study (GWAS data in 3,141 pancreatic cancer patients and 3,367 controls with European ancestry.Using the gene set ridge regression in association studies (GRASS method, we analyzed 197 pathways identified from the Kyoto Encyclopedia of Genes and Genomes database. We used the logistic kernel machine (LKM test to identify major contributing genes to each pathway. We conducted functional enrichment analysis of the most significant genes (P<0.01 using the Database for Annotation, Visualization, and Integrated Discovery (DAVID.Two pathways were significantly associated with risk of pancreatic cancer after adjusting for multiple comparisons (P<0.00025 and in replication testing: neuroactive ligand-receptor interaction, (Ps<0.00002, and the olfactory transduction pathway (P = 0.0001. LKM test identified four genes that were significantly associated with risk of pancreatic cancer after Bonferroni correction (P<1×10(-5: ABO, HNF1A, OR13C4, and SHH. Functional enrichment analysis using DAVID consistently found the G protein-coupled receptor signaling pathway (including both neuroactive ligand-receptor interaction and olfactory transduction pathways to be the most significant pathway for pancreatic cancer risk in this study population.These novel findings provide new perspectives on genetic susceptibility to and molecular mechanisms of pancreatic cancer.

  19. A genome-wide association study of upper aerodigestive tract cancers conducted within the INHANCE consortium.

    Directory of Open Access Journals (Sweden)

    James D McKay

    2011-03-01

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

  20. A genome-wide association study of upper aerodigestive tract cancers conducted within the INHANCE consortium.

    LENUS (Irish Health Repository)

    McKay, James D

    2011-03-01

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

  1. Genetically engineered mouse models of prostate cancer

    NARCIS (Netherlands)

    Nawijn, Martijn C.; Bergman, Andreas M.; van der Poel, Henk G.

    2008-01-01

    Objectives: Mouse models of prostate cancer are used to test the contribution of individual genes to the transformation process, evaluate the collaboration between multiple genetic lesions observed in a single tumour, and perform preclinical intervention studies in prostate cancer research. Methods:

  2. Genomic alterations in BCL2L1 and DLC1 contribute to drug sensitivity in gastric cancer.

    Science.gov (United States)

    Park, Hansoo; Cho, Sung-Yup; Kim, Hyerim; Na, Deukchae; Han, Jee Yun; Chae, Jeesoo; Park, Changho; Park, Ok-Kyoung; Min, Seoyeon; Kang, Jinjoo; Choi, Boram; Min, Jimin; Kwon, Jee Young; Suh, Yun-Suhk; Kong, Seong-Ho; Lee, Hyuk-Joon; Liu, Edison T; Kim, Jong-Il; Kim, Sunghoon; Yang, Han-Kwang; Lee, Charles

    2015-10-01

    Gastric cancer (GC) is the third leading cause of cancer-related deaths worldwide. Recent high-throughput analyses of genomic alterations revealed several driver genes and altered pathways in GC. However, therapeutic applications from genomic data are limited, largely as a result of the lack of druggable molecular targets and preclinical models for drug selection. To identify new therapeutic targets for GC, we performed array comparative genomic hybridization (aCGH) of DNA from 103 patients with GC for copy number alteration (CNA) analysis, and whole-exome sequencing from 55 GCs from the same patients for mutation profiling. Pathway analysis showed recurrent alterations in the Wnt signaling [APC, CTNNB1, and DLC1 (deleted in liver cancer 1)], ErbB signaling (ERBB2, PIK3CA, and KRAS), and p53 signaling/apoptosis [TP53 and BCL2L1 (BCL2-like 1)] pathways. In 18.4% of GC cases (19/103), amplification of the antiapoptotic gene BCL2L1 was observed, and subsequently a BCL2L1 inhibitor was shown to markedly decrease cell viability in BCL2L1-amplified cell lines and in similarly altered patient-derived GC xenografts, especially when combined with other chemotherapeutic agents. In 10.9% of cases (6/55), mutations in DLC1 were found and were also shown to confer a growth advantage for these cells via activation of Rho-ROCK signaling, rendering these cells more susceptible to a ROCK inhibitor. Taken together, our study implicates BCL2L1 and DLC1 as potential druggable targets for specific subsets of GC cases. PMID:26401016

  3. Recapitulating Human Gastric Cancer Pathogenesis: Experimental Models of Gastric Cancer.

    Science.gov (United States)

    Ding, Lin; El Zaatari, Mohamad; Merchant, Juanita L

    2016-01-01

    This review focuses on the various experimental models to study gastric cancer pathogenesis, with the role of genetically engineered mouse models (GEMMs) used as the major examples. We review differences in human stomach anatomy compared to the stomachs of the experimental models, including the mouse and invertebrate models such as Drosophila and C. elegans. The contribution of major signaling pathways, e.g., Notch, Hedgehog, AKT/PI3K is discussed in the context of their potential contribution to foregut tumorigenesis. We critically examine the rationale behind specific GEMMs, chemical carcinogens, dietary promoters, Helicobacter infection, and direct mutagenesis of relevant oncogenes and tumor suppressor that have been developed to study gastric cancer pathogenesis. Despite species differences, more efficient and effective models to test specific genes and pathways disrupted in human gastric carcinogenesis have yet to emerge. As we better understand these species differences, "humanized" versions of mouse models will more closely approximate human gastric cancer pathogenesis. Towards that end, epigenetic marks on chromatin, the gut microbiota, and ways of manipulating the immune system will likely move center stage, permitting greater overlap between rodent and human cancer phenotypes thus providing a unified progression model. PMID:27573785

  4. The Genomic and Proteomic Content of Cancer Cell-Derived Exosomes

    Directory of Open Access Journals (Sweden)

    Meredith C Henderson

    2012-04-01

    Full Text Available 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 mRNA, miRNA, 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.

  5. NMD Microarray Analysis for Rapid Genome-Wide Screen of Mutated Genes in Cancer

    Directory of Open Access Journals (Sweden)

    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.

  6. A genome-wide association study of breast cancer in women of African ancestry

    OpenAIRE

    Chen, Fang; Chen, Gary K.; Stram, Daniel O.; Millikan, Robert C.; Ambrosone, Christine B.; John, Esther M; Bernstein, Leslie; Zheng, Wei; Palmer, Julie R.; Jennifer J Hu; Rebbeck, Tim R.; Ziegler, Regina G.; Nyante, Sarah; Bandera, Elisa V.; Sue A Ingles

    2012-01-01

    Genome-wide association studies (GWAS) in diverse populations are needed to reveal variants that are more common and/or limited to defined populations. We conducted a GWAS of breast cancer in women of African ancestry, with genotyping of > 1,000,000 SNPs in 3,153 African American cases and 2,831 controls, and replication testing of the top 66 associations in an additional 3,607 breast cancer cases and 11,330 controls of African ancestry. Two of the 66 SNPs replicated (p < 0.05) in stage 2, wh...

  7. Time-dependent ARMA modeling of genomic sequences

    Directory of Open Access Journals (Sweden)

    Schonfeld Dan

    2008-08-01

    Full Text Available Abstract Background Over the past decade, many investigators have used sophisticated time series tools for the analysis of genomic sequences. Specifically, the correlation of the nucleotide chain has been studied by examining the properties of the power spectrum. The main limitation of the power spectrum is that it is restricted to stationary time series. However, it has been observed over the past decade that genomic sequences exhibit non-stationary statistical behavior. Standard statistical tests have been used to verify that the genomic sequences are indeed not stationary. More recent analysis of genomic data has relied on time-varying power spectral methods to capture the statistical characteristics of genomic sequences. Techniques such as the evolutionary spectrum and evolutionary periodogram have been successful in extracting the time-varying correlation structure. The main difficulty in using time-varying spectral methods is that they are extremely unstable. Large deviations in the correlation structure results from very minor perturbations in the genomic data and experimental procedure. A fundamental new approach is needed in order to provide a stable platform for the non-stationary statistical analysis of genomic sequences. Results In this paper, we propose to model non-stationary genomic sequences by a time-dependent autoregressive moving average (TD-ARMA process. The model is based on a classical ARMA process whose coefficients are allowed to vary with time. A series expansion of the time-varying coefficients is used to form a generalized Yule-Walker-type system of equations. A recursive least-squares algorithm is subsequently used to estimate the time-dependent coefficients of the model. The non-stationary parameters estimated are used as a basis for statistical inference and biophysical interpretation of genomic data. In particular, we rely on the TD-ARMA model of genomic sequences to investigate the statistical properties and

  8. Whole-genome sequencing identifies genomic heterogeneity at a nucleotide and chromosomal level in bladder cancer

    OpenAIRE

    Morrison, Carl D.; Liu, Pengyuan; Woloszynska-Read, Anna; Zhang, Jianmin; Luo, Wei; Qin, Maochun; Bshara, Wiam; Conroy, Jeffrey M; Sabatini, Linda; Vedell, Peter; Xiong, Donghai; Liu, Song; Wang, Jianmin; Shen, He; Li, Yinwei

    2014-01-01

    Genetic alterations are frequently observed in bladder cancer. In this study, we demonstrate that bladder tumors can be classified into two different types based on the spectrum of genetic diversity they confer. In one class of tumors, we observed tumor protein p53 mutations and a large number of single-nucleotide and structural variants. Another characteristic of this group was chromosome shattering, known as chromothripsis, and mutational heterogeneity. The other two bladder tumors did not ...

  9. Functional genomics identifies therapeutic targets for MYC-driven cancer

    OpenAIRE

    Toyoshima, Masafumi; Howie, Heather L; Imakura, Maki; Walsh, Ryan M.; Annis, James E.; Chang, Aaron N; Frazier, Jason; Chau, B. Nelson; Loboda, Andrey; Linsley, Peter S; Cleary, Michele A.; Park, Julie R.; Grandori, Carla

    2012-01-01

    MYC oncogene family members are broadly implicated in human cancers, yet are considered “undruggable” as they encode transcription factors. MYC also carries out essential functions in proliferative tissues, suggesting that its inhibition could cause severe side effects. We elected to identify synthetic lethal interactions with c-MYC overexpression (MYC-SL) in a collection of ∼3,300 druggable genes, using high-throughput siRNA screening. Of 49 genes selected for follow-up, 48 were confirmed by...

  10. The utility of Apc-mutant rats in modeling human colon cancer

    Directory of Open Access Journals (Sweden)

    Amy A. Irving

    2014-11-01

    Full Text Available Prior to the advent of genetic engineering in the mouse, the rat was the model of choice for investigating the etiology of cancer. Now, recent advances in the manipulation of the rat genome, combined with a growing recognition of the physiological differences between mice and rats, have reignited interest in the rat as a model of human cancer. Two recently developed rat models, the polyposis in the rat colon (Pirc and Kyoto Apc Delta (KAD strains, each carry mutations in the intestinal-cancer-associated adenomatous polyposis coli (Apc gene. In contrast to mouse models carrying Apc mutations, in which cancers develop mainly in the small intestine rather than in the colon and there is no gender bias, these rat models exhibit colonic predisposition and gender-specific susceptibility, as seen in human colon cancer. The rat also provides other experimental resources as a model organism that are not provided by the mouse: the structure of its chromosomes facilitates the analysis of genomic events, the size of its colon permits longitudinal analysis of tumor growth, and the size of biological samples from the animal facilitates multiplexed molecular analyses of the tumor and its host. Thus, the underlying biology and experimental resources of these rat models provide important avenues for investigation. We anticipate that advances in disease modeling in the rat will synergize with resources that are being developed in the mouse to provide a deeper understanding of human colon cancer.

  11. Genetic imbalances in precursor lesions of endometrial cancer detected by comparative genomic hybridization.

    Science.gov (United States)

    Kiechle, M; Hinrichs, M; Jacobsen, A; Lüttges, J; Pfisterer, J; Kommoss, F; Arnold, N

    2000-06-01

    Endometrial hyperplasia is regarded as a precursor lesion of endometrioid adenocarcinomas of the endometrium. The genetic events involved in the multistep process from normal endometrial glandular tissue to invasive endometrial carcinomas are primarily unknown. We chose endometrial hyperplasia as a model for identifying chromosomal aberrations occurring during carcinogenesis. Comparative genomic hybridization (CGH) was performed on 47 formalin-fixed, paraffin-embedded specimens of endometrial hyperplasia using the microdissection technique to increase the number of tumor cells in the samples and reduce contamination from normal cells. CGH analysis revealed that 24 out of 47 (51%) samples had detectable chromosomal imbalances, whereas 23 (49%) were in a genetically balanced state. The incidence of aberrant CGH profiles tended to parallel dysplasia grade, ranging from 22% aberrant profiles in simple hyperplasia to 67% in complex hyperplasia with atypia. The most frequent imbalances were 1p, 16p, and 20q underrepresentations and 4q overrepresentations. Copy number changes in 1p were more frequent in atypical complex hyperplasia than in complex lesions without atypical cells or simple lesions (42% versus 20% and 0%). Our results show that endometrial hyperplasia reveals recurrent chromosomal imbalances which tend to increase with the presence of atypical cells. The most frequent aberrations in endometrial cancer, 1q and 8q overrepresentations, are not present or are rare in its precursor lesions. This analysis provides evidence that tumorigenesis proceeds through the accumulation of a series of genetic alterations and suggests a stepwise mode of tumorigenesis. PMID:10854205

  12. Short Inverted Repeats Are Hotspots for Genetic Instability: Relevance to Cancer Genomes

    Directory of Open Access Journals (Sweden)

    Steve Lu

    2015-03-01

    Full Text Available Analyses of chromosomal aberrations in human genetic disorders have revealed that inverted repeat sequences (IRs often co-localize with endogenous chromosomal instability and breakage hotspots. Approximately 80% of all IRs in the human genome are short (<100 bp, yet the mutagenic potential of such short cruciform-forming sequences has not been characterized. Here, we find that short IRs are enriched at translocation breakpoints in human cancer and stimulate the formation of DNA double-strand breaks (DSBs and deletions in mammalian and yeast cells. We provide evidence for replication-related mechanisms of IR-induced genetic instability and a novel XPF cleavage-based mechanism independent of DNA replication. These discoveries implicate short IRs as endogenous sources of DNA breakage involved in disease etiology and suggest that these repeats represent a feature of genome plasticity that may contribute to the evolution of the human genome by providing a means for diversity within the population.

  13. Genome-based versus gene-based theory of cancer: Possible implications for clinical practice

    Indian Academy of Sciences (India)

    Nataša Todorović-Raković

    2011-09-01

    The current state in oncology research indicates that the attempts to explain such complex process as cancerogenesis by a single or several genetic mutations were not successful enough. On the other hand, chromosomal/genomic instability – almost universal features of malignant tumours which influence a global pattern of gene expression and, subsequently, many oncogenic pathways – were often disregarded and considered nonessential to clinical application. However, a new arising field of system biology including ‘new forms’ of genome diversity such as copy number variations (CNV) and high-throughput oncogene mutation profiling now reveal all the complexity of cancer and provide the final explanation of the oncogenic pathways, based on stochastic (onco)genomic variation rather than on (onco)genic concepts.

  14. Functional genomic analysis of drug sensitivity pathways to guide adjuvant strategies in breast cancer

    DEFF Research Database (Denmark)

    Swanton, Charles; Szallasi, Zoltan Imre; Brenton, James D.;

    2008-01-01

    ) as well as endocrine therapies such as tamoxifen. Given the limited power of microarray signatures to predict therapeutic response in associative studies of small clinical trial cohorts, the use of functional genomic data combined with expression or sequence analysis of genes and microRNAs implicated...... in drug response in human tumours may provide a more robust method to guide adjuvant treatment strategies in breast cancer that are transferable across different expression platforms and patient cohorts....

  15. Expression genomics in breast cancer research: microarrays at the crossroads of biology and medicine

    OpenAIRE

    Miller, Lance D; Liu, Edison T

    2007-01-01

    Genome-wide expression microarray studies have revealed that the biological and clinical heterogeneity of breast cancer can be partly explained by information embedded within a complex but ordered transcriptional architecture. Comprising this architecture are gene expression networks, or signatures, reflecting biochemical and behavioral properties of tumors that might be harnessed to improve disease subtyping, patient prognosis and prediction of therapeutic response. Emerging 'hypothesis-driv...

  16. Genomics and premalignant breast lesions: clues to the development and progression of lobular breast cancer

    OpenAIRE

    Mastracci, Teresa L; Boulos, Fouad I; Andrulis, Irene L.; Lam, Wan L.

    2007-01-01

    Advances in genomic technology have improved our understanding of the genetic events that parallel breast cancer development. Because almost all mammary carcinomas develop in the terminal duct lobular units of the breast, understanding the events involved in mammary gland development make it possible to recognize those events that, when altered, contribute to breast neoplasia. In this review we focus on lobular carcinomas, discussing the pathology, development, and progression of premalignant...

  17. Structural variation discovery in the cancer genome using next generation sequencing: Computational solutions and perspectives

    OpenAIRE

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

    2015-01-01

    Somatic Structural Variations (SVs) are a complex collection of chromosomal mutations that could directly contribute to carcinogenesis. Next Generation Sequencing (NGS) technology has emerged as the primary means of interrogating the SVs of the cancer genome in recent investigations. Sophisticated computational methods are required to accurately identify the SV events and delineate their breakpoints from the massive amounts of reads generated by a NGS experiment. In this review, we provide an...

  18. BiGG Models: A platform for integrating, standardizing and sharing genome-scale models.

    Science.gov (United States)

    King, Zachary A; Lu, Justin; Dräger, Andreas; Miller, Philip; Federowicz, Stephen; Lerman, Joshua A; Ebrahim, Ali; Palsson, Bernhard O; Lewis, Nathan E

    2016-01-01

    Genome-scale metabolic models are mathematically-structured knowledge bases that can be used to predict metabolic pathway usage and growth phenotypes. Furthermore, they can generate and test hypotheses when integrated with experimental data. To maximize the value of these models, centralized repositories of high-quality models must be established, models must adhere to established standards and model components must be linked to relevant databases. Tools for model visualization further enhance their utility. To meet these needs, we present BiGG Models (http://bigg.ucsd.edu), a completely redesigned Biochemical, Genetic and Genomic knowledge base. BiGG Models contains more than 75 high-quality, manually-curated genome-scale metabolic models. On the website, users can browse, search and visualize models. BiGG Models connects genome-scale models to genome annotations and external databases. Reaction and metabolite identifiers have been standardized across models to conform to community standards and enable rapid comparison across models. Furthermore, BiGG Models provides a comprehensive application programming interface for accessing BiGG Models with modeling and analysis tools. As a resource for highly curated, standardized and accessible models of metabolism, BiGG Models will facilitate diverse systems biology studies and support knowledge-based analysis of diverse experimental data.

  19. BiGG Models: A platform for integrating, standardizing and sharing genome-scale models.

    Science.gov (United States)

    King, Zachary A; Lu, Justin; Dräger, Andreas; Miller, Philip; Federowicz, Stephen; Lerman, Joshua A; Ebrahim, Ali; Palsson, Bernhard O; Lewis, Nathan E

    2016-01-01

    Genome-scale metabolic models are mathematically-structured knowledge bases that can be used to predict metabolic pathway usage and growth phenotypes. Furthermore, they can generate and test hypotheses when integrated with experimental data. To maximize the value of these models, centralized repositories of high-quality models must be established, models must adhere to established standards and model components must be linked to relevant databases. Tools for model visualization further enhance their utility. To meet these needs, we present BiGG Models (http://bigg.ucsd.edu), a completely redesigned Biochemical, Genetic and Genomic knowledge base. BiGG Models contains more than 75 high-quality, manually-curated genome-scale metabolic models. On the website, users can browse, search and visualize models. BiGG Models connects genome-scale models to genome annotations and external databases. Reaction and metabolite identifiers have been standardized across models to conform to community standards and enable rapid comparison across models. Furthermore, BiGG Models provides a comprehensive application programming interface for accessing BiGG Models with modeling and analysis tools. As a resource for highly curated, standardized and accessible models of metabolism, BiGG Models will facilitate diverse systems biology studies and support knowledge-based analysis of diverse experimental data. PMID:26476456

  20. A Three-Dimensional Model of the Yeast Genome

    Science.gov (United States)

    Noble, William; Duan, Zhi-Jun; Andronescu, Mirela; Schutz, Kevin; McIlwain, Sean; Kim, Yoo Jung; Lee, Choli; Shendure, Jay; Fields, Stanley; Blau, C. Anthony

    Layered on top of information conveyed by DNA sequence and chromatin are higher order structures that encompass portions of chromosomes, entire chromosomes, and even whole genomes. Interphase chromosomes are not positioned randomly within the nucleus, but instead adopt preferred conformations. Disparate DNA elements co-localize into functionally defined aggregates or factories for transcription and DNA replication. In budding yeast, Drosophila and many other eukaryotes, chromosomes adopt a Rabl configuration, with arms extending from centromeres adjacent to the spindle pole body to telomeres that abut the nuclear envelope. Nonetheless, the topologies and spatial relationships of chromosomes remain poorly understood. Here we developed a method to globally capture intra- and inter-chromosomal interactions, and applied it to generate a map at kilobase resolution of the haploid genome of Saccharomyces cerevisiae. The map recapitulates known features of genome organization, thereby validating the method, and identifies new features. Extensive regional and higher order folding of individual chromosomes is observed. Chromosome XII exhibits a striking conformation that implicates the nucleolus as a formidable barrier to interaction between DNA sequences at either end. Inter-chromosomal contacts are anchored by centromeres and include interactions among transfer RNA genes, among origins of early DNA replication and among sites where chromosomal breakpoints occur. Finally, we constructed a three-dimensional model of the yeast genome. Our findings provide a glimpse of the interface between the form and function of a eukaryotic genome.

  1. European genome-wide association study identifies SLC14A1 as a new urinary bladder cancer susceptibility gene

    NARCIS (Netherlands)

    Rafnar, T.; Vermeulen, H.H.M.; Sulem, P.; Thorleifsson, G.; Aben, K.K.H.; Witjes, J.A.; Grotenhuis, A.J.; Verhaegh, G.W.C.T.; Hulsbergen- van de Kaa, C.A.; Besenbacher, S.; Gudbjartsson, D.; Stacey, S.N.; Gudmundsson, J.; Johannsdottir, H.; Bjarnason, H.; Zanon, C.; Helgadottir, H.; Jonasson, J.G.; Tryggvadottir, L.; Jonsson, E.; Geirsson, G.; Nikulasson, S.; Petursdottir, V.; Bishop, D.T.; Chung-Sak, S.; Choudhury, A.; Elliott, F.; Barrett, J.H.; Knowles, M.A.; Verdier, P. de; Ryk, C.; Lindblom, A.; Rudnai, P.; Gurzau, E.; Koppova, K.; Vineis, P.; Polidoro, S.; Guarrera, S.; Sacerdote, C.; Panadero, A.; Sanz-Velez, J.I.; Sanchez, M.; Valdivia, G.; Garcia-Prats, M.D.; Hengstler, J.G.; Selinski, S.; Gerullis, H.; Ovsiannikov, D.; Khezri, A.; Aminsharifi, A.; Malekzadeh, M.; Berg, L.H. van den; Ophoff, R.A.; Veldink, J.H.; Zeegers, M.P.; Kellen, E.; Fostinelli, J.; Andreoli, D.; Arici, C.; Porru, S.; Buntinx, F.; Ghaderi, A.; Golka, K.; Mayordomo, J.I.; Matullo, G.; Kumar, R.; Steineck, G.; Kiltie, A.E.; Kong, A.; Thorsteinsdottir, U.; Stefansson, K.; Kiemeney, L.A.L.M.

    2011-01-01

    Three genome-wide association studies in Europe and the USA have reported eight urinary bladder cancer (UBC) susceptibility loci. Using extended case and control series and 1000 Genomes imputations of 5 340 737 single-nucleotide polymorphisms (SNPs), we searched for additional loci in the European G

  2. Large BRCA1 and BRCA2 genomic rearrangements in Danish high risk breast-ovarian cancer families

    DEFF Research Database (Denmark)

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

    2009-01-01

    BRCA1 and BRCA2 germ-line mutations predispose to breast and ovarian cancer. Large genomic rearrangements of BRCA1 account for 0-36% of all disease causing mutations in various populations, while large genomic rearrangements in BRCA2 are more rare. We examined 642 East Danish breast and/or ovarian...

  3. 1-Mb resolution array-based comparative genomic hybridization using a BAC clone set optimized for cancer gene analysis

    NARCIS (Netherlands)

    Greshock, J; Naylor, TL; Margolin, A; Diskin, S; Cleaver, SH; Futreal, PA; deJong, PJ; Zhao, SY; Liebman, M; Weber, BL

    2004-01-01

    Array-based comparative genomic hybridization (aCGH) is a recently developed tool for genome-wide determination of DNA copy number alterations. This technology has tremendous potential for disease-gene discovery in cancer and developmental disorders as well as numerous other applications. However, w

  4. Genomic alterations indicate tumor origin and varied metastatic potential of disseminated cells from prostate-cancer patients

    OpenAIRE

    Holcomb, Ilona N.; Grove, Douglas I.; Kinnunen, Martin; Friedman, Cynthia L.; Gallaher, Ian S.; Todd M. Morgan; Sather, Cassandra L.; Delrow, Jeffrey J; Peter S Nelson; Lange, Paul H.; Ellis, William J; True, Lawrence D.; Janet M Young; Hsu, Li; Trask, Barbara J.

    2008-01-01

    Disseminated epithelial cells can be isolated from the bone marrow of a far greater fraction of prostate-cancer patients than the fraction of patients who progress to metastatic disease. To provide a better understanding of these cells, we have characterized their genomic alterations. We first present an array comparative genomic hybridization method capable of detecting genomic changes in the small number of disseminated cells (10-20) that can typically be obtained from bone-marrow aspirates...

  5. Epidemiological studies of esophageal cancer in the era of genome-wide association studies

    Institute of Scientific and Technical Information of China (English)

    An-Hui; Wang; Yuan; Liu; Bo; Wang; Yi-Xuan; He; Ye-Xian; Fang; Yong-Ping; Yan

    2014-01-01

    Esophageal cancer(EC) caused about 395000 deaths in 2010. China has the most cases of EC and EC is the fourth leading cause of cancer death in China. Esophageal squamous cell carcinoma(ESCC) is the predominant histologic type(90%-95%), while the incidence of esophageal adenocarcinoma(EAC) remains extremely low in China. Traditional epidemiological studies have revealed that environmental carcinogens are risk factors for EC. Molecular epidemiological studies revealed that susceptibility to EC is influenced by both environmental and genetic risk factors. Of all the risk factors for EC, some are associated with the risk of ESCC and others with the risk of EAC. However, the details and mechanisms of risk factors involved in the process for EC are unclear. The advanced methods and techniques used in human genome studies bring a great opportunity for researchers to explore and identify the details of those risk factors or susceptibility genes involved inthe process of EC. Human genome epidemiology is a new branch of epidemiology, which leads the epidemiology study from the molecular epidemiology era to the era of genome wide association studies(GWAS). Here we review the epidemiological studies of EC(especially ESCC) in the era of GWAS, and provide an overview of the general risk factors and those genomic variants(genes, SNPs, miRNAs, proteins) involved in the process of ESCC.

  6. A novel genomic alteration of LSAMP associates with aggressive prostate cancer in African American men

    Directory of Open Access Journals (Sweden)

    Gyorgy Petrovics

    2015-12-01

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

  7. A genome-wide scan for breast cancer risk haplotypes among African American women.

    Directory of Open Access Journals (Sweden)

    Chi Song

    Full Text Available Genome-wide association studies (GWAS simultaneously investigating hundreds of thousands of single nucleotide polymorphisms (SNP have become a powerful tool in the investigation of new disease susceptibility loci. Haplotypes are sometimes thought to be superior to SNPs and are promising in genetic association analyses. The application of genome-wide haplotype analysis, however, is hindered by the complexity of haplotypes themselves and sophistication in computation. We systematically analyzed the haplotype effects for breast cancer risk among 5,761 African American women (3,016 cases and 2,745 controls using a sliding window approach on the genome-wide scale. Three regions on chromosomes 1, 4 and 18 exhibited moderate haplotype effects. Furthermore, among 21 breast cancer susceptibility loci previously established in European populations, 10p15 and 14q24 are likely to harbor novel haplotype effects. We also proposed a heuristic of determining the significance level and the effective number of independent tests by the permutation analysis on chromosome 22 data. It suggests that the effective number was approximately half of the total (7,794 out of 15,645, thus the half number could serve as a quick reference to evaluating genome-wide significance if a similar sliding window approach of haplotype analysis is adopted in similar populations using similar genotype density.

  8. Genomic responses in mouse models poorly mimic human inflammatory diseases

    OpenAIRE

    Seok, Junhee; Warren, H. Shaw; Cuenca, Alex G.; Mindrinos, Michael N.; Baker, Henry V.; Xu, Weihong; Richards, Daniel R; McDonald-Smith, Grace P.; Gao, Hong; Hennessy, Laura; Finnerty, Celeste C.; López, Cecilia M.; Honari, Shari; Moore, Ernest E; Minei, Joseph P.

    2013-01-01

    A cornerstone of modern biomedical research is the use of mouse models to explore basic pathophysiological mechanisms, evaluate new therapeutic approaches, and make go or no-go decisions to carry new drug candidates forward into clinical trials. Systematic studies evaluating how well murine models mimic human inflammatory diseases are nonexistent. Here, we show that, although acute inflammatory stresses from different etiologies result in highly similar genomic responses in humans, the respon...

  9. Integrative genomic analyses of a novel cytokine, interleukin-34 and its potential role in cancer prediction.

    Science.gov (United States)

    Wang, Bo; Xu, Wenming; Tan, Miaolian; Xiao, Yan; Yang, Haiwei; Xia, Tian-Song

    2015-01-01

    Interleukin-34 (IL-34) is a novel cytokine, which is composed of 222 amino acids and forms homodimers. It binds to the macrophage colony-stimulating factor (M-CSF) receptor and plays an important role in innate immunity and inflammatory processes. In the present study, we identified the completed IL-34 gene in 25 various mammalian genomes and found that IL-34 existed in all types of vertebrates, including fish, amphibians, birds and mammals. These species have a similar 7 exon/6 intron gene organization. The phylogenetic tree indicated that the IL-34 gene from the primate lineage, rodent lineage and teleost lineage form a species-specific cluster. It was found mammalian that IL-34 was under positive selection pressure with the identified positively selected site, 196Val. Fifty-five functionally relevant single nucleotide polymorphisms (SNPs), including 32 SNPs causing missense mutations, 3 exonic splicing enhancer SNPs and 20 SNPs causing nonsense mutations were identified from 2,141 available SNPs in the human IL-34 gene. IL-34 was expressed in various types of cancer, including blood, brain, breast, colorectal, eye, head and neck, lung, ovarian and skin cancer. A total of 5 out of 40 tests (1 blood cancer, 1 brain cancer, 1 colorectal cancer and 2 lung cancer) revealed an association between IL-34 gene expression and cancer prognosis. It was found that the association between the expression of IL-34 and cancer prognosis varied in different types of cancer, even in the same types of cancer from different databases. This suggests that the function of IL-34 in these tumors may be multidimensional. The upstream transcription factor 1 (USF1), regulatory factor X-1 (RFX1), the Sp1 transcription factor 1 , POU class 3 homeobox 2 (POU3F2) and forkhead box L1 (FOXL1) regulatory transcription factor binding sites were identified in the IL-34 gene upstream (promoter) region, which may be involved in the effects of IL-34 in tumors. PMID:25395235

  10. Development of a Mouse Model of Menopausal Ovarian Cancer

    OpenAIRE

    Elizabeth R Smith; Ying eWang; Xiang-Xi Mike Xu

    2014-01-01

    Despite significant understanding of the genetic mutations involved in ovarian epithelial cancer and advances in genomic approaches for expression and mutation profiling of tumor tissues, several key questions in ovarian cancer biology remain enigmatic: the mechanism for the well-established impact of reproductive factors on ovarian cancer risk remains obscure; questions of the cell of origin of ovarian cancer continue to be debated; and the precursor lesion, sequence, or events in progressi...

  11. Genome-wide interrogation identifies YAP1 variants associated with survival of small-cell lung cancer patients.

    Science.gov (United States)

    Wu, Chen; Xu, Binghe; Yuan, Peng; Miao, Xiaoping; Liu, Yu; Guan, Yin; Yu, Dianke; Xu, Jian; Zhang, Tongwen; Shen, Hongbing; Wu, Tangchun; Lin, Dongxin

    2010-12-01

    Although most patients with small-cell lung cancer respond to chemotherapy, the survival time is highly diverse. We conducted a genome-wide analysis to examine whether germline genetic variations are prognostic factors in small-cell lung cancer patients treated with the same chemotherapy regimen. Genome-wide scan of single nucleotide polymorphisms (SNP) was performed using blood DNA to identify genotypes associated with overall survival in 245 patients treated with platinum-based chemotherapy, and the results were replicated in another independent set of 305 patients. Associations were estimated by Cox models and function of the variants was examined by biochemical assays. We found that rs1820453 T>G SNP within the promoter region of YAP1 on chromosome 11q22 and rs716274 A>G SNP in the region of downstream of DYNC2H1 on chromosome 11q22.3 are associated with small-cell lung cancer survival. In pooled analysis of 2 independent cohorts, the adjusted hazard ratio for patients with the rs1820453 TG or GG genotype was 1.49 (95% CI, 1.19-1.85; P = 0.0004) and 1.65 (95% CI, 1.36-2.01; P = 4.76 × 10(-7)), respectively, compared with the TT genotype; and for patients with the rs716274 AG or GG genotype was 1.83 (95% CI, 1.47-2.29; P = 8.74 × 10(-8)) and 2.96 (95% CI, 1.90-4.62; P = 1.59 × 10(-6)), respectively, compared with the AA genotype. Functional analysis showed that the rs1820453 T>G change creates a transcriptional factor binding site and results in downregulation of YAP1 expression. These results suggest that YAP1 may play an important role in prognosis of small-cell lung cancer patients treated with platinum-based chemotherapy.

  12. Cancer Therapy Directed by Comprehensive Genomic Profiling: A Single Center Study.

    Science.gov (United States)

    Wheler, Jennifer J; Janku, Filip; Naing, Aung; Li, Yali; Stephen, Bettzy; Zinner, Ralph; Subbiah, Vivek; Fu, Siqing; Karp, Daniel; Falchook, Gerald S; Tsimberidou, Apostolia M; Piha-Paul, Sarina; Anderson, Roosevelt; Ke, Danxia; Miller, Vincent; Yelensky, Roman; Lee, J Jack; Hong, David S; Kurzrock, Razelle

    2016-07-01

    Innovative molecular diagnostics deployed in the clinic enable new ways to stratify patients into appropriate treatment regimens. These approaches may resolve a major challenge for early-phase clinical trials, which is to recruit patients who, while having failed previous treatments, may nevertheless respond to molecularly targeted drugs. We report the findings of a prospective, single-center study conducted in patients with diverse refractory cancers who underwent comprehensive genomic profiling (CGP; next-generation sequencing, 236 genes). Of the 500 patients enrolled, 188 (37.6%) received either matched (N = 122/188, 65%) or unmatched therapy (N = 66/188, 35%). The most common reasons that patients were not evaluable for treatment included insufficient tissue, death, or hospice transfer. The median number of molecular alterations per patient was five (range, 1-14); median number of prior therapies, four. The most common diagnoses were ovarian cancer (18%), breast cancer (16%), sarcoma (13%), and renal cancer (7%). Of the 339 successfully profiled patients, 317 (93.5%) had at least one potentially actionable alteration. By calculating matching scores, based on the number of drug matches and genomic aberrations per patient, we found that high scores were independently associated with a greater frequency of stable disease ≥6 months/partial/complete remission [22% (high scores) vs. 9% (low scores), P = 0.024], longer time-to-treatment failure [hazard ratio (HR) = 0.52; 95% confidence interval (CI) = 0.36-0.74; P = 0.0003], and survival (HR = 0.65; 95% CI = 0.43-1.0; P = 0.05). Collectively, this study offers a clinical proof of concept for the utility of CGP in assigning therapy to patients with refractory malignancies, especially in those patients with multiple genomic aberrations for whom combination therapies could be implemented. Cancer Res; 76(13); 3690-701. ©2016 AACR. PMID:27197177

  13. Identification of novel targets for breast cancer by exploring gene switches on a genome scale

    Directory of Open Access Journals (Sweden)

    Wu Ming

    2011-11-01

    Full Text Available Abstract Background An important feature that emerges from analyzing gene regulatory networks is the "switch-like behavior" or "bistability", a dynamic feature of a particular gene to preferentially toggle between two steady-states. The state of gene switches plays pivotal roles in cell fate decision, but identifying switches has been difficult. Therefore a challenge confronting the field is to be able to systematically identify gene switches. Results We propose a top-down mining approach to exploring gene switches on a genome-scale level. Theoretical analysis, proof-of-concept examples, and experimental studies demonstrate the ability of our mining approach to identify bistable genes by sampling across a variety of different conditions. Applying the approach to human breast cancer data identified genes that show bimodality within the cancer samples, such as estrogen receptor (ER and ERBB2, as well as genes that show bimodality between cancer and non-cancer samples, where tumor-associated calcium signal transducer 2 (TACSTD2 is uncovered. We further suggest a likely transcription factor that regulates TACSTD2. Conclusions Our mining approach demonstrates that one can capitalize on genome-wide expression profiling to capture dynamic properties of a complex network. To the best of our knowledge, this is the first attempt in applying mining approaches to explore gene switches on a genome-scale, and the identification of TACSTD2 demonstrates that single cell-level bistability can be predicted from microarray data. Experimental confirmation of the computational results suggest TACSTD2 could be a potential biomarker and attractive candidate for drug therapy against both ER+ and ER- subtypes of breast cancer, including the triple negative subtype.

  14. Genomic Testing and Therapies for Breast Cancer in Clinical Practice

    Science.gov (United States)

    Haas, Jennifer S.; Phillips, Kathryn A.; Liang, Su-Ying; Hassett, Michael J.; Keohane, Carol; Elkin, Elena B.; Armstrong, Joanne; Toscano, Michele

    2011-01-01

    Purpose: Given the likely proliferation of targeted testing and treatment strategies for cancer, a better understanding of the utilization patterns of human epidermal growth factor receptor 2 (HER2) testing and trastuzumab and newer gene expression profiling (GEP) for risk stratification and chemotherapy decision making are important. Study Design: Cross-sectional. Methods: We performed a medical record review of women age 35 to 65 years diagnosed between 2006 and 2007 with invasive localized breast cancer, identified using claims from a large national health plan (N = 775). Results: Almost all women received HER2 testing (96.9%), and 24.9% of women with an accepted indication received GEP. Unexplained socioeconomic differences in GEP use were apparent after adjusting for age and clinical characteristics; specifically, GEP use increased with income. For example, those in the lowest income category (< $40,000) were less likely than those with an income of $125,000 or more to receive GEP (odds ratio, 0.34; 95% CI, 0.16 to 0.73). A majority of women (57.7%) with HER2-positive disease received trastuzumab; among these women, differences in age and clinical characteristics were not apparent, although surprisingly, those in the lowest income category were more likely than those in the high-income category to receive trastuzumab (P = .02). Among women who did not have a positive HER2 test, 3.9% still received trastuzumab. Receipt of adjuvant chemotherapy increased as GEP score indicated greater risk of recurrence. Conclusion: Identifying and eliminating unnecessary variation in the use of these expensive tests and treatments should be part of quality improvement and efficiency programs. PMID:21886507

  15. Modeling genomic regulatory networks with big data.

    Science.gov (United States)

    Bolouri, Hamid

    2014-05-01

    High-throughput sequencing, large-scale data generation projects, and web-based cloud computing are changing how computational biology is performed, who performs it, and what biological insights it can deliver. I review here the latest developments in available data, methods, and software, focusing on the modeling and analysis of the gene regulatory interactions in cells. Three key findings are: (i) although sophisticated computational resources are increasingly available to bench biologists, tailored ongoing education is necessary to avoid the erroneous use of these resources. (ii) Current models of the regulation of gene expression are far too simplistic and need updating. (iii) Integrative computational analysis of large-scale datasets is becoming a fundamental component of molecular biology. I discuss current and near-term opportunities and challenges related to these three points.

  16. Genome-Wide Meta-Analyses of Breast, Ovarian, and Prostate Cancer Association Studies Identify Multiple New Susceptibility Loci Shared by at Least Two Cancer Types

    DEFF Research Database (Denmark)

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

    2016-01-01

    UNLABELLED: Breast, ovarian, and prostate cancers are hormone-related and may have a shared genetic basis, but this has not been investigated systematically by genome-wide association (GWA) studies. Meta-analyses combining the largest GWA meta-analysis data sets for these cancers totaling 112,349...

  17. Common variants associated with breast cancer in genome-wide association studies are modifiers of breast cancer risk in BRCA1 and BRCA2 mutation carriers.

    NARCIS (Netherlands)

    Wang, X.; Pankratz, V.S.; Fredericksen, Z.; Tarrell, R.; Karaus, M.; McGuffog, L.; Pharaoh, P.D.; Ponder, B.A.J.; Dunning, A.M.; Peock, S.; Cook, M.; Oliver, C.; Frost, D.; Sinilnikova, O.M.; Stoppa-Lyonnet, D.; Mazoyer, S.; Houdayer, C.; Hogervorst, F.B.L.; Hooning, M.J.; Ligtenberg, M.J.L.; Spurdle, A.; Chenevix-Trench, G.; Schmutzler, R.K.; Wappenschmidt, B.; Engel, C.; Meindl, A.; Domchek, S.M.; Nathanson, K.L.; Rebbeck, T.R.; Singer, C.F.; Gschwantler-Kaulich, D.; Dressler, C.; Fink, A.; Szabo, C.I.; Zikan, M.; Foretova, L.; Claes, K.; Thomas, G.; Hoover, R.N.; Hunter, D.J.; Chanock, S.J.; Easton, D.F.; Antoniou, A.C.; Couch, F.J.

    2010-01-01

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

  18. Common variants associated with breast cancer in genome-wide association studies are modifiers of breast cancer risk in BRCA1 and BRCA2 mutation carriers

    NARCIS (Netherlands)

    Wang, Xianshu; Pankratz, V. Shane; Fredericksen, Zachary; Tarrell, Robert; Karaus, Mary; McGuffog, Lesley; Pharaoh, Paul D. P.; Ponder, Bruce A. J.; Dunning, Alison M.; Peock, Susan; Cook, Margaret; Oliver, Clare; Frost, Debra; Sinilnikova, Olga M.; Stoppa-Lyonnet, Dominique; Mazoyer, Sylvie; Houdayer, Claude; Hogervorst, Frans B. L.; Hooning, Maartje J.; Ligtenberg, Marjolijn J.; Spurdle, Amanda; Chenevix-Trench, Georgia; Schmutzler, Rita K.; Wappenschmidt, Barbara; Engel, Christoph; Meindl, Alfons; Domchek, Susan M.; Nathanson, Katherine L.; Rebbeck, Timothy R.; Singer, Christian F.; Gschwantler-Kaulich, Daphne; Dressler, Catherina; Fink, Anneliese; Szabo, Csilla I.; Zikan, Michal; Foretova, Lenka; Claes, Kathleen; Thomas, Gilles; Hoover, Robert N.; Hunter, David J.; Chanock, Stephen J.; Easton, Douglas F.; Antoniou, Antonis C.; Couch, Fergus J.

    2010-01-01

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

  19. Genome Editing and Its Applications in Model Organisms

    Directory of Open Access Journals (Sweden)

    Dongyuan Ma

    2015-12-01

    Full Text Available Technological advances are important for innovative biological research. Development of molecular tools for DNA manipulation, such as zinc finger nucleases (ZFNs, transcription activator-like effector nucleases (TALENs, and the clustered regularly-interspaced short palindromic repeat (CRISPR/CRISPR-associated (Cas, has revolutionized genome editing. These approaches can be used to develop potential therapeutic strategies to effectively treat heritable diseases. In the last few years, substantial progress has been made in CRISPR/Cas technology, including technical improvements and wide application in many model systems. This review describes recent advancements in genome editing with a particular focus on CRISPR/Cas, covering the underlying principles, technological optimization, and its application in zebrafish and other model organisms, disease modeling, and gene therapy used for personalized medicine.

  20. CRISPR-Cas9 systems: versatile cancer modelling platforms and promising therapeutic strategies.

    Science.gov (United States)

    Wen, Wan-Shun; Yuan, Zhi-Min; Ma, Shi-Jie; Xu, Jiang; Yuan, Dong-Tang

    2016-03-15

    The RNA-guided nuclease CRISPR-Cas9 (clustered regularly interspaced short palindromic repeats-CRISPR associated nuclease 9) and its variants such as nickase Cas9, dead Cas9, guide RNA scaffolds and RNA-targeting Cas9 are convenient and versatile platforms for site-specific genome editing and epigenome modulation. They are easy-to-use, simple-to-design and capable of targeting multiple loci simultaneously. Given that cancer develops from cumulative genetic and epigenetic alterations, CRISPR-Cas9 and its variants (hereafter referred to as CRISPR-Cas9 systems) hold extensive application potentials in cancer modeling and therapy. To date, they have already been applied to model oncogenic mutations in cell lines (e.g., Choi and Meyerson, Nat Commun 2014;5:3728) and in adult animals (e.g., Xue et al., Nature 2014;514:380-4), as well as to combat cancer by disabling oncogenic viruses (e.g., Hu et al., Biomed Res Int 2014;2014:612823) or by manipulating cancer genome (e.g., Liu et al., Nat Commun 2014;5:5393). Given the importance of epigenome and transcriptome in tumourigenesis, manipulation of cancer epigenome and transcriptome for cancer modeling and therapy is a promising area in the future. Whereas (epi)genetic modifications of cancer microenvironment with CRISPR-Cas9 systems for therapeutic purposes represent another promising area in cancer research. Herein, we introduce the functions and mechanisms of CRISPR-Cas9 systems in genome editing and epigenome modulation, retrospect their applications in cancer modelling and therapy, discuss limitations and possible solutions and propose future directions, in hope of providing concise and enlightening information for readers interested in this area.

  1. Genome scale metabolic modeling of the riboflavin overproducer Ashbya gossypii.

    Science.gov (United States)

    Ledesma-Amaro, Rodrigo; Kerkhoven, Eduard J; Revuelta, José Luis; Nielsen, Jens

    2014-06-01

    Ashbya gossypii is a filamentous fungus that naturally overproduces riboflavin, or vitamin B2. Advances in genetic and metabolic engineering of A. gossypii have permitted the switch from industrial chemical synthesis to the current biotechnological production of this vitamin. Additionally, A. gossypii is a model organism with one of the smallest eukaryote genomes being phylogenetically close to Saccharomyces cerevisiae. It has therefore been used to study evolutionary aspects of bakers' yeast. We here reconstructed the first genome scale metabolic model of A. gossypii, iRL766. The model was validated by biomass growth, riboflavin production and substrate utilization predictions. Gene essentiality analysis of the A. gossypii model in comparison with the S. cerevisiae model demonstrated how the whole-genome duplication event that separates the two species has led to an even spread of paralogs among all metabolic pathways. Additionally, iRL766 was used to integrate transcriptomics data from two different growth stages of A. gossypii, comparing exponential growth to riboflavin production stages. Both reporter metabolite analysis and in silico identification of transcriptionally regulated enzymes demonstrated the important involvement of beta-oxidation and the glyoxylate cycle in riboflavin production. PMID:24374726

  2. Genomic breeding value estimation using nonparametric additive regression models

    Directory of Open Access Journals (Sweden)

    Solberg Trygve

    2009-01-01

    Full Text Available Abstract Genomic selection refers to the use of genomewide dense markers for breeding value estimation and subsequently for selection. The main challenge of genomic breeding value estimation is the estimation of many effects from a limited number of observations. Bayesian methods have been proposed to successfully cope with these challenges. As an alternative class of models, non- and semiparametric models were recently introduced. The present study investigated the ability of nonparametric additive regression models to predict genomic breeding values. The genotypes were modelled for each marker or pair of flanking markers (i.e. the predictors separately. The nonparametric functions for the predictors were estimated simultaneously using additive model theory, applying a binomial kernel. The optimal degree of smoothing was determined by bootstrapping. A mutation-drift-balance simulation was carried out. The breeding values of the last generation (genotyped was predicted using data from the next last generation (genotyped and phenotyped. The results show moderate to high accuracies of the predicted breeding values. A determination of predictor specific degree of smoothing increased the accuracy.

  3. Landscape of somatic mutations in 560 breast cancer whole-genome sequences.

    Science.gov (United States)

    Nik-Zainal, Serena; Davies, Helen; Staaf, Johan; Ramakrishna, Manasa; Glodzik, Dominik; Zou, Xueqing; Martincorena, Inigo; Alexandrov, Ludmil B; Martin, Sancha; Wedge, David C; Van Loo, Peter; Ju, Young Seok; Smid, Marcel; Brinkman, Arie B; Morganella, Sandro; Aure, Miriam R; Lingjærde, Ole Christian; Langerød, Anita; Ringnér, Markus; Ahn, Sung-Min; Boyault, Sandrine; Brock, Jane E; Broeks, Annegien; Butler, Adam; Desmedt, Christine; Dirix, Luc; Dronov, Serge; Fatima, Aquila; Foekens, John A; Gerstung, Moritz; Hooijer, Gerrit K J; Jang, Se Jin; Jones, David R; Kim, Hyung-Yong; King, Tari A; Krishnamurthy, Savitri; Lee, Hee Jin; Lee, Jeong-Yeon; Li, Yilong; McLaren, Stuart; Menzies, Andrew; Mustonen, Ville; O'Meara, Sarah; Pauporté, Iris; Pivot, Xavier; Purdie, Colin A; Raine, Keiran; Ramakrishnan, Kamna; Rodríguez-González, F Germán; Romieu, Gilles; Sieuwerts, Anieta M; Simpson, Peter T; Shepherd, Rebecca; Stebbings, Lucy; Stefansson, Olafur A; Teague, Jon; Tommasi, Stefania; Treilleux, Isabelle; Van den Eynden, Gert G; Vermeulen, Peter; Vincent-Salomon, Anne; Yates, Lucy; Caldas, Carlos; van't Veer, Laura; Tutt, Andrew; Knappskog, Stian; Tan, Benita Kiat Tee; Jonkers, Jos; Borg, Åke; Ueno, Naoto T; Sotiriou, Christos; Viari, Alain; Futreal, P Andrew; Campbell, Peter J; Span, Paul N; Van Laere, Steven; Lakhani, Sunil R; Eyfjord, Jorunn E; Thompson, Alastair M; Birney, Ewan; Stunnenberg, Hendrik G; van de Vijver, Marc J; Martens, John W M; Børresen-Dale, Anne-Lise; Richardson, Andrea L; Kong, Gu; Thomas, Gilles; Stratton, Michael R

    2016-06-01

    We analysed whole-genome sequences of 560 breast cancers to advance understanding of the driver mutations conferring clonal advantage and the mutational processes generating somatic mutations. We found that 93 protein-coding cancer genes carried probable driver mutations. Some non-coding regions exhibited high mutation frequencies, but most have distinctive structural features probably causing elevated mutation rates and do not contain driver mutations. Mutational signature analysis was extended to genome rearrangements and revealed twelve base substitution and six rearrangement signatures. Three rearrangement signatures, characterized by tandem duplications or deletions, appear associated with defective homologous-recombination-based DNA repair: one with deficient BRCA1 function, another with deficient BRCA1 or BRCA2 function, the cause of the third is unknown. This analysis of all classes of somatic mutation across exons, introns and intergenic regions highlights the repertoire of cancer genes and mutational processes operating, and progresses towards a comprehensive account of the somatic genetic basis of breast cancer. PMID:27135926

  4. Extending pathways and processes using molecular interaction networks to analyse cancer genome data

    Directory of Open Access Journals (Sweden)

    Krasnogor Natalio

    2010-12-01

    Full Text Available Abstract Background Cellular processes and pathways, whose deregulation may contribute to the development of cancers, are often represented as cascades of proteins transmitting a signal from the cell surface to the nucleus. However, recent functional genomic experiments have identified thousands of interactions for the signalling canonical proteins, challenging the traditional view of pathways as independent functional entities. Combining information from pathway databases and interaction networks obtained from functional genomic experiments is therefore a promising strategy to obtain more robust pathway and process representations, facilitating the study of cancer-related pathways. Results We present a methodology for extending pre-defined protein sets representing cellular pathways and processes by mapping them onto a protein-protein interaction network, and extending them to include densely interconnected interaction partners. The added proteins display distinctive network topological features and molecular function annotations, and can be proposed as putative new components, and/or as regulators of the communication between the different cellular processes. Finally, these extended pathways and processes are used to analyse their enrichment in pancreatic mutated genes. Significant associations between mutated genes and certain processes are identified, enabling an analysis of the influence of previously non-annotated cancer mutated genes. Conclusions The proposed method for extending cellular pathways helps to explain the functions of cancer mutated genes by exploiting the synergies of canonical knowledge and large-scale interaction data.

  5. 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.

  6. 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.

  7. Pathway analysis of bladder cancer genome-wide association study identifies novel pathways involved in bladder cancer development

    Science.gov (United States)

    Chen, Meng; Rothman, Nathaniel; Ye, Yuanqing; Gu, Jian; Scheet, Paul A.; Huang, Maosheng; Chang, David W.; Dinney, Colin P.; Silverman, Debra T.; Figueroa, Jonine D.; Chanock, Stephen J.; Wu, Xifeng

    2016-01-01

    Genome-wide association studies (GWAS) are designed to identify individual regions associated with cancer risk, but only explain a small fraction of the inherited variability. Alternative approach analyzing genetic variants within biological pathways has been proposed to discover networks of susceptibility genes with additional effects. The gene set enrichment analysis (GSEA) may complement and expand traditional GWAS analysis to identify novel genes and pathways associated with bladder cancer risk. We selected three GSEA methods: Gen-Gen, Aligator, and the SNP Ratio Test to evaluate cellular signaling pathways involved in bladder cancer susceptibility in a Texas GWAS population. The candidate genetic polymorphisms from the significant pathway selected by GSEA were validated in an independent NCI GWAS. We identified 18 novel pathways (P < 0.05) significantly associated with bladder cancer risk. Five of the most promising pathways (P ≤ 0.001 in any of the three GSEA methods) among the 18 pathways included two cell cycle pathways and neural cell adhesion molecule (NCAM), platelet-derived growth factor (PDGF), and unfolded protein response pathways. We validated the candidate polymorphisms in the NCI GWAS and found variants of RAPGEF1, SKP1, HERPUD1, CACNB2, CACNA1C, CACNA1S, COL4A2, SRC, and CACNA1C were associated with bladder cancer risk. Two CCNE1 variants, rs8102137 and rs997669, from cell cycle pathways showed the strongest associations; the CCNE1 signal at 19q12 has already been reported in previous GWAS. These findings offer additional etiologic insights highlighting the specific genes and pathways associated with bladder cancer development. GSEA may be a complementary tool to GWAS to identify additional loci of cancer susceptibility.

  8. Substantial contribution of extrinsic risk factors to cancer development | Office of Cancer Genomics

    Science.gov (United States)

    Recent research has highlighted a strong correlation between tissue-specific cancer risk and the lifetime number of tissue-specific stem-cell divisions. Whether such correlation implies a high unavoidable intrinsic cancer risk has become a key public health debate with the dissemination of the 'bad luck' hypothesis. Here we provide evidence that intrinsic risk factors contribute only modestly (less than ~10-30% of lifetime risk) to cancer development.

  9. Genome-wide association study of colorectal cancer identifies six new susceptibility loci

    Science.gov (United States)

    Schumacher, Fredrick R.; Schmit, Stephanie L.; Jiao, Shuo; Edlund, Christopher K.; Wang, Hansong; Zhang, Ben; Hsu, Li; Huang, Shu-Chen; Fischer, Christopher P.; Harju, John F.; Idos, Gregory E.; Lejbkowicz, Flavio; Manion, Frank J.; McDonnell, Kevin; McNeil, Caroline E.; Melas, Marilena; Rennert, Hedy S.; Shi, Wei; Thomas, Duncan C.; Van Den Berg, David J.; Hutter, Carolyn M.; Aragaki, Aaron K.; Butterbach, Katja; Caan, Bette J.; Carlson, Christopher S.; Chanock, Stephen J.; Curtis, Keith R.; Fuchs, Charles S.; Gala, Manish; Giovannucci, Edward L.; Gogarten, Stephanie M.; Hayes, Richard B.; Henderson, Brian; Hunter, David J.; Jackson, Rebecca D.; Kolonel, Laurence N.; Kooperberg, Charles; Küry, Sébastien; LaCroix, Andrea; Laurie, Cathy C.; Laurie, Cecelia A.; Lemire, Mathieu; Levine, David; Ma, Jing; Makar, Karen W.; Qu, Conghui; Taverna, Darin; Ulrich, Cornelia M.; Wu, Kana; Kono, Suminori; West, Dee W.; Berndt, Sonja I.; Bezieau, Stéphane; Brenner, Hermann; Campbell, Peter T.; Chan, Andrew T.; Chang-Claude, Jenny; Coetzee, Gerhard A.; Conti, David V.; Duggan, David; Figueiredo, Jane C.; Fortini, Barbara K.; Gallinger, Steven J.; Gauderman, W. James; Giles, Graham; Green, Roger; Haile, Robert; Harrison, Tabitha A.; Hoffmeister, Michael; Hopper, John L.; Hudson, Thomas J.; Jacobs, Eric; Iwasaki, Motoki; Jee, Sun Ha; Jenkins, Mark; Jia, Wei-Hua; Joshi, Amit; Li, Li; Lindor, Noralene M.; Matsuo, Keitaro; Moreno, Victor; Mukherjee, Bhramar; Newcomb, Polly A.; Potter, John D.; Raskin, Leon; Rennert, Gad; Rosse, Stephanie; Severi, Gianluca; Schoen, Robert E.; Seminara, Daniela; Shu, Xiao-Ou; Slattery, Martha L.; Tsugane, Shoichiro; White, Emily; Xiang, Yong-Bing; Zanke, Brent W.; Zheng, Wei; Le Marchand, Loic; Casey, Graham; Gruber, Stephen B.; Peters, Ulrike

    2016-01-01

    Genetic susceptibility to colorectal cancer is caused by rare pathogenic mutations and common genetic variants that contribute to familial risk. Here we report the results of a two-stage association study with 18,299 cases of colorectal cancer and 19,656 controls, with follow-up of the most statistically significant genetic loci in 4,725 cases and 9,969 controls from two Asian consortia. We describe six new susceptibility loci reaching a genome-wide threshold of P<5.0E-08. These findings provide additional insight into the underlying biological mechanisms of colorectal cancer and demonstrate the scientific value of large consortia-based genetic epidemiology studies. PMID:26151821

  10. Genome-wide Analysis Identifies Novel Loci Associated with Ovarian Cancer Outcomes

    DEFF Research Database (Denmark)

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

    2015-01-01

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

  11. Identification of seven new prostate cancer susceptibility loci through a genome-wide association study

    Science.gov (United States)

    Eeles, Rosalind A.; Kote-Jarai, Zsofia; Olama, Ali Amin Al; Giles, Graham G.; Guy, Michelle; Severi, Gianluca; Muir, Kenneth; Hopper, John L.; Henderson, Brian E.; Haiman, Christopher A.; Schleutker, Johanna; Hamdy, Freddie C.; Neal, David E.; Donovan, Jenny L.; Stanford, Janet L.; Ostrander, Elaine A.; Ingles, Sue A.; John, Esther M.; Thibodeau, Stephen N.; Schaid, Daniel; Park, Jong Y.; Spurdle, Amanda; Clements, Judith; Dickinson, Joanne L.; Maier, Christiane; Vogel, Walther; Dörk, Thilo; Rebbeck, Timothy R.; Cooney, Kathleen A.; Cannon-Albright, Lisa; Chappuis, Pierre O.; Hutter, Pierre; Zeegers, Maurice; Kaneva, Radka; Zhang, Hong-Wei; Lu, Yong-Jie; Foulkes, William D.; English, Dallas R.; Leongamornlert, Daniel A.; Tymrakiewicz, Malgorzata; Morrison, Jonathan; Ardern-Jones, Audrey T.; Hall, Amanda L.; O’Brien, Lynne T.; Wilkinson, Rosemary A.; Saunders, Edward J.; Page, Elizabeth C.; Sawyer, Emma J.; Edwards, Stephen M.; Dearnaley, David P.; Horwich, Alan; Huddart, Robert A.; Khoo, Vincent S.; Parker, Christopher C.; Van As, Nicholas; Woodhouse, Christopher J.; Thompson, Alan; Christmas, Tim; Ogden, Chris; Cooper, Colin S.; Southey, Melissa C.; Lophatananon, Artitaya; Liu, Jo-Fen; Kolonel, Laurence N.; Le Marchand, Loic; Wahlfors, Tiina; Tammela, Teuvo L.; Auvinen, Anssi; Lewis, Sarah J.; Cox, Angela; FitzGerald, Liesel M.; Koopmeiners, Joseph S.; Karyadi, Danielle M.; Kwon, Erika M.; Stern, Mariana C.; Corral, Roman; Joshi, Amit D.; Shahabi, Ahva; McDonnell, Shannon K.; Sellers, Thomas A; Pow-Sang, Julio; Chambers, Suzanne; Aitken, Joanne; Gardiner, R.A. (Frank); Batra, Jyotsna; Kedda, Mary Anne; Lose, Felicity; Polanowski, Andrea; Patterson, Briony; Serth, Jürgen; Meyer, Andreas; Luedeke, Manuel; Stefflova, Klara; Ray, Anna M.; Lange, Ethan M.; Farnham, Jim; Khan, Humera; Slavov, Chavdar; Mitkova, Atanaska; Cao, Guangwen; Easton, Douglas F.

    2010-01-01

    Prostate cancer (PrCa) is the most frequently diagnosed male cancer in developed countries. To identify common PrCa susceptibility alleles, we have previously conducted a genome-wide association study in which 541, 129 SNPs were genotyped in 1,854 PrCa cases with clinically detected disease and 1,894 controls. We have now evaluated promising associations in a second stage, in which we genotyped 43,671 SNPs in 3,650 PrCa cases and 3,940 controls, and a third stage, involving an additional 16,229 cases and 14,821 controls from 21 studies. In addition to previously identified loci, we identified a further seven new prostate cancer susceptibility loci on chromosomes 2, 4, 8, 11, and 22 (P=1.6×10−8 to P=2.7×10−33). PMID:19767753

  12. Tapping CD4 T cells for cancer immunotherapy: the choice of personalized genomics.

    Science.gov (United States)

    Zanetti, Maurizio

    2015-03-01

    Cellular immune responses that protect against tumors typically have been attributed to CD8 T cells. However, CD4 T cells also play a central role. It was shown recently that, in a patient with metastatic cholangiocarcinoma, CD4 T cells specific for a peptide from a mutated region of ERBB2IP could arrest tumor progression. This and other recent findings highlight new opportunities for CD4 T cells in cancer immunotherapy. In this article, I discuss the role and regulation of CD4 T cells in response to tumor Ags. Emphasis is placed on the types of Ags and mechanisms that elicit tumor-protective responses. I discuss the advantages and drawbacks of cancer immunotherapy through personalized genomics. These considerations should help to guide the design of next-generation therapeutic cancer vaccines.

  13. Genome-wide association study identifies a common variant in RAD51B associated with male breast cancer risk

    DEFF Research Database (Denmark)

    Orr, Nick; Lemnrau, Alina; Cooke, Rosie;

    2012-01-01

    We conducted a genome-wide association study of male breast cancer comprising 823 cases and 2,795 controls of European ancestry, with validation in independent sample sets totaling 438 cases and 474 controls. A SNP in RAD51B at 14q24.1 was significantly associated with male breast cancer risk (P ...

  14. Genome-wide association study of subtype-specific epithelial ovarian cancer risk alleles using pooled DNA

    DEFF Research Database (Denmark)

    Earp, Madalene A; Kelemen, Linda E; Magliocco, Anthony M;

    2014-01-01

    Epithelial ovarian cancer (EOC) is a heterogeneous cancer with both genetic and environmental risk factors. Variants influencing the risk of developing the less-common EOC subtypes have not been fully investigated. We performed a genome-wide association study (GWAS) of EOC according to subtype by...

  15. Genome-scale modeling for metabolic engineering

    Energy Technology Data Exchange (ETDEWEB)

    Simeonidis, E; Price, ND

    2015-01-13

    We focus on the application of constraint-based methodologies and, more specifically, flux balance analysis in the field of metabolic engineering, and enumerate recent developments and successes of the field. We also review computational frameworks that have been developed with the express purpose of automatically selecting optimal gene deletions for achieving improved production of a chemical of interest. The application of flux balance analysis methods in rational metabolic engineering requires a metabolic network reconstruction and a corresponding in silico metabolic model for the microorganism in question. For this reason, we additionally present a brief overview of automated reconstruction techniques. Finally, we emphasize the importance of integrating metabolic networks with regulatory information-an area which we expect will become increasingly important for metabolic engineering-and present recent developments in the field of metabolic and regulatory integration.

  16. Mammary-Stem-Cell-Based Somatic Mouse Models Reveal Breast Cancer Drivers Causing Cell Fate Dysregulation

    Directory of Open Access Journals (Sweden)

    Zheng Zhang

    2016-09-01

    Full Text Available Cancer genomics has provided an unprecedented opportunity for understanding genetic causes of human cancer. However, distinguishing which mutations are functionally relevant to cancer pathogenesis remains a major challenge. We describe here a mammary stem cell (MaSC organoid-based approach for rapid generation of somatic genetically engineered mouse models (GEMMs. By using RNAi and CRISPR-mediated genome engineering in MaSC-GEMMs, we have discovered that inactivation of Ptpn22 or Mll3, two genes mutated in human breast cancer, greatly accelerated PI3K-driven mammary tumorigenesis. Using these tumor models, we have also identified genetic alterations promoting tumor metastasis and causing resistance to PI3K-targeted therapy. Both Ptpn22 and Mll3 inactivation resulted in disruption of mammary gland differentiation and an increase in stem cell activity. Mechanistically, Mll3 deletion enhanced stem cell activity through activation of the HIF pathway. Thus, our study has established a robust in vivo platform for functional cancer genomics and has discovered functional breast cancer mutations.

  17. Genomic Prostate Cancer Classifier Predicts Biochemical Failure and Metastases in Patients After Postoperative Radiation Therapy

    Energy Technology Data Exchange (ETDEWEB)

    Den, Robert B., E-mail: Robert.Den@jeffersonhospital.org [Kimmel Cancer Center, Jefferson Medical College of Thomas Jefferson University, Philadelphia, Pennsylvania (United States); Feng, Felix Y. [University of Michigan, Michigan Union, Michigan (United States); Showalter, Timothy N. [University of Virginia School of Medicine, Charlottesville, Virginia (United States); Mishra, Mark V. [University of Maryland Medical Center, Baltimore, Maryland (United States); Trabulsi, Edouard J.; Lallas, Costas D.; Gomella, Leonard G.; Kelly, W. Kevin; Birbe, Ruth C.; McCue, Peter A. [Kimmel Cancer Center, Jefferson Medical College of Thomas Jefferson University, Philadelphia, Pennsylvania (United States); Ghadessi, Mercedeh; Yousefi, Kasra; Davicioni, Elai [GenomeDx Biosciences Inc., Vancouver, British Columbia (Canada); Knudsen, Karen E.; Dicker, Adam P. [Kimmel Cancer Center, Jefferson Medical College of Thomas Jefferson University, Philadelphia, Pennsylvania (United States)

    2014-08-01

    Purpose: To test the hypothesis that a genomic classifier (GC) would predict biochemical failure (BF) and distant metastasis (DM) in men receiving radiation therapy (RT) after radical prostatectomy (RP). Methods and Materials: Among patients who underwent post-RP RT, 139 were identified for pT3 or positive margin, who did not receive neoadjuvant hormones and had paraffin-embedded specimens. Ribonucleic acid was extracted from the highest Gleason grade focus and applied to a high-density-oligonucleotide microarray. Receiver operating characteristic, calibration, cumulative incidence, and Cox regression analyses were performed to assess GC performance for predicting BF and DM after post-RP RT in comparison with clinical nomograms. Results: The area under the receiver operating characteristic curve of the Stephenson model was 0.70 for both BF and DM, with addition of GC significantly improving area under the receiver operating characteristic curve to 0.78 and 0.80, respectively. Stratified by GC risk groups, 8-year cumulative incidence was 21%, 48%, and 81% for BF (P<.0001) and for DM was 0, 12%, and 17% (P=.032) for low, intermediate, and high GC, respectively. In multivariable analysis, patients with high GC had a hazard ratio of 8.1 and 14.3 for BF and DM. In patients with intermediate or high GC, those irradiated with undetectable prostate-specific antigen (PSA ≤0.2 ng/mL) had median BF survival of >8 years, compared with <4 years for patients with detectable PSA (>0.2 ng/mL) before initiation of RT. At 8 years, the DM cumulative incidence for patients with high GC and RT with undetectable PSA was 3%, compared with 23% with detectable PSA (P=.03). No outcome differences were observed for low GC between the treatment groups. Conclusion: The GC predicted BF and metastasis after post-RP irradiation. Patients with lower GC risk may benefit from delayed RT, as opposed to those with higher GC; however, this needs prospective validation. Genomic-based models

  18. Use of Whole Genome Sequencing for Diagnosis and Discovery in the Cancer Genetics Clinic

    Directory of Open Access Journals (Sweden)

    Samantha B. Foley

    2015-01-01

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

  19. An Integrative Approach for the Large-scale Identification of Human Genome Kinases Regulating Cancer Metastasis

    Science.gov (United States)

    Zhang, Hanshuo; Wu, Pu-Yen; Ma, Ming; Ye, Yanzheng; Hao, Yang; Yang, Junyu; Yin, Shenyi; Sun, Changhong; Phan, John H.; Wang, May D.; Xi, Jianzhong Jeff

    2016-01-01

    Kinases regulate the majority of biological processes and become one of important groups of drug targets. To identify more kinases being potential for cancer therapy, we developed an integrative approach for the large-scale screen of functional genes capable of regulating the main traits of cancer metastasis, including cell migration as well as invasion. We first employed self-assembled cell microarray (SAMcell) to screen functional genes that regulate cancer cell migration using a siRNA library targeting 710 human genome kinase genes. We identified 81 genes capable of significantly regulating cancer cell migration. Following with invasion assays and bio-informatics analysis, we discovered that 16 genes with differentially expression in cancer samples can regulate both cell migration and invasion, among which 10 genes have been well known to play critical roles in the cancer development. The remaining 6 genes were experimentally validated to have the capacities of regulating the metastasis-related traits, including cell proliferation, apoptosis and anoikis activities besides cell motility. Together, these findings provide a new insight into the therapeutic use of human kinases. PMID:23751374

  20. Use of genome-wide association studies for cancer research and drug repositioning.

    Directory of Open Access Journals (Sweden)

    Jizhun Zhang

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

  1. Increased Proportion of Variance Explained and Prediction Accuracy of Survival of Breast Cancer Patients with Use of Whole-Genome Multiomic Profiles.

    Science.gov (United States)

    Vazquez, Ana I; Veturi, Yogasudha; Behring, Michael; Shrestha, Sadeep; Kirst, Matias; Resende, Marcio F R; de Los Campos, Gustavo

    2016-07-01

    Whole-genome multiomic profiles hold valuable information for the analysis and prediction of disease risk and progression. However, integrating high-dimensional multilayer omic data into risk-assessment models is statistically and computationally challenging. We describe a statistical framework, the Bayesian generalized additive model ((BGAM), and present software for integrating multilayer high-dimensional inputs into risk-assessment models. We used BGAM and data from The Cancer Genome Atlas for the analysis and prediction of survival after diagnosis of breast cancer. We developed a sequence of studies to (1) compare predictions based on single omics with those based on clinical covariates commonly used for the assessment of breast cancer patients (COV), (2) evaluate the benefits of combining COV and omics, (3) compare models based on (a) COV and gene expression profiles from oncogenes with (b) COV and whole-genome gene expression (WGGE) profiles, and (4) evaluate the impacts of combining multiple omics and their interactions. We report that (1) WGGE profiles and whole-genome methylation (METH) profiles offer more predictive power than any of the COV commonly used in clinical practice (e.g., subtype and stage), (2) adding WGGE or METH profiles to COV increases prediction accuracy, (3) the predictive power of WGGE profiles is considerably higher than that based on expression from large-effect oncogenes, and (4) the gain in prediction accuracy when combining multiple omics is consistent. Our results show the feasibility of omic integration and highlight the importance of WGGE and METH profiles in breast cancer, achieving gains of up to 7 points area under the curve (AUC) over the COV in some cases. PMID:27129736

  2. Endocrine-Therapy-Resistant ESR1 Variants Revealed by Genomic Characterization of Breast-Cancer-Derived Xenografts

    Directory of Open Access Journals (Sweden)

    Shunqiang Li

    2013-09-01

    Full Text Available To characterize patient-derived xenografts (PDXs for functional studies, we made whole-genome comparisons with originating breast cancers representative of the major intrinsic subtypes. Structural and copy number aberrations were found to be retained with high fidelity. However, at the single-nucleotide level, variable numbers of PDX-specific somatic events were documented, although they were only rarely functionally significant. Variant allele frequencies were often preserved in the PDXs, demonstrating that clonal representation can be transplantable. Estrogen-receptor-positive PDXs were associated with ESR1 ligand-binding-domain mutations, gene amplification, or an ESR1/YAP1 translocation. These events produced different endocrine-therapy-response phenotypes in human, cell line, and PDX endocrine-response studies. Hence, deeply sequenced PDX models are an important resource for the search for genome-forward treatment options and capture endocrine-drug-resistance etiologies that are not observed in standard cell lines. The originating tumor genome provides a benchmark for assessing genetic drift and clonal representation after transplantation.

  3. Alternate estrogen receptors promote invasion of inflammatory breast cancer cells via non-genomic signaling.

    Directory of Open Access Journals (Sweden)

    Kazufumi Ohshiro

    Full Text Available Although Inflammatory Breast Cancer (IBC is a rare and an aggressive type of locally advanced breast cancer with a generally worst prognosis, little work has been done in identifying the status of non-genomic signaling in the invasiveness of IBC. The present study was performed to explore the status of non-genomic signaling as affected by various estrogenic and anti-estrogenic agents in IBC cell lines SUM149 and SUM190. We have identified the presence of estrogen receptor α (ERα variant, ERα36 in SUM149 and SUM190 cells. This variant as well as ERβ was present in a substantial concentration in IBC cells. The treatment with estradiol (E2, anti-estrogenic agents 4-hydroxytamoxifen and ICI 182780, ERβ specific ligand DPN and GPR30 agonist G1 led to a rapid activation of p-ERK1/2, suggesting the involvement of ERα36, ERβ and GPR30 in the non-genomic signaling pathway in these cells. We also found a substantial increase in the cell migration and invasiveness of SUM149 cells upon the treatment with these ligands. Both basal and ligand-induced migration and invasiveness of SUM149 cells were drastically reduced in the presence of MEK inhibitor U0126, implicating that the phosphorylation of ERK1/2 by MEK is involved in the observed motility and invasiveness of IBC cells. We also provide evidence for the upregulation of p-ERK1/2 through immunostaining in IBC patient samples. These findings suggest a role of non-genomic signaling through the activation of p-ERK1/2 in the hormonal dependence of IBC by a combination of estrogen receptors. These findings only explain the failure of traditional anti-estrogen therapies in ER-positive IBC which induces the non-genomic signaling, but also opens newer avenues for design of modified therapies targeting these estrogen receptors.

  4. Genome-scale constraint-based modeling of Geobacter metallireducens

    Directory of Open Access Journals (Sweden)

    Famili Iman

    2009-01-01

    Full Text Available Abstract Background Geobacter metallireducens was the first organism that can be grown in pure culture to completely oxidize organic compounds with Fe(III oxide serving as electron acceptor. Geobacter species, including G. sulfurreducens and G. metallireducens, are used for bioremediation and electricity generation from waste organic matter and renewable biomass. The constraint-based modeling approach enables the development of genome-scale in silico models that can predict the behavior of complex biological systems and their responses to the environments. Such a modeling approach was applied to provide physiological and ecological insights on the metabolism of G. metallireducens. Results The genome-scale metabolic model of G. metallireducens was constructed to include 747 genes and 697 reactions. Compared to the G. sulfurreducens model, the G. metallireducens metabolic model contains 118 unique reactions that reflect many of G. metallireducens' specific metabolic capabilities. Detailed examination of the G. metallireducens model suggests that its central metabolism contains several energy-inefficient reactions that are not present in the G. sulfurreducens model. Experimental biomass yield of G. metallireducens growing on pyruvate was lower than the predicted optimal biomass yield. Microarray data of G. metallireducens growing with benzoate and acetate indicated that genes encoding these energy-inefficient reactions were up-regulated by benzoate. These results suggested that the energy-inefficient reactions were likely turned off during G. metallireducens growth with acetate for optimal biomass yield, but were up-regulated during growth with complex electron donors such as benzoate for rapid energy generation. Furthermore, several computational modeling approaches were applied to accelerate G. metallireducens research. For example, growth of G. metallireducens with different electron donors and electron acceptors were studied using the genome

  5. Whole genome sequence analysis suggests intratumoral heterogeneity in dissemination of breast cancer to lymph nodes.

    Directory of Open Access Journals (Sweden)

    Kevin Blighe

    Full Text Available BACKGROUND: Intratumoral heterogeneity may help drive resistance to targeted therapies in cancer. In breast cancer, the presence of nodal metastases is a key indicator of poorer overall survival. The aim of this study was to identify somatic genetic alterations in early dissemination of breast cancer by whole genome next generation sequencing (NGS of a primary breast tumor, a matched locally-involved axillary lymph node and healthy normal DNA from blood. METHODS: Whole genome NGS was performed on 12 µg (range 11.1-13.3 µg of DNA isolated from fresh-frozen primary breast tumor, axillary lymph node and peripheral blood following the DNA nanoball sequencing protocol. Single nucleotide variants, insertions, deletions, and substitutions were identified through a bioinformatic pipeline and compared to CIN25, a key set of genes associated with tumor metastasis. RESULTS: Whole genome sequencing revealed overlapping variants between the tumor and node, but also variants that were unique to each. Novel mutations unique to the node included those found in two CIN25 targets, TGIF2 and CCNB2, which are related to transcription cyclin activity and chromosomal stability, respectively, and a unique frameshift in PDS5B, which is required for accurate sister chromatid segregation during cell division. We also identified dominant clonal variants that progressed from tumor to node, including SNVs in TP53 and ARAP3, which mediates rearrangements to the cytoskeleton and cell shape, and an insertion in TOP2A, the expression of which is significantly associated with tumor proliferation and can segregate breast cancers by outcome. CONCLUSION: This case study provides preliminary evidence that primary tumor and early nodal metastasis have largely overlapping somatic genetic alterations. There were very few mutations unique to the involved node. However, significant conclusions regarding early dissemination needs analysis of a larger number of patient samples.

  6. 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.

  7. Understanding Cancer Prognosis

    Medline Plus

    Full Text Available ... Types Recurrent Cancer Common Cancer Types Bladder Cancer Breast Cancer Colorectal Cancer Kidney (Renal Cell) Cancer Leukemia Lung ... Biology Cancer Genomics Causes of Cancer Diagnosis Prevention Screening & Early Detection Treatment Cancer & Public Health Cancer Health ...

  8. Public Health Action Model for Cancer Survivorship.

    Science.gov (United States)

    Moore, Angela R; Buchanan, Natasha D; Fairley, Temeika L; Lee Smith, Judith

    2015-12-01

    Long-term objectives associated with cancer survivors have been suggested by Healthy People 2020, including increasing the proportion of survivors living beyond 5 years after diagnosis and improving survivors' mental and physical health-related quality of life. Prior to reaching these objectives, several intermediate steps must be taken to improve the physical, social, emotional, and financial well-being of cancer survivors. Public health has a role in developing strategic, actionable, and measurable approaches to facilitate change at multiple levels to improve the lives of survivors and their families. The social ecological model has been used by the public health community as the foundation of multilevel intervention design and implementation, encouraging researchers and practitioners to explore methods that promote internal and external changes at the individual, interpersonal, organizational, community, and policy levels. The survivorship community, including public health professionals, providers, policymakers, survivors, advocates, and caregivers, must work collaboratively to identify, develop, and implement interventions that benefit cancer survivors. The National Action Plan for Cancer Survivorship highlights public health domains and associated strategies that can be the impetus for collaboration between and among the levels in the social ecological model and are integral to improving survivor outcomes. This paper describes the Public Health Action Model for Cancer Survivorship, an integrative framework that combines the National Action Plan for Cancer Survivorship with the social ecological model to demonstrate how interaction among the various levels may promote better outcomes for survivors. PMID:26590641

  9. Using Boolean Logic Modeling of Gene Regulatory Networks to Exploit the Links Between Cancer and Metabolism for Therapeutic Purposes.

    Science.gov (United States)

    Arshad, Osama A; Venkatasubramani, Priyadharshini S; Datta, Aniruddha; Venkatraj, Jijayanagaram

    2016-01-01

    The uncontrolled cell proliferation that is characteristically associated with cancer is usually accompanied by alterations in the genome and cell metabolism. Indeed, the phenomenon of cancer cells metabolizing glucose using a less efficient anaerobic process even in the presence of normal oxygen levels, termed the Warburg effect, is currently considered to be one of the hallmarks of cancer. Diabetes, much like cancer, is defined by significant metabolic changes. Recent epidemiological studies have shown that diabetes patients treated with the antidiabetic drug Metformin have significantly lowered risk of cancer as compared to patients treated with other antidiabetic drugs. We utilize a Boolean logic model of the pathways commonly mutated in cancer to not only investigate the efficacy of Metformin for cancer therapeutic purposes but also demonstrate how Metformin in concert with other cancer drugs could provide better and less toxic clinical outcomes as compared to using cancer drugs alone.

  10. A bayesian integrative model for genetical genomics with spatially informed variable selection.

    Science.gov (United States)

    Cassese, Alberto; Guindani, Michele; Vannucci, Marina

    2014-01-01

    We consider a Bayesian hierarchical model for the integration of gene expression levels with comparative genomic hybridization (CGH) array measurements collected on the same subjects. The approach defines a measurement error model that relates the gene expression levels to latent copy number states. In turn, the latent states are related to the observed surrogate CGH measurements via a hidden Markov model. The model further incorporates variable selection with a spatial prior based on a probit link that exploits dependencies across adjacent DNA segments. Posterior inference is carried out via Markov chain Monte Carlo stochastic search techniques. We study the performance of the model in simulations and show better results than those achieved with recently proposed alternative priors. We also show an application to data from a genomic study on lung squamous cell carcinoma, where we identify potential candidates of associations between copy number variants and the transcriptional activity of target genes. Gene ontology (GO) analyses of our findings reveal enrichments in genes that code for proteins involved in cancer. Our model also identifies a number of potential candidate biomarkers for further experimental validation. PMID:25288877

  11. Ovarian Cancer Pathogenesis: A Model in Evolution

    Directory of Open Access Journals (Sweden)

    Alison M. Karst

    2010-01-01

    Full Text Available Ovarian cancer is a deadly disease for which there is no effective means of early detection. Ovarian carcinomas comprise a diverse group of neoplasms, exhibiting a wide range of morphological characteristics, clinical manifestations, genetic alterations, and tumor behaviors. This high degree of heterogeneity presents a major clinical challenge in both diagnosing and treating ovarian cancer. Furthermore, the early events leading to ovarian carcinoma development are poorly understood, thus complicating efforts to develop screening modalities for this disease. Here, we provide an overview of the current models of ovarian cancer pathogenesis, highlighting recent findings implicating the fallopian tube fimbria as a possible site of origin of ovarian carcinomas. The ovarian cancer model will continue to evolve as we learn more about the genetics and etiology of this disease.

  12. Recurrent genomic gains in preinvasive lesions as a biomarker of risk for lung cancer.

    Directory of Open Access Journals (Sweden)

    Pierre P Massion

    Full Text Available Lung carcinoma development is accompanied by field changes that may have diagnostic significance. We have previously shown the importance of chromosomal aneusomy in lung cancer progression. Here, we tested whether genomic gains in six specific loci, TP63 on 3q28, EGFR on 7p12, MYC on 8q24, 5p15.2, and centromeric regions for chromosomes 3 (CEP3 and 6 (CEP6, may provide further value in the prediction of lung cancer. Bronchial biopsy specimens were obtained by LIFE bronchoscopy from 70 subjects (27 with prevalent lung cancers and 43 individuals without lung cancer. Twenty six biopsies were read as moderate dysplasia, 21 as severe dysplasia and 23 as carcinoma in situ (CIS. Four-micron paraffin sections were submitted to a 4-target FISH assay (LAVysion, Abbott Molecular and reprobed for TP63 and CEP 3 sequences. Spot counts were obtained in 30-50 nuclei per specimen for each probe. Increased gene copy number in 4 of the 6 probes was associated with increased risk of being diagnosed with lung cancer both in unadjusted analyses (odds ratio = 11, p<0.05 and adjusted for histology grade (odds ratio = 17, p<0.05. The most informative 4 probes were TP63, MYC, CEP3 and CEP6. The combination of these 4 probes offered a sensitivity of 82% for lung cancer and a specificity of 58%. These results indicate that specific cytogenetic alterations present in preinvasive lung lesions are closely associated with the diagnosis of lung cancer and may therefore have value in assessing lung cancer risk.

  13. Tracking genomic cancer evolution for precision medicine: the lung TRACERx study.

    Directory of Open Access Journals (Sweden)

    Mariam Jamal-Hanjani

    2014-07-01

    Full Text Available The importance of intratumour genetic and functional heterogeneity is increasingly recognised as a driver of cancer progression and survival outcome. Understanding how tumour clonal heterogeneity impacts upon therapeutic outcome, however, is still an area of unmet clinical and scientific need. TRACERx (TRAcking non-small cell lung Cancer Evolution through therapy [Rx], a prospective study of patients with primary non-small cell lung cancer (NSCLC, aims to define the evolutionary trajectories of lung cancer in both space and time through multiregion and longitudinal tumour sampling and genetic analysis. By following cancers from diagnosis to relapse, tracking the evolutionary trajectories of tumours in relation to therapeutic interventions, and determining the impact of clonal heterogeneity on clinical outcomes, TRACERx may help to identify novel therapeutic targets for NSCLC and may also serve as a model applicable to other cancer types.

  14. Combining Chromosomal Arm Status and Significantly Aberrant Genomic Locations Reveals New Cancer Subtypes

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    Tal Shay

    2009-01-01

    Full Text Available Many types of tumors exhibit characteristic chromosomal losses or gains, as well as local amplifications and deletions. Within any given tumor type, sample specific amplifications and deletions are also observed. Typically, a region that is aberrant in more tumors, or whose copy number change is stronger, would be considered as a more promising candidate to be biologically relevant to cancer. We sought for an intuitive method to define such aberrations and prioritize them. We define V, the “volume” associated with an aberration, as the product of three factors: (a fraction of patients with the aberration, (b the aberration’s length and (c its amplitude. Our algorithm compares the values of V derived from the real data to a null distribution obtained by permutations, and yields the statistical significance (p-value of the measured value of V. We detected genetic locations that were significantly aberrant, and combine them with chromosomal arm status (gain/loss to create a succinct fingerprint of the tumor genome. This genomic fingerprint is used to visualize the tumors, highlighting events that are co-occurring or mutually exclusive. We apply the method on three different public array CGH datasets of Medulloblastoma and Neuroblastoma, and demonstrate its ability to detect chromosomal regions that were known to be altered in the tested cancer types, as well as to suggest new genomic locations to be tested. We identified a potential new subtype of Medulloblastoma, which is analogous to Neuroblastoma type 1.

  15. [HPV-associated head and neck cancer : mutational signature and genomic aberrations].

    Science.gov (United States)

    Wagner, S; Würdemann, N; Hübbers, C; Reuschenbach, M; Prigge, E-S; Wichmann, G; Hess, J; Dietz, A; Dürst, M; Tinhofer, I; von Knebel-Döberitz, M; Wittekindt, C; Klussmann, J P

    2015-11-01

    A significantly increasing proportion of oropharyngeal head and neck carcinomas (OSCC) in North America and Europe are associated with human papillomavirus (HPV) infections. HPV-related OSCC is regarded as a distinct tumor type with regard to its cellular, biologic, and clinical characteristics. Patients with HPV-related OSCC have significantly better local control, but higher rates of regional lymph node and distant metastases as compared to patients with HPV-negative OSCC. Classical molecular genetic investigations demonstrated specific chromosomal aberration signatures in HPV-related OSCC, and recent developments in next generation sequencing (NGS) technology have rendered possible the sequencing of entire genomes, and thus detection of specific mutations, in just a few days. Initial data from The Cancer Genome Atlas (TCGA) project obtained by using genome-wide high throughput methods have confirmed that HPV-related OSCC contain fewer, albeit more specific mutations than HPV-negative tumors. Additionally, these data revealed the presence of specific-potentially therapeutically targetable-activating driver mutations in subgroups of HPV-positive OSCC, some of which have a prognostic impact. Specific targeted NGS technologies provide new possibilities for identification of diagnostic, prognostic, and predictive biomarkers and the development of personalized cancer treatment. Patients with HPV-positive tumors are likely to profit from these developments in the future, since the genetic alterations are relatively homogenous and frequently lead to signal pathway activation. There is an urgent need for network research activities to carry out the necessary basic research in prospective cohort studies.

  16. 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)

    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

  17. Emerging and Evolving Ovarian Cancer Animal Models

    OpenAIRE

    Bobbs, Alexander S; Jennifer M. Cole; Cowden Dahl, Karen D.

    2015-01-01

    Ovarian cancer (OC) is the leading cause of death from a gynecological malignancy in the United States. By the time a woman is diagnosed with OC, the tumor has usually metastasized. Mouse models that are used to recapitulate different aspects of human OC have been evolving for nearly 40 years. Xenograft studies in immunocompromised and immunocompetent mice have enhanced our knowledge of metastasis and immune cell involvement in cancer. Patient-derived xenografts (PDXs) can accurately reflect ...

  18. Building prognostic models for breast cancer patients using clinical variables and hundreds of gene expression signatures

    Directory of Open Access Journals (Sweden)

    Liu Yufeng

    2011-01-01

    Full Text Available Abstract Background Multiple breast cancer gene expression profiles have been developed that appear to provide similar abilities to predict outcome and may outperform clinical-pathologic criteria; however, the extent to which seemingly disparate profiles provide additive prognostic information is not known, nor do we know whether prognostic profiles perform equally across clinically defined breast cancer subtypes. We evaluated whether combining the prognostic powers of standard breast cancer clinical variables with a large set of gene expression signatures could improve on our ability to predict patient outcomes. Methods Using clinical-pathological variables and a collection of 323 gene expression "modules", including 115 previously published signatures, we build multivariate Cox proportional hazards models using a dataset of 550 node-negative systemically untreated breast cancer patients. Models predictive of pathological complete response (pCR to neoadjuvant chemotherapy were also built using this approach. Results We identified statistically significant prognostic models for relapse-free survival (RFS at 7 years for the entire population, and for the subgroups of patients with ER-positive, or Luminal tumors. Furthermore, we found that combined models that included both clinical and genomic parameters improved prognostication compared with models with either clinical or genomic variables alone. Finally, we were able to build statistically significant combined models for pathological complete response (pCR predictions for the entire population. Conclusions Integration of gene expression signatures and clinical-pathological factors is an improved method over either variable type alone. Highly prognostic models could be created when using all patients, and for the subset of patients with lymph node-negative and ER-positive breast cancers. Other variables beyond gene expression and clinical-pathological variables, like gene mutation status or DNA

  19. ALK evaluation in the world of multiplex testing: Network Genomic Medicine (NGM): the Cologne model for implementing personalised oncology.

    Science.gov (United States)

    Heydt, C; Kostenko, A; Merkelbach-Bruse, S; Wolf, J; Büttner, R

    2016-09-01

    Comprehensive molecular genotyping of lung cancers has become a key requirement for guiding therapeutic decisions. As a paradigm model of implementing next-generation comprehensive diagnostics, Network Genomic Medicine (NGM) has established central diagnostic and clinical trial platforms for centralised testing and decentralised personalised treatment in clinical practice. Here, we describe the structures of the NGM network and give a summary of technologies to identify patients with anaplastic lymphoma kinase (ALK) fusion-positive lung adenocarcinomas. As unifying test platforms will become increasingly important for delivering reliable, quick and affordable tests, the NGM diagnostic platform is currently implementing a comprehensive hybrid capture-based parallel sequencing pan-cancer assay.

  20. Genome-wide analysis of alternative transcripts in human breast cancer

    Science.gov (United States)

    Wen, Ji; Toomer, Kevin H.

    2016-01-01

    Transcript variants play a critical role in diversifying gene expression. Alternative splicing is a major mechanism for generating transcript variants. A number of genes have been implicated in breast cancer pathogenesis with their aberrant expression of alternative transcripts. In this study, we performed genome-wide analyses of transcript variant expression in breast cancer. With RNA-Seq data from 105 patients, we characterized the transcriptome of breast tumors, by pairwise comparison of gene expression in the breast tumor versus matched healthy tissue from each patient. We identified 2839 genes, ~10 % of protein-coding genes in the human genome, that had differential expression of transcript variants between tumors and healthy tissues. The validity of the computational analysis was confirmed by quantitative RT-PCR assessment of transcript variant expression from four top candidate genes. The alternative transcript profiling led to classification of breast cancer into two subgroups and yielded a novel molecular signature that could be prognostic of patients’ tumor burden and survival. We uncovered nine splicing factors (FOX2, MBNL1, QKI, PTBP1, ELAVL1, HNRNPC, KHDRBS1, SFRS2, and TIAR) that were involved in aberrant splicing in breast cancer. Network analyses for the coordinative patterns of transcript variant expression identified twelve “hub” genes that differentiated the cancerous and normal transcriptomes. Dysregulated expression of alternative transcripts may reveal novel biomarkers for tumor development. It may also suggest new therapeutic targets, such as the “hub” genes identified through the network analyses of transcript variant expression, or splicing factors implicated in the formation of the tumor transcriptome. PMID:25913416

  1. Structural variation discovery in the cancer genome using next generation sequencing: Computational solutions and perspectives

    Science.gov (United States)

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

    2015-01-01

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

  2. Cancer Biomarkers from Genome-Scale DNA Methylation: Comparison of Evolutionary and Semantic Analysis Methods

    Directory of Open Access Journals (Sweden)

    Ioannis Valavanis

    2015-11-01

    Full Text Available DNA methylation profiling exploits microarray technologies, thus yielding a wealth of high-volume data. Here, an intelligent framework is applied, encompassing epidemiological genome-scale DNA methylation data produced from the Illumina’s Infinium Human Methylation 450K Bead Chip platform, in an effort to correlate interesting methylation patterns with cancer predisposition and, in particular, breast cancer and B-cell lymphoma. Feature selection and classification are employed in order to select, from an initial set of ~480,000 methylation measurements at CpG sites, predictive cancer epigenetic biomarkers and assess their classification power for discriminating healthy versus cancer related classes. Feature selection exploits evolutionary algorithms or a graph-theoretic methodology which makes use of the semantics information included in the Gene Ontology (GO tree. The selected features, corresponding to methylation of CpG sites, attained moderate-to-high classification accuracies when imported to a series of classifiers evaluated by resampling or blindfold validation. The semantics-driven selection revealed sets of CpG sites performing similarly with evolutionary selection in the classification tasks. However, gene enrichment and pathway analysis showed that it additionally provides more descriptive sets of GO terms and KEGG pathways regarding the cancer phenotypes studied here. Results support the expediency of this methodology regarding its application in epidemiological studies.

  3. Genome-wide association study of pancreatic cancer in Japanese population.

    Directory of Open Access Journals (Sweden)

    Siew-Kee Low

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

  4. The utility of Apc-mutant rats in modeling human colon cancer

    OpenAIRE

    Irving, Amy A.; Kazuto Yoshimi; Hart, Marcia L.; Taybor Parker; Linda Clipson; Ford, Madeline R; Takashi Kuramoto; Dove, William F; Amos-Landgraf, James M.

    2014-01-01

    Prior to the advent of genetic engineering in the mouse, the rat was the model of choice for investigating the etiology of cancer. Now, recent advances in the manipulation of the rat genome, combined with a growing recognition of the physiological differences between mice and rats, have reignited interest in the rat as a model of human cancer. Two recently developed rat models, the polyposis in the rat colon (Pirc) and Kyoto Apc Delta (KAD) strains, each carry mutations in the intestinal-canc...

  5. Cancer-predisposition gene KLLN maintains pericentric H3K9 trimethylation protecting genomic stability

    Science.gov (United States)

    Nizialek, Emily A.; Sankunny, Madhav; Niazi, Farshad; Eng, Charis

    2016-01-01

    Maintenance of proper chromatin states and genomic stability is vital for normal development and health across a range of organisms. Here, we report on the role of KLLN in maintenance of pericentric H3K9 trimethylation (H3K9me3) and genomic stability. Germline hypermethylation of KLLN, a gene uncovered well after the human genome project, has been linked to Cowden cancer-predisposition syndrome (CS) in PTEN wild-type cases. KLLN first identified as a p53-dependent tumor suppressor gene, was believed to bind randomly to DNA and cause S-phase arrest. Using chromatin immunoprecipitation-based sequencing (ChIP-seq), we demonstrated that KLLN binds to DNA regions enriched with H3K9me3. KLLN overexpression correlated with increased H3K9 methyltransferase activity and increased global H3K9me3, while knockdown of KLLN had an opposite effect. We also found KLLN to localize to pericentric regions, with loss of KLLN resulting in dysregulation of pericentric heterochromatin, with consequent chromosomal instability manifested by increased micronuclei formation and numerical chromosomal aberrations. Interestingly, we show that KLLN interacts with DBC1, with consequent abrogation of DBC1 inhibition of SUV39H1, a H3K9 methyltransferase, suggesting the mode of KLLN regulating H3K9me3. These results suggest a critical role for KLLN as a potential regulator of pericentric heterochromatin formation, genomic stability and gene expression. PMID:26673699

  6. Branching process models of cancer

    CERN Document Server

    Durrett, Richard

    2015-01-01

    This volume develops results on continuous time branching processes and applies them to study rate of tumor growth, extending classic work on the Luria-Delbruck distribution. As a consequence, the authors calculate the probability that mutations that confer resistance to treatment are present at detection and quantify the extent of tumor heterogeneity. As applications, the authors evaluate ovarian cancer screening strategies and give rigorous proofs for results of Heano and Michor concerning tumor metastasis. These notes should be accessible to students who are familiar with Poisson processes and continuous time. Richard Durrett is mathematics professor at Duke University, USA. He is the author of 8 books, over 200 journal articles, and has supervised more than 40 Ph.D. students. Most of his current research concerns the applications of probability to biology: ecology, genetics, and most recently cancer.

  7. Mathematical models of breast and ovarian cancers.

    Science.gov (United States)

    Botesteanu, Dana-Adriana; Lipkowitz, Stanley; Lee, Jung-Min; Levy, Doron

    2016-07-01

    Women constitute the majority of the aging United States (US) population, and this has substantial implications on cancer population patterns and management practices. Breast cancer is the most common women's malignancy, while ovarian cancer is the most fatal gynecological malignancy in the US. In this review, we focus on these subsets of women's cancers, seen more commonly in postmenopausal and elderly women. In order to systematically investigate the complexity of cancer progression and response to treatment in breast and ovarian malignancies, we assert that integrated mathematical modeling frameworks viewed from a systems biology perspective are needed. Such integrated frameworks could offer innovative contributions to the clinical women's cancers community, as answers to clinical questions cannot always be reached with contemporary clinical and experimental tools. Here, we recapitulate clinically known data regarding the progression and treatment of the breast and ovarian cancers. We compare and contrast the two malignancies whenever possible in order to emphasize areas where substantial contributions could be made by clinically inspired and validated mathematical modeling. We show how current paradigms in the mathematical oncology community focusing on the two malignancies do not make comprehensive use of, nor substantially reflect existing clinical data, and we highlight the modeling areas in most critical need of clinical data integration. We emphasize that the primary goal of any mathematical study of women's cancers should be to address clinically relevant questions. WIREs Syst Biol Med 2016, 8:337-362. doi: 10.1002/wsbm.1343 For further resources related to this article, please visit the WIREs website. PMID:27259061

  8. Translocation and deletion breakpoints in cancer genomes are associated with potential non-B DNA-forming sequences

    Science.gov (United States)

    Bacolla, Albino; Tainer, John A.; Vasquez, Karen M.; Cooper, David N.

    2016-01-01

    Gross chromosomal rearrangements (including translocations, deletions, insertions and duplications) are a hallmark of cancer genomes and often create oncogenic fusion genes. An obligate step in the generation of such gross rearrangements is the formation of DNA double-strand breaks (DSBs). Since the genomic distribution of rearrangement breakpoints is non-random, intrinsic cellular factors may predispose certain genomic regions to breakage. Notably, certain DNA sequences with the potential to fold into secondary structures [potential non-B DNA structures (PONDS); e.g. triplexes, quadruplexes, hairpin/cruciforms, Z-DNA and single-stranded looped-out structures with implications in DNA replication and transcription] can stimulate the formation of DNA DSBs. Here, we tested the postulate that these DNA sequences might be found at, or in close proximity to, rearrangement breakpoints. By analyzing the distribution of PONDS-forming sequences within ±500 bases of 19 947 translocation and 46 365 sequence-characterized deletion breakpoints in cancer genomes, we find significant association between PONDS-forming repeats and cancer breakpoints. Specifically, (AT)n, (GAA)n and (GAAA)n constitute the most frequent repeats at translocation breakpoints, whereas A-tracts occur preferentially at deletion breakpoints. Translocation breakpoints near PONDS-forming repeats also recur in different individuals and patient tumor samples. Hence, PONDS-forming sequences represent an intrinsic risk factor for genomic rearrangements in cancer genomes. PMID:27084947

  9. Colorectal Cancer and the Human Gut Microbiome: Reproducibility with Whole-Genome Shotgun Sequencing.

    Directory of Open Access Journals (Sweden)

    Emily Vogtmann

    Full Text Available Accumulating evidence indicates that the gut microbiota affects colorectal cancer development, but previous studies have varied in population, technical methods, and associations with cancer. Understanding these variations is needed for comparisons and for potential pooling across studies. Therefore, we performed whole-genome shotgun sequencing on fecal samples from 52 pre-treatment colorectal cancer cases and 52 matched controls from Washington, DC. We compared findings from a previously published 16S rRNA study to the metagenomics-derived taxonomy within the same population. In addition, metagenome-predicted genes, modules, and pathways in the Washington, DC cases and controls were compared to cases and controls recruited in France whose specimens were processed using the same platform. Associations between the presence of fecal Fusobacteria, Fusobacterium, and Porphyromonas with colorectal cancer detected by 16S rRNA were reproduced by metagenomics, whereas higher relative abundance of Clostridia in cancer cases based on 16S rRNA was merely borderline based on metagenomics. This demonstrated that within the same sample set, most, but not all taxonomic associations were seen with both methods. Considering significant cancer associations with the relative abundance of genes, modules, and pathways in a recently published French metagenomics dataset, statistically significant associations in the Washington, DC population were detected for four out of 10 genes, three out of nine modules, and seven out of 17 pathways. In total, colorectal cancer status in the Washington, DC study was associated with 39% of the metagenome-predicted genes, modules, and pathways identified in the French study. More within and between population comparisons are needed to identify sources of variation and disease associations that can be reproduced despite these variations. Future studies should have larger sample sizes or pool data across studies to have sufficient

  10. Colorectal Cancer and the Human Gut Microbiome: Reproducibility with Whole-Genome Shotgun Sequencing.

    Science.gov (United States)

    Vogtmann, Emily; Hua, Xing; Zeller, Georg; Sunagawa, Shinichi; Voigt, Anita Y; Hercog, Rajna; Goedert, James J; Shi, Jianxin; Bork, Peer; Sinha, Rashmi

    2016-01-01

    Accumulating evidence indicates that the gut microbiota affects colorectal cancer development, but previous studies have varied in population, technical methods, and associations with cancer. Understanding these variations is needed for comparisons and for potential pooling across studies. Therefore, we performed whole-genome shotgun sequencing on fecal samples from 52 pre-treatment colorectal cancer cases and 52 matched controls from Washington, DC. We compared findings from a previously published 16S rRNA study to the metagenomics-derived taxonomy within the same population. In addition, metagenome-predicted genes, modules, and pathways in the Washington, DC cases and controls were compared to cases and controls recruited in France whose specimens were processed using the same platform. Associations between the presence of fecal Fusobacteria, Fusobacterium, and Porphyromonas with colorectal cancer detected by 16S rRNA were reproduced by metagenomics, whereas higher relative abundance of Clostridia in cancer cases based on 16S rRNA was merely borderline based on metagenomics. This demonstrated that within the same sample set, most, but not all taxonomic associations were seen with both methods. Considering significant cancer associations with the relative abundance of genes, modules, and pathways in a recently published French metagenomics dataset, statistically significant associations in the Washington, DC population were detected for four out of 10 genes, three out of nine modules, and seven out of 17 pathways. In total, colorectal cancer status in the Washington, DC study was associated with 39% of the metagenome-predicted genes, modules, and pathways identified in the French study. More within and between population comparisons are needed to identify sources of variation and disease associations that can be reproduced despite these variations. Future studies should have larger sample sizes or pool data across studies to have sufficient power to detect

  11. Genomic agonism and phenotypic antagonism between estrogen and progesterone receptors in breast cancer.

    Science.gov (United States)

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

    2016-06-01

    The functional role of progesterone receptor (PR) and its impact on estrogen signaling in breast cancer remain controversial. In primary ER(+) (estrogen receptor-positive)/PR(+) human tumors, we report that PR reprograms estrogen signaling as a genomic agonist and a phenotypic antagonist. In isolation, estrogen and progestin act as genomic agonists by regulating the expression of common target genes in similar directions, but at different levels. Similarly, in isolation, progestin is also a weak phenotypic agonist of estrogen action. However, in the presence of both hormones, progestin behaves as a phenotypic estrogen antagonist. PR remodels nucleosomes to noncompetitively redirect ER genomic binding to distal enhancers enriched for BRCA1 binding motifs and sites that link PR and ER/PR complexes. When both hormones are present, progestin modulates estrogen action, such that responsive transcriptomes, cellular processes, and ER/PR recruitment to genomic sites correlate with those observed with PR alone, but not ER alone. Despite this overall correlation, the transcriptome patterns modulated by dual treatment are sufficiently different from individual treatments, such that antagonism of oncogenic processes is both predicted and observed. Combination therapies using the selective PR modulator/antagonist (SPRM) CDB4124 in combination with tamoxifen elicited 70% cytotoxic tumor regression of T47D tumor xenografts, whereas individual therapies inhibited tumor growth without net regression. Our findings demonstrate that PR redirects ER chromatin binding to antagonize estrogen signaling and that SPRMs can potentiate responses to antiestrogens, suggesting that cotargeting of ER and PR in ER(+)/PR(+) breast cancers should be explored. PMID:27386569

  12. Genomic responses in mouse models poorly mimic human inflammatory diseases

    Science.gov (United States)

    Seok, Junhee; Warren, H. Shaw; Cuenca, Alex G.; Mindrinos, Michael N.; Baker, Henry V.; Xu, Weihong; Richards, Daniel R.; McDonald-Smith, Grace P.; Gao, Hong; Hennessy, Laura; Finnerty, Celeste C.; López, Cecilia M.; Honari, Shari; Moore, Ernest E.; Minei, Joseph P.; Cuschieri, Joseph; Bankey, Paul E.; Johnson, Jeffrey L.; Sperry, Jason; Nathens, Avery B.; Billiar, Timothy R.; West, Michael A.; Jeschke, Marc G.; Klein, Matthew B.; Gamelli, Richard L.; Gibran, Nicole S.; Brownstein, Bernard H.; Miller-Graziano, Carol; Calvano, Steve E.; Mason, Philip H.; Cobb, J. Perren; Rahme, Laurence G.; Lowry, Stephen F.; Maier, Ronald V.; Moldawer, Lyle L.; Herndon, David N.; Davis, Ronald W.; Xiao, Wenzhong; Tompkins, Ronald G.; Abouhamze, Amer; Balis, Ulysses G. J.; Camp, David G.; De, Asit K.; Harbrecht, Brian G.; Hayden, Douglas L.; Kaushal, Amit; O’Keefe, Grant E.; Kotz, Kenneth T.; Qian, Weijun; Schoenfeld, David A.; Shapiro, Michael B.; Silver, Geoffrey M.; Smith, Richard D.; Storey, John D.; Tibshirani, Robert; Toner, Mehmet; Wilhelmy, Julie; Wispelwey, Bram; Wong, Wing H

    2013-01-01

    A cornerstone of modern biomedical research is the use of mouse models to explore basic pathophysiological mechanisms, evaluate new therapeutic approaches, and make go or no-go decisions to carry new drug candidates forward into clinical trials. Systematic studies evaluating how well murine models mimic human inflammatory diseases are nonexistent. Here, we show that, although acute inflammatory stresses from different etiologies result in highly similar genomic responses in humans, the responses in corresponding mouse models correlate poorly with the human conditions and also, one another. Among genes changed significantly in humans, the murine orthologs are close to random in matching their human counterparts (e.g., R2 between 0.0 and 0.1). In addition to improvements in the current animal model systems, our study supports higher priority for translational medical research to focus on the more complex human conditions rather than relying on mouse models to study human inflammatory diseases. PMID:23401516

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

    OpenAIRE

    Garcia-Closas, Montserrat; Couch, Fergus J.; Lindstrom, Sara; Michailidou, Kyriaki; Schmidt, Marjanka K.; Brook, Mark N.; Orr, Nick; Rhie, Suhn Kyong; Riboli, Elio; Feigelson, Heather s; Le Marchand, Loic; Buring, Julie E.; Eccles, Diana; Miron, Penelope; Fasching, Peter A.

    2013-01-01

    Estrogen receptor (ER)-negative tumors represent 20–30% of all breast cancers, with a higher proportion occurring in younger women and women of African ancestry1. The etiology2 and clinical behavior3 of ER-negative tumors are different from those of tumors expressing ER (ER positive), including differences in genetic predisposition4. To identify susceptibility loci specific to ER-negative disease, we combined in a meta-analysis 3 genome-wide association studies of 4,193 ER-negative breast can...

  14. GENOMIC LANDSCAPE OF NON-SMALL CELL LUNG CANCER IN SMOKERS AND NEVER SMOKERS

    Science.gov (United States)

    Govindan, Ramaswamy; Ding, Li; Griffith, Malachi; Subramanian, Janakiraman; Dees, Nathan D.; Kanchi, Krishna L.; Maher, Christopher A.; Fulton, Robert; Fulton, Lucinda; Wallis, John; Chen, Ken; Walker, Jason; McDonald, Sandra; Bose, Ron; Ornitz, David; Xiong, Donghai; You, Ming; Dooling, David J.; Watson, Mark; Mardis, Elaine R.

    2013-01-01

    Summary We report the results of whole genome and transcriptome sequencing of tumor and adjacent normal tissue samples from 17 patients with non-small cell lung carcinoma (NSCLC). We identified 3,726 point mutations and over 90 indels in the coding sequence, with an average mutation frequency more than 10-fold higher in smokers than in never-smokers. Novel alterations in genes involved in chromatic modification and DNA repair pathways were identified along with DACH1, CFTR, RELN, ABCB5, and HGF. Deep digital sequencing revealed diverse clonality patterns in both never smokers and smokers. All validated EFGR and KRAS mutations were present in the founder clones, suggesting possible roles in cancer initiation. Analysis revealed 14 fusions including ROS1 and ALK as well as novel metabolic enzymes. Cell cycle and JAK-STAT pathways are significantly altered in lung cancer along with perturbations in 54 genes that are potentially targetable with currently available drugs. PMID:22980976

  15. In Silico Experimental Modeling of Cancer Treatment

    OpenAIRE

    Trisilowati; D. G. Mallet

    2012-01-01

    In silico experimental modeling of cancer involves combining findings from biological literature with computer-based models of biological systems in order to conduct investigations of hypotheses entirely in the computer laboratory. In this paper, we discuss the use of in silico modeling as a precursor to traditional clinical and laboratory research, allowing researchers to refine their experimental programs with an aim to reducing costs and increasing research efficiency. We explain the metho...

  16. Specific genomic aberrations in primary colorectal cancer are associated with liver metastases

    Directory of Open Access Journals (Sweden)

    Wessels Lodewyk F

    2010-12-01

    Full Text Available Abstract Background Accurate staging of colorectal cancer (CRC with clinicopathological parameters is important for predicting prognosis and guiding treatment but provides no information about organ site of metastases. Patterns of genomic aberrations in primary colorectal tumors may reveal a chromosomal signature for organ specific metastases. Methods Array Comparative Genomic Hybridization (aCGH was employed to asses DNA copy number changes in primary colorectal tumors of three distinctive patient groups. This included formalin-fixed, paraffin-embedded tissue of patients who developed liver metastases (LM; n = 36, metastases (PM; n = 37 and a group that remained metastases-free (M0; n = 25. A novel statistical method for identifying recurrent copy number changes, KC-SMART, was used to find specific locations of genomic aberrations specific for various groups. We created a classifier for organ specific metastases based on the aCGH data using Prediction Analysis for Microarrays (PAM. Results Specifically in the tumors of primary CRC patients who subsequently developed liver metastasis, KC-SMART analysis identified genomic aberrations on chromosome 20q. LM-PAM, a shrunken centroids classifier for liver metastases occurrence, was able to distinguish the LM group from the other groups (M0&PM with 80% accuracy (78% sensitivity and 86% specificity. The classification is predominantly based on chromosome 20q aberrations. Conclusion Liver specific CRC metastases may be predicted with a high accuracy based on specific genomic aberrations in the primary CRC tumor. The ability to predict the site of metastases is important for improvement of personalized patient management.

  17. 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

    Full Text Available BACKGROUND: 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. METHODOLOGY/PRINCIPAL FINDINGS: 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. CONCLUSIONS/SIGNIFICANCE: Our approach allows more precisely profiling of functionally relevant epigenetic signatures that are associated with cancer

  18. Translating genomics: cancer genetics, public health and the making of the (de)molecularised body in Cuba and Brazil.

    Science.gov (United States)

    Gibbon, Sahra

    2016-01-01

    This article examines how cancer genetics has emerged as a focus for research and healthcare in Cuba and Brazil. Drawing on ethnographic research undertaken in community genetics clinics and cancer genetics services, the article examines how the knowledge and technologies associated with this novel area of healthcare are translated and put to work by researchers, health professionals, patients and their families in these two contexts. It illuminates the comparative similarities and differences in how cancer genetics is emerging in relation to transnational research priorities, the history and contemporary politics of public health and embodied vulnerability to cancer that reconfigures the scope and meaning of genomics as "personalised" medicine.

  19. Current state of genome-scale modeling in filamentous fungi

    DEFF Research Database (Denmark)

    Brandl, Julian; Andersen, Mikael Rørdam

    2015-01-01

    The group of filamentous fungi contains important species used in industrial biotechnology for acid, antibiotics and enzyme production. Their unique lifestyle turns these organisms into a valuable genetic reservoir of new natural products and biomass degrading enzymes that has not been used to full...... testing them in vivo. The increasing availability of high quality models and molecular biological tools for manipulating filamentous fungi renders the model-guided engineering of these fungal factories possible with comprehensive metabolic networks. A typical fungal model contains on average 1138 unique...... metabolic reactions and 1050 ORFs, making them a vast knowledge-base of fungal metabolism. In the present review we focus on the current state as well as potential future applications of genome-scale models in filamentous fungi....

  20. Preclinical fluorescent mouse models of pancreatic cancer

    Science.gov (United States)

    Bouvet, Michael; Hoffman, Robert M.

    2007-02-01

    Here we describe our cumulative experience with the development and preclinical application of several highly fluorescent, clinically-relevant, metastatic orthotopic mouse models of pancreatic cancer. These models utilize the human pancreatic cancer cell lines which have been genetically engineered to selectively express high levels of the bioluminescent green fluorescent (GFP) or red fluorescent protein (RFP). Fluorescent tumors are established subcutaneously in nude mice, and tumor fragments are then surgically transplanted onto the pancreas. Locoregional tumor growth and distant metastasis of these orthotopic implants occurs spontaneously and rapidly throughout the abdomen in a manner consistent with clinical human disease. Highly specific, high-resolution, real-time visualization of tumor growth and metastasis may be achieved in vivo without the need for contrast agents, invasive techniques, or expensive imaging equipment. We have shown a high correlation between florescent optical imaging and magnetic resonance imaging in these models. Alternatively, transplantation of RFP-expressing tumor fragments onto the pancreas of GFP-expressing transgenic mice may be used to facilitate visualization of tumor-host interaction between the pancreatic tumor fragments and host-derived stroma and vasculature. Such in vivo models have enabled us to serially visualize and acquire images of the progression of pancreatic cancer in the live animal, and to demonstrate the real-time antitumor and antimetastatic effects of several novel therapeutic strategies on pancreatic malignancy. These fluorescent models are therefore powerful and reliable tools with which to investigate human pancreatic cancer and therapeutic strategies directed against it.

  1. Large genomic rearrangement of BRCA1 and BRCA2 genes in familial breast cancer patients in Korea.

    Science.gov (United States)

    Cho, Ja Young; Cho, Dae-Yeon; Ahn, Sei Hyun; Choi, Su-Youn; Shin, Inkyung; Park, Hyun Gyu; Lee, Jong Won; Kim, Hee Jeong; Yu, Jong Han; Ko, Beom Seok; Ku, Bo Kyung; Son, Byung Ho

    2014-06-01

    We screened large genomic rearrangements of the BRCA1 and BRCA2 genes in Korean, familial breast cancer patients. Multiplex ligation-dependent probe amplification assay was used to identify BRCA1 and BRCA2 genomic rearrangements in 226 Korean familial breast cancer patients with risk factors for BRCA1 and BRCA2 mutations, who previously tested negative for point mutations in the two genes. We identified only one large deletion (c.4186-1593_4676-1465del) in BRCA1. No large rearrangements were found in BRCA2. Our result indicates that large genomic rearrangement in the BRCA1 and BRCA2 genes does not seem like a major determinant of breast cancer susceptibility in the Korean population. A large-scale study needs to validate our result in Korea.

  2. Epigenetic mechanisms and cancer: an interface between the environment and the genome.

    Science.gov (United States)

    Herceg, Zdenko; Vaissière, Thomas

    2011-07-01

    Although epidemiological studies support the role of environment in a wide range of human cancers, the precise mechanisms by which environmental exposures promote cancer development and progression remain poorly understood. Environmental factors have been proposed to promote the development of malignancies by eliciting epigenetic changes; however, it is only with recent advances in epigenetics and epigenomics that target genes and the mechanisms underlying environmental influences are beginning to be elucidated. Because epigenetic mechanisms may function as an interface between environmental factors and the genome, deregulation of the epigenome by environmental stressors is likely to disrupt different cellular processes and contribute to cancer risk. In addition, the early appearance and ubiquity of epigenetic changes in virtually all steps of tumor development and progression in most, if not all, human neoplasms, make them attractive targets for biomarker discovery and targeted prevention. At the cellular level, aberrant epigenetic changes associated with environmental exposures may deregulate key cellular processes (including transcriptional control, DNA repair, cell cycle control, and carcinogen detoxification), which can be further modulated by environmental stressors, thus defining not only the phenotype of the disease but also potential biomarkers. This review summarizes recent progress in our understanding of the epigenetic mechanisms through which environmental factors may promote tumor development, with a particular focus on human lung cancer.

  3. Isolation and bioinformatics analysis of differentially methylated genomic fragments in human gastric cancer

    Institute of Scientific and Technical Information of China (English)

    Ai-Jun Liao; Qi Su; Xun Wang; Bin Zeng; Wei Shi

    2008-01-01

    AIM:To isolate and analyze the DNA sequences which are methylated differentially between gastric cancer and normal gastric mucosa.METHODS:The differentially methylated DNA sequences between gastric cancer and normal gastric mucosa were isolated by methylation-sensitive representational difference analysis (MS-RDA).Similarities between the separated fragments and the human genomic DNA were analyzed with Basic Local Alignment Search Tool (BLAST).RESULTS:Three differentially methylated DNA sequences were obtained,two of which have been accepted by GenBank.The accession numbers are AY887106 and AY887107.AY887107 was highly similar to the 11th exon of LOC440683 (98%),3'end of LOC440887 (99%),and promoter and exon regions of DRD5 (94%).AY887106 was consistent (98%) with a CpG island in ribosomal RNA isolated from colorectal cancer by Minoru Toyota in 1999.CONCLUSION:The methylation degree is different between gastric cancer and normal gastric mucosa.The differentially methylated DNA sequences can be isolated effectively by MS-RDA.

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

    Science.gov (United States)

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

    2013-01-01

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

  5. An arranged marriage for precision medicine: hypoxia and genomic assays in localized prostate cancer radiotherapy.

    Science.gov (United States)

    Bristow, R G; Berlin, A; Dal Pra, A

    2014-03-01

    Prostate cancer (CaP) is the most commonly diagnosed malignancy in males in the Western world with one in six males diagnosed in their lifetime. Current clinical prognostication groupings use pathologic Gleason score, pre-treatment prostatic-specific antigen and Union for International Cancer Control-TNM staging to place patients with localized CaP into low-, intermediate- and high-risk categories. These categories represent an increasing risk of biochemical failure and CaP-specific mortality rates, they also reflect the need for increasing treatment intensity and justification for increased side effects. In this article, we point out that 30-50% of patients will still fail image-guided radiotherapy or surgery despite the judicious use of clinical risk categories owing to interpatient heterogeneity in treatment response. To improve treatment individualization, better predictors of prognosis and radiotherapy treatment response are needed to triage patients to bespoke and intensified CaP treatment protocols. These should include the use of pre-treatment genomic tests based on DNA or RNA indices and/or assays that reflect cancer metabolism, such as hypoxia assays, to define patient-specific CaP progression and aggression. More importantly, it is argued that these novel prognostic assays could be even more useful if combined together to drive forward precision cancer medicine for localized CaP.

  6. Radiotherapy for glioblastoma: reorganization of genome maintenance mechanisms involved in the process of inhibiting cancer

    International Nuclear Information System (INIS)

    Glioblastoma is a very aggressive brain tumor, which occurs in Glial cells. The treatment consists in chemotherapy, surgery and radiotherapy. The radiotherapy is a treatment method that uses ionizing radiation to kill cancer cells. The cells have genome maintenance mechanisms (MMG) distributed in apoptosis, DNA damage response, and cell cycle pathways. These pathways are formed by sets of proteins and perform specific functions within the cell (example: induce cell death). The mutation of these proteins associated with the failure of the MMG can cause the activation of mutations and consequently induce the development of cancer. This work, objective has to identify pathways and proteins expressed in cancer treatment using free software of the statistical analysis, developed in Fortran and R platforms to show the effects caused by radiation in the proteins of cancerous tissues. The results, were fond to pathways of glioblastoma treated with radiotherapy, activation of apoptosis and response to DNA damage pathways, indicating that there is death of carcinogenic tissue caused by radiation and that some cells are triggering a process of DNA repair. (author)

  7. Sensitivity and specificity of the empirical lymphocyte genome sensitivity (LGS) assay: implications for improving cancer diagnostics.

    Science.gov (United States)

    Anderson, Diana; Najafzadeh, Mojgan; Gopalan, Rajendran; Ghaderi, Nader; Scally, Andrew J; Britland, Stephen T; Jacobs, Badie K; Reynolds, P Dominic; Davies, Justin; Wright, Andrew L; Al-Ghazal, Shariff; Sharpe, David; Denyer, Morgan C

    2014-10-01

    Lymphocyte responses from 208 individuals: 20 with melanoma, 34 with colon cancer, and 4 with lung cancer (58), 18 with suspected melanoma, 28 with polyposis, and 10 with COPD (56), and 94 healthy volunteers were examined. The natural logarithm of the Olive tail moment (OTM) was plotted for exposure to UVA through 5 different agar depths (100 cell measurements/depth) and analyzed using a repeated measures regression model. Responses of patients with cancer plateaued after treatment with different UVA intensities, but returned toward control values for healthy volunteers. For precancerous conditions and suspected cancers, intermediate responses occurred. ROC analysis of mean log OTMs, for cancers plus precancerous/suspect conditions vs. controls, cancer vs. precancerous/suspect conditions plus controls, and cancer vs. controls, gave areas under the curve of 0.87, 0.89, and 0.93, respectively (P<0.001). Optimization allowed test sensitivity or specificity to approach 100% with acceptable complementary measures. This modified comet assay could represent a stand-alone test or an adjunct to other investigative procedures for detecting cancer.

  8. The state of genomic health care and cancer. Are we going two steps forward and one step backward?

    Science.gov (United States)

    Greco, Karen E; Mahon, Suzanne M

    2011-01-01

    As the application of genomic information and technology crosses the horizon of health care into our everyday lives, expanding genomic knowledge continues to affect how health care services are defined and delivered. Genomic discoveries have led to enhanced clinical capabilities to predict susceptibility to common diseases and conditions such as cancer, diabetes, cardiovascular disease, and Alzheimer's disease. Hundreds of genetic tests are now available that can identify individuals who carry one or more gene mutations that increase their risk of developing cancer or other common diseases. Increased availability and direct-to-consumer marketing of genetic testing is moving genetic testing away from trained genetics health professionals and into the hands of primary care providers and consumers. Genetic tests available on the Internet are being directly marketed to individuals, who can order these tests and receive a report of their risk for numerous health conditions and diseases. Health care providers are expected to interpret these test results, evaluate their accuracy, address the psychosocial consequences of those distressed by receiving their results, and translate genomic information into effective care. However, as we move two steps forward, we are also moving one step backward because many health care providers are unprepared for this genomic revolution. A number of international education, practice, and policy efforts are underway to address the challenges health care providers face in providing competent genomic health care in the context of unprecedented access to information, technology, and global communication. Efforts to integrate standard of care guidelines into electronic medical records increases health care providers' access to information for individuals at risk fo or diagnosed with a genomic condition. Development of genomic competencie for health care providers has led to increased genomic content in academic pro grams. These and other

  9. Molecular profiling of indolent human prostate cancer:tackling technical challenges to achieve high-fidelity genome-wide data

    Institute of Scientific and Technical Information of China (English)

    Thomas A. Dunn; Helen L. Fedor; Angelo M. De Marzo; Jun Luo

    2012-01-01

    The contemporary problem of prostate cancer overtreatment can be partially attributed to the diagnosis of potentially indolent prostate cancers that pose low risk to aged men,and lack of sufficiently accurate risk stratification methods to reliably seek out men with indolent diseases.Since progressive acquisition and accumulation of genomic alterations,both genetic and epigenetic,is a defining feature of all human cancers at different stages of disease progression,it is hypothesized that RNA and DNA alterations characteristic of indolent prostate tumors may be different from those previously characterized in the setting of clinically significant prostate cancer.Approaches capable of detecting such alterations on a genome-wide level are the most promising.Such analysis may uncover molecular events defining early initiating stages along the natural history of prostate cancer progression,and ultimately lead to rational development of risk stratification methods for identification of men who can safely forego treatment.However,defining and characterizing indolent prostate cancer in a clinically relevant context remains a challenge,particularly when genome-wide approaches are employed to profile formalin-fixed paraffin-embedded (FFPE) tissue specimens.Here,we provide the conceptual basis underlying the importance of understanding indolent prostate cancer from molecular profiling studies,identify the key hurdles in sample acquisition and variables that affect molecular data derived from FFPE tissues,and highlight recent progresses in efforts to address these technical challenges.

  10. Optimization of primer design for the detection of variable genomic lesions in cancer.

    Science.gov (United States)

    Bashir, Ali; Liu, Yu-Tsueng; Raphael, Benjamin J; Carson, Dennis; Bafna, Vineet

    2007-11-01

    Primer approximation multiplex PCR (PAMP) is a new experimental protocol for efficiently assaying structural variation in genomes. PAMP is particularly suited to cancer genomes where the precise breakpoints of alterations such as deletions or translocations vary between patients. The design of PCR primer sets for PAMP is challenging because a large number of primer pairs are required to detect alterations in the hundreds of kilobases range that can occur in cancer. These sets of primers must achieve high coverage of the region of interest, while avoiding primer dimers and satisfying the physico-chemical constraints of good PCR primers. We describe a natural formulation of these constraints as a combinatorial optimization problem. We show that the PAMP primer design problem is NP-hard, and design algorithms based on simulated annealing and integer programming, that provide good solutions to this problem in practice. The algorithms are applied to a test region around the known CDKN2A deletion, which show excellent results even in a 1:49 mixture of mutated:wild-type cells. We use these test results to help set design parameters for larger problems. We can achieve near-optimal designs for regions close to 1 Mb. PMID:17766270

  11. Development of cancer-initiating cells and immortalizedcells with genomic instability

    Institute of Scientific and Technical Information of China (English)

    Ken-ichi Yoshioka; Yuko Atsumi; Hitoshi Nakagama; Hirobumi Teraoka

    2015-01-01

    Cancers that develop after middle age usually exhibitgenomic instability and multiple mutations. This is indirect contrast to pediatric tumors that usually developas a result of specific chromosomal translocations andepigenetic aberrations. The development of genomicinstability is associated with mutations that contributeto cellular immortalization and transformation. Canceroccurs when cancer-initiating cells (CICs), also calledcancer stem cells, develop as a result of these mutations.In this paper, we explore how CICs develop as a resultof genomic instability, including looking at which cancersuppression mechanisms are abrogated. A recent in vitrostudy revealed the existence of a CIC induction pathwayin differentiating stem cells. Under aberrant differentiationconditions, cells become senescent and develop genomicinstabilities that lead to the development of CICs. Theresulting CICs contain a mutation in the alternativereading frame of CDKN2A (ARF)/p53 module, i.e. , ineither ARF or p53. We summarize recently establishedknowledge of CIC development and cellular immortality,explore the role of the ARF/p53 module in protectingcells from transformation, and describe a risk factorfor genomic destabilization that increases during theprocess of normal cell growth and differentiation and isassociated with the downregulation of histone H2AX tolevels representative of growth arrest in normal cells.

  12. Cancer immunotherapy : insights from transgenic animal models

    NARCIS (Netherlands)

    McLaughlin, PMJ; Kroesen, BJ; Harmsen, MC; de Leij, LFMH

    2001-01-01

    A wide range of strategies in cancer immunotherapy has been developed in the last decade, some of which are currently being used in clinical settings. The development of these immunotherapeutical strategies has been facilitated by the generation of relevant transgenic animal models. Since the differ

  13. Mouse models of intestinal inflammation and cancer.

    Science.gov (United States)

    Westbrook, Aya M; Szakmary, Akos; Schiestl, Robert H

    2016-09-01

    Chronic inflammation is strongly associated with approximately one-fifth of all human cancers. Arising from combinations of factors such as environmental exposures, diet, inherited gene polymorphisms, infections, or from dysfunctions of the immune response, chronic inflammation begins as an attempt of the body to remove injurious stimuli; however, over time, this results in continuous tissue destruction and promotion and maintenance of carcinogenesis. Here, we focus on intestinal inflammation and its associated cancers, a group of diseases on the rise and affecting millions of people worldwide. Intestinal inflammation can be widely grouped into inflammatory bowel diseases (ulcerative colitis and Crohn's disease) and celiac disease. Long-standing intestinal inflammation is associated with colorectal cancer and small-bowel adenocarcinoma, as well as extraintestinal manifestations, including lymphomas and autoimmune diseases. This article highlights potential mechanisms of pathogenesis in inflammatory bowel diseases and celiac disease, as well as those involved in the progression to associated cancers, most of which have been identified from studies utilizing mouse models of intestinal inflammation. Mouse models of intestinal inflammation can be widely grouped into chemically induced models; genetic models, which make up the bulk of the studied models; adoptive transfer models; and spontaneous models. Studies in these models have lead to the understanding that persistent antigen exposure in the intestinal lumen, in combination with loss of epithelial barrier function, and dysfunction and dysregulation of the innate and adaptive immune responses lead to chronic intestinal inflammation. Transcriptional changes in this environment leading to cell survival, hyperplasia, promotion of angiogenesis, persistent DNA damage, or insufficient repair of DNA damage due to an excess of proinflammatory mediators are then thought to lead to sustained malignant transformation. With

  14. Antiangiogenic cancer drug using the zebrafish model.

    Science.gov (United States)

    Santoro, Massimo M

    2014-09-01

    The process of de novo vessel formation, called angiogenesis, is essential for tumor progression and spreading. Targeting of molecular pathways involved in such tumor angiogenetic processes by using specific drugs or inhibitors is important for developing new anticancer therapies. Drug discovery remains to be the main focus for biomedical research and represents the essence of antiangiogenesis cancer research. To pursue these molecular and pharmacological goals, researchers need to use animal models that facilitate the elucidation of tumor angiogenesis mechanisms and the testing of antiangiogenic therapies. The past few years have seen the zebrafish system emerge as a valid model organism to study developmental angiogenesis and, more recently, as an alternative vertebrate model for cancer research. In this review, we will discuss why the zebrafish model system has the advantage of being a vertebrate model equipped with easy and powerful transgenesis as well as imaging tools to investigate not only physiological angiogenesis but also tumor angiogenesis. We will also highlight the potential of zebrafish for identifying antitumor angiogenesis drugs to block tumor development and progression. We foresee the zebrafish model as an important system that can possibly complement well-established mouse models in cancer research to generate novel insights into the molecular mechanism of the tumor angiogenesis. PMID:24903092

  15. Domestic dogs and cancer research: a breed-based genomics approach.

    Science.gov (United States)

    Davis, Brian W; Ostrander, Elaine A

    2014-01-01

    Domestic dogs are unique from other animal models of cancer in that they generally experience spontaneous disease. In addition, most types of cancer observed in humans are found in dogs, suggesting that canines may be an informative system for the study of cancer genetics. Domestic dogs are divided into over 175 breeds, with members of each breed sharing significant phenotypes. The breed barrier enhances the utility of the model, especially for genetic studies where small numbers of genes are hypothesized to account for the breed cancer susceptibility. These facts, combined with recent advances in high-throughput sequencing technologies allows for an unrivaled ability to use pet dog populations to find often subtle mutations that promote cancer susceptibility and progression in dogs as a whole. The meticulous record keeping associated with dog breeding makes the model still more powerful, as it facilitates both association analysis and family-based linkage studies. Key to the success of these studies is their cooperative nature, with owners, scientists, veterinarians and breed clubs working together to avoid the cost and unpopularity of developing captive populations. In this article we explore these principals and advocate for colony-free, genetic studies that will enhance our ability to diagnose and treat cancer in dogs and humans alike.

  16. Next-generation genome-scale models for metabolic engineering

    DEFF Research Database (Denmark)

    King, Zachary A.; Lloyd, Colton J.; Feist, Adam M.;

    2015-01-01

    Constraint-based reconstruction and analysis (COBRA) methods have become widely used tools for metabolic engineering in both academic and industrial laboratories. By employing a genome-scale in silico representation of the metabolic network of a host organism, COBRA methods can be used to predict...... optimal genetic modifications that improve the rate and yield of chemical production. A new generation of COBRA models and methods is now being developed. -. encompassing many biological processes and simulation strategies. -. and next-generation models enable new types of predictions. Here, three key...... examples of applying COBRA methods to strain optimization are presented and discussed. Then, an outlook is provided on the next generation of COBRA models and the new types of predictions they will enable for systems metabolic engineering....

  17. TP53 Variations in Human Cancers: New Lessons from the IARC TP53 Database and Genomics Data.

    Science.gov (United States)

    Bouaoun, Liacine; Sonkin, Dmitriy; Ardin, Maude; Hollstein, Monica; Byrnes, Graham; Zavadil, Jiri; Olivier, Magali

    2016-09-01

    TP53 gene mutations are one of the most frequent somatic events in cancer. The IARC TP53 Database (http://p53.iarc.fr) is a popular resource that compiles occurrence and phenotype data on TP53 germline and somatic variations linked to human cancer. The deluge of data coming from cancer genomic studies generates new data on TP53 variations and attracts a growing number of database users for the interpretation of TP53 variants. Here, we present the current contents and functionalities of the IARC TP53 Database and perform a systematic analysis of TP53 somatic mutation data extracted from this database and from genomic data repositories. This analysis showed that IARC has more TP53 somatic mutation data than genomic repositories (29,000 vs. 4,000). However, the more complete screening achieved by genomic studies highlighted some overlooked facts about TP53 mutations, such as the presence of a significant number of mutations occurring outside the DNA-binding domain in specific cancer types. We also provide an update on TP53 inherited variants including the ones that should be considered as neutral frequent variations. We thus provide an update of current knowledge on TP53 variations in human cancer as well as inform users on the efficient use of the IARC TP53 Database. PMID:27328919

  18. TP53 Variations in Human Cancers: New Lessons from the IARC TP53 Database and Genomics Data.

    Science.gov (United States)

    Bouaoun, Liacine; Sonkin, Dmitriy; Ardin, Maude; Hollstein, Monica; Byrnes, Graham; Zavadil, Jiri; Olivier, Magali

    2016-09-01

    TP53 gene mutations are one of the most frequent somatic events in cancer. The IARC TP53 Database (http://p53.iarc.fr) is a popular resource that compiles occurrence and phenotype data on TP53 germline and somatic variations linked to human cancer. The deluge of data coming from cancer genomic studies generates new data on TP53 variations and attracts a growing number of database users for the interpretation of TP53 variants. Here, we present the current contents and functionalities of the IARC TP53 Database and perform a systematic analysis of TP53 somatic mutation data extracted from this database and from genomic data repositories. This analysis showed that IARC has more TP53 somatic mutation data than genomic repositories (29,000 vs. 4,000). However, the more complete screening achieved by genomic studies highlighted some overlooked facts about TP53 mutations, such as the presence of a significant number of mutations occurring outside the DNA-binding domain in specific cancer types. We also provide an update on TP53 inherited variants including the ones that should be considered as neutral frequent variations. We thus provide an update of current knowledge on TP53 variations in human cancer as well as inform users on the efficient use of the IARC TP53 Database.

  19. Quantitative and Sensitive Detection of Cancer Genome Amplifications from Formalin Fixed Paraffin Embedded Tumors with Droplet Digital PCR.

    Science.gov (United States)

    Nadauld, Lincoln; Regan, John F; Miotke, Laura; Pai, Reet K; Longacre, Teri A; Kwok, Shirley S; Saxonov, Serge; Ford, James M; Ji, Hanlee P

    2012-01-01

    For the analysis of cancer, there is great interest in rapid and accurate detection of cancer genome amplifications containing oncogenes that are potential therapeutic targets. The vast majority of cancer tissue samples are formalin fixed and paraffin embedded (FFPE) which enables histopathological examination and long term archiving. However, FFPE cancer genomic DNA is oftentimes degraded and generally a poor substrate for many molecular biology assays. To overcome the issues of poor DNA quality from FFPE samples and detect oncogenic copy number amplifications with high accuracy and sensitivity, we developed a novel approach. Our assay requires nanogram amounts of genomic DNA, thus facilitating study of small amounts of clinical samples. Using droplet digital PCR (ddPCR), we can determine the relative copy number of specific genomic loci even in the presence of intermingled normal tissue. We used a control dilution series to determine the limits of detection for the ddPCR assay and report its improved sensitivity on minimal amounts of DNA compared to standard real-time PCR. To develop this approach, we designed an assay for the fibroblast growth factor receptor 2 gene (FGFR2) that is amplified in a gastric and breast cancers as well as others. We successfully utilized ddPCR to ascertain FGFR2 amplifications from FFPE-preserved gastrointestinal adenocarcinomas. PMID:23682346

  20. Extensive Transcriptomic and Genomic Analysis Provides New Insights about Luminal Breast Cancers

    Science.gov (United States)

    Tishchenko, Inna; Milioli, Heloisa Helena; Riveros, Carlos; Moscato, Pablo

    2016-01-01

    Despite constituting approximately two thirds of all breast cancers, the luminal A and B tumours are poorly classified at both clinical and molecular levels. There are contradictory reports on the nature of these subtypes: some define them as intrinsic entities, others as a continuum. With the aim of addressing these uncertainties and identifying molecular signatures of patients at risk, we conducted a comprehensive transcriptomic and genomic analysis of 2,425 luminal breast cancer samples. Our results indicate that the separation between the molecular luminal A and B subtypes—per definition—is not associated with intrinsic characteristics evident in the differentiation between other subtypes. Moreover, t-SNE and MST-kNN clustering approaches based on 10,000 probes, associated with luminal tumour initiation and/or development, revealed the close connections between luminal A and B tumours, with no evidence of a clear boundary between them. Thus, we considered all luminal tumours as a single heterogeneous group for analysis purposes. We first stratified luminal tumours into two distinct groups by their HER2 gene cluster co-expression: HER2-amplified luminal and ordinary-luminal. The former group is associated with distinct transcriptomic and genomic profiles, and poor prognosis; it comprises approximately 8% of all luminal cases. For the remaining ordinary-luminal tumours we further identified the molecular signature correlated with disease outcomes, exhibiting an approximately continuous gene expression range from low to high risk. Thus, we employed four virtual quantiles to segregate the groups of patients. The clinico-pathological characteristics and ratios of genomic aberrations are concordant with the variations in gene expression profiles, hinting at a progressive staging. The comparison with the current separation into luminal A and B subtypes revealed a substantially improved survival stratification. Concluding, we suggest a review of the definition of

  1. caBIG™ VISDA: Modeling, visualization, and discovery for cluster analysis of genomic data

    Directory of Open Access Journals (Sweden)

    Xuan Jianhua

    2008-09-01

    clustering, and phenotype clustering (wherein phenotype labels for samples are known, albeit with minor algorithm modifications customized to each of these tasks. Conclusion VISDA achieved robust and superior clustering accuracy, compared with several benchmark clustering schemes. The model order selection scheme in VISDA was shown to be effective for high dimensional genomic data clustering. On muscular dystrophy data and muscle regeneration data, VISDA identified biologically relevant co-expressed gene clusters. VISDA also captured the pathological relationships among different phenotypes revealed at the molecular level, through phenotype clustering on muscular dystrophy data and multi-category cancer data.

  2. Understanding Cancer Prognosis

    Medline Plus

    Full Text Available ... Partners & Collaborators Spotlight on Scientists Research Areas Cancer Biology Cancer Genomics Causes of Cancer Diagnosis Prevention Screening & ... Collaborators Spotlight on Scientists NCI Research Areas Cancer Biology Cancer Genomics Causes of Cancer Diagnosis Prevention Screening & ...

  3. Towards a multiscale model of colorectal cancer

    Institute of Scientific and Technical Information of China (English)

    Ingeborg MM van Leeuwen; Carina M Edwards; Mohammad Ilyas; Helen M Byrne

    2007-01-01

    Colorectal cancer (CRC) is one of the best characterised cancers, with extensive data documenting the sequential gene mutations that underlie its development.Complementary datasets are also being generated describing changes in protein and RNA expression,tumour biology and clinical outcome. Both the quantity and the variety of information are inexorably increasing and there is now an accompanying need to integrate these highly disparate datasets. In this article we aim to explain why we believe that mathematical modelling represents a natural tool or language with which to integrate these data and, in so doing, to provide insight into CRC.

  4. The Causal Meaning of Genomic Predictors and How It Affects Construction and Comparison of Genome-Enabled Selection Models

    Science.gov (United States)

    Valente, Bruno D.; Morota, Gota; Peñagaricano, Francisco; Gianola, Daniel; Weigel, Kent; Rosa, Guilherme J. M.

    2015-01-01

    The term “effect” in additive genetic effect suggests a causal meaning. However, inferences of such quantities for selection purposes are typically viewed and conducted as a prediction task. Predictive ability as tested by cross-validation is currently the most acceptable criterion for comparing models and evaluating new methodologies. Nevertheless, it does not directly indicate if predictors reflect causal effects. Such evaluations would require causal inference methods that are not typical in genomic prediction for selection. This suggests that the usual approach to infer genetic effects contradicts the label of the quantity inferred. Here we investigate if genomic predictors for selection should be treated as standard predictors or if they must reflect a causal effect to be useful, requiring causal inference methods. Conducting the analysis as a prediction or as a causal inference task affects, for example, how covariates of the regression model are chosen, which may heavily affect the magnitude of genomic predictors and therefore selection decisions. We demonstrate that selection requires learning causal genetic effects. However, genomic predictors from some models might capture noncausal signal, providing good predictive ability but poorly representing true genetic effects. Simulated examples are used to show that aiming for predictive ability may lead to poor modeling decisions, while causal inference approaches may guide the construction of regression models that better infer the target genetic effect even when they underperform in cross-validation tests. In conclusion, genomic selection models should be constructed to aim primarily for identifiability of causal genetic effects, not for predictive ability. PMID:25908318

  5. Whole genome RNA expression profiling for the identification of novel biomarkers in the diagnosis and prognosis of biliary tract cancer

    OpenAIRE

    Chapman, M H

    2011-01-01

    Biliary tract cancer (BTC) is difficult to diagnose, in part related to the lack of reliable tumour markers. The aim of this project was to use whole genome RNA expression profiling in order to identify novel biomarkers for diagnosis and prognosis in biliary tract cancer. Chapter 1 summarises clinical aspects of BTC as well as current diagnostic and prognostic tests. Chapter 2 addresses the identification of circulating tumour cells for the diagnosis of BTC. It includes d...

  6. Computational methods for detecting copy number variations in cancer genome using next generation sequencing: principles and challenges

    OpenAIRE

    Liu, Biao; Morrison, Carl D.; Johnson, Candace S.; Trump, Donald L.; Qin, Maochun; Conroy, Jeffrey C.; Wang, Jianmin; Liu, Song

    2013-01-01

    Accurate detection of somatic copy number variations (CNVs) is an essential part of cancer genome analysis, and plays an important role in oncotarget identifications. Next generation sequencing (NGS) holds the promise to revolutionize somatic CNV detection. In this review, we provide an overview of current analytic tools used for CNV detection in NGS-based cancer studies. We summarize the NGS data types used for CNV detection, decipher the principles for data preprocessing, segmentation, and ...

  7. Alternate Service Delivery Models in Cancer Genetic Counseling: A Mini-Review.

    Science.gov (United States)

    Buchanan, Adam Hudson; Rahm, Alanna Kulchak; Williams, Janet L

    2016-01-01

    Demand for cancer genetic counseling has grown rapidly in recent years as germline genomic information has become increasingly incorporated into cancer care, and the field has entered the public consciousness through high-profile celebrity publications. Increased demand and existing variability in the availability of trained cancer genetics clinicians place a priority on developing and evaluating alternate service delivery models for genetic counseling. This mini-review summarizes the state of science regarding service delivery models, such as telephone counseling, telegenetics, and group counseling. Research on comparative effectiveness of these models in traditional individual, in-person genetic counseling has been promising for improving access to care in a manner acceptable to patients. Yet, it has not fully evaluated the short- and long-term patient- and system-level outcomes that will help answer the question of whether these models achieve the same beneficial psychosocial and behavioral outcomes as traditional cancer genetic counseling. We propose a research agenda focused on comparative effectiveness of available service delivery models and how to match models to patients and practice settings. Only through this rigorous research can clinicians and systems find the optimal balance of clinical quality, ready and secure access to care, and financial sustainability. Such research will be integral to achieving the promise of genomic medicine in oncology. PMID:27242960

  8. Alternate service delivery models in cancer genetic counseling: a mini-review

    Directory of Open Access Journals (Sweden)

    Adam Hudson Buchanan

    2016-05-01

    Full Text Available Demand for cancer genetic counseling has grown rapidly in recent years as germline genomic information has become increasingly incorporated into cancer care and the field has entered the public consciousness through high-profile celebrity publications. Increased demand and existing variability in the availability of trained cancer genetics clinicians place a priority on developing and evaluating alternate service delivery models for genetic counseling. This mini-review summarizes the state of science regarding service delivery models such as telephone counseling, telegenetics and group counseling. Research on comparative effectiveness of these models in traditional individual, in-person genetic counseling has been promising for improving access to care in a manner acceptable to patients. Yet, it has not fully evaluated the short- and long-term patient- and system-level outcomes that will help answer the question of whether these models achieve the same beneficial psychosocial and behavioral outcomes as traditional cancer genetic counseling. We propose a research agenda focused on comparative effectiveness of available service delivery models and how to match models to patients and practice settings. Only through this rigorous research can clinicians and systems find the optimal balance of clinical quality, ready and secure access to care, and financial sustainability. Such research will be integral to achieving the promise of genomic medicine in oncology.

  9. Prognostic Impact of Array-based Genomic Profiles in Esophageal Squamous Cell Cancer

    International Nuclear Information System (INIS)

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

  10. Genome network medicine: innovation to overcome huge challenges in cancer therapy.

    Science.gov (United States)

    Roukos, Dimitrios H

    2014-01-01

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

  11. Genome-wide search for gene-gene interactions in colorectal cancer.

    Directory of Open Access Journals (Sweden)

    Shuo Jiao

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

  12. Comprehensive Resources for Tomato Functional Genomics Based on the Miniature Model Tomato Micro-Tom

    OpenAIRE

    Matsukura, C; Aoki, K.; Fukuda, N.; Mizoguchi, T.; Asamizu, E; Saito, T.; Shibata, D.; Ezura, H.

    2008-01-01

    Tomato (Solanum lycopersicum L., Solanaceae) is an excellent model plant for genomic research of solanaceous plants, as well as for studying the development, ripening, and metabolism of fruit. In 2003, the International Solanaceae Project (SOL, www.sgn.cornell.edu ) was initiated by members from more than 30 countries, and the tomato genome-sequencing project is currently underway. Genome sequence of tomato obtained by this project will provide a firm foundation for forthcoming genomic studie...

  13. Association between 5p12 genomic markers and breast cancer susceptibility: evidence from 19 case-control studies.

    Directory of Open Access Journals (Sweden)

    Xiaofeng Wang

    Full Text Available BACKGROUND: The association between polymorphisms on 5p12 and breast cancer (BC has been widely evaluated since it was first identified through genome-wide association approach; however, the studies have yielded contradictory results. We sought to investigate this inconsistency by performing a comprehensive meta-analysis on two wildly studied polymorphisms (rs10941679 and rs4415084 on 5p12. METHODS: Databases including Pubmed, EMBASE, Web of Science, EBSCO, and Cochrane Library databases were searched to find relevant studies. Odds ratios (ORs with 95% confidence intervals (CIs were used to assess the strength of association. The random-effects model was applied, addressing heterogeneity and publication bias. RESULTS: A total of 19 articles involving 100,083 cases and 163,894 controls were included. An overall random-effects per-allele OR of 1.09 (95% CI: 1.06-1.12; P = 4.5 × 10(-8 and 1.09 (95% CI: 1.05-1.12; P = 4.2 × 10(-7 was found for the rs10941679 and rs4415084 polymorphism respectively. Significant results were found in Asians and Caucasians when stratified by ethnicity; whereas no significant associations were found among Africans/African-Americans. Similar results were also observed using dominant or recessive genetic models. In addition, we find both rs4415084 and rs10941679 conferred significantly greater risks of ER-positive breast cancer than of ER-negative tumors. CONCLUSIONS: Our findings demonstrated that rs10941679-G allele and rs4415084-T allele might be risk-conferring factors for the development of breast cancer, especially in Caucasians and East-Asians.

  14. Lessons learned from the application of whole-genome analysis to the treatment of patients with advanced cancers

    Science.gov (United States)

    Laskin, Janessa; Jones, Steven; Aparicio, Samuel; Chia, Stephen; Ch'ng, Carolyn; Deyell, Rebecca; Eirew, Peter; Fok, Alexandra; Gelmon, Karen; Ho, Cheryl; Huntsman, David; Jones, Martin; Kasaian, Katayoon; Karsan, Aly; Leelakumari, Sreeja; Li, Yvonne; Lim, Howard; Ma, Yussanne; Mar, Colin; Martin, Monty; Moore, Richard; Mungall, Andrew; Mungall, Karen; Pleasance, Erin; Rassekh, S. Rod; Renouf, Daniel; Shen, Yaoqing; Schein, Jacqueline; Schrader, Kasmintan; Sun, Sophie; Tinker, Anna; Zhao, Eric; Yip, Stephen; Marra, Marco A.

    2015-01-01

    Given the success of targeted agents in specific populations it is expected that some degree of molecular biomarker testing will become standard of care for many, if not all, cancers. To facilitate this, cancer centers worldwide are experimenting with targeted “panel” sequencing of selected mutations. Recent advances in genomic technology enable the generation of genome-scale data sets for individual patients. Recognizing the risk, inherent in panel sequencing, of failing to detect meaningful somatic alterations, we sought to establish processes to integrate data from whole-genome analysis (WGA) into routine cancer care. Between June 2012 and August 2014, 100 adult patients with incurable cancers consented to participate in the Personalized OncoGenomics (POG) study. Fresh tumor and blood samples were obtained and used for whole-genome and RNA sequencing. Computational approaches were used to identify candidate driver mutations, genes, and pathways. Diagnostic and drug information were then sought based on these candidate “drivers.” Reports were generated and discussed weekly in a multidisciplinary team setting. Other multidisciplinary working groups were assembled to establish guidelines on the interpretation, communication, and integration of individual genomic findings into patient care. Of 78 patients for whom WGA was possible, results were considered actionable in 55 cases. In 23 of these 55 cases, the patients received treatments motivated by WGA. Our experience indicates that a multidisciplinary team of clinicians and scientists can implement a paradigm in which WGA is integrated into the care of late stage cancer patients to inform systemic therapy decisions. PMID:27148575

  15. A multi-stage genome-wide association study of bladder cancer identifies multiple susceptibility loci

    Science.gov (United States)

    Rothman, Nathaniel; Garcia-Closas, Montserrat; Chatterjee, Nilanjan; Malats, Nuria; Wu, Xifeng; Figueroa, Jonine; Real, Francisco X; Van Den Berg, David; Matullo, Giuseppe; Baris, Dalsu; Thun, Michael; Kiemeney, Lambertus A; Vineis, Paolo; De Vivo, Immaculata; Albanes, Demetrius; Purdue, Mark P; Rafnar, Thorunn; Hildebrandt, Michelle A T; Kiltie, Anne E; Cussenot, Olivier; Golka, Klaus; Kumar, Rajiv; Taylor, Jack A; Mayordomo, Jose I; Jacobs, Kevin B; Kogevinas, Manolis; Hutchinson, Amy; Wang, Zhaoming; Fu, Yi-Ping; Prokunina-Olsson, Ludmila; Burdette, Laurie; Yeager, Meredith; Wheeler, William; Tardón, Adonina; Serra, Consol; Carrato, Alfredo; García-Closas, Reina; Lloreta, Josep; Johnson, Alison; Schwenn, Molly; Karagas, Margaret R; Schned, Alan; Andriole, Gerald; Grubb, Robert; Black, Amanda; Jacobs, Eric J; Diver, W Ryan; Gapstur, Susan M; Weinstein, Stephanie J; Virtamo, Jarmo; Cortessis, Victoria K; Gago-Dominguez, Manuela; Pike, Malcolm C; Stern, Mariana C; Yuan, Jian-Min; Hunter, David; McGrath, Monica; Dinney, Colin P; Czerniak, Bogdan; Chen, Meng; Yang, Hushan; Vermeulen, Sita H; Aben, Katja K; Witjes, J Alfred; Makkinje, Remco R; Sulem, Patrick; Besenbacher, Soren; Stefansson, Kari; Riboli, Elio; Brennan, Paul; Panico, Salvatore; Navarro, Carmen; Allen, Naomi E; Bueno-de-Mesquita, H Bas; Trichopoulos, Dimitrios; Caporaso, Neil; Landi, Maria Teresa; Canzian, Federico; Ljungberg, Borje; Tjonneland, Anne; Clavel-Chapelon, Francoise; Bishop, David T; Teo, Mark T W; Knowles, Margaret A; Guarrera, Simonetta; Polidoro, Silvia; Ricceri, Fulvio; Sacerdote, Carlotta; Allione, Alessandra; Cancel-Tassin, Geraldine; Selinski, Silvia; Hengstler, Jan G; Dietrich, Holger; Fletcher, Tony; Rudnai, Peter; Gurzau, Eugen; Koppova, Kvetoslava; Bolick, Sophia C E; Godfrey, Ashley; Xu, Zongli; Sanz-Velez, José I; García-Prats, María D; Sanchez, Manuel; Valdivia, Gabriel; Porru, Stefano; Benhamou, Simone; Hoover, Robert N; Fraumeni, Joseph F; Silverman, Debra T; Chanock, Stephen J

    2010-01-01

    We conducted a multi-stage, genome-wide association study (GWAS) of bladder cancer with a primary scan of 589,299 single nucleotide polymorphisms (SNPs) in 3,532 cases and 5,120 controls of European descent (5 studies) followed by a replication strategy, which included 8,381 cases and 48,275 controls (16 studies). In a combined analysis, we identified three new regions associated with bladder cancer on chromosomes 22q13.1, 19q12 and 2q37.1; rs1014971, (P=8×10−12) maps to a non-genic region of chromosome 22q13.1; rs8102137 (P=2×10−11) on 19q12 maps to CCNE1; and rs11892031 (P=1×10−7) maps to the UGT1A cluster on 2q37.1. We confirmed four previous GWAS associations on chromosomes 3q28, 4p16.3, 8q24.21 and 8q24.3, validated previous candidate associations for the GSTM1 deletion (P=4×10−11) and a tag SNP for NAT2 acetylation status (P=4×10−11), as well as demonstrated smoking interactions with both regions. Our findings on common variants associated with bladder cancer risk should provide new insights into mechanisms of carcinogenesis. PMID:20972438

  16. A genome-wide map of aberrantly expressed chromosomal islands in colorectal cancer

    Directory of Open Access Journals (Sweden)

    Castanos-Velez Esmeralda

    2006-09-01

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

  17. Modeling pancreatic cancer with organoids

    NARCIS (Netherlands)

    Baker, Lindsey A; Tiriac, Hervé; Clevers, Hans; Tuveson, David A

    2016-01-01

    Pancreatic ductal adenocarcinoma (PDA) is a highly lethal malignancy for which new treatment and diagnostic approaches are urgently needed. In order for such breakthroughs to be discovered, researchers require systems that accurately model the development and biology of PDA. While cell lines, geneti

  18. Comparison of 6q25 Breast Cancer Hits from Asian and European Genome Wide Association Studies in the Breast Cancer Association Consortium (BCAC)

    NARCIS (Netherlands)

    Hein, Rebecca; Maranian, Melanie; Hopper, John L.; Kapuscinski, Miroslaw K.; Southey, Melissa C.; Park, Daniel J.; Schmidt, Marjanka K.; Broeks, Annegien; Hogervorst, Frans B. L.; Bueno-de-Mesquit, H. Bas; Muir, Kenneth R.; Lophatananon, Artitaya; Rattanamongkongul, Suthee; Puttawibul, Puttisak; Fasching, Peter A.; Hein, Alexander; Ekici, Arif B.; Beckmann, Matthias W.; Fletcher, Olivia; Johnson, Nichola; Silva, Isabel dos Santos; Peto, Julian; Sawyer, Elinor; Tomlinson, Ian; Kerin, Michael; Miller, Nicola; Marmee, Frederick; Schneeweiss, Andreas; Sohn, Christof; Burwinkel, Barbara; Guenel, Pascal; Cordina-Duverger, Emilie; Menegaux, Florence; Truong, Therese; Bojesen, Stig E.; Nordestgaard, Borge G.; Flyger, Henrik; Milne, Roger L.; Arias Perez, Jose Ignacio; Pilar Zamora, M.; Benitez, Javier; Anton-Culver, Hoda; Ziogas, Argyrios; Bernstein, Leslie; Clarke, Christina A.; Brenner, Hermann; Mueller, Heiko; Arndt, Volker; Stegmaier, Christa; Rahman, Nazneen; Seal, Sheila; Turnbull, Clare; Renwick, Anthony; Meindl, Alfons; Schott, Sarah; Bartram, Claus R.; Schmutzler, Rita K.; Brauch, Hiltrud; Hamann, Ute; Ko, Yon-Dschun; Wang-Gohrke, Shan; Doerk, Thilo; Schuermann, Peter; Karstens, Johann H.; Hillemanns, Peter; Nevanlinna, Heli; Heikkinen, Tuomas; Aittomaki, Kristiina; Blomqvist, Carl; Bogdanova, Natalia V.; Zalutsky, Iosif V.; Antonenkova, Natalia N.; Bermisheva, Marina; Prokovieva, Darya; Farahtdinova, Albina; Khusnutdinova, Elza; Lindblom, Annika; Margolin, Sara; Mannermaa, Arto; Kataja, Vesa; Kosma, Veli-Matti; Hartikainen, Jaana; Chen, Xiaoqing; Beesley, Jonathan; Lambrechts, Diether; Zhao, Hui; Neven, Patrick; Wildiers, Hans; Nickels, Stefan; Flesch-Janys, Dieter; Radice, Paolo; Peterlongo, Paolo; Manoukian, Siranoush; Barile, Monica; Couch, Fergus J.; Olson, Janet E.; Wang, Xianshu; Fredericksen, Zachary; Giles, Graham G.; Baglietto, Laura; McLean, Catriona A.; Severi, Gianluca; Offit, Kenneth; Robson, Mark; Gaudet, Mia M.; Vijai, Joseph; Alnaes, Grethe Grenaker; Kristensen, Vessela; Borresen-Dale, Anne-Lise; John, Esther M.; Miron, Alexander; Winqvist, Robert; Pylkas, Katri; Jukkola-Vuorinen, Arja; Grip, Mervi; Andrulis, Irene L.; Knight, Julia A.; Glendon, Gord; Mulligan, Anna Marie; Figueroa, Jonine D.; Garcia-Closas, Montserrat; Lissowska, Jolanta; Sherman, Mark E.; Hooning, Maartje; Martens, John W. M.; Seynaeve, Caroline; Collee, Margriet; Hall, Per; Humpreys, Keith; Czene, Kamila; Liu, Jianjun; Cox, Angela; Brock, Ian W.; Cross, Simon S.; Reed, Malcolm W. R.; Ahmed, Shahana; Ghoussaini, Maya; Pharoah, Paul D. P.; Kang, Daehee; Yoo, Keun-Young; Noh, Dong-Young; Jakubowska, Anna; Jaworska, Katarzyna; Durda, Katarzyna; Zlowocka, Elzbieta; Sangrajrang, Suleeporn; Gaborieau, Valerie; Brennan, Paul; McKay, James; Shen, Chen-Yang; Yu, Jyh-Cherng; Hsu, Huan-Ming; Hou, Ming-Feng; Orr, Nick; Schoemaker, Minouk; Ashworth, Alan; Swerdlow, Anthony; Trentham-Dietz, Amy; Newcomb, Polly A.; Titus, Linda; Egan, Kathleen M.; Chenevix-Trench, Georgia; Antoniou, Antonis C.; Humphreys, Manjeet K.; Morrison, Jonathan; Chang-Claude, Jenny; Easton, Douglas F.; Dunning, Alison M.

    2012-01-01

    The 6q25.1 locus was first identified via a genome-wide association study (GWAS) in Chinese women and marked by single nucleotide polymorphism (SNP) rs2046210, approximately 180 Kb upstream of ESR1. There have been conflicting reports about the association of this locus with breast cancer in Europea

  19. Models of breast cancer: quo vadis, animal modeling?

    International Nuclear Information System (INIS)

    Rodent models for breast cancer have for many decades provided unparalleled insights into cellular and molecular aspects of neoplastic transformation and tumorigenesis. Despite recent improvements in the fidelity of genetically engineered mice, rodent models are still being criticized by many colleagues for not being 'authentic' enough to the human disease. Motives for this criticism are manifold and range from a very general antipathy against the rodent model system to well-founded arguments that highlight physiological variations between species. Newly proposed differences in genetic pathways that cause cancer in humans and mice invigorated the ongoing discussion about the legitimacy of the murine system to model the human disease. The present commentary intends to stimulate a debate on this subject by providing the background about new developments in animal modeling, by disputing suggested limitations of genetically engineered mice, and by discussing improvements but also ambiguous expectations on the authenticity of xenograft models to faithfully mimic the human disease

  20. Genome-wide association analysis of more than 120,000 individuals identifies 15 new susceptibility loci for breast cancer

    DEFF Research Database (Denmark)

    Michailidou, Kyriaki; Beesley, Jonathan; Lindstrom, Sara;

    2015-01-01

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