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Sample records for cancer models genomic

  1. Cancer genomics object model: an object model for multiple functional genomics data for cancer research.

    Science.gov (United States)

    Park, Yu Rang; Lee, Hye Won; Cho, Sung Bum; Kim, Ju Han

    2007-01-01

    The development of functional genomics including transcriptomics, proteomics and metabolomics allow us to monitor a large number of key cellular pathways simultaneously. Several technology-specific data models have been introduced for the representation of functional genomics experimental data, including the MicroArray Gene Expression-Object Model (MAGE-OM), the Proteomics Experiment Data Repository (PEDRo), and the Tissue MicroArray-Object Model (TMA-OM). Despite the increasing number of cancer studies using multiple functional genomics technologies, there is still no integrated data model for multiple functional genomics experimental and clinical data. We propose an object-oriented data model for cancer genomics research, Cancer Genomics Object Model (CaGe-OM). We reference four data models: Functional Genomic-Object Model, MAGE-OM, TMAOM and PEDRo. The clinical and histopathological information models are created by analyzing cancer management workflow and referencing the College of American Pathology Cancer Protocols and National Cancer Institute Common Data Elements. The CaGe-OM provides a comprehensive data model for integrated storage and analysis of clinical and multiple functional genomics data.

  2. Genome scale metabolic modeling of cancer

    DEFF Research Database (Denmark)

    Nilsson, Avlant; Nielsen, Jens

    2016-01-01

    been used as scaffolds for analysis of high throughput data to allow mechanistic interpretation of changes in expression. Finally, GEMs allow quantitative flux predictions using flux balance analysis (FBA). Here we critically review the requirements for successful FBA simulations of cancer cells......Cancer cells reprogram metabolism to support rapid proliferation and survival. Energy metabolism is particularly important for growth and genes encoding enzymes involved in energy metabolism are frequently altered in cancer cells. A genome scale metabolic model (GEM) is a mathematical formalization...... of metabolism which allows simulation and hypotheses testing of metabolic strategies. It has successfully been applied to many microorganisms and is now used to study cancer metabolism. Generic models of human metabolism have been reconstructed based on the existence of metabolic genes in the human genome...

  3. Human Cancer Models Initiative | Office of Cancer Genomics

    Science.gov (United States)

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

  4. Feature selection and survival modeling in The Cancer Genome Atlas

    Directory of Open Access Journals (Sweden)

    Kim H

    2013-09-01

    Full Text Available Hyunsoo Kim,1 Markus Bredel2 1Department of Pathology, The University of Alabama at Birmingham, Birmingham, AL, USA; 2Department of Radiation Oncology, and Comprehensive Cancer Center, The University of Alabama at Birmingham, Birmingham, AL, USA Purpose: Personalized medicine is predicated on the concept of identifying subgroups of a common disease for better treatment. Identifying biomarkers that predict disease subtypes has been a major focus of biomedical science. In the era of genome-wide profiling, there is controversy as to the optimal number of genes as an input of a feature selection algorithm for survival modeling. Patients and methods: The expression profiles and outcomes of 544 patients were retrieved from The Cancer Genome Atlas. We compared four different survival prediction methods: (1 1-nearest neighbor (1-NN survival prediction method; (2 random patient selection method and a Cox-based regression method with nested cross-validation; (3 least absolute shrinkage and selection operator (LASSO optimization using whole-genome gene expression profiles; or (4 gene expression profiles of cancer pathway genes. Results: The 1-NN method performed better than the random patient selection method in terms of survival predictions, although it does not include a feature selection step. The Cox-based regression method with LASSO optimization using whole-genome gene expression data demonstrated higher survival prediction power than the 1-NN method, but was outperformed by the same method when using gene expression profiles of cancer pathway genes alone. Conclusion: The 1-NN survival prediction method may require more patients for better performance, even when omitting censored data. Using preexisting biological knowledge for survival prediction is reasonable as a means to understand the biological system of a cancer, unless the analysis goal is to identify completely unknown genes relevant to cancer biology. Keywords: brain, feature selection

  5. 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.

  6. 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.

  7. 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...

  8. 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.

  9. Precision cancer mouse models through genome editing with CRISPR-Cas9

    OpenAIRE

    Mou, Haiwei; Kennedy, Zachary; Anderson, Daniel G.; Yin, Hao; Xue, Wen

    2015-01-01

    The cancer genome is highly complex, with hundreds of point mutations, translocations, and chromosome gains and losses per tumor. To understand the effects of these alterations, precise models are needed. Traditional approaches to the construction of mouse models are time-consuming and laborious, requiring manipulation of embryonic stem cells and multiple steps. The recent development of the clustered regularly interspersed short palindromic repeats (CRISPR)-Cas9 system, a powerful genome-edi...

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

    DEFF Research Database (Denmark)

    Ghaffari, Pouyan; Mardinoglu, Adil; Asplund, Anna

    2015-01-01

    Human cancer cell lines are used as important model systems to study molecular mechanisms associated with tumor growth, hereunder how genomic and biological heterogeneity found in primary tumors affect cellular phenotypes. We reconstructed Genome scale metabolic models (GEMs) for eleven cell lines...... based on RNA-Seq data and validated the functionality of these models with data from metabolite profiling. We used cell line-specific GEMs to analyze the differences in the metabolism of cancer cell lines, and to explore the heterogeneous expression of the metabolic subsystems. Furthermore, we predicted...... antimetabolites using two cell lines with different phenotypic origins, and found that it is effective in inhibiting the growth of these cell lines. Using immunohistochemistry, we also showed high or moderate expression levels of proteins targeted by the validated antimetabolite. Identified anti-growth factors...

  12. 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.

  13. Comparison of mortality and incidence cancer risk and models of genomic instability: the Techa River cohort

    Energy Technology Data Exchange (ETDEWEB)

    Eidemueller, Markus; Jacob, Peter [Helmholtz Zentrum Muenchen, Institut fuer Strahlenschutz, Neuherberg (Germany); Ostroumova, Zhenia; Krestinina, Ludmila; Akleyev, Alexander [Urals Research Center for Radiation Medicine, Chelyabinsk (Russian Federation)

    2009-07-01

    Solid cancer mortality and incidence risk after radiation exposure in the Techa River Cohort in the Southern Urals region of Russia is analyzed. Residents along the Techa River received protracted exposure in the 1950s due to the releases of radioactive materials from the Mayak plutonium complex. The analysis is performed within the framework of the biologically based two-stage clonal expansion (TSCE) model and with excess relative risk models. TSCE models including effects of radiation-induced genomic instability are applied to the data and it is found that the best description of the radiation risk is achieved with the same model of genomic instability both for the mortality and incidence cohort. By a direct comparison of the cancer risk in both cohorts it is shown how the mortality and incidence rates and excess relative risk can be related. The TSCE parameters, that describe effective biological time scales in the process of cancer development, turn out to be similar for the mortality and incidence data sets.

  14. Collaborators | Office of Cancer Genomics

    Science.gov (United States)

    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.

  15. 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:

  16. 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.

  17. The Global Cancer Genomics Consortium: interfacing genomics and cancer medicine.

    Science.gov (United States)

    2012-08-01

    The Global Cancer Genomics Consortium (GCGC) is an international collaborative platform that amalgamates cancer biologists, cutting-edge genomics, and high-throughput expertise with medical oncologists and surgical oncologists; they address the most important translational questions that are central to cancer research and treatment. The annual GCGC symposium was held at the Advanced Centre for Treatment Research and Education in Cancer, Mumbai, India, from November 9 to 11, 2011. The symposium showcased international next-generation sequencing efforts that explore cancer-specific transcriptomic changes, single-nucleotide polymorphism, and copy number variations in various types of cancers, as well as the structural genomics approach to develop new therapeutic targets and chemical probes. From the spectrum of studies presented at the symposium, it is evident that the translation of emerging cancer genomics knowledge into clinical applications can only be achieved through the integration of multidisciplinary expertise. In summary, the GCGC symposium provided practical knowledge on structural and cancer genomics approaches, as well as an exclusive platform for focused cancer genomics endeavors.

  18. 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*

  19. 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; Lathrop, Mark; Samuel, Didier; Thomas, Gilles; Zucman-Rossi, Jessica; Lichter, Peter; Eils, Roland; Brors, Benedikt; Korbel, Jan O.; Korshunov, Andrey; Landgraf, Pablo; Lehrach, Hans; Pfister, Stefan; Radlwimmer, Bernhard; Reifenberger, Guido; Taylor, Michael D.; von Kalle, Christof; Majumder, Partha P.; Sarin, Rajiv; Scarpa, Aldo; Pederzoli, Paolo; Lawlor, Rita T.; Delledonne, Massimo; Bardelli, Alberto; Biankin, Andrew V.; Grimmond, Sean M.; Gress, Thomas; Klimstra, David; Zamboni, Giuseppe; Shibata, Tatsuhiro; Nakamura, Yusuke; Nakagawa, Hidewaki; Kusuda, Jun; Tsunoda, Tatsuhiko; Miyano, Satoru; Aburatani, Hiroyuki; Kato, Kazuto; Fujimoto, Akihiro; Yoshida, Teruhiko; Campo, Elias; Lopez-Otin, Carlos; Estivill, Xavier; Guigo, Roderic; de Sanjose, Silvia; Piris, Miguel A.; Montserrat, Emili; Gonzalez-Diaz, Marcos; Puente, Xose S.; Jares, Pedro; Valencia, Alfonso; Himmelbaue, Heinz; Quesada, Victor; Bea, Silvia; Stratton, Michael R.; Futreal, P. Andrew; Campbell, Peter J.; Vincent-Salomon, Anne; Richardson, Andrea L.; Reis-Filho, Jorge S.; van de Vijver, Marc; Thomas, Gilles; Masson-Jacquemier, Jocelyne D.; Aparicio, Samuel; Borg, Ake; Borresen-Dale, Anne-Lise; Caldas, Carlos; Foekens, John A.; Stunnenberg, Hendrik G.; van't Veer, Laura; Easton, Douglas F.; Spellman, Paul T.; Martin, Sancha; Chin, Lynda; Collins, Francis S.; Compton, Carolyn C.; Ferguson, Martin L.; Getz, Gad; Gunter, Chris; Guyer, Mark; Hayes, D. Neil; Lander, Eric S.; Ozenberger, Brad; Penny, Robert; Peterson, Jane; Sander, Chris; Speed, Terence P.; Spellman, Paul T.; Wheeler, David A.; Wilson, Richard K.; Chin, Lynda; Knoppers, Bartha M.; Lander, Eric S.; Lichter, Peter; Stratton, Michael R.; Bobrow, Martin; Burke, Wylie; Collins, Francis S.; DePinho, Ronald A.; Easton, Douglas F.; Futreal, P. Andrew; Green, Anthony R.; Guyer, Mark; Hamilton, Stanley R.; Hubbard, Tim J.; Kallioniemi, Olli P.; Kennedy, Karen L.; Ley, Timothy J.; Liu, Edison T.; Lu, Youyong; Majumder, Partha; Marra, Marco; Ozenberger, Brad; Peterson, Jane; Schafer, Alan J.; Spellman, Paul T.; Stunnenberg, Hendrik G.; Wainwright, Brandon J.; Wilson, Richard K.; Yang, Huanming

    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

  20. 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.

  1. 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.

  2. CRISPR-Cas9 Knockin Mice for Genome Editing and Cancer Modeling

    OpenAIRE

    Platt, Randall J.; Chen, Sidi; ZHOU Yang; Yim, Michael J.; Swiech, Lukasz; Kempton, Hannah R.; Dahlman, James E.; Parnas, Oren; Eisenhaure, Thomas M.; Jovanovic, Marko; Graham, Daniel B.; Jhunjhunwala, Siddharth; Xavier, Ramnik J.; Langer, Robert; Anderson, Daniel G.

    2014-01-01

    CRISPR-Cas9 is a versatile genome editing technology for studying the functions of genetic elements. To broadly enable the application of Cas9 in vivo, we established a Cre-dependent Cas9 knockin mouse. We demonstrated in vivo as well as ex vivo genome editing using adeno-associated virus (AAV)-, lentivirus-, or particle-mediated delivery of guide RNA in neurons, immune cells, and endothelial cells. Using these mice, we simultaneously modeled the dynamics of KRAS, p53, and LKB1, the top three...

  3. 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.

  4. Functional Genomics for Personalized Cancer Therapy

    Science.gov (United States)

    Tyner, Jeffrey W.

    2017-01-01

    Integration of functional and genomic screening strategies reveals clinically actionable genetic events that impact the effectiveness of cancer treatment regimens and the outcomes of cancer patients. PMID:24990879

  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. 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.

  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. 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

  11. Comparative genomic analysis of esophageal cancers.

    Science.gov (United States)

    Caygill, Christine P J; Gatenby, Piers A C; Herceg, Zdenko; Lima, Sheila C S; Pinto, Luis F R; Watson, Anthony; Wu, Ming-Shiang

    2014-09-01

    The following, from the 12th OESO World Conference: Cancers of the Esophagus, includes commentaries on comparative genomic analysis of esophageal cancers: genomic polymorphisms, the genetic and epigenetic drivers in esophageal cancers, and the collection of data in the UK Barrett's Oesophagus Registry.

  12. 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.

  13. 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......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 genetic mechanisms. These modeling approaches have proven to be highly useful to determine population genetic parameters as well as prediction of genetic risk or value. We present a series of statistical modelling approaches that use prior biological information for evaluating the collective action...... of sets of genetic variants. We have applied these approaches to whole genome sequences and a complex trait phenotype resistance to starvation collected on inbred lines from the Drosophila Genome Reference Panel population. We identified a number of genomic features classification schemes (e.g. prior QTL...

  14. Integration of genomics in cancer care

    DEFF Research Database (Denmark)

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

    2013-01-01

    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...

  15. 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.

  16. 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 ...

  17. 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....

  18. Endometrial and acute myeloid leukemia cancer genomes characterized

    Science.gov (United States)

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

  19. 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.

  20. 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.

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

    Directory of Open Access Journals (Sweden)

    William E. Gillanders

    2011-11-01

    Full Text Available 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.

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

    Energy Technology Data Exchange (ETDEWEB)

    Li, Lijin [Department of Surgery, Washington University School of Medicine, St. Louis, MO 63110 (United States); Goedegebuure, Peter [Department of Surgery, Washington University School of Medicine, St. Louis, MO 63110 (United States); The Alvin J. Siteman Cancer Center at Barnes-Jewish Hospital and Washington University School of Medicine, St. Louis, MO 63110 (United States); Mardis, Elaine R. [The Alvin J. Siteman Cancer Center at Barnes-Jewish Hospital and Washington University School of Medicine, St. Louis, MO 63110 (United States); The Genome Institute at Washington University School of Medicine, St. Louis, MO 63108 (United States); Ellis, Matthew J.C. [The Alvin J. Siteman Cancer Center at Barnes-Jewish Hospital and Washington University School of Medicine, St. Louis, MO 63110 (United States); Department of Medicine, Washington University School of Medicine, St. Louis, MO 63110 (United States); Zhang, Xiuli; Herndon, John M. [Department of Surgery, Washington University School of Medicine, St. Louis, MO 63110 (United States); Fleming, Timothy P. [Department of Surgery, Washington University School of Medicine, St. Louis, MO 63110 (United States); The Alvin J. Siteman Cancer Center at Barnes-Jewish Hospital and Washington University School of Medicine, St. Louis, MO 63110 (United States); Carreno, Beatriz M. [The Alvin J. Siteman Cancer Center at Barnes-Jewish Hospital and Washington University School of Medicine, St. Louis, MO 63110 (United States); Department of Medicine, Washington University School of Medicine, St. Louis, MO 63110 (United States); Hansen, Ted H. [The Alvin J. Siteman Cancer Center at Barnes-Jewish Hospital and Washington University School of Medicine, St. Louis, MO 63110 (United States); Department of Pathology and Immunology, Washington University School of Medicine, St. Louis, MO 63110 (United States); Gillanders, William E., E-mail: gillandersw@wudosis.wustl.edu [Department of Surgery, Washington University School of Medicine, St. Louis, MO 63110 (United States); The Alvin J. Siteman Cancer Center at Barnes-Jewish Hospital and Washington University School of Medicine, St. Louis, MO 63110 (United States)

    2011-11-25

    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.

  3. 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.

  4. 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.

  5. 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).

  6. Genome Stability Pathways in Head and Neck Cancers

    Directory of Open Access Journals (Sweden)

    Glenn Jenkins

    2013-01-01

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

  7. 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.

  8. 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

  9. 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.

  10. Single-cell analysis in cancer genomics

    Science.gov (United States)

    Saadatpour, Assieh; Lai, Shujing; Guo, Guoji; Yuan, Guo-Cheng

    2017-01-01

    Genetic changes and environmental differences result in cellular heterogeneity among cancer cells within the same tumor, thereby complicating treatment outcomes. Recent advances in single-cell technologies have opened new avenues to characterize the intra-tumor cellular heterogeneity, identify rare cell types, measure mutation rates, and, ultimately, guide diagnosis and treatment. In this paper, we review the recent single-cell technological and computational advances at the genomic, transcriptomic, and proteomic levels, and discuss their applications in cancer research. PMID:26450340

  11. 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:

  12. 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.

  13. 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

  14. 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.

  15. 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.

  16. 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

  17. 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.

  18. CRISPR-Cas9: from Genome Editing to Cancer Research.

    Science.gov (United States)

    Chen, Si; Sun, Heng; Miao, Kai; Deng, Chu-Xia

    2016-01-01

    Cancer development is a multistep process triggered by innate and acquired mutations, which cause the functional abnormality and determine the initiation and progression of tumorigenesis. Gene editing is a widely used engineering tool for generating mutations that enhance tumorigenesis. The recent developed clustered regularly interspaced short palindromic repeats-CRISPR-associated 9 (CRISPR-Cas9) system renews the genome editing approach into a more convenient and efficient way. By rapidly introducing genetic modifications in cell lines, organs and animals, CRISPR-Cas9 system extends the gene editing into whole genome screening, both in loss-of-function and gain-of-function manners. Meanwhile, the system accelerates the establishment of animal cancer models, promoting in vivo studies for cancer research. Furthermore, CRISPR-Cas9 system is modified into diverse innovative tools for observing the dynamic bioprocesses in cancer studies, such as image tracing for targeted DNA, regulation of transcription activation or repression. Here, we view recent technical advances in the application of CRISPR-Cas9 system in cancer genetics, large-scale cancer driver gene hunting, animal cancer modeling and functional studies.

  19. 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.

  20. Reconstructing cancer genomes from paired-end sequencing data

    Directory of Open Access Journals (Sweden)

    Oesper Layla

    2012-04-01

    Full Text Available Abstract Background A cancer genome is derived from the germline genome through a series of somatic mutations. Somatic structural variants - including duplications, deletions, inversions, translocations, and other rearrangements - result in a cancer genome that is a scrambling of intervals, or "blocks" of the germline genome sequence. We present an efficient algorithm for reconstructing the block organization of a cancer genome from paired-end DNA sequencing data. Results By aligning paired reads from a cancer genome - and a matched germline genome, if available - to the human reference genome, we derive: (i a partition of the reference genome into intervals; (ii adjacencies between these intervals in the cancer genome; (iii an estimated copy number for each interval. We formulate the Copy Number and Adjacency Genome Reconstruction Problem of determining the cancer genome as a sequence of the derived intervals that is consistent with the measured adjacencies and copy numbers. We design an efficient algorithm, called Paired-end Reconstruction of Genome Organization (PREGO, to solve this problem by reducing it to an optimization problem on an interval-adjacency graph constructed from the data. The solution to the optimization problem results in an Eulerian graph, containing an alternating Eulerian tour that corresponds to a cancer genome that is consistent with the sequencing data. We apply our algorithm to five ovarian cancer genomes that were sequenced as part of The Cancer Genome Atlas. We identify numerous rearrangements, or structural variants, in these genomes, analyze reciprocal vs. non-reciprocal rearrangements, and identify rearrangements consistent with known mechanisms of duplication such as tandem duplications and breakage/fusion/bridge (B/F/B cycles. Conclusions We demonstrate that PREGO efficiently identifies complex and biologically relevant rearrangements in cancer genome sequencing data. An implementation of the PREGO algorithm is

  1. 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.

  2. Genomic Instability and Breast Cancer

    Science.gov (United States)

    2011-01-01

    medium containing 10% bovine serum and penicillin /streptomycin. Transient transfection was performed with the polyethyleni- mine (25 kDa) method. Stable...mutations in 13 Fanc genes and renders cells hypersensitive to DNA interstrand cross-linking (ICL) agents. A central event in the FA pathway is mono...interstrand cross-links. Fanconi anemia (FA) is characterized bycongenital malformations, bone marrowfailure, cancer, and hypersensitivity toDNA interstrand

  3. 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...

  4. The Genomic Evolution of Prostate Cancer

    Science.gov (United States)

    2015-10-01

    clone can give rise to both low grade and high grade disease. Conversely, lymph node metastases are closely related to high grade cancer. Alterations...going. Because of the overall low quality of the DNA (including whole genome amplification) the analysis is taking longer than expected but still...a postbaccalaureate student and am actively recruiting for a postdoctoral position. Opportunities for Training As per the SOW, I have attended

  5. DNA secondary structures and epigenetic determinants of cancer genome evolution

    OpenAIRE

    2010-01-01

    An unstable genome is a hallmark of many cancers. It is unclear, however, whether some mutagenic features driving somatic alterations in cancer are encoded in the genome sequence and whether they can operate in a tissue-specific manner. We performed a genome-wide analysis of 663,446 DNA breakpoints associated with somatic copy-number alterations (SCNAs) from 2,792 cancer samples classified into 26 cancer types. Many SCNA breakpoints are spatially clustered in cancer genomes. We observed a sig...

  6. 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.

  7. Genomic analysis of a spontaneous model of breast cancer metastasis to bone reveals a role for the extracellular matrix.

    Science.gov (United States)

    Eckhardt, Bedrich L; Parker, Belinda S; van Laar, Ryan K; Restall, Christina M; Natoli, Anthony L; Tavaria, Michael D; Stanley, Kym L; Sloan, Erica K; Moseley, Jane M; Anderson, Robin L

    2005-01-01

    A clinically relevant model of spontaneous breast cancer metastasis to multiple sites, including bone, was characterized and used to identify genes involved in metastatic progression. The metastatic potential of several genetically related tumor lines was assayed using a novel real-time quantitative RT-PCR assay of tumor burden. Based on this assay, the tumor lines were categorized as nonmetastatic (67NR), weakly metastatic to lymph node (168FARN) or lung (66cl4), or highly metastatic to lymph node, lung, and bone (4T1.2 and 4T1.13). In vitro assays that mimic stages of metastasis showed that highly metastatic tumors lines were more adhesive, invasive, and migratory than the less metastatic lines. To identify metastasis-related genes in this model, each metastatic tumor was array profiled against the nonmetastatic 67NR using 15,000 mouse cDNA arrays. A significant proportion of genes relating to the extracellular matrix had elevated expression in highly metastatic tumors. The role of one of these genes, POEM, was further investigated in the model. In situ hybridization showed that POEM expression was specific to the tumor epithelium of highly metastatic tumors. Decreased POEM expression in 4T1.2 tumors significantly inhibited spontaneous metastasis to the lung, bone, and kidney. Taken together, our data support a role for the extracellular matrix in metastatic progression and describe, for the first time, a role for POEM in this process.

  8. 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

  9. 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.

  10. 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.

  11. 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.

  12. Genome-wide Association Studies from the Cancer Genetic Markers of Susceptibility (CGEMS) Initiative | Office of Cancer Genomics

    Science.gov (United States)

    CGEMS identifies common inherited genetic variations associated with a number of cancers, including breast and prostate. Data from these genome-wide association studies (GWAS) are available through the Division of Cancer Epidemiology & Genetics website.

  13. 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.

  14. 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.

  15. Pan-cancer analysis of ROS1 genomic aberrations

    OpenAIRE

    Wang, Yidan; 王奕丹

    2015-01-01

    The ROS proto-oncogene 1 (ROS1) encodes the ROS1 receptor kinase. ROS1 rearrangements are known to be oncogenic in glioblastoma, non–small-cell lung carcinoma (NSCLC) and cholangiocarcinoma. The clinical relevance of ROS1 genomic aberrations in other human cancers is largely unexamined. Here, we performed a pan-cancer analysis of ROS1 genomic aberrations across 20 cancer sites by interrogating the whole-exome sequencing data of the Cancer Genome Atlas (TCGA) via the cBioportal (www.cbioportal...

  16. 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.

  17. 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...

  18. 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.

  19. 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....

  20. Evolution of cancer suppression as revealed by mammalian comparative genomics.

    Science.gov (United States)

    Tollis, Marc; Schiffman, Joshua D; Boddy, Amy M

    2017-02-02

    Cancer suppression is an important feature in the evolution of large and long-lived animals. While some tumor suppression pathways are conserved among all multicellular organisms, others mechanisms of cancer resistance are uniquely lineage specific. Comparative genomics has become a powerful tool to discover these unique and shared molecular adaptations in respect to cancer suppression. These findings may one day be translated to human patients through evolutionary medicine. Here, we will review theory and methods of comparative cancer genomics and highlight major findings of cancer suppression across mammals. Our current knowledge of cancer genomics suggests that more efficient DNA repair and higher sensitivity to DNA damage may be the key to tumor suppression in large or long-lived mammals.

  1. 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.

  2. Biology of breast cancer during pregnancy using genomic profiling.

    Science.gov (United States)

    Azim, Hatem A; Brohée, Sylvain; Peccatori, Fedro A; Desmedt, Christine; Loi, Sherene; Lambrechts, Diether; Dell'Orto, Patrizia; Majjaj, Samira; Jose, Vinu; Rotmensz, Nicole; Ignatiadis, Michail; Pruneri, Giancarlo; Piccart, Martine; Viale, Giuseppe; Sotiriou, Christos

    2014-08-01

    Breast cancer during pregnancy is rare and is associated with relatively poor prognosis. No information is available on its biological features at the genomic level. Using a dataset of 54 pregnant and 113 non-pregnant breast cancer patients, we evaluated the pattern of hot spot somatic mutations and did transcriptomic profiling using Sequenom and Affymetrix respectively. We performed gene set enrichment analysis to evaluate the pathways associated with diagnosis during pregnancy. We also evaluated the expression of selected cancer-related genes in pregnant and non-pregnant patients and correlated the results with changes occurring in the normal breast using a pregnant murine model. We finally investigated aberrations associated with disease-free survival (DFS). No significant differences in mutations were observed. Of the total number of patients, 18.6% of pregnant and 23% of non-pregnant patients had a PIK3CA mutation. Around 30% of tumors were basal, with no differences in the distribution of breast cancer molecular subtypes between pregnant and non-pregnant patients. Two pathways were enriched in tumors diagnosed during pregnancy: the G protein-coupled receptor pathway and the serotonin receptor pathway (FDR pregnancy had higher expression of PD1 (PDCD1; P=0.015), PDL1 (CD274; P=0.014), and gene sets related to SRC (P=0.004), IGF1 (P=0.032), and β-catenin (P=0.019). Their expression increased almost linearly throughout gestation when evaluated on the normal breast using a pregnant mouse model underscoring the potential effect of the breast microenvironment on tumor phenotype. No genes were associated with DFS in a multivariate model, which could be due to low statistical power. Diagnosis during pregnancy impacts the breast cancer transcriptome including potential cancer targets.

  3. 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.

  4. Multiscale cancer modeling.

    Science.gov (United States)

    Deisboeck, Thomas S; Wang, Zhihui; Macklin, Paul; Cristini, Vittorio

    2011-08-15

    Simulating cancer behavior across multiple biological scales in space and time, i.e., multiscale cancer modeling, is increasingly being recognized as a powerful tool to refine hypotheses, focus experiments, and enable more accurate predictions. A growing number of examples illustrate the value of this approach in providing quantitative insights in the initiation, progression, and treatment of cancer. In this review, we introduce the most recent and important multiscale cancer modeling works that have successfully established a mechanistic link between different biological scales. Biophysical, biochemical, and biomechanical factors are considered in these models. We also discuss innovative, cutting-edge modeling methods that are moving predictive multiscale cancer modeling toward clinical application. Furthermore, because the development of multiscale cancer models requires a new level of collaboration among scientists from a variety of fields such as biology, medicine, physics, mathematics, engineering, and computer science, an innovative Web-based infrastructure is needed to support this growing community.

  5. Panx3 links body mass index and tumorigenesis in a genetically heterogeneous mouse model of carcinogen-induced cancer. | Office of Cancer Genomics

    Science.gov (United States)

    Body mass index (BMI) has been implicated as a primary factor influencing cancer development. However, understanding the relationship between these two complex traits has been confounded by both environmental and genetic heterogeneity. Analysis of QTL linked to tumorigenesis and BMI identified several loci associated with both phenotypes. Exploring these loci in greater detail revealed a novel relationship between the Pannexin 3 gene (Panx3) and both BMI and tumorigenesis. Panx3 is positively associated with BMI and is strongly tied to a lipid metabolism gene expression network.

  6. Gremlin: an interactive visualization model for analyzing genomic rearrangements.

    Science.gov (United States)

    O'Brien, Trevor M; Ritz, Anna M; Raphael, Benjamin J; Laidlaw, David H

    2010-01-01

    In this work we present, apply, and evaluate a novel, interactive visualization model for comparative analysis of structural variants and rearrangements in human and cancer genomes, with emphasis on data integration and uncertainty visualization. To support both global trend analysis and local feature detection, this model enables explorations continuously scaled from the high-level, complete genome perspective, down to the low-level, structural rearrangement view, while preserving global context at all times. We have implemented these techniques in Gremlin, a genomic rearrangement explorer with multi-scale, linked interactions, which we apply to four human cancer genome data sets for evaluation. Using an insight-based evaluation methodology, we compare Gremlin to Circos, the state-of-the-art in genomic rearrangement visualization, through a small user study with computational biologists working in rearrangement analysis. Results from user study evaluations demonstrate that this visualization model enables more total insights, more insights per minute, and more complex insights than the current state-of-the-art for visual analysis and exploration of genome rearrangements.

  7. Cancer genetics and genomics: essentials for oncology nurses.

    Science.gov (United States)

    Boucher, Jean; Habin, Karleen; Underhill, Meghan

    2014-06-01

    Cancer genetics and genomics are rapidly evolving, with new discoveries emerging in genetic mutations, variants, genomic sequencing, risk-reduction methods, and targeted therapies. To educate patients and families, state-of-the-art care requires nurses to understand terminology, scientific and technological advances, and pharmacogenomics. Clinical application of cancer genetics and genomics involves working in interdisciplinary teams to properly identify patient risk through assessing family history, facilitating genetic testing and counseling services, applying risk-reduction methods, and administering and monitoring targeted therapies.

  8. 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.

  9. Whole genome sequencing for childhood cancer in Denmark

    DEFF Research Database (Denmark)

    Gupta, Ramneek

    of host, tumour and gut microbiome’s genomes. In Europe, cancer accounts for approximately 25% of all deaths in children >1 year. Most cured patients are burdened by late effects, including risk of second cancer and debilitating toxicities. Recent advancements in genetic sequencing technology...

  10. Databases and web tools for cancer genomics study.

    Science.gov (United States)

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

    2015-02-01

    Publicly-accessible resources have promoted the advance of scientific discovery. The era of genomics and big data has brought the need for collaboration and data sharing in order to make effective use of this new knowledge. Here, we describe the web resources for cancer genomics research and rate them on the basis of the diversity of cancer types, sample size, omics data comprehensiveness, and user experience. The resources reviewed include data repository and analysis tools; and we hope such introduction will promote the awareness and facilitate the usage of these resources in the cancer research community.

  11. 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.

  12. 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 ...

  13. 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.

  14. Clinical implications of genomics for cancer risk genetics.

    Science.gov (United States)

    Thomas, David M; James, Paul A; Ballinger, Mandy L

    2015-06-01

    The study of human genetics has provided substantial insight into cancer biology. With an increase in sequencing capacity and a reduction in sequencing costs, genomics will probably transform clinical cancer genetics. A heritable basis for many cancers is accepted, but so far less than half the genetic drivers have been identified. Genomics will increasingly be applied to populations irrespective of family history, which will change the framework of phenotype-directed genetic testing. Panel testing and whole genome sequencing will identify novel, polygenic, and de-novo determinants of cancer risk, often with lower penetrance, which will challenge present binary clinical classification systems and management algorithms. In the future, genotype-stratified public screening and prevention programmes could form part of tailored population risk management. The integration of research with clinical practice will result in so-called discovery cohorts that will help identify clinically significant genetic variation.

  15. 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

  16. 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.

  17. 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.

  18. [Current topics in mutations in the cancer genome].

    Science.gov (United States)

    Iwaya, Takeshi; Mimori, Koshi; Wakabayashi, Go

    2012-03-01

    Several oncogenes and tumor suppressor genes are involved in the multistep process of carcinogenesis in many cancer types. Recently, global mutational analyses have revealed that the cancer genome has far greater numbers of mutations than previously thought. Furthermore, the next-generation sequencing method, which has a different principle from conventional Sanger sequencing, has provided more information on the cancer genome such as new cancer-related genes and the existence of many rearrangements in solid cancers. Somatic mutations occurring in cancer cells are divided into "driver" and "passenger" mutations. Driver mutations confer a growth advantage upon the neoplastic clone and are crucial for carcinogenesis. The remaining large majority of mutations are passengers, which, by definition, do not confer a growth advantage. Driver genes with low-frequency mutation rates (less than 10%) are also involved in carcinogenesis along with well-known drivers with high-frequency mutations. There are now several celebrated examples of anticancer drugs of which the efficacy in cancer patients can be predicted based on the genotype of several driver genes, such as EGFR, KRAS, and BRAF on the EGFR signaling pathway. The complete catalogs of somatic mutations provided by the sequencing of the cancer genome are expected to prompt new approaches to diagnosis, therapy, and potentially prevention.

  19. 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.

  20. Tolerance of Whole-Genome Doubling Propagates Chromosomal Instability and Accelerates Cancer Genome Evolution

    DEFF Research Database (Denmark)

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

    2014-01-01

    The contribution of whole-genome doubling to chromosomal instability (CIN) and tumor evolution is unclear. We use long-term culture of isogenic tetraploid cells from a stable diploid colon cancer progenitor to investigate how a genome-doubling event affects genome stability over time. Rare cells...... that survive genome doubling demonstrate increased tolerance to chromosome aberrations. Tetraploid cells do not exhibit increased frequencies of structural or numerical CIN per chromosome. However, the tolerant phenotype in tetraploid cells, coupled with a doubling of chromosome aberrations per cell, allows...... chromosome abnormalities to evolve specifically in tetraploids, recapitulating chromosomal changes in genomically complex colorectal tumors. Finally, a genome-doubling event is independently predictive of poor relapse-free survival in early-stage disease in two independent cohorts in multivariate analyses...

  1. HCMI Organization | Office of Cancer Genomics

    Science.gov (United States)

    Consortium HCMI was created and funded by the National Cancer Institute, Cancer Research UK, foundation Hubrecht Organoid Technology, and Wellcome Trust Sanger Institute. Together, these organizations develop policy and make programmatic decisions to contribute to the function of the HCMI. National Cancer Institute

  2. A mathematical model of radiation carcinogenesis with induction of genomic instability and cell death.

    Science.gov (United States)

    Ohtaki, M; Niwa, O

    2001-11-01

    We developed a mathematical model of carcinogenesis that incorporates genomic instability, a feature characterized by long-term destabilization of the genome in irradiated cells that leads to an increase in cancer risk in the exposed individuals at the cancer-prone age. This model also considers the induction of cell death, another important effect of radiation on cells. It is assumed that cell killing by radiation may occur at all stages of the carcinogenic process. The resulting model can explain not only the paradoxical relationship between low mutation rates and high cancer incidence but also the low-order dose-response relationship of cancer risk.

  3. 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.

  4. Outsmarting cancer: the power of hybrid genomic/proteomic biomarkers to predict drug response.

    Science.gov (United States)

    Rexer, Brent N; Arteaga, Carlos L

    2014-01-01

    A recent study by Niepel and colleagues describes a novel approach to predicting response to targeted anti-cancer therapies. The authors used biochemical profiling of signaling activity in basal and ligand-stimulated states for a panel of receptor and intracellular kinases to develop predictive models of drug sensitivity. In some cases, the response to ligand stimulation predicted drug response better than did target abundance or genomic alterations in the targeted pathway. Furthermore, combining biochemical profiles with genomic information was better at predicting drug response. This work suggests that incorporating biochemical signaling profiles with genomic alterations should provide powerful predictors of response to molecularly targeted therapies.

  5. Molecular cytogenetic applications in analysis of the cancer genome.

    Science.gov (United States)

    Rao, Pulivarthi H; Nandula, Subhadra V; Murty, Vundavalli V

    2007-01-01

    Cancer cells exhibit nonrandom and complex chromosome abnormalities. The role of genomic changes in cancer is well established. However, the identification of complex and cryptic chromosomal changes is beyond the resolution of conventional banding methods. The fluorescence microscopy afforded by imaging technologies, developed recently, facilitates a precise identification of these chromosome alterations in cancer. The three most commonly utilized molecular cytogenetics methods comparative genomic hybridization, spectral karyotype, and fluorescence in situ hybridization, that have already become benchmark tools in cancer cytogenetics, are described in this chapter. Comparative genomic hybridization is a powerful tool for screening copy-number changes in tumor genomes without the need for preparation of metaphases from tumor cells. Multicolor spectral karyotype permits visualization of all chromosomes in one experiment permitting identification of precise chromosomal changes on metaphases derived from tumor cells. The uses of fluorescence in situ hybridization are diverse, including mapping of alteration in single copy genes, chromosomal regions, or entire chromosomes. The opportunities to detect genetic alterations in cancer cells continue to evolve with the use of these methodologies both in diagnosis and research.

  6. 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

  7. HUMAN CANCER IS A PARASITE SPREAD VIA INTRUSION IN GENOME

    Directory of Open Access Journals (Sweden)

    Sergey N. Rumyantsev

    2013-03-01

    Full Text Available The present article is devoted to further development of new paradigm about the biology of human cancer: the hypothesis of parasitic nature, origin and evolution of the phenomenon. The study included integrative reconsidering, and reinterpretation of the make-ups, traits and processes existing both in human and animal cancers. It was demonstrated that human cancer possesses nearly analogous set of traits characteristic of transmissible animal cancer. Undoubted analogies are seen in the prevalence, clinical exposure, progression of disease, origin of causative agents, immune response against invasion and especially in the intrinsic deviations of the leading traits of cancerous cells. Both human and animal cancers are highly exceptional pathogens. But in contrast to contagious animal cancers the cells of of human cancer can not pass between individuals as usual infectious agents. Exhaustive evidence of the parasitic nature and evolutionary origin of human cancer was revealed and interpreted. In contrast to animal cancer formed of solitary cell lineage, human cancer consists of a couple of lineages constructed under different genetic regulations and performed different structural and physiological functions. The complex make-up of cancer composition remains stable over sequential propagation. The subsistence of human cancer regularly includes obligatory interchange of its successive forms. Human cancer possesses its own biological watch and the ability to gobble its victim, transmit via the intrusion of the genome, perform intercommunications within the tumor components and between the dispersed subunits of cancer. Such intrinsic traits characterize human cancer as a primitively structured parasite that can be classified in Class Mammalians, Species Genomeintruder malevolent (G.malevolent.

  8. 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.

  9. 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

  10. 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.

  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. A Genome-wide Pleiotropy Scan for Prostate Cancer Risk

    Science.gov (United States)

    Panagiotou, Orestis A; Travis, Ruth C; Campa, Daniele; Berndt, Sonja I.; Lindstrom, Sara; Kraft, Peter; Schumacher, Fredrick R.; Siddiq, Afshan; Papatheodorou, Stefania I.; Stanford, Janet L.; Albanes, Demetrius; Virtamo, Jarmo; Weinstein, Stephanie J.; Diver, W. Ryan; Gapstur, Susan M.; Stevens, Victoria L.; Boeing, Heiner; Bueno-de-Mesquita, H. Bas; Gurrea, Aurelio Barricarte; Kaaks, Rudolf; Khaw, Kay-Tee; Krogh, Vittorio; Overvad, Kim; Riboli, Elio; Trichopoulos, Dimitrios; Giovannucci, Edward; Stampfer, Meir; Haiman, Christopher; Henderson, Brian; Le Marchand, Loic; Gaziano, J. Michael; Hunter, DavidJ.; Koutros, Stella; Yeager, Meredith; Hoover, Robert N.; Chanock, Stephen J.; Wacholder, Sholom; Key, Timothy J.; Tsilidis, Konstantinos K

    2014-01-01

    Background No single-nucleotide polymorphisms (SNPs) specific for aggressive prostate cancer have been identified in genome-wide association studies (GWAS). Objective To test if SNPs associated with other traits may also affect the risk of aggressive prostate cancer. Design, setting, and participants SNPs implicated in any phenotype other than prostate cancer (p ≤ 10−7) were identified through the catalog of published GWAS and tested in 2891 aggressive prostate cancer cases and 4592 controls from the Breast and Prostate Cancer Cohort Consortium (BPC3). The 40 most significant SNPs were followed up in 4872 aggressive prostate cancer cases and 24 534 controls from the Prostate Cancer Association Group to Investigate Cancer Associated Alterations in the Genome (PRACTICAL) consortium. Outcome measurements and statistical analysis Odds ratios (ORs) and 95% confidence intervals (CIs) for aggressive prostate cancer were estimated. Results and limitations A total of 4666 SNPs were evaluated by the BPC3. Two signals were seen in regions already reported for prostate cancer risk. rs7014346 at 8q24.21 was marginally associated with aggressive prostate cancer in the BPC3 trial (p = 1.6 × 10-6), whereas after meta-analysis by PRACTICAL the summary OR was 1.21 (95%CI 1.16–1.27; p = 3.22 × 10−18). rs9900242 at 17q24.3 was also marginally associated with aggressive disease in the meta-analysis (OR 0.90, 95% CI 0.86–0.94; p = 2.5 × 10−6). Neither of these SNPs remained statistically significant when conditioning on correlated known prostate cancer SNPs. The meta-analysis by BPC3 and PRACTICAL identified a third promising signal, marked by rs16844874 at 2q34, independent of known prostate cancer loci (OR 1.12,95% CI 1.06–1.19; p = 4.67 × 10−5); it has been shown that SNPs correlated with this signal affect glycine concentrations. The main limitation is the heterogeneity in the definition of aggressive prostate cancer between BPC3 and PRACTICAL. Conclusions We did

  13. 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:

  14. 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.

  15. Analyzing Somatic Genome Rearrangements in Human Cancers by Using Whole-Exome Sequencing | Office of Cancer Genomics

    Science.gov (United States)

    Although exome sequencing data are generated primarily to detect single-nucleotide variants and indels, they can also be used to identify a subset of genomic rearrangements whose breakpoints are located in or near exons. Using >4,600 tumor and normal pairs across 15 cancer types, we identified over 9,000 high confidence somatic rearrangements, including a large number of gene fusions.

  16. 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.

  17. A Genomic Microchip for Oral Cancer.

    Science.gov (United States)

    Sarode, Gargi S; Sarode, Sachin C; Maniyar, Nikunj; Patil, Shankargouda

    2017-03-01

    A series of genetic mutations in somatic cell results in cancer. The cells of malignant tumor have the ability to acclimate to the microenvironmental changes. This can be attributed to the nature of tumor cell biology, i.e., based on effectual molecular signaling events.

  18. 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.

  19. Multiple models for Rosaceae genomics.

    Science.gov (United States)

    Shulaev, Vladimir; Korban, Schuyler S; Sosinski, Bryon; Abbott, Albert G; Aldwinckle, Herb S; Folta, Kevin M; Iezzoni, Amy; Main, Dorrie; Arús, Pere; Dandekar, Abhaya M; Lewers, Kim; Brown, Susan K; Davis, Thomas M; Gardiner, Susan E; Potter, Daniel; Veilleux, Richard E

    2008-07-01

    The plant family Rosaceae consists of over 100 genera and 3,000 species that include many important fruit, nut, ornamental, and wood crops. Members of this family provide high-value nutritional foods and contribute desirable aesthetic and industrial products. Most rosaceous crops have been enhanced by human intervention through sexual hybridization, asexual propagation, and genetic improvement since ancient times, 4,000 to 5,000 B.C. Modern breeding programs have contributed to the selection and release of numerous cultivars having significant economic impact on the U.S. and world markets. In recent years, the Rosaceae community, both in the United States and internationally, has benefited from newfound organization and collaboration that have hastened progress in developing genetic and genomic resources for representative crops such as apple (Malus spp.), peach (Prunus spp.), and strawberry (Fragaria spp.). These resources, including expressed sequence tags, bacterial artificial chromosome libraries, physical and genetic maps, and molecular markers, combined with genetic transformation protocols and bioinformatics tools, have rendered various rosaceous crops highly amenable to comparative and functional genomics studies. This report serves as a synopsis of the resources and initiatives of the Rosaceae community, recent developments in Rosaceae genomics, and plans to apply newly accumulated knowledge and resources toward breeding and crop improvement.

  20. Clonal expansion and linear genome evolution through breast cancer progression from pre-invasive stages to asynchronous metastasis

    DEFF Research Database (Denmark)

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

    step. Our data, contrary to the proposed model of early dissemination of metastatic cells and parallel progression of primary tumors and metastases, provide evidence of linear progression of breast cancer with relatively late dissemination from the primary tumor. The genomic discordance between......Evolution of the breast cancer genome from pre-invasive stages to asynchronous metastasis is complex and mostly unexplored, but highly demanded as it may provide novel markers for and mechanistic insights in cancer progression. The increasing use of personalized therapy of breast cancer...... necessitates knowledge of the degree of genomic concordance between different steps of malignant progression as primary tumors often are used as surrogates of systemic disease. Based on exome sequencing we performed copy number profiling and point mutation detection on successive steps of breast cancer...

  1. Clonal expansion and linear genome evolution through breast cancer progression from pre-invasive stages to asynchronous metastasis

    DEFF Research Database (Denmark)

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

    2015-01-01

    step. Our data, contrary to the proposed model of early dissemination of metastatic cells and parallel progression of primary tumors and metastases, provide evidence of linear progression of breast cancer with relatively late dissemination from the primary tumor. The genomic discordance between......Evolution of the breast cancer genome from pre-invasive stages to asynchronous metastasis is complex and mostly unexplored, but highly demanded as it may provide novel markers for and mechanistic insights in cancer progression. The increasing use of personalized therapy of breast cancer...... necessitates knowledge of the degree of genomic concordance between different steps of malignant progression as primary tumors often are used as surrogates of systemic disease. Based on exome sequencing we performed copy number profiling and point mutation detection on successive steps of breast cancer...

  2. Genomic predictors for treatment of late stage prostate cancer

    Directory of Open Access Journals (Sweden)

    Daniel H Shevrin

    2016-01-01

    Full Text Available In spite of the development of new treatments for late stage prostate cancer, significant challenges persist to match individuals with effective targeted therapies. Genomic classification using high-throughput sequencing technologies has the potential to achieve this goal and make precision medicine a reality in the management of men with castrate-resistant prostate cancer. This chapter reviews some of the most recent studies that have resulted in significant progress in determining the landscape of somatic genomic alterations in this cohort and, more importantly, have provided clinically actionable information that could guide treatment decisions. This chapter reviews the current understanding of common alterations such as alterations of the androgen receptor and PTEN pathway, as well as ETS gene fusions and the growing importance of PARP inhibition. It also reviews recent studies that characterize the evolution to neuroendocrine tumors, which is becoming an increasingly important clinical problem. Finally, this chapter reviews recent innovative studies that characterize the compelling evolutionary history of lethal prostate cancer evidenced by polyclonal seeding and interclonal cooperation between metastasis and the importance of tumor clone dynamics measured serially in response to treatment. The genomic landscape of late stage prostate cancer is becoming better defined, and the prospect for assigning clinically actionable data to inform rationale treatment for individuals with this disease is becoming a reality.

  3. Apoptotic and genomic effects of corilagin on SKOV3 ovarian cancer cell line

    Science.gov (United States)

    Attar, Rukset; Cincin, Zeynep Birsu; Bireller, Elif Sinem; Cakmakoglu, Bedia

    2017-01-01

    Corilagin is a member of the tannin family and has been isolated from traditional Chinese medicinal plants, such as Phyllanthus spp. Corilagin has anti-inflammatory, antioxidative, antiatherogenic, and antihypertensive effects in various experimental models. In this research, we aimed to investigate for the first time whether corilagin had apoptotic and genomic effects in ovarian cancer treatment in the same study. The potential apoptotic of corilagin was investigated using a WST1 cell proliferation test, caspase 3, and mitochondrial membrane potential JC1 assays in a time- and dose-dependent manner. Genomic changes in expression levels against corilagin treatment were measured using an Illumina human HT-12V4 BeadChip microarray. Bioinformatic data analyses were performed using GenomeStudio and Ingenuity Pathway Analysis software. The data of our study demonstrated that there were statistically significant time- and dose-dependent increases in caspase 3 enzymatic activity and loss of mitochondrial membrane potential in line with decreases in cancer cell proliferation. According to gene-ontology analysis, we found that adherens junctions, antigen processing and presentation, and the phosphatidylinositol signaling system were the most statistically significant networks in response to corilagin treatment on SKOV3 cells, in a time- and dose-dependent manner. The apoptotic and genome-wide effects of corilagin on ovarian cancer cells were examined in detail for the first time in the literature. The results of our study suggest that corilagin might have the potential to be used as a new treatment option for epithelial ovarian cancer.

  4. A novel approach for determining cancer genomic breakpoints in the presence of normal DNA.

    Directory of Open Access Journals (Sweden)

    Yu-Tsueng Liu

    Full Text Available CDKN2A (encodes p16(INK4A and p14(ARF deletion, which results in both Rb and p53 inactivation, is the most common chromosomal anomaly in human cancers. To precisely map the deletion breakpoints is important to understanding the molecular mechanism of genomic rearrangement and may also be useful for clinical applications. However, current methods for determining the breakpoint are either of low resolution or require the isolation of relatively pure cancer cells, which can be difficult for clinical samples that are typically contaminated with various amounts of normal host cells. To overcome this hurdle, we have developed a novel approach, designated Primer Approximation Multiplex PCR (PAMP, for enriching breakpoint sequences followed by genomic tiling array hybridization to locate the breakpoints. In a series of proof-of-concept experiments, we were able to identify cancer-derived CDKN2A genomic breakpoints when more than 99.9% of wild type genome was present in a model system. This design can be scaled up with bioinformatics support and can be applied to validate other candidate cancer-associated loci that are revealed by other more systemic but lower throughput assays.

  5. 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

  6. 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...

  7. Genome Sequence of a Helicobacter pylori Strain Isolated from a Mexican Patient with Intestinal Gastric Cancer

    Science.gov (United States)

    Larios-Serrato, Violeta; Olguín-Ruiz, Gabriela Edith; Sánchez-Vallejo, Carlos Javier; Torres-López, Roberto Carlos; Avilés-Jiménez, Francisco; Camorlinga-Ponce, Margarita

    2014-01-01

    Helicobacter pylori strains are the major risk factor for gastric cancer. Strains vary in their content of disease-associated genes, so genome-wide analysis of cancer-isolated strains will help elucidate their pathogenesis and genetic diversity. We present the draft genome sequence of H. pylori isolated from a Mexican patient with intestinal gastric cancer. PMID:24459275

  8. Inferences from Genomic Models in Stratified Populations

    DEFF Research Database (Denmark)

    Janss, Luc; de los Campos, Gustavo; Sheehan, Nuala

    2012-01-01

    Unaccounted population stratification can lead to spurious associations in genome-wide association studies (GWAS) and in this context several methods have been proposed to deal with this problem. An alternative line of research uses whole-genome random regression (WGRR) models that fit all markers...... are unsatisfactory. Here we address this problem and describe a reparameterization of a WGRR model, based on an eigenvalue decomposition, for simultaneous inference of parameters and unobserved population structure. This allows estimation of genomic parameters with and without inclusion of marker......-derived eigenvectors that account for stratification. The method is illustrated with grain yield in wheat typed for 1279 genetic markers, and with height, HDL cholesterol and systolic blood pressure from the British 1958 cohort study typed for 1 million SNP genotypes. Both sets of data show signs of population...

  9. 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

  10. Molecular genetics and genomics progress in urothelial bladder cancer.

    Science.gov (United States)

    Netto, George J

    2013-11-01

    The clinical management of solid tumor patients has recently undergone a paradigm shift as the result of the accelerated advances in cancer genetics and genomics. Molecular diagnostics is now an integral part of routine clinical management in lung, colon, and breast cancer patients. In a disappointing contrast, molecular biomarkers remain largely excluded from current management algorithms of urologic malignancies. The need for new treatment alternatives and validated prognostic molecular biomarkers that can help clinicians identify patients in need of early aggressive management is pressing. Identifying robust predictive biomarkers that can stratify response to newly introduced targeted therapeutics is another crucially needed development. The following is a brief discussion of some promising candidate biomarkers that may soon become a part of clinical management of bladder cancers.

  11. 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.

  12. 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...

  13. Dynamics of genomic clones in breast cancer patient xenografts at single cell resolution

    Science.gov (United States)

    Eirew, Peter; Steif, Adi; Khattra, Jaswinder; Ha, Gavin; Yap, Damian; Farahani, Hossein; Gelmon, Karen; Chia, Stephen; Mar, Colin; Wan, Adrian; Laks, Emma; Biele, Justina; Shumansky, Karey; Rosner, Jamie; McPherson, Andrew; Nielsen, Cydney; Roth, Andrew J. L.; Lefebvre, Calvin; Bashashati, Ali; de Souza, Camila; Siu, Celia; Aniba, Radhouane; Brimhall, Jazmine; Oloumi, Arusha; Osako, Tomo; Bruna, Alejandra; Sandoval, Jose; Algara, Teresa; Greenwood, Wendy; Leung, Kaston; Cheng, Hongwei; Xue, Hui; Wang, Yuzhuo; Lin, Dong; Mungall, Andrew J.; Moore, Richard; Zhao, Yongjun; Lorette, Julie; Nguyen, Long; Huntsman, David; Eaves, Connie J.; Hansen, Carl; Marra, Marco A.; Caldas, Carlos; Shah, Sohrab P.; Aparicio, Samuel

    2016-01-01

    Human cancers, including breast cancers, are comprised of clones differing in mutation content. Clones evolve dynamically in space and time following principles of Darwinian evolution1,2, underpinning important emergent features such as drug resistance and metastasis3–7. Human breast cancer xenoengraftment is used as a means of capturing and studying tumour biology, and breast tumour xenografts are generally assumed to be reasonable models of the originating tumours8–10. However the consequences and reproducibility of engraftment and propagation on the genomic clonal architecture of tumours has not been systematically examined at single cell resolution. Here we show by both deep genome and single cell sequencing methods, the clonal dynamics of initial engraftment and subsequent serial propagation of primary and metastatic human breast cancers in immunodeficient mice. In all 15 cases examined, clonal selection on engraftment was observed in both primary and metastatic breast tumours, varying in degree from extreme selective engraftment of minor (<5% of starting population) clones to moderate, polyclonal engraftment. Furthermore, ongoing clonal dynamics during serial passaging is a feature of tumours experiencing modest initial selection. Through single cell sequencing, we show that major mutation clusters estimated from tumour population sequencing relate predictably to the most abundant clonal genotypes, even in clonally complex and rapidly evolving cases. Finally, we show that similar clonal expansion patterns can emerge in independent grafts of the same starting tumour population, indicating that genomic aberrations can be reproducible determinants of evolutionary trajectories. Our results show that measurement of genomically defined clonal population dynamics will be highly informative for functional studies utilizing patient-derived breast cancer xenoengraftment. PMID:25470049

  14. Integrated genomic and epigenomic analysis of breast cancer brain metastasis.

    Directory of Open Access Journals (Sweden)

    Bodour Salhia

    Full Text Available The brain is a common site of metastatic disease in patients with breast cancer, which has few therapeutic options and dismal outcomes. The purpose of our study was to identify common and rare events that underlie breast cancer brain metastasis. We performed deep genomic profiling, which integrated gene copy number, gene expression and DNA methylation datasets on a collection of breast brain metastases. We identified frequent large chromosomal gains in 1q, 5p, 8q, 11q, and 20q and frequent broad-level deletions involving 8p, 17p, 21p and Xq. Frequently amplified and overexpressed genes included ATAD2, BRAF, DERL1, DNMTRB and NEK2A. The ATM, CRYAB and HSPB2 genes were commonly deleted and underexpressed. Knowledge mining revealed enrichment in cell cycle and G2/M transition pathways, which contained AURKA, AURKB and FOXM1. Using the PAM50 breast cancer intrinsic classifier, Luminal B, Her2+/ER negative, and basal-like tumors were identified as the most commonly represented breast cancer subtypes in our brain metastasis cohort. While overall methylation levels were increased in breast cancer brain metastasis, basal-like brain metastases were associated with significantly lower levels of methylation. Integrating DNA methylation data with gene expression revealed defects in cell migration and adhesion due to hypermethylation and downregulation of PENK, EDN3, and ITGAM. Hypomethylation and upregulation of KRT8 likely affects adhesion and permeability. Genomic and epigenomic profiling of breast brain metastasis has provided insight into the somatic events underlying this disease, which have potential in forming the basis of future therapeutic strategies.

  15. Integrated genomic and epigenomic analysis of breast cancer brain metastasis.

    Science.gov (United States)

    Salhia, Bodour; Kiefer, Jeff; Ross, Julianna T D; Metapally, Raghu; Martinez, Rae Anne; Johnson, Kyle N; DiPerna, Danielle M; Paquette, Kimberly M; Jung, Sungwon; Nasser, Sara; Wallstrom, Garrick; Tembe, Waibhav; Baker, Angela; Carpten, John; Resau, Jim; Ryken, Timothy; Sibenaller, Zita; Petricoin, Emanuel F; Liotta, Lance A; Ramanathan, Ramesh K; Berens, Michael E; Tran, Nhan L

    2014-01-01

    The brain is a common site of metastatic disease in patients with breast cancer, which has few therapeutic options and dismal outcomes. The purpose of our study was to identify common and rare events that underlie breast cancer brain metastasis. We performed deep genomic profiling, which integrated gene copy number, gene expression and DNA methylation datasets on a collection of breast brain metastases. We identified frequent large chromosomal gains in 1q, 5p, 8q, 11q, and 20q and frequent broad-level deletions involving 8p, 17p, 21p and Xq. Frequently amplified and overexpressed genes included ATAD2, BRAF, DERL1, DNMTRB and NEK2A. The ATM, CRYAB and HSPB2 genes were commonly deleted and underexpressed. Knowledge mining revealed enrichment in cell cycle and G2/M transition pathways, which contained AURKA, AURKB and FOXM1. Using the PAM50 breast cancer intrinsic classifier, Luminal B, Her2+/ER negative, and basal-like tumors were identified as the most commonly represented breast cancer subtypes in our brain metastasis cohort. While overall methylation levels were increased in breast cancer brain metastasis, basal-like brain metastases were associated with significantly lower levels of methylation. Integrating DNA methylation data with gene expression revealed defects in cell migration and adhesion due to hypermethylation and downregulation of PENK, EDN3, and ITGAM. Hypomethylation and upregulation of KRT8 likely affects adhesion and permeability. Genomic and epigenomic profiling of breast brain metastasis has provided insight into the somatic events underlying this disease, which have potential in forming the basis of future therapeutic strategies.

  16. 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.

  17. 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.

  18. 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...

  19. 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.

  20. CGCI Investigators Reveal Comprehensive Landscape of Diffuse Large B-Cell Lymphoma (DLBCL) Genomes | Office of Cancer Genomics

    Science.gov (United States)

    Researchers from British Columbia Cancer Agency used whole genome sequencing to analyze 40 DLBCL cases and 13 cell lines in order to fill in the gaps of the complex landscape of DLBCL genomes. Their analysis, “Mutational and structural analysis of diffuse large B-cell lymphoma using whole genome sequencing,” was published online in Blood on May 22. The authors are Ryan Morin, Marco Marra, and colleagues.  

  1. 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.

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

    Science.gov (United States)

    Torres-Ruiz, Raul; Rodriguez-Perales, Sandra

    2015-09-14

    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. Pattern Analysis and Decision Support for Cancer through Clinico-Genomic Profiles

    Science.gov (United States)

    Exarchos, Themis P.; Giannakeas, Nikolaos; Goletsis, Yorgos; Papaloukas, Costas; Fotiadis, Dimitrios I.

    Advances in genome technology are playing a growing role in medicine and healthcare. With the development of new technologies and opportunities for large-scale analysis of the genome, genomic data have a clear impact on medicine. Cancer prognostics and therapeutics are among the first major test cases for genomic medicine, given that all types of cancer are related with genomic instability. In this paper we present a novel system for pattern analysis and decision support in cancer. The system integrates clinical data from electronic health records and genomic data. Pattern analysis and data mining methods are applied to these integrated data and the discovered knowledge is used for cancer decision support. Through this integration, conclusions can be drawn for early diagnosis, staging and cancer treatment.

  4. Modelling mutational landscapes of human cancers in vitro

    Science.gov (United States)

    Olivier, Magali; Weninger, Annette; Ardin, Maude; Huskova, Hana; Castells, Xavier; Vallée, Maxime P.; McKay, James; Nedelko, Tatiana; Muehlbauer, Karl-Rudolf; Marusawa, Hiroyuki; Alexander, John; Hazelwood, Lee; Byrnes, Graham; Hollstein, Monica; Zavadil, Jiri

    2014-03-01

    Experimental models that recapitulate mutational landscapes of human cancers are needed to decipher the rapidly expanding data on human somatic mutations. We demonstrate that mutation patterns in immortalised cell lines derived from primary murine embryonic fibroblasts (MEFs) exposed in vitro to carcinogens recapitulate key features of mutational signatures observed in human cancers. In experiments with several cancer-causing agents we obtained high genome-wide concordance between human tumour mutation data and in vitro data with respect to predominant substitution types, strand bias and sequence context. Moreover, we found signature mutations in well-studied human cancer driver genes. To explore endogenous mutagenesis, we used MEFs ectopically expressing activation-induced cytidine deaminase (AID) and observed an excess of AID signature mutations in immortalised cell lines compared to their non-transgenic counterparts. MEF immortalisation is thus a simple and powerful strategy for modelling cancer mutation landscapes that facilitates the interpretation of human tumour genome-wide sequencing data.

  5. Genome profiling of ERBB2-amplified breast cancers

    Directory of Open Access Journals (Sweden)

    Ayed Farhat

    2010-10-01

    Full Text Available Abstract Background 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. Methods 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. Results 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

  6. 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.

  7. 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.

  8. 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.

  9. 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.

  10. Kinetics Modeling of Cancer Immunology.

    Science.gov (United States)

    1986-05-09

    CANCER IMMUNOLOGY -1 DTICS ELECTED SEP 9 8 UNITED STATES NAVAL ACADEMY ANNAPOLIS, MARYLAND V ,1986 %,e docment ha le approved for public A." I and sale...1986 4. TITLE (and Subtitle) S. TYPE OF REPORT & PERIOD COVERED KINETICS MODELING OF CANCER IMMUNOLOGY Final: 1985/1986 6. PERFORMING ORG. REPORT...137 (1986) "Kinetics Modeling of Cancer Immunology " A Trident Scholar Project Report by Midn I/C Scott Helmers, Class of 1986 United States Naval

  11. 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.

  12. 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

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

    Science.gov (United States)

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

  14. [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.

  15. 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.

  16. 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.

  17. Radiation induced genome instability: multiscale modelling and data analysis

    Science.gov (United States)

    Andreev, Sergey; Eidelman, Yuri

    2012-07-01

    Genome instability (GI) is thought to be an important step in cancer induction and progression. Radiation induced GI is usually defined as genome alterations in the progeny of irradiated cells. The aim of this report is to demonstrate an opportunity for integrative analysis of radiation induced GI on the basis of multiscale modelling. Integrative, systems level modelling is necessary to assess different pathways resulting in GI in which a variety of genetic and epigenetic processes are involved. The multilevel modelling includes the Monte Carlo based simulation of several key processes involved in GI: DNA double strand breaks (DSBs) generation in cells initially irradiated as well as in descendants of irradiated cells, damage transmission through mitosis. Taking the cell-cycle-dependent generation of DNA/chromosome breakage into account ensures an advantage in estimating the contribution of different DNA damage response pathways to GI, as to nonhomologous vs homologous recombination repair mechanisms, the role of DSBs at telomeres or interstitial chromosomal sites, etc. The preliminary estimates show that both telomeric and non-telomeric DSB interactions are involved in delayed effects of radiation although differentially for different cell types. The computational experiments provide the data on the wide spectrum of GI endpoints (dicentrics, micronuclei, nonclonal translocations, chromatid exchanges, chromosome fragments) similar to those obtained experimentally for various cell lines under various experimental conditions. The modelling based analysis of experimental data demonstrates that radiation induced GI may be viewed as processes of delayed DSB induction/interaction/transmission being a key for quantification of GI. On the other hand, this conclusion is not sufficient to understand GI as a whole because factors of DNA non-damaging origin can also induce GI. Additionally, new data on induced pluripotent stem cells reveal that GI is acquired in normal mature

  18. 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.

  19. 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).

  20. Genome-wide association study of colorectal cancer in Hispanics

    Science.gov (United States)

    Schmit, Stephanie L.; Schumacher, Fredrick R.; Edlund, Christopher K.; Conti, David V.; Ihenacho, Ugonna; Wan, Peggy; Van Den Berg, David; Casey, Graham; Fortini, Barbara K.; Lenz, Heinz-Josef; Tusié-Luna, Teresa; Aguilar-Salinas, Carlos A.; Moreno-Macías, Hortensia; Huerta-Chagoya, Alicia; Ordóñez-Sánchez, María Luisa; Rodríguez-Guillén, Rosario; Cruz-Bautista, Ivette; Rodríguez-Torres, Maribel; Muñóz-Hernández, Linda Liliana; Arellano-Campos, Olimpia; Gómez, Donají; Alvirde, Ulices; González-Villalpando, Clicerio; González-Villalpando, María Elena; Le Marchand, Loic; Haiman, Christopher A.; Figueiredo, Jane C.

    2016-01-01

    Genome-wide association studies (GWAS) have identified 58 susceptibility alleles across 37 regions associated with the risk of colorectal cancer (CRC) with P < 5×10−8. Most studies have been conducted in non-Hispanic whites and East Asians; however, the generalizability of these findings and the potential for ethnic-specific risk variation in Hispanic and Latino (HL) individuals have been largely understudied. We describe the first GWAS of common genetic variation contributing to CRC risk in HL (1611 CRC cases and 4330 controls). We also examine known susceptibility alleles and implement imputation-based fine-mapping to identify potential ethnicity-specific association signals in known risk regions. We discovered 17 variants across 4 independent regions that merit further investigation due to suggestive CRC associations (P < 1×10−6) at 1p34.3 (rs7528276; Odds Ratio (OR) = 1.86 [95% confidence interval (CI): 1.47–2.36); P = 2.5×10−7], 2q23.3 (rs1367374; OR = 1.37 (95% CI: 1.21–1.55); P = 4.0×10−7), 14q24.2 (rs143046984; OR = 1.65 (95% CI: 1.36–2.01); P = 4.1×10−7) and 16q12.2 [rs142319636; OR = 1.69 (95% CI: 1.37–2.08); P=7.8×10−7]. Among the 57 previously published CRC susceptibility alleles with minor allele frequency ≥1%, 76.5% of SNPs had a consistent direction of effect and 19 (33.3%) were nominally statistically significant (P < 0.05). Further, rs185423955 and rs60892987 were identified as novel secondary susceptibility variants at 3q26.2 (P = 5.3×10–5) and 11q12.2 (P = 6.8×10−5), respectively. Our findings demonstrate the importance of fine mapping in HL. These results are informative for variant prioritization in functional studies and future risk prediction modeling in minority populations. PMID:27207650

  1. 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.

  2. 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.

  3. 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.

  4. 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.

  5. 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.

  6. 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.

  7. 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.

  8. 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.

  9. 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.

  10. 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.

  11. 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.

  12. Correction for Measurement Error from Genotyping-by-Sequencing in Genomic Variance and Genomic Prediction Models

    DEFF Research Database (Denmark)

    Ashraf, Bilal; Janss, Luc; Jensen, Just

    . In the current work we show how the correction for measurement error in GBSeq can also be applied in whole genome genomic variance and genomic prediction models. Bayesian whole-genome random regression models are proposed to allow implementation of large-scale SNP-based models with a per-SNP correction......Genotyping-by-sequencing (GBSeq) is becoming a cost-effective genotyping platform for species without available SNP arrays. GBSeq considers to sequence short reads from restriction sites covering a limited part of the genome (e.g., 5-10%) with low sequencing depth per individual (e.g., 5-10X per...... sample). The GBSeq data can be used directly in genomic models in the form of individual SNP allele-frequency estimates (e.g., reference reads/total reads per polymorphic site per individual), but is subject to measurement error due to the low sequencing depth per individual. Due to technical reasons...

  13. The Broad Institute: Screening for Dependencies in Cancer Cell Lines Using Small Molecules | Office of Cancer Genomics

    Science.gov (United States)

    Using cancer cell-line profiling, we established an ongoing resource to identify, as comprehensively as possible, the drug-targetable dependencies that specific genomic alterations impart on human cancers. We measured the sensitivity of hundreds of genetically characterized cancer cell lines to hundreds of small-molecule probes and drugs that have highly selective interactions with their targets, and that collectively modulate many distinct nodes in cancer cell circuitry.

  14. 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 ...

  15. 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

  16. 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...

  17. 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......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...

  18. Mouse Models of Gastric Cancer

    Directory of Open Access Journals (Sweden)

    Timothy C. Wang

    2013-01-01

    Full Text Available Animal models have greatly enriched our understanding of the molecular mechanisms of numerous types of cancers. Gastric cancer is one of the most common cancers worldwide, with a poor prognosis and high incidence of drug-resistance. However, most inbred strains of mice have proven resistant to gastric carcinogenesis. To establish useful models which mimic human gastric cancer phenotypes, investigators have utilized animals infected with Helicobacter species and treated with carcinogens. In addition, by exploiting genetic engineering, a variety of transgenic and knockout mouse models of gastric cancer have emerged, such as INS-GAS mice and TFF1 knockout mice. Investigators have used the combination of carcinogens and gene alteration to accelerate gastric cancer development, but rarely do mouse models show an aggressive and metastatic gastric cancer phenotype that could be relevant to preclinical studies, which may require more specific targeting of gastric progenitor cells. Here, we review current gastric carcinogenesis mouse models and provide our future perspectives on this field.

  19. 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.

  20. 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.

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

    DEFF Research Database (Denmark)

    Have, Christian Theil; Mørk, Søren

    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...... 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...... as output. The model can be used to obtain the most probable genome annotation based on a combination of i: a gene finder score of each gene candidate and ii: the sequence of the reading frames of gene candidates through a genome. The model --- as well as a higher order variant --- is developed and tested...

  2. The genomic landscape of response to EGFR blockade in colorectal cancer.

    Science.gov (United States)

    Bertotti, Andrea; Papp, Eniko; Jones, Siân; Adleff, Vilmos; Anagnostou, Valsamo; Lupo, Barbara; Sausen, Mark; Phallen, Jillian; Hruban, Carolyn A; Tokheim, Collin; Niknafs, Noushin; Nesselbush, Monica; Lytle, Karli; Sassi, Francesco; Cottino, Francesca; Migliardi, Giorgia; Zanella, Eugenia R; Ribero, Dario; Russolillo, Nadia; Mellano, Alfredo; Muratore, Andrea; Paraluppi, Gianluca; Salizzoni, Mauro; Marsoni, Silvia; Kragh, Michael; Lantto, Johan; Cassingena, Andrea; Li, Qing Kay; Karchin, Rachel; Scharpf, Robert; Sartore-Bianchi, Andrea; Siena, Salvatore; Diaz, Luis A; Trusolino, Livio; Velculescu, Victor E

    2015-10-08

    Colorectal cancer is the third most common cancer worldwide, with 1.2 million patients diagnosed annually. In late-stage colorectal cancer, the most commonly used targeted therapies are the monoclonal antibodies cetuximab and panitumumab, which prevent epidermal growth factor receptor (EGFR) activation. Recent studies have identified alterations in KRAS and other genes as likely mechanisms of primary and secondary resistance to anti-EGFR antibody therapy. Despite these efforts, additional mechanisms of resistance to EGFR blockade are thought to be present in colorectal cancer and little is known about determinants of sensitivity to this therapy. To examine the effect of somatic genetic changes in colorectal cancer on response to anti-EGFR antibody therapy, here we perform complete exome sequence and copy number analyses of 129 patient-derived tumour grafts and targeted genomic analyses of 55 patient tumours, all of which were KRAS wild-type. We analysed the response of tumours to anti-EGFR antibody blockade in tumour graft models and in clinical settings and functionally linked therapeutic responses to mutational data. In addition to previously identified genes, we detected mutations in ERBB2, EGFR, FGFR1, PDGFRA, and MAP2K1 as potential mechanisms of primary resistance to this therapy. Novel alterations in the ectodomain of EGFR were identified in patients with acquired resistance to EGFR blockade. Amplifications and sequence changes in the tyrosine kinase receptor adaptor gene IRS2 were identified in tumours with increased sensitivity to anti-EGFR therapy. Therapeutic resistance to EGFR blockade could be overcome in tumour graft models through combinatorial therapies targeting actionable genes. These analyses provide a systematic approach to evaluating response to targeted therapies in human cancer, highlight new mechanisms of responsiveness to anti-EGFR therapies, and delineate new avenues for intervention in managing colorectal cancer.

  3. Prediction of cancer cell sensitivity to natural products based on genomic and chemical properties

    Directory of Open Access Journals (Sweden)

    Zhenyu Yue

    2015-11-01

    Full Text Available Natural products play a significant role in cancer chemotherapy. They are likely to provide many lead structures, which can be used as templates for the construction of novel drugs with enhanced antitumor activity. Traditional research approaches studied structure-activity relationship of natural products and obtained key structural properties, such as chemical bond or group, with the purpose of ascertaining their effect on a single cell line or a single tissue type. Here, for the first time, we develop a machine learning method to comprehensively predict natural products responses against a panel of cancer cell lines based on both the gene expression and the chemical properties of natural products. The results on two datasets, training set and independent test set, show that this proposed method yields significantly better prediction accuracy. In addition, we also demonstrate the predictive power of our proposed method by modeling the cancer cell sensitivity to two natural products, Curcumin and Resveratrol, which indicate that our method can effectively predict the response of cancer cell lines to these two natural products. Taken together, the method will facilitate the identification of natural products as cancer therapies and the development of precision medicine by linking the features of patient genomes to natural product sensitivity.

  4. Prediction of cancer cell sensitivity to natural products based on genomic and chemical properties.

    Science.gov (United States)

    Yue, Zhenyu; Zhang, Wenna; Lu, Yongming; Yang, Qiaoyue; Ding, Qiuying; Xia, Junfeng; Chen, Yan

    2015-01-01

    Natural products play a significant role in cancer chemotherapy. They are likely to provide many lead structures, which can be used as templates for the construction of novel drugs with enhanced antitumor activity. Traditional research approaches studied structure-activity relationship of natural products and obtained key structural properties, such as chemical bond or group, with the purpose of ascertaining their effect on a single cell line or a single tissue type. Here, for the first time, we develop a machine learning method to comprehensively predict natural products responses against a panel of cancer cell lines based on both the gene expression and the chemical properties of natural products. The results on two datasets, training set and independent test set, show that this proposed method yields significantly better prediction accuracy. In addition, we also demonstrate the predictive power of our proposed method by modeling the cancer cell sensitivity to two natural products, Curcumin and Resveratrol, which indicate that our method can effectively predict the response of cancer cell lines to these two natural products. Taken together, the method will facilitate the identification of natural products as cancer therapies and the development of precision medicine by linking the features of patient genomes to natural product sensitivity.

  5. Genetic basis of kidney cancer: role of genomics for the development of disease-based therapeutics.

    Science.gov (United States)

    Linehan, W Marston

    2012-11-01

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

  6. Identification of cancer risk lncRNAs and cancer risk pathways regulated by cancer risk lncRNAs based on genome sequencing data in human cancers.

    Science.gov (United States)

    Li, Yiran; Li, Wan; Liang, Binhua; Li, Liansheng; Wang, Li; Huang, Hao; Guo, Shanshan; Wang, Yahui; He, Yuehan; Chen, Lina; He, Weiming

    2016-12-19

    Cancer is a group of diseases involving abnormal cell growth with the potential to invade or spread to other parts of the body. The complexity of cancer can be reduced to a small number of underlying principles like cancer hallmarks which could govern the transformation of normal cells to cancer. Besides, the growth and metastasis of cancer often relate to combined effects of long non-coding RNAs (lncRNAs). Here, we performed comprehensive analysis for lncRNA expression profiles and clinical data of six types of human cancer patients from The Cancer Genome Atlas (TCGA), and identified six risk pathways and twenty three lncRNAs. In addition, twenty three cancer risk lncRNAs which were closely related to the occurrence or development of cancer had a good classification performance for samples of testing datasets of six cancer datasets. More important, these lncRNAs were able to separate samples in the entire cancer dataset into high-risk group and low-risk group with significantly different overall survival (OS), which was further validated in ten validation datasets. In our study, the robust and effective cancer biomarkers were obtained from cancer datasets which had information of normal-tumor samples. Overall, our research can provide a new perspective for the further study of clinical diagnosis and treatment of cancer.

  7. 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.

  8. Dog models of naturally occurring cancer.

    Science.gov (United States)

    Rowell, Jennie L; McCarthy, Donna O; Alvarez, Carlos E

    2011-07-01

    Studies using dogs provide an ideal solution to the gap in animal models for natural disease and translational medicine. This is evidenced by approximately 400 inherited disorders being characterized in domesticated dogs, most of which are relevant to humans. There are several hundred isolated populations of dogs (breeds) and each has a vastly reduced genetic variation compared with humans; this simplifies disease mapping and pharmacogenomics. Dogs age five- to eight-fold faster than do humans, share environments with their owners, are usually kept until old age and receive a high level of health care. Farseeing investigators recognized this potential and, over the past decade, have developed the necessary tools and infrastructure to utilize this powerful model of human disease, including the sequencing of the dog genome in 2005. Here, we review the nascent convergence of genetic and translational canine models of spontaneous disease, focusing on cancer.

  9. 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

  10. 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

  11. Cross-cancer genome-wide analysis of lung, ovary, breast, prostate, and colorectal cancer reveals novel pleiotropic associations

    NARCIS (Netherlands)

    Fehringer, G. (Gordon); P. Kraft (Peter); P.D.P. Pharoah (Paul); R. Eeles (Rosalind); Chatterjee, N. (Nilanjan); F.R. Schumacher (Fredrick R); J.M. Schildkraut (Joellen); S. Lindstrom (Stephen); P. Brennan (Paul); H. Bickeböller (Heike); R. Houlston (Richard); M.T. Landi (Maria Teresa); N.E. Caporaso (Neil); Risch, A. (Angela); A.A. Al Olama (Ali Amin); S.I. Berndt (Sonja); Giovannucci, E.L. (Edward L.); H. Grönberg (Henrik); Z. Kote-Jarai; Ma, J. (Jing); K.R. Muir (K.); M.J. Stampfer (Meir J.); Stevens, V.L. (Victoria L.); F. Wiklund (Fredrik); W.C. Willett (Walter C.); E.L. Goode (Ellen); Permuth, J.B. (Jennifer B.); H. Risch (Harvey); Reid, B.M. (Brett M.); Bezieau, S. (Stephane); H. Brenner (Hermann); Chan, A.T. (Andrew T.); J. Chang-Claude (Jenny); T.J. Hudson (Thomas); Kocarnik, J.K. (Jonathan K.); P. Newcomb (Polly); Schoen, R.E. (Robert E.); Slattery, M.L. (Martha L.); White, E. (Emily); M.A. Adank (Muriel); H. Ahsan (Habibul); K. Aittomäki (Kristiina); Baglietto, L. (Laura); Blomquist, C. (Carl); F. Canzian (Federico); K. Czene (Kamila); I. dos Santos Silva (Isabel); Eliassen, A.H. (A. Heather); J.D. Figueroa (Jonine); D. Flesch-Janys (Dieter); O. Fletcher (Olivia); M. García-Closas (Montserrat); M.M. Gaudet (Mia); Johnson, N. (Nichola); P. Hall (Per); A. Hazra (Aditi); R. Hein (Rebecca); Hofman, A. (Albert); J.L. Hopper (John); A. Irwanto (Astrid); M. Johansson (Mattias); R. Kaaks (Rudolf); M.G. Kibriya (Muhammad); P. Lichtner (Peter); J. Liu (Jianjun); E. Lund (Eiliv); Makalic, E. (Enes); A. Meindl (Alfons); B. Müller-Myhsok (B.); Muranen, T.A. (Taru A.); H. Nevanlinna (Heli); P.H.M. Peeters; J. Peto (Julian); R. Prentice (Ross); N. Rahman (Nazneen); M.-J. Sanchez (Maria-Jose); D.F. Schmidt (Daniel); R.K. Schmutzler (Rita); M.C. Southey (Melissa); Tamimi, R. (Rulla); S.P.L. Travis (Simon); C. Turnbull (Clare); Uitterlinden, A.G. (Andre G.); Z. Wang (Zhaoming); A.S. Whittemore (Alice); X.R. Yang (Xiaohong); W. Zheng (Wei); D. Buchanan (Daniel); G. Casey (Graham); G. Conti (Giario); C.K. Edlund (Christopher); S. Gallinger (Steve); R. Haile (Robert); M. Jenkins (Mark); Marchand, L. (Loïcle); Li, L. (Li); N.M. Lindor (Noralane); Schmit, S.L. (Stephanie L.); S.N. Thibodeau (Stephen); M.O. Woods (Michael); T. Rafnar (Thorunn); J. Gudmundsson (Julius); S.N. Stacey (Simon); Stefansson, K. (Kari); P. Sulem (Patrick); Chen, Y.A. (Y. Ann); J.P. Tyrer (Jonathan); Christiani, D.C. (David C.); Wei, Y. (Yongyue); H. Shen (Hongbing); Z. Hu (Zhibin); X.-O. Shu (Xiao-Ou); Shiraishi, K. (Kouya); A. Takahashi (Atsushi); Y. Bossé (Yohan); M. Obeidat; D.C. Nickle (David C.); W. Timens (Wim); M. Freedman (Matthew); Li, Q. (Qiyuan); D. Seminara (Daniela); S.J. Chanock (Stephen); Gong, J. (Jian); U. Peters (Ulrike); S.B. Gruber (Stephen); Amos, C.I. (Christopher I.); T.A. Sellers (Thomas A.); D.F. Easton (Douglas F.); D. Hunter (David); C.A. Haiman (Christopher A.); B.E. Henderson (Brian); R.J. Hung (Rayjean)

    2016-01-01

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

  12. Cross-cancer genome-wide analysis of lung, ovary, breast, prostate, and colorectal cancer reveals novel pleiotropic associations

    NARCIS (Netherlands)

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

    2016-01-01

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

  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. 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.

  15. 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.

  16. 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

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

    Directory of Open Access Journals (Sweden)

    Shengda Lin

    2016-01-01

    Full Text Available 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.

  18. SIGMA2: A system for the integrative genomic multi-dimensional analysis of cancer genomes, epigenomes, and transcriptomes

    Directory of Open Access Journals (Sweden)

    MacAulay Calum

    2008-10-01

    Full Text Available Abstract Background High throughput microarray technologies have afforded the investigation of genomes, epigenomes, and transcriptomes at unprecedented resolution. However, software packages to handle, analyze, and visualize data from these multiple 'omics disciplines have not been adequately developed. Results Here, we present SIGMA2, a system for the integrative genomic multi-dimensional analysis of cancer genomes, epigenomes, and transcriptomes. Multi-dimensional datasets can be simultaneously visualized and analyzed with respect to each dimension, allowing combinatorial integration of the different assays belonging to the different 'omics. Conclusion The identification of genes altered at multiple levels such as copy number, loss of heterozygosity (LOH, DNA methylation and the detection of consequential changes in gene expression can be concertedly performed, establishing SIGMA2 as a novel tool to facilitate the high throughput systems biology analysis of cancer.

  19. 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.

  20. 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.

  1. A genome assembly-integrated dog 1 Mb BAC microarray: a cytogenetic resource for canine cancer studies and comparative genomic analysis.

    Science.gov (United States)

    Thomas, R; Duke, S E; Karlsson, E K; Evans, A; Ellis, P; Lindblad-Toh, K; Langford, C F; Breen, M

    2008-01-01

    Molecular cytogenetic studies have been instrumental in defining the nature of numerical and structural chromosome changes in human cancers, but their significance remains to be fully understood. The emergence of high quality genome assemblies for several model organisms provides exciting opportunities to develop novel genome-integrated molecular cytogenetic resources that now permit a comparative approach to evaluating the relevance of tumor-associated chromosome aberrations, both within and between species. We have used the dog genome sequence assembly to identify a framework panel of 2,097 bacterial artificial chromosome (BAC) clones, selected at intervals of approximately one megabase. Each clone has been evaluated by multicolor fluorescence in situ hybridization (FISH) to confirm its unique cytogenetic location in concordance with its reported position in the genome assembly, providing new information on the organization of the dog genome. This panel of BAC clones also represents a powerful cytogenetic resource with numerous potential applications. We have used the clone set to develop a genome-wide microarray for comparative genomic hybridization (aCGH) analysis, and demonstrate its application in detection of tumor-associated DNA copy number aberrations (CNAs) including single copy deletions and amplifications, regional aneuploidy and whole chromosome aneuploidy. We also show how individual clones selected from the BAC panel can be used as FISH probes in direct evaluation of tumor karyotypes, to verify and explore CNAs detected using aCGH analysis. This cytogenetically validated, genome integrated BAC clone panel has enormous potential for aiding gene discovery through a comparative approach to molecular oncology.

  2. 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....

  3. Delineation of Methyl-DNA Binding Protein Interactions in the Prostate Cancer Genome (PC110091)

    Science.gov (United States)

    2014-03-01

    DNA Binding Protein Interactions in the Prostate Cancer Genome (PC110091) PRINCIPAL INVESTIGATOR: Roderick T Hori, PhD...13. SUPPLEMENTARY NOTES Prostate Cancer, Methylated DNA, Methyl- CpG Binding Domain, Chromatin Immunoprecipitation 14. ABSTRACT The purpose...of this study is to generate a genome-wide association profile of Methyl- CpG Domain-containing (MBD) proteins, such as MeCP2, MBD1, MBD2 and MBD4, in

  4. Whole-genome sequencing analysis of phenotypic heterogeneity and anticipation in Li-Fraumeni cancer predisposition syndrome.

    Science.gov (United States)

    Ariffin, Hany; Hainaut, Pierre; Puzio-Kuter, Anna; Choong, Soo Sin; Chan, Adelyne Sue Li; Tolkunov, Denis; Rajagopal, Gunaretnam; Kang, Wenfeng; Lim, Leon Li Wen; Krishnan, Shekhar; Chen, Kok-Siong; Achatz, Maria Isabel; Karsa, Mawar; Shamsani, Jannah; Levine, Arnold J; Chan, Chang S

    2014-10-28

    The Li-Fraumeni syndrome (LFS) and its variant form (LFL) is a familial predisposition to multiple forms of childhood, adolescent, and adult cancers associated with germ-line mutation in the TP53 tumor suppressor gene. Individual disparities in tumor patterns are compounded by acceleration of cancer onset with successive generations. It has been suggested that this apparent anticipation pattern may result from germ-line genomic instability in TP53 mutation carriers, causing increased DNA copy-number variations (CNVs) with successive generations. To address the genetic basis of phenotypic disparities of LFS/LFL, we performed whole-genome sequencing (WGS) of 13 subjects from two generations of an LFS kindred. Neither de novo CNV nor significant difference in total CNV was detected in relation with successive generations or with age at cancer onset. These observations were consistent with an experimental mouse model system showing that trp53 deficiency in the germ line of father or mother did not increase CNV occurrence in the offspring. On the other hand, individual records on 1,771 TP53 mutation carriers from 294 pedigrees were compiled to assess genetic anticipation patterns (International Agency for Research on Cancer TP53 database). No strictly defined anticipation pattern was observed. Rather, in multigeneration families, cancer onset was delayed in older compared with recent generations. These observations support an alternative model for apparent anticipation in which rare variants from noncarrier parents may attenuate constitutive resistance to tumorigenesis in the offspring of TP53 mutation carriers with late cancer onset.

  5. 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.

  6. Whole-genome sequencing and comprehensive molecular profiling identify new driver mutations in gastric cancer

    NARCIS (Netherlands)

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

    2014-01-01

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

  7. TALEN-mediated somatic mutagenesis in murine models of cancer.

    Science.gov (United States)

    Zhang, Shuyuan; Li, Lin; Kendrick, Sara L; Gerard, Robert D; Zhu, Hao

    2014-09-15

    Cancer genome sequencing has identified numerous somatic mutations whose biologic relevance is uncertain. In this study, we used genome-editing tools to create and analyze targeted somatic mutations in murine models of liver cancer. Transcription activator-like effector nucleases (TALEN) were designed against β-catenin (Ctnnb1) and adenomatous polyposis coli (Apc), two commonly mutated genes in hepatocellular carcinoma (HCC), to generate isogenic HCC cell lines. Both mutant cell lines exhibited evidence of Wnt pathway dysregulation. We asked whether these TALENs could create targeted somatic mutations after hydrodynamic transfection into mouse liver. TALENs targeting β-catenin promoted endogenous HCC carrying the intended gain-of-function mutations. However, TALENs targeting Apc were not as efficient in inducing in vivo homozygous loss-of-function mutations. We hypothesized that hepatocyte polyploidy might be protective against TALEN-induced loss of heterozygosity, and indeed Apc gene editing was less efficient in tetraploid than in diploid hepatocytes. To increase efficiency, we administered adenoviral Apc TALENs and found that we could achieve a higher mutagenesis rate in vivo. Our results demonstrate that genome-editing tools can enable the in vivo study of cancer genes and faithfully recapitulate the mosaic nature of mutagenesis in mouse cancer models. Cancer Res; 74(18); 5311-21. ©2014 AACR.

  8. 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

  9. 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.

  10. 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.

  11. 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...

  12. 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...

  13. 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 de...

  14. 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 of h...

  15. 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.

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

    Science.gov (United States)

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

    2015-01-01

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

  17. 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.

  18. 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

  19. 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

  20. 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.

  1. Gender-Associated Genomic Differences in Colorectal Cancer: Clinical Insight from Feminization of Male Cancer Cells

    Directory of Open Access Journals (Sweden)

    Rola H. Ali

    2014-09-01

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

  2. Gender-associated genomic differences in colorectal cancer: clinical insight from feminization of male cancer cells.

    Science.gov (United States)

    Ali, Rola H; Marafie, Makia J; Bitar, Milad S; Al-Dousari, Fahad; Ismael, Samar; Bin Haider, Hussain; Al-Ali, Waleed; Jacob, Sindhu P; Al-Mulla, Fahd

    2014-09-29

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

  3. Building a data sharing model for global genomic research.

    Science.gov (United States)

    Kosseim, Patricia; Dove, Edward S; Baggaley, Carman; Meslin, Eric M; Cate, Fred H; Kaye, Jane; Harris, Jennifer R; Knoppers, Bartha M

    2014-08-11

    Data sharing models designed to facilitate global business provide insights for improving transborder genomic data sharing. We argue that a flexible, externally endorsed, multilateral arrangement, combined with an objective third-party assurance mechanism, can effectively balance privacy with the need to share genomic data globally.

  4. 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

  5. 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,

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

    Directory of Open Access Journals (Sweden)

    Fang Liu

    2014-01-01

    Full Text Available 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 associations for colorectal cancer under biomedical big data environment. The proposed method is engineered with multiple technologies, including extracting clinical concepts using the unified medical language system (UMLS, extracting genes through the literature mining, and mining clinic-genomic associations through statistical analysis. We applied this method to datasets extracted from both gene expression omnibus (GEO and genetic association database (GAD. A total of 23517 clinic-genomic associations between 139 clinical concepts and 7914 genes were obtained, of which 3474 associations between 31 clinical concepts and 1689 genes were identified as highly reliable ones. Evaluation and interpretation were performed using UMLS, KEGG, and Gephi, and potential new discoveries were explored. The proposed method is effective in mining valuable knowledge from available biomedical big data and achieves a good performance in bridging clinical data with genomic data for colorectal cancer.

  7. A Genome-wide Breast Cancer Scan in African Americans

    Science.gov (United States)

    2012-06-01

    of Experimental Therapy and Molecular Pathology and Division of Epidemiology, Netherlands Cancer Institute–Antoni van Leeuwenhoek Hospital, Amsterdam...Centre, University of Oxford, Oxford, UK. 81Family Cancer Clinic, Netherlands Cancer Institut–Antoni van Leeuwenhoek Hospital, Amsterdam, The Netherlands

  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. Use of genome-scale microbial models for metabolic engineering

    DEFF Research Database (Denmark)

    Patil, Kiran Raosaheb; Åkesson, M.; Nielsen, Jens

    2004-01-01

    network structures. The major challenge for metabolic engineering in the post-genomic era is to broaden its design methodologies to incorporate genome-scale biological data. Genome-scale stoichiometric models of microorganisms represent a first step in this direction.......Metabolic engineering serves as an integrated approach to design new cell factories by providing rational design procedures and valuable mathematical and experimental tools. Mathematical models have an important role for phenotypic analysis, but can also be used for the design of optimal metabolic...

  10. 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...

  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. 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.

  13. Genomics and epigenomics: new promises of personalized medicine for cancer patients.

    Science.gov (United States)

    Schweiger, Michal-Ruth; Barmeyer, Christian; Timmermann, Bernd

    2013-09-01

    Recent years have brought about a marked extension of our understanding of the somatic basis of cancer. Parallel to the large-scale investigation of diverse tumor genomes the knowledge arose that cancer pathologies are most often not restricted to single genomic events. In contrast, a large number of different alterations in the genomes and epigenomes come together and promote the malignant transformation. The combination of mutations, structural variations and epigenetic alterations differs between each tumor, making individual diagnosis and treatment strategies necessary. This view is summarized in the new discipline of personalized medicine. To satisfy the ideas of this approach each tumor needs to be fully characterized and individual diagnostic and therapeutic strategies designed. Here, we will discuss the power of high-throughput sequencing technologies for genomic and epigenomic analyses. We will provide insight into the current status and how these technologies can be transferred to routine clinical usage.

  14. Origins of DNA Replication and Amplification in the Breast Cancer Genome

    Science.gov (United States)

    2011-09-01

    identified 53,914 origins in the MCF-7 genome, with a median width of 1.5 kb using the methodology as follows: We used BEDTools ( Quinlan et al...are collaborating with David Gilbert (University of Florida – Tallahassee) to determine the replication foci higher order structure in the nucleus...Cancer Cell 10: 515-527. Quinlan AR, Hall IM. (2010) BEDTools: a flexible suite of utilities for comparing genomic features. Bioinformatics. 26: 841-2

  15. 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.

  16. 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.

  17. Identifying master regulators of cancer and their downstream targets by integrating genomic and epigenomic features.

    Science.gov (United States)

    Gevaert, Olivier; Plevritis, Sylvia

    2013-01-01

    Vast amounts of molecular data characterizing the genome, epigenome and transcriptome are becoming available for a variety of cancers. The current challenge is to integrate these diverse layers of molecular biology information to create a more comprehensive view of key biological processes underlying cancer. We developed a biocomputational algorithm that integrates copy number, DNA methylation, and gene expression data to study master regulators of cancer and identify their targets. Our algorithm starts by generating a list of candidate driver genes based on the rationale that genes that are driven by multiple genomic events in a subset of samples are unlikely to be randomly deregulated. We then select the master regulators from the candidate driver and identify their targets by inferring the underlying regulatory network of gene expression. We applied our biocomputational algorithm to identify master regulators and their targets in glioblastoma multiforme (GBM) and serous ovarian cancer. Our results suggest that the expression of candidate drivers is more likely to be influenced by copy number variations than DNA methylation. Next, we selected the master regulators and identified their downstream targets using module networks analysis. As a proof-of-concept, we show that the GBM and ovarian cancer module networks recapitulate known processes in these cancers. In addition, we identify master regulators that have not been previously reported and suggest their likely role. In summary, focusing on genes whose expression can be explained by their genomic and epigenomic aberrations is a promising strategy to identify master regulators of cancer.

  18. Exploiting linkage disequilibrium in statistical modelling in quantitative genomics

    DEFF Research Database (Denmark)

    Wang, Lei

    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...... 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 improves...

  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. 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

  1. 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.

  2. 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.

  3. 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.

  4. 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

  5. Complete Genome Sequence of Helicobacter pylori Strain 29CaP Isolated from a Mexican Patient with Gastric Cancer

    Science.gov (United States)

    Mucito-Varela, Eduardo; Castillo-Rojas, Gonzalo; Cevallos, Miguel A.; Lozano, Luis; Merino, Enrique; López-Leal, Gamaliel

    2016-01-01

    Helicobacter pylori infection is a risk factor for the development of gastric cancer and other gastroduodenal diseases. We report here the complete genome sequence of H. pylori strain 29CaP, isolated from a Mexican patient with gastric cancer. The genomic data analysis revealed a cag-negative H. pylori strain that contains a prophage sequence. PMID:26769924

  6. Cross-Cancer Genome-Wide Analysis of Lung, Ovary, Breast, Prostate, and Colorectal Cancer Reveals Novel Pleiotropic Associations.

    Science.gov (United States)

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

    2016-09-01

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

  7. Drosophila models for cancer research.

    Science.gov (United States)

    Vidal, Marcos; Cagan, Ross L

    2006-02-01

    Drosophila is a model system for cancer research. Investigation with fruit flies has facilitated a number of important recent discoveries in the field: the hippo signaling pathway, which coordinates cell proliferation and death to achieve normal tissue size; 'social' behaviors of cells, including cell competition and apoptosis-induced compensatory proliferation, that help ensure normal tissue size; and a growing understanding of how oncogenes and tumor suppressors cooperate to achieve tumor growth and metastasis in situ. In the future, Drosophila models can be extended beyond basic research in the search for human therapeutics.

  8. Genome-wide transcript profiling reveals novel breast cancer-associated intronic sense RNAs.

    Science.gov (United States)

    Kim, Sang Woo; Fishilevich, Elane; Arango-Argoty, Gustavo; Lin, Yuefeng; Liu, Guodong; Li, Zhihua; Monaghan, A Paula; Nichols, Mark; John, Bino

    2015-01-01

    Non-coding RNAs (ncRNAs) play major roles in development and cancer progression. To identify novel ncRNAs that may identify key pathways in breast cancer development, we performed high-throughput transcript profiling of tumor and normal matched-pair tissue samples. Initial transcriptome profiling using high-density genome-wide tiling arrays revealed changes in over 200 novel candidate genomic regions that map to intronic regions. Sixteen genomic loci were identified that map to the long introns of five key protein-coding genes, CRIM1, EPAS1, ZEB2, RBMS1, and RFX2. Consistent with the known role of the tumor suppressor ZEB2 in the cancer-associated epithelial to mesenchymal transition (EMT), in situ hybridization reveals that the intronic regions deriving from ZEB2 as well as those from RFX2 and EPAS1 are down-regulated in cells of epithelial morphology, suggesting that these regions may be important for maintaining normal epithelial cell morphology. Paired-end deep sequencing analysis reveals a large number of distinct genomic clusters with no coding potential within the introns of these genes. These novel transcripts are only transcribed from the coding strand. A comprehensive search for breast cancer associated genes reveals enrichment for transcribed intronic regions from these loci, pointing to an underappreciated role of introns or mechanisms relating to their biology in EMT and breast cancer.

  9. Genome-wide transcript profiling reveals novel breast cancer-associated intronic sense RNAs.

    Directory of Open Access Journals (Sweden)

    Sang Woo Kim

    Full Text Available Non-coding RNAs (ncRNAs play major roles in development and cancer progression. To identify novel ncRNAs that may identify key pathways in breast cancer development, we performed high-throughput transcript profiling of tumor and normal matched-pair tissue samples. Initial transcriptome profiling using high-density genome-wide tiling arrays revealed changes in over 200 novel candidate genomic regions that map to intronic regions. Sixteen genomic loci were identified that map to the long introns of five key protein-coding genes, CRIM1, EPAS1, ZEB2, RBMS1, and RFX2. Consistent with the known role of the tumor suppressor ZEB2 in the cancer-associated epithelial to mesenchymal transition (EMT, in situ hybridization reveals that the intronic regions deriving from ZEB2 as well as those from RFX2 and EPAS1 are down-regulated in cells of epithelial morphology, suggesting that these regions may be important for maintaining normal epithelial cell morphology. Paired-end deep sequencing analysis reveals a large number of distinct genomic clusters with no coding potential within the introns of these genes. These novel transcripts are only transcribed from the coding strand. A comprehensive search for breast cancer associated genes reveals enrichment for transcribed intronic regions from these loci, pointing to an underappreciated role of introns or mechanisms relating to their biology in EMT and breast cancer.

  10. 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.

  11. Tumor Genomic Profiling in Breast Cancer Patients Using Targeted Massively Parallel Sequencing

    Science.gov (United States)

    2015-04-30

    McDonald S, Watson M, Dooling DJ, Ota D, Chang LW, Bose R, Ley TJ, 18 Piwnica-Worms D, Stuart JM, Wilson RK, Mardis ER. Whole- genome analysis informs...AWARD NUMBER: W81XWH-13-1-0032 TITLE: Tumor Genomic Profiling in Breast Cancer Patients Using Targeted Massively Parallel Sequencing PRINCIPAL...THE ABOVE ADDRESS. 1. REPORT DATE I 2. REPORT TYPE 3. DATES COVERED 04-30-2015 Annual 01-01-2014 to 04-30-2015 4. TITLE AND SUBTITLE Tumor genomic

  12. Integrated proteo-genomic approach for early diagnosis and prognosis of cancer.

    Science.gov (United States)

    Shukla, Hem D; Mahmood, Javed; Vujaskovic, Zeljko

    2015-12-01

    Cancer is the leading cause of mortality among men and women worldwide. Despite the availability of numerous diagnostic techniques for various cancers, the overall survival rate remains low and the majority of patients die due to late diagnosis and advanced stage of the disease. Diagnosing and treating cancer at its early stages ideally during the precancerous phase could significantly increase survival rate with the possibility of cure and prolong survival. Cancer is a genetic disease and it is illicitly activated by the acquisition of somatic DNA lesions and aberrations in genome structure and defects in maintenance and repair. These somatic DNA mutations known as driver mutations seem to be the prime cause in initiating tumorigenesis. The advances in genomic technologies have immensely facilitated the understanding of cancer progression and metastasis, and the discovery of novel biomarkers. However, changes in somatic mutational landscape of the oncogenome are translated into aberrantly regulated oncoproteome which drives the cancer initiation. Thus, combination of proteomic and genomic technologies is urgently required to discover biomarkers for early diagnosis. The recent advances in human genome based detection of cancer using advanced genomic technologies like NextGen Sequencing, digital PCR, cfDNA technology have shown promise; for example oncogenic somatic mutation variants, transcriptomic analysis, copy number variant, and methylation data from the Cancer Genome Atlas. Similarly, oncoproteomics has the potential to revolutionize clinical management of the disease, including cancer diagnosis and screening based on new proteomic database which embodies somatic variants and post translational modifications, thus devising proteomic technologies as a complement to histopathology. Further, the use of multiple proteomic and genomic biomarkers rather than a single gene or protein could greatly improve diagnostic accuracy and enhance the predictive power for

  13. 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 KJ; 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.

    2016-01-01

    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. 93 protein-coding cancer genes carried likely driver mutations. Some non-coding regions exhibited high mutation frequencies but most have distinctive structural features probably causing elevated mutation rates and do not harbour driver mutations. Mutational signature analysis was extended to genome rearrangements and revealed 12 base substitution and six rearrangement signatures. Three rearrangement signatures, characterised 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 operative, and progresses towards a comprehensive account of the somatic genetic basis of breast cancer. PMID:27135926

  14. An open access pilot freely sharing cancer genomic data from participants in Texas.

    Science.gov (United States)

    Becnel, Lauren B; Pereira, Stacey; Drummond, Jennifer A; Gingras, Marie-Claude; Covington, Kyle R; Kovar, Christie L; Doddapaneni, Harsha Vardhan; Hu, Jianhong; Muzny, Donna; McGuire, Amy L; Wheeler, David A; Gibbs, Richard A

    2016-02-16

    Genomic data sharing in cancer has been restricted to aggregate or controlled-access initiatives to protect the privacy of research participants. By limiting access to these data, it has been argued that the autonomy of individuals who decide to participate in data sharing efforts has been superseded and the utility of the data as research and educational tools reduced. In a pilot Open Access (OA) project from the CPRIT-funded Texas Cancer Research Biobank, many Texas cancer patients were willing to openly share genomic data from tumor and normal matched pair specimens. For the first time, genetic data from 7 human cancer cases with matched normal are freely available without requirement for data use agreements nor any major restriction except that end users cannot attempt to re-identify the participants (http://txcrb.org/open.html).

  15. 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

  16. 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.

  17. Spherical Cancer Models in Tumor Biology

    Directory of Open Access Journals (Sweden)

    Louis-Bastien Weiswald

    2015-01-01

    Full Text Available Three-dimensional (3D in vitro models have been used in cancer research as an intermediate model between in vitro cancer cell line cultures and in vivo tumor. Spherical cancer models represent major 3D in vitro models that have been described over the past 4 decades. These models have gained popularity in cancer stem cell research using tumorospheres. Thus, it is crucial to define and clarify the different spherical cancer models thus far described. Here, we focus on in vitro multicellular spheres used in cancer research. All these spherelike structures are characterized by their well-rounded shape, the presence of cancer cells, and their capacity to be maintained as free-floating cultures. We propose a rational classification of the four most commonly used spherical cancer models in cancer research based on culture methods for obtaining them and on subsequent differences in sphere biology: the multicellular tumor spheroid model, first described in the early 70s and obtained by culture of cancer cell lines under nonadherent conditions; tumorospheres, a model of cancer stem cell expansion established in a serum-free medium supplemented with growth factors; tissue-derived tumor spheres and organotypic multicellular spheroids, obtained by tumor tissue mechanical dissociation and cutting. In addition, we describe their applications to and interest in cancer research; in particular, we describe their contribution to chemoresistance, radioresistance, tumorigenicity, and invasion and migration studies. Although these models share a common 3D conformation, each displays its own intrinsic properties. Therefore, the most relevant spherical cancer model must be carefully selected, as a function of the study aim and cancer type.

  18. Genomic and phenotypic profiles of two Brazilian breast cancer cell lines derived from primary human tumors

    DEFF Research Database (Denmark)

    Corrêa, Natássia C R; Kuasne, Hellen; Faria, Jerusa A Q A

    2013-01-01

    Breast cancer is the most common type of cancer among women worldwide. Research using breast cancer cell lines derived from primary tumors may provide valuable additional knowledge regarding this type of cancer. Therefore, the aim of this study was to investigate the phenotypic profiles of MACL-1...... and MGSO-3, the only Brazilian breast cancer cell lines available for comparative studies. We evaluated the presence of hormone receptors, proliferation, differentiation and stem cell markers, using immunohistochemical staining of the primary tumor, cultured cells and xenografts implanted....... This shift in expression may be due to the selection of an 'establishment' phenotype in vitro. Whole-genome DNA evaluation showed a large amount of copy number alterations (CNAs) in the two cell lines. These findings render MACL-1 and MGSO-3 the first characterized Brazilian breast cancer cell lines...

  19. Global Genomic Analysis of Prostate, Breast and Pancreatic Cancer

    Science.gov (United States)

    2012-10-01

    Gleason grade to assess prognosis of the disease and risk assessment tools such as CAPRA -S (Cancer of the Prostate Risk Assessment Post- Surgical...JF, Carroll PR. The CAPRA -S score: A straightforward tool for improved prediction of outcomes after radical prostatectomy.Cancer. 2011 Nov 15;117(22

  20. Network Based Prediction Model for Genomics Data Analysis*

    OpenAIRE

    Huang, Ying; Wang, Pei

    2012-01-01

    Biological networks, such as genetic regulatory networks and protein interaction networks, provide important information for studying gene/protein activities. In this paper, we propose a new method, NetBoosting, for incorporating a priori biological network information in analyzing high dimensional genomics data. Specially, we are interested in constructing prediction models for disease phenotypes of interest based on genomics data, and at the same time identifying disease susceptible genes. ...

  1. 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.

  2. 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.

  3. Cross-cancer genome-wide analysis of lung, ovary, breast, prostate and colorectal cancer reveals novel pleiotropic associations

    Science.gov (United States)

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

    2016-01-01

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

  4. 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.

  5. 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.

  6. Clinical genomics information management software linking cancer genome sequence and clinical decisions.

    Science.gov (United States)

    Watt, Stuart; Jiao, Wei; Brown, Andrew M K; Petrocelli, Teresa; Tran, Ben; Zhang, Tong; McPherson, John D; Kamel-Reid, Suzanne; Bedard, Philippe L; Onetto, Nicole; Hudson, Thomas J; Dancey, Janet; Siu, Lillian L; Stein, Lincoln; Ferretti, Vincent

    2013-09-01

    Using sequencing information to guide clinical decision-making requires coordination of a diverse set of people and activities. In clinical genomics, the process typically includes sample acquisition, template preparation, genome data generation, analysis to identify and confirm variant alleles, interpretation of clinical significance, and reporting to clinicians. We describe a software application developed within a clinical genomics study, to support this entire process. The software application tracks patients, samples, genomic results, decisions and reports across the cohort, monitors progress and sends reminders, and works alongside an electronic data capture system for the trial's clinical and genomic data. It incorporates systems to read, store, analyze and consolidate sequencing results from multiple technologies, and provides a curated knowledge base of tumor mutation frequency (from the COSMIC database) annotated with clinical significance and drug sensitivity to generate reports for clinicians. By supporting the entire process, the application provides deep support for clinical decision making, enabling the generation of relevant guidance in reports for verification by an expert panel prior to forwarding to the treating physician.

  7. Genomic Basis of Prostate Cancer Health Disparity Among African American Men

    Science.gov (United States)

    2015-10-01

    Nothing to Report APPENDIX Attached Robust Genomic Predictor of Prostate Cancer Metastasis Alexander Pearlman1, Kinnari Upadhyay1*, Kim Cole1...the International Society of Urological Pathology consensus conference. Am J Surg Pathol 38:1017-22, 2014 15. Cullen J, Rosner IL, Brand TC, et al: A

  8. 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,...

  9. 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

  10. 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

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

    NARCIS (Netherlands)

    Smid, M.; Rodriguez-Gonzalez, F.G.; Sieuwerts, A.M.; Salgado, R.; Smissen, W.J. Prager-Van der; Vlugt-Daane, M.V.; Galen, A. van; Nik-Zainal, S.; Staaf, J.; Brinkman, A.B.; Vijver, M.J. van de; Richardson, A.L.; Fatima, A.; Berentsen, K.; Butler, A.; Martin, S.; Davies, H.R.; Debets, R.; Gelder, M.E. Meijer-van; Deurzen, C.H. van; MacGrogan, G.; Eynden, G.G. Van den; Purdie, C.; Thompson, A.M.; Caldas, C.; Span, P.N; Simpson, P.T.; Lakhani, S.R.; Laere, S. van; Desmedt, C.; Ringner, M.; Tommasi, S.; Eyford, J.; Broeks, A.; Vincent-Salomon, A.; Futreal, P.A.; Knappskog, S.; King, T.; Thomas, G; Viari, A.; Langerod, A.; Borresen-Dale, A.L.; Birney, E.; Stunnenberg, H.G.; Stratton, M.; Foekens, J.A.; Martens, J.W.M.

    2016-01-01

    A 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, TP53, PIK3CA,

  12. Integrating proteomic and functional genomic technologies in discovery-driven translational breast cancer research

    DEFF Research Database (Denmark)

    Celis, Julio E; Gromov, Pavel; Gromova, Irina

    2003-01-01

    The application of state-of-the-art proteomics and functional genomics technologies to the study of cancer is rapidly shifting toward the analysis of clinically relevant samples derived from patients, as the ultimate aim of translational research is to bring basic discoveries closer to the bedsid...

  13. Gross genomic damage measured by DNA image cytometry independently predicts gastric cancer patient survival

    NARCIS (Netherlands)

    Belien, J.A.M.; Buffart, T.E.; Gill, A.; Broeckaert, M.A.M.; Quirke, P.; Meijer, G.A.; Grabsch, H.

    2009-01-01

    BACKGROUND: DNA aneuploidy reflects gross genomic changes. It can be measured by flow cytometry (FCM-DNA) or image cytometry (ICM-DNA). In gastric cancer, the prevalence of DNA aneuploidy has been reported to range from 27 to 100%, with conflicting associations with clinicopathological variables. Th

  14. 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.

  15. Chromothripsis is a common mechanism driving genomic rearrangements in primary and metastatic colorectal cancer

    NARCIS (Netherlands)

    Kloosterman, W.P.; Hoogstraat, M.; Paling, O.; Tavakoli-Yaraki, M.; Renkens, I.; Vermaat, J.E.; van Roosmalen, M.; van Lieshout, S.; Nijman, I.J.; Roessingh, W.; Van't Slot, R.; van de Belt, J.; Guryev, V.; Koudijs, M.J.; Voest, E.E.; Cuppen, E.

    2011-01-01

    ABSTRACT: BACKGROUND: Structural rearrangements form a major class of somatic variation in cancer genomes. Local chromosome shattering, termed chromothripsis, is a mechanism proposed to be the cause of clustered chromosomal rearrangements and was recently described to occur in a small percentage of

  16. Chromothripsis is a common mechanism driving genomic rearrangements in primary and metastatic colorectal cancer

    NARCIS (Netherlands)

    Kloosterman, W.P.; Hoogstraat, M.; Paling, O.; Tavakoli-Yaraki, M.; Renkens, I.; Vermaat, J.S.; Roosmalen, van M.J.; Lieshout, van S.; Nijman, I.J.; Roessingh, W.; Slot, van 't R.; Belt, van de J.

    2011-01-01

    Background - Structural rearrangements form a major class of somatic variation in cancer genomes. Local chromosome shattering, termed chromothripsis, is a mechanism proposed to be the cause of clustered chromosomal rearrangements and was recently described to occur in a small percentage of tumors. T

  17. 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.

  18. 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.

  19. 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.

  20. 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.

  1. 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...... 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...

  2. [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.

  3. An integrated 3-Dimensional Genome Modeling Engine for data-driven simulation of spatial genome organization.

    Science.gov (United States)

    Szałaj, Przemysław; Tang, Zhonghui; Michalski, Paul; Pietal, Michal J; Luo, Oscar J; Sadowski, Michał; Li, Xingwang; Radew, Kamen; Ruan, Yijun; Plewczynski, Dariusz

    2016-12-01

    ChIA-PET is a high-throughput mapping technology that reveals long-range chromatin interactions and provides insights into the basic principles of spatial genome organization and gene regulation mediated by specific protein factors. Recently, we showed that a single ChIA-PET experiment provides information at all genomic scales of interest, from the high-resolution locations of binding sites and enriched chromatin interactions mediated by specific protein factors, to the low resolution of nonenriched interactions that reflect topological neighborhoods of higher-order chromosome folding. This multilevel nature of ChIA-PET data offers an opportunity to use multiscale 3D models to study structural-functional relationships at multiple length scales, but doing so requires a structural modeling platform. Here, we report the development of 3D-GNOME (3-Dimensional Genome Modeling Engine), a complete computational pipeline for 3D simulation using ChIA-PET data. 3D-GNOME consists of three integrated components: a graph-distance-based heat map normalization tool, a 3D modeling platform, and an interactive 3D visualization tool. Using ChIA-PET and Hi-C data derived from human B-lymphocytes, we demonstrate the effectiveness of 3D-GNOME in building 3D genome models at multiple levels, including the entire genome, individual chromosomes, and specific segments at megabase (Mb) and kilobase (kb) resolutions of single average and ensemble structures. Further incorporation of CTCF-motif orientation and high-resolution looping patterns in 3D simulation provided additional reliability of potential biologically plausible topological structures.

  4. 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.

  5. 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.

  6. Commentary on Almassalha et al., "The Greater Genomic Landscape: The Heterogeneous Evolution of Cancer".

    Science.gov (United States)

    Lynch, Henry T; Rendell, Marc; Shaw, Trudy G; Silberstein, Peter; Ngo, Binh T

    2016-10-01

    In this issue of Cancer Research, Almassalha and colleagues have proposed a new concept of the development of malignancy, that of the greater genomic landscape. They propose a stressor-related exploration of intracellular genomic sites as a response mechanism. This process can express sites with beneficial or deleterious effects, among them those that promote cell proliferation. They point out that their conception is broader, although certainly inclusive, of the process of gene induction. The authors view the physical process of chromatin reorganization as central to the exploration of the genomic landscape. Accordingly, they advocate the development of agents to limit chromatin structural modification as a chemotherapeutic approach in cancer. We found their theory relevant to understand the phenotypic heterogeneity of malignancy, particularly in familial cancer syndromes. For example, the familial atypical multiple mole melanoma (FAMMM) syndrome, related to a gene mutation, is characterized by a diversity of melanocytic lesions, only some of which become malignant melanoma. This new conceptualization can do much to increase understanding of the diversity of malignancy in families with hereditary cancer. Cancer Res; 76(19); 5602-4. ©2016 AACR.

  7. 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.

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

    Science.gov (United States)

    Ali Hassan, Nur Zarina; Mokhtar, Norfilza Mohd; Kok Sin, Teow; Mohamed Rose, Isa; Sagap, Ismail; Harun, Roslan; Jamal, Rahman

    2014-01-01

    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.

  9. 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.

  10. 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

  11. 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.

  12. 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

  13. The importance of p53 pathway genetics in inherited and somatic cancer genomes.

    Science.gov (United States)

    Stracquadanio, Giovanni; Wang, Xuting; Wallace, Marsha D; Grawenda, Anna M; Zhang, Ping; Hewitt, Juliet; Zeron-Medina, Jorge; Castro-Giner, Francesc; Tomlinson, Ian P; Goding, Colin R; Cygan, Kamil J; Fairbrother, William G; Thomas, Laurent F; Sætrom, Pål; Gemignani, Federica; Landi, Stefano; Schuster-Böckler, Benjamin; Bell, Douglas A; Bond, Gareth L

    2016-04-01

    Decades of research have shown that mutations in the p53 stress response pathway affect the incidence of diverse cancers more than mutations in other pathways. However, most evidence is limited to somatic mutations and rare inherited mutations. Using newly abundant genomic data, we demonstrate that commonly inherited genetic variants in the p53 pathway also affect the incidence of a broad range of cancers more than variants in other pathways. The cancer-associated single nucleotide polymorphisms (SNPs) of the p53 pathway have strikingly similar genetic characteristics to well-studied p53 pathway cancer-causing somatic mutations. Our results enable insights into p53-mediated tumour suppression in humans and into p53 pathway-based cancer surveillance and treatment strategies.

  14. 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

  15. 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

  16. 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

  17. 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.

  18. A comprehensive catalogue of somatic mutations in cancer genomes.

    Science.gov (United States)

    Friedberg, Errol C

    2010-04-04

    This Hot Topics contribution considers two recently published papers that demonstrate the utility of advanced DNA sequencing technologies for identifying classes of mutations other than base substitutions. Data are presented from genome analyses of immortalized cell lines derived from a malignant melanoma and a small cell carcinoma of the lung. Among other observations the studies suggest the operation of novel DNA repair mechanisms or modes.

  19. Systematic identification of genomic markers of drug sensitivity in cancer cells.

    Science.gov (United States)

    Garnett, Mathew J; Edelman, Elena J; Heidorn, Sonja J; Greenman, Chris D; Dastur, Anahita; Lau, King Wai; Greninger, Patricia; Thompson, I Richard; Luo, Xi; Soares, Jorge; Liu, Qingsong; Iorio, Francesco; Surdez, Didier; Chen, Li; Milano, Randy J; Bignell, Graham R; Tam, Ah T; Davies, Helen; Stevenson, Jesse A; Barthorpe, Syd; Lutz, Stephen R; Kogera, Fiona; Lawrence, Karl; McLaren-Douglas, Anne; Mitropoulos, Xeni; Mironenko, Tatiana; Thi, Helen; Richardson, Laura; Zhou, Wenjun; Jewitt, Frances; Zhang, Tinghu; O'Brien, Patrick; Boisvert, Jessica L; Price, Stacey; Hur, Wooyoung; Yang, Wanjuan; Deng, Xianming; Butler, Adam; Choi, Hwan Geun; Chang, Jae Won; Baselga, Jose; Stamenkovic, Ivan; Engelman, Jeffrey A; Sharma, Sreenath V; Delattre, Olivier; Saez-Rodriguez, Julio; Gray, Nathanael S; Settleman, Jeffrey; Futreal, P Andrew; Haber, Daniel A; Stratton, Michael R; Ramaswamy, Sridhar; McDermott, Ultan; Benes, Cyril H

    2012-03-28

    Clinical responses to anticancer therapies are often restricted to a subset of patients. In some cases, mutated cancer genes are potent biomarkers for responses to targeted agents. Here, to uncover new biomarkers of sensitivity and resistance to cancer therapeutics, we screened a panel of several hundred cancer cell lines--which represent much of the tissue-type and genetic diversity of human cancers--with 130 drugs under clinical and preclinical investigation. In aggregate, we found that mutated cancer genes were associated with cellular response to most currently available cancer drugs. Classic oncogene addiction paradigms were modified by additional tissue-specific or expression biomarkers, and some frequently mutated genes were associated with sensitivity to a broad range of therapeutic agents. Unexpected relationships were revealed, including the marked sensitivity of Ewing's sarcoma cells harbouring the EWS (also known as EWSR1)-FLI1 gene translocation to poly(ADP-ribose) polymerase (PARP) inhibitors. By linking drug activity to the functional complexity of cancer genomes, systematic pharmacogenomic profiling in cancer cell lines provides a powerful biomarker discovery platform to guide rational cancer therapeutic strategies.

  20. 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.

  1. Score-based prediction of genomic islands in prokaryotic genomes using hidden Markov models

    Directory of Open Access Journals (Sweden)

    Surovcik Katharina

    2006-03-01

    Full Text Available Abstract Background Horizontal gene transfer (HGT is considered a strong evolutionary force shaping the content of microbial genomes in a substantial manner. It is the difference in speed enabling the rapid adaptation to changing environmental demands that distinguishes HGT from gene genesis, duplications or mutations. For a precise characterization, algorithms are needed that identify transfer events with high reliability. Frequently, the transferred pieces of DNA have a considerable length, comprise several genes and are called genomic islands (GIs or more specifically pathogenicity or symbiotic islands. Results We have implemented the program SIGI-HMM that predicts GIs and the putative donor of each individual alien gene. It is based on the analysis of codon usage (CU of each individual gene of a genome under study. CU of each gene is compared against a carefully selected set of CU tables representing microbial donors or highly expressed genes. Multiple tests are used to identify putatively alien genes, to predict putative donors and to mask putatively highly expressed genes. Thus, we determine the states and emission probabilities of an inhomogeneous hidden Markov model working on gene level. For the transition probabilities, we draw upon classical test theory with the intention of integrating a sensitivity controller in a consistent manner. SIGI-HMM was written in JAVA and is publicly available. It accepts as input any file created according to the EMBL-format. It generates output in the common GFF format readable for genome browsers. Benchmark tests showed that the output of SIGI-HMM is in agreement with known findings. Its predictions were both consistent with annotated GIs and with predictions generated by different methods. Conclusion SIGI-HMM is a sensitive tool for the identification of GIs in microbial genomes. It allows to interactively analyze genomes in detail and to generate or to test hypotheses about the origin of acquired

  2. Comprehensive genomic sequencing and the molecular profiles of clinically advanced breast cancer.

    Science.gov (United States)

    Ross, Jeffrey S; Gay, Laurie M

    2017-02-01

    Targeting specific mutations that have arisen within a tumour is a promising means of increasing the efficacy of treatments, and breast cancer is no exception to this new paradigm of personalised medicine. Traditional DNA sequencing methods used to characterise clinical cancer specimens and impact treatment decisions are highly sensitive, but are often limited in their scope to known mutational hot spots. Next-generation sequencing (NGS) technologies can also test for these well-known hot spots, as well as identifying insertions and deletions, copy number changes such as ERBB2 (HER2) gene amplification, and a wide array of fusion or rearrangement events. By rapidly analysing many genes in parallel, NGS technologies can make efficient use of precious biopsy material. Comprehensive genomic profiling (CGP) by NGS can reveal targetable, clinically relevant genomic alterations that can stratify tumours by predicted sensitivity to a variety of therapies, including HER2- or MTOR-targeted therapies, immunotherapies, and other kinase inhibitors. Many clinically relevant genomic alterations would not be identified by IHC or hotspot testing, but can be detected by NGS. In addition to the most common breast carcinoma subtypes, rare subtypes analysed with CGP also harbour clinically relevant genomic alterations that can potentially direct therapy selection, illustrating that CGP is a powerful tool for guiding treatment across all breast cancer subtypes.

  3. 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.

  4. 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.

  5. 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.

  6. 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.

  7. Protein-Protein Interactions (PPI) reagents: | Office of Cancer Genomics

    Science.gov (United States)

    The CTD2 Center at Emory University has a library of genes used to study protein-protein interactions in mammalian cells. These genes are cloned in different mammalian expression vectors. A list of available cancer-associated genes can be accessed below.

  8. Protein-Protein Interaction Reagents | Office of Cancer Genomics

    Science.gov (United States)

    The CTD2 Center at Emory University has a library of genes used to study protein-protein interactions in mammalian cells. These genes are cloned in different mammalian expression vectors. A list of available cancer-associated genes can be accessed below. Emory_CTD^2_PPI_Reagents.xlsx Contact: Haian Fu

  9. 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.

  10. Genomic and transcriptomic plasticity in treatment-naive ovarian cancer

    NARCIS (Netherlands)

    Hoogstraat, Marlous; de Pagter, Mirjam S; Cirkel, Geert A; van Roosmalen, Markus J; Harkins, Timothy T; Duran, Karen; Kreeftmeijer, Jennifer; Renkens, Ivo; Witteveen, Petronella O; Lee, Clarence C; Nijman, Isaac J; Guy, Tanisha; van 't Slot, Ruben; Jonges, Trudy N; Lolkema, Martijn P; Koudijs, Marco J; Zweemer, Ronald P; Voest, Emile E; Cuppen, Edwin; Kloosterman, Wigard P

    2014-01-01

    Intra-tumor heterogeneity is a hallmark of many cancers and may lead to therapy resistance or interfere with personalized treatment strategies. Here, we combined topographic mapping of somatic breakpoints and transcriptional profiling to probe intra-tumor heterogeneity of treatment-naïve stage IIIC/

  11. 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...

  12. Collaborative cancer epidemiology in the 21st century: the model of cancer consortia.

    Science.gov (United States)

    Burgio, Michael R; Ioannidis, John P A; Kaminski, Brett M; Derycke, Eric; Rogers, Scott; Khoury, Muin J; Seminara, Daniela

    2013-12-01

    During the last two decades, epidemiology has undergone a rapid evolution toward collaborative research. The proliferation of multi-institutional, interdisciplinary consortia has acquired particular prominence in cancer research. Herein, we describe the characteristics of a network of 49 established cancer epidemiology consortia (CEC) currently supported by the Epidemiology and Genomics Research Program (EGRP) at the National Cancer Institute (NCI). This collection represents the largest disease-based research network for collaborative cancer research established in population sciences. We describe the funding trends, geographic distribution, and areas of research focus. The CEC have been partially supported by 201 grants and yielded 3,876 publications between 1995 and 2011. We describe this output in terms of interdisciplinary collaboration and translational evolution. We discuss challenges and future opportunities in the establishment and conduct of large-scale team science within the framework of CEC, review future prospects for this approach to large-scale, interdisciplinary cancer research, and describe a model for the evolution of an integrated Network of Cancer Consortia optimally suited to address and support 21st-century epidemiology.

  13. Neocaridina denticulata: A Decapod Crustacean Model for Functional Genomics.

    Science.gov (United States)

    Mykles, Donald L; Hui, Jerome H L

    2015-11-01

    A decapod crustacean model is needed for understanding the molecular mechanisms underlying physiological processes, such as reproduction, sex determination, molting and growth, immunity, regeneration, and response to stress. Criteria for selection are: life-history traits, adult size, availability and ease of culture, and genomics and genetic manipulation. Three freshwater species are considered: cherry shrimp, Neocaridina denticulata; red swamp crayfish, Procambarus clarkii; and redclaw crayfish, Cherax quadricarinatus. All three are readily available, reproduce year round, and grow rapidly. The crayfish species require more space for culture than does N. denticulata. The transparent cuticle of cherry shrimp provides for direct assessment of reproductive status, stage of molt, and tissue-specific expression of reporter genes, and facilitates screening of mutations affecting phenotype. Moreover, a preliminary genome of N. denticulata is available and efforts toward complete genome sequencing and transcriptome sequencing have been initiated. Neocaridina denticulata possesses the best combination of traits that make it most suitable as a model for functional genomics. The next step is to obtain the complete genome sequence and to develop molecular technologies for the screening of mutants and for manipulating tissue-specific gene expression.

  14. Genome-scale modeling of human metabolism - a systems biology approach.

    Science.gov (United States)

    Mardinoglu, Adil; Gatto, Francesco; Nielsen, Jens

    2013-09-01

    Altered metabolism is linked to the appearance of various human diseases and a better understanding of disease-associated metabolic changes may lead to the identification of novel prognostic biomarkers and the development of new therapies. Genome-scale metabolic models (GEMs) have been employed for studying human metabolism in a systematic manner, as well as for understanding complex human diseases. In the past decade, such metabolic models - one of the fundamental aspects of systems biology - have started contributing to the understanding of the mechanistic relationship between genotype and phenotype. In this review, we focus on the construction of the Human Metabolic Reaction database, the generation of healthy cell type- and cancer-specific GEMs using different procedures, and the potential applications of these developments in the study of human metabolism and in the identification of metabolic changes associated with various disorders. We further examine how in silico genome-scale reconstructions can be employed to simulate metabolic flux distributions and how high-throughput omics data can be analyzed in a context-dependent fashion. Insights yielded from this mechanistic modeling approach can be used for identifying new therapeutic agents and drug targets as well as for the discovery of novel biomarkers. Finally, recent advancements in genome-scale modeling and the future challenge of developing a model of whole-body metabolism are presented. The emergent contribution of GEMs to personalized and translational medicine is also discussed.

  15. Genomic characterization of explant tumorgraft models derived from fresh patient tumor tissue

    Directory of Open Access Journals (Sweden)

    Monsma David J

    2012-06-01

    Full Text Available Abstract Background There is resurgence within drug and biomarker development communities for the use of primary tumorgraft models as improved predictors of patient tumor response to novel therapeutic strategies. Despite perceived advantages over cell line derived xenograft models, there is limited data comparing the genotype and phenotype of tumorgrafts to the donor patient tumor, limiting the determination of molecular relevance of the tumorgraft model. This report directly compares the genomic characteristics of patient tumors and the derived tumorgraft models, including gene expression, and oncogenic mutation status. Methods Fresh tumor tissues from 182 cancer patients were implanted subcutaneously into immune-compromised mice for the development of primary patient tumorgraft models. Histological assessment was performed on both patient tumors and the resulting tumorgraft models. Somatic mutations in key oncogenes and gene expression levels of resulting tumorgrafts were compared to the matched patient tumors using the OncoCarta (Sequenom, San Diego, CA and human gene microarray (Affymetrix, Santa Clara, CA platforms respectively. The genomic stability of the established tumorgrafts was assessed across serial in vivo generations in a representative subset of models. The genomes of patient tumors that formed tumorgrafts were compared to those that did not to identify the possible molecular basis to successful engraftment or rejection. Results Fresh tumor tissues from 182 cancer patients were implanted into immune-compromised mice with forty-nine tumorgraft models that have been successfully established, exhibiting strong histological and genomic fidelity to the originating patient tumors. Comparison of the transcriptomes and oncogenic mutations between the tumorgrafts and the matched patient tumors were found to be stable across four tumorgraft generations. Not only did the various tumors retain the differentiation pattern, but supporting

  16. 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.

  17. Genome-wide association study identifies multiple loci associated with bladder cancer risk

    Science.gov (United States)

    Figueroa, Jonine D.; Ye, Yuanqing; Siddiq, Afshan; Garcia-Closas, Montserrat; Chatterjee, Nilanjan; Prokunina-Olsson, Ludmila; Cortessis, Victoria K.; Kooperberg, Charles; Cussenot, Olivier; Benhamou, Simone; Prescott, Jennifer; Porru, Stefano; Dinney, Colin P.; Malats, Núria; Baris, Dalsu; Purdue, Mark; Jacobs, Eric J.; Albanes, Demetrius; Wang, Zhaoming; Deng, Xiang; Chung, Charles C.; Tang, Wei; Bas Bueno-de-Mesquita, H.; Trichopoulos, Dimitrios; Ljungberg, Börje; Clavel-Chapelon, Françoise; Weiderpass, Elisabete; Krogh, Vittorio; Dorronsoro, Miren; Travis, Ruth; Tjønneland, Anne; Brenan, Paul; Chang-Claude, Jenny; Riboli, Elio; Conti, David; Gago-Dominguez, Manuela; Stern, Mariana C.; Pike, Malcolm C.; Van Den Berg, David; Yuan, Jian-Min; Hohensee, Chancellor; Rodabough, Rebecca; Cancel-Tassin, Geraldine; Roupret, Morgan; Comperat, Eva; Chen, Constance; De Vivo, Immaculata; Giovannucci, Edward; Hunter, David J.; Kraft, Peter; Lindstrom, Sara; Carta, Angela; Pavanello, Sofia; Arici, Cecilia; Mastrangelo, Giuseppe; Kamat, Ashish M.; Lerner, Seth P.; Barton Grossman, H.; Lin, Jie; Gu, Jian; Pu, Xia; Hutchinson, Amy; Burdette, Laurie; Wheeler, William; Kogevinas, Manolis; Tardón, Adonina; Serra, Consol; Carrato, Alfredo; García-Closas, Reina; Lloreta, Josep; Schwenn, Molly; Karagas, Margaret R.; Johnson, Alison; Schned, Alan; Armenti, Karla R.; Hosain, G.M.; Andriole, Gerald; Grubb, Robert; Black, Amanda; Ryan Diver, W.; Gapstur, Susan M.; Weinstein, Stephanie J.; Virtamo, Jarmo; Haiman, Chris A.; Landi, Maria T.; Caporaso, Neil; Fraumeni, Joseph F.; Vineis, Paolo; Wu, Xifeng; Silverman, Debra T.; Chanock, Stephen; Rothman, Nathaniel

    2014-01-01

    Candidate gene and genome-wide association studies (GWAS) have identified 11 independent susceptibility loci associated with bladder cancer risk. To discover additional risk variants, we conducted a new GWAS of 2422 bladder cancer cases and 5751 controls, followed by a meta-analysis with two independently published bladder cancer GWAS, resulting in a combined analysis of 6911 cases and 11 814 controls of European descent. TaqMan genotyping of 13 promising single nucleotide polymorphisms with P < 1 × 10−5 was pursued in a follow-up set of 801 cases and 1307 controls. Two new loci achieved genome-wide statistical significance: rs10936599 on 3q26.2 (P = 4.53 × 10−9) and rs907611 on 11p15.5 (P = 4.11 × 10−8). Two notable loci were also identified that approached genome-wide statistical significance: rs6104690 on 20p12.2 (P = 7.13 × 10−7) and rs4510656 on 6p22.3 (P = 6.98 × 10−7); these require further studies for confirmation. In conclusion, our study has identified new susceptibility alleles for bladder cancer risk that require fine-mapping and laboratory investigation, which could further understanding into the biological underpinnings of bladder carcinogenesis. PMID:24163127

  18. Analysis of Heritability and Shared Heritability Based on Genome-Wide Association Studies for 13 Cancer Types

    Science.gov (United States)

    Wheeler, William A.; Yeager, Meredith; Panagiotou, Orestis; Wang, Zhaoming; Berndt, Sonja I.; Lan, Qing; Abnet, Christian C.; Amundadottir, Laufey T.; Figueroa, Jonine D.; Landi, Maria Teresa; Mirabello, Lisa; Savage, Sharon A.; Taylor, Philip R.; Vivo, Immaculata De; McGlynn, Katherine A.; Purdue, Mark P.; Rajaraman, Preetha; Adami, Hans-Olov; Ahlbom, Anders; Albanes, Demetrius; Amary, Maria Fernanda; An, She-Juan; Andersson, Ulrika; Andriole, Gerald; Andrulis, Irene L.; Angelucci, Emanuele; Ansell, Stephen M.; Arici, Cecilia; Armstrong, Bruce K.; Arslan, Alan A.; Austin, Melissa A.; Baris, Dalsu; Barkauskas, Donald A.; Bassig, Bryan A.; Becker, Nikolaus; Benavente, Yolanda; Benhamou, Simone; Berg, Christine; Van Den Berg, David; Bernstein, Leslie; Bertrand, Kimberly A.; Birmann, Brenda M.; Black, Amanda; Boeing, Heiner; Boffetta, Paolo; Boutron-Ruault, Marie-Christine; Bracci, Paige M.; Brinton, Louise; Brooks-Wilson, Angela R.; Bueno-de-Mesquita, H. Bas; Burdett, Laurie; Buring, Julie; Butler, Mary Ann; Cai, Qiuyin; Cancel-Tassin, Geraldine; Canzian, Federico; Carrato, Alfredo; Carreon, Tania; Carta, Angela; Chan, John K. C.; Chang, Ellen T.; Chang, Gee-Chen; Chang, I-Shou; Chang, Jiang; Chang-Claude, Jenny; Chen, Chien-Jen; Chen, Chih-Yi; Chen, Chu; Chen, Chung-Hsing; Chen, Constance; Chen, Hongyan; Chen, Kexin; Chen, Kuan-Yu; Chen, Kun-Chieh; Chen, Ying; Chen, Ying-Hsiang; Chen, Yi-Song; Chen, Yuh-Min; Chien, Li-Hsin; Chirlaque, María-Dolores; Choi, Jin Eun; Choi, Yi Young; Chow, Wong-Ho; Chung, Charles C.; Clavel, Jacqueline; Clavel-Chapelon, Françoise; Cocco, Pierluigi; Colt, Joanne S.; Comperat, Eva; Conde, Lucia; Connors, Joseph M.; Conti, David; Cortessis, Victoria K.; Cotterchio, Michelle; Cozen, Wendy; Crouch, Simon; Crous-Bou, Marta; Cussenot, Olivier; Davis, Faith G.; Ding, Ti; Diver, W. Ryan; Dorronsoro, Miren; Dossus, Laure; Duell, Eric J.; Ennas, Maria Grazia; Erickson, Ralph L.; Feychting, Maria; Flanagan, Adrienne M.; Foretova, Lenka; Fraumeni, Joseph F.; Freedman, Neal D.; Beane Freeman, Laura E.; Fuchs, Charles; Gago-Dominguez, Manuela; Gallinger, Steven; Gao, Yu-Tang; Gapstur, Susan M.; Garcia-Closas, Montserrat; García-Closas, Reina; Gascoyne, Randy D.; Gastier-Foster, Julie; Gaudet, Mia M.; Gaziano, J. Michael; Giffen, Carol; Giles, Graham G.; Giovannucci, Edward; Glimelius, Bengt; Goggins, Michael; Gokgoz, Nalan; Goldstein, Alisa M.; Gorlick, Richard; Gross, Myron; Grubb, Robert; Gu, Jian; Guan, Peng; Gunter, Marc; Guo, Huan; Habermann, Thomas M.; Haiman, Christopher A.; Halai, Dina; Hallmans, Goran; Hassan, Manal; Hattinger, Claudia; He, Qincheng; He, Xingzhou; Helzlsouer, Kathy; Henderson, Brian; Henriksson, Roger; Hjalgrim, Henrik; Hoffman-Bolton, Judith; Hohensee, Chancellor; Holford, Theodore R.; Holly, Elizabeth A.; Hong, Yun-Chul; Hoover, Robert N.; Horn-Ross, Pamela L.; Hosain, G. M. Monawar; Hosgood, H. Dean; Hsiao, Chin-Fu; Hu, Nan; Hu, Wei; Hu, Zhibin; Huang, Ming-Shyan; Huerta, Jose-Maria; Hung, Jen-Yu; Hutchinson, Amy; Inskip, Peter D.; Jackson, Rebecca D.; Jacobs, Eric J.; Jenab, Mazda; Jeon, Hyo-Sung; Ji, Bu-Tian; Jin, Guangfu; Jin, Li; Johansen, Christoffer; Johnson, Alison; Jung, Yoo Jin; Kaaks, Rudolph; Kamineni, Aruna; Kane, Eleanor; Kang, Chang Hyun; Karagas, Margaret R.; Kelly, Rachel S.; Khaw, Kay-Tee; Kim, Christopher; Kim, Hee Nam; Kim, Jin Hee; Kim, Jun Suk; Kim, Yeul Hong; Kim, Young Tae; Kim, Young-Chul; Kitahara, Cari M.; Klein, Alison P.; Klein, Robert J.; Kogevinas, Manolis; Kohno, Takashi; Kolonel, Laurence N.; Kooperberg, Charles; Kricker, Anne; Krogh, Vittorio; Kunitoh, Hideo; Kurtz, Robert C.; Kweon, Sun-Seog; LaCroix, Andrea; Lawrence, Charles; Lecanda, Fernando; Lee, Victor Ho Fun; Li, Donghui; Li, Haixin; Li, Jihua; Li, Yao-Jen; Li, Yuqing; Liao, Linda M.; Liebow, Mark; Lightfoot, Tracy; Lim, Wei-Yen; Lin, Chien-Chung; Lin, Dongxin; Lindstrom, Sara; Linet, Martha S.; Link, Brian K.; Liu, Chenwei; Liu, Jianjun; Liu, Li; Ljungberg, Börje; Lloreta, Josep; Lollo, Simonetta Di; Lu, Daru; Lund, Eiluv; Malats, Nuria; Mannisto, Satu; Marchand, Loic Le; Marina, Neyssa; Masala, Giovanna; Mastrangelo, Giuseppe; Matsuo, Keitaro; Maynadie, Marc; McKay, James; McKean-Cowdin, Roberta; Melbye, Mads; Melin, Beatrice S.; Michaud, Dominique S.; Mitsudomi, Tetsuya; Monnereau, Alain; Montalvan, Rebecca; Moore, Lee E.; Mortensen, Lotte Maxild; Nieters, Alexandra; North, Kari E.; Novak, Anne J.; Oberg, Ann L.; Offit, Kenneth; Oh, In-Jae; Olson, Sara H.; Palli, Domenico; Pao, William; Park, In Kyu; Park, Jae Yong; Park, Kyong Hwa; Patiño-Garcia, Ana; Pavanello, Sofia; Peeters, Petra H. M.; Perng, Reury-Perng; Peters, Ulrike; Petersen, Gloria M.; Picci, Piero; Pike, Malcolm C.; Porru, Stefano; Prescott, Jennifer; Prokunina-Olsson, Ludmila; Qian, Biyun; Qiao, You-Lin; Rais, Marco; Riboli, Elio; Riby, Jacques; Risch, Harvey A.; Rizzato, Cosmeri; Rodabough, Rebecca; Roman, Eve; Roupret, Morgan; Ruder, Avima M.; de Sanjose, Silvia; Scelo, Ghislaine; Schned, Alan; Schumacher, Fredrick; Schwartz, Kendra; Schwenn, Molly; Scotlandi, Katia; Seow, Adeline; Serra, Consol; Serra, Massimo; Sesso, Howard D.; Setiawan, Veronica Wendy; Severi, Gianluca; Severson, Richard K.; Shanafelt, Tait D.; Shen, Hongbing; Shen, Wei; Shin, Min-Ho; Shiraishi, Kouya; Shu, Xiao-Ou; Siddiq, Afshan; Sierrasesúmaga, Luis; Sihoe, Alan Dart Loon; Skibola, Christine F.; Smith, Alex; Smith, Martyn T.; Southey, Melissa C.; Spinelli, John J.; Staines, Anthony; Stampfer, Meir; Stern, Marianna C.; Stevens, Victoria L.; Stolzenberg-Solomon, Rachael S.; Su, Jian; Su, Wu-Chou; Sund, Malin; Sung, Jae Sook; Sung, Sook Whan; Tan, Wen; Tang, Wei; Tardón, Adonina; Thomas, David; Thompson, Carrie A.; Tinker, Lesley F.; Tirabosco, Roberto; Tjønneland, Anne; Travis, Ruth C.; Trichopoulos, Dimitrios; Tsai, Fang-Yu; Tsai, Ying-Huang; Tucker, Margaret; Turner, Jenny; Vajdic, Claire M.; Vermeulen, Roel C. H.; Villano, Danylo J.; Vineis, Paolo; Virtamo, Jarmo; Visvanathan, Kala; Wactawski-Wende, Jean; Wang, Chaoyu; Wang, Chih-Liang; Wang, Jiu-Cun; Wang, Junwen; Wei, Fusheng; Weiderpass, Elisabete; Weiner, George J.; Weinstein, Stephanie; Wentzensen, Nicolas; White, Emily; Witzig, Thomas E.; Wolpin, Brian M.; Wong, Maria Pik; Wu, Chen; Wu, Guoping; Wu, Junjie; Wu, Tangchun; Wu, Wei; Wu, Xifeng; Wu, Yi-Long; Wunder, Jay S.; Xiang, Yong-Bing; Xu, Jun; Xu, Ping; Yang, Pan-Chyr; Yang, Tsung-Ying; Ye, Yuanqing; Yin, Zhihua; Yokota, Jun; Yoon, Ho-Il; Yu, Chong-Jen; Yu, Herbert; Yu, Kai; Yuan, Jian-Min; Zelenetz, Andrew; Zeleniuch-Jacquotte, Anne; Zhang, Xu-Chao; Zhang, Yawei; Zhao, Xueying; Zhao, Zhenhong; Zheng, Hong; Zheng, Tongzhang; Zheng, Wei; Zhou, Baosen; Zhu, Meng; Zucca, Mariagrazia; Boca, Simina M.; Cerhan, James R.; Ferri, Giovanni M.; Hartge, Patricia; Hsiung, Chao Agnes; Magnani, Corrado; Miligi, Lucia; Morton, Lindsay M.; Smedby, Karin E.; Teras, Lauren R.; Vijai, Joseph; Wang, Sophia S.; Brennan, Paul; Caporaso, Neil E.; Hunter, David J.; Kraft, Peter; Rothman, Nathaniel; Silverman, Debra T.; Slager, Susan L.; Chanock, Stephen J.; Chatterjee, Nilanjan

    2015-01-01

    Background: Studies of related individuals have consistently demonstrated notable familial aggregation of cancer. We aim to estimate the heritability and genetic correlation attributable to the additive effects of common single-nucleotide polymorphisms (SNPs) for cancer at 13 anatomical sites. Methods: Between 2007 and 2014, the US National Cancer Institute has generated data from genome-wide association studies (GWAS) for 49 492 cancer case patients and 34 131 control patients. We apply novel mixed model methodology (GCTA) to this GWAS data to estimate the heritability of individual cancers, as well as the proportion of heritability attributable to cigarette smoking in smoking-related cancers, and the genetic correlation between pairs of cancers. Results: GWAS heritability was statistically significant at nearly all sites, with the estimates of array-based heritability, hl 2, on the liability threshold (LT) scale ranging from 0.05 to 0.38. Estimating the combined heritability of multiple smoking characteristics, we calculate that at least 24% (95% confidence interval [CI] = 14% to 37%) and 7% (95% CI = 4% to 11%) of the heritability for lung and bladder cancer, respectively, can be attributed to genetic determinants of smoking. Most pairs of cancers studied did not show evidence of strong genetic correlation. We found only four pairs of cancers with marginally statistically significant correlations, specifically kidney and testes (ρ = 0.73, SE = 0.28), diffuse large B-cell lymphoma (DLBCL) and pediatric osteosarcoma (ρ = 0.53, SE = 0.21), DLBCL and chronic lymphocytic leukemia (CLL) (ρ = 0.51, SE =0.18), and bladder and lung (ρ = 0.35, SE = 0.14). Correlation analysis also indicates that the genetic architecture of lung cancer differs between a smoking population of European ancestry and a nonsmoking Asian population, allowing for the possibility that the genetic etiology for the same disease can vary by population and environmental exposures. Conclusion: Our

  19. Clonal expansion and linear genome evolution through breast cancer progression from pre-invasive stages to asynchronous metastasis

    DEFF Research Database (Denmark)

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

    2015-01-01

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

  20. 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.

  1. 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.

  2. The genome of the model beetle and pest Tribolium castaneum

    DEFF Research Database (Denmark)

    Denell, Robin; Gibbs, Richard; Muzny, Donna

    2008-01-01

    Tribolium castaneum is a member of the most species-rich eukaryotic order, a powerful model organism for the study of generalized insect development, and an important pest of stored agricultural products. We describe its genome sequence here. This omnivorous beetle has evolved the ability to inte...

  3. The genome sequence of the model ascomycete fungus Podospora anserina

    NARCIS (Netherlands)

    Espagne, Eric; Lespinet, Olivier; Malagnac, Fabienne; Da Silva, Corinne; Jaillon, Olivier; Porcel, Betina M; Couloux, Arnaud; Aury, Jean-Marc; Ségurens, Béatrice; Poulain, Julie; Anthouard, Véronique; Grossetete, Sandrine; Khalili, Hamid; Coppin, Evelyne; Déquard-Chablat, Michelle; Picard, Marguerite; Contamine, Véronique; Arnaise, Sylvie; Bourdais, Anne; Berteaux-Lecellier, Véronique; Gautheret, Daniel; de Vries, Ronald P; Battaglia, Evy; Coutinho, Pedro M; Danchin, Etienne Gj; Henrissat, Bernard; Khoury, Riyad El; Sainsard-Chanet, Annie; Boivin, Antoine; Pinan-Lucarré, Bérangère; Sellem, Carole H; Debuchy, Robert; Wincker, Patrick; Weissenbach, Jean; Silar, Philippe

    2008-01-01

    BACKGROUND: The dung-inhabiting ascomycete fungus Podospora anserina is a model used to study various aspects of eukaryotic and fungal biology, such as ageing, prions and sexual development. RESULTS: We present a 10X draft sequence of P. anserina genome, linked to the sequences of a large expressed

  4. Genomic profiling of inflammatory breast cancer: a review.

    Science.gov (United States)

    Bertucci, François; Finetti, Pascal; Vermeulen, Peter; Van Dam, Peter; Dirix, Luc; Birnbaum, Daniel; Viens, Patrice; Van Laere, Steven

    2014-10-01

    Inflammatory breast cancer (IBC) is a rare but aggressive form of breast cancer. Despite efforts in the past decade to delineate the molecular biology of IBC by applying high-throughput molecular profiling technologies to clinical samples, IBC remains insufficiently characterized. The reasons for that include limited sizes of the study population, heterogeneity with respect to the composition of the IBC and non-IBC control groups and technological differences across studies. In 2008, the World IBC Consortium was founded to foster collaboration between research groups focusing on IBC. One of the initial projects was to redefine the molecular profile of IBC using an unprecedented number of samples and search for gene signatures associated with survival and response to neo-adjuvant chemotherapy. Here, we provide an overview of all the molecular profiling studies that have been performed on IBC clinical samples to date.

  5. Unique Genomic Alterations in Prostate Cancers in African American Men

    Science.gov (United States)

    2015-12-01

    with MNX1 mRNA in AA PCa by Pearson Product Moment. Correlation coefficient and p-value are shown. 13 Subtask 6: Validation of key gene...associated with aggressive pathological features (high Gleason score , seminal vesicle invasion and extracapsular extension). Figure 6. Expression of...was seen in stromal tissues. C, D. Weak expression of MNX1 mRNA in prostate cancer cells (arrowheads). Subtask 4: Correlate expression

  6. Laboratory animal models for esophageal cancer

    Directory of Open Access Journals (Sweden)

    Dhanya Venugopalan Nair

    2016-11-01

    Full Text Available The incidence of esophageal cancer is rapidly increasing especially in developing countries. The major risk factors include unhealthy lifestyle practices such as alcohol consumption, smoking, and chewing tobacco to name a few. Diagnosis at an advanced stage and poor prognosis make esophageal cancer one of the most lethal diseases. These factors have urged further research in understanding the pathophysiology of the disease. Animal models not only aid in understanding the molecular pathogenesis of esophageal cancer but also help in developing therapeutic interventions for the disease. This review throws light on the various recent laboratory animal models for esophageal cancer.

  7. Identification of chromosome aberrations in sporadic microsatellite stable and unstable colorectal cancers using array comparative genomic hybridization

    DEFF Research Database (Denmark)

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

    2011-01-01

    Colorectal cancer (CRC) is one of the most common cancers in Denmark and in the western world in general, and the prognosis is generally poor. According to the traditional molecular classification of sporadic colorectal cancer, microsatellite stable (MSS)/chromosome unstable (CIN) colorectal...... cancers constitute approximately 85% of sporadic cases, whereas microsatellite unstable (MSI) cases constitute the remaining 15%. In this study, we used array comparative genomic hybridization (aCGH) to identify genomic hotspot regions that harbor recurrent copy number changes. The study material...

  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. 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.

  10. 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.

  11. Genome-wide interaction study of smoking and bladder cancer risk

    Science.gov (United States)

    Figueroa, Jonine D.; Han, Summer S.; Garcia-Closas, Montserrat; Baris, Dalsu; Jacobs, Eric J.; Kogevinas, Manolis; Schwenn, Molly; Malats, Nuria; Johnson, Alison; Purdue, Mark P.; Caporaso, Neil; Landi, Maria Teresa; Prokunina-Olsson, Ludmila; Wang, Zhaoming; Hutchinson, Amy; Burdette, Laurie; Wheeler, William; Vineis, Paolo; Siddiq, Afshan; Cortessis, Victoria K.; Kooperberg, Charles; Cussenot, Olivier; Benhamou, Simone; Prescott, Jennifer; Porru, Stefano; Bueno-de-Mesquita, H.Bas; Trichopoulos, Dimitrios; Ljungberg, Börje; Clavel-Chapelon, Françoise; Weiderpass, Elisabete; Krogh, Vittorio; Dorronsoro, Miren; Travis, Ruth; Tjønneland, Anne; Brenan, Paul; Chang-Claude, Jenny; Riboli, Elio; Conti, David; Gago-Dominguez, Manuela; Stern, Mariana C.; Pike, Malcolm C.; Van Den Berg, David; Yuan, Jian-Min; Hohensee, Chancellor; Rodabough, Rebecca; Cancel-Tassin, Geraldine; Roupret, Morgan; Comperat, Eva; Chen, Constance; De Vivo, Immaculata; Giovannucci, Edward; Hunter, David J.; Kraft, Peter; Lindstrom, Sara; Carta, Angela; Pavanello, Sofia; Arici, Cecilia; Mastrangelo, Giuseppe; Karagas, Margaret R.; Schned, Alan; Armenti, Karla R.; Hosain, G.M.Monawar; Haiman, Chris A.; Fraumeni, Joseph F.; Chanock, Stephen J.; Chatterjee, Nilanjan; Rothman, Nathaniel; Silverman, Debra T.

    2014-01-01

    Bladder cancer is a complex disease with known environmental and genetic risk factors. We performed a genome-wide interaction study (GWAS) of smoking and bladder cancer risk based on primary scan data from 3002 cases and 4411 controls from the National Cancer Institute Bladder Cancer GWAS. Alternative methods were used to evaluate both additive and multiplicative interactions between individual single nucleotide polymorphisms (SNPs) and smoking exposure. SNPs with interaction P values < 5 × 10− 5 were evaluated further in an independent dataset of 2422 bladder cancer cases and 5751 controls. We identified 10 SNPs that showed association in a consistent manner with the initial dataset and in the combined dataset, providing evidence of interaction with tobacco use. Further, two of these novel SNPs showed strong evidence of association with bladder cancer in tobacco use subgroups that approached genome-wide significance. Specifically, rs1711973 (FOXF2) on 6p25.3 was a susceptibility SNP for never smokers [combined odds ratio (OR) = 1.34, 95% confidence interval (CI) = 1.20–1.50, P value = 5.18 × 10− 7]; and rs12216499 (RSPH3-TAGAP-EZR) on 6q25.3 was a susceptibility SNP for ever smokers (combined OR = 0.75, 95% CI = 0.67–0.84, P value = 6.35 × 10− 7). In our analysis of smoking and bladder cancer, the tests for multiplicative interaction seemed to more commonly identify susceptibility loci with associations in never smokers, whereas the additive interaction analysis identified more loci with associations among smokers—including the known smoking and NAT2 acetylation interaction. Our findings provide additional evidence of gene–environment interactions for tobacco and bladder cancer. PMID:24662972

  12. 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.

  13. 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.

  14. 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.

  15. 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.

  16. BaalChIP: Bayesian analysis of allele-specific transcription factor binding in cancer genomes.

    Science.gov (United States)

    de Santiago, Ines; Liu, Wei; Yuan, Ke; O'Reilly, Martin; Chilamakuri, Chandra Sekhar Reddy; Ponder, Bruce A J; Meyer, Kerstin B; Markowetz, Florian

    2017-02-24

    Allele-specific measurements of transcription factor binding from ChIP-seq data are key to dissecting the allelic effects of non-coding variants and their contribution to phenotypic diversity. However, most methods of detecting an allelic imbalance assume diploid genomes. This assumption severely limits their applicability to cancer samples with frequent DNA copy-number changes. Here we present a Bayesian statistical approach called BaalChIP to correct for the effect of background allele frequency on the observed ChIP-seq read counts. BaalChIP allows the joint analysis of multiple ChIP-seq samples across a single variant and outperforms competing approaches in simulations. Using 548 ENCODE ChIP-seq and six targeted FAIRE-seq samples, we show that BaalChIP effectively corrects allele-specific analysis for copy-number variation and increases the power to detect putative cis-acting regulatory variants in cancer genomes.

  17. Transmissible [corrected] dog cancer genome reveals the origin and history of an ancient cell lineage.

    Science.gov (United States)

    Murchison, Elizabeth P; Wedge, David C; Alexandrov, Ludmil B; Fu, Beiyuan; Martincorena, Inigo; Ning, Zemin; Tubio, Jose M C; Werner, Emma I; Allen, Jan; De Nardi, Andrigo Barboza; Donelan, Edward M; Marino, Gabriele; Fassati, Ariberto; Campbell, Peter J; Yang, Fengtang; Burt, Austin; Weiss, Robin A; Stratton, Michael R

    2014-01-24

    Canine transmissible venereal tumor (CTVT) is the oldest known somatic cell lineage. It is a transmissible cancer that propagates naturally in dogs. We sequenced the genomes of two CTVT tumors and found that CTVT has acquired 1.9 million somatic substitution mutations and bears evidence of exposure to ultraviolet light. CTVT is remarkably stable and lacks subclonal heterogeneity despite thousands of rearrangements, copy-number changes, and retrotransposon insertions. More than 10,000 genes carry nonsynonymous variants, and 646 genes have been lost. CTVT first arose in a dog with low genomic heterozygosity that may have lived about 11,000 years ago. The cancer spawned by this individual dispersed across continents about 500 years ago. Our results provide a genetic identikit of an ancient dog and demonstrate the robustness of mammalian somatic cells to survive for millennia despite a massive mutation burden.

  18. Ectopic expression of cancer/testis antigen SSX2 induces DNA damage and promotes genomic instability

    DEFF Research Database (Denmark)

    Greve, Katrine Buch Vidén; Lindgreen, Jonas; Terp, Mikkel Green

    2015-01-01

    replication stress translates into mitotic defects and genomic instability. Arrest of cell growth and induction of DNA double-strand breaks was also observed in MCF7 breast cancer cells in response to SSX2 expression. Additionally, MCF7 cells with ectopic SSX2 expression demonstrated typical signs......SSX cancer/testis antigens are frequently expressed in melanoma tumors and represent attractive targets for immunotherapy, but their role in melanoma tumorigenesis has remained elusive. Here, we investigated the cellular effects of SSX2 expression. In A375 melanoma cells, SSX2 expression resulted...... of SSX2 expression in melanoma cell lines demonstrated that SSX2 supports the growth of melanoma cells. Our results reveal two important phenotypes of ectopic SSX2 expression that may drive/support tumorigenesis: First, immediate induction of genomic instability, and second, long-term support of tumor...

  19. 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.

  20. 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.

  1. Generation of mouse models of myeloid malignancy with combinatorial genetic lesions using CRISPR-Cas9 genome editing.

    Science.gov (United States)

    Heckl, Dirk; Kowalczyk, Monika S; Yudovich, David; Belizaire, Roger; Puram, Rishi V; McConkey, Marie E; Thielke, Anne; Aster, Jon C; Regev, Aviv; Ebert, Benjamin L

    2014-09-01

    Genome sequencing studies have shown that human malignancies often bear mutations in four or more driver genes, but it is difficult to recapitulate this degree of genetic complexity in mouse models using conventional breeding. Here we use the CRISPR-Cas9 system of genome editing to overcome this limitation. By delivering combinations of small guide RNAs (sgRNAs) and Cas9 with a lentiviral vector, we modified up to five genes in a single mouse hematopoietic stem cell (HSC), leading to clonal outgrowth and myeloid malignancy. We thereby generated models of acute myeloid leukemia (AML) with cooperating mutations in genes encoding epigenetic modifiers, transcription factors and mediators of cytokine signaling, recapitulating the combinations of mutations observed in patients. Our results suggest that lentivirus-delivered sgRNA:Cas9 genome editing should be useful to engineer a broad array of in vivo cancer models that better reflect the complexity of human disease.

  2. An improved method for detecting and delineating genomic regions with altered gene expression in cancer

    OpenAIRE

    2008-01-01

    Genomic regions with altered gene expression are a characteristic feature of cancer cells. We present a novel method for identifying such regions in gene expression maps. This method is based on total variation minimization, a classical signal restoration technique. In systematic evaluations, we show that our method combines top-notch detection performance with an ability to delineate relevant regions without excessive over-segmentation, making it a significant advance over existing methods. ...

  3. Comprehensive long-span paired-end-tag mapping reveals characteristic patterns of structural variations in epithelial cancer genomes.

    Science.gov (United States)

    Hillmer, Axel M; Yao, Fei; Inaki, Koichiro; Lee, Wah Heng; Ariyaratne, Pramila N; Teo, Audrey S M; Woo, Xing Yi; Zhang, Zhenshui; Zhao, Hao; Ukil, Leena; Chen, Jieqi P; Zhu, Feng; So, Jimmy B Y; Salto-Tellez, Manuel; Poh, Wan Ting; Zawack, Kelson F B; Nagarajan, Niranjan; Gao, Song; Li, Guoliang; Kumar, Vikrant; Lim, Hui Ping J; Sia, Yee Yen; Chan, Chee Seng; Leong, See Ting; Neo, Say Chuan; Choi, Poh Sum D; Thoreau, Hervé; Tan, Patrick B O; Shahab, Atif; Ruan, Xiaoan; Bergh, Jonas; Hall, Per; Cacheux-Rataboul, Valère; Wei, Chia-Lin; Yeoh, Khay Guan; Sung, Wing-Kin; Bourque, Guillaume; Liu, Edison T; Ruan, Yijun

    2011-05-01

    Somatic genome rearrangements are thought to play important roles in cancer development. We optimized a long-span paired-end-tag (PET) sequencing approach using 10-Kb genomic DNA inserts to study human genome structural variations (SVs). The use of a 10-Kb insert size allows the identification of breakpoints within repetitive or homology-containing regions of a few kilobases in size and results in a higher physical coverage compared with small insert libraries with the same sequencing effort. We have applied this approach to comprehensively characterize the SVs of 15 cancer and two noncancer genomes and used a filtering approach to strongly enrich for somatic SVs in the cancer genomes. Our analyses revealed that most inversions, deletions, and insertions are germ-line SVs, whereas tandem duplications, unpaired inversions, interchromosomal translocations, and complex rearrangements are over-represented among somatic rearrangements in cancer genomes. We demonstrate that the quantitative and connective nature of DNA-PET data is precise in delineating the genealogy of complex rearrangement events, we observe signatures that are compatible with breakage-fusion-bridge cycles, and we discover that large duplications are among the initial rearrangements that trigger genome instability for extensive amplification in epithelial cancers.

  4. 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

  5. 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

  6. 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.

  7. 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.

  8. Genome Editing and Its Applications in Model Organisms.

    Science.gov (United States)

    Ma, Dongyuan; Liu, Feng

    2015-12-01

    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.

  9. 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.

  10. 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.

  11. Modeling protein network evolution under genome duplication and domain shuffling

    Directory of Open Access Journals (Sweden)

    Isambert Hervé

    2007-11-01

    Full Text Available Abstract Background Successive whole genome duplications have recently been firmly established in all major eukaryote kingdoms. Such exponential evolutionary processes must have largely contributed to shape the topology of protein-protein interaction (PPI networks by outweighing, in particular, all time-linear network growths modeled so far. Results We propose and solve a mathematical model of PPI network evolution under successive genome duplications. This demonstrates, from first principles, that evolutionary conservation and scale-free topology are intrinsically linked properties of PPI networks and emerge from i prevailing exponential network dynamics under duplication and ii asymmetric divergence of gene duplicates. While required, we argue that this asymmetric divergence arises, in fact, spontaneously at the level of protein-binding sites. This supports a refined model of PPI network evolution in terms of protein domains under exponential and asymmetric duplication/divergence dynamics, with multidomain proteins underlying the combinatorial formation of protein complexes. Genome duplication then provides a powerful source of PPI network innovation by promoting local rearrangements of multidomain proteins on a genome wide scale. Yet, we show that the overall conservation and topology of PPI networks are robust to extensive domain shuffling of multidomain proteins as well as to finer details of protein interaction and evolution. Finally, large scale features of direct and indirect PPI networks of S. cerevisiae are well reproduced numerically with only two adjusted parameters of clear biological significance (i.e. network effective growth rate and average number of protein-binding domains per protein. Conclusion This study demonstrates the statistical consequences of genome duplication and domain shuffling on the conservation and topology of PPI networks over a broad evolutionary scale across eukaryote kingdoms. In particular, scale

  12. 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.

  13. 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:

  14. 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.

  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. Genome-scale modeling for metabolic engineering.

    Science.gov (United States)

    Simeonidis, Evangelos; Price, Nathan D

    2015-03-01

    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.

  17. Comparative genomic analysis of primary tumors and metastases in breast cancer.

    Science.gov (United States)

    Bertucci, François; Finetti, Pascal; Guille, Arnaud; Adélaïde, José; Garnier, Séverine; Carbuccia, Nadine; Monneur, Audrey; Charafe-Jauffret, Emmanuelle; Goncalves, Anthony; Viens, Patrice; Birnbaum, Daniel; Chaffanet, Max

    2016-05-10

    Personalized medicine uses genomic information for selecting therapy in patients with metastatic cancer. An issue is the optimal tissue source (primary tumor or metastasis) for testing. We compared the DNA copy number and mutational profiles of primary breast cancers and paired metastases from 23 patients using whole-genome array-comparative genomic hybridization and next-generation sequencing of 365 "cancer-associated" genes. Primary tumors and metastases harbored copy number alterations (CNAs) and mutations common in breast cancer and showed concordant profiles. The global concordance regarding CNAs was shown by clustering and correlation matrix, which showed that each metastasis correlated more strongly with its paired tumor than with other samples. Genes with recurrent amplifications in breast cancer showed 100% (ERBB2, FGFR1), 96% (CCND1), and 88% (MYC) concordance for the amplified/non-amplified status. Among all samples, 499 mutations were identified, including 39 recurrent (AKT1, ERBB2, PIK3CA, TP53) and 460 non-recurrent variants. The tumors/metastases concordance of variants was 75%, higher for recurrent (92%) than for non-recurrent (73%) variants. Further mutational discordance came from very different variant allele frequencies for some variants. We showed that the chosen targeted therapy in two clinical trials of personalized medicine would be concordant in all but one patient (96%) when based on the molecular profiling of tumor and paired metastasis. Our results suggest that the genotyping of primary tumor may be acceptable to guide systemic treatment if the metastatic sample is not obtainable. However, given the rare but potentially relevant divergences for some actionable driver genes, the profiling of metastatic sample is recommended.

  18. 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.

  19. 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

  20. Mouse Tumor Biology (MTB): a database of mouse models for human cancer.

    Science.gov (United States)

    Bult, Carol J; Krupke, Debra M; Begley, Dale A; Richardson, Joel E; Neuhauser, Steven B; Sundberg, John P; Eppig, Janan T

    2015-01-01

    The Mouse Tumor Biology (MTB; http://tumor.informatics.jax.org) database is a unique online compendium of mouse models for human cancer. MTB provides online access to expertly curated information on diverse mouse models for human cancer and interfaces for searching and visualizing data associated with these models. The information in MTB is designed to facilitate the selection of strains for cancer research and is a platform for mining data on tumor development and patterns of metastases. MTB curators acquire data through manual curation of peer-reviewed scientific literature and from direct submissions by researchers. Data in MTB are also obtained from other bioinformatics resources including PathBase, the Gene Expression Omnibus and ArrayExpress. Recent enhancements to MTB improve the association between mouse models and human genes commonly mutated in a variety of cancers as identified in large-scale cancer genomics studies, provide new interfaces for exploring regions of the mouse genome associated with cancer phenotypes and incorporate data and information related to Patient-Derived Xenograft models of human cancers.

  1. Dogs as a Model for Cancer.

    Science.gov (United States)

    Gardner, Heather L; Fenger, Joelle M; London, Cheryl A

    2016-01-01

    Spontaneous cancers in client-owned dogs closely recapitulate their human counterparts with respect to clinical presentation, histological features, molecular profiles, and response and resistance to therapy, as well as the evolution of drug-resistant metastases. In several instances the incorporation of dogs with cancer into the preclinical development path of cancer therapeutics has influenced outcome by helping to establish pharmacokinetic/pharmacodynamics relationships, dose/regimen, expected clinical toxicities, and ultimately the potential for biologic activity. As our understanding regarding the molecular drivers of canine cancers has improved, unique opportunities have emerged to leverage this spontaneous model to better guide cancer drug development so that therapies likely to fail are eliminated earlier and therapies with true potential are optimized prior to human studies. Both pets and people benefit from this approach, as it provides dogs with access to cutting-edge cancer treatments and helps to insure that people are given treatments more likely to succeed.

  2. 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

  3. The Naked Mole Rat Genome Resource: facilitating analyses of cancer and longevity-related adaptations

    Science.gov (United States)

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

    2014-01-01

    Motivation: The naked mole rat (Heterocephalus glaber) is an exceptionally long-lived and cancer-resistant rodent native to East Africa. Although its genome was previously sequenced, here we report a new assembly sequenced by us with substantially higher N50 values for scaffolds and contigs. Results: We analyzed the annotation of this new improved assembly and identified candidate genomic adaptations which may have contributed to the evolution of the naked mole rat’s extraordinary traits, including in regions of p53, and the hyaluronan receptors CD44 and HMMR (RHAMM). Furthermore, we developed a freely available web portal, the Naked Mole Rat Genome Resource (http://www.naked-mole-rat.org), featuring the data and results of our analysis, to assist researchers interested in the genome and genes of the naked mole rat, and also to facilitate further studies on this fascinating species. Availability and implementation: The Naked Mole Rat Genome Resource is freely available online at http://www.naked-mole-rat.org. This resource is open source and the source code is available at https://github.com/maglab/naked-mole-rat-portal. Contact: jp@senescence.info PMID:25172923

  4. 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.

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

    Science.gov (United States)

    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 MJ; Ashton, Katie; Otton, Geoffrey; Proietto, Tony; Liu, Tao; Mints, Miriam; Tham, Emma; Consortium, CHIBCHA; Jun Li, Mulin; 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

    2016-01-01

    We conducted a meta-analysis of three endometrial cancer GWAS and two replication phases totaling 7,737 endometrial cancer cases and 37,144 controls of European ancestry. Genome-wide imputation and meta-analysis identified five novel 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). A second independent 8q24.21 signal (rs17232730) was found. Functional studies of the 13q22.1 locus showed that rs9600103 (pairwise r2=0.98 with rs11841589) is located in a region of active chromatin that interacts with the KLF5 promoter region. The rs9600103-T endometrial cancer protective allele suppressed gene expression in vitro suggesting that regulation of KLF5 expression, 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

  6. 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.

  7. Capturing Genomic Evolution of Lung Cancers through Liquid Biopsy for Circulating Tumor DNA

    Directory of Open Access Journals (Sweden)

    Michael Offin

    2017-01-01

    Full Text Available Genetic sequencing of malignancies has become increasingly important to uncover therapeutic targets and capture the tumor’s dynamic changes to drug sensitivity and resistance through genomic evolution. In lung cancers, the current standard of tissue biopsy at the time of diagnosis and progression is not always feasible or practical and may underestimate intratumoral heterogeneity. Technological advances in genetic sequencing have enabled the use of circulating tumor DNA (ctDNA analysis to obtain information on both targetable mutations and capturing real-time Darwinian evolution of tumor clones and drug resistance mechanisms under selective therapeutic pressure. The ability to analyze ctDNA from plasma, CSF, or urine enables a comprehensive view of cancers as systemic diseases and captures intratumoral heterogeneity. Here, we describe these recent advances in the setting of lung cancers and advocate for further research and the incorporation of ctDNA analysis in clinical trials of targeted therapies. By capturing genomic evolution in a noninvasive manner, liquid biopsy for ctDNA analysis could accelerate therapeutic discovery and deliver the next leap forward in precision medicine for patients with lung cancers and other solid tumors.

  8. 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.

  9. 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

  10. 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

  11. 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...

  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 Analysis Identifies Novel Loci Associated with Ovarian Cancer Outcomes

    DEFF Research Database (Denmark)

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

    2015-01-01

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

  14. 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 a much larger stage 2 set of 4,651 cases and 6,966 controls from the Ovarian Cancer Association Consortium. Given that most of the top 20 SNPs from pooling were validated in the same samples by individual genotyping, the lack of replication is likely to be due to the relatively small sample size in our...... stage 1 GWAS rather than due to problems with the pooling approach. We conclude that there are unlikely to be any moderate or large effects on ovarian cancer risk untagged by less dense arrays. However, our study lacked power to make clear statements on the existence of hitherto untagged small...

  15. 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

  16. 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.

  17. A genome-wide association study identifies a new ovarian cancer susceptibility locus on 9p22.2

    DEFF Research Database (Denmark)

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

    2009-01-01

    Epithelial ovarian cancer has a major heritable component, but the known susceptibility genes explain less than half the excess familial risk. We performed a genome-wide association study (GWAS) to identify common ovarian cancer susceptibility alleles. We evaluated 507,094 SNPs genotyped in 1,817...

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

    DEFF Research Database (Denmark)

    Petrovics, Gyorgy; Li, Hua; Stümpel, Tanja;

    2015-01-01

    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 syst...

  19. 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...

  20. 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

  1. Differential pathway dependency discovery associated with drug response across cancer cell lines. | Office of Cancer Genomics

    Science.gov (United States)

    The effort to personalize treatment plans for cancer patients involves the identification of drug treatments that can effectively target the disease while minimizing the likelihood of adverse reactions. In this study, the gene-expression profile of 810 cancer cell lines and their response data to 368 small molecules from the Cancer Therapeutics Research Portal (CTRP) are analyzed to identify pathways with significant rewiring between genes, or differential gene dependency, between sensitive and non-sensitive cell lines.

  2. 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...... 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....

  3. Genomic profiling of murine mammary tumors identifies potential personalized drug targets for p53-deficient mammary cancers

    Directory of Open Access Journals (Sweden)

    Adam D. Pfefferle

    2016-07-01

    Full Text Available Targeted therapies against basal-like breast tumors, which are typically ‘triple-negative breast cancers (TNBCs’, remain an important unmet clinical need. Somatic TP53 mutations are the most common genetic event in basal-like breast tumors and TNBC. To identify additional drivers and possible drug targets of this subtype, a comparative study between human and murine tumors was performed by utilizing a murine Trp53-null mammary transplant tumor model. We show that two subsets of murine Trp53-null mammary transplant tumors resemble aspects of the human basal-like subtype. DNA-microarray, whole-genome and exome-based sequencing approaches were used to interrogate the secondary genetic aberrations of these tumors, which were then compared to human basal-like tumors to identify conserved somatic genetic features. DNA copy-number variation produced the largest number of conserved candidate personalized drug targets. These candidates were filtered using a DNA-RNA Pearson correlation cut-off and a requirement that the gene was deemed essential in at least 5% of human breast cancer cell lines from an RNA-mediated interference screen database. Five potential personalized drug target genes, which were spontaneously amplified loci in both murine and human basal-like tumors, were identified: Cul4a, Lamp1, Met, Pnpla6 and Tubgcp3. As a proof of concept, inhibition of Met using crizotinib caused Met-amplified murine tumors to initially undergo complete regression. This study identifies Met as a promising drug target in a subset of murine Trp53-null tumors, thus identifying a potential shared driver with a subset of human basal-like breast cancers. Our results also highlight the importance of comparative genomic studies for discovering personalized drug targets and for providing a preclinical model for further investigations of key tumor signaling pathways.

  4. Endocrine-Therapy-Resistant ESR1 Variants Revealed by Genomic Characterization of Breast-Cancer-Derived Xenografts

    Science.gov (United States)

    Li, Shunqiang; Shen, Dong; Shao, Jieya; Crowder, Robert; Liu, Wenbin; Prat, Aleix; He, Xiaping; Liu, Shuying; Hoog, Jeremy; Lu, Charles; Ding, Li; Griffith, Obi L.; Miller, Christopher; Larson, Dave; Fulton, Robert S.; Harrison, Michelle; Mooney, Tom; McMichael, Joshua F.; Luo, Jingqin; Tao, Yu; Goncalves, Rodrigo; Schlosberg, Christopher; Hiken, Jeffrey F.; Saied, Laila; Sanchez, Cesar; Giuntoli, Therese; Bumb, Caroline; Cooper, Crystal; Kitchens, Robert T.; Lin, Austin; Phommaly, Chanpheng; Davies, Sherri R.; Zhang, Jin; Kavuri, Megha Shyam; McEachern, Donna; Dong, Yi Yu; Ma, Cynthia; Pluard, Timothy; Naughton, Michael; Bose, Ron; Suresh, Rama; McDowell, Reida; Michel, Loren; Aft, Rebecca; Gillanders, William; DeSchryver, Katherine; Wilson, Richard K.; Wang, Shaomeng; Mills, Gordon B.; Gonzalez-Angulo, Ana; Edwards, John R.; Maher, Christopher; Perou, Charles M.; Mardis, Elaine R.; Ellis, Matthew J.

    2013-01-01

    SUMMARY 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. PMID:24055055

  5. 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.

  6. 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.

  7. 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.

  8. Integrating Multiscale Modeling with Drug Effects for Cancer Treatment.

    Science.gov (United States)

    Li, Xiangfang L; Oduola, Wasiu O; Qian, Lijun; Dougherty, Edward R

    2015-01-01

    In this paper, we review multiscale modeling for cancer treatment with the incorporation of drug effects from an applied system's pharmacology perspective. Both the classical pharmacology and systems biology are inherently quantitative; however, systems biology focuses more on networks and multi factorial controls over biological processes rather than on drugs and targets in isolation, whereas systems pharmacology has a strong focus on studying drugs with regard to the pharmacokinetic (PK) and pharmacodynamic (PD) relations accompanying drug interactions with multiscale physiology as well as the prediction of dosage-exposure responses and economic potentials of drugs. Thus, it requires multiscale methods to address the need for integrating models from the molecular levels to the cellular, tissue, and organism levels. It is a common belief that tumorigenesis and tumor growth can be best understood and tackled by employing and integrating a multifaceted approach that includes in vivo and in vitro experiments, in silico models, multiscale tumor modeling, continuous/discrete modeling, agent-based modeling, and multiscale modeling with PK/PD drug effect inputs. We provide an example application of multiscale modeling employing stochastic hybrid system for a colon cancer cell line HCT-116 with the application of Lapatinib drug. It is observed that the simulation results are similar to those observed from the setup of the wet-lab experiments at the Translational Genomics Research Institute.

  9. Genome-wide DNA methylation modified by soy phytoestrogens: role for epigenetic therapeutics in prostate cancer?

    Science.gov (United States)

    Karsli-Ceppioglu, Seher; Ngollo, Marjolaine; Adjakly, Mawussi; Dagdemir, Aslihan; Judes, Gaëlle; Lebert, André; Boiteux, Jean-Paul; Penault-LLorca, Frédérique; Bignon, Yves-Jean; Guy, Laurent; Bernard-Gallon, Dominique

    2015-04-01

    In prostate cancer, DNA methylation is significantly associated with tumor initiation, progression, and metastasis. Previous studies have suggested that soy phytoestrogens might regulate DNA methylation at individual candidate gene loci and that they play a crucial role as potential therapeutic agents for prostate cancer. The purpose of our study was to examine the modulation effects of phytoestrogens on a genome-wide scale in regards to DNA methylation in prostate cancer. Prostate cancer cell lines DU-145 and LNCaP were treated with 40 μM of genistein and 110 μM of daidzein. DNMT inhibitor 5-azacytidine (2 μM) and the methylating agent budesonide (2 μM) were used to compare their demethylation/methylation effects with phytoestrogens. The regulatory effects of phytoestrogens on DNA methylation were analyzed by using a methyl-DNA immunoprecipitation method coupled with Human DNA Methylation Microarrays (MeDIP-chip). We observed that the methylation profiles of 58 genes were altered by genistein and daidzein treatments in DU-145 and LNCaP prostate cancer cells. In addition, the methylation frequencies of the MAD1L1, TRAF7, KDM4B, and hTERT genes were remarkably modified by genistein treatment. Our results suggest that the modulation effects of phytoestrogens on DNA methylation essentially lead to inhibition of cell growth and induction of apoptosis. Genome-wide methylation profiling reported here suggests that epigenetic regulation mechanisms and, by extension, epigenetics-driven novel therapeutic candidates warrant further consideration in future "omics" studies of prostate cancer.

  10. Skeletal muscle mitochondrial uncoupling in a murine cancer cachexia model.

    Science.gov (United States)

    Tzika, A Aria; Fontes-Oliveira, Cibely Cristine; Shestov, Alexander A; Constantinou, Caterina; Psychogios, Nikolaos; Righi, Valeria; Mintzopoulos, Dionyssios; Busquets, Silvia; Lopez-Soriano, Francisco J; Milot, Sylvain; Lepine, Francois; Mindrinos, Michael N; Rahme, Laurence G; Argiles, Josep M

    2013-09-01

    Approximately half of all cancer patients present with cachexia, a condition in which disease-associated metabolic changes lead to a severe loss of skeletal muscle mass. Working toward an integrated and mechanistic view of cancer cachexia, we investigated the hypothesis that cancer promotes mitochondrial uncoupling in skeletal muscle. We subjected mice to in vivo phosphorous-31 nuclear magnetic resonance (31P NMR) spectroscopy and subjected murine skeletal muscle samples to gas chromatography/mass spectrometry (GC/MS). The mice used in both experiments were Lewis lung carcinoma models of cancer cachexia. A novel 'fragmented mass isotopomer' approach was used in our dynamic analysis of 13C mass isotopomer data. Our 31P NMR and GC/MS results indicated that the adenosine triphosphate (ATP) synthesis rate and tricarboxylic acid (TCA) cycle flux were reduced by 49% and 22%, respectively, in the cancer-bearing mice (p<0.008; t-test vs. controls). The ratio of ATP synthesis rate to the TCA cycle flux (an index of mitochondrial coupling) was reduced by 32% in the cancer-bearing mice (p=0.036; t-test vs. controls). Genomic analysis revealed aberrant expression levels for key regulatory genes and transmission electron microscopy (TEM) revealed ultrastructural abnormalities in the muscle fiber, consistent with the presence of abnormal, giant mitochondria. Taken together, these data suggest that mitochondrial uncoupling occurs in cancer cachexia and thus point to the mitochondria as a potential pharmaceutical target for the treatment of cachexia. These findings may prove relevant to elucidating the mechanisms underlying skeletal muscle wasting observed in other chronic diseases, as well as in aging.

  11. 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

    2015-10-01

    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.

  12. 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.

  13. Frontiers in cancer epidemiology: a challenge to the research community from the Epidemiology and Genomics Research Program at the National Cancer Institute.

    Science.gov (United States)

    Khoury, Muin J; Freedman, Andrew N; Gillanders, Elizabeth M; Harvey, Chinonye E; Kaefer, Christie; Reid, Britt C; Rogers, Scott; Schully, Sheri D; Seminara, Daniela; Verma, Mukesh

    2012-07-01

    The Epidemiology and Genomics Research Program (EGRP) at the National Cancer Institute (NCI) is developing scientific priorities for cancer epidemiology research in the next decade. We would like to engage the research community and other stakeholders in a planning effort that will include a workshop in December 2012 to help shape new foci for cancer epidemiology research. To facilitate the process of defining the future of cancer epidemiology, we invite the research community to join in an ongoing web-based conversation at http://blog-epi.grants.cancer.gov/ to develop priorities and the next generation of high-impact studies.

  14. 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.

  15. Computational Modelling in Cancer: Methods and Applications

    Directory of Open Access Journals (Sweden)

    Konstantina Kourou

    2015-01-01

    Full Text Available Computational modelling of diseases is an emerging field, proven valuable for the diagnosis, prognosis and treatment of the disease. Cancer is one of the diseases where computational modelling provides enormous advancements, allowing the medical professionals to perform in silico experiments and gain insights prior to any in vivo procedure. In this paper, we review the most recent computational models that have been proposed for cancer. Well known databases used for computational modelling experiments, as well as, the various markup language representations are discussed. In addition, recent state of the art research studies related to tumour growth and angiogenesis modelling are presented.

  16. 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.

  17. 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.

  18. 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.

  19. 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.

  20. Whole-genome sequencing analysis of phenotypic heterogeneity and anticipation in Li–Fraumeni cancer predisposition syndrome

    OpenAIRE

    Ariffin, Hany; Hainaut,Pierre; Puzio-Kuter, Anna; Choong, Soo Sin; Chan, Adelyne Sue Li; Tolkunov, Denis; Rajagopal, Gunaretnam; Kang, Wenfeng; Lim, Leon Li Wen; Krishnan, Shekhar; Chen, Kok-Siong; Achatz, Maria Isabel; Karsa, Mawar; Shamsani, Jannah; Levine, Arnold J.

    2014-01-01

    Germ-line mutation in the tumor suppressor TP53 causes Li–Fraumeni syndrome (LFS), a complex predisposition to multiple cancers. Types of cancers and ages at diagnosis vary among subjects and families, with apparent genetic anticipation: i.e., earlier cancer onset with successive generations. It has been proposed that anticipation is caused by accumulation of copy-number variations (CNV) in a context of TP53 haploinsufficiency. Using genome/exome sequencing, we found no evidence of increased ...

  1. 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.

  2. Tracking Genomic Cancer Evolution for Precision Medicine: The Lung TRACERx Study

    Science.gov (United States)

    Jamal-Hanjani, Mariam; Hackshaw, Alan; Ngai, Yenting; Shaw, Jacqueline; Dive, Caroline; Quezada, Sergio; Middleton, Gary; de Bruin, Elza; Le Quesne, John; Shafi, Seema; Falzon, Mary; Horswell, Stuart; Blackhall, Fiona; Khan, Iftekhar; Janes, Sam; Nicolson, Marianne; Lawrence, David; Forster, Martin; Fennell, Dean; Lee, Siow-Ming; Lester, Jason; Kerr, Keith; Muller, Salli; Iles, Natasha; Smith, Sean; Murugaesu, Nirupa; Mitter, Richard; Salm, Max; Stuart, Aengus; Matthews, Nik; Adams, Haydn; Ahmad, Tanya; Attanoos, Richard; Bennett, Jonathan; Birkbak, Nicolai Juul; Booton, Richard; Brady, Ged; Buchan, Keith; Capitano, Arrigo; Chetty, Mahendran; Cobbold, Mark; Crosbie, Philip; Davies, Helen; Denison, Alan; Djearman, Madhav; Goldman, Jacki; Haswell, Tom; Joseph, Leena; Kornaszewska, Malgorzata; Krebs, Matthew; Langman, Gerald; MacKenzie, Mairead; Millar, Joy; Morgan, Bruno; Naidu, Babu; Nonaka, Daisuke; Peggs, Karl; Pritchard, Catrin; Remmen, Hardy; Rowan, Andrew; Shah, Rajesh; Smith, Elaine; Summers, Yvonne; Taylor, Magali; Veeriah, Selvaraju; Waller, David; Wilcox, Ben; Wilcox, Maggie; Woolhouse, Ian; McGranahan, Nicholas; Swanton, Charles

    2014-01-01

    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. PMID:25003521

  3. 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.

  4. [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.

  5. Ecological genomics meets community-level modelling of biodiversity: mapping the genomic landscape of current and future environmental adaptation.

    Science.gov (United States)

    Fitzpatrick, Matthew C; Keller, Stephen R

    2015-01-01

    Local adaptation is a central feature of most species occupying spatially heterogeneous environments, and may factor critically in responses to environmental change. However, most efforts to model the response of species to climate change ignore intraspecific variation due to local adaptation. Here, we present a new perspective on spatial modelling of organism-environment relationships that combines genomic data and community-level modelling to develop scenarios regarding the geographic distribution of genomic variation in response to environmental change. Rather than modelling species within communities, we use these techniques to model large numbers of loci across genomes. Using balsam poplar (Populus balsamifera) as a case study, we demonstrate how our framework can accommodate nonlinear responses of loci to environmental gradients. We identify a threshold response to temperature in the circadian clock gene GIGANTEA-5 (GI5), suggesting that this gene has experienced strong local adaptation to temperature. We also demonstrate how these methods can map ecological adaptation from genomic data, including the identification of predicted differences in the genetic composition of populations under current and future climates. Community-level modelling of genomic variation represents an important advance in landscape genomics and spatial modelling of biodiversity that moves beyond species-level assessments of climate change vulnerability.

  6. Genomic pathways modulated by Twist in breast cancer

    OpenAIRE

    Vesuna, Farhad; Bergman, Yehudit; Raman, Venu

    2017-01-01

    Background The basic helix-loop-helix transcription factor TWIST1 (Twist) is involved in embryonic cell lineage determination and mesodermal differentiation. There is evidence to indicate that Twist expression plays a role in breast tumor formation and metastasis, but the role of Twist in dysregulating pathways that drive the metastatic cascade is unclear. Moreover, many of the genes and pathways dysregulated by Twist in cell lines and mouse models have not been validated against data obtaine...

  7. An object model for genome information at all levels of resolution

    Energy Technology Data Exchange (ETDEWEB)

    Honda, S.; Parrott, N.W.; Smith, R.; Lawrence, C.

    1993-12-31

    An object model for genome data at all levels of resolution is described. The model was derived by considering the requirements for representing genome related objects in three application domains: genome maps, large-scale DNA sequencing, and exploring functional information in gene and protein sequences. The methodology used for the object-oriented analysis is also described.

  8. 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.

  9. 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

  10. 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

  11. 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

  12. 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.

  13. Copy number analysis identifies novel interactions between genomic loci in ovarian cancer.

    Directory of Open Access Journals (Sweden)

    Kylie L Gorringe

    Full Text Available Ovarian cancer is a heterogeneous disease displaying complex genomic alterations, and consequently, it has been difficult to determine the most relevant copy number alterations with the scale of studies to date. We obtained genome-wide copy number alteration (CNA data from four different SNP array platforms, with a final data set of 398 ovarian tumours, mostly of the serous histological subtype. Frequent CNA aberrations targeted many thousands of genes. However, high-level amplicons and homozygous deletions enabled filtering of this list to the most relevant. The large data set enabled refinement of minimal regions and identification of rare amplicons such as at 1p34 and 20q11. We performed a novel co-occurrence analysis to assess cooperation and exclusivity of CNAs and analysed their relationship to patient outcome. Positive associations were identified between gains on 19 and 20q, gain of 20q and loss of X, and between several regions of loss, particularly 17q. We found weak correlations of CNA at genomic loci such as 19q12 with clinical outcome. We also assessed genomic instability measures and found a correlation of the number of higher amplitude gains with poorer overall survival. By assembling the largest collection of ovarian copy number data to date, we have been able to identify the most frequent aberrations and their interactions.

  14. Copy number analysis identifies novel interactions between genomic loci in ovarian cancer.

    Science.gov (United States)

    Gorringe, Kylie L; George, Joshy; Anglesio, Michael S; Ramakrishna, Manasa; Etemadmoghadam, Dariush; Cowin, Prue; Sridhar, Anita; Williams, Louise H; Boyle, Samantha E; Yanaihara, Nozomu; Okamoto, Aikou; Urashima, Mitsuyoshi; Smyth, Gordon K; Campbell, Ian G; Bowtell, David D L

    2010-09-10

    Ovarian cancer is a heterogeneous disease displaying complex genomic alterations, and consequently, it has been difficult to determine the most relevant copy number alterations with the scale of studies to date. We obtained genome-wide copy number alteration (CNA) data from four different SNP array platforms, with a final data set of 398 ovarian tumours, mostly of the serous histological subtype. Frequent CNA aberrations targeted many thousands of genes. However, high-level amplicons and homozygous deletions enabled filtering of this list to the most relevant. The large data set enabled refinement of minimal regions and identification of rare amplicons such as at 1p34 and 20q11. We performed a novel co-occurrence analysis to assess cooperation and exclusivity of CNAs and analysed their relationship to patient outcome. Positive associations were identified between gains on 19 and 20q, gain of 20q and loss of X, and between several regions of loss, particularly 17q. We found weak correlations of CNA at genomic loci such as 19q12 with clinical outcome. We also assessed genomic instability measures and found a correlation of the number of higher amplitude gains with poorer overall survival. By assembling the largest collection of ovarian copy number data to date, we have been able to identify the most frequent aberrations and their interactions.

  15. 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

  16. Genome remodelling in a basal-like breast cancer metastasis and xenograft.

    Science.gov (United States)

    Ding, Li; Ellis, Matthew J; Li, Shunqiang; Larson, David E; Chen, Ken; Wallis, John W; Harris, Christopher C; McLellan, Michael D; Fulton, Robert S; Fulton, Lucinda L; Abbott, Rachel M; Hoog, Jeremy; Dooling, David J; Koboldt, Daniel C; Schmidt, Heather; Kalicki, Joelle; Zhang, Qunyuan; Chen, Lei; Lin, Ling; Wendl, Michael C; McMichael, Joshua F; Magrini, Vincent J; Cook, Lisa; McGrath, Sean D; Vickery, Tammi L; Appelbaum, Elizabeth; Deschryver, Katherine; Davies, Sherri; Guintoli, Therese; Lin, Li; Crowder, Robert; Tao, Yu; Snider, Jacqueline E; Smith, Scott M; Dukes, Adam F; Sanderson, Gabriel E; Pohl, Craig S; Delehaunty, Kim D; Fronick, Catrina C; Pape, Kimberley A; Reed, Jerry S; Robinson, Jody S; Hodges, Jennifer S; Schierding, William; Dees, Nathan D; Shen, Dong; Locke, Devin P; Wiechert, Madeline E; Eldred, James M; Peck, Josh B; Oberkfell, Benjamin J; Lolofie, Justin T; Du, Feiyu; Hawkins, Amy E; O'Laughlin, Michelle D; Bernard, Kelly E; Cunningham, Mark; Elliott, Glendoria; Mason, Mark D; Thompson, Dominic M; Ivanovich, Jennifer L; Goodfellow, Paul J; Perou, Charles M; Weinstock, George M; Aft, Rebecca; Watson, Mark; Ley, Timothy J; Wilson, Richard K; Mardis, Elaine R

    2010-04-15

    Massively parallel DNA sequencing technologies provide an unprecedented ability to screen entire genomes for genetic changes associated with tumour progression. Here we describe the genomic analyses of four DNA samples from an African-American patient with basal-like breast cancer: peripheral blood, the primary tumour, a brain metastasis and a xenograft derived from the primary tumour. The metastasis contained two de novo mutations and a large deletion not present in the primary tumour, and was significantly enriched for 20 shared mutations. The xenograft retained all primary tumour mutations and displayed a mutation enrichment pattern that resembled the metastasis. Two overlapping large deletions, encompassing CTNNA1, were present in all three tumour samples. The differential mutation frequencies and structural variation patterns in metastasis and xenograft compared with the primary tumour indicate that secondary tumours may arise from a minority of cells within the primary tumour.

  17. Hypoxia in models of lung cancer

    DEFF Research Database (Denmark)

    Graves, Edward E; Vilalta, Marta; Cecic, Ivana K

    2010-01-01

    PURPOSE: To efficiently translate experimental methods from bench to bedside, it is imperative that laboratory models of cancer mimic human disease as closely as possible. In this study, we sought to compare patterns of hypoxia in several standard and emerging mouse models of lung cancer...... to establish the appropriateness of each for evaluating the role of oxygen in lung cancer progression and therapeutic response. EXPERIMENTAL DESIGN: Subcutaneous and orthotopic human A549 lung carcinomas growing in nude mice as well as spontaneous K-ras or Myc-induced lung tumors grown in situ......H2AX foci in vitro and in vivo. Finally, our findings were compared with oxygen electrode measurements of human lung cancers. RESULTS: Minimal fluoroazomycin arabinoside and pimonidazole accumulation was seen in tumors growing within the lungs, whereas subcutaneous tumors showed substantial trapping...

  18. Identification of genetic determinants of breast cancer immune phenotypes by integrative genome-scale analysis

    Science.gov (United States)

    Simeone, Ines; Anjum, Samreen; Mokrab, Younes; Bertucci, François; Finetti, Pascal; Curigliano, Giuseppe; Cerulo, Luigi; Tomei, Sara; Delogu, Lucia Gemma; Maccalli, Cristina; Miller, Lance D.; Ceccarelli, Michele

    2017-01-01

    ABSTRACT Cancer immunotherapy is revolutionizing the clinical management of several tumors, but has demonstrated limited activity in breast cancer. The development of more effective treatments is hindered by incomplete knowledge of the genetic determinant of immune responsiveness. To fill this gap, we mined copy number alteration, somatic mutation, and expression data from The Cancer Genome Atlas (TCGA). By using RNA-sequencing data from 1,004 breast cancers, we defined distinct immune phenotypes characterized by progressive expression of transcripts previously associated with immune-mediated rejection. The T helper 1 (Th-1) phenotype (ICR4), which also displays upregulation of immune-regulatory transcripts such as PDL1, PD1, FOXP3, IDO1, and CTLA4, was associated with prolonged patients' survival. We validated these findings in an independent meta-cohort of 1,954 breast cancer gene expression data. Chromosome segment 4q21, which includes genes encoding for the Th-1 chemokines CXCL9-11, was significantly amplified only in the immune favorable phenotype (ICR4). The mutation and neoantigen load progressively decreased from ICR4 to ICR1 but could not fully explain immune phenotypic differences. Mutations of TP53 were enriched in the immune favorable phenotype (ICR4). Conversely, the presence of MAP3K1 and MAP2K4 mutations were tightly associated with an immune-unfavorable phenotype (ICR1). Using both the TCGA and the validation dataset, the degree of MAPK deregulation segregates breast tumors according to their immune disposition. These findings suggest that mutation-driven perturbations of MAPK pathways are linked to the negative regulation of intratumoral immune response in breast cancer. Modulations of MAPK pathways could be experimentally tested to enhance breast cancer immune sensitivity. PMID:28344865

  19. 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

  20. Genome-wide association analyses identify new susceptibility loci for oral cavity and pharyngeal cancer.

    Science.gov (United States)

    Lesseur, Corina; Diergaarde, Brenda; Olshan, Andrew F; Wünsch-Filho, Victor; Ness, Andrew R; Liu, Geoffrey; Lacko, Martin; Eluf-Neto, José; Franceschi, Silvia; Lagiou, Pagona; Macfarlane, Gary J; Richiardi, Lorenzo; Boccia, Stefania; Polesel, Jerry; Kjaerheim, Kristina; Zaridze, David; Johansson, Mattias; Menezes, Ana M; Curado, Maria Paula; Robinson, Max; Ahrens, Wolfgang; Canova, Cristina; Znaor, Ariana; Castellsagué, Xavier; Conway, David I; Holcátová, Ivana; Mates, Dana; Vilensky, Marta; Healy, Claire M; Szeszenia-Dąbrowska, Neonila; Fabiánová, Eleonóra; Lissowska, Jolanta; Grandis, Jennifer R; Weissler, Mark C; Tajara, Eloiza H; Nunes, Fabio D; de Carvalho, Marcos B; Thomas, Steve; Hung, Rayjean J; Peters, Wilbert H M; Herrero, Rolando; Cadoni, Gabriella; Bueno-de-Mesquita, H Bas; Steffen, Annika; Agudo, Antonio; Shangina, Oxana; Xiao, Xiangjun; Gaborieau, Valérie; Chabrier, Amélie; Anantharaman, Devasena; Boffetta, Paolo; Amos, Christopher I; McKay, James D; Brennan, Paul

    2016-12-01

    We conducted a genome-wide association study of oral cavity and pharyngeal cancer in 6,034 cases and 6,585 controls from Europe, North America and South America. We detected eight significantly associated loci (P < 5 × 10(-8)), seven of which are new for these cancer sites. Oral and pharyngeal cancers combined were associated with loci at 6p21.32 (rs3828805, HLA-DQB1), 10q26.13 (rs201982221, LHPP) and 11p15.4 (rs1453414, OR52N2-TRIM5). Oral cancer was associated with two new regions, 2p23.3 (rs6547741, GPN1) and 9q34.12 (rs928674, LAMC3), and with known cancer-related loci-9p21.3 (rs8181047, CDKN2B-AS1) and 5p15.33 (rs10462706, CLPTM1L). Oropharyngeal cancer associations were limited to the human leukocyte antigen (HLA) region, and classical HLA allele imputation showed a protective association with the class II haplotype HLA-DRB1*1301-HLA-DQA1*0103-HLA-DQB1*0603 (odds ratio (OR) = 0.59, P = 2.7 × 10(-9)). Stratified analyses on a subgroup of oropharyngeal cases with information available on human papillomavirus (HPV) status indicated that this association was considerably stronger in HPV-positive (OR = 0.23, P = 1.6 × 10(-6)) than in HPV-negative (OR = 0.75, P = 0.16) cancers.

  1. 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.

  2. High-resolution comparative genomic hybridization of inflammatory breast cancer and identification of candidate genes.

    Directory of Open Access Journals (Sweden)

    Ismahane Bekhouche

    Full Text Available 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 relatively close. However, IBCs showed more frequent "complex" patterns and a higher percentage of genes with CNAs per sample. The number of altered regions was similar in both types, although some regions were altered more frequently and/or with higher amplitude in IBCs. Many genes were similarly altered in both types; however, more genes displayed recurrent amplifications in IBCs. The percentage of genes whose mRNA expression correlated with CNAs was similar in both types for the gained genes, but ∼7-fold lower in IBCs for the lost genes. Integrated analysis identified 24 potential candidate IBC-specific genes. Their combined expression accurately distinguished IBCs and nIBCS in an independent validation set, and retained an independent prognostic value in a series of 1,781 nIBCs, reinforcing the hypothesis for a link with IBC aggressiveness. Consistent with the hyperproliferative and invasive phenotype of IBC these genes are notably involved in protein translation, cell cycle, RNA processing and transcription, metabolism, and cell migration. CONCLUSIONS: Our results suggest a higher genomic instability of IBC. We established the first repertory of DNA copy number alterations in this tumor, and provided a list of genes that may contribute to its aggressiveness and represent novel therapeutic targets.

  3. 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

  4. 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.

  5. 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.

  6. 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.

  7. Next-generation genome-scale models for metabolic engineering.

    Science.gov (United States)

    King, Zachary A; Lloyd, Colton J; Feist, Adam M; Palsson, Bernhard O

    2015-12-01

    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.

  8. Genome-wide association study identifies novel breast cancer susceptibility loci

    Science.gov (United States)

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

    2009-01-01

    Breast cancer exhibits familial aggregation, consistent with variation in genetic susceptibility to the disease. Known susceptibility genes account for less than 25% of the familial risk of breast cancer, and the residual genetic variance is likely to be due to variants conferring more moderate risks. To identify further susceptibility alleles, we conducted a two-stage genome-wide association study in 4,398 breast cancer cases and 4,316 controls, followed by a third stage in which 30 single nucleotide polymorphisms (SNPs) were tested for confirmation in 21,860 cases and 22,578 controls from 22 studies. We used 227,876 SNPs that were estimated to correlate with 77% of known common SNPs in Europeans at r2>0.5. SNPs in five novel independent loci exhibited strong and consistent evidence of association with breast cancer (P<10−7). Four of these contain plausible causative genes (FGFR2, TNRC9, MAP3K1 and LSP1). At the second stage, 1,792 SNPs were significant at the P<0.05 level compared with an estimated 1,343 that would be expected by chance, indicating that many additional common susceptibility alleles may be identifiable by this approach. PMID:17529967

  9. Degradation of the cancer genomic DNA deaminase APOBEC3B by SIV Vif.

    Science.gov (United States)

    Land, Allison M; Wang, Jiayi; Law, Emily K; Aberle, Ryan; Kirmaier, Andrea; Krupp, Annabel; Johnson, Welkin E; Harris, Reuben S

    2015-11-24

    APOBEC3B is a newly identified source of mutation in many cancers, including breast, head/neck, lung, bladder, cervical, and ovarian. APOBEC3B is a member of the APOBEC3 family of enzymes that deaminate DNA cytosine to produce the pro-mutagenic lesion, uracil. Several APOBEC3 family members function to restrict virus replication. For instance, APOBEC3D, APOBEC3F, APOBEC3G, and APOBEC3H combine to restrict HIV-1 in human lymphocytes. HIV-1 counteracts these APOBEC3s with the viral protein Vif, which targets the relevant APOBEC3s for proteasomal degradation. While APOBEC3B does not restrict HIV-1 and is not targeted by HIV-1 Vif in CD4-positive T cells, we asked whether related lentiviral Vif proteins could degrade APOBEC3B. Interestingly, several SIV Vif proteins are capable of promoting APOBEC3B degradation, with SIVmac239 Vif proving the most potent. This likely occurs through the canonical polyubiquitination mechanism as APOBEC3B protein levels are restored by MG132 treatment and by altering a conserved E3 ligase-binding motif. We further show that SIVmac239 Vif can prevent APOBEC3B mediated geno/cytotoxicity and degrade endogenous APOBEC3B in several cancer cell lines. Our data indicate that the APOBEC3B degradation potential of SIV Vif is an effective tool for neutralizing the cancer genomic DNA deaminase APOBEC3B. Further optimization of this natural APOBEC3 antagonist may benefit cancer therapy.

  10. Pathway analysis for genome-wide association study of lung cancer in Han Chinese population.

    Directory of Open Access Journals (Sweden)

    Ruyang Zhang

    Full Text Available Genome-wide association studies (GWAS have identified a number of genetic variants associated with lung cancer risk. However, these loci explain only a small fraction of lung cancer hereditability and other variants with weak effect may be lost in the GWAS approach due to the stringent significance level after multiple comparison correction. In this study, in order to identify important pathways involving the lung carcinogenesis, we performed a two-stage pathway analysis in GWAS of lung cancer in Han Chinese using gene set enrichment analysis (GSEA method. Predefined pathways by BioCarta and KEGG databases were systematically evaluated on Nanjing study (Discovery stage: 1,473 cases and 1,962 controls and the suggestive pathways were further to be validated in Beijing study (Replication stage: 858 cases and 1,115 controls. We found that four pathways (achPathway, metPathway, At1rPathway and rac1Pathway were consistently significant in both studies and the P values for combined dataset were 0.012, 0.010, 0.022 and 0.005 respectively. These results were stable after sensitivity analysis based on gene definition and gene overlaps between pathways. These findings may provide new insights into the etiology of lung cancer.

  11. 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.

  12. 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.

  13. Genome-wide analysis of the homeobox C6 transcriptional network in prostate cancer.

    Science.gov (United States)

    McCabe, Colleen D; Spyropoulos, Demetri D; Martin, David; Moreno, Carlos S

    2008-03-15

    Homeobox transcription factors are developmentally regulated genes that play crucial roles in tissue patterning. Homeobox C6 (HOXC6) is overexpressed in prostate cancers and correlated with cancer progression, but the downstream targets of HOXC6 are largely unknown. We have performed genome-wide localization analysis to identify promoters bound by HOXC6 in prostate cancer cells. This analysis identified 468 reproducibly bound promoters whose associated genes are involved in functions such as cell proliferation and apoptosis. We have complemented these data with expression profiling of prostates from mice with homozygous disruption of the Hoxc6 gene to identify 31 direct regulatory target genes of HOXC6. We show that HOXC6 directly regulates expression of bone morphogenic protein 7, fibroblast growth factor receptor 2, insulin-like growth factor binding protein 3, and platelet-derived growth factor receptor alpha (PDGFRA) in prostate cells and indirectly influences the Notch and Wnt signaling pathways in vivo. We further show that inhibition of PDGFRA reduces proliferation of prostate cancer cells, and that overexpression of HOXC6 can overcome the effects of PDGFRA inhibition. HOXC6 regulates genes with both oncogenic and tumor suppressor activities as well as several genes such as CD44 that are important for prostate branching morphogenesis and metastasis to the bone microenvironment.

  14. 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.

  15. 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

    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

  16. 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.

  17. 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

  18. 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

  19. 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.

  20. GENOME-BASED MODELING AND DESIGN OF METABOLIC INTERACTIONS IN MICROBIAL COMMUNITIES

    Directory of Open Access Journals (Sweden)

    Radhakrishnan Mahadevan

    2012-10-01

    With the advent of genome sequencing, omics technologies, bioinformatics and genome-scale modeling, researchers now have unprecedented capabilities to analyze and engineer the metabolism of microbial communities. The goal of this review is to summarize recent applications of genome-scale metabolic modeling to microbial communities. A brief introduction to lumped community models is used to motivate the need for genome-level descriptions of individual species and their metabolic interactions. The review of genome-scale models begins with static modeling approaches, which are appropriate for communities where the extracellular environment can be assumed to be time invariant or slowly varying. Dynamic extensions of the static modeling approach are described, and then applications of genome-scale models for design of synthetic microbial communities are reviewed. The review concludes with a summary of metagenomic tools for analyzing community metabolism and an outlook for future research.

  1. A comprehensive analysis of genome-wide association studies to identify prostate cancer susceptibility loci for the Romanian population.

    Science.gov (United States)

    Rădăvoi, George Daniel; Pricop, Cătălin; Jinga, Viorel; Mateş, Dana; Rădoi, Viorica Elena; Jinga, Mariana; Ursu, Radu Ioan; Bratu, Ovidiu Gabriel; Mischianu, Dan Liviu Dorel; Iordache, Paul

    2016-01-01

    The aim of this study is to examine a large dataset of single nucleotide polymorphism known to be associated with prostate cancer from previous genome-wide association studies and create a dataset of single nucleotide polymorphisms that can be used in replication studies for the Romanian population. This study will define a list of markers showing a significant association with this phenotype. We propose the results of this study as a starting point for any Romanian genome-wide association studies researching the genetic susceptibility for prostate cancer.

  2. 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.

  3. 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.

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

    DEFF Research Database (Denmark)

    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...

  5. Genomic gain of the PRL-3 gene may represent poor prognosis of primary colorectal cancer, and associate with liver metastasis.

    Science.gov (United States)

    Nakayama, N; Yamashita, K; Tanaka, T; Kawamata, H; Ooki, A; Sato, T; Nakamura, T; Watanabe, M

    2016-01-01

    PRL-3 genomic copy number is increased in colorectal cancer (CRC), and PRL-3 expression is closely associated with lymph node and liver metastasis of CRC. However, the clinical significance of PRL-3 genomic gain for CRC remains obscure. Here, PRL-3 genomic status in 109 primary CRC tumors and in 44 CRC tumors that had metastasized to the liver, was quantified using real time PCR. Association of PRL-3 genomic status with clinicopathological factors and prognosis was assessed in detail. PRL-3 genomic gain was identified in 31 primary CRC (27.4 %) and was more frequently seen in stage III than in stage II (p = 0.025). Among the clinicopathological factors assessed, PRL-3 genomic gain was significantly associated with poorly differentiated histology (p = 0.0039). Moreover, CRC patients with PRL-3 genomic gain exhibited poorer prognosis than those with no gain in stage II-IV CRC (p = 0.017). PRL-3 genomic gain was identified in 18 (41 %) of the liver metastasis tumors, and this frequency of gain was significantly increased as compared to that of the corresponding primary CRCs (11 %) (p = 0.001). Our findings suggested that PRL-3 genomic gain may represent an aggressive phenotype of primary CRC, and may associate with liver metastasis.

  6. 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.

  7. Diagnostics for stochastic genome-scale modeling via model slicing and debugging.

    Directory of Open Access Journals (Sweden)

    Kevin J Tsai

    Full Text Available Modeling of biological behavior has evolved from simple gene expression plots represented by mathematical equations to genome-scale systems biology networks. However, due to obstacles in complexity and scalability of creating genome-scale models, several biological modelers have turned to programming or scripting languages and away from modeling fundamentals. In doing so, they have traded the ability to have exchangeable, standardized model representation formats, while those that remain true to standardized model representation are faced with challenges in model complexity and analysis. We have developed a model diagnostic methodology inspired by program slicing and debugging and demonstrate the effectiveness of the methodology on a genome-scale metabolic network model published in the BioModels database. The computer-aided identification revealed specific points of interest such as reversibility of reactions, initialization of species amounts, and parameter estimation that improved a candidate cell's adenosine triphosphate production. We then compared the advantages of our methodology over other modeling techniques such as model checking and model reduction. A software application that implements the methodology is available at http://gel.ym.edu.tw/gcs/.

  8. Diagnostics for stochastic genome-scale modeling via model slicing and debugging.

    Science.gov (United States)

    Tsai, Kevin J; Chang, Chuan-Hsiung

    2014-01-01

    Modeling of biological behavior has evolved from simple gene expression plots represented by mathematical equations to genome-scale systems biology networks. However, due to obstacles in complexity and scalability of creating genome-scale models, several biological modelers have turned to programming or scripting languages and away from modeling fundamentals. In doing so, they have traded the ability to have exchangeable, standardized model representation formats, while those that remain true to standardized model representation are faced with challenges in model complexity and analysis. We have developed a model diagnostic methodology inspired by program slicing and debugging and demonstrate the effectiveness of the methodology on a genome-scale metabolic network model published in the BioModels database. The computer-aided identification revealed specific points of interest such as reversibility of reactions, initialization of species amounts, and parameter estimation that improved a candidate cell's adenosine triphosphate production. We then compared the advantages of our methodology over other modeling techniques such as model checking and model reduction. A software application that implements the methodology is available at http://gel.ym.edu.tw/gcs/.

  9. Alternative splicing and differential gene expression in colon cancer detected by a whole genome exon array

    Directory of Open Access Journals (Sweden)

    Sugnet Charles

    2006-12-01

    Full Text Available Abstract Background Alternative splicing is a mechanism for increasing protein diversity by excluding or including exons during post-transcriptional processing. Alternatively spliced proteins are particularly relevant in oncology since they may contribute to the etiology of cancer, provide selective drug targets, or serve as a marker set for cancer diagnosis. While conventional identification of splice variants generally targets individual genes, we present here a new exon-centric array (GeneChip Human Exon 1.0 ST that allows genome-wide identification of differential splice variation, and concurrently provides a flexible and inclusive analysis of gene expression. Results We analyzed 20 paired tumor-normal colon cancer samples using a microarray designed to detect over one million putative exons that can be virtually assembled into potential gene-level transcripts according to various levels of prior supporting evidence. Analysis of high confidence (empirically supported transcripts identified 160 differentially expressed genes, with 42 genes occupying a network impacting cell proliferation and another twenty nine genes with unknown functions. A more speculative analysis, including transcripts based solely on computational prediction, produced another 160 differentially expressed genes, three-fourths of which have no previous annotation. We also present a comparison of gene signal estimations from the Exon 1.0 ST and the U133 Plus 2.0 arrays. Novel splicing events were predicted by experimental algorithms that compare the relative contribution of each exon to the cognate transcript intensity in each tissue. The resulting candidate splice variants were validated with RT-PCR. We found nine genes that were differentially spliced between colon tumors and normal colon tissues, several of which have not been previously implicated in cancer. Top scoring candidates from our analysis were also found to substantially overlap with EST-based bioinformatic

  10. Quantitative assessment model for gastric cancer screening

    Institute of Scientific and Technical Information of China (English)

    Kun Chen; Wei-Ping Yu; Liang Song; Yi-Min Zhu

    2005-01-01

    AIM: To set up a mathematic model for gastric cancer screening and to evaluate its function in mass screening for gastric cancer.METHODS: A case control study was carried on in 66patients and 198 normal people, then the risk and protective factors of gastric cancer were determined, including heavy manual work, foods such as small yellow-fin tuna, dried small shrimps, squills, crabs, mothers suffering from gastric diseases, spouse alive, use of refrigerators and hot food,etc. According to some principles and methods of probability and fuzzy mathematics, a quantitative assessment model was established as follows: first, we selected some factors significant in statistics, and calculated weight coefficient for each one by two different methods; second, population space was divided into gastric cancer fuzzy subset and non gastric cancer fuzzy subset, then a mathematic model for each subset was established, we got a mathematic expression of attribute degree (AD).RESULTS: Based on the data of 63 patients and 693 normal people, AD of each subject was calculated. Considering the sensitivity and specificity, the thresholds of AD values calculated were configured with 0.20 and 0.17, respectively.According to these thresholds, the sensitivity and specificity of the quantitative model were about 69% and 63%.Moreover, statistical test showed that the identification outcomes of these two different calculation methods were identical (P>0.05).CONCLUSION: The validity of this method is satisfactory.It is convenient, feasible, economic and can be used to determine individual and population risks of gastric cancer.

  11. DNA Damage Follows Repair Factor Depletion and Portends Genome Variation in Cancer Cells after Pore Migration.

    Science.gov (United States)

    Irianto, Jerome; Xia, Yuntao; Pfeifer, Charlotte R; Athirasala, Avathamsa; Ji, Jiazheng; Alvey, Cory; Tewari, Manu; Bennett, Rachel R; Harding, Shane M; Liu, Andrea J; Greenberg, Roger A; Discher, Dennis E

    2017-01-23

    Migration through micron-size constrictions has been seen to rupture the nucleus, release nuclear-localized GFP, and cause localized accumulations of ectopic 53BP1-a DNA repair protein. Here, constricted migration of two human cancer cell types and primary mesenchymal stem cells (MSCs) increases DNA breaks throughout the nucleoplasm as assessed by endogenous damage markers and by electrophoretic "comet" measurements. Migration also causes multiple DNA repair proteins to segregate away from DNA, with cytoplasmic mis-localization sustained for many hours as is relevant to delayed repair. Partial knockdown of repair factors that also regulate chromosome copy numbers is seen to increase DNA breaks in U2OS osteosarcoma cells without affecting migration and with nucleoplasmic patterns of damage similar to constricted migration. Such depletion also causes aberrant levels of DNA. Migration-induced nuclear damage is nonetheless reversible for wild-type and sub-cloned U2OS cells, except for lasting genomic differences between stable clones as revealed by DNA arrays and sequencing. Gains and losses of hundreds of megabases in many chromosomes are typical of the changes and heterogeneity in bone cancer. Phenotypic differences that arise from constricted migration of U2OS clones are further illustrated by a clone with a highly elongated and stable MSC-like shape that depends on microtubule assembly downstream of the transcription factor GATA4. Such changes are consistent with reversion to a more stem-like state upstream of cancerous osteoblastic cells. Migration-induced genomic instability can thus associate with heritable changes.

  12. 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.

  13. 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.

  14. Computer models of bacterial cells: from generalized coarsegrained to genome-specific modular models

    Science.gov (United States)

    Nikolaev, Evgeni V.; Atlas, Jordan C.; Shuler, Michael L.

    2006-09-01

    We discuss a modular modelling framework to rapidly develop mathematical models of bacterial cells that would explicitly link genomic details to cell physiology and population response. An initial step in this approach is the development of a coarse-grained model, describing pseudo-chemical interactions between lumped species. A hybrid model of interest can then be constructed by embedding genome-specific detail for a particular cellular subsystem (e.g. central metabolism), called here a module, into the coarse-grained model. Specifically, a new strategy for sensitivity analysis of the cell division limit cycle is introduced to identify which pseudo-molecular processes should be delumped to implement a particular biological function in a growing cell (e.g. ethanol overproduction or pathogen viability). To illustrate the modeling principles and highlight computational challenges, the Cornell coarsegrained model of Escherichia coli B/r-A is used to benchmark the proposed framework.

  15. 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

  16. Understanding Cancer Prognosis

    Medline Plus

    Full Text Available ... Effects of Childhood Cancer Treatment Pediatric Supportive Care Unusual Cancers of Childhood Treatment Childhood Cancer Genomics Study ... Genomics Causes of Cancer Diagnosis Prevention Screening & Early Detection Treatment Cancer & Public Health Cancer Health Disparities Childhood ...

  17. 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 & ...

  18. A single-step genomic model with direct estimation of marker effects.

    Science.gov (United States)

    Liu, Z; Goddard, M E; Reinhardt, F; Reents, R

    2014-09-01

    Compared with the currently widely used multi-step genomic models for genomic evaluation, single-step genomic models can provide more accurate genomic evaluation by jointly analyzing phenotypes and genotypes of all animals and can properly correct for the effect of genomic preselection on genetic evaluations. The objectives of this study were to introduce a single-step genomic model, allowing a direct estimation of single nucleotide polymorphism (SNP) effects, and to develop efficient computing algorithms for solving equations of the single-step SNP model. We proposed an alternative to the current single-step genomic model based on the genomic relationship matrix by including an additional step for estimating the effects of SNP markers. Our single-step SNP model allowed flexible modeling of SNP effects in terms of the number and variance of SNP markers. Moreover, our single-step SNP model included a residual polygenic effect with trait-specific variance for reducing inflation in genomic prediction. A kernel calculation of the SNP model involved repeated multiplications of the inverse of the pedigree relationship matrix of genotyped animals with a vector, for which numerical methods such as preconditioned conjugate gradients can be used. For estimating SNP effects, a special updating algorithm was proposed to separate residual polygenic effects from the SNP effects. We extended our single-step SNP model to general multiple-trait cases. By taking advantage of a block-diagonal (co)variance matrix of SNP effects, we showed how to estimate multivariate SNP effects in an efficient way. A general prediction formula was derived for candidates without phenotypes, which can be used for frequent, interim genomic evaluations without running the whole genomic evaluation process. We discussed various issues related to implementation of the single-step SNP model in Holstein populations with an across-country genomic reference population.

  19. Novel personalized pathway-based metabolomics models reveal key metabolic pathways for breast cancer diagnosis

    DEFF Research Database (Denmark)

    Huang, Sijia; Chong, Nicole; Lewis, Nathan

    2016-01-01

    . Methods: We propose that higher-order functional representation of metabolomics data, such as pathway-based metabolomic features, can be used as robust biomarkers for breast cancer. Towards this, we have developed a new computational method that uses personalized pathway dysregulation scores for disease...... the Curve, a receiver operating characteristic curve) of 0.968 and 0.934, sensitivities of 0.946 and 0.954, and specificities of 0.934 and 0.918. These two metabolomics-based pathway models are further validated by RNA-Seq-based TCGA (The Cancer Genome Atlas) breast cancer data, with AUCs of 0.995 and 0.......993. Moreover, important metabolic pathways, such as taurine and hypotaurine metabolism and the alanine, aspartate, and glutamate pathway, are revealed as critical biological pathways for early diagnosis of breast cancer. Conclusions: We have successfully developed a new type of pathway-based model to study...

  20. 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.

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

    Science.gov (United States)

    Schumacher, Fredrick R.; Berndt, Sonja I.; Siddiq, Afshan; Jacobs, Kevin B.; Wang, Zhaoming; Lindstrom, Sara; Stevens, Victoria L.; Chen, Constance; Mondul, Alison M.; Travis, Ruth C.; Stram, Daniel O.; Eeles, Rosalind A.; Easton, Douglas F.; Giles, Graham; Hopper, John L.; Neal, David E.; Hamdy, Freddie C.; Donovan, Jenny L.; Muir, Kenneth; Al Olama, Ali Amin; Kote-Jarai, Zsofia; Guy, Michelle; Severi, Gianluca; Grönberg, Henrik; Isaacs, William B.; Karlsson, Robert; Wiklund, Fredrik; Xu, Jianfeng; Allen, Naomi E.; Andriole, Gerald L.; Barricarte, Aurelio; Boeing, Heiner; Bas Bueno-de-Mesquita, H.; Crawford, E. David; Diver, W. Ryan; Gonzalez, Carlos A.; Gaziano, J. Michael; Giovannucci, Edward L.; Johansson, Mattias; Le Marchand, Loic; Ma, Jing; Sieri, Sabina; Stattin, Pär; Stampfer, Meir J.; Tjonneland, Anne; Vineis, Paolo; Virtamo, Jarmo; Vogel, Ulla; Weinstein, Stephanie J.; Yeager, Meredith; Thun, Michael J.; Kolonel, Laurence N.; Henderson, Brian E.; Albanes, Demetrius; Hayes, Richard B.; Spencer Feigelson, Heather; Riboli, Elio; Hunter, David J.; Chanock, Stephen J.; Haiman, Christopher A.; Kraft, Peter

    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 identified at least 30 distinct loci associated with small differences in risk. We conducted a GWAS in 2782 advanced PrCa cases (Gleason grade ≥ 8 or tumor stage C/D) and 4458 controls with 571 243 single nucleotide polymorphisms (SNPs). Based on in silico replication of 4679 SNPs (Stage 1, P < 0.02) in two published GWAS with 7358 PrCa cases and 6732 controls, we identified a new susceptibility locus associated with overall PrCa risk at 2q37.3 (rs2292884, P= 4.3 × 10−8). We also confirmed a locus suggested by an earlier GWAS at 12q13 (rs902774, P= 8.6 × 10−9). The estimated per-allele odds ratios for these loci (1.14 for rs2292884 and 1.17 for rs902774) did not differ between advanced and non-advanced PrCa (case-only test for heterogeneity P= 0.72 and P= 0.61, respectively). Further studies will be needed to assess whether these or other loci are differentially associated with PrCa subtypes. PMID:21743057

  2. 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

  3. Non-Genomic Actions of the Androgen Receptor in Prostate Cancer

    Science.gov (United States)

    Leung, Jacky K.; Sadar, Marianne D.

    2017-01-01

    Androgen receptor (AR) is a validated drug target for prostate cancer based on its role in proliferation, survival, and metastases of prostate cancer cells. Unfortunately, despite recent improvements to androgen deprivation therapy and the advent of better antiandrogens with a superior affinity for the AR ligand-binding domain (LBD), most patients with recurrent disease will eventually develop lethal metastatic castration-resistant prostate cancer (CRPC). Expression of constitutively active AR splice variants that lack the LBD contribute toward therapeutic resistance by bypassing androgen blockade and antiandrogens. In the canonical pathway, binding of androgen to AR LBD triggers the release of AR from molecular chaperones which enable conformational changes and protein–protein interactions to facilitate its nuclear translocation where it regulates the expression of target genes. However, preceding AR function in the nucleus, initial binding of androgen to AR LBD in the cytoplasm may already initiate signal transduction pathways to modulate cellular proliferation and migration. In this article, we review the significance of signal transduction pathways activated by rapid, non-genomic signaling of the AR during the progression to metastatic CRPC and put into perspective the implications for current and novel therapies that target different domains of AR.

  4. 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.

  5. Cancer 2015”: A Prospective, Population-Based Cancer Cohort—Phase 1: Feasibility of Genomics-Guided Precision Medicine in the Clinic

    Directory of Open Access Journals (Sweden)

    John P. Parisot

    2015-10-01

    Full Text Available “Cancer 2015” is a longitudinal and prospective cohort. It is a phased study whose aim was to pilot recruiting 1000 patients during phase 1 to establish the feasibility of providing a population-based genomics cohort. Newly diagnosed adult patients with solid cancers, with residual tumour material for molecular genomics testing, were recruited into the cohort for the collection of a dataset containing clinical, molecular pathology, health resource use and outcomes data. 1685 patients have been recruited over almost 3 years from five hospitals. Thirty-two percent are aged between 61–70 years old, with a median age of 63 years. Diagnostic tumour samples were obtained for 90% of these patients for multiple parallel sequencing. Patients identified with somatic mutations of potentially “actionable” variants represented almost 10% of those tumours sequenced, while 42% of the cohort had no mutations identified. These genomic data were annotated with information such as cancer site, stage, morphology, treatment and patient outcomes and health resource use and cost. This cohort has delivered its main objective of establishing an upscalable genomics cohort within a clinical setting and in phase 2 aims to develop a protocol for how genomics testing can be used in real-time clinical decision-making, providing evidence on the value of precision medicine to clinical practice.

  6. 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.

  7. KEAP1 loss modulates sensitivity to kinase targeted therapy in lung cancer. | Office of Cancer Genomics

    Science.gov (United States)

    Inhibitors that target the receptor tyrosine kinase (RTK)/Ras/mitogen-activated protein kinase (MAPK) pathway have led to clinical responses in lung and other cancers, but some patients fail to respond and in those that do resistance inevitably occurs (Balak et al., 2006; Kosaka et al., 2006; Rudin et al., 2013; Wagle et al., 2011). To understand intrinsic and acquired resistance to inhibition of MAPK signaling, we performed CRISPR-Cas9 gene deletion screens in the setting of BRAF, MEK, EGFR, and ALK inhibition.

  8. 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

  9. Genome-wide association study yields variants at 20p12.2 that associate with urinary bladder cancer

    NARCIS (Netherlands)

    Rafnar, T.; Sulem, P.; Thorleifsson, G.; Vermeulen, S.; Helgason, H.; Saemundsdottir, J.; Gudjonsson, S.A.; Sigurdsson, A.; Stacey, S.N.; Gudmundsson, J.; Johannsdottir, H.; Alexiusdottir, K.; Petursdottir, V.; Nikulasson, S.; Geirsson, G.; Jonsson, T.; Aben, K.K.H.; Grotenhuis, A.J.; Verhaegh, G.W.C.T.; Dudek, A.M.D.; Witjes, J.A.; Heijden, A.G. van der; Vrieling, A.; Galesloot, T.E.; Juan, A. de; Panadero, A.; Rivera, F.; Hurst, C.; Bishop, D.T.; Sak, S.C.; Choudhury, A.; Teo, M.T.; Arici, C.; Carta, A.; Toninelli, E.; Verdier, P. de; Rudnai, P.; Gurzau, E; Koppova, K.; Keur, K.A. van der; Lurkin, I.; Goossens, M.; Kellen, E.; Guarrera, S.; Russo, A.; Critelli, R.; Sacerdote, C.; Vineis, P.; Krucker, C.; Zeegers, M.P.; Gerullis, H.; Ovsiannikov, D.; Volkert, F.; Hengstler, J.G.; Selinski, S.; Magnusson, O.T.; Masson, G.; Kong, A.; Gudbjartsson, D.; Lindblom, A.; Zwarthoff, E.; Porru, S.; Golka, K.; Buntinx, F.; Matullo, G.; Kumar, R.; Mayordomo, J.I.; Steineck, D.G.; Kiltie, A.E.; Jonsson, E.; Radvanyi, F.; Knowles, M.A.; Thorsteinsdottir, U.; Kiemeney, B.; Stefansson, K.

    2014-01-01

    Genome-wide association studies (GWAS) of urinary bladder cancer (UBC) have yielded common variants at 12 loci that associate with risk of the disease. We report here the results of a GWAS of UBC including 1670 UBC cases and 90 180 controls, followed by replication analysis in additional 5266 UBC ca

  10. Genome-wide association analysis of more than 120,000 individuals identifies 15 new susceptibility loci for breast cancer

    NARCIS (Netherlands)

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

    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 similar to 14% of the familial risk of the disease. To identify new susceptibility loci, we performed a meta-analysis of 11 GWAS, comprising

  11. Genome-wide association analysis of more than 120,000 individuals identifies 15 new susceptibility loci for breast cancer

    NARCIS (Netherlands)

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

    2015-01-01

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

  12. Genome-wide association analysis of more than 120,000 individuals identifies 15 new susceptibility loci for breast cancer