WorldWideScience

Sample records for cancer models genomic

  1. Comprehensive copy number profiles of breast cancer cell model genomes

    OpenAIRE

    Shadeo, Ashleen; Lam, Wan L.

    2006-01-01

    Introduction Breast cancer is the most commonly diagnosed cancer in women worldwide and consequently has been extensively investigated in terms of histopathology, immunochemistry and familial history. Advances in genome-wide approaches have contributed to molecular classification with respect to genomic changes and their subsequent effects on gene expression. Cell lines have provided a renewable resource that is readily used as model systems for breast cancer cell biology. A thorough characte...

  2. Human Cancer Classification: A Systems Biology- Based Model Integrating Morphology, Cancer Stem Cells, Proteomics, and Genomics

    OpenAIRE

    Halliday A Idikio

    2011-01-01

    Human cancer classification is currently based on the idea of cell of origin, light and electron microscopic attributes of the cancer. What is not yet integrated into cancer classification are the functional attributes of these cancer cells. Recent innovative techniques in biology have provided a wealth of information on the genomic, transcriptomic and proteomic changes in cancer cells. The emergence of the concept of cancer stem cells needs to be included in a classification model to capture...

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

    Science.gov (United States)

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

    2005-01-01

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

  4. 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...

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

    Directory of Open Access Journals (Sweden)

    Dexter Tim J

    2010-09-01

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

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

    OpenAIRE

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

    2005-01-01

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

  7. 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

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

    OpenAIRE

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

    2010-01-01

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

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

    OpenAIRE

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

    2014-01-01

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

  10. 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.

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

    Science.gov (United States)

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

    2016-01-01

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

  12. 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...... 85 antimetabolites that can inhibit growth of, or even kill, any of the cell lines, while at the same time not being toxic for 83 different healthy human cell types. 60 of these antimetabolites were found to inhibit growth in all cell lines. Finally, we experimentally validated one of the predicted...... 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...

  13. The Cancer Genome Atlas ovarian cancer analysis

    Science.gov (United States)

    An analysis of genomic changes in ovarian cancer has provided the most comprehensive and integrated view of cancer genes for any cancer type to date. Ovarian serous adenocarcinoma tumors from 500 patients were examined by The Cancer Genome Atlas (TCGA) Re

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

    Directory of Open Access Journals (Sweden)

    Varun Chalivendra

    2015-03-01

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

  16. Mathematical modelling of the radiation-induced bystander effect and transmissible genomic instability applied to cancer

    Energy Technology Data Exchange (ETDEWEB)

    Little, M.P. (Dept. of Epidemiology and Public Health, Imperial College Faculty of Medicine, London (United Kingdom)); Prise, K.; Folkard, M. (Gray Cancer Institute, Mount Vernon Hospital, Northwood (United Kingdom)); Belyakov, O. (Radiation and Nuclear Safety Authority, Research and Environmental Surveillance, Radiation Biology Laboratory, Helsinki (Finland))

    2008-12-15

    A variety of quasi-mechanistic models of carcinogenesis are reviewed, and in particular, the multi-stage model of Armitage and Doll and the two-mutation model of Moolgavkar, Venzon, and Knudson. Both the latter models, and various generalizations of them also, are capable of describing at least qualitatively many of the observed patterns of excess cancer risk following ionizing radiation exposure. However, there are certain inconsistencies with the biological and epidemiological data both for the multi-stage model and the two-mutation model. In particular, there are indications that the two-mutation model is not totally suitable for describing the pattern of excess risk for solid cancers that is often seen after exposure to radiation, although leukaemia may be better fitted by this type of model. Generalizations of the model of Moolgavkar, Venzon, and Knudson which require three or more mutations, and models allowing for genomic instability, are easier to reconcile with the epidemiological and biological data relating to solid cancers. Bystander effects, whereby cells that are not directly exposed to ionizing radiation exhibit adverse biological effects, have been observed in a number of experimental systems. In contrast to the large amount of work on developing carcinogenesis models over the last 50 years, there has been comparatively little work on developing quasi-mechanistic models of the bystander effect, reflecting the comparatively recently available experimental data elucidating this phenomenon. The few quasi-mechanistic models of the bystander effect that have been developed are surveyed. In particular, a novel stochastic model of the radiation-induced bystander effect is considered that takes account of spatial location, cell killing and repopulation, features not explicitly taken into account in many previous models. The ionizing radiation dose- and time-responses of this model are explored, and it is shown to exhibit pronounced downward curvature in the

  17. Evolution of the cancer genome

    OpenAIRE

    Yates, Lucy R.; Campbell, Peter J

    2012-01-01

    The advent of massively parallel sequencing technologies has allowed the characterization of cancer genomes at an unprecedented resolution. Investigation of the mutational landscape of tumours is providing new insights into cancer genome evolution, laying bare the interplay of somatic mutation, adaptation of clones to their environment and natural selection. These studies have demonstrated the extent of the heterogeneity of cancer genomes, have allowed inferences to be made about the forces t...

  18. 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:

  19. 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.

  20. Genomics: Drugs, diabetes and cancer

    OpenAIRE

    Birnbaum, Morris J.; Shaw, Reuben J

    2011-01-01

    Variation in a genomic region that contains the cancer-a ssociated gene ATM affects a patient’s response to the diabetes drug metformin. Two experts discuss the implications for understanding diabetes and the link to cancer.

  1. 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*

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

    Directory of Open Access Journals (Sweden)

    Hongye Liu

    2006-07-01

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

  3. 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

  4. 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.

  5. 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.

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

    Science.gov (United States)

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

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

    Science.gov (United States)

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

  8. International network of cancer genome projects.

    OpenAIRE

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

    2010-01-01

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

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

    OpenAIRE

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

    2016-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Nunes Virginia

    2008-01-01

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

  11. 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

  12. Clinical Implications of the Cancer Genome

    OpenAIRE

    MacConaill, Laura E; Garraway, Levi A

    2010-01-01

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

  13. Genome-Scale Models

    DEFF Research Database (Denmark)

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

    2016-01-01

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

  14. Integration of genomics in cancer care

    DEFF Research Database (Denmark)

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

    2013-01-01

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

  15. 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...... 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...

  16. 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 ...

  17. 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.

  18. Genomic tumor evolution of breast cancer.

    Science.gov (United States)

    Sato, Fumiaki; Saji, Shigehira; Toi, Masakazu

    2016-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Yan P Yu

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

  20. Functional genomics and cancer drug target discovery.

    Science.gov (United States)

    Moody, Susan E; Boehm, Jesse S; Barbie, David A; Hahn, William C

    2010-06-01

    The recent development of technologies for whole-genome sequencing, copy number analysis and expression profiling enables the generation of comprehensive descriptions of cancer genomes. However, although the structural analysis and expression profiling of tumors and cancer cell lines can allow the identification of candidate molecules that are altered in the malignant state, functional analyses are necessary to confirm such genes as oncogenes or tumor suppressors. Moreover, recent research suggests that tumor cells also depend on synthetic lethal targets, which are not mutated or amplified in cancer genomes; functional genomics screening can facilitate the discovery of such targets. This review provides an overview of the tools available for the study of functional genomics, and discusses recent research involving the use of these tools to identify potential novel drug targets in cancer. PMID:20521217

  1. Characterizing the cancer genome in lung adenocarcinoma

    OpenAIRE

    Weir, Barbara A.; Woo, Michele S.; Getz, Gad; Perner, Sven; Ding, Li; Beroukhim, Rameen; Lin, William M.; Province, Michael A; Kraja, Aldi; Johnson, Laura A.; Shah, Kinjal; Sato, Mitsuo; Thomas, Roman K.; Barletta, Justine A; Borecki, Ingrid B

    2007-01-01

    Somatic alterations in cellular DNA underlie almost all human cancers1. The prospect of targeted therapies2 and the development of high-resolution, genome-wide approaches3–8 are now spurring systematic efforts to characterize cancer genomes. Here we report a large-scale project to characterize copy-number alterations in primary lung adenocarcinomas. By analysis of a large collection of tumors (n = 371) using dense single nucleotide polymorphism arrays, we identify a total of 57 significantly ...

  2. 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.

  3. 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.

  4. Genomic Biomarkers for Breast Cancer Risk.

    Science.gov (United States)

    Walsh, Michael F; Nathanson, Katherine L; Couch, Fergus J; Offit, Kenneth

    2016-01-01

    Clinical risk assessment for cancer predisposition includes a three-generation pedigree and physical examination to identify inherited syndromes. Additionally genetic and genomic biomarkers may identify individuals with a constitutional basis for their disease that may not be evident clinically. Genomic biomarker testing may detect molecular variations in single genes, panels of genes, or entire genomes. The strength of evidence for the association of a genomic biomarker with disease risk may be weak or strong. The factors contributing to clinical validity and utility of genomic biomarkers include functional laboratory analyses and genetic epidemiologic evidence. Genomic biomarkers may be further classified as low, moderate or highly penetrant based on the likelihood of disease. Genomic biomarkers for breast cancer are comprised of rare highly penetrant mutations of genes such as BRCA1 or BRCA2, moderately penetrant mutations of genes such as CHEK2, as well as more common genomic variants, including single nucleotide polymorphisms, associated with modest effect sizes. When applied in the context of appropriate counseling and interpretation, identification of genomic biomarkers of inherited risk for breast cancer may decrease morbidity and mortality, allow for definitive prevention through assisted reproduction, and serve as a guide to targeted therapy . PMID:26987529

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

    International Nuclear Information System (INIS)

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

  6. Genomic determinants of somatic copy number alterations across human cancers.

    Science.gov (United States)

    Zhang, Yanping; Xu, Hongen; Frishman, Dmitrij

    2016-03-01

    Somatic copy number alterations (SCNAs) play an important role in carcinogenesis. However, the impact of genomic architecture on the global patterns of SCNAs in cancer genomes remains elusive. In this work, we conducted multiple linear regression (MLR) analyses of the pooled SCNA data from The Cancer Genome Atlas (TCGA) Pan-Cancer project. We performed MLR analyses for 11 individual cancer types and three different kinds of SCNAs-amplifications and deletions, telomere-bound and interstitial SCNAs and local SCNAs. Our MLR model explains >30% of the pooled SCNA breakpoint variation, with the explanatory power ranging from 13 to 32% for different cancer types and SCNA types. In addition to confirming previously identified features [e.g. long interspersed element-1 (L1) and short interspersed nuclear elements], we also identified several novel informative features, including distance to telomere, distance to centromere and low-complexity repeats. The results of the MLR analyses were additionally confirmed on an independent SCNA data set obtained from the catalogue of somatic mutations in cancer database. Using a rare-event logistic regression model and an extremely randomized tree classifier, we revealed that genomic features are informative for defining common SCNA breakpoint hotspots. Our findings shed light on the molecular mechanisms of SCNA generation in cancer. PMID:26732428

  7. Cancer Genome Atlas Pan-cancer Analysis Project

    OpenAIRE

    Zhang, Kun; Wang, Hong

    2015-01-01

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

  8. CTD² Publication Guidelines | Office of Cancer Genomics

    Science.gov (United States)

    The Cancer Target Discovery and Development (CTD2) Network is a “community resource project” supported by the National Cancer Institute’s Office of Cancer Genomics. Members of the Network release data to the broader research community by depositing data into NCI-supported or public databases. Data deposition is NOT equivalent to publishing in a peer-reviewed journal. Unless there is a manuscript associated with a dataset, the Network considers data to be formally unpublished.

  9. Genomic rearrangements of PTEN in prostate cancer

    Directory of Open Access Journals (Sweden)

    Sopheap ePhin

    2013-09-01

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

  10. Cancer Genome Atlas Pan-cancer Analysis Project

    Directory of Open Access Journals (Sweden)

    Kun ZHANG

    2015-04-01

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

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

    Science.gov (United States)

    Zhang, Kun; Wang, Hong

    2015-04-01

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

  12. The genomics and genetics of endometrial cancer

    Directory of Open Access Journals (Sweden)

    Bell DW

    2012-03-01

    Full Text Available Andrea J O’Hara,  Daphne W Bell National Human Genome Research Institute, Cancer Genetics Branch, National Institutes of Health, Bethesda, MD, USAAbstract: Most sporadic endometrial cancers (ECs can be histologically classified as endometrioid, serous, or clear cell. Each histotype has a distinct natural history, clinical behavior, and genetic etiology. Endometrioid ECs have an overall favorable prognosis. They are typified by high frequency genomic alterations affecting PIK3CA, PIK3R1, PTEN, KRAS, FGFR2, ARID1A (BAF250a, and CTNNB1 (β-catenin, as well as epigenetic silencing of MLH1 resulting in microsatellite instability. Serous and clear cell ECs are clinically aggressive tumors that are rare at presentation but account for a disproportionate fraction of all endometrial cancer deaths. Serous ECs tend to be aneuploid and are typified by frequent genomic alterations affecting TP53 (p53, PPP2R1A, HER-2/ERBB2, PIK3CA, and PTEN; additionally, they display dysregulation of E-cadherin, p16, cyclin E, and BAF250a. The genetic etiology of clear cell ECs resembles that of serous ECs, but it remains relatively poorly defined. A detailed discussion of the characteristic patterns of genomic alterations that distinguish the three major histotypes of endometrial cancer is reviewed herein.Keywords: endometrial, cancer, genomics, genetics, sporadic

  13. Functional annotation of rare gene aberration drivers of pancreatic cancer | Office of Cancer Genomics

    Science.gov (United States)

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

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

    Science.gov (United States)

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

  15. Childhood Cancer Genomics Gaps and Opportunities - Workshop Summary

    Science.gov (United States)

    NCI convened a workshop of representative research teams that have been leaders in defining the genomic landscape of childhood cancers to discuss the influence of genomic discoveries on the future of childhood cancer research.

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

    Directory of Open Access Journals (Sweden)

    Senthil Kumar Pazhanisamy

    2009-01-01

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

  17. 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.

  18. 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

  19. Dr. Marco Marra: Pioneer and Visionary in Cancer Genomics Research | Office of Cancer Genomics

    Science.gov (United States)

    Dr. Marco Marra is a highly distinguished genomics and bioinformatics researcher. He is the Director of Canada’s Michael Smith Genome Sciences Centre at the BC Cancer Agency and holds a faculty position at the University of British Columbia. The Centre is a state-of-the-art sequencing facility in Vancouver, Canada, with a major focus on the study of cancers.  Many of their research projects are undertaken in collaborations with other Canadian and international institutions.

  20. Elevated tolerance to aneuploidy in cancer cells: estimating the fitness effects of chromosome number alterations by in silico modelling of somatic genome evolution.

    Science.gov (United States)

    Valind, Anders; Jin, Yuesheng; Gisselsson, David

    2013-01-01

    An unbalanced chromosome number (aneuploidy) is present in most malignant tumours and has been attributed to mitotic mis-segregation of chromosomes. However, recent studies have shown a relatively high rate of chromosomal mis-segregation also in non-neoplastic human cells, while the frequency of aneuploid cells remains low throughout life in most normal tissues. This implies that newly formed aneuploid cells are subject to negative selection in healthy tissues and that attenuation of this selection could contribute to aneuploidy in cancer. To test this, we modelled cellular growth as discrete time branching processes, during which chromosome gains and losses were generated and their host cells subjected to selection pressures of various magnitudes. We then assessed experimentally the frequency of chromosomal mis-segregation as well as the prevalence of aneuploid cells in human non-neoplastic cells and in cancer cells. Integrating these data into our models allowed estimation of the fitness reduction resulting from a single chromosome copy number change to an average of ≈30% in normal cells. In comparison, cancer cells showed an average fitness reduction of only 6% (p = 0.0008), indicative of aneuploidy tolerance. Simulations based on the combined presence of chromosomal mis-segregation and aneuploidy tolerance reproduced distributions of chromosome aberrations in >400 cancer cases with higher fidelity than models based on chromosomal mis-segregation alone. Reverse engineering of aneuploid cancer cell development in silico predicted that aneuploidy intolerance is a stronger limiting factor for clonal expansion of aneuploid cells than chromosomal mis-segregation rate. In conclusion, our findings indicate that not only an elevated chromosomal mis-segregation rate, but also a generalised tolerance to novel chromosomal imbalances contribute to the genomic landscape of human tumours. PMID:23894657

  1. 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

  2. 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.

  3. 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.

  4. 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.

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

    OpenAIRE

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

    2005-01-01

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

  6. Resources | Office of Cancer Genomics

    Science.gov (United States)

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

  7. TARGET Publication Guidelines | Office of Cancer Genomics

    Science.gov (United States)

    Like other NCI large-scale genomics initiatives, TARGET is a community resource project and data are made available rapidly after validation for use by other researchers. To act in accord with the Fort Lauderdale principles and support the continued prompt public release of large-scale genomic data prior to publication, researchers who plan to prepare manuscripts containing descriptions of TARGET pediatric cancer data that would be of comparable scope to an initial TARGET disease-specific comprehensive, global analysis publication, and journal editors who receive such manuscripts, are stron

  8. Integrative prescreening in analysis of multiple cancer genomic studies

    Directory of Open Access Journals (Sweden)

    Song Rui

    2012-07-01

    Full Text Available Abstract Background In high throughput cancer genomic studies, results from the analysis of single datasets often suffer from a lack of reproducibility because of small sample sizes. Integrative analysis can effectively pool and analyze multiple datasets and provides a cost effective way to improve reproducibility. In integrative analysis, simultaneously analyzing all genes profiled may incur high computational cost. A computationally affordable remedy is prescreening, which fits marginal models, can be conducted in a parallel manner, and has low computational cost. Results An integrative prescreening approach is developed for the analysis of multiple cancer genomic datasets. Simulation shows that the proposed integrative prescreening has better performance than alternatives, particularly including prescreening with individual datasets, an intensity approach and meta-analysis. We also analyze multiple microarray gene profiling studies on liver and pancreatic cancers using the proposed approach. Conclusions The proposed integrative prescreening provides an effective way to reduce the dimensionality in cancer genomic studies. It can be coupled with existing analysis methods to identify cancer markers.

  9. 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

  10. Comprehensive genomic profiles of small cell lung cancer.

    Science.gov (United States)

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

    2015-08-01

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

  11. 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.

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

    Science.gov (United States)

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

    2011-01-01

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

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

    Science.gov (United States)

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

    2014-01-01

    The International Cancer Genome Consortium (ICGC) aims to catalog genomic abnormalities in tumors from 50 different cancer types. Genome sequencing reveals hundreds to thousands of somatic mutations in each tumor, but only a minority drive tumor progression. We present the result of discussions within the ICGC on how to address the challenge of identifying mutations that contribute to oncogenesis, tumor maintenance or response to therapy, and recommend computational techniques to annotate somatic variants and predict their impact on cancer phenotype. PMID:23900255

  14. 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...... 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....

  15. 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.

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

    Science.gov (United States)

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

    2012-06-01

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

  17. 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.

  18. Identifying driver mutations in sequenced cancer genomes

    DEFF Research Database (Denmark)

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

    2014-01-01

    protein sequence or structure. Finally, we review techniques to identify recurrent combinations of somatic mutations, including approaches that examine mutations in known pathways or protein-interaction networks, as well as de novo approaches that identify combinations of mutations according to......-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......, 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...

  19. Identification of cancer-driver genes in focal genomic alterations from whole genome sequencing data.

    Science.gov (United States)

    Jang, Ho; Hur, Youngmi; Lee, Hyunju

    2016-01-01

    DNA copy number alterations (CNAs) are the main genomic events that occur during the initiation and development of cancer. Distinguishing driver aberrant regions from passenger regions, which might contain candidate target genes for cancer therapies, is an important issue. Several methods for identifying cancer-driver genes from multiple cancer patients have been developed for single nucleotide polymorphism (SNP) arrays. However, for NGS data, methods for the SNP array cannot be directly applied because of different characteristics of NGS such as higher resolutions of data without predefined probes and incorrectly mapped reads to reference genomes. In this study, we developed a wavelet-based method for identification of focal genomic alterations for sequencing data (WIFA-Seq). We applied WIFA-Seq to whole genome sequencing data from glioblastoma multiforme, ovarian serous cystadenocarcinoma and lung adenocarcinoma, and identified focal genomic alterations, which contain candidate cancer-related genes as well as previously known cancer-driver genes. PMID:27156852

  20. Identification of cancer-driver genes in focal genomic alterations from whole genome sequencing data

    Science.gov (United States)

    Jang, Ho; Hur, Youngmi; Lee, Hyunju

    2016-01-01

    DNA copy number alterations (CNAs) are the main genomic events that occur during the initiation and development of cancer. Distinguishing driver aberrant regions from passenger regions, which might contain candidate target genes for cancer therapies, is an important issue. Several methods for identifying cancer-driver genes from multiple cancer patients have been developed for single nucleotide polymorphism (SNP) arrays. However, for NGS data, methods for the SNP array cannot be directly applied because of different characteristics of NGS such as higher resolutions of data without predefined probes and incorrectly mapped reads to reference genomes. In this study, we developed a wavelet-based method for identification of focal genomic alterations for sequencing data (WIFA-Seq). We applied WIFA-Seq to whole genome sequencing data from glioblastoma multiforme, ovarian serous cystadenocarcinoma and lung adenocarcinoma, and identified focal genomic alterations, which contain candidate cancer-related genes as well as previously known cancer-driver genes. PMID:27156852

  1. Genome Wide Methylome Alterations in Lung Cancer.

    Science.gov (United States)

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

    2015-01-01

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

  2. Genetics and genomics of prostate cancer

    Institute of Scientific and Technical Information of China (English)

    Michael Dean; Hong Lou

    2013-01-01

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

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

    Institute of Scientific and Technical Information of China (English)

    Erina; Takai; Shinichi; Yachida

    2015-01-01

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

  4. Transcriptional consequences of genomic structural aberrations in breast cancer

    OpenAIRE

    Inaki, Koichiro; Hillmer, Axel M.; Ukil, Leena; Yao, Fei; Woo, Xing Yi; Vardy, Leah A; Zawack, Kelson Folkvard Braaten; Lee, Charlie Wah Heng; Ariyaratne, Pramila Nuwantha; Chan, Yang Sun; Desai, Kartiki Vasant; Bergh, Jonas; Hall, Per; Putti, Thomas Choudary; Ong, Wai Loon

    2011-01-01

    Using a long-span, paired-end deep sequencing strategy, we have comprehensively identified cancer genome rearrangements in eight breast cancer genomes. Herein, we show that 40%–54% of these structural genomic rearrangements result in different forms of fusion transcripts and that 44% are potentially translated. We find that single segmental tandem duplication spanning several genes is a major source of the fusion gene transcripts in both cell lines and primary tumors involving adjacent genes ...

  5. Genome Wide Methylome Alterations in Lung Cancer.

    Directory of Open Access Journals (Sweden)

    Nandita Mullapudi

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

  6. 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.; Rowan, Andrew J.; Grönroos, Eva; Endesfelder, David; Joshi, Tejal; Mouradov, Dmitri; Gibbs, Peter; Ward, Robyn L.; Hawkins, Nicholas J.; Szallasi, Zoltan Imre; Sieber, Oliver M.; Swanton, Charles

    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 ...

  7. 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.

  8. Association between invasive ovarian cancer susceptibility and 11 best candidate SNPs from breast cancer genome-wide association study

    DEFF Research Database (Denmark)

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

    2009-01-01

    Because both ovarian and breast cancer are hormone-related and are known to have some predisposition genes in common, we evaluated 11 of the most significant hits (six with confirmed associations with breast cancer) from the breast cancer genome-wide association study for association with invasive.......01-1.13, P-trend = 0.02 for all types of ovarian cancer and OR 1.14 95% CI 1.07-1.22, P-trend = 0.00017 for serous ovarian cancer]. In conclusion, we found that rs4954956 was associated with increased ovarian cancer risk, particularly for serous ovarian cancer. However, none of the six confirmed breast...... ovarian cancer. Eleven SNPs were initially genotyped in 2927 invasive ovarian cancer cases and 4143 controls from six ovarian cancer case-control studies. Genotype frequencies in cases and controls were compared using a likelihood ratio test in a logistic regression model stratified by study. Initially...

  9. Tolerance whole of genome doubling propagates chromosomal instability and accelerates cancer genome evolution

    OpenAIRE

    Dewhurst, Sally M; McGranahan, Nicholas; Burrell, Rebecca A.; Rowan, Andrew J.; Grönroos, Eva; Endesfelder, David; Joshi, Tejal; Mouradov, Dmitri; Gibbs, Peter; Ward, Robyn L.; Hawkins, Nicholas J.; Szallasi, Zoltan; Sieber, Oliver M.; Swanton, Charles

    2014-01-01

    The contribution of whole genome doubling to chromosomal instability (CIN) and tumour 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, t...

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

    Science.gov (United States)

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

  11. Characterizing genomic alterations in cancer by complementary functional associations.

    Science.gov (United States)

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

    2016-05-01

    Systematic efforts to sequence the cancer genome have identified large numbers of mutations and copy number alterations in human cancers. However, elucidating the functional consequences of these variants, and their interactions to drive or maintain oncogenic states, remains a challenge in cancer research. We developed REVEALER, a computational method that identifies combinations of mutually exclusive genomic alterations correlated with functional phenotypes, such as the activation or gene dependency of oncogenic pathways or sensitivity to a drug treatment. We used REVEALER to uncover complementary genomic alterations associated with the transcriptional activation of β-catenin and NRF2, MEK-inhibitor sensitivity, and KRAS dependency. REVEALER successfully identified both known and new associations, demonstrating the power of combining functional profiles with extensive characterization of genomic alterations in cancer genomes. PMID:27088724

  12. Interest and Informational Preferences Regarding Genomic Testing for Modest Increases in Colorectal Cancer Risk

    Science.gov (United States)

    Anderson, Allison E.; Flores, Kristina G.; Boonyasiriwat, Watcharaporn; Gammon, Amanda; Kohlmann, Wendy; Birmingham, Wendy C.; Schwartz, Marc D.; Samadder, Jewel; Boucher, Ken; Kinney, Anita Y.

    2014-01-01

    Background/Aims To explore interest in genomic testing for modest changes in colorectal cancer risk and preferences for receiving genomic risk communications among individuals with intermediate disease risk due to a family history of colorectal cancer. Methods Surveys were conducted on 278 men and women at intermediate risk for colorectal cancer enrolled in a randomized trial comparing a remote personalized risk communication intervention (TeleCARE) aimed at promoting colonoscopy to a generic print control condition. Guided by Leventhal’s Common Sense Model of Self-regulation, we examined demographic and psychosocial factors possibly associated with interest in SNP testing. Descriptive statistics and logistic regression models were used to identify factors associated with testing interest and preferences for receiving genomic risk communications. Results Three-fourths of participants expressed interest in SNP testing for colorectal cancer risk. Testing interest did not markedly change across behavior modifier scenarios. Participants preferred to receive genomic risk communications from a variety of sources: printed materials, (69.1%), oncologists (59.5%), primary-care physicians (58.1%), and the web (57.9%). Overall, persons who were unmarried (p=0.029), younger (p=0.003), and with greater cancer-related fear (p=0.019) were more likely to express interest in predictive genomic testing for colorectal cancer risk. In a stratified analysis, cancer related fear was associated with interest in predictive genomic testing in the intervention group (p=0.017) but not the control group. Conclusions Individuals with intermediate familial risk for colorectal cancer are highly interested in genomic testing for modest increases in disease risk, specifically unmarried persons, younger age groups, and those with greater cancer fear. PMID:24435063

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

    Science.gov (United States)

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

  14. A microscopic landscape of the invasive breast cancer genome

    OpenAIRE

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

    2016-01-01

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

  15. Perspectives of Integrative Cancer Genomics in Next Generation Sequencing Era

    OpenAIRE

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

    2012-01-01

    The explosive development of genomics technologies including microarrays and next generation sequencing (NGS) has provided comprehensive maps of cancer genomes, including the expression of mRNAs and microRNAs, DNA copy numbers, sequence variations, and epigenetic changes. These genome-wide profiles of the genetic aberrations could reveal the candidates for diagnostic and/or prognostic biomarkers as well as mechanistic insights into tumor development and progression. Recent efforts to establis...

  16. Minimal model for genome evolution and growth

    OpenAIRE

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

    2002-01-01

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

  17. 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.

  18. 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 ...

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

    OpenAIRE

    Zack, Travis Ian

    2014-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Vollan Hans

    2011-11-01

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

  1. Databases and Web Tools for Cancer Genomics Study

    Institute of Scientific and Technical Information of China (English)

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

    2015-01-01

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

  2. 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.

  3. Methods for detection of subtle mutations in cancer genomes

    DEFF Research Database (Denmark)

    Dahl, Christina; Ralfkiaer, Ulrik; Guldberg, Per

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

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

    Science.gov (United States)

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

    2013-10-01

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

  5. 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.

  6. 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.

  7. 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

  8. 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.

  9. [Genome-wide association study(GWAS) and genetic risk of prostate cancer].

    Science.gov (United States)

    Nakagawa, Hidewaki; Akamatsu, Shusuke; Takata, Ryo

    2016-01-01

    It is evident that genetic factors play critical roles in prostate cancer development. GWAS (genome-wide association studies) in multiple ethnic groups have been identifying more than 100 loci or genes which was significantly associated with prostate cancer susceptibility. They include several loci at 8q24, prostate-specific gene, inflammation gene, and metabolism-related genes. Risk prediction for prostate cancer by combining multiple SNPs is still primitive and not sufficiently accurate for clinical use, but this model could have a potential to affect clinical decision when it is applied to patients with gray-zone PSA or very high risk of prostate cancer. PMID:26793876

  10. Cancer Therapy Evaluation Program | Office of Cancer Genomics

    Science.gov (United States)

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

  11. Robust Automatic Breast Cancer Staging Using A Combination of Functional Genomics and Image-Omics

    Science.gov (United States)

    Su, Hai; Shen, Yong; Xing, Fuyong; Qi, Xin; Hirshfield, Kim M.; Yang, Lin; Foran, David J.

    2016-01-01

    Breast cancer is one of the leading cancers worldwide. Precision medicine is a new trend that systematically examines molecular and functional genomic information within each patient's cancer to identify the patterns that may affect treatment decisions and potential outcomes. As a part of precision medicine, computer-aided diagnosis enables joint analysis of functional genomic information and image from pathological images. In this paper we propose an integrated framework for breast cancer staging using image-omics and functional genomic information. The entire biomedical imaging informatics framework consists of image-omics extraction, feature combination, and classification. First, a robust automatic nuclei detection and segmentation is presented to identify tumor regions, delineate nuclei boundaries and calculate a set of image-based morphological features; next, the low dimensional image-omics is obtained through principal component analysis and is concatenated with the functional genomic features identified by a linear model. A support vector machine for differentiating stage I breast cancer from other stages are learned. We experimentally demonstrate that compared with a single type of representation (image-omics), the combination of image-omics and functional genomic feature can improve the classification accuracy by 3%. PMID:26737959

  12. Endoplasmic Reticulum Stress, Genome Damage, and Cancer

    OpenAIRE

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

    2015-01-01

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

  13. Endoplasmic reticulum stress, genome damage and cancer

    OpenAIRE

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

    2015-01-01

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

  14. Genomic insights into a contagious cancer in Tasmanian devils.

    Science.gov (United States)

    Grueber, Catherine E; Peel, Emma; Gooley, Rebecca; Belov, Katherine

    2015-09-01

    The Tasmanian devil faces extinction due to a contagious cancer. Genetic and genomic technologies revealed that the disease arose in a Schwann cell of a female devil. Instead of dying with the original host, the tumour was passed from animal to animal, slipping under the radar of the immune system. Studying the genomes of the devil and the cancer has driven our understanding of this unique disease. From characterising immune genes and immune responses to studying tumour evolution, we have begun to uncover how a cancer can be 'caught' and are using genomic data to manage an insurance population of disease-free devils for the long-term survival of the species. PMID:26027792

  15. Minimal model for genome evolution and growth

    CERN Document Server

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

    2002-01-01

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

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

    OpenAIRE

    Garnett, Mathew J.; McDermott, Ultan

    2014-01-01

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

  17. A microscopic landscape of the invasive breast cancer genome

    Science.gov (United States)

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

    2016-01-01

    Histologic grade is one of the most important microscopic features used to predict the prognosis of invasive breast cancer and may serve as a marker for studying cancer driving genomic abnormalities in vivo. We analyzed whole genome sequencing data from 680 cases of TCGA invasive ductal carcinomas of the breast and correlated them to corresponding pathology information. Ten genetic abnormalities were found to be statistically associated with histologic grade, including three most prevalent cancer driver events, TP53 and PIK3CA mutations and MYC amplification. A distinct genetic interaction among these genomic abnormalities was revealed as measured by the histologic grading score. While TP53 mutation and MYC amplification were synergistic in promoting tumor progression, PIK3CA mutation was found to have alleviated the oncogenic effect of either the TP53 mutation or MYC amplification, and was associated with a significant reduction in mitotic activity in TP53 mutated and/or MYC amplified breast cancer. Furthermore, we discovered that different types of genetic abnormalities (mutation versus amplification) within the same cancer driver gene (PIK3CA or GATA3) were associated with opposite histologic changes in invasive breast cancer. In conclusion, our study suggests that histologic grade may serve as a biomarker to define cancer driving genetic events in vivo. PMID:27283966

  18. A microscopic landscape of the invasive breast cancer genome.

    Science.gov (United States)

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

    2016-01-01

    Histologic grade is one of the most important microscopic features used to predict the prognosis of invasive breast cancer and may serve as a marker for studying cancer driving genomic abnormalities in vivo. We analyzed whole genome sequencing data from 680 cases of TCGA invasive ductal carcinomas of the breast and correlated them to corresponding pathology information. Ten genetic abnormalities were found to be statistically associated with histologic grade, including three most prevalent cancer driver events, TP53 and PIK3CA mutations and MYC amplification. A distinct genetic interaction among these genomic abnormalities was revealed as measured by the histologic grading score. While TP53 mutation and MYC amplification were synergistic in promoting tumor progression, PIK3CA mutation was found to have alleviated the oncogenic effect of either the TP53 mutation or MYC amplification, and was associated with a significant reduction in mitotic activity in TP53 mutated and/or MYC amplified breast cancer. Furthermore, we discovered that different types of genetic abnormalities (mutation versus amplification) within the same cancer driver gene (PIK3CA or GATA3) were associated with opposite histologic changes in invasive breast cancer. In conclusion, our study suggests that histologic grade may serve as a biomarker to define cancer driving genetic events in vivo. PMID:27283966

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

    Science.gov (United States)

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

    2016-01-01

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

  20. Onco-proteogenomics: cancer proteomics joins forces with genomics.

    Science.gov (United States)

    Alfaro, Javier A; Sinha, Ankit; Kislinger, Thomas; Boutros, Paul C

    2014-11-01

    The complexities of tumor genomes are rapidly being uncovered, but how they are regulated into functional proteomes remains poorly understood. Standard proteomics workflows use databases of known proteins, but these databases do not capture the uniqueness of the cancer transcriptome, with its point mutations, unusual splice variants and gene fusions. Onco-proteogenomics integrates mass spectrometry-generated data with genomic information to identify tumor-specific peptides. Linking tumor-derived DNA, RNA and protein measurements into a central-dogma perspective has the potential to improve our understanding of cancer biology. PMID:25357240

  1. Comprehensive genomic profiles of small cell lung cancer

    OpenAIRE

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

    2015-01-01

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

  2. Genomic analysis and selected molecular pathways in rare cancers

    International Nuclear Information System (INIS)

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

  3. Quantification of read species behavior within whole genome sequencing of cancer genomes for the stratification and visualization of genomic variation.

    Science.gov (United States)

    Hibsh, Dror; Buetow, Kenneth H; Yaari, Gur; Efroni, Sol

    2016-05-19

    The cancer genome is abnormal genome, and the ability to monitor its sequence had undergone a technological revolution. Yet prognosis and diagnosis remain an expert-based decision, with only limited abilities to provide machine-based decisions. We introduce a heterogeneity-based method for stratifying and visualizing whole-genome sequencing (WGS) reads. This method uses the heterogeneity within WGS reads to markedly reduce the dimensionality of next-generation sequencing data; it is available through the tool HiBS (Heterogeneity-Based Subclassification) that allows cancer sample classification. We validated HiBS using >200 WGS samples from nine different cancer types from The Cancer Genome Atlas (TCGA). With HiBS, we show progress with two WGS related issues: (i) differentiation between normal (NB) and tumor (TP) samples based solely on the information structure of their WGS data, and (ii) identification of specific regions of chromosomal amplification/deletion and their association with tumor stage. By comparing results to those obtained through available WGS analyses tools, we demonstrate some of the novelties obtained by the approach implemented in HiBS and also show nearly perfect normal/tumor classification, used to identify known and unknown chromosomal aberrations. Finally, the HiBS index has been associated with breast cancer tumor stage. PMID:26809676

  4. 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

  5. Multiscale modeling of three-dimensional genome

    Science.gov (United States)

    Zhang, Bin; Wolynes, Peter

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

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

    Science.gov (United States)

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

    2009-01-01

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

  7. 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.

  8. 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.

  9. Cancer Genomics and Biology 2015 – Meeting Report

    Science.gov (United States)

    Chow, Louis WC.; Costa, Luis; Teh, Bin-Tean; Li, Da-Qiang; Feng, Gu; Guan, Xin-Yuan; Nair, Asha; Zhu, Li; Sugimoto, Masahiro; Dutt, Amit; Toi, Masakazu; Gupta, Sudeep; Badwe, Rajendra; Knapp, Stefan; Pillai, M. Radhakrishna; Kumar, Rakesh

    2016-01-01

    The Cancer Genomics and Biology 2015 meeting embodied a three way collaboration among colleagues from the Global Cancer Genomics Consortium (GCGC), the Unifaith Cancer Institute China and Jiujiang University of China. The meeting marks the fifth and the last meeting of GCGC, which was formed in 2010. Previous four GCGC meetings have been held at the Tata Memorial Center- Mumbai, Institute of Molecular Medicine-Lisbon, and Graduate Medical School Kyoto University-Kyoto. In contrast to the genomic themes of the previous meetings, the 2015 conference theme was at the interface of laboratory and translation research and emerging therapeutics as reflected in the shared interests of all three collaborative entities – Cancer Genomics and Biology 2015. This year's conference was co-organized by the Jiujiang University at the Run Run Shaw building, Jiujiang University, Jiujiang City, China, on November 13 and 14, 2015. The conference attracted over 174 participants with 13 platform presentations. Scientific sessions included a plenary and five platform scientific sessions with themes ranging from biomarkers, stem cells and markers of the tumor microenvironment, proteomics and epigenetics, big data, to hormone and expression profiles. The meeting concluded with closing remarks by conference co-chairs emphasizing with the need to broaden membership across the globe, establishing priorities, and redrafting a white paper to launch a new consortium.

  10. Genomic Predictors of Outcome in Prostate Cancer

    NARCIS (Netherlands)

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

    2015-01-01

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

  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. Significance of duon mutations in cancer genomes

    OpenAIRE

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

    2016-01-01

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

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

    Science.gov (United States)

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

    2015-09-22

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

  15. 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.

  16. 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.

  17. Median Approximations for Genomes Modeled as Matrices.

    Science.gov (United States)

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

    2016-04-01

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

  18. Genome Sequencing and Analysis of the Tasmanian Devil and Its Transmissible Cancer

    OpenAIRE

    Murchison, Elizabeth P.; Schulz-Trieglaff, Ole B.; Ning, Zemin; Alexandrov, Ludmil B.; Bauer, Markus J.; Fu, Beiyuan; Hims, Matthew; Ding, Zhihao; Ivakhno, Sergii; Stewart, Caitlin; Ng, Bee Ling; Wong, Wendy; Aken, Bronwen; White, Simon; Alsop, Amber

    2012-01-01

    Summary The Tasmanian devil (Sarcophilus harrisii), the largest marsupial carnivore, is endangered due to a transmissible facial cancer spread by direct transfer of living cancer cells through biting. Here we describe the sequencing, assembly, and annotation of the Tasmanian devil genome and whole-genome sequences for two geographically distant subclones of the cancer. Genomic analysis suggests that the cancer first arose from a female Tasmanian devil and that the clone has subsequently genet...

  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. PMID:18487361

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

    Directory of Open Access Journals (Sweden)

    Rachael Natrajan

    2016-02-01

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

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

    Science.gov (United States)

    Natrajan, Rachael; Sailem, Heba; Mardakheh, Faraz K.; Arias Garcia, Mar; Tape, Christopher J.; Dowsett, Mitch; Bakal, Chris; Yuan, Yinyin

    2016-01-01

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

  2. Mouse models of colorectal cancer

    Institute of Scientific and Technical Information of China (English)

    Yunguang Tong; Wancai Yang; H. Phillip Koeffler

    2011-01-01

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

  3. Advances in Swine Biomedical Model Genomics

    Directory of Open Access Journals (Sweden)

    Joan K. Lunney

    2007-01-01

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

  4. 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...

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

    Science.gov (United States)

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

  6. Breakpoint analysis of transcriptional and genomic profiles uncovers novel gene fusions spanning multiple human cancer types.

    Directory of Open Access Journals (Sweden)

    Craig P Giacomini

    2013-04-01

    Full Text Available Gene fusions, like BCR/ABL1 in chronic myelogenous leukemia, have long been recognized in hematologic and mesenchymal malignancies. The recent finding of gene fusions in prostate and lung cancers has motivated the search for pathogenic gene fusions in other malignancies. Here, we developed a "breakpoint analysis" pipeline to discover candidate gene fusions by tell-tale transcript level or genomic DNA copy number transitions occurring within genes. Mining data from 974 diverse cancer samples, we identified 198 candidate fusions involving annotated cancer genes. From these, we validated and further characterized novel gene fusions involving ROS1 tyrosine kinase in angiosarcoma (CEP85L/ROS1, SLC1A2 glutamate transporter in colon cancer (APIP/SLC1A2, RAF1 kinase in pancreatic cancer (ATG7/RAF1 and anaplastic astrocytoma (BCL6/RAF1, EWSR1 in melanoma (EWSR1/CREM, CDK6 kinase in T-cell acute lymphoblastic leukemia (FAM133B/CDK6, and CLTC in breast cancer (CLTC/VMP1. Notably, while these fusions involved known cancer genes, all occurred with novel fusion partners and in previously unreported cancer types. Moreover, several constituted druggable targets (including kinases, with therapeutic implications for their respective malignancies. Lastly, breakpoint analysis identified new cell line models for known rearrangements, including EGFRvIII and FIP1L1/PDGFRA. Taken together, we provide a robust approach for gene fusion discovery, and our results highlight a more widespread role of fusion genes in cancer pathogenesis.

  7. Integrating genomics in head and neck cancer treatment: Promises and pitfalls.

    Science.gov (United States)

    Thariat, Juliette; Vignot, Stéphane; Lapierre, Ariane; Falk, Alexander T; Guigay, Joel; Van Obberghen-Schilling, Ellen; Milano, Gerard

    2015-09-01

    Head and neck squamous cell carcinomas (HNSCC) represent a multifactorial disease of poor prognosis. They have lagged behind other cancers in terms of personalized therapy. With expansion and high throughput sequencing methods, recent landmark exonic studies and Cancer Genome Atlas data have identified genes relevant to carcinogenesis and cancer progression. Mutational profiles and rates vary widely depending on exposure to carcinogens, anatomic subsites and human papilloma virus (HPV) infection. Tumors may exhibit specific, tissue-specific, not exclusively HPV-related, gene alterations, such those observed in oral cavity cancers in Asia or Occident. Except for the PI3K pathway, the rate of mutations in HPV+ cancers is much lower than in tobacco/alcohol-related cancers. Somatic driver mutation analyses show that relatively few driver genes are druggable in HNSCC and that tumor suppressor gene alterations prevail. More mature for therapeutic applications is the oncogenic PI3K pathway, with preclinical human xenograft models suggesting that PI3KCA pathway mutations may be used as predictive biomarkers and clinical data showing efficacy of mTOR/Akt inhibitors. Therapeutic guidance, to date, relies on classical histoprognostic factors, anatomic subsite and HPV status, with integration of hierarchized supervised mutational profiling to provide additional therapeutic options in advanced HNSCC in a near future. Unsupervised controlled genomic analyses remain necessary to unravel potentially relevant genes. PMID:25979769

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

    Directory of Open Access Journals (Sweden)

    Jian-Wei Liang

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

  9. Animal Models of Colorectal Cancer

    Science.gov (United States)

    Johnson, Robert L.; Fleet, James C.

    2012-01-01

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

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

    Science.gov (United States)

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

    2005-03-20

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

  11. Advances in Swine Biomedical Model Genomics

    OpenAIRE

    Lunney, Joan K.

    2007-01-01

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

  12. 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.

  13. Cancer Metabolism: A Modeling Perspective

    DEFF Research Database (Denmark)

    Ghaffari, Pouyan; Mardinoglu, Adil; Nielsen, Jens

    2015-01-01

    . 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...... 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...... 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...

  14. 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.

  15. 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.

  16. 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.  

  17. 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.

  18. Engineered Swine Models of Cancer.

    Science.gov (United States)

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

    2016-01-01

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

  19. Engineered Swine Models of Cancer

    Science.gov (United States)

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

    2016-01-01

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

  20. 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.

  1. Genome profiling of ERBB2-amplified breast cancers

    International Nuclear Information System (INIS)

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

  2. The Cancer Genomics Hub (CGHub): overcoming cancer through the power of torrential data.

    Science.gov (United States)

    Wilks, Christopher; Cline, Melissa S; Weiler, Erich; Diehkans, Mark; Craft, Brian; Martin, Christy; Murphy, Daniel; Pierce, Howdy; Black, John; Nelson, Donavan; Litzinger, Brian; Hatton, Thomas; Maltbie, Lori; Ainsworth, Michael; Allen, Patrick; Rosewood, Linda; Mitchell, Elizabeth; Smith, Bradley; Warner, Jim; Groboske, John; Telc, Haifang; Wilson, Daniel; Sanford, Brian; Schmidt, Hannes; Haussler, David; Maltbie, Daniel

    2014-01-01

    The Cancer Genomics Hub (CGHub) is the online repository of the sequencing programs of the National Cancer Institute (NCI), including The Cancer Genomics Atlas (TCGA), the Cancer Cell Line Encyclopedia (CCLE) and the Therapeutically Applicable Research to Generate Effective Treatments (TARGET) projects, with data from 25 different types of cancer. The CGHub currently contains >1.4 PB of data, has grown at an average rate of 50 TB a month and serves >100 TB per week. The architecture of CGHub is designed to support bulk searching and downloading through a Web-accessible application programming interface, enforce patient genome confidentiality in data storage and transmission and optimize for efficiency in access and transfer. In this article, we describe the design of these three components, present performance results for our transfer protocol, GeneTorrent, and finally report on the growth of the system in terms of data stored and transferred, including estimated limits on the current architecture. Our experienced-based estimates suggest that centralizing storage and computational resources is more efficient than wide distribution across many satellite labs. Database URL: https://cghub.ucsc.edu. PMID:25267794

  3. Human DNA repair diseases: From genome instability to cancer

    Directory of Open Access Journals (Sweden)

    Carlos R. Machado

    1997-12-01

    Full Text Available Several human genetic syndromes have long been recognized to be defective in DNA repair mechanisms. This was first discovered by Cleaver (1968, who showed that cells from patients with xeroderma pigmentosum (XP were defective for the ability to remove ultraviolet (UV-induced lesions from their genome. Since then, new discoveries have promoted DNA repair studies to one of the most exciting areas of molecular biology. The present work intends to give a brief summary of the main known human genetic diseases related to DNA repair and how they may be linked to acquired diseases such as cancer

  4. Functional genomics of the chicken - a model organism

    Science.gov (United States)

    The chicken has reached model organism status after genome sequencing and development of high-throughput tools for the exploration of functional elements of the genome. Functional genomics focuses on understanding the function and regulation of genes and gene products on a global or genome-wide scal...

  5. 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.

  6. 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.

  7. The Mouse Genome Database (MGD): premier model organism resource for mammalian genomics and genetics

    OpenAIRE

    Blake, J. A.; Bult, C. J.; J.A. Kadin; J.E. Richardson; Eppig, J T

    2010-01-01

    The Mouse Genome Database (MGD) is the community model organism database for the laboratory mouse and the authoritative source for phenotype and functional annotations of mouse genes. MGD includes a complete catalog of mouse genes and genome features with integrated access to genetic, genomic and phenotypic information, all serving to further the use of the mouse as a model system for studying human biology and disease. MGD is a major component of the Mouse Genome Informatics (MGI, http://www...

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

    Directory of Open Access Journals (Sweden)

    Moreau Thierry

    2010-03-01

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

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

    Science.gov (United States)

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

    2016-01-01

    Somatically acquired genomic alterations that drive oncogenic cellular processes are of great scientific and clinical interest. Since the initiation of large-scale cancer genomic projects (e.g., the Cancer Genome Project, The Cancer Genome Atlas, and the International Cancer Genome Consortium cancer genome projects), a number of web-based portals have been created to facilitate access to multidimensional oncogenomic data and assist with the interpretation of the data. The portals provide the visualization of small-size mutations, copy number variations, methylation, and gene/protein expression data that can be correlated with the available clinical, epidemiological, and molecular features. Additionally, the portals enable to analyze the gathered data with the use of various user-friendly statistical tools. Herein, we present a highly illustrated review of seven portals, i.e., Tumorscape, UCSC Cancer Genomics Browser, ICGC Data Portal, COSMIC, cBioPortal, IntOGen, and BioProfiling.de. All of the selected portals are user-friendly and can be exploited by scientists from different cancer-associated fields, including those without bioinformatics background. It is expected that the use of the portals will contribute to a better understanding of cancer molecular etiology and will ultimately accelerate the translation of genomic knowledge into clinical practice. PMID:26484415

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2013-10-03

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

  13. A factor analysis model for functional genomics

    OpenAIRE

    Shioda Romy; Kustra Rafal; Zhu Mu

    2006-01-01

    Abstract Background Expression array data are used to predict biological functions of uncharacterized genes by comparing their expression profiles to those of characterized genes. While biologically plausible, this is both statistically and computationally challenging. Typical approaches are computationally expensive and ignore correlations among expression profiles and functional categories. Results We propose a factor analysis model (FAM) for functional genomics and give a two-step algorith...

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

    Science.gov (United States)

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

    2016-06-01

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

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

    OpenAIRE

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

    2015-01-01

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

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

    Science.gov (United States)

    Geifman, Nophar; Butte, Atul J.

    2016-01-01

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

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

    OpenAIRE

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

    2014-01-01

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

  18. 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.

  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. Genomic instability and radiation risk in molecular pathways to colon cancer.

    Science.gov (United States)

    Kaiser, Jan Christian; Meckbach, Reinhard; Jacob, Peter

    2014-01-01

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

  1. Genomic instability and radiation risk in molecular pathways to colon cancer.

    Directory of Open Access Journals (Sweden)

    Jan Christian Kaiser

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

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

    OpenAIRE

    Aaraby Yoheswaran Nielsen; Morten Frier Gjerstorff

    2016-01-01

    Genomic instability is a hallmark of human cancer and an enabling factor for the genetic alterations that drive cancer development. The processes involved in genomic instability resemble those of meiosis, where genetic material is interchanged between homologous chromosomes. In most types of human cancer, epigenetic changes, including hypomethylation of gene promoters, lead to the ectopic expression of a large number of proteins normally restricted to the germ cells of the testis. Due to the ...

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

    OpenAIRE

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

    2012-01-01

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

  4. The Impact of Genomic Profiling for Novel Cancer Therapy--Recent Progress in Non-Small Cell Lung Cancer.

    Science.gov (United States)

    Xie, Jingwu; Zhang, Xiaoli

    2016-01-20

    There is high expectation for significant improvements in cancer patient care after completion of the human genome project in 2003. Through pains-taking analyses of genomic profiles in cancer patients, a number of targetable gene alterations have been discovered, with some leading to novel therapies, such as activating mutations of EGFR, BRAF and ALK gene fusions. As a result, clinical management of cancer through targeted therapy has finally become a reality for a subset of cancers, such as lung adenocarcinomas and melanomas. In this review, we summarize how gene mutation discovery leads to new treatment strategies using non-small cell lung cancer (NSCLC) as an example. We also discuss possible future implications of cancer genome analyses. PMID:26842989

  5. Whole-genome characterization of chemoresistant ovarian cancer.

    Science.gov (United States)

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

    2015-05-28

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

  6. Mutation of mitochondria genome: trigger of somatic cell transforming to cancer cell.

    Science.gov (United States)

    Jianping, Du

    2010-01-01

    Nearly 80 years ago, scientist Otto Warburg originated a hypothesis that the cause of cancer is primarily a defect in energy metabolism. Following studies showed that mitochondria impact carcinogenesis to remodel somatic cells to cancer cells through modifying the genome, through maintenance the tumorigenic phenotype, and through apoptosis. And the Endosymbiotic Theory explains the origin of mitochondria and eukaryotes, on the other hands, the mitochondria also can fall back. Compared to chromosome genomes, the mitochondria genomes were not restricted by introns so they were mutated(fall back) easy. The result is that mitochondria lose function and internal environment of somatic cell become acid and evoked chromosome genomes to mutate, in the end somatic cells become cancer cells. It is the trigger of somatic cell transforming to cancer cell that mitochondria genome happen mutation and lose function. PMID:20181100

  7. 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.

  8. 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.

  9. Breast Cancer Risk Prediction Models

    Science.gov (United States)

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

  10. 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.

  11. 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.

  12. 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.

  13. 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.

  14. 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.

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

    International Nuclear Information System (INIS)

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

  16. 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 ...

  17. Genome sequencing and analysis of the Tasmanian devil and its transmissible cancer.

    Science.gov (United States)

    Murchison, Elizabeth P; Schulz-Trieglaff, Ole B; Ning, Zemin; Alexandrov, Ludmil B; Bauer, Markus J; Fu, Beiyuan; Hims, Matthew; Ding, Zhihao; Ivakhno, Sergii; Stewart, Caitlin; Ng, Bee Ling; Wong, Wendy; Aken, Bronwen; White, Simon; Alsop, Amber; Becq, Jennifer; Bignell, Graham R; Cheetham, R Keira; Cheng, William; Connor, Thomas R; Cox, Anthony J; Feng, Zhi-Ping; Gu, Yong; Grocock, Russell J; Harris, Simon R; Khrebtukova, Irina; Kingsbury, Zoya; Kowarsky, Mark; Kreiss, Alexandre; Luo, Shujun; Marshall, John; McBride, David J; Murray, Lisa; Pearse, Anne-Maree; Raine, Keiran; Rasolonjatovo, Isabelle; Shaw, Richard; Tedder, Philip; Tregidgo, Carolyn; Vilella, Albert J; Wedge, David C; Woods, Gregory M; Gormley, Niall; Humphray, Sean; Schroth, Gary; Smith, Geoffrey; Hall, Kevin; Searle, Stephen M J; Carter, Nigel P; Papenfuss, Anthony T; Futreal, P Andrew; Campbell, Peter J; Yang, Fengtang; Bentley, David R; Evers, Dirk J; Stratton, Michael R

    2012-02-17

    The Tasmanian devil (Sarcophilus harrisii), the largest marsupial carnivore, is endangered due to a transmissible facial cancer spread by direct transfer of living cancer cells through biting. Here we describe the sequencing, assembly, and annotation of the Tasmanian devil genome and whole-genome sequences for two geographically distant subclones of the cancer. Genomic analysis suggests that the cancer first arose from a female Tasmanian devil and that the clone has subsequently genetically diverged during its spread across Tasmania. The devil cancer genome contains more than 17,000 somatic base substitution mutations and bears the imprint of a distinct mutational process. Genotyping of somatic mutations in 104 geographically and temporally distributed Tasmanian devil tumors reveals the pattern of evolution and spread of this parasitic clonal lineage, with evidence of a selective sweep in one geographical area and persistence of parallel lineages in other populations. PMID:22341448

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

    International Nuclear Information System (INIS)

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

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

    Science.gov (United States)

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

    2012-07-26

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

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

    Science.gov (United States)

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

    2012-01-01

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

  1. 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.

  2. 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; Krzystanek, Marcin; Favero, Francesco; Wang, Zhigang C; Richardson, Andrea L; Silver, Daniel P; Szallasi, Zoltan Imre; Birkbak, Nicolai Juul

    2015-01-01

    accumulation of similar genomic scars also show increased sensitivity to platinum-based chemotherapy. Therefore, reliable biomarkers to identify DNA repair-deficient cancers prior to treatment may be useful for directing patients to platinum chemotherapy and possibly PARP inhibitors. Recently, three SNP array......-based signatures of chromosomal instability were published that each quantitate a distinct type of genomic scar considered likely to be caused by improper DNA repair. They measure telomeric allelic imbalance (named NtAI), large scale transition (named LST), and loss of heterozygosity (named HRD-LOH), and it is...... suggested that these signatures may act as biomarkers for the state of DNA repair deficiency in a given cancer. We explored the pan-cancer distribution of scores of the three signatures utilizing a panel of 5371 tumors representing 15 cancer types from The Cancer Genome Atlas, and found a good correlation...

  3. Next-generation sequence analysis of cancer xenograft models.

    Directory of Open Access Journals (Sweden)

    Fernando J Rossello

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

  4. Engineered Swine Models of Cancer

    OpenAIRE

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

    2016-01-01

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

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

    Science.gov (United States)

    Nielsen, Aaraby Yoheswaran; Gjerstorff, Morten Frier

    2016-01-01

    Genomic instability is a hallmark of human cancer and an enabling factor for the genetic alterations that drive cancer development. The processes involved in genomic instability resemble those of meiosis, where genetic material is interchanged between homologous chromosomes. In most types of human cancer, epigenetic changes, including hypomethylation of gene promoters, lead to the ectopic expression of a large number of proteins normally restricted to the germ cells of the testis. Due to the 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. PMID:27275820

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

    OpenAIRE

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

    2008-01-01

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

  7. Needles in a haystack: finding recurrent genomic changes in breast cancer

    OpenAIRE

    Cidado, Justin; Beaver, Julia A.; Park, Ben Ho

    2013-01-01

    Significant advances over the past decade have enabled scientists to obtain increasingly detailed molecular profiles of breast cancer. The recent analysis by The Cancer Genome Atlas published in the September 2012 issue of Nature is the most comprehensive description of breast cancer 'omics' to date. This study is impressive in its scope and scale, with the findings reconfirming the heterogeneity of breast cancer and highlighting the future challenges in translating these findings for clinica...

  8. Recent patents and advances in genomic biomarker discovery for colorectal cancers.

    Science.gov (United States)

    Quyun, Chen; Ye, Zhiyun; Lin, Sheng-Cai; Lin, Biaoyang

    2010-06-01

    Colorectal cancer (CRC) is the third most common cancer in the world. Early diagnosis of colorectal cancer is the key to reducing the death rate of CRC patients. Predicting the response to current therapeutic modalities of CRC will also have a great impact on patient care. This review summarizes recent advances and patents in biomarker discovery in CRC under five major categories; including genomic changes, expression changes, mutations, epigenetic changes and microRNAs. The interesting patents include: 1) a patent for a method to differentiate normal exfoliated cells from cancer cells based on whether they were subjected to apoptosis and DNA degradation; 2) A model (PM-33 multiple molecular marker model) based on expression changes of up-regulation of the MDM2, DUSP6, and NFl genes down-regulation of the RNF4, MMD and EIF2S3 genes, which achieved an 88% sensitivity, and an 82% specificity for CRC diagnosis; 3) gene mutations in PTEN, KRAS, PIK3CA for predicting the response to anti-EGFR therapies, a common drug used for CRC treatment; 4) patents on epigenetic changes of ITGA4, SEPT9, ALX4, TFAP2E FOXL2, SARM1, ID4 etc. and many key miRNAs. Finally, future directions in the fields were commented on or suggested, including the combination of multiple categories of biomarkers and pathway central or network-based biomarker panels. PMID:20426761

  9. 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.

  10. 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.

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

    OpenAIRE

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

    2011-01-01

    Abstract Background It has been postulated that ionizing radiation induces breast cancers among atomic bomb (A-bomb) survivors. We have reported a higher incidence of HER2 and C-MYC oncogene amplification in breast cancers from A-bomb survivors. The purpose of this study was to clarify the effect of A-bomb radiation exposure on genomic instability (GIN), which is an important hallmark of carcinogenesis, in archival formalin-fixed paraffin-embedded (FFPE) tissues of breast cancer by using micr...

  12. 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....

  13. The search for cis-regulatory driver mutations in cancer genomes

    OpenAIRE

    Poulos, Rebecca C.; Sloane, Mathew A; Hesson, Luke B; Wong, Jason W. H.

    2015-01-01

    With the advent of high-throughput and relatively inexpensive whole-genome sequencing technology, the focus of cancer research has begun to shift toward analyses of somatic mutations in non-coding cis-regulatory elements of the cancer genome. Cis-regulatory elements play an important role in gene regulation, with mutations in these elements potentially resulting in changes to the expression of linked genes. The recent discoveries of recurrent TERT promoter mutations in melanoma, and recurrent...

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

    OpenAIRE

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

    2013-01-01

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

  15. 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 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...... using the probabilistic logic programming language and machine learning system PRISM - a fast and efficient model prototyping environment, using bacterial gene finding performance as a benchmark of signal strength. The model is used to prune a set of gene predictions from an underlying gene finder and...

  16. Mouse models for colorectal cancer

    OpenAIRE

    KARIM, BAKTIAR O.; Huso, David L.

    2013-01-01

    Colorectal cancer (CRC) is the third leading cause of cancer-related death in the United States, with the number of affected people increasing. There are many risk factors that increase CRC risk, including family or personal history of CRC, smoking, consumption of red meat, obesity, and alcohol consumption. Conversely, increased screening, maintaining healthy body weight, not smoking, and limiting intake of red meat are all associated with reduced CRC morbidity and mortality. Mouse models of ...

  17. A Genome-Wide Systematic Analysis Reveals Different and Predictive Proliferation Expression Signatures of Cancerous vs. Non-Cancerous Cells

    OpenAIRE

    Waldman, Yedael Y.; Geiger, Tamar; Ruppin, Eytan

    2013-01-01

    Understanding cell proliferation mechanisms has been a long-lasting goal of the scientific community and specifically of cancer researchers. Previous genome-scale studies of cancer proliferation determinants have mainly relied on knockdown screens aimed to gauge their effects on cancer growth. This powerful approach has several limitations such as off-target effects, partial knockdown, and masking effects due to functional backups. Here we employ a complementary approach and assign each gene ...

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

    Science.gov (United States)

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

  19. 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.

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

    OpenAIRE

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

    2008-01-01

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

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

    Science.gov (United States)

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

    2015-01-01

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

  2. Tumor-Derived Cell Lines as Molecular Models of Cancer Pharmacogenomics.

    Science.gov (United States)

    Goodspeed, Andrew; Heiser, Laura M; Gray, Joe W; Costello, James C

    2016-01-01

    Compared with normal cells, tumor cells have undergone an array of genetic and epigenetic alterations. Often, these changes underlie cancer development, progression, and drug resistance, so the utility of model systems rests on their ability to recapitulate the genomic aberrations observed in primary tumors. Tumor-derived cell lines have long been used to study the underlying biologic processes in cancer, as well as screening platforms for discovering and evaluating the efficacy of anticancer therapeutics. Multiple -omic measurements across more than a thousand cancer cell lines have been produced following advances in high-throughput technologies and multigroup collaborative projects. These data complement the large, international cancer genomic sequencing efforts to characterize patient tumors, such as The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC). Given the scope and scale of data that have been generated, researchers are now in a position to evaluate the similarities and differences that exist in genomic features between cell lines and patient samples. As pharmacogenomics models, cell lines offer the advantages of being easily grown, relatively inexpensive, and amenable to high-throughput testing of therapeutic agents. Data generated from cell lines can then be used to link cellular drug response to genomic features, where the ultimate goal is to build predictive signatures of patient outcome. This review highlights the recent work that has compared -omic profiles of cell lines with primary tumors, and discusses the advantages and disadvantages of cancer cell lines as pharmacogenomic models of anticancer therapies. PMID:26248648

  3. 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.

  4. 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.

  5. 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

  6. Personalized medicine approaches for colon cancer driven by genomics and systems biology: OncoTrack.

    Science.gov (United States)

    Henderson, David; Ogilvie, Lesley A; Hoyle, Nicholas; Keilholz, Ulrich; Lange, Bodo; Lehrach, Hans

    2014-09-01

    The post-genomic era promises to pave the way to a personalized understanding of disease processes, with technological and analytical advances helping to solve some of the world's health challenges. Despite extraordinary progress in our understanding of cancer pathogenesis, the disease remains one of the world's major medical problems. New therapies and diagnostic procedures to guide their clinical application are urgently required. OncoTrack, a consortium between industry and academia, supported by the Innovative Medicines Initiative, signifies a new era in personalized medicine, which synthesizes current technological advances in omics techniques, systems biology approaches, and mathematical modeling. A truly personalized molecular imprint of the tumor micro-environment and subsequent diagnostic and therapeutic insight is gained, with the ultimate goal of matching the "right" patient to the "right" drug and identifying predictive biomarkers for clinical application. This comprehensive mapping of the colon cancer molecular landscape in tandem with crucial, clinical functional annotation for systems biology analysis provides unprecedented insight and predictive power for colon cancer management. Overall, we show that major biotechnological developments in tandem with changes in clinical thinking have laid the foundations for the OncoTrack approach and the future clinical application of a truly personalized approach to colon cancer theranostics. PMID:25074435

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

    Directory of Open Access Journals (Sweden)

    Allison Silverstein

    2016-01-01

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

  8. A somatic reference standard for cancer genome sequencing

    Science.gov (United States)

    Craig, David W.; Nasser, Sara; Corbett, Richard; Chan, Simon K.; Murray, Lisa; Legendre, Christophe; Tembe, Waibhav; Adkins, Jonathan; Kim, Nancy; Wong, Shukmei; Baker, Angela; Enriquez, Daniel; Pond, Stephanie; Pleasance, Erin; Mungall, Andrew J.; Moore, Richard A.; McDaniel, Timothy; Ma, Yussanne; Jones, Steven J. M.; Marra, Marco A.; Carpten, John D.; Liang, Winnie S.

    2016-01-01

    Large-scale multiplexed identification of somatic alterations in cancer has become feasible with next generation sequencing (NGS). However, calibration of NGS somatic analysis tools has been hampered by a lack of tumor/normal reference standards. We thus performed paired PCR-free whole genome sequencing of a matched metastatic melanoma cell line (COLO829) and normal across three lineages and across separate institutions, with independent library preparations, sequencing, and analysis. We generated mean mapped coverages of 99X for COLO829 and 103X for the paired normal across three institutions. Results were combined with previously generated data allowing for comparison to a fourth lineage on earlier NGS technology. Aggregate variant detection led to the identification of consensus variants, including key events that represent hallmark mutation types including amplified BRAF V600E, a CDK2NA small deletion, a 12 kb PTEN deletion, and a dinucleotide TERT promoter substitution. Overall, common events include >35,000 point mutations, 446 small insertion/deletions, and >6,000 genes affected by copy number changes. We present this reference to the community as an initial standard for enabling quantitative evaluation of somatic mutation pipelines across institutions. PMID:27094764

  9. A somatic reference standard for cancer genome sequencing.

    Science.gov (United States)

    Craig, David W; Nasser, Sara; Corbett, Richard; Chan, Simon K; Murray, Lisa; Legendre, Christophe; Tembe, Waibhav; Adkins, Jonathan; Kim, Nancy; Wong, Shukmei; Baker, Angela; Enriquez, Daniel; Pond, Stephanie; Pleasance, Erin; Mungall, Andrew J; Moore, Richard A; McDaniel, Timothy; Ma, Yussanne; Jones, Steven J M; Marra, Marco A; Carpten, John D; Liang, Winnie S

    2016-01-01

    Large-scale multiplexed identification of somatic alterations in cancer has become feasible with next generation sequencing (NGS). However, calibration of NGS somatic analysis tools has been hampered by a lack of tumor/normal reference standards. We thus performed paired PCR-free whole genome sequencing of a matched metastatic melanoma cell line (COLO829) and normal across three lineages and across separate institutions, with independent library preparations, sequencing, and analysis. We generated mean mapped coverages of 99X for COLO829 and 103X for the paired normal across three institutions. Results were combined with previously generated data allowing for comparison to a fourth lineage on earlier NGS technology. Aggregate variant detection led to the identification of consensus variants, including key events that represent hallmark mutation types including amplified BRAF V600E, a CDK2NA small deletion, a 12 kb PTEN deletion, and a dinucleotide TERT promoter substitution. Overall, common events include >35,000 point mutations, 446 small insertion/deletions, and >6,000 genes affected by copy number changes. We present this reference to the community as an initial standard for enabling quantitative evaluation of somatic mutation pipelines across institutions. PMID:27094764

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

    Science.gov (United States)

    Olson, P N

    2007-08-01

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

  11. 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. PMID:26909576

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

    OpenAIRE

    Pesko, Kendra; Voigt, Emily A.; Swick, Adam; Morley, Valerie J.; Timm, Collin; Yin, John; Paul E. Turner

    2015-01-01

    Gene order is often highly conserved within taxonomic groups, such that organisms with rearranged genomes tend to be less fit than wild type 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 non-segmented RNA viruses (order Mononegavirales) have specific genome architecture: 3′ UTR – core protein genes – envelo...

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

    Science.gov (United States)

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

    2012-01-01

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

  14. Genome Informed Trait-Based Models

    Science.gov (United States)

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

    2013-12-01

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

  15. Aquatic models, genomics and chemical risk management.

    Science.gov (United States)

    Cheng, Keith C; Hinton, David E; Mattingly, Carolyn J; Planchart, Antonio

    2012-01-01

    The 5th Aquatic Animal Models for Human Disease meeting follows four previous meetings (Nairn et al., 2001; Schmale, 2004; Schmale et al., 2007; Hinton et al., 2009) in which advances in aquatic animal models for human disease research were reported, and community discussion of future direction was pursued. At this meeting, discussion at a workshop entitled Bioinformatics and Computational Biology with Web-based Resources (20 September 2010) led to an important conclusion: Aquatic model research using feral and experimental fish, in combination with web-based access to annotated anatomical atlases and toxicological databases, yields data that advance our understanding of human gene function, and can be used to facilitate environmental management and drug development. We propose here that the effects of genes and environment are best appreciated within an anatomical context - the specifically affected cells and organs in the whole animal. We envision the use of automated, whole-animal imaging at cellular resolution and computational morphometry facilitated by high-performance computing and automated entry into toxicological databases, as anchors for genetic and toxicological data, and as connectors between human and model system data. These principles should be applied to both laboratory and feral fish populations, which have been virtually irreplaceable sentinals for environmental contamination that results in human morbidity and mortality. We conclude that automation, database generation, and web-based accessibility, facilitated by genomic/transcriptomic data and high-performance and cloud computing, will potentiate the unique and potentially key roles that aquatic models play in advancing systems biology, drug development, and environmental risk management. PMID:21763781

  16. 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...

  17. Will we cure cancer by sequencing thousands of genomes?

    OpenAIRE

    Nicholson, Joshua M.

    2013-01-01

    Abstract The promise to understand cancer and develop efficacious therapies by sequencing thousands of cancers has not occurred. Mutations in specific genes termed oncogenes and tumor suppressor genes are extremely heterogeneous amongst the same type of cancer as well as between cancers. They provide little selective advantage to the cancer and in functional tests have yet to be shown to be sufficient for transformation. Here I discuss the karyotyptic theory of cancer and ask...

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

    Science.gov (United States)

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

    2016-01-01

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

  19. Facilitating a culture of responsible and effective sharing of cancer genome data.

    Science.gov (United States)

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

    2016-05-01

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

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

    OpenAIRE

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

    2011-01-01

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

  1. 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

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

    Directory of Open Access Journals (Sweden)

    Li Wenting

    2012-06-01

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

  3. A genome-wide systematic analysis reveals different and predictive proliferation expression signatures of cancerous vs. non-cancerous cells.

    Directory of Open Access Journals (Sweden)

    Yedael Y Waldman

    Full Text Available Understanding cell proliferation mechanisms has been a long-lasting goal of the scientific community and specifically of cancer researchers. Previous genome-scale studies of cancer proliferation determinants have mainly relied on knockdown screens aimed to gauge their effects on cancer growth. This powerful approach has several limitations such as off-target effects, partial knockdown, and masking effects due to functional backups. Here we employ a complementary approach and assign each gene a cancer Proliferation Index (cPI that quantifies the association between its expression levels and growth rate measurements across 60 cancer cell lines. Reassuringly, genes found essential in cancer gene knockdown screens exhibit significant positive cPI values, while tumor suppressors exhibit significant negative cPI values. Cell cycle, DNA replication, splicing and protein production related processes are positively associated with cancer proliferation, while cellular migration is negatively associated with it - in accordance with the well known "go or grow" dichotomy. A parallel analysis of genes' non-cancerous proliferation indices (nPI across 224 lymphoblastoid cell lines reveals surprisingly marked differences between cancerous and non-cancerous proliferation. These differences highlight genes in the translation and spliceosome machineries as selective cancer proliferation-associated proteins. A cross species comparison reveals that cancer proliferation resembles that of microorganisms while non-cancerous proliferation does not. Furthermore, combining cancerous and non-cancerous proliferation signatures leads to enhanced prediction of patient outcome and gene essentiality in cancer. Overall, these results point to an inherent difference between cancerous and non-cancerous proliferation determinants, whose understanding may contribute to the future development of novel cancer-specific anti-proliferative drugs.

  4. An Integrative Genomics Approach for Associating GWAS Information with Triple-Negative Breast Cancer

    OpenAIRE

    Chindo Hicks; Ranjit Kumar; Antonio Pannuti; Kandis Backus; Alexandra Brown; Jesus Monico; Lucio Miele

    2013-01-01

    Genome-wide association studies (GWAS) have identified genetic variants associated with an increased risk of developing breast cancer. However, the association of genetic variants and their associated genes with the most aggressive subset of breast cancer, the triple-negative breast cancer (TNBC), remains a central puzzle in molecular epidemiology. The objective of this study was to determine whether genes containing single nucleotide polymorphisms (SNPs) associated with an increased risk of ...

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

    OpenAIRE

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

    2008-01-01

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

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

    OpenAIRE

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

    2016-01-01

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

  7. 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

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

    Science.gov (United States)

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

    2016-07-01

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

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

    Science.gov (United States)

    Eralp, Yesim

    2016-01-01

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

  10. 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,

  11. 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...

  12. Time series model based on global structure of complete genome

    CERN Document Server

    Yu, Z G; Anh, Vo

    2001-01-01

    A time series model based on the global structure of the complete genome is proposed. Three kinds of length sequences of the complete genome are considered. The correlation dimensions and Hurst exponents of the length sequences are calculated. Using these two exponents, some interesting results related to the problem of classification and evolution relationship of bacteria are obtained.

  13. 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...... pooling genomic DNA from 545 cases and 398 controls of European descent, and testing for allelic associations. We evaluated for replication 188 variants from the GWAS [56 variants for mucinous, 55 for endometrioid and clear cell, 53 for low-malignant potential (LMP) serous, and 24 for invasive serous EOC......], selected using pre-defined criteria. Genotypes from 13,188 cases and 23,164 controls of European descent were used to perform unconditional logistic regression under the log-additive genetic model; odds ratios (OR) and 95 % confidence intervals are reported. Nine variants tagging six loci were associated...

  14. 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.

  15. 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

  16. ANIMAL MODELS OF CANCER: A REVIEW

    OpenAIRE

    Archana M Navale

    2013-01-01

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

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

    International Nuclear Information System (INIS)

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

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

    Science.gov (United States)

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

    2015-03-26

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

  19. Mathematical and Statistical Modeling in Cancer Systems Biology

    Directory of Open Access Journals (Sweden)

    Rachael eHageman Blair

    2012-06-01

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

  20. A comparative genomics approach to understanding transmissible cancer in Tasmanian devils.

    Science.gov (United States)

    Deakin, Janine E; Belov, Katherine

    2012-01-01

    A fatal contagious cancer is driving an entire species to extinction. Comparative genomics will unravel the origin and evolution of devil facial tumor disease (DFTD). The DFTD allograft arose from a Schwann cell in a female Tasmanian devil more than 15 years ago; since then, the tumor has passed through at least 100,000 hosts, evolving and mutating along the way. Tumor genome sequencing and molecular cytogenetic technologies now allow direct comparisons of candidate genes involved in tumorigenesis in human cancers. As a stable transmissible cancer, DFTD provides unique insights into cancer development, progression, and immune evasion and is likely to help increase our understanding of human cancer. In addition, these studies provide hope for discoveries of drug targets or vaccine candidates that will prevent the extinction of this iconic Australian marsupial. PMID:22657390

  1. 13A. Integrative Cancer Care: The Life Over Cancer Model

    OpenAIRE

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

    2013-01-01

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

  2. Genomic profiles of colorectal cancers differ based on patient smoking status.

    Science.gov (United States)

    Swede, Helen; Bartos, Jeremy D; Chen, Neng; Shaukat, Aasma; Dutt, Smitha S; McQuaid, Devin A; Natarajan, Nachimuthu; Rodriguez-Bigas, Miguel A; Nowak, Norma J; Wiseman, Sam M; Alrawi, Sadir; Brenner, Bruce M; Petrelli, Nicholas J; Cummings, K Michael; Stoler, Daniel L; Anderson, Garth R

    2006-07-15

    Human sporadic colorectal cancer is the result of a lengthy somatic evolutionary process facilitated by various forms of genomic instability. Such instability arises endogenously from mutations in genes whose role is to preserve genomic integrity, and exogenously from environmental agents that generate genomic damage. We have found that cigarette smoking shifts the genomic profiles and genomic instability patterns of colorectal carcinomas. The genomic profiles of 57 consecutive cancers were examined; 31 cases were current or former smokers and 26 were nonsmokers. Genome-wide allelotypes of 348 markers were examined, along with comparative genomic hybridization (CGH) on ordered BAC microarrays, microsatellite instability, and inter-(simple sequence repeat) polymerase chain reaction instability. Tumors from nonsmokers exhibited losses of heterozygosity, particularly on chromosomes 14 and 18, whereas tumors from smokers exhibited a more diffuse pattern of allelic losses. Tumors from smokers exhibited higher overall rates of loss of heterozygosity, but showed lower rates of background microsatellite instability (MSI-L). On BAC array CGH, higher levels of generalized amplifications and deletions were observed in tumors from smokers, differentially affecting male smokers. In the transforming growth factor-beta signaling pathway, MADH4 mutations were more common in tumors from smokers, whereas transforming growth factor-beta RII mutations were more common among nonsmokers. PMID:16843098

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

    Directory of Open Access Journals (Sweden)

    Habermann Jens K

    2011-10-01

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

  4. 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

  5. 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...

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

    Science.gov (United States)

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

    2015-01-01

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

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

    Science.gov (United States)

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

    2015-01-01

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

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

    Science.gov (United States)

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

    2016-01-01

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

  9. 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.

  10. Clinical application of high-throughput genomic technologies for treatment selection in breast cancer

    OpenAIRE

    Hansen, Aaron R.; Bedard, Philippe L.

    2013-01-01

    Large-scale collaborative initiatives using next-generation DNA sequencing and other high-throughput technologies have begun to characterize the genomic landscape of breast cancer. These landmark studies have identified infrequent driver mutations that are potential targets for therapeutic intervention with approved or investigational drug treatments, among other important discoveries. Recently, many institutions have launched molecular screening programs that apply high-throughput genomic te...

  11. Use of genome-scale microbial models for metabolic engineering

    DEFF Research Database (Denmark)

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

    2004-01-01

    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...... 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....

  12. AACR precision medicine series: Highlights of the integrating clinical genomics and cancer therapy meeting.

    Science.gov (United States)

    Maggi, Elaine; Montagna, Cristina

    2015-12-01

    The American Association for Cancer Research (AACR) Precision Medicine Series "Integrating Clinical Genomics and Cancer Therapy" took place June 13-16, 2015 in Salt Lake City, Utah. The conference was co-chaired by Charles L. Sawyers form Memorial Sloan Kettering Cancer Center in New York, Elaine R. Mardis form Washington University School of Medicine in St. Louis, and Arul M. Chinnaiyan from University of Michigan in Ann Arbor. About 500 clinicians, basic science investigators, bioinformaticians, and postdoctoral fellows joined together to discuss the current state of Clinical Genomics and the advances and challenges of integrating Next Generation Sequencing (NGS) technologies into clinical practice. The plenary sessions and panel discussions covered current platforms and sequencing approaches adopted for NGS assays of cancer genome at several national and international institutions, different approaches used to map and classify targetable sequence variants, and how information acquired with the sequencing of the cancer genome is used to guide treatment options. While challenges still exist from a technological perspective, it emerged that there exists considerable need for the development of tools to aid the identification of the therapy most suitable based on the mutational profile of the somatic cancer genome. The process to match patients to ongoing clinical trials is still complex. In addition, the need for centralized data repositories, preferably linked to well annotated clinical records, that aid sharing of sequencing information is central to begin understanding the contribution of variants of unknown significance to tumor etiology and response to therapy. Here we summarize the highlights of this stimulating four-day conference with a major emphasis on the open problems that the clinical genomics community is currently facing and the tools most needed for advancing this field. PMID:26554403

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

    Science.gov (United States)

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

    2015-09-01

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

  14. 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.

  15. The Tip of the Iceberg: Clinical Implications of Genomic Sequencing Projects in Head and Neck Cancer

    Directory of Open Access Journals (Sweden)

    Andrew C. Birkeland

    2015-10-01

    Full Text Available Recent genomic sequencing studies have provided valuable insight into genetic aberrations in head and neck squamous cell carcinoma. Despite these great advances, certain hurdles exist in translating genomic findings to clinical care. Further correlation of genetic findings to clinical outcomes, additional analyses of subgroups of head and neck cancers and follow-up investigation into genetic heterogeneity are needed. While the development of targeted therapy trials is of key importance, numerous challenges exist in establishing and optimizing such programs. This review discusses potential upcoming steps for further genetic evaluation of head and neck cancers and implementation of genetic findings into precision medicine trials.

  16. Integrative genomic analyses reveal an androgen-driven somatic alteration landscape in early-onset prostate cancer

    DEFF Research Database (Denmark)

    Weischenfeldt, Joachim; Simon, Ronald; Feuerbach, Lars; Schlangen, Karin; Weichenhan, Dieter; Minner, Sarah; Wuttig, Daniela; Warnatz, Hans-Jörg; Stehr, Henning; Rausch, Tobias; Jäger, Natalie; Gu, Lei; Bogatyrova, Olga; Stütz, Adrian M; Claus, Rainer; Eils, Jürgen; Eils, Roland; Gerhäuser, Clarissa; Huang, Po-Hsien; Hutter, Barbara; Kabbe, Rolf; Lawerenz, Christian; Radomski, Sylwester; Bartholomae, Cynthia C; Fälth, Maria; Gade, Stephan; Schmidt, Manfred; Amschler, Nina; Haß, Thomas; Galal, Rami; Gjoni, Jovisa; Kuner, Ruprecht; Baer, Constance; Masser, Sawinee; von Kalle, Christof; Zichner, Thomas; Benes, Vladimir; Raeder, Benjamin; Mader, Malte; Amstislavskiy, Vyacheslav; Avci, Meryem; Lehrach, Hans; Parkhomchuk, Dmitri; Sultan, Marc; Burkhardt, Lia; Graefen, Markus; Huland, Hartwig; Kluth, Martina; Krohn, Antje; Sirma, Hüseyin; Stumm, Laura; Steurer, Stefan; Grupp, Katharina; Sültmann, Holger; Sauter, Guido; Plass, Christoph; Brors, Benedikt; Yaspo, Marie-Laure; Korbel, Jan O; Schlomm, Thorsten

    2013-01-01

    Early-onset prostate cancer (EO-PCA) represents the earliest clinical manifestation of prostate cancer. To compare the genomic alteration landscapes of EO-PCA with "classical" (elderly-onset) PCA, we performed deep sequencing-based genomics analyses in 11 tumors diagnosed at young age, and pursue...

  17. Genome-wide assessment of the association of rare and common copy number variations to testicular germ cell cancer

    DEFF Research Database (Denmark)

    Edsgard, Stefan Daniel; Dalgaard, Marlene Danner; Weinhold, Nils; Wesolowska, Agata; Rajpert-De Meyts, Ewa; Ottesen, Anne Marie; Juul, Anders; Skakkebæk, Niels Erik; Jensen, Thomas Skøt; Gupta, Ramneek; Leffers, Henrik; Brunak, Søren

    2013-01-01

    Testicular germ cell cancer (TGCC) is one of the most heritable forms of cancer. Previous genome-wide association studies have focused on single nucleotide polymorphisms, largely ignoring the influence of copy number variants (CNVs). Here we present a genome-wide study of CNV on a cohort of 212...

  18. Genome sequencing and analysis of the model grass Brachypodium distachyon.

    Science.gov (United States)

    2010-02-11

    Three subfamilies of grasses, the Ehrhartoideae, Panicoideae and Pooideae, provide the bulk of human nutrition and are poised to become major sources of renewable energy. Here we describe the genome sequence of the wild grass Brachypodium distachyon (Brachypodium), which is, to our knowledge, the first member of the Pooideae subfamily to be sequenced. Comparison of the Brachypodium, rice and sorghum genomes shows a precise history of genome evolution across a broad diversity of the grasses, and establishes a template for analysis of the large genomes of economically important pooid grasses such as wheat. The high-quality genome sequence, coupled with ease of cultivation and transformation, small size and rapid life cycle, will help Brachypodium reach its potential as an important model system for developing new energy and food crops. PMID:20148030

  19. 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.

  20. 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.

  1. 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

  2. Exploiting linkage disequilibrium in statistical modelling in quantitative genomics

    DEFF Research Database (Denmark)

    Wang, Lei

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

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

    OpenAIRE

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

    2016-01-01

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

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

    OpenAIRE

    Gerlinger, M; Swanton, C.

    2010-01-01

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

  5. A Mouse Model for Human Anal Cancer

    OpenAIRE

    Stelzer, Marie K.; Pitot, Henry C.; Liem, Amy; Schweizer, Johannes; Mahoney, Charles; Lambert, Paul F.

    2010-01-01

    Human anal cancers are associated with high-risk human papillomaviruses (HPVs) that cause other anogenital cancers and head and neck cancers. As with other cancers, HPV16 is the most common high-risk HPV in anal cancers. We describe the generation and characterization of a mouse model for human anal cancer. This model makes use of K14E6 and K14E7 transgenic mice in which the HPV16 E6 and E7 genes are directed in their expression to stratified squamous epithelia. HPV16 E6 and E7 possess oncoge...

  6. Cancer classification in the genomic era: five contemporary problems

    OpenAIRE

    Song, Qingxuan; Merajver, Sofia D.; Li, Jun Z.

    2015-01-01

    Classification is an everyday instinct as well as a full-fledged scientific discipline. Throughout the history of medicine, disease classification is central to how we develop knowledge, make diagnosis, and assign treatment. Here, we discuss the classification of cancer and the process of categorizing cancer subtypes based on their observed clinical and biological features. Traditionally, cancer nomenclature is primarily based on organ location, e.g., “lung cancer” designates a tumor originat...

  7. The Genomic and Metabolomic profiling of pancreas cancer

    OpenAIRE

    Sanyal, Sudip

    2015-01-01

    Despite the considerable expansion of knowledge in the development of pancreatic cancer, there has been little progress made in facilitating an early diagnosis of this disease and predicting an accurate response to treatment. We aim to translate this knowledge to clinical practice by using a prospective database of precursor cystic lesions in pancreas cancer, assessing the use of over-expressed genes in pancreatic juice as a surrogate marker of these pancreas cancer and finally, downstream of...

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

    International Nuclear Information System (INIS)

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

  9. GREVE: Genomic Recurrent Event ViEwer to assist the identification of patterns across individual cancer samples

    OpenAIRE

    Cazier, Jean-Baptiste; Holmes, Chris C.; Broxholme, John

    2012-01-01

    Summary: GREVE has been developed to assist with the identification of recurrent genomic aberrations across cancer samples. The exact characterization of such aberrations remains a challenge despite the availability of increasing amount of data, from SNParray to next-generation sequencing. Furthermore, genomic aberrations in cancer are especially difficult to handle because they are, by nature, unique to the patients. However, their recurrence in specific regions of the genome has been shown ...

  10. 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.

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

    OpenAIRE

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

    2013-01-01

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

  12. Mutation of mitochondria genome: trigger of somatic cell transforming to cancer cell

    OpenAIRE

    Jianping Du

    2010-01-01

    Abstract Nearly 80 years ago, scientist Otto Warburg originated a hypothesis that the cause of cancer is primarily a defect in energy metabolism. Following studies showed that mitochondria impact carcinogenesis to remodel somatic cells to cancer cells through modifying the genome, through maintenance the tumorigenic phenotype, and through apoptosis. And the Endosymbiotic Theory explains the origin of mitochondria and eukaryotes, on the other hands, the mitochondria also can fall back. Compare...

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

    International Nuclear Information System (INIS)

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

  14. 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...... 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...

  15. Isolation and genomic analysis of circulating tumor cells from castration resistant metastatic prostate cancer

    International Nuclear Information System (INIS)

    The number of circulating tumor cells (CTCs) in metastatic prostate cancer patients provides prognostic and predictive information. However, it is the molecular characterization of CTCs that offers insight into the biology of these tumor cells in the context of personalized treatment. We developed a novel approach to isolate CTCs away from hematopoietic cells with high purity, enabling genomic analysis of these cells. The isolation protocol involves immunomagnetic enrichment followed by fluorescence activated cell sorting (IE/FACS). To evaluate the feasibility of isolation of CTCs by IE/FACS and downstream genomic profiling, we conducted a pilot study in patients with metastatic castration resistant prostate cancer (CRPC). Twenty (20) sequential CRPC patients were assayed using CellSearch™. Twelve (12) patients positive for CTCs were subjected to immunomagnetic enrichment and fluorescence activated cell sorting (IE/FACS) to isolate CTCs. Genomic DNA of CTCs was subjected to whole genome amplification (WGA) followed by gene copy number analysis via array comparative genomic hybridization (aCGH). CTCs from nine (9) patients successfully profiled were observed to have multiple copy number aberrations including those previously reported in primary prostate tumors such as gains in 8q and losses in 8p. High-level copy number gains at the androgen receptor (AR) locus were observed in 7 (78%) cases. Comparison of genomic profiles between CTCs and archival primary tumors from the same patients revealed common lineage. However, high-level copy number gains in the AR locus were observed in CTCs, but not in the matched archival primary tumors. We developed a new approach to isolate prostate CTCs without significant leukocyte admixture, and to subject them to genome-wide copy number analysis. Our assay may be utilized to explore genomic events involved in cancer progression, e.g. development of castration resistance and to monitor therapeutic efficacy of targeted therapies in

  16. 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...

  17. 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...

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

    Science.gov (United States)

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

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

    Directory of Open Access Journals (Sweden)

    Oikawa Masahiro

    2011-12-01

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

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

    International Nuclear Information System (INIS)

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

  1. Specialized Hidden Markov Model Databases for Microbial Genomics

    OpenAIRE

    Martin Gollery

    2003-01-01

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

  2. 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.

  3. Genomic heterogeneity and instability in colorectal cancer: spectral karyotyping, glutathione transferase-Ml and ras.

    Science.gov (United States)

    Bartos, Jeremy D; Stoler, Daniel L; Matsui, Sei-ichi; Swede, Helen; Willmott, Lyndsay J; Sait, Sheila N; Petrelli, Nicholas J; Anderson, Garth R

    2004-12-21

    Genomic instability in cancer is frequently described as being either chromosomal instability or microsatellite instability, although when events within chromosomes are monitored, extensive intrachromosomal instability is also found. Spectral karyotyping was used to visualize how extensively genomic instability gives rise to intratumor genomic heterogeneity in sporadic colorectal carcinomas. Two factors were then examined which might relate to intrachromosomal instability in colorectal cancers: the presence of the glutathione transferase-Ml gene to detoxify potential carcinogens, and the presence of activated ras which has been associated with chromosomal instability when first expressed. Intrachromosomal genomic instability was previously determined by inter-(simple sequence repeat) PCR (inter-SSR PCR) and by fractional allelic loss rate for 348 markers. GSTM1 status was determined for each of 49 tumors through use of specific PCR, and 28 of the tumors showed the GSTM1 null genotype. A significant association was found between GSTMl-null status and elevated inter-(simple sequence repeat) PCR instability. In contrast, no association was found with fractional allelic loss rate. The first exons of the K-ras and H-ras oncogenes were sequenced in 72 colorectal cancers; 19 of the tumors had a mutation in codon 12 of the K-ras gene (24.5%), but no H-ras mutations were found. A weak correlation (p=0.10) was observed between mutant K-ras and inter-(simple sequence repeat) PCR genomic instability, and no association existed with fractional allelic loss rate. PMID:15542115

  4. A genome-wide association study of breast and prostate cancer in the NHLBI's Framingham Heart Study

    OpenAIRE

    Kreger Bernard E; Finger Daniel; Rosenberg Carol L; Murabito Joanne M; Levy Daniel; Splansky Greta; Antman Karen; Hwang Shih-Jen

    2007-01-01

    Abstract Background Breast and prostate cancer are two commonly diagnosed cancers in the United States. Prior work suggests that cancer causing genes and cancer susceptibility genes can be identified. Methods We conducted a genome-wide association study (Affymetrix 100K SNP GeneChip) of cancer in the community-based Framingham Heart Study. We report on 2 cancer traits – prostate cancer and breast cancer – in up to 1335 participants from 330 families (54% women, mean entry age 33 years). Multi...

  5. 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

  6. 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,...

  7. Optimizing mouse models for precision cancer prevention.

    Science.gov (United States)

    Le Magnen, Clémentine; Dutta, Aditya; Abate-Shen, Cory

    2016-03-01

    As cancer has become increasingly prevalent, cancer prevention research has evolved towards placing a greater emphasis on reducing cancer deaths and minimizing the adverse consequences of having cancer. 'Precision cancer prevention' takes into account the collaboration of intrinsic and extrinsic factors in influencing cancer incidence and aggressiveness in the context of the individual, as well as recognizing that such knowledge can improve early detection and enable more accurate discrimination of cancerous lesions. However, mouse models, and particularly genetically engineered mouse (GEM) models, have yet to be fully integrated into prevention research. In this Opinion article, we discuss opportunities and challenges for precision mouse modelling, including the essential criteria of mouse models for prevention research, representative success stories and opportunities for more refined analyses in future studies. PMID:26893066

  8. 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.

  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. 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.

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

    Science.gov (United States)

    VanRaden, P M

    2016-03-01

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

  12. Building a better model of cancer

    Directory of Open Access Journals (Sweden)

    DeGregori James

    2006-10-01

    Full Text Available Abstract The 2006 Cold Spring Harbor Laboratory meeting on the Mechanisms and Models of Cancer was held August 16–20. The meeting featured several hundred presentations of many short talks (mostly selected from the abstracts and posters, with the airing of a number of exciting new discoveries. We will focus this meeting review on models of cancer (primarily mouse models, highlighting recent advances in new mouse models that better recapitulate sporadic tumorigenesis, demonstrations of tumor addiction to tumor suppressor inactivation, new insight into senescence as a tumor barrier, improved understanding of the evolutionary paths of cancer development, and environmental/immunological influences on cancer.

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

    Directory of Open Access Journals (Sweden)

    Agren Rasmus

    2011-01-01

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

  14. 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

  15. An ecological model organism flies into the genomics era.

    Science.gov (United States)

    Santure, Anna W

    2016-03-01

    Despite the very rapid 'genomicization' of the field of Molecular Ecology in recent years, there have been relatively few annotated whole-genome assemblies of nonmodel organisms published. Instead, molecular ecologists have more frequently utilized next-generation sequencing technologies to develop genome-wide markers or to generate transcriptome data. Whole-genome assemblies are more expensive and require considerable computational resources and bioinformatic expertise. However, the availability of an annotated genome offers exciting opportunities to address fundamental questions in ecology and evolution that are difficult to address with moderate sets of markers or by transcriptome sequencing. Such questions include elucidating the roles of natural and sexual selection in shaping diversity, determining the roles of regulatory and protein-coding change in the evolution of traits, and determining the genomic architecture of sex-specific trait variation. Arguably, these questions are most tractable - and most interesting - in well-characterized species for which there is already some knowledge of natural and sexual selection, and of the traits that are most likely to link to fitness. In this issue, Mueller et al. () present the assembly and annotation of the genome of the blue tit (Cyanistes caeruleus), a model ecological species. In addition, by sequencing the transcriptome of male and female blue tits, the authors identify and annotate sex-biased gene expression and conclude that noncoding RNA genes are likely to play a significant role in sex-biased expression. By making their assembly and annotation publically available and accessible via a genome browser, Mueller et al. () offer exciting possibilities for further research into the genomic basis of adaptation, and investigation of the roles of natural and sexual selection, in this well-studied ecological model species. PMID:26813493

  16. Optimization of novel vector systems for functional genomics in cancer research

    DEFF Research Database (Denmark)

    Schmidt, Steffen

    Optimization of novel vector systems for functional genomics in cancer research Steffen Schmidt1*, Stephanie Blaich2, Rainer Wittig3, Stefan Lyer4, Caroline End2, Melanie Hudler2, Lukasz Kacprzyk2, Angela Riedel1,2, Helle Christiansen1, Jan Mollenhauer1,2 1 Molekylær Onkologi, Medicinsk...... for Lokal Tumor Terapi, Universitet Hospital, Waldstraße1, 91054 Erlangen, Tyskland * Præsenterende forfatter Large datasets about differentially expressed genes in cancer tissue have been recovered by expression profiling using microarray technologies. To study the effects of these genes in cancer...... cells will lead to an improved understanding of the molecular mechanisms underlying cancer and may result in the identification of novel druggable targets for cancer treatment. We established a novel rapid technique to generate stable cell lines with inducible overexpression of genes. This enables for...

  17. 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

  18. 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

  19. 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

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

    Science.gov (United States)

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

    2016-05-01

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

  1. 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

  2. Understanding Cancer Prognosis

    Medline Plus

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

  3. The genomics of oral cancer and wound healing

    Directory of Open Access Journals (Sweden)

    Aswini Y

    2009-03-01

    Full Text Available Oral cancer is the most common malignancy in India, where it is epidemiologically linked to the chewing of betel quid and other carcinogens. But various point mutations were detectable in the p53 and p15 genes. Hence, this review was conducted with the aim to find out genetic risks as well as markers for oral cancers and wound healing. Tobacco-related cancers are associated with polymorphisms of the CYP1A1 and GSTM1 genes in terms of genotype frequencies and cigarette smoking dose. Expression of E6/E7 were also found in tumors, most of which were derived from the oropharynx. Presence of homozygous arginine at codon 72 renders p53 about seven times more susceptible to E6-mediated proteolytic degradation. Erythropoietin, vascular permeability factor (VPF, also known as vascular endothelial growth factor or VEGF, and PDGF has been implicated as one of the principal mitogens involved in cutaneous wound healing. Activation of NF-kB is associated with enhanced cell survival. Human papilloma virus status is a significantly favorable prognostic factor in tonsilar cancer and may be used as a marker in order to optimize the treatment of patients with this type of cancer.

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

    International Nuclear Information System (INIS)

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

  5. Gamma-retrovirus integration marks cell type-specific cancer genes: a novel profiling tool in cancer genomics

    OpenAIRE

    Gilroy, Kathryn L.; Terry, Anne; Naseer, Asif; De Ridder, Jeroen; Allahyar, Amin; Wang, Weiwei; Carpenter, Eric; Mason, Andrew; Wong, Gane K-S; Cameron, Ewan R; Kilbey, Anna; Neil, James C.

    2016-01-01

    Retroviruses have been foundational in cancer research since early studies identified proto-oncogenes as targets for insertional mutagenesis. Integration of murine gamma-retroviruses into the host genome favours promoters and enhancers and entails interaction of viral integrase with host BET/bromodomain factors. We report that this integration pattern is conserved in feline leukaemia virus (FeLV), a gamma-retrovirus that infects many human cell types. Analysis of FeLV insertion sites in the M...

  6. An Inherited Efficiencies Model of Non-Genomic Evolution

    Science.gov (United States)

    New, Michael H.; Pohorille, Andrew

    1999-01-01

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

  7. 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.

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

    Science.gov (United States)

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

    2015-12-01

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

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

    Science.gov (United States)

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

    2016-04-26

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

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

    Science.gov (United States)

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

    2016-01-01

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

  11. 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.

  12. Genomic aberrations relate early and advanced stage ovarian cancer

    NARCIS (Netherlands)

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

    2012-01-01

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

  13. 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...

  14. Synthetic Genetic Targeting of Genome Instability in Cancer

    International Nuclear Information System (INIS)

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

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

    Science.gov (United States)

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

    2016-06-01

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

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

    Science.gov (United States)

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

    2016-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Donghoon Lee

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

  18. Animal models of ovarian cancer

    OpenAIRE

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

    2003-01-01

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

  19. Genome and transcriptome sequencing in prospective metastatic triple-negative breast cancer uncovers therapeutic vulnerabilities.

    Science.gov (United States)

    Craig, David W; O'Shaughnessy, Joyce A; Kiefer, Jeffrey A; Aldrich, Jessica; Sinari, Shripad; Moses, Tracy M; Wong, Shukmei; Dinh, Jennifer; Christoforides, Alexis; Blum, Joanne L; Aitelli, Cristi L; Osborne, Cynthia R; Izatt, Tyler; Kurdoglu, Ahmet; Baker, Angela; Koeman, Julie; Barbacioru, Catalin; Sakarya, Onur; De La Vega, Francisco M; Siddiqui, Asim; Hoang, Linh; Billings, Paul R; Salhia, Bodour; Tolcher, Anthony W; Trent, Jeffrey M; Mousses, Spyro; Von Hoff, Daniel; Carpten, John D

    2013-01-01

    Triple-negative breast cancer (TNBC) is characterized by the absence of expression of estrogen receptor, progesterone receptor, and HER-2. Thirty percent of patients recur after first-line treatment, and metastatic TNBC (mTNBC) has a poor prognosis with median survival of one year. Here, we present initial analyses of whole genome and transcriptome sequencing data from 14 prospective mTNBC. We have cataloged the collection of somatic genomic alterations in these advanced tumors, particularly those that may inform targeted therapies. Genes mutated in multiple tumors included TP53, LRP1B, HERC1, CDH5, RB1, and NF1. Notable genes involved in focal structural events were CTNNA1, PTEN, FBXW7, BRCA2, WT1, FGFR1, KRAS, HRAS, ARAF, BRAF, and PGCP. Homozygous deletion of CTNNA1 was detected in 2 of 6 African Americans. RNA sequencing revealed consistent overexpression of the FOXM1 gene when tumor gene expression was compared with nonmalignant breast samples. Using an outlier analysis of gene expression comparing one cancer with all the others, we detected expression patterns unique to each patient's tumor. Integrative DNA/RNA analysis provided evidence for deregulation of mutated genes, including the monoallelic expression of TP53 mutations. Finally, molecular alterations in several cancers supported targeted therapeutic intervention on clinical trials with known inhibitors, particularly for alterations in the RAS/RAF/MEK/ERK and PI3K/AKT/mTOR pathways. In conclusion, whole genome and transcriptome profiling of mTNBC have provided insights into somatic events occurring in this difficult to treat cancer. These genomic data have guided patients to investigational treatment trials and provide hypotheses for future trials in this irremediable cancer. PMID:23171949

  20. Stemming Cancer: Functional Genomics of Cancer Stem Cells in Solid Tumors

    OpenAIRE

    Regenbrecht, C. R. A.; Lehrach, H; Adjaye, J.

    2008-01-01

    Cancer stem cells (CSCs) were discovered about 15 years ago in hematopoietic cancers. Subsequently, cancer stem cells were discovered in various solid tumors. Based on parallels with normal stem cells, a developmental process of cancer stem cells follows paths of organized, hierarchical structure of cells with different degrees of maturity. While some investigators have reported particular markers as identification of cancer stem cells, these markers require further research. In this review, ...

  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. 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. PMID:26002561

  3. 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.

  4. Whole-Genome Sequencing Reveals Diverse Models of Structural Variations in Esophageal Squamous Cell Carcinoma.

    Science.gov (United States)

    Cheng, Caixia; Zhou, Yong; Li, Hongyi; Xiong, Teng; Li, Shuaicheng; Bi, Yanghui; Kong, Pengzhou; Wang, Fang; Cui, Heyang; Li, Yaoping; Fang, Xiaodong; Yan, Ting; Li, Yike; Wang, Juan; Yang, Bin; Zhang, Ling; Jia, Zhiwu; Song, Bin; Hu, Xiaoling; Yang, Jie; Qiu, Haile; Zhang, Gehong; Liu, Jing; Xu, Enwei; Shi, Ruyi; Zhang, Yanyan; Liu, Haiyan; He, Chanting; Zhao, Zhenxiang; Qian, Yu; Rong, Ruizhou; Han, Zhiwei; Zhang, Yanlin; Luo, Wen; Wang, Jiaqian; Peng, Shaoliang; Yang, Xukui; Li, Xiangchun; Li, Lin; Fang, Hu; Liu, Xingmin; Ma, Li; Chen, Yunqing; Guo, Shiping; Chen, Xing; Xi, Yanfeng; Li, Guodong; Liang, Jianfang; Yang, Xiaofeng; Guo, Jiansheng; Jia, JunMei; Li, Qingshan; Cheng, Xiaolong; Zhan, Qimin; Cui, Yongping

    2016-02-01

    Comprehensive identification of somatic structural variations (SVs) and understanding their mutational mechanisms in cancer might contribute to understanding biological differences and help to identify new therapeutic targets. Unfortunately, characterization of complex SVs across the whole genome and the mutational mechanisms underlying esophageal squamous cell carcinoma (ESCC) is largely unclear. To define a comprehensive catalog of somatic SVs, affected target genes, and their underlying mechanisms in ESCC, we re-analyzed whole-genome sequencing (WGS) data from 31 ESCCs using Meerkat algorithm to predict somatic SVs and Patchwork to determine copy-number changes. We found deletions and translocations with NHEJ and alt-EJ signature as the dominant SV types, and 16% of deletions were complex deletions. SVs frequently led to disruption of cancer-associated genes (e.g., CDKN2A and NOTCH1) with different mutational mechanisms. Moreover, chromothripsis, kataegis, and breakage-fusion-bridge (BFB) were identified as contributing to locally mis-arranged chromosomes that occurred in 55% of ESCCs. These genomic catastrophes led to amplification of oncogene through chromothripsis-derived double-minute chromosome formation (e.g., FGFR1 and LETM2) or BFB-affected chromosomes (e.g., CCND1, EGFR, ERBB2, MMPs, and MYC), with approximately 30% of ESCCs harboring BFB-derived CCND1 amplification. Furthermore, analyses of copy-number alterations reveal high frequency of whole-genome duplication (WGD) and recurrent focal amplification of CDCA7 that might act as a potential oncogene in ESCC. Our findings reveal molecular defects such as chromothripsis and BFB in malignant transformation of ESCCs and demonstrate diverse models of SVs-derived target genes in ESCCs. These genome-wide SV profiles and their underlying mechanisms provide preventive, diagnostic, and therapeutic implications for ESCCs. PMID:26833333

  5. MuSiC: Identifying mutational significance in cancer genomes

    OpenAIRE

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

    2012-01-01

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

  6. 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

    . Here we describe the essence of a long-term initiative undertaken by The Danish Centre for Translational Breast Cancer Research and currently underway for cancer biomarker discovery using fresh tissue biopsies and bio-fluids. The Centre is a virtual hub that brings together scientists working......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 bedside...... in various areas of basic cancer research such as cell cycle control, invasion and micro-environmental alterations, apoptosis, cell signaling, and immunology, with clinicians (oncologists, surgeons), pathologists, and epidemiologists, with the aim of understanding the molecular mechanisms underlying breast...

  7. Liver cancer mortality rate model in Thailand

    Science.gov (United States)

    Sriwattanapongse, Wattanavadee; Prasitwattanaseree, Sukon

    2013-09-01

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

  8. 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...

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

    Science.gov (United States)

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

    2015-10-01

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

  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. 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.

  12. High-Resolution Genomic and Expression Profiling Reveals 105 Putative Amplification Target Genes in Pancreatic Cancer

    Directory of Open Access Journals (Sweden)

    Eija H. Mahlamaki

    2004-09-01

    Full Text Available Comparative genomic hybridization (CGH studies have provided a wealth of information on common copy number aberrations in pancreatic cancer, but the genes affected by these aberrations are largely unknown. To identify putative amplification target genes in pancreatic cancer, we performed a parallel copy number and expression survey in 13 pancreatic cancer cell lines using a 12,232-clone cDNA microarray, providing an average resolution of 300 kb throughout the human genome. CGH on cDNA microarray allowed highly accurate mapping of copy number increases and resulted in identification of 24 independent amplicons, ranging in size from 130 kb to 11 Mb. Statistical evaluation of gene copy number and expression data across all 13 cell lines revealed a set of 105 genes whose elevated expression levels were directly attributable to increased copy number. These included genes previously reported to be amplified in cancer as well as several novel targets for copy number alterations, such as p21-activated kinase 4 (PAK4, which was previously shown to be involved in cell migration, cell adhesion, and anchorage-independent growth. In conclusion, our results implicate a set of 105 genes that is likely to be actively involved in the development and progression of pancreatic cancer.

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

    Directory of Open Access Journals (Sweden)

    Meredith C Henderson

    2012-04-01

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

  14. The search for cis-regulatory driver mutations in cancer genomes.

    Science.gov (United States)

    Poulos, Rebecca C; Sloane, Mathew A; Hesson, Luke B; Wong, Jason W H

    2015-10-20

    With the advent of high-throughput and relatively inexpensive whole-genome sequencing technology, the focus of cancer research has begun to shift toward analyses of somatic mutations in non-coding cis-regulatory elements of the cancer genome. Cis-regulatory elements play an important role in gene regulation, with mutations in these elements potentially resulting in changes to the expression of linked genes. The recent discoveries of recurrent TERT promoter mutations in melanoma, and recurrent mutations that create a super-enhancer regulating TAL1 expression in T-cell acute lymphoblastic leukaemia (T-ALL), have sparked significant interest in the search for other somatic cis-regulatory mutations driving cancer development. In this review, we look more closely at the TERT promoter and TAL1 enhancer alterations and use these examples to ask whether other cis-regulatory mutations may play a role in cancer susceptibility. In doing so, we make observations from the data emerging from recent research in this field, and describe the experimental and analytical approaches which could be adopted in the hope of better uncovering the true functional significance of somatic cis-regulatory mutations in cancer. PMID:26356674

  15. Genomic alterations in breast cancer patients in betel quid and non betel quid chewers.

    Science.gov (United States)

    Kaushal, Mishi; Mishra, Ashwani K; Sharma, Jagannath; Zomawia, Eric; Kataki, Amal; Kapur, Sujala; Saxena, Sunita

    2012-01-01

    Betel Quid (BQ) chewing independently contributes to oral, hepatic and esophageal carcinomas. Strong association of breast cancer risk with BQ chewing in Northeast Indian population has been reported where this habit is prodigal. We investigated genomic alterations in breast cancer patients with and without BQ chewing exposure. Twenty six BQ chewers (BQC) and 17 non BQ chewer (NBQC) breast cancer patients from Northeast India were analyzed for genomic alterations and pathway networks using SNP array and IPA. BQC tumors showed significantly (PETS2 etc in BQC and two networks "Molecular Transport, Nucleic Acid Metabolism, Small Molecule Biochemistry" and "Cellular Development, Embryonic Development, Organismal Development" including genes RPN2, EMR3, VAV1, NNAT and MUC16 etc were seen in NBQC. Common alterations (>30%) were seen in 27 regions. Three networks were significant in common regions with key roles of PTK2, RPN2, EMR3, VAV1, NNAT, MUC16, MYC and YWHAZ genes. These data show that breast cancer arising by environmental carcinogens exemplifies genetic alterations differing from those observed in the non exposed ones. A number of genetic changes are shared in both tumor groups considered as crucial in breast cancer progression. PMID:22937096

  16. 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.

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

    OpenAIRE

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

    2012-01-01

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

  18. The Path(way) Less Traveled: A Pathway-Oriented Approach to Providing Information about Precision Cancer Medicine on My Cancer Genome12

    Science.gov (United States)

    Taylor, Alexandria D.; Micheel, Christine M.; Anderson, Ingrid A.; Levy, Mia A.; Lovly, Christine M.

    2016-01-01

    This perspective describes the motivation, development, and implementation of pathway-based content for My Cancer Genome, an online precision medicine knowledge resource describing clinical implications of genetic alterations in cancer. As researchers uncover more about cancer pathogenesis, we are learning more not only about the specific genes and proteins involved but also about how those genes and proteins interact with others along cell signaling pathways. This knowledge has led researchers and clinicians to begin to think about cancer therapy using a pathway-based approach. To facilitate this approach, My Cancer Genome used a list of more than 800 cancer-related genes to identify 20 cancer-relevant pathways and then created content focused on demonstrating the therapeutic relevance of these pathways. PMID:27084433

  19. The Path(way Less Traveled: A Pathway-Oriented Approach to Providing Information about Precision Cancer Medicine on My Cancer Genome

    Directory of Open Access Journals (Sweden)

    Alexandria D. Taylor

    2016-04-01

    Full Text Available This perspective describes the motivation, development, and implementation of pathway-based content for My Cancer Genome, an online precision medicine knowledge resource describing clinical implications of genetic alterations in cancer. As researchers uncover more about cancer pathogenesis, we are learning more not only about the specific genes and proteins involved but also about how those genes and proteins interact with others along cell signaling pathways. This knowledge has led researchers and clinicians to begin to think about cancer therapy using a pathway-based approach. To facilitate this approach, My Cancer Genome used a list of more than 800 cancer-related genes to identify 20 cancer-relevant pathways and then created content focused on demonstrating the therapeutic relevance of these pathways.

  20. Spatial and temporal diversity in genomic instability processes defines lung cancer evolution.

    Science.gov (United States)

    de Bruin, Elza C; McGranahan, Nicholas; Mitter, Richard; Salm, Max; Wedge, David C; Yates, Lucy; Jamal-Hanjani, Mariam; Shafi, Seema; Murugaesu, Nirupa; Rowan, Andrew J; Grönroos, Eva; Muhammad, Madiha A; Horswell, Stuart; Gerlinger, Marco; Varela, Ignacio; Jones, David; Marshall, John; Voet, Thierry; Van Loo, Peter; Rassl, Doris M; Rintoul, Robert C; Janes, Sam M; Lee, Siow-Ming; Forster, Martin; Ahmad, Tanya; Lawrence, David; Falzon, Mary; Capitanio, Arrigo; Harkins, Timothy T; Lee, Clarence C; Tom, Warren; Teefe, Enock; Chen, Shann-Ching; Begum, Sharmin; Rabinowitz, Adam; Phillimore, Benjamin; Spencer-Dene, Bradley; Stamp, Gordon; Szallasi, Zoltan; Matthews, Nik; Stewart, Aengus; Campbell, Peter; Swanton, Charles

    2014-10-10

    Spatial and temporal dissection of the genomic changes occurring during the evolution of human non-small cell lung cancer (NSCLC) may help elucidate the basis for its dismal prognosis. We sequenced 25 spatially distinct regions from seven operable NSCLCs and found evidence of branched evolution, with driver mutations arising before and after subclonal diversification. There was pronounced intratumor heterogeneity in copy number alterations, translocations, and mutations associated with APOBEC cytidine deaminase activity. Despite maintained carcinogen exposure, tumors from smokers showed a relative decrease in smoking-related mutations over time, accompanied by an increase in APOBEC-associated mutations. In tumors from former smokers, genome-doubling occurred within a smoking-signature context before subclonal diversification, which suggested that a long period of tumor latency had preceded clinical detection. The regionally separated driver mutations, coupled with the relentless and heterogeneous nature of the genome instability processes, are likely to confound treatment success in NSCLC. PMID:25301630

  1. 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.

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

    Directory of Open Access Journals (Sweden)

    Steve Lu

    2015-03-01

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

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

    OpenAIRE

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

    2014-01-01

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

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

    OpenAIRE

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

    2008-01-01

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

  5. 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

    2011-01-01

    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. PMID:21467267

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

    DEFF Research Database (Denmark)

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

    2009-01-01

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

  7. Spatial and temporal diversity in genomic instability processes defines lung cancer evolution

    OpenAIRE

    de Bruin, Elza C.; McGranahan, Nicholas; Mitter, Richard; Salm, Max; Wedge, David C; Yates, Lucy; Jamal-Hanjani, Mariam; Shafi, Seema; Murugaesu, Nirupa; Rowan, Andrew J.; Grönroos, Eva; Muhammad, Madiha A.; Horswell, Stuart; Gerlinger, Marco; Varela, Ignacio

    2014-01-01

    Spatial and temporal dissection of the genomic changes occurring during the evolution of human non–small cell lung cancer (NSCLC) may help elucidate the basis for its dismal prognosis. We sequenced 25 spatially distinct regions from seven operable NSCLCs and found evidence of branched evolution, with driver mutations arising before and after subclonal diversification. There was pronounced intratumor heterogeneity in copy number alterations, translocations, and mutations associated with APOBEC...

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

    OpenAIRE

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

    2007-01-01

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

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

    OpenAIRE

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

    2015-01-01

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

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

    OpenAIRE

    Miller, Lance D; Liu, Edison T

    2007-01-01

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

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

    DEFF Research Database (Denmark)

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

    2008-01-01

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

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

    Science.gov (United States)

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

    2016-01-01

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

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

    OpenAIRE

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

    2012-01-01

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

  14. Animal Models of Cancer Pain

    OpenAIRE

    Pacharinsak, Cholawat; Beitz, Alvin

    2008-01-01

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

  15. 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.

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

    Directory of Open Access Journals (Sweden)

    Chi Song

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

  17. 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.

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

    OpenAIRE

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

    2013-01-01

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

  19. 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.

    2014-01-01

    Genome sequencing studies have shown that human malignancies often bear mutations in four or more driver genes1, 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 editing2–4 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 the human disease. 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. PMID:24952903

  20. ANIMAL MODELS OF CANCER: A REVIEW

    Directory of Open Access Journals (Sweden)

    Archana M. Navale

    2013-01-01

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

  1. Meta-analysis of genome-wide association from genomic prediction models.

    Science.gov (United States)

    Bernal Rubio, Y L; Gualdrón Duarte, J L; Bates, R O; Ernst, C W; Nonneman, D; Rohrer, G A; King, A; Shackelford, S D; Wheeler, T L; Cantet, R J C; Steibel, J P

    2016-02-01

    Genome-wide association (GWA) studies based on GBLUP models are a common practice in animal breeding. However, effect sizes of GWA tests are small, requiring larger sample sizes to enhance power of detection of rare variants. Because of difficulties in increasing sample size in animal populations, one alternative is to implement a meta-analysis (MA), combining information and results from independent GWA studies. Although this methodology has been used widely in human genetics, implementation in animal breeding has been limited. Thus, we present methods to implement a MA of GWA, describing the proper approach to compute weights derived from multiple genomic evaluations based on animal-centric GBLUP models. Application to real datasets shows that MA increases power of detection of associations in comparison with population-level GWA, allowing for population structure and heterogeneity of variance components across populations to be accounted for. Another advantage of MA is that it does not require access to genotype data that is required for a joint analysis. Scripts related to the implementation of this approach, which consider the strength of association as well as the sign, are distributed and thus account for heterogeneity in association phase between QTL and SNPs. Thus, MA of GWA is an attractive alternative to summarizing results from multiple genomic studies, avoiding restrictions with genotype data sharing, definition of fixed effects and different scales of measurement of evaluated traits. PMID:26607299

  2. Advances in Swine Biomedical Model Genomics

    Science.gov (United States)

    The swine has been a major biomedical model species, for transplantation, heart disease, allergies and asthma, as well as normal neonatal development and reproductive physiology. Swine have been used extensively for studies of infectious disease processes and analyses of preventative strategies, inc...

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

    Science.gov (United States)

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

    2015-01-01

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

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

    Science.gov (United States)

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

    2016-07-01

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

  5. An algorithm for classifying tumors based on genomic aberrations and selecting representative tumor models

    Directory of Open Access Journals (Sweden)

    Coon John

    2010-06-01

    Full Text Available Abstract Background Cancer is a heterogeneous disease caused by genomic aberrations and characterized by significant variability in clinical outcomes and response to therapies. Several subtypes of common cancers have been identified based on alterations of individual cancer genes, such as HER2, EGFR, and others. However, cancer is a complex disease driven by the interaction of multiple genes, so the copy number status of individual genes is not sufficient to define cancer subtypes and predict responses to treatments. A classification based on genome-wide copy number patterns would be better suited for this purpose. Method To develop a more comprehensive cancer taxonomy based on genome-wide patterns of copy number abnormalities, we designed an unsupervised classification algorithm that identifies genomic subgroups of tumors. This algorithm is based on a modified genomic Non-negative Matrix Factorization (gNMF algorithm and includes several additional components, namely a pilot hierarchical clustering procedure to determine the number of clusters, a multiple random initiation scheme, a new stop criterion for the core gNMF, as well as a 10-fold cross-validation stability test for quality assessment. Result We applied our algorithm to identify genomic subgroups of three major cancer types: non-small cell lung carcinoma (NSCLC, colorectal cancer (CRC, and malignant melanoma. High-density SNP array datasets for patient tumors and established cell lines were used to define genomic subclasses of the diseases and identify cell lines representative of each genomic subtype. The algorithm was compared with several traditional clustering methods and showed improved performance. To validate our genomic taxonomy of NSCLC, we correlated the genomic classification with disease outcomes. Overall survival time and time to recurrence were shown to differ significantly between the genomic subtypes. Conclusions We developed an algorithm for cancer classification

  6. A Model for Counselling Cancer Patients.

    Science.gov (United States)

    Jevne, Ronna F.; Nekolaichuk, Cheryl L.; Williamson, F. Helen A.

    1998-01-01

    Describes a model for counseling cancer patients that integrates the unique features of the cancer experience within a basic counseling framework. It combines a nine-step problem-solving approach with a biopsychosocial perspective, placing greater emphasis on the person than the problem. Utilizes innovative questioning techniques and strategies.…

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

    Science.gov (United States)

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

    2014-06-01

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

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

    Science.gov (United States)

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

    2016-06-01

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

  9. 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.

  10. 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.

  11. 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.

  12. Development of a Mouse Model of Menopausal Ovarian Cancer

    OpenAIRE

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

    2014-01-01

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

  13. 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.

  14. Genome-wide DNA methylation profiling in triple-negative breast cancer reveals epigenetic signatures with important clinical value

    Science.gov (United States)

    Stirzaker, Clare; Zotenko, Elena; Clark, Susan J

    2016-01-01

    abstract Analysis of cancer methylomes has dramatically changed our concept of the potential of diagnostic and prognostic methylation biomarkers in disease stratification. Through whole-genome methylation capture sequencing of triple-negative breast cancers (TNBCs) we recently identified differentially methylated regions with diagnostic and prognostic value that promise to stratify TNBCs for more personalized management. PMID:27308556

  15. Genome-wide association study identifies a common variant in RAD51B associated with male breast cancer risk

    DEFF Research Database (Denmark)

    Orr, Nick; Lemnrau, Alina; Cooke, Rosie;

    2012-01-01

    We conducted a genome-wide association study of male breast cancer comprising 823 cases and 2,795 controls of European ancestry, with validation in independent sample sets totaling 438 cases and 474 controls. A SNP in RAD51B at 14q24.1 was significantly associated with male breast cancer risk (P ...

  16. 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

  17. Genomic Prostate Cancer Classifier Predicts Biochemical Failure and Metastases in Patients After Postoperative Radiation Therapy

    International Nuclear Information System (INIS)

    Purpose: To test the hypothesis that a genomic classifier (GC) would predict biochemical failure (BF) and distant metastasis (DM) in men receiving radiation therapy (RT) after radical prostatectomy (RP). Methods and Materials: Among patients who underwent post-RP RT, 139 were identified for pT3 or positive margin, who did not receive neoadjuvant hormones and had paraffin-embedded specimens. Ribonucleic acid was extracted from the highest Gleason grade focus and applied to a high-density-oligonucleotide microarray. Receiver operating characteristic, calibration, cumulative incidence, and Cox regression analyses were performed to assess GC performance for predicting BF and DM after post-RP RT in comparison with clinical nomograms. Results: The area under the receiver operating characteristic curve of the Stephenson model was 0.70 for both BF and DM, with addition of GC significantly improving area under the receiver operating characteristic curve to 0.78 and 0.80, respectively. Stratified by GC risk groups, 8-year cumulative incidence was 21%, 48%, and 81% for BF (P<.0001) and for DM was 0, 12%, and 17% (P=.032) for low, intermediate, and high GC, respectively. In multivariable analysis, patients with high GC had a hazard ratio of 8.1 and 14.3 for BF and DM. In patients with intermediate or high GC, those irradiated with undetectable prostate-specific antigen (PSA ≤0.2 ng/mL) had median BF survival of >8 years, compared with <4 years for patients with detectable PSA (>0.2 ng/mL) before initiation of RT. At 8 years, the DM cumulative incidence for patients with high GC and RT with undetectable PSA was 3%, compared with 23% with detectable PSA (P=.03). No outcome differences were observed for low GC between the treatment groups. Conclusion: The GC predicted BF and metastasis after post-RP irradiation. Patients with lower GC risk may benefit from delayed RT, as opposed to those with higher GC; however, this needs prospective validation. Genomic-based models

  18. 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

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

    Science.gov (United States)

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

    2010-01-01

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

  20. Increased Proportion of Variance Explained and Prediction Accuracy of Survival of Breast Cancer Patients with Use of Whole-Genome Multiomic Profiles.

    Science.gov (United States)

    Vazquez, Ana I; Veturi, Yogasudha; Behring, Michael; Shrestha, Sadeep; Kirst, Matias; Resende, Marcio F R; de Los Campos, Gustavo

    2016-07-01

    Whole-genome multiomic profiles hold valuable information for the analysis and prediction of disease risk and progression. However, integrating high-dimensional multilayer omic data into risk-assessment models is statistically and computationally challenging. We describe a statistical framework, the Bayesian generalized additive model ((BGAM), and present software for integrating multilayer high-dimensional inputs into risk-assessment models. We used BGAM and data from The Cancer Genome Atlas for the analysis and prediction of survival after diagnosis of breast cancer. We developed a sequence of studies to (1) compare predictions based on single omics with those based on clinical covariates commonly used for the assessment of breast cancer patients (COV), (2) evaluate the benefits of combining COV and omics, (3) compare models based on (a) COV and gene expression profiles from oncogenes with (b) COV and whole-genome gene expression (WGGE) profiles, and (4) evaluate the impacts of combining multiple omics and their interactions. We report that (1) WGGE profiles and whole-genome methylation (METH) profiles offer more predictive power than any of the COV commonly used in clinical practice (e.g., subtype and stage), (2) adding WGGE or METH profiles to COV increases prediction accuracy, (3) the predictive power of WGGE profiles is considerably higher than that based on expression from large-effect oncogenes, and (4) the gain in prediction accuracy when combining multiple omics is consistent. Our results show the feasibility of omic integration and highlight the importance of WGGE and METH profiles in breast cancer, achieving gains of up to 7 points area under the curve (AUC) over the COV in some cases. PMID:27129736

  1. Genome sequence analysis of Helicobacter pylori strains associated with gastric ulceration and gastric cancer

    Directory of Open Access Journals (Sweden)

    Peek Richard M

    2009-01-01

    Full Text Available Abstract Background Persistent colonization of the human stomach by Helicobacter pylori is associated with asymptomatic gastric inflammation (gastritis and an increased risk of duodenal ulceration, gastric ulceration, and non-cardia gastric cancer. In previous studies, the genome sequences of H. pylori strains from patients with gastritis or duodenal ulcer disease have been analyzed. In this study, we analyzed the genome sequences of an H. pylori strain (98-10 isolated from a patient with gastric cancer and an H. pylori strain (B128 isolated from a patient with gastric ulcer disease. Results Based on multilocus sequence typing, strain 98-10 was most closely related to H. pylori strains of East Asian origin and strain B128 was most closely related to strains of European origin. Strain 98-10 contained multiple features characteristic of East Asian strains, including a type s1c vacA allele and a cagA allele encoding an EPIYA-D tyrosine phosphorylation motif. A core genome of 1237 genes was present in all five strains for which genome sequences were available. Among the 1237 core genes, a subset of alleles was highly divergent in the East Asian strain 98-10, encoding proteins that exhibited H. pylori strains associated with gastric cancer or premalignant gastric lesions. Conclusion These data provide insight into the diversity that exists among H. pylori strains from diverse clinical and geographic origins. Highly divergent alleles and strain-specific genes identified in this study may represent useful biomarkers for analyzing geographic partitioning of H. pylori and for identifying strains capable of inducing malignant or premalignant gastric lesions.

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

    Science.gov (United States)

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

  3. 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.

  4. 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.

  5. An Integrative Approach for the Large-scale Identification of Human Genome Kinases Regulating Cancer Metastasis

    Science.gov (United States)

    Zhang, Hanshuo; Wu, Pu-Yen; Ma, Ming; Ye, Yanzheng; Hao, Yang; Yang, Junyu; Yin, Shenyi; Sun, Changhong; Phan, John H.; Wang, May D.; Xi, Jianzhong Jeff

    2016-01-01

    Kinases regulate the majority of biological processes and become one of important groups of drug targets. To identify more kinases being potential for cancer therapy, we developed an integrative approach for the large-scale screen of functional genes capable of regulating the main traits of cancer metastasis, including cell migration as well as invasion. We first employed self-assembled cell microarray (SAMcell) to screen functional genes that regulate cancer cell migration using a siRNA library targeting 710 human genome kinase genes. We identified 81 genes capable of significantly regulating cancer cell migration. Following with invasion assays and bio-informatics analysis, we discovered that 16 genes with differentially expression in cancer samples can regulate both cell migration and invasion, among which 10 genes have been well known to play critical roles in the cancer development. The remaining 6 genes were experimentally validated to have the capacities of regulating the metastasis-related traits, including cell proliferation, apoptosis and anoikis activities besides cell motility. Together, these findings provide a new insight into the therapeutic use of human kinases. PMID:23751374

  6. 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

  7. 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.

  8. Genome-wide linkage scan for colorectal cancer susceptibility genes supports linkage to chromosome 3q

    Directory of Open Access Journals (Sweden)

    Velculescu Victor E

    2008-04-01

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

  9. 151 Using genomics to search for new viral causes and treatments for human cancer

    OpenAIRE

    Moore, Patrick S.; Chang, Yuan

    2014-01-01

    Although animal polyomaviruses, such as SV40, have been critical models in cancer research for over one-half century, polyomaviruses have not—until recently—been linked to human cancer. Using digital transcriptome subtraction, Merkel cell polyomavirus (MCV) was discovered in 2008 to infect most Merkel cell carcinomas, the most severe form of skin cancer. Normally, MCV is an common and asymptomatic infection of the human skin. In Merkel cell tumors, however, the virus integrates and undergoes ...

  10. 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; Knoop, Ann S; Jensen, Jeanette D; Bak, Martin; Mollenhauer, Jan; Kruse, Torben A; Thomassen, Mads

    2015-01-01

    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......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...

  11. 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; Knoop, Ann; Jensen, Jeanette Dupont; Bak, Martin; Mollenhauer, Jan; Kruse, Torben A; Thomassen, Mads

    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......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...

  12. 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.

  13. Integrated clinical, whole-genome, and transcriptome analysis of multisampled lethal metastatic prostate cancer.

    Science.gov (United States)

    Bova, G Steven; Kallio, Heini M L; Annala, Matti; Kivinummi, Kati; Högnäs, Gunilla; Häyrynen, Sergei; Rantapero, Tommi; Kivinen, Virpi; Isaacs, William B; Tolonen, Teemu; Nykter, Matti; Visakorpi, Tapio

    2016-05-01

    We report the first combined analysis of whole-genome sequence, detailed clinical history, and transcriptome sequence of multiple prostate cancer metastases in a single patient (A21). Whole-genome and transcriptome sequence was obtained from nine anatomically separate metastases, and targeted DNA sequencing was performed in cancerous and noncancerous foci within the primary tumor specimen removed 5 yr before death. Transcriptome analysis revealed increased expression of androgen receptor (AR)-regulated genes in liver metastases that harbored an AR p.L702H mutation, suggesting a dominant effect by the mutation despite being present in only one of an estimated 16 copies per cell. The metastases harbored several alterations to the PI3K/AKT pathway, including a clonal truncal mutation in PIK3CG and present in all metastatic sites studied. The list of truncal genomic alterations shared by all metastases included homozygous deletion of TP53, hemizygous deletion of RB1 and CHD1, and amplification of FGFR1. If the patient were treated today, given this knowledge, the use of second-generation androgen-directed therapies, cessation of glucocorticoid administration, and therapeutic inhibition of the PI3K/AKT pathway or FGFR1 receptor could provide personalized benefit. Three previously unreported truncal clonal missense mutations (ABCC4 p.R891L, ALDH9A1 p.W89R, and ASNA1 p.P75R) were expressed at the RNA level and assessed as druggable. The truncal status of mutations may be critical for effective actionability and merit further study. Our findings suggest that a large set of deeply analyzed cases could serve as a powerful guide to more effective prostate cancer basic science and personalized cancer medicine clinical trials. PMID:27148588

  14. Integrated clinical, whole-genome, and transcriptome analysis of multisampled lethal metastatic prostate cancer

    Science.gov (United States)

    Bova, G. Steven; Kallio, Heini M.L.; Annala, Matti; Kivinummi, Kati; Högnäs, Gunilla; Häyrynen, Sergei; Rantapero, Tommi; Kivinen, Virpi; Isaacs, William B.; Tolonen, Teemu; Nykter, Matti; Visakorpi, Tapio

    2016-01-01

    We report the first combined analysis of whole-genome sequence, detailed clinical history, and transcriptome sequence of multiple prostate cancer metastases in a single patient (A21). Whole-genome and transcriptome sequence was obtained from nine anatomically separate metastases, and targeted DNA sequencing was performed in cancerous and noncancerous foci within the primary tumor specimen removed 5 yr before death. Transcriptome analysis revealed increased expression of androgen receptor (AR)-regulated genes in liver metastases that harbored an AR p.L702H mutation, suggesting a dominant effect by the mutation despite being present in only one of an estimated 16 copies per cell. The metastases harbored several alterations to the PI3K/AKT pathway, including a clonal truncal mutation in PIK3CG and present in all metastatic sites studied. The list of truncal genomic alterations shared by all metastases included homozygous deletion of TP53, hemizygous deletion of RB1 and CHD1, and amplification of FGFR1. If the patient were treated today, given this knowledge, the use of second-generation androgen-directed therapies, cessation of glucocorticoid administration, and therapeutic inhibition of the PI3K/AKT pathway or FGFR1 receptor could provide personalized benefit. Three previously unreported truncal clonal missense mutations (ABCC4 p.R891L, ALDH9A1 p.W89R, and ASNA1 p.P75R) were expressed at the RNA level and assessed as druggable. The truncal status of mutations may be critical for effective actionability and merit further study. Our findings suggest that a large set of deeply analyzed cases could serve as a powerful guide to more effective prostate cancer basic science and personalized cancer medicine clinical trials.

  15. Building predictive models for feature selection in genomic mining

    OpenAIRE

    Figini, Silvia; Giudici, Paolo

    2006-01-01

    Building predictive models for genomic mining requires feature selection, as an essential preliminary step to reduce the large number of variable available. Feature selection is a process to select a subset of features which is the most essential for the intended tasks such as classification, clustering or regression analysis. In gene expression microarray data, being able to select a few genes not only makes data analysis efficient but also helps their biological interpretation. Microarray d...

  16. A bayesian integrative model for genetical genomics with spatially informed variable selection.

    Science.gov (United States)

    Cassese, Alberto; Guindani, Michele; Vannucci, Marina

    2014-01-01

    We consider a Bayesian hierarchical model for the integration of gene expression levels with comparative genomic hybridization (CGH) array measurements collected on the same subjects. The approach defines a measurement error model that relates the gene expression levels to latent copy number states. In turn, the latent states are related to the observed surrogate CGH measurements via a hidden Markov model. The model further incorporates variable selection with a spatial prior based on a probit link that exploits dependencies across adjacent DNA segments. Posterior inference is carried out via Markov chain Monte Carlo stochastic search techniques. We study the performance of the model in simulations and show better results than those achieved with recently proposed alternative priors. We also show an application to data from a genomic study on lung squamous cell carcinoma, where we identify potential candidates of associations between copy number variants and the transcriptional activity of target genes. Gene ontology (GO) analyses of our findings reveal enrichments in genes that code for proteins involved in cancer. Our model also identifies a number of potential candidate biomarkers for further experimental validation. PMID:25288877

  17. Whole-genome sequencing of bladder cancers reveals somatic CDKN1A mutations and clinicopathological associations with mutation burden

    OpenAIRE

    Cazier, J.-B.; Rao, S. R.; Mclean, C. M.; A. L. Walker; Wright, B J; Jaeger, E. E. M.; Kartsonaki, C.; Marsden, L.; Yau, C; Camps, C.; Kaisaki, P.; ,; Allan, Christopher; Attar, Moustafa; Bell, John

    2014-01-01

    Bladder cancers are a leading cause of death from malignancy. Molecular markers might predict disease progression and behaviour more accurately than the available prognostic factors. Here we use whole-genome sequencing to identify somatic mutations and chromosomal changes in 14 bladder cancers of different grades and stages. As well as detecting the known bladder cancer driver mutations, we report the identification of recurrent protein-inactivating mutations in CDKN1A and FAT1. The former ar...

  18. Impact of a bronchial genomic classifier on clinical decision making in patients undergoing diagnostic evaluation for lung cancer

    OpenAIRE

    Ferguson, J. Scott; Van Wert, Ryan; Choi, Yoonha; Rosenbluth, Michael J.; Smith, Kate Porta; Huang, Jing; Spira, Avrum

    2016-01-01

    Background Bronchoscopy is frequently used for the evaluation of suspicious pulmonary lesions found on computed tomography, but its sensitivity for detecting lung cancer is limited. Recently, a bronchial genomic classifier was validated to improve the sensitivity of bronchoscopy for lung cancer detection, demonstrating a high sensitivity and negative predictive value among patients at intermediate risk (10–60 %) for lung cancer with an inconclusive bronchoscopy. Our objective for this study w...

  19. [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. PMID:26507715

  20. Combining Chromosomal Arm Status and Significantly Aberrant Genomic Locations Reveals New Cancer Subtypes

    Directory of Open Access Journals (Sweden)

    Tal Shay

    2009-01-01

    Full Text Available Many types of tumors exhibit characteristic chromosomal losses or gains, as well as local amplifications and deletions. Within any given tumor type, sample specific amplifications and deletions are also observed. Typically, a region that is aberrant in more tumors, or whose copy number change is stronger, would be considered as a more promising candidate to be biologically relevant to cancer. We sought for an intuitive method to define such aberrations and prioritize them. We define V, the “volume” associated with an aberration, as the product of three factors: (a fraction of patients with the aberration, (b the aberration’s length and (c its amplitude. Our algorithm compares the values of V derived from the real data to a null distribution obtained by permutations, and yields the statistical significance (p-value of the measured value of V. We detected genetic locations that were significantly aberrant, and combine them with chromosomal arm status (gain/loss to create a succinct fingerprint of the tumor genome. This genomic fingerprint is used to visualize the tumors, highlighting events that are co-occurring or mutually exclusive. We apply the method on three different public array CGH datasets of Medulloblastoma and Neuroblastoma, and demonstrate its ability to detect chromosomal regions that were known to be altered in the tested cancer types, as well as to suggest new genomic locations to be tested. We identified a potential new subtype of Medulloblastoma, which is analogous to Neuroblastoma type 1.

  1. Gamma-Retrovirus Integration Marks Cell Type-Specific Cancer Genes: A Novel Profiling Tool in Cancer Genomics

    Science.gov (United States)

    Gilroy, Kathryn L.; Terry, Anne; Naseer, Asif; de Ridder, Jeroen; Wang, Weiwei; Carpenter, Eric; Mason, Andrew; Wong, Gane K-S.; Kilbey, Anna; Neil, James C.

    2016-01-01

    Retroviruses have been foundational in cancer research since early studies identified proto-oncogenes as targets for insertional mutagenesis. Integration of murine gamma-retroviruses into the host genome favours promoters and enhancers and entails interaction of viral integrase with host BET/bromodomain factors. We report that this integration pattern is conserved in feline leukaemia virus (FeLV), a gamma-retrovirus that infects many human cell types. Analysis of FeLV insertion sites in the MCF-7 mammary carcinoma cell line revealed strong bias towards active chromatin marks with no evidence of significant post-integration growth selection. The most prominent FeLV integration targets had little overlap with the most abundantly expressed transcripts, but were strongly enriched for annotated cancer genes. A meta-analysis based on several gamma-retrovirus integration profiling (GRIP) studies in human cells (CD34+, K562, HepG2) revealed a similar cancer gene bias but also remarkable cell-type specificity, with prominent exceptions including a universal integration hotspot at the long non-coding RNA MALAT1. Comparison of GRIP targets with databases of super-enhancers from the same cell lines showed that these have only limited overlap and that GRIP provides unique insights into the upstream drivers of cell growth. These observations elucidate the oncogenic potency of the gamma-retroviruses and support the wider application of GRIP to identify the genes and growth regulatory circuits that drive distinct cancer types. PMID:27097319

  2. Gamma-Retrovirus Integration Marks Cell Type-Specific Cancer Genes: A Novel Profiling Tool in Cancer Genomics.

    Science.gov (United States)

    Gilroy, Kathryn L; Terry, Anne; Naseer, Asif; de Ridder, Jeroen; Allahyar, Amin; Wang, Weiwei; Carpenter, Eric; Mason, Andrew; Wong, Gane K-S; Cameron, Ewan R; Kilbey, Anna; Neil, James C

    2016-01-01

    Retroviruses have been foundational in cancer research since early studies identified proto-oncogenes as targets for insertional mutagenesis. Integration of murine gamma-retroviruses into the host genome favours promoters and enhancers and entails interaction of viral integrase with host BET/bromodomain factors. We report that this integration pattern is conserved in feline leukaemia virus (FeLV), a gamma-retrovirus that infects many human cell types. Analysis of FeLV insertion sites in the MCF-7 mammary carcinoma cell line revealed strong bias towards active chromatin marks with no evidence of significant post-integration growth selection. The most prominent FeLV integration targets had little overlap with the most abundantly expressed transcripts, but were strongly enriched for annotated cancer genes. A meta-analysis based on several gamma-retrovirus integration profiling (GRIP) studies in human cells (CD34+, K562, HepG2) revealed a similar cancer gene bias but also remarkable cell-type specificity, with prominent exceptions including a universal integration hotspot at the long non-coding RNA MALAT1. Comparison of GRIP targets with databases of super-enhancers from the same cell lines showed that these have only limited overlap and that GRIP provides unique insights into the upstream drivers of cell growth. These observations elucidate the oncogenic potency of the gamma-retroviruses and support the wider application of GRIP to identify the genes and growth regulatory circuits that drive distinct cancer types. PMID:27097319

  3. Cancer associated epigenetic transitions identified by genome-wide histone methylation binding profiles in human colorectal cancer samples and paired normal mucosa

    International Nuclear Information System (INIS)

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

  4. Understanding Cancer Prognosis

    Medline Plus

    Full Text Available ... Types Recurrent Cancer Common Cancer Types Bladder Cancer Breast Cancer Colorectal Cancer Kidney (Renal Cell) Cancer Leukemia Lung ... Biology Cancer Genomics Causes of Cancer Diagnosis Prevention Screening & Early Detection Treatment Cancer & Public Health Cancer Health ...

  5. Computer model challenges breast cancer treatment strategy.

    Science.gov (United States)

    Retsky, M W; Swartzendruber, D E; Bame, P D; Wardwell, R H

    1994-01-01

    The breast cancer treatment failure rate remains unacceptably high. The current breast cancer treatment paradigm, based primarily on Gompertzian kinetics and animal models, advocates short-course, intensive chemotherapy subsequent to tumor debulking, citing drug resistance and host toxicity as the primary reasons for treatment failure. To better understand treatment failure, we have studied breast cancer from the perspective of computer modeling. Our results demonstrate breast cancers grow in an irregular fashion; this differs from the Gompertzian mode of animal models and thus challenges the validity of the current paradigm. Clinical and laboratory data support the concept of irregular growth rather than the common claim that human tumors grow in a Gompertzian fashion. Treatment failure mechanisms for breast cancer appear to differ from those for animal models, and thus treatments optimize on animal models may not be optimal for breast cancer. A failure mechanism consistent with our results involves temporarily dormant tumor cells in anatomical or pharmacological sanctuary, which eventually result in aggressive metastatic disease. PMID:7994590

  6. 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

    2014-07-01

    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

  7. 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.

  8. Cancer-predisposition gene KLLN maintains pericentric H3K9 trimethylation protecting genomic stability.

    Science.gov (United States)

    Nizialek, Emily A; Sankunny, Madhav; Niazi, Farshad; Eng, Charis

    2016-05-01

    Maintenance of proper chromatin states and genomic stability is vital for normal development and health across a range of organisms. Here, we report on the role of KLLN in maintenance of pericentric H3K9 trimethylation (H3K9me3) and genomic stability. Germline hypermethylation of KLLN, a gene uncovered well after the human genome project, has been linked to Cowden cancer-predisposition syndrome (CS) in PTEN wild-type cases. KLLN first identified as a p53-dependent tumor suppressor gene, was believed to bind randomly to DNA and cause S-phase arrest. Using chromatin immunoprecipitation-based sequencing (ChIP-seq), we demonstrated that KLLN binds to DNA regions enriched with H3K9me3. KLLN overexpression correlated with increased H3K9 methyltransferase activity and increased global H3K9me3, while knockdown of KLLN had an opposite effect. We also found KLLN to localize to pericentric regions, with loss of KLLN resulting in dysregulation of pericentric heterochromatin, with consequent chromosomal instability manifested by increased micronuclei formation and numerical chromosomal aberrations. Interestingly, we show that KLLN interacts with DBC1, with consequent abrogation of DBC1 inhibition of SUV39H1, a H3K9 methyltransferase, suggesting the mode of KLLN regulating H3K9me3. These results suggest a critical role for KLLN as a potential regulator of pericentric heterochromatin formation, genomic stability and gene expression. PMID:26673699

  9. Cancer-predisposition gene KLLN maintains pericentric H3K9 trimethylation protecting genomic stability

    Science.gov (United States)

    Nizialek, Emily A.; Sankunny, Madhav; Niazi, Farshad; Eng, Charis

    2016-01-01

    Maintenance of proper chromatin states and genomic stability is vital for normal development and health across a range of organisms. Here, we report on the role of KLLN in maintenance of pericentric H3K9 trimethylation (H3K9me3) and genomic stability. Germline hypermethylation of KLLN, a gene uncovered well after the human genome project, has been linked to Cowden cancer-predisposition syndrome (CS) in PTEN wild-type cases. KLLN first identified as a p53-dependent tumor suppressor gene, was believed to bind randomly to DNA and cause S-phase arrest. Using chromatin immunoprecipitation-based sequencing (ChIP-seq), we demonstrated that KLLN binds to DNA regions enriched with H3K9me3. KLLN overexpression correlated with increased H3K9 methyltransferase activity and increased global H3K9me3, while knockdown of KLLN had an opposite effect. We also found KLLN to localize to pericentric regions, with loss of KLLN resulting in dysregulation of pericentric heterochromatin, with consequent chromosomal instability manifested by increased micronuclei formation and numerical chromosomal aberrations. Interestingly, we show that KLLN interacts with DBC1, with consequent abrogation of DBC1 inhibition of SUV39H1, a H3K9 methyltransferase, suggesting the mode of KLLN regulating H3K9me3. These results suggest a critical role for KLLN as a potential regulator of pericentric heterochromatin formation, genomic stability and gene expression. PMID:26673699

  10. 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. PMID:25270536

  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. Cancer Biomarkers from Genome-Scale DNA Methylation: Comparison of Evolutionary and Semantic Analysis Methods

    Directory of Open Access Journals (Sweden)

    Ioannis Valavanis

    2015-11-01

    Full Text Available DNA methylation profiling exploits microarray technologies, thus yielding a wealth of high-volume data. Here, an intelligent framework is applied, encompassing epidemiological genome-scale DNA methylation data produced from the Illumina’s Infinium Human Methylation 450K Bead Chip platform, in an effort to correlate interesting methylation patterns with cancer predisposition and, in particular, breast cancer and B-cell lymphoma. Feature selection and classification are employed in order to select, from an initial set of ~480,000 methylation measurements at CpG sites, predictive cancer epigenetic biomarkers and assess their classification power for discriminating healthy versus cancer related classes. Feature selection exploits evolutionary algorithms or a graph-theoretic methodology which makes use of the semantics information included in the Gene Ontology (GO tree. The selected features, corresponding to methylation of CpG sites, attained moderate-to-high classification accuracies when imported to a series of classifiers evaluated by resampling or blindfold validation. The semantics-driven selection revealed sets of CpG sites performing similarly with evolutionary selection in the classification tasks. However, gene enrichment and pathway analysis showed that it additionally provides more descriptive sets of GO terms and KEGG pathways regarding the cancer phenotypes studied here. Results support the expediency of this methodology regarding its application in epidemiological studies.

  13. 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.

  14. Management of multipartite genomes: the Vibrio cholerae model.

    Science.gov (United States)

    Val, Marie-Eve; Soler-Bistué, Alfonso; Bland, Michael J; Mazel, Didier

    2014-12-01

    A minority of bacterial species has been found to carry a genome divided among several chromosomes. Among these, all Vibrio species harbor a genome split into two chromosomes of uneven size, with distinctive replication origins whose replication firing involves common and specific factors. Most of our current knowledge on replication and segregation in multi-chromosome bacteria has come from the study of Vibrio cholerae, which is now the model organism for this field. It has been firmly established that replication of the two V. cholerae chromosomes is temporally regulated and coupled to the cell cycle, but the mediators of these processes are as yet mostly unknown. The two chromosomes are also organized along different patterns within the cell and occupy different subcellular domains. The selective advantages provided by this partitioning into two replicons are still unclear and are a key motivation for these studies. PMID:25460805

  15. Translocation and deletion breakpoints in cancer genomes are associated with potential non-B DNA-forming sequences

    Science.gov (United States)

    Bacolla, Albino; Tainer, John A.; Vasquez, Karen M.; Cooper, David N.

    2016-01-01

    Gross chromosomal rearrangements (including translocations, deletions, insertions and duplications) are a hallmark of cancer genomes and often create oncogenic fusion genes. An obligate step in the generation of such gross rearrangements is the formation of DNA double-strand breaks (DSBs). Since the genomic distribution of rearrangement breakpoints is non-random, intrinsic cellular factors may predispose certain genomic regions to breakage. Notably, certain DNA sequences with the potential to fold into secondary structures [potential non-B DNA structures (PONDS); e.g. triplexes, quadruplexes, hairpin/cruciforms, Z-DNA and single-stranded looped-out structures with implications in DNA replication and transcription] can stimulate the formation of DNA DSBs. Here, we tested the postulate that these DNA sequences might be found at, or in close proximity to, rearrangement breakpoints. By analyzing the distribution of PONDS-forming sequences within ±500 bases of 19 947 translocation and 46 365 sequence-characterized deletion breakpoints in cancer genomes, we find significant association between PONDS-forming repeats and cancer breakpoints. Specifically, (AT)n, (GAA)n and (GAAA)n constitute the most frequent repeats at translocation breakpoints, whereas A-tracts occur preferentially at deletion breakpoints. Translocation breakpoints near PONDS-forming repeats also recur in different individuals and patient tumor samples. Hence, PONDS-forming sequences represent an intrinsic risk factor for genomic rearrangements in cancer genomes. PMID:27084947

  16. Ovarian Cancers Harboring Inactivating Mutations in CDK12 Display a Distinct Genomic Instability Pattern Characterized by Large Tandem Duplications.

    Science.gov (United States)

    Popova, Tatiana; Manié, Elodie; Boeva, Valentina; Battistella, Aude; Goundiam, Oumou; Smith, Nicholas K; Mueller, Christopher R; Raynal, Virginie; Mariani, Odette; Sastre-Garau, Xavier; Stern, Marc-Henri

    2016-04-01

    CDK12 is a recurrently mutated gene in serous ovarian carcinoma, whose downregulation is associated with impaired expression of DNA damage repair genes and subsequent hypersensitivity to DNA-damaging agents and PARP1/2 inhibitors. In this study, we investigated the genomic landscape associated with CDK12 inactivation in patients with serous ovarian carcinoma. We show that CDK12 loss was consistently associated with a particular genomic instability pattern characterized by hundreds of tandem duplications of up to 10 megabases (Mb) in size. Tandem duplications were characterized by a bimodal (∼0.3 and ∼3 Mb) size distribution and overlapping microhomology at the breakpoints. This genomic instability, denoted as the CDK12 TD-plus phenotype, is remarkably distinct from other alteration patterns described in breast and ovarian cancers. The CDK12 TD-plus phenotype was associated with a greater than 10% gain in genomic content and occurred at a 3% to 4% rate in The Cancer Genome Atlas-derived and in-house cohorts of patients with serous ovarian carcinoma. Moreover, CDK12-inactivating mutations together with the TD-plus phenotype were also observed in prostate cancers. Our finding provides new insight toward deciphering the function of CDK12 in genome maintenance and oncogenesis. Cancer Res; 76(7); 1882-91. ©2016 AACR. PMID:26787835

  17. 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

  18. Public Health Action Model for Cancer Survivorship.

    Science.gov (United States)

    Moore, Angela R; Buchanan, Natasha D; Fairley, Temeika L; Lee Smith, Judith

    2015-12-01

    Long-term objectives associated with cancer survivors have been suggested by Healthy People 2020, including increasing the proportion of survivors living beyond 5 years after diagnosis and improving survivors' mental and physical health-related quality of life. Prior to reaching these objectives, several intermediate steps must be taken to improve the physical, social, emotional, and financial well-being of cancer survivors. Public health has a role in developing strategic, actionable, and measurable approaches to facilitate change at multiple levels to improve the lives of survivors and their families. The social ecological model has been used by the public health community as the foundation of multilevel intervention design and implementation, encouraging researchers and practitioners to explore methods that promote internal and external changes at the individual, interpersonal, organizational, community, and policy levels. The survivorship community, including public health professionals, providers, policymakers, survivors, advocates, and caregivers, must work collaboratively to identify, develop, and implement interventions that benefit cancer survivors. The National Action Plan for Cancer Survivorship highlights public health domains and associated strategies that can be the impetus for collaboration between and among the levels in the social ecological model and are integral to improving survivor outcomes. This paper describes the Public Health Action Model for Cancer Survivorship, an integrative framework that combines the National Action Plan for Cancer Survivorship with the social ecological model to demonstrate how interaction among the various levels may promote better outcomes for survivors. PMID:26590641

  19. Genomic agonism and phenotypic antagonism between estrogen and progesterone receptors in breast cancer.

    Science.gov (United States)

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

    2016-06-01

    The functional role of progesterone receptor (PR) and its impact on estrogen signaling in breast cancer remain controversial. In primary ER(+) (estrogen receptor-positive)/PR(+) human tumors, we report that PR reprograms estrogen signaling as a genomic agonist and a phenotypic antagonist. In isolation, estrogen and progestin act as genomic agonists by regulating the expression of common target genes in similar directions, but at different levels. Similarly, in isolation, progestin is also a weak phenotypic agonist of estrogen action. However, in the presence of both hormones, progestin behaves as a phenotypic estrogen antagonist. PR remodels nucleosomes to noncompetitively redirect ER genomic binding to distal enhancers enriched for BRCA1 binding motifs and sites that link PR and ER/PR complexes. When both hormones are present, progestin modulates estrogen action, such that responsive transcriptomes, cellular processes, and ER/PR recruitment to genomic sites correlate with those observed with PR alone, but not ER alone. Despite this overall correlation, the transcriptome patterns modulated by dual treatment are sufficiently different from individual treatments, such that antagonism of oncogenic processes is both predicted and observed. Combination therapies using the selective PR modulator/antagonist (SPRM) CDB4124 in combination with tamoxifen elicited 70% cytotoxic tumor regression of T47D tumor xenografts, whereas individual therapies inhibited tumor growth without net regression. Our findings demonstrate that PR redirects ER chromatin binding to antagonize estrogen signaling and that SPRMs can potentiate responses to antiestrogens, suggesting that cotargeting of ER and PR in ER(+)/PR(+) breast cancers should be explored. PMID:27386569

  20. 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

  1. 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 or......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...

  2. Ovarian Cancer Pathogenesis: A Model in Evolution

    Directory of Open Access Journals (Sweden)

    Alison M. Karst

    2010-01-01

    Full Text Available Ovarian cancer is a deadly disease for which there is no effective means of early detection. Ovarian carcinomas comprise a diverse group of neoplasms, exhibiting a wide range of morphological characteristics, clinical manifestations, genetic alterations, and tumor behaviors. This high degree of heterogeneity presents a major clinical challenge in both diagnosing and treating ovarian cancer. Furthermore, the early events leading to ovarian carcinoma development are poorly understood, thus complicating efforts to develop screening modalities for this disease. Here, we provide an overview of the current models of ovarian cancer pathogenesis, highlighting recent findings implicating the fallopian tube fimbria as a possible site of origin of ovarian carcinomas. The ovarian cancer model will continue to evolve as we learn more about the genetics and etiology of this disease.

  3. Colorectal Cancer and the Human Gut Microbiome: Reproducibility with Whole-Genome Shotgun Sequencing

    Science.gov (United States)

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

    2016-01-01

    Accumulating evidence indicates that the gut microbiota affects colorectal cancer development, but previous studies have varied in population, technical methods, and associations with cancer. Understanding these variations is needed for comparisons and for potential pooling across studies. Therefore, we performed whole-genome shotgun sequencing on fecal samples from 52 pre-treatment colorectal cancer cases and 52 matched controls from Washington, DC. We compared findings from a previously published 16S rRNA study to the metagenomics-derived taxonomy within the same population. In addition, metagenome-predicted genes, modules, and pathways in the Washington, DC cases and controls were compared to cases and controls recruited in France whose specimens were processed using the same platform. Associations between the presence of fecal Fusobacteria, Fusobacterium, and Porphyromonas with colorectal cancer detected by 16S rRNA were reproduced by metagenomics, whereas higher relative abundance of Clostridia in cancer cases based on 16S rRNA was merely borderline based on metagenomics. This demonstrated that within the same sample set, most, but not all taxonomic associations were seen with both methods. Considering significant cancer associations with the relative abundance of genes, modules, and pathways in a recently published French metagenomics dataset, statistically significant associations in the Washington, DC population were detected for four out of 10 genes, three out of nine modules, and seven out of 17 pathways. In total, colorectal cancer status in the Washington, DC study was associated with 39% of the metagenome-predicted genes, modules, and pathways identified in the French study. More within and between population comparisons are needed to identify sources of variation and disease associations that can be reproduced despite these variations. Future studies should have larger sample sizes or pool data across studies to have sufficient power to detect

  4. Colorectal Cancer and the Human Gut Microbiome: Reproducibility with Whole-Genome Shotgun Sequencing.

    Science.gov (United States)

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

    2016-01-01

    Accumulating evidence indicates that the gut microbiota affects colorectal cancer development, but previous studies have varied in population, technical methods, and associations with cancer. Understanding these variations is needed for comparisons and for potential pooling across studies. Therefore, we performed whole-genome shotgun sequencing on fecal samples from 52 pre-treatment colorectal cancer cases and 52 matched controls from Washington, DC. We compared findings from a previously published 16S rRNA study to the metagenomics-derived taxonomy within the same population. In addition, metagenome-predicted genes, modules, and pathways in the Washington, DC cases and controls were compared to cases and controls recruited in France whose specimens were processed using the same platform. Associations between the presence of fecal Fusobacteria, Fusobacterium, and Porphyromonas with colorectal cancer detected by 16S rRNA were reproduced by metagenomics, whereas higher relative abundance of Clostridia in cancer cases based on 16S rRNA was merely borderline based on metagenomics. This demonstrated that within the same sample set, most, but not all taxonomic associations were seen with both methods. Considering significant cancer associations with the relative abundance of genes, modules, and pathways in a recently published French metagenomics dataset, statistically significant associations in the Washington, DC population were detected for four out of 10 genes, three out of nine modules, and seven out of 17 pathways. In total, colorectal cancer status in the Washington, DC study was associated with 39% of the metagenome-predicted genes, modules, and pathways identified in the French study. More within and between population comparisons are needed to identify sources of variation and disease associations that can be reproduced despite these variations. Future studies should have larger sample sizes or pool data across studies to have sufficient power to detect

  5. 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

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

    OpenAIRE

    Irving, Amy A.; Kazuto Yoshimi; Hart, Marcia L.; Taybor Parker; Linda Clipson; Ford, Madeline R; Takashi Kuramoto; Dove, William F; Amos-Landgraf, James M.

    2014-01-01

    Prior to the advent of genetic engineering in the mouse, the rat was the model of choice for investigating the etiology of cancer. Now, recent advances in the manipulation of the rat genome, combined with a growing recognition of the physiological differences between mice and rats, have reignited interest in the rat as a model of human cancer. Two recently developed rat models, the polyposis in the rat colon (Pirc) and Kyoto Apc Delta (KAD) strains, each carry mutations in the intestinal-canc...

  7. Emerging and Evolving Ovarian Cancer Animal Models

    OpenAIRE

    Bobbs, Alexander S; Jennifer M. Cole; Cowden Dahl, Karen D.

    2015-01-01

    Ovarian cancer (OC) is the leading cause of death from a gynecological malignancy in the United States. By the time a woman is diagnosed with OC, the tumor has usually metastasized. Mouse models that are used to recapitulate different aspects of human OC have been evolving for nearly 40 years. Xenograft studies in immunocompromised and immunocompetent mice have enhanced our knowledge of metastasis and immune cell involvement in cancer. Patient-derived xenografts (PDXs) can accurately reflect ...

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

    OpenAIRE

    Garcia-Closas, Montserrat; Couch, Fergus J.; Lindstrom, Sara; Michailidou, Kyriaki; Schmidt, Marjanka K.; Brook, Mark N.; Orr, Nick; Rhie, Suhn Kyong; Riboli, Elio; Feigelson, Heather s; Le Marchand, Loic; Buring, Julie E.; Eccles, Diana; Miron, Penelope; Fasching, Peter A.

    2013-01-01

    Estrogen receptor (ER)-negative tumors represent 20–30% of all breast cancers, with a higher proportion occurring in younger women and women of African ancestry1. The etiology2 and clinical behavior3 of ER-negative tumors are different from those of tumors expressing ER (ER positive), including differences in genetic predisposition4. To identify susceptibility loci specific to ER-negative disease, we combined in a meta-analysis 3 genome-wide association studies of 4,193 ER-negative breast can...

  9. GENOMIC LANDSCAPE OF NON-SMALL CELL LUNG CANCER IN SMOKERS AND NEVER SMOKERS

    Science.gov (United States)

    Govindan, Ramaswamy; Ding, Li; Griffith, Malachi; Subramanian, Janakiraman; Dees, Nathan D.; Kanchi, Krishna L.; Maher, Christopher A.; Fulton, Robert; Fulton, Lucinda; Wallis, John; Chen, Ken; Walker, Jason; McDonald, Sandra; Bose, Ron; Ornitz, David; Xiong, Donghai; You, Ming; Dooling, David J.; Watson, Mark; Mardis, Elaine R.

    2013-01-01

    Summary We report the results of whole genome and transcriptome sequencing of tumor and adjacent normal tissue samples from 17 patients with non-small cell lung carcinoma (NSCLC). We identified 3,726 point mutations and over 90 indels in the coding sequence, with an average mutation frequency more than 10-fold higher in smokers than in never-smokers. Novel alterations in genes involved in chromatic modification and DNA repair pathways were identified along with DACH1, CFTR, RELN, ABCB5, and HGF. Deep digital sequencing revealed diverse clonality patterns in both never smokers and smokers. All validated EFGR and KRAS mutations were present in the founder clones, suggesting possible roles in cancer initiation. Analysis revealed 14 fusions including ROS1 and ALK as well as novel metabolic enzymes. Cell cycle and JAK-STAT pathways are significantly altered in lung cancer along with perturbations in 54 genes that are potentially targetable with currently available drugs. PMID:22980976

  10. 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

  11. 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.

  12. Mathematical models of breast and ovarian cancers.

    Science.gov (United States)

    Botesteanu, Dana-Adriana; Lipkowitz, Stanley; Lee, Jung-Min; Levy, Doron

    2016-07-01

    Women constitute the majority of the aging United States (US) population, and this has substantial implications on cancer population patterns and management practices. Breast cancer is the most common women's malignancy, while ovarian cancer is the most fatal gynecological malignancy in the US. In this review, we focus on these subsets of women's cancers, seen more commonly in postmenopausal and elderly women. In order to systematically investigate the complexity of cancer progression and response to treatment in breast and ovarian malignancies, we assert that integrated mathematical modeling frameworks viewed from a systems biology perspective are needed. Such integrated frameworks could offer innovative contributions to the clinical women's cancers community, as answers to clinical questions cannot always be reached with contemporary clinical and experimental tools. Here, we recapitulate clinically known data regarding the progression and treatment of the breast and ovarian cancers. We compare and contrast the two malignancies whenever possible in order to emphasize areas where substantial contributions could be made by clinically inspired and validated mathematical modeling. We show how current paradigms in the mathematical oncology community focusing on the two malignancies do not make comprehensive use of, nor substantially reflect existing clinical data, and we highlight the modeling areas in most critical need of clinical data integration. We emphasize that the primary goal of any mathematical study of women's cancers should be to address clinically relevant questions. WIREs Syst Biol Med 2016, 8:337-362. doi: 10.1002/wsbm.1343 For further resources related to this article, please visit the WIREs website. PMID:27259061

  13. 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

  14. Translating genomics: cancer genetics, public health and the making of the (de)molecularised body in Cuba and Brazil.

    Science.gov (United States)

    Gibbon, Sahra

    2016-03-01

    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. PMID:27008076

  15. 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. PMID:24588670

  16. Open pipelines for integrated tumor genome profiles reveal differences between pancreatic cancer tumors and cell lines

    International Nuclear Information System (INIS)

    We describe open, reproducible pipelines that create an integrated genomic profile of a cancer and use the profile to find mutations associated with disease and potentially useful drugs. These pipelines analyze high-throughput cancer exome and transcriptome sequence data together with public databases to find relevant mutations and drugs. The three pipelines that we have developed are: (1) an exome analysis pipeline, which uses whole or targeted tumor exome sequence data to produce a list of putative variants (no matched normal data are needed); (2) a transcriptome analysis pipeline that processes whole tumor transcriptome sequence (RNA-seq) data to compute gene expression and find potential gene fusions; and (3) an integrated variant analysis pipeline that uses the tumor variants from the exome pipeline and tumor gene expression from the transcriptome pipeline to identify deleterious and druggable mutations in all genes and in highly expressed genes. These pipelines are integrated into the popular Web platform Galaxy at #http://usegalaxy.org/cancer# to make them accessible and reproducible, thereby providing an approach for doing standardized, distributed analyses in clinical studies. We have used our pipeline to identify similarities and differences between pancreatic adenocarcinoma cancer cell lines and primary tumors

  17. Radiotherapy for glioblastoma: reorganization of genome maintenance mechanisms involved in the process of inhibiting cancer

    International Nuclear Information System (INIS)

    Glioblastoma is a very aggressive brain tumor, which occurs in Glial cells. The treatment consists in chemotherapy, surgery and radiotherapy. The radiotherapy is a treatment method that uses ionizing radiation to kill cancer cells. The cells have genome maintenance mechanisms (MMG) distributed in apoptosis, DNA damage response, and cell cycle pathways. These pathways are formed by sets of proteins and perform specific functions within the cell (example: induce cell death). The mutation of these proteins associated with the failure of the MMG can cause the activation of mutations and consequently induce the development of cancer. This work, objective has to identify pathways and proteins expressed in cancer treatment using free software of the statistical analysis, developed in Fortran and R platforms to show the effects caused by radiation in the proteins of cancerous tissues. The results, were fond to pathways of glioblastoma treated with radiotherapy, activation of apoptosis and response to DNA damage pathways, indicating that there is death of carcinogenic tissue caused by radiation and that some cells are triggering a process of DNA repair. (author)

  18. 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.

  19. Genomic Profiling of Thyroid Cancer Reveals a Role for Thyroglobulin in Metastasis.

    Science.gov (United States)

    Siraj, Abdul K; Masoodi, Tariq; Bu, Rong; Beg, Shaham; Al-Sobhi, Saif S; Al-Dayel, Fouad; Al-Dawish, Mohammed; Alkuraya, Fowzan S; Al-Kuraya, Khawla S

    2016-06-01

    Papillary thyroid carcinoma (PTC) has a wide geographic variation in incidence; it is most common in Saudi Arabia, where it is only second to breast cancer as the most common cancer among females. Genomic profiling of PTC from Saudi Arabia has not been attempted previously. We performed whole-exome sequencing of 101 PTC samples and the corresponding genomic DNA to identify genes with recurrent somatic mutations, then sequenced these genes by using a next-generation gene-panel approach in an additional 785 samples. In addition to BRAF, N-RAS, and H-RAS, which have previously been shown to be recurrently mutated in PTC, our analysis highlights additional genes, including thyroglobulin (TG), which harbored somatic mutations in 3% of the entire cohort. Surprisingly, although TG mutations were not exclusive to mutations in the RAS-MAP kinase pathway, their presence was associated with a significantly worse clinical outcome, which suggests a pathogenic role beyond driving initial oncogenesis. Analysis of metastatic PTC tissue revealed significant enrichment for TG mutations (p evolution. PMID:27236916

  20. Development of cancer-initiating cells and immortalizedcells with genomic instability

    Institute of Scientific and Technical Information of China (English)

    Ken-ichi Yoshioka; Yuko Atsumi; Hitoshi Nakagama; Hirobumi Teraoka

    2015-01-01

    Cancers that develop after middle age usually exhibitgenomic instability and multiple mutations. This is indirect contrast to pediatric tumors that usually developas a result of specific chromosomal translocations andepigenetic aberrations. The development of genomicinstability is associated with mutations that contributeto cellular immortalization and transformation. Canceroccurs when cancer-initiating cells (CICs), also calledcancer stem cells, develop as a result of these mutations.In this paper, we explore how CICs develop as a resultof genomic instability, including looking at which cancersuppression mechanisms are abrogated. A recent in vitrostudy revealed the existence of a CIC induction pathwayin differentiating stem cells. Under aberrant differentiationconditions, cells become senescent and develop genomicinstabilities that lead to the development of CICs. Theresulting CICs contain a mutation in the alternativereading frame of CDKN2A (ARF)/p53 module, i.e. , ineither ARF or p53. We summarize recently establishedknowledge of CIC development and cellular immortality,explore the role of the ARF/p53 module in protectingcells from transformation, and describe a risk factorfor genomic destabilization that increases during theprocess of normal cell growth and differentiation and isassociated with the downregulation of histone H2AX tolevels representative of growth arrest in normal cells.

  1. Optimization of primer design for the detection of variable genomic lesions in cancer.

    Science.gov (United States)

    Bashir, Ali; Liu, Yu-Tsueng; Raphael, Benjamin J; Carson, Dennis; Bafna, Vineet

    2007-11-01

    Primer approximation multiplex PCR (PAMP) is a new experimental protocol for efficiently assaying structural variation in genomes. PAMP is particularly suited to cancer genomes where the precise breakpoints of alterations such as deletions or translocations vary between patients. The design of PCR primer sets for PAMP is challenging because a large number of primer pairs are required to detect alterations in the hundreds of kilobases range that can occur in cancer. These sets of primers must achieve high coverage of the region of interest, while avoiding primer dimers and satisfying the physico-chemical constraints of good PCR primers. We describe a natural formulation of these constraints as a combinatorial optimization problem. We show that the PAMP primer design problem is NP-hard, and design algorithms based on simulated annealing and integer programming, that provide good solutions to this problem in practice. The algorithms are applied to a test region around the known CDKN2A deletion, which show excellent results even in a 1:49 mixture of mutated:wild-type cells. We use these test results to help set design parameters for larger problems. We can achieve near-optimal designs for regions close to 1 Mb. PMID:17766270

  2. Allelic losses at genomic instability-associated loci in villous adenomas and adjacent colorectal cancers.

    Science.gov (United States)

    Brenner, Bruce M; Stoler, Daniel L; Rodriguez, Luz; Karpenko, Matthew J; Swede, Helen; Petrelli, Nicholas J; Anderson, Garth R

    2007-04-01

    Allelic imbalances in premalignant villous adenomas were compared with those in adjacent microdissected colorectal carcinoma that had arisen directly from the adenomas. Carcinoma-adenoma pairs were examined from 17 patients who underwent resections for colorectal cancer. In all, 28 microsatellite markers were examined, from regions of the genome where individual allelic losses have been associated with overall genomic instability in colorectal carcinomas. Microsatellite instability (MSI) was also evaluated for each marker in each tissue type. Loss of heterozygosity for multiple markers was found in 35% of adenomas and 65% of carcinomas; the average fractional allelic loss rate was 2.5 times higher in carcinomas than in adenomas. Of the 17 patients, 4 had MSI for >30% of markers in both adenoma and carcinoma, with no significant differences between the two tissues. Markers with particularly high imbalance rates in adenomas were seen on chromosomes 11, 14, and 15. These findings provide further evidence that genomic instability is an ongoing process during carcinogenesis, with a markedly increased frequency of allelic losses seen in carcinomas, compared with adjacent adenomas. Markers on chromosomes 11, 14, and 15 may become valuable tools in the identification of patients destined to progress to colorectal carcinomas. PMID:17350461

  3. caBIG™ VISDA: Modeling, visualization, and discovery for cluster analysis of genomic data

    Directory of Open Access Journals (Sweden)

    Xuan Jianhua

    2008-09-01

    clustering, and phenotype clustering (wherein phenotype labels for samples are known, albeit with minor algorithm modifications customized to each of these tasks. Conclusion VISDA achieved robust and superior clustering accuracy, compared with several benchmark clustering schemes. The model order selection scheme in VISDA was shown to be effective for high dimensional genomic data clustering. On muscular dystrophy data and muscle regeneration data, VISDA identified biologically relevant co-expressed gene clusters. VISDA also captured the pathological relationships among different phenotypes revealed at the molecular level, through phenotype clustering on muscular dystrophy data and multi-category cancer data.

  4. In Silico Experimental Modeling of Cancer Treatment

    OpenAIRE

    Trisilowati; D. G. Mallet

    2012-01-01

    In silico experimental modeling of cancer involves combining findings from biological literature with computer-based models of biological systems in order to conduct investigations of hypotheses entirely in the computer laboratory. In this paper, we discuss the use of in silico modeling as a precursor to traditional clinical and laboratory research, allowing researchers to refine their experimental programs with an aim to reducing costs and increasing research efficiency. We explain the metho...

  5. Quantitative and Sensitive Detection of Cancer Genome Amplifications from Formalin Fixed Paraffin Embedded Tumors with Droplet Digital PCR.

    Science.gov (United States)

    Nadauld, Lincoln; Regan, John F; Miotke, Laura; Pai, Reet K; Longacre, Teri A; Kwok, Shirley S; Saxonov, Serge; Ford, James M; Ji, Hanlee P

    2012-01-01

    For the analysis of cancer, there is great interest in rapid and accurate detection of cancer genome amplifications containing oncogenes that are potential therapeutic targets. The vast majority of cancer tissue samples are formalin fixed and paraffin embedded (FFPE) which enables histopathological examination and long term archiving. However, FFPE cancer genomic DNA is oftentimes degraded and generally a poor substrate for many molecular biology assays. To overcome the issues of poor DNA quality from FFPE samples and detect oncogenic copy number amplifications with high accuracy and sensitivity, we developed a novel approach. Our assay requires nanogram amounts of genomic DNA, thus facilitating study of small amounts of clinical samples. Using droplet digital PCR (ddPCR), we can determine the relative copy number of specific genomic loci even in the presence of intermingled normal tissue. We used a control dilution series to determine the limits of detection for the ddPCR assay and report its improved sensitivity on minimal amounts of DNA compared to standard real-time PCR. To develop this approach, we designed an assay for the fibroblast growth factor receptor 2 gene (FGFR2) that is amplified in a gastric and breast cancers as well as others. We successfully utilized ddPCR to ascertain FGFR2 amplifications from FFPE-preserved gastrointestinal adenocarcinomas. PMID:23682346

  6. TP53 Variations in Human Cancers: New Lessons from the IARC TP53 Database and Genomics Data.

    Science.gov (United States)

    Bouaoun, Liacine; Sonkin, Dmitriy; Ardin, Maude; Hollstein, Monica; Byrnes, Graham; Zavadil, Jiri; Olivier, Magali

    2016-09-01

    TP53 gene mutations are one of the most frequent somatic events in cancer. The IARC TP53 Database (http://p53.iarc.fr) is a popular resource that compiles occurrence and phenotype data on TP53 germline and somatic variations linked to human cancer. The deluge of data coming from cancer genomic studies generates new data on TP53 variations and attracts a growing number of database users for the interpretation of TP53 variants. Here, we present the current contents and functionalities of the IARC TP53 Database and perform a systematic analysis of TP53 somatic mutation data extracted from this database and from genomic data repositories. This analysis showed that IARC has more TP53 somatic mutation data than genomic repositories (29,000 vs. 4,000). However, the more complete screening achieved by genomic studies highlighted some overlooked facts about TP53 mutations, such as the presence of a significant number of mutations occurring outside the DNA-binding domain in specific cancer types. We also provide an update on TP53 inherited variants including the ones that should be considered as neutral frequent variations. We thus provide an update of current knowledge on TP53 variations in human cancer as well as inform users on the efficient use of the IARC TP53 Database. PMID:27328919

  7. Comprehensive Resources for Tomato Functional Genomics Based on the Miniature Model Tomato Micro-Tom

    OpenAIRE

    Matsukura, C; Aoki, K.; Fukuda, N.; Mizoguchi, T.; Asamizu, E; Saito, T.; Shibata, D.; Ezura, H.

    2008-01-01

    Tomato (Solanum lycopersicum L., Solanaceae) is an excellent model plant for genomic research of solanaceous plants, as well as for studying the development, ripening, and metabolism of fruit. In 2003, the International Solanaceae Project (SOL, www.sgn.cornell.edu ) was initiated by members from more than 30 countries, and the tomato genome-sequencing project is currently underway. Genome sequence of tomato obtained by this project will provide a firm foundation for forthcoming genomic studie...

  8. Extensive Transcriptomic and Genomic Analysis Provides New Insights about Luminal Breast Cancers

    Science.gov (United States)

    Tishchenko, Inna; Milioli, Heloisa Helena; Riveros, Carlos; Moscato, Pablo

    2016-01-01

    Despite constituting approximately two thirds of all breast cancers, the luminal A and B tumours are poorly classified at both clinical and molecular levels. There are contradictory reports on the nature of these subtypes: some define them as intrinsic entities, others as a continuum. With the aim of addressing these uncertainties and identifying molecular signatures of patients at risk, we conducted a comprehensive transcriptomic and genomic analysis of 2,425 luminal breast cancer samples. Our results indicate that the separation between the molecular luminal A and B subtypes—per definition—is not associated with intrinsic characteristics evident in the differentiation between other subtypes. Moreover, t-SNE and MST-kNN clustering approaches based on 10,000 probes, associated with luminal tumour initiation and/or development, revealed the close connections between luminal A and B tumours, with no evidence of a clear boundary between them. Thus, we considered all luminal tumours as a single heterogeneous group for analysis purposes. We first stratified luminal tumours into two distinct groups by their HER2 gene cluster co-expression: HER2-amplified luminal and ordinary-luminal. The former group is associated with distinct transcriptomic and genomic profiles, and poor prognosis; it comprises approximately 8% of all luminal cases. For the remaining ordinary-luminal tumours we further identified the molecular signature correlated with disease outcomes, exhibiting an approximately continuous gene expression range from low to high risk. Thus, we employed four virtual quantiles to segregate the groups of patients. The clinico-pathological characteristics and ratios of genomic aberrations are concordant with the variations in gene expression profiles, hinting at a progressive staging. The comparison with the current separation into luminal A and B subtypes revealed a substantially improved survival stratification. Concluding, we suggest a review of the definition of

  9. Flexible positions, managed hopes: the promissory bioeconomy of a whole genome sequencing cancer study.

    Science.gov (United States)

    Haase, Rachel; Michie, Marsha; Skinner, Debra

    2015-04-01

    Genomic research has rapidly expanded its scope and ambition over the past decade, promoted by both public and private sectors as having the potential to revolutionize clinical medicine. This promissory bioeconomy of genomic research and technology is generated by, and in turn generates, the hopes and expectations shared by investors, researchers and clinicians, patients, and the general public alike. Examinations of such bioeconomies have often focused on the public discourse, media representations, and capital investments that fuel these "regimes of hope," but also crucial are the more intimate contexts of small-scale medical research, and the private hopes, dreams, and disappointments of those involved. Here we examine one local site of production in a university-based clinical research project that sought to identify novel cancer predisposition genes through whole genome sequencing in individuals at high risk for cancer. In-depth interviews with 24 adults who donated samples to the study revealed an ability to shift flexibly between positioning themselves as research participants on the one hand, and as patients or as family members of patients, on the other. Similarly, interviews with members of the research team highlighted the dual nature of their positions as researchers and as clinicians. For both parties, this dual positioning shaped their investment in the project and valuing of its possible outcomes. In their narratives, all parties shifted between these different relational positions as they managed hopes and expectations for the research project. We suggest that this flexibility facilitated study implementation and participation in the face of potential and probable disappointment on one or more fronts, and acted as a key element in the resilience of this local promissory bioeconomy. We conclude that these multiple dimensions of relationality and positionality are inherent and essential in the creation of any complex economy, "bio" or otherwise. PMID

  10. A Novel Bioluminescence Orthotopic Mouse Model for Advanced Lung Cancer

    OpenAIRE

    Li, Bo; Torossian, Artour; Li, Wenyan; Schleicher, Stephen; Niu, Kathy; Giacalone, Nicholas J; Kim, Sung June; Chen, Heidi; Gonzalez, Adriana; Moretti, Luigi; Lu, Bo

    2011-01-01

    Lung cancer is the leading cause of cancer-related death in the United States despite recent advances in our understanding of this challenging disease. An animal model for high-throughput screening of therapeutic agents for advanced lung cancer could help promote the development of more successful treatment interventions. To develop our orthotopic lung cancer model, luciferase-expressing A549 cancer cells were injected into the mediastinum of athymic nude mice. To determine whether the model ...

  11. Model Checking of a Diabetes-Cancer Model

    Science.gov (United States)

    Gong, Haijun; Zuliani, Paolo; Clarke, Edmund M.

    2011-06-01

    Accumulating evidence suggests that cancer incidence might be associated with diabetes mellitus, especially Type II diabetes which is characterized by hyperinsulinaemia, hyperglycaemia, obesity, and overexpression of multiple WNT pathway components. These diabetes risk factors can activate a number of signaling pathways that are important in the development of different cancers. To systematically understand the signaling components that link diabetes and cancer risk, we have constructed a single-cell, Boolean network model by integrating the signaling pathways that are influenced by these risk factors to study insulin resistance, cancer cell proliferation and apoptosis. Then, we introduce and apply the Symbolic Model Verifier (SMV), a formal verification tool, to qualitatively study some temporal logic properties of our diabetes-cancer model. The verification results show that the diabetes risk factors might not increase cancer risk in normal cells, but they will promote cell proliferation if the cell is in a precancerous or cancerous stage characterized by losses of the tumor-suppressor proteins ARF and INK4a.

  12. Accumulation of mutations over the complete mitochondrial genome in tobacco-related oral cancer from northeast India.

    Science.gov (United States)

    Mondal, Rosy; Ghosh, Sankar Kumar

    2013-08-01

    Northeast India has one of the world's highest incidences of oral cancer and 90% of them are related to tobacco. We examined the complete mitochondrial genome to determine hot spot mutations in oral cancer. The complete mitochondrial genome was sequenced using PGM™ from 10 patients matched blood and tumour tissue. Overall, 26 somatic mutations were found of which nine mutations in d-loop and 17 mutations in the coding region. The mutations at nucleotide positions 16294, 16325 and 16463 in d-loop and 4136, 13542 and 13869 in coding region are probably an indication to be a hot spot mutation in oral cancer. The knowledge about role, patterns and timing of mitochondrial mutations may serve to be facilitating clinical applications and hot spot mutations may be helpful in assessing cancer risk in tumour. PMID:23350716

  13. Zebrafish models for the functional genomics of neurogenetic disorders.

    Science.gov (United States)

    Kabashi, Edor; Brustein, Edna; Champagne, Nathalie; Drapeau, Pierre

    2011-03-01

    In this review, we consider recent work using zebrafish to validate and study the functional consequences of mutations of human genes implicated in a broad range of degenerative and developmental disorders of the brain and spinal cord. Also we present technical considerations for those wishing to study their own genes of interest by taking advantage of this easily manipulated and clinically relevant model organism. Zebrafish permit mutational analyses of genetic function (gain or loss of function) and the rapid validation of human variants as pathological mutations. In particular, neural degeneration can be characterized at genetic, cellular, functional, and behavioral levels. Zebrafish have been used to knock down or express mutations in zebrafish homologs of human genes and to directly express human genes bearing mutations related to neurodegenerative disorders such as spinal muscular atrophy, ataxia, hereditary spastic paraplegia, amyotrophic lateral sclerosis (ALS), epilepsy, Huntington's disease, Parkinson's disease, fronto-temporal dementia, and Alzheimer's disease. More recently, we have been using zebrafish to validate mutations of synaptic genes discovered by large-scale genomic approaches in developmental disorders such as autism, schizophrenia, and non-syndromic mental retardation. Advances in zebrafish genetics such as multigenic analyses and chemical genetics now offer a unique potential for disease research. Thus, zebrafish hold much promise for advancing the functional genomics of human diseases, the understanding of the genetics and cell biology of degenerative and developmental disorders, and the discovery of therapeutics. This article is part of a Special Issue entitled Zebrafish Models of Neurological Diseases. PMID:20887784

  14. 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 & ...

  15. 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.

  16. 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. PMID:24318985

  17. Prognostic Impact of Array-based Genomic Profiles in Esophageal Squamous Cell Cancer

    International Nuclear Information System (INIS)

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

  18. Whole genome RNA expression profiling for the identification of novel biomarkers in the diagnosis and prognosis of biliary tract cancer

    OpenAIRE

    Chapman, M H

    2011-01-01

    Biliary tract cancer (BTC) is difficult to diagnose, in part related to the lack of reliable tumour markers. The aim of this project was to use whole genome RNA expression profiling in order to identify novel biomarkers for diagnosis and prognosis in biliary tract cancer. Chapter 1 summarises clinical aspects of BTC as well as current diagnostic and prognostic tests. Chapter 2 addresses the identification of circulating tumour cells for the diagnosis of BTC. It includes d...

  19. Computational methods for detecting copy number variations in cancer genome using next generation sequencing: principles and challenges

    OpenAIRE

    Liu, Biao; Morrison, Carl D.; Johnson, Candace S.; Trump, Donald L.; Qin, Maochun; Conroy, Jeffrey C.; Wang, Jianmin; Liu, Song

    2013-01-01

    Accurate detection of somatic copy number variations (CNVs) is an essential part of cancer genome analysis, and plays an important role in oncotarget identifications. Next generation sequencing (NGS) holds the promise to revolutionize somatic CNV detection. In this review, we provide an overview of current analytic tools used for CNV detection in NGS-based cancer studies. We summarize the NGS data types used for CNV detection, decipher the principles for data preprocessing, segmentation, and ...

  20. Lessons learned from the application of whole-genome analysis to the treatment of patients with advanced cancers

    Science.gov (United States)

    Laskin, Janessa; Jones, Steven; Aparicio, Samuel; Chia, Stephen; Ch'ng, Carolyn; Deyell, Rebecca; Eirew, Peter; Fok, Alexandra; Gelmon, Karen; Ho, Cheryl; Huntsman, David; Jones, Martin; Kasaian, Katayoon; Karsan, Aly; Leelakumari, Sreeja; Li, Yvonne; Lim, Howard; Ma, Yussanne; Mar, Colin; Martin, Monty; Moore, Richard; Mungall, Andrew; Mungall, Karen; Pleasance, Erin; Rassekh, S. Rod; Renouf, Daniel; Shen, Yaoqing; Schein, Jacqueline; Schrader, Kasmintan; Sun, Sophie; Tinker, Anna; Zhao, Eric; Yip, Stephen; Marra, Marco A.

    2015-01-01

    Given the success of targeted agents in specific populations it is expected that some degree of molecular biomarker testing will become standard of care for many, if not all, cancers. To facilitate this, cancer centers worldwide are experimenting with targeted “panel” sequencing of selected mutations. Recent advances in genomic technology enable the generation of genome-scale data sets for individual patients. Recognizing the risk, inherent in panel sequencing, of failing to detect meaningful somatic alterations, we sought to establish processes to integrate data from whole-genome analysis (WGA) into routine cancer care. Between June 2012 and August 2014, 100 adult patients with incurable cancers consented to participate in the Personalized OncoGenomics (POG) study. Fresh tumor and blood samples were obtained and used for whole-genome and RNA sequencing. Computational approaches were used to identify candidate driver mutations, genes, and pathways. Diagnostic and drug information were then sought based on these candidate “drivers.” Reports were generated and discussed weekly in a multidisciplinary team setting. Other multidisciplinary working groups were assembled to establish guidelines on the interpretation, communication, and integration of individual genomic findings into patient care. Of 78 patients for whom WGA was possible, results were considered actionable in 55 cases. In 23 of these 55 cases, the patients received treatments motivated by WGA. Our experience indicates that a multidisciplinary team of clinicians and scientists can implement a paradigm in which WGA is integrated into the care of late stage cancer patients to inform systemic therapy decisions. PMID:27148575

  1. Association between 5p12 genomic markers and breast cancer susceptibility: evidence from 19 case-control studies.

    Directory of Open Access Journals (Sweden)

    Xiaofeng Wang

    Full Text Available BACKGROUND: The association between polymorphisms on 5p12 and breast cancer (BC has been widely evaluated since it was first identified through genome-wide association approach; however, the studies have yielded contradictory results. We sought to investigate this inconsistency by performing a comprehensive meta-analysis on two wildly studied polymorphisms (rs10941679 and rs4415084 on 5p12. METHODS: Databases including Pubmed, EMBASE, Web of Science, EBSCO, and Cochrane Library databases were searched to find relevant studies. Odds ratios (ORs with 95% confidence intervals (CIs were used to assess the strength of association. The random-effects model was applied, addressing heterogeneity and publication bias. RESULTS: A total of 19 articles involving 100,083 cases and 163,894 controls were included. An overall random-effects per-allele OR of 1.09 (95% CI: 1.06-1.12; P = 4.5 × 10(-8 and 1.09 (95% CI: 1.05-1.12; P = 4.2 × 10(-7 was found for the rs10941679 and rs4415084 polymorphism respectively. Significant results were found in Asians and Caucasians when stratified by ethnicity; whereas no significant associations were found among Africans/African-Americans. Similar results were also observed using dominant or recessive genetic models. In addition, we find both rs4415084 and rs10941679 conferred significantly greater risks of ER-positive breast cancer than of ER-negative tumors. CONCLUSIONS: Our findings demonstrated that rs10941679-G allele and rs4415084-T allele might be risk-conferring factors for the development of breast cancer, especially in Caucasians and East-Asians.

  2. Mouse models of intestinal inflammation and cancer.

    Science.gov (United States)

    Westbrook, Aya M; Szakmary, Akos; Schiestl, Robert H

    2016-09-01

    Chronic inflammation is strongly associated with approximately one-fifth of all human cancers. Arising from combinations of factors such as environmental exposures, diet, inherited gene polymorphisms, infections, or from dysfunctions of the immune response, chronic inflammation begins as an attempt of the body to remove injurious stimuli; however, over time, this results in continuous tissue destruction and promotion and maintenance of carcinogenesis. Here, we focus on intestinal inflammation and its associated cancers, a group of diseases on the rise and affecting millions of people worldwide. Intestinal inflammation can be widely grouped into inflammatory bowel diseases (ulcerative colitis and Crohn's disease) and celiac disease. Long-standing intestinal inflammation is associated with colorectal cancer and small-bowel adenocarcinoma, as well as extraintestinal manifestations, including lymphomas and autoimmune diseases. This article highlights potential mechanisms of pathogenesis in inflammatory bowel diseases and celiac disease, as well as those involved in the progression to associated cancers, most of which have been identified from studies utilizing mouse models of intestinal inflammation. Mouse models of intestinal inflammation can be widely grouped into chemically induced models; genetic models, which make up the bulk of the studied models; adoptive transfer models; and spontaneous models. Studies in these models have lead to the understanding that persistent antigen exposure in the intestinal lumen, in combination with loss of epithelial barrier function, and dysfunction and dysregulation of the innate and adaptive immune responses lead to chronic intestinal inflammation. Transcriptional changes in this environment leading to cell survival, hyperplasia, promotion of angiogenesis, persistent DNA damage, or insufficient repair of DNA damage due to an excess of proinflammatory mediators are then thought to lead to sustained malignant transformation. With

  3. 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.

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

    Science.gov (United States)

    Parisot, John P; Thorne, Heather; Fellowes, Andrew; Doig, Ken; Lucas, Mark; McNeil, John J; Doble, Brett; Dobrovic, Alexander; John, Thomas; James, Paul A; Lipton, Lara; Ashley, David; Hayes, Theresa; McMurrick, Paul; Richardson, Gary; Lorgelly, Paula; Fox, Stephen B; Thomas, David M

    2015-01-01

    "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. PMID:26529019

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

    Science.gov (United States)

    Parisot, John P.; Thorne, Heather; Fellowes, Andrew; Doig, Ken; Lucas, Mark; McNeil, John J.; Doble, Brett; Dobrovic, Alexander; John, Thomas; James, Paul A.; Lipton, Lara; Ashley, David; Hayes, Theresa; McMurrick, Paul; Richardson, Gary; Lorgelly, Paula; Fox, Stephen B.; Thomas, David M.

    2015-01-01

    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. PMID:26529019

  6. Antiangiogenic cancer drug using the zebrafish model.

    Science.gov (United States)

    Santoro, Massimo M

    2014-09-01

    The process of de novo vessel formation, called angiogenesis, is essential for tumor progression and spreading. Targeting of molecular pathways involved in such tumor angiogenetic processes by using specific drugs or inhibitors is important for developing new anticancer therapies. Drug discovery remains to be the main focus for biomedical research and represents the essence of antiangiogenesis cancer research. To pursue these molecular and pharmacological goals, researchers need to use animal models that facilitate the elucidation of tumor angiogenesis mechanisms and the testing of antiangiogenic therapies. The past few years have seen the zebrafish system emerge as a valid model organism to study developmental angiogenesis and, more recently, as an alternative vertebrate model for cancer research. In this review, we will discuss why the zebrafish model system has the advantage of being a vertebrate model equipped with easy and powerful transgenesis as well as imaging tools to investigate not only physiological angiogenesis but also tumor angiogenesis. We will also highlight the potential of zebrafish for identifying antitumor angiogenesis drugs to block tumor development and progression. We foresee the zebrafish model as an important system that can possibly complement well-established mouse models in cancer research to generate novel insights into the molecular mechanism of the tumor angiogenesis. PMID:24903092

  7. 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.

  8. Alternate service delivery models in cancer genetic counseling: a mini-review

    Directory of Open Access Journals (Sweden)

    Adam Hudson Buchanan

    2016-05-01

    Full Text Available Demand for cancer genetic counseling has grown rapidly in recent years as germline genomic information has become increasingly incorporated into cancer care and the field has entered the public consciousness through high-profile celebrity publications. Increased demand and existing variability in the availability of trained cancer genetics clinicians place a priority on developing and evaluating alternate service delivery models for genetic counseling. This mini-review summarizes the state of science regarding service delivery models such as telephone counseling, telegenetics and group counseling. Research on comparative effectiveness of these models in traditional individual, in-person genetic counseling has been promising for improving access to care in a manner acceptable to patients. Yet, it has not fully evaluated the short- and long-term patient- and system-level outcomes that will help answer the question of whether these models achieve the same beneficial psychosocial and behavioral outcomes as traditional cancer genetic counseling. We propose a research agenda focused on comparative effectiveness of available service delivery models and how to match models to patients and practice settings. Only through this rigorous research can clinicians and systems find the optimal balance of clinical quality, ready and secure access to care, and financial sustainability. Such research will be integral to achieving the promise of genomic medicine in oncology.

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

    Science.gov (United States)

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

    2016-01-01

    Demand for cancer genetic counseling has grown rapidly in recent years as germline genomic information has become increasingly incorporated into cancer care, and the field has entered the public consciousness through high-profile celebrity publications. Increased demand and existing variability in the availability of trained cancer genetics clinicians place a priority on developing and evaluating alternate service delivery models for genetic counseling. This mini-review summarizes the state of science regarding service delivery models, such as telephone counseling, telegenetics, and group counseling. Research on comparative effectiveness of these models in traditional individual, in-person genetic counseling has been promising for improving access to care in a manner acceptable to patients. Yet, it has not fully evaluated the short- and long-term patient- and system-level outcomes that will help answer the question of whether these models achieve the same beneficial psychosocial and behavioral outcomes as traditional cancer genetic counseling. We propose a research agenda focused on comparative effectiveness of available service delivery models and how to match models to patients and practice settings. Only through this rigorous research can clinicians and systems find the optimal balance of clinical quality, ready and secure access to care, and financial sustainability. Such research will be integral to achieving the promise of genomic medicine in oncology. PMID:27242960

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

    Science.gov (United States)

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

    2016-01-01

    Demand for cancer genetic counseling has grown rapidly in recent years as germline genomic information has become increasingly incorporated into cancer care, and the field has entered the public consciousness through high-profile celebrity publications. Increased demand and existing variability in the availability of trained cancer genetics clinicians place a priority on developing and evaluating alternate service delivery models for genetic counseling. This mini-review summarizes the state of science regarding service delivery models, such as telephone counseling, telegenetics, and group counseling. Research on comparative effectiveness of these models in traditional individual, in-person genetic counseling has been promising for improving access to care in a manner acceptable to patients. Yet, it has not fully evaluated the short- and long-term patient- and system-level outcomes that will help answer the question of whether these models achieve the same beneficial psychosocial and behavioral outcomes as traditional cancer genetic counseling. We propose a research agenda focused on comparative effectiveness of available service delivery models and how to match models to patients and practice settings. Only through this rigorous research can clinicians and systems find the optimal balance of clinical quality, ready and secure access to care, and financial sustainability. Such research will be integral to achieving the promise of genomic medicine in oncology.

  11. Genetic profiles of gastroesophageal cancer: combined analysis using expression array and tiling array--comparative genomic hybridization

    DEFF Research Database (Denmark)

    Jönsson, Mats; Isinger-Ekstrand, Anna; Johansson, Jan; Ohlsson, Mattias; Francis, Princy; Staaf, Johan; Jönsson, Mats; Borg, Ake; Nilbert, Mef

    2010-01-01

    We aimed to characterize the genomic profiles of adenocarcinomas in the gastroesophageal junction in relation to cancers in the esophagus and the stomach. Profiles of gains/losses as well as gene expression profiles were obtained from 27 gastroesophageal adenocarcinomas by means of 32k high-resol...

  12. Data Mining on Survival Prediction after Chemotherapy for Diffuse Large-B-Cell Lymphoma and Genomics of Metastasis Cancer

    Directory of Open Access Journals (Sweden)

    Shen Lu

    2014-12-01

    Full Text Available This research pertains to the applications of data mining of microarray databases for large-B-cell Lymphoma and metastasis cancer, the latter of which little has been known about the genomic events that regulate the transformation of a tumor into a metastatic phenotype.

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

    DEFF Research Database (Denmark)

    Michailidou, Kyriaki; Beesley, Jonathan; Lindstrom, Sara;

    2015-01-01

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

  14. Genomic prediction and genomic variance partitioning of daily and residual feed intake in pigs using Bayesian Power Lasso models

    DEFF Research Database (Denmark)

    Do, Duy Ngoc; Janss, L. L. G.; Strathe, Anders Bjerring;

    Improvement of feed efficiency is essential in pig breeding and selection for reduced residual feed intake (RFI) is an option. The study applied Bayesian Power LASSO (BPL) models with different power parameter to investigate genetic architecture, to predict genomic breeding values, and to partition...... genomic variance for RFI and daily feed intake (DFI). A total of 1272 Duroc pigs had both genotypic and phenotypic records for these traits. Significant SNPs were detected on chromosome 1 (SSC 1) and SSC 14 for RFI and on SSC 1 for DFI. BPL models had similar accuracy and bias as GBLUP method but use of...

  15. Integrative genomic analyses reveal an androgen-driven somatic alteration landscape in early-onset prostate cancer.

    Science.gov (United States)

    Weischenfeldt, Joachim; Simon, Ronald; Feuerbach, Lars; Schlangen, Karin; Weichenhan, Dieter; Minner, Sarah; Wuttig, Daniela; Warnatz, Hans-Jörg; Stehr, Henning; Rausch, Tobias; Jäger, Natalie; Gu, Lei; Bogatyrova, Olga; Stütz, Adrian M; Claus, Rainer; Eils, Jürgen; Eils, Roland; Gerhäuser, Clarissa; Huang, Po-Hsien; Hutter, Barbara; Kabbe, Rolf; Lawerenz, Christian; Radomski, Sylwester; Bartholomae, Cynthia C; Fälth, Maria; Gade, Stephan; Schmidt, Manfred; Amschler, Nina; Haß, Thomas; Galal, Rami; Gjoni, Jovisa; Kuner, Ruprecht; Baer, Constance; Masser, Sawinee; von Kalle, Christof; Zichner, Thomas; Benes, Vladimir; Raeder, Benjamin; Mader, Malte; Amstislavskiy, Vyacheslav; Avci, Meryem; Lehrach, Hans; Parkhomchuk, Dmitri; Sultan, Marc; Burkhardt, Lia; Graefen, Markus; Huland, Hartwig; Kluth, Martina; Krohn, Antje; Sirma, Hüseyin; Stumm, Laura; Steurer, Stefan; Grupp, Katharina; Sültmann, Holger; Sauter, Guido; Plass, Christoph; Brors, Benedikt; Yaspo, Marie-Laure; Korbel, Jan O; Schlomm, Thorsten

    2013-02-11

    Early-onset prostate cancer (EO-PCA) represents the earliest clinical manifestation of prostate cancer. To compare the genomic alteration landscapes of EO-PCA with "classical" (elderly-onset) PCA, we performed deep sequencing-based genomics analyses in 11 tumors diagnosed at young age, and pursued comparative assessments with seven elderly-onset PCA genomes. Remarkable age-related differences in structural rearrangement (SR) formation became evident, suggesting distinct disease pathomechanisms. Whereas EO-PCAs harbored a prevalence of balanced SRs, with a specific abundance of androgen-regulated ETS gene fusions including TMPRSS2:ERG, elderly-onset PCAs displayed primarily non-androgen-associated SRs. Data from a validation cohort of > 10,000 patients showed age-dependent androgen receptor levels and a prevalence of SRs affecting androgen-regulated genes, further substantiating the activity of a characteristic "androgen-type" pathomechanism in EO-PCA. PMID:23410972

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

    OpenAIRE

    Lan, Qing; Hsiung, Chao A.; Matsuo, Keitaro; Hong, Yun-Chul; Seow, Adeline; Wang, Zhaoming; Hosgood, H Dean; Chen, Kexin; Wang, Jiu-Cun; Chatterjee, Nilanjan; Hu, Wei; Wong, Maria Pik; Zheng, Wei; Caporaso, Neil; PARK, JAE YONG

    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 China, South Korea, Japan, Singapore, Taiwan, and Hong Kong. We genotyped the most promising variants (associated at P < 5 × 10-6) in an additional 1,099 cases and 2,913 controls. We identified three...

  17. Regularized multivariate regression for identifying master predictors with application to integrative genomics study of breast cancer

    OpenAIRE

    PENG, JIE; Zhu, Ji; Bergamaschi, Anna; Han, Wonshik; Noh, Dong-Young; Pollack, Jonathan R; Wang, Pei

    2010-01-01

    In this paper, we propose a new method remMap -- REgularized Multivariate regression for identifying MAster Predictors -- for fitting multivariate response regression models under the high-dimension-low-sample-size setting. remMap is motivated by investigating the regulatory relationships among different biological molecules based on multiple types of high dimensional genomic data. Particularly, we are interested in studying the influence of DNA copy number alterations on RNA transcript level...

  18. Paired ductal carcinoma in situ and invasive breast cancer lesions in the D-loop of the mitochondrial genome indicate a cancerization field effect.

    Science.gov (United States)

    Maggrah, Andrea; Robinson, Kerry; Creed, Jennifer; Wittock, Roy; Gehman, Ken; Gehman, Teresa; Brown, Helen; Harbottle, Andrew; Froberg, M Kent; Klein, Daniel; Reguly, Brian; Parr, Ryan

    2013-01-01

    Alterations in the mitochondrial genome have been chronicled in most solid tumors, including breast cancer. The intent of this paper is to compare and document somatic mitochondrial D-loop mutations in paired samples of ductal carcinoma in situ (DCIS) and invasive breast cancer (IBC) indicating a potential breast ductal epithelial cancerization field effect. Paired samples of these histopathologies were laser-captured microdissected (LCM) from biopsy, lumpectomy, and mastectomy tissues. Blood samples were collected as germplasm control references. For each patient, hypervariable region 1 (HV1) in the D-loop portion of the mitochondrial genome (mtGenome) was sequenced for all 3 clinical samples. Specific parallel somatic heteroplasmic alterations between these histopathologies, particularly at sites 16189, 16223, 16224, 16270, and 16291, suggest the presence of an epithelial, mitochondrial cancerization field effect. These results indicate that further characterization of the mutational pathway of DCIS and IBC may help establish the invasive potential of DCIS. Moreover, this paper indicates that biofluids with low cellularity, such as nipple aspirate fluid and/or ductal lavage, warrant further investigation as early and minimally invasive detection mediums of a cancerization field effect within breast tissue. PMID:23509716

  19. Whole genome comparative analysis of channel catfish (Ictalurus punctatus) with four model fish species

    OpenAIRE

    Jiang, Yanliang; Gao, Xiaoyu; Liu, Shikai; Zhang, Yu; Liu, Hong; Sun, Fanyue; Bao, Lisui; Waldbieser, Geoff; Liu, Zhanjiang

    2013-01-01

    Background Comparative mapping is a powerful tool to study evolution of genomes. It allows transfer of genome information from the well-studied model species to non-model species. Catfish is an economically important aquaculture species in United States. A large amount of genome resources have been developed from catfish including genetic linkage maps, physical maps, BAC end sequences (BES), integrated linkage and physical maps using BES-derived markers, physical map contig-specific sequences...

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

    DEFF Research Database (Denmark)

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

    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...... the previous studies, which would account for some of the remaining risk. We therefore conducted a time- and cost-effective stage 1 GWAS on 342 invasive serous cases and 643 controls genotyped on pooled DNA using the high-density Illumina 1M-Duo array. We followed up 20 of the most significantly...... associated SNPs, which are not well tagged by the lower density arrays used by the published GWAS, and genotyping them on individual DNA. Most of the top 20 SNPs were clearly validated by individually genotyping the samples used in the pools. However, none of the 20 SNPs replicated when tested for...