Literature DB >> 22585861

Essential gene profiles in breast, pancreatic, and ovarian cancer cells.

Richard Marcotte1, Kevin R Brown2,3, Fernando Suarez1, Azin Sayad2, Konstantina Karamboulas2, Paul M Krzyzanowski1, Fabrice Sircoulomb1, Mauricio Medrano4,1, Yaroslav Fedyshyn2, Judice L Y Koh2,3, Dewald van Dyk2, Bodhana Fedyshyn2, Marianna Luhova2, Glauber C Brito3, Franco J Vizeacoumar2, Frederick S Vizeacoumar5, Alessandro Datti5,6, Dahlia Kasimer2, Alla Buzina2, Patricia Mero2, Christine Misquitta2, Josee Normand1, Maliha Haider1, Troy Ketela2,3, Jeffrey L Wrana7,5, Robert Rottapel4,1,3, Benjamin G Neel4,1, Jason Moffat2,7.   

Abstract

UNLABELLED: Genomic analyses are yielding a host of new information on the multiple genetic abnormalities associated with specific types of cancer. A comprehensive description of cancer-associated genetic abnormalities can improve our ability to classify tumors into clinically relevant subgroups and, on occasion, identify mutant genes that drive the cancer phenotype ("drivers"). More often, though, the functional significance of cancer-associated mutations is difficult to discern. Genome-wide pooled short hairpin RNA (shRNA) screens enable global identification of the genes essential for cancer cell survival and proliferation, providing a "functional genomic" map of human cancer to complement genomic studies. Using a lentiviral shRNA library targeting ~16,000 genes and a newly developed, dynamic scoring approach, we identified essential gene profiles in 72 breast, pancreatic, and ovarian cancer cell lines. Integrating our results with current and future genomic data should facilitate the systematic identification of drivers, unanticipated synthetic lethal relationships, and functional vulnerabilities of these tumor types. SIGNIFICANCE: This study presents a resource of genome-scale, pooled shRNA screens for 72 breast, pancreatic, and ovarian cancer cell lines that will serve as a functional complement to genomics data, facilitate construction of essential gene profiles, help uncover synthetic lethal relationships, and identify uncharacterized genetic vulnerabilities in these tumor types. SIGNIFICANCE: This study presents a resource of genome-scale, pooled shRNA screens for 72 breast, pancreatic, and ovarian cancer cell lines that will serve as a functional complement to genomics data, facilitate construction of essential gene profiles, help uncover synthetic lethal relationships, and identify uncharacterized genetic vulnerabilities in these tumor types. ©2011 AACR.

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Year:  2011        PMID: 22585861      PMCID: PMC5057396          DOI: 10.1158/2159-8290.CD-11-0224

Source DB:  PubMed          Journal:  Cancer Discov        ISSN: 2159-8274            Impact factor:   39.397


  79 in total

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3.  Gene expression patterns of breast carcinomas distinguish tumor subclasses with clinical implications.

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Journal:  Oncogene       Date:  2001-10-18       Impact factor: 9.867

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10.  Cancer vulnerabilities unveiled by genomic loss.

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Journal:  Cell       Date:  2012-08-17       Impact factor: 41.582

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