American Association for Cancer Research
21598290cd110224-sup-stab_2_xls_55k.xls (38.5 kB)

Supplementary Table 2 from Essential Gene Profiles in Breast, Pancreatic, and Ovarian Cancer Cells

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posted on 2023-04-03, 20:27 authored by Richard Marcotte, Kevin R. Brown, Fernando Suarez, Azin Sayad, Konstantina Karamboulas, Paul M. Krzyzanowski, Fabrice Sircoulomb, Mauricio Medrano, Yaroslav Fedyshyn, Judice L.Y. Koh, Dewald van Dyk, Bohdana Fedyshyn, Marianna Luhova, Glauber C. Brito, Franco J. Vizeacoumar, Frederick S. Vizeacoumar, Alessandro Datti, Dahlia Kasimer, Alla Buzina, Patricia Mero, Christine Misquitta, Josee Normand, Maliha Haider, Troy Ketela, Jeffrey L. Wrana, Robert Rottapel, Benjamin G. Neel, Jason Moffat

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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. Cancer Discovery; 2(2); 172–89. © 2011 AACR.This article is highlighted in the In This Issue feature, p. 95.