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Cell DOI:10.1016/j.cell.2017.06.010

Defining a Cancer Dependency Map.

Publication TypeJournal Article
Year of Publication2017
AuthorsTsherniak, A, Vazquez, F, Montgomery, PG, Weir, BA, Kryukov, G, Cowley, GS, Gill, S, Harrington, WF, Pantel, S, Krill-Burger, JM, Meyers, RM, Ali, L, Goodale, A, Lee, Y, Jiang, G, Hsiao, J, Gerath, WFJ, Howell, S, Merkel, E, Ghandi, M, Garraway, LA, Root, DE, Golub, TR, Boehm, JS, Hahn, WC
JournalCell
Volume170
Issue3
Pages564-576.e16
Date Published2017 Jul 27
ISSN1097-4172
KeywordsCell Line, Tumor, Humans, Neoplasms, RNA Interference, Software, Ubiquitin
Abstract

Most human epithelial tumors harbor numerous alterations, making it difficult to predict which genes are required for tumor survival. To systematically identify cancer dependencies, we analyzed 501 genome-scale loss-of-function screens performed in diverse human cancer cell lines. We developed DEMETER, an analytical framework that segregates on- from off-target effects of RNAi. 769 genes were differentially required in subsets of these cell lines at a threshold of six SDs from the mean. We found predictive models for 426 dependencies (55%) by nonlinear regression modeling considering 66,646 molecular features. Many dependencies fall into a limited number of classes, and unexpectedly, in 82% of models, the top biomarkers were expression based. We demonstrated the basis behind one such predictive model linking hypermethylation of the UBB ubiquitin gene to a dependency on UBC. Together, these observations provide a foundation for a cancer dependency map that facilitates the prioritization of therapeutic targets.

DOI10.1016/j.cell.2017.06.010
Pubmed

http://www.ncbi.nlm.nih.gov/pubmed/28753430?dopt=Abstract

Alternate JournalCell
PubMed ID28753430
PubMed Central IDPMC5667678
Grant ListP01 CA203655 / CA / NCI NIH HHS / United States
U01 CA199253 / CA / NCI NIH HHS / United States
R01 CA130988 / CA / NCI NIH HHS / United States
U01 CA176058 / CA / NCI NIH HHS / United States
U54 CA112962 / CA / NCI NIH HHS / United States