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Project DRIVE: A Compendium of Cancer Dependencies and Synthetic Lethal Relationships Uncovered by Large-Scale, Deep RNAi Screening.

Authors :
McDonald ER 3rd
de Weck A
Schlabach MR
Billy E
Mavrakis KJ
Hoffman GR
Belur D
Castelletti D
Frias E
Gampa K
Golji J
Kao I
Li L
Megel P
Perkins TA
Ramadan N
Ruddy DA
Silver SJ
Sovath S
Stump M
Weber O
Widmer R
Yu J
Yu K
Yue Y
Abramowski D
Ackley E
Barrett R
Berger J
Bernard JL
Billig R
Brachmann SM
Buxton F
Caothien R
Caushi JX
Chung FS
Cortés-Cros M
deBeaumont RS
Delaunay C
Desplat A
Duong W
Dwoske DA
Eldridge RS
Farsidjani A
Feng F
Feng J
Flemming D
Forrester W
Galli GG
Gao Z
Gauter F
Gibaja V
Haas K
Hattenberger M
Hood T
Hurov KE
Jagani Z
Jenal M
Johnson JA
Jones MD
Kapoor A
Korn J
Liu J
Liu Q
Liu S
Liu Y
Loo AT
Macchi KJ
Martin T
McAllister G
Meyer A
Mollé S
Pagliarini RA
Phadke T
Repko B
Schouwey T
Shanahan F
Shen Q
Stamm C
Stephan C
Stucke VM
Tiedt R
Varadarajan M
Venkatesan K
Vitari AC
Wallroth M
Weiler J
Zhang J
Mickanin C
Myer VE
Porter JA
Lai A
Bitter H
Lees E
Keen N
Kauffmann A
Stegmeier F
Hofmann F
Schmelzle T
Sellers WR
Source :
Cell [Cell] 2017 Jul 27; Vol. 170 (3), pp. 577-592.e10.
Publication Year :
2017

Abstract

Elucidation of the mutational landscape of human cancer has progressed rapidly and been accompanied by the development of therapeutics targeting mutant oncogenes. However, a comprehensive mapping of cancer dependencies has lagged behind and the discovery of therapeutic targets for counteracting tumor suppressor gene loss is needed. To identify vulnerabilities relevant to specific cancer subtypes, we conducted a large-scale RNAi screen in which viability effects of mRNA knockdown were assessed for 7,837 genes using an average of 20 shRNAs per gene in 398 cancer cell lines. We describe findings of this screen, outlining the classes of cancer dependency genes and their relationships to genetic, expression, and lineage features. In addition, we describe robust gene-interaction networks recapitulating both protein complexes and functional cooperation among complexes and pathways. This dataset along with a web portal is provided to the community to assist in the discovery and translation of new therapeutic approaches for cancer.<br /> (Copyright © 2017 Elsevier Inc. All rights reserved.)

Details

Language :
English
ISSN :
1097-4172
Volume :
170
Issue :
3
Database :
MEDLINE
Journal :
Cell
Publication Type :
Academic Journal
Accession number :
28753431
Full Text :
https://doi.org/10.1016/j.cell.2017.07.005