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Defining a Cancer Dependency Map.

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.
PMID
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Authors

Mayor MeshTerms
Keywords

RNAi screens

cancer dependencies

cancer targets

genetic vulnerabilities

genomic biomarkers

precision medicine

predictive modeling

seed effects

shRNA

Journal Title cell
Publication Year Start




PMID- 28753430
OWN - NLM
STAT- MEDLINE
DA  - 20170728
DCOM- 20170808
LR  - 20170808
IS  - 1097-4172 (Electronic)
IS  - 0092-8674 (Linking)
VI  - 170
IP  - 3
DP  - 2017 Jul 27
TI  - Defining a Cancer Dependency Map.
PG  - 564-576.e16
LID - S0092-8674(17)30651-7 [pii]
LID - 10.1016/j.cell.2017.06.010 [doi]
AB  - 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.
CI  - Copyright (c) 2017 Elsevier Inc. All rights reserved.
FAU - Tsherniak, Aviad
AU  - Tsherniak A
AD  - Broad Institute of Harvard and MIT, 415 Main Street, Cambridge, MA, USA.
FAU - Vazquez, Francisca
AU  - Vazquez F
AD  - Broad Institute of Harvard and MIT, 415 Main Street, Cambridge, MA, USA;
      Dana-Farber Cancer Institute, 450 Brookline Avenue, Boston, MA, USA.
FAU - Montgomery, Phil G
AU  - Montgomery PG
AD  - Broad Institute of Harvard and MIT, 415 Main Street, Cambridge, MA, USA.
FAU - Weir, Barbara A
AU  - Weir BA
AD  - Broad Institute of Harvard and MIT, 415 Main Street, Cambridge, MA, USA;
      Dana-Farber Cancer Institute, 450 Brookline Avenue, Boston, MA, USA.
FAU - Kryukov, Gregory
AU  - Kryukov G
AD  - Broad Institute of Harvard and MIT, 415 Main Street, Cambridge, MA, USA;
      Dana-Farber Cancer Institute, 450 Brookline Avenue, Boston, MA, USA.
FAU - Cowley, Glenn S
AU  - Cowley GS
AD  - Broad Institute of Harvard and MIT, 415 Main Street, Cambridge, MA, USA.
FAU - Gill, Stanley
AU  - Gill S
AD  - Broad Institute of Harvard and MIT, 415 Main Street, Cambridge, MA, USA;
      Dana-Farber Cancer Institute, 450 Brookline Avenue, Boston, MA, USA.
FAU - Harrington, William F
AU  - Harrington WF
AD  - Broad Institute of Harvard and MIT, 415 Main Street, Cambridge, MA, USA.
FAU - Pantel, Sasha
AU  - Pantel S
AD  - Broad Institute of Harvard and MIT, 415 Main Street, Cambridge, MA, USA.
FAU - Krill-Burger, John M
AU  - Krill-Burger JM
AD  - Broad Institute of Harvard and MIT, 415 Main Street, Cambridge, MA, USA.
FAU - Meyers, Robin M
AU  - Meyers RM
AD  - Broad Institute of Harvard and MIT, 415 Main Street, Cambridge, MA, USA.
FAU - Ali, Levi
AU  - Ali L
AD  - Broad Institute of Harvard and MIT, 415 Main Street, Cambridge, MA, USA.
FAU - Goodale, Amy
AU  - Goodale A
AD  - Broad Institute of Harvard and MIT, 415 Main Street, Cambridge, MA, USA.
FAU - Lee, Yenarae
AU  - Lee Y
AD  - Broad Institute of Harvard and MIT, 415 Main Street, Cambridge, MA, USA.
FAU - Jiang, Guozhi
AU  - Jiang G
AD  - Broad Institute of Harvard and MIT, 415 Main Street, Cambridge, MA, USA.
FAU - Hsiao, Jessica
AU  - Hsiao J
AD  - Broad Institute of Harvard and MIT, 415 Main Street, Cambridge, MA, USA.
FAU - Gerath, William F J
AU  - Gerath WFJ
AD  - Broad Institute of Harvard and MIT, 415 Main Street, Cambridge, MA, USA.
FAU - Howell, Sara
AU  - Howell S
AD  - Broad Institute of Harvard and MIT, 415 Main Street, Cambridge, MA, USA.
FAU - Merkel, Erin
AU  - Merkel E
AD  - Broad Institute of Harvard and MIT, 415 Main Street, Cambridge, MA, USA.
FAU - Ghandi, Mahmoud
AU  - Ghandi M
AD  - Broad Institute of Harvard and MIT, 415 Main Street, Cambridge, MA, USA.
FAU - Garraway, Levi A
AU  - Garraway LA
AD  - Broad Institute of Harvard and MIT, 415 Main Street, Cambridge, MA, USA;
      Dana-Farber Cancer Institute, 450 Brookline Avenue, Boston, MA, USA; Department
      of Medicine, Brigham and Women's Hospital, 75 Francis Street, Boston, MA, USA;
      Harvard Medical School, 25 Shattuck Street, Boston, MA, USA; Howard Hughes
      Medical Institute, 4000 Jones Bridge Road, Chevy Chase, MD, USA.
FAU - Root, David E
AU  - Root DE
AD  - Broad Institute of Harvard and MIT, 415 Main Street, Cambridge, MA, USA.
FAU - Golub, Todd R
AU  - Golub TR
AD  - Broad Institute of Harvard and MIT, 415 Main Street, Cambridge, MA, USA;
      Dana-Farber Cancer Institute, 450 Brookline Avenue, Boston, MA, USA; Harvard
      Medical School, 25 Shattuck Street, Boston, MA, USA; Howard Hughes Medical
      Institute, 4000 Jones Bridge Road, Chevy Chase, MD, USA.
FAU - Boehm, Jesse S
AU  - Boehm JS
AD  - Broad Institute of Harvard and MIT, 415 Main Street, Cambridge, MA, USA.
FAU - Hahn, William C
AU  - Hahn WC
AD  - Broad Institute of Harvard and MIT, 415 Main Street, Cambridge, MA, USA;
      Dana-Farber Cancer Institute, 450 Brookline Avenue, Boston, MA, USA; Department
      of Medicine, Brigham and Women's Hospital, 75 Francis Street, Boston, MA, USA;
      Harvard Medical School, 25 Shattuck Street, Boston, MA, USA. Electronic address: 
      [email protected]
LA  - eng
PT  - Journal Article
PL  - United States
TA  - Cell
JT  - Cell
JID - 0413066
RN  - 0 (Ubiquitin)
SB  - IM
MH  - Cell Line, Tumor
MH  - Humans
MH  - Neoplasms/*genetics/*pathology
MH  - RNA Interference
MH  - Software
MH  - Ubiquitin/genetics
OTO - NOTNLM
OT  - RNAi screens
OT  - cancer dependencies
OT  - cancer targets
OT  - genetic vulnerabilities
OT  - genomic biomarkers
OT  - precision medicine
OT  - predictive modeling
OT  - seed effects
OT  - shRNA
EDAT- 2017/07/29 06:00
MHDA- 2017/08/09 06:00
CRDT- 2017/07/29 06:00
PHST- 2017/01/12 [received]
PHST- 2017/04/09 [revised]
PHST- 2017/06/07 [accepted]
AID - S0092-8674(17)30651-7 [pii]
AID - 10.1016/j.cell.2017.06.010 [doi]
PST - ppublish
SO  - Cell. 2017 Jul 27;170(3):564-576.e16. doi: 10.1016/j.cell.2017.06.010.