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Abstract 5455: Integrative analysis of the Cancer Cell Line Encyclopedia reveals genetic and transcriptional predictors of compound sensitivity

Authors :
Vic Meyer
Jodi Meltzer
Lauren Murray
William R. Sellers
Giordano Caponigro
Robert Schlegel
Laura E. MacConaill
Peter Finan
Jennifer L. Harris
Sungjoon Kim
John Che
Dmitriy Sonkin
Scott Mahan
Michael D. Jones
Supriya Gupta
Pichai Raman
Nanxin Li
Christine D. Wilson
Jared L. Nedzel
Nicolas Stransky
Kavitha Venkhatesan
Adam Callahan
Kristin G. Ardlie
Jill P. Mesirov
Ted Liefeld
Levi A. Garraway
Matthew Meyerson
Adam Margolin
Gad Getz
Michael R. Reich
Barbara L. Weber
Lili Niu
Reid M. Pinchback
Todd R. Golub
Carrie Sougnez
Robert C. Onofrio
Andrew I. Su
Aaron Shipway
Wendy Winckler
Ingo H. Engels
Gregory V. Kryukov
Joseph Thibault
Michael F. Berger
Michael Morrissey
Markus Warmuth
Charlie Hatton
Emanuele Palescandolo
Paula Morais
Jordi Barretina
John Monahan
Source :
Cancer Research. 71:5455-5455
Publication Year :
2011
Publisher :
American Association for Cancer Research (AACR), 2011.

Abstract

Comprehensive genomic characterization of cancer is proceeding at a rapidly accelerating pace, mainly due to the expanded use of massively parallel sequencing. Despite the promise of cancer genomics, many cancer drugs still fail in the clinic due to nonresponsive patients and this translates into a significant unmet medical need. Accurate predictions of which patients are more likely to respond to drugs in development could speed clinical trials and personalize treatments. Here we propose the use of a compendium of experimentally tractable cancer model systems, ∼1000 human genomically-annotated cancer cell lines (at the level of gene expression, DNA copy number alterations and mutations), coupled with pharmacological profiling, to systematically link genetic and transcriptional features to drug response. This resource, the Cancer Cell Line Encyclopedia (CCLE), is available online at www.broadinstitute.org/ccle. Through computational predictive modeling we have both rediscovered molecular features that predict response to several drugs and also uncovered a number of novel potential biomarkers of sensitivity and resistance to targeted agents and chemotherapy drugs. For instance, we have found that response to topoisomerase 1 inhibitors seem to be driven by expression of a single gene. We have also observed that tissue lineage is a key predictor for sensitivity to certain compounds, providing rationale for clinical trials of these drugs in particular cancer types. Our cell line-based platform provides a valuable tool for the development of personalized cancer medicine, revealing critical tumor dependencies and helping to stratify patients for clinical trials. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 5455. doi:10.1158/1538-7445.AM2011-5455

Details

ISSN :
15387445 and 00085472
Volume :
71
Database :
OpenAIRE
Journal :
Cancer Research
Accession number :
edsair.doi...........921107a14f00b4f9f5d0776d7a220d7f
Full Text :
https://doi.org/10.1158/1538-7445.am2011-5455