Harnessing Connectivity in a Large-Scale Small-Molecule Sensitivity Dataset

Brinton Seashore‐Ludlow(Broad Institute), Matthew G. Rees(Broad Institute), Jaime H. Cheah(Broad Institute), Murat Cokol(Sabancı Üniversitesi), Edmund V. Price(Broad Institute), Matthew E. Coletti(Broad Institute), Victor Jones(Broad Institute), Nicole E. Bodycombe(Broad Institute), Christian K. Soule(Broad Institute), Joshua Gould(Broad Institute), Benjamin Alexander(Broad Institute), Ava Li(Broad Institute), Philip Montgomery(Broad Institute), Mathias J. Wawer(Broad Institute), Nurdan Kuru(Sabancı Üniversitesi), Joanne Kotz(Broad Institute), C. Suk-Yee Hon(Broad Institute), Benito Muñoz(Broad Institute), Ted Liefeld(Broad Institute), Vlado Dančík(Broad Institute), Joshua A. Bittker(Broad Institute), Michelle Palmer(Broad Institute), James E. Bradner(Broad Institute), Alykhan F. Shamji(Broad Institute), Paul A. Clemons(Broad Institute), Stuart L. Schreiber(Broad Institute)
Cancer Discovery
October 19, 2015
Cited by 884Open Access
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Abstract

UNLABELLED: Identifying genetic alterations that prime a cancer cell to respond to a particular therapeutic agent can facilitate the development of precision cancer medicines. Cancer cell-line (CCL) profiling of small-molecule sensitivity has emerged as an unbiased method to assess the relationships between genetic or cellular features of CCLs and small-molecule response. Here, we developed annotated cluster multidimensional enrichment analysis to explore the associations between groups of small molecules and groups of CCLs in a new, quantitative sensitivity dataset. This analysis reveals insights into small-molecule mechanisms of action, and genomic features that associate with CCL response to small-molecule treatment. We are able to recapitulate known relationships between FDA-approved therapies and cancer dependencies and to uncover new relationships, including for KRAS-mutant cancers and neuroblastoma. To enable the cancer community to explore these data, and to generate novel hypotheses, we created an updated version of the Cancer Therapeutic Response Portal (CTRP v2). SIGNIFICANCE: We present the largest CCL sensitivity dataset yet available, and an analysis method integrating information from multiple CCLs and multiple small molecules to identify CCL response predictors robustly. We updated the CTRP to enable the cancer research community to leverage these data and analyses.


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