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Cancer Discov. 2015 Nov;5(11):1210-23. doi: 10.1158/2159-8290.CD-15-0235. Epub 2015 Oct 19.

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

Author information

1
Center for the Science of Therapeutics, Broad Institute, Cambridge, Massachusetts.
2
Faculty of Engineering and Natural Sciences, Sabanci University, Istanbul, Turkey.
3
Center for the Science of Therapeutics, Broad Institute, Cambridge, Massachusetts. Cancer Biology and Medical Oncology, Harvard Medical School, Boston, Massachusetts.
4
Center for the Science of Therapeutics, Broad Institute, Cambridge, Massachusetts. pclemons@broadinstitute.org stuart_schreiber@harvard.edu ashamji@broadinstitute.org.

Abstract

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.

PMID:
26482930
PMCID:
PMC4631646
DOI:
10.1158/2159-8290.CD-15-0235
[Indexed for MEDLINE]
Free PMC Article
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