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

Brinton Seashore-Ludlow1, Matthew G Rees1, Jaime H Cheah1

  • 1Center for the Science of Therapeutics, Broad Institute, Cambridge, Massachusetts.

Cancer Discovery
|October 21, 2015
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Summary

Researchers identified genetic features linked to cancer cell drug response using a large dataset and new analysis methods. This work advances precision medicine by uncovering new therapeutic targets and updating the Cancer Therapeutic Response Portal.

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Area of Science:

  • Oncology
  • Genomics
  • Pharmacology

Background:

  • Precision cancer medicine relies on identifying genetic alterations that predict therapeutic response.
  • Cancer cell-line (CCL) profiling offers an unbiased approach to link CCL features with drug sensitivity.

Purpose of the Study:

  • To explore associations between small molecules and CCLs using a quantitative sensitivity dataset.
  • To uncover mechanisms of action and genomic features correlating with CCL drug response.

Main Methods:

  • Developed annotated cluster multidimensional enrichment analysis.
  • Analyzed a new, large quantitative sensitivity dataset of cancer cell lines and small molecules.
  • Updated the Cancer Therapeutic Response Portal (CTRP v2).

Main Results:

  • Recapitulated known drug-response relationships and identified novel ones.
  • Discovered new associations for KRAS-mutant cancers and neuroblastoma.
  • Revealed insights into small-molecule mechanisms and predictive genomic features.

Conclusions:

  • Presented the largest CCL sensitivity dataset to date.
  • Developed a robust analysis method for identifying drug response predictors.
  • Enhanced the CTRP to facilitate cancer research and hypothesis generation.