|Publication Type||Journal Article|
|Year of Publication||2015|
|Authors||Seashore-Ludlow, B, Rees, MG, Cheah, JH, Cokol, M, Price, EV, Coletti, ME, Jones, V, Bodycombe, NE, Soule, CK, Gould, J, Alexander, B, Li, A, Montgomery, P, Wawer, MJ, Kuru, N, Kotz, JD, C Hon, S-Y, Munoz, B, Liefeld, T, Dančík, V, Bittker, JA, Palmer, M, Bradner, JE, Shamji, AF, Clemons, PA, Schreiber, SL|
|Date Published||2015 Nov|
|Keywords||Antineoplastic Agents, Cell Line, Tumor, Cell Proliferation, Cell Survival, Cluster Analysis, Computational Biology, Datasets as Topic, Dose-Response Relationship, Drug, Drug Resistance, Neoplasm, Drug Screening Assays, Antitumor, Drug Synergism, Gene Expression Regulation, Neoplastic, Humans, Mutation, Neoplasms, Protein Kinase Inhibitors, Small Molecule Libraries|
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.
|Alternate Journal||Cancer Discov|
|PubMed Central ID||PMC4631646|
|Grant List|| / / Howard Hughes Medical Institute / United States |
RC2 CA148399 / CA / NCI NIH HHS / United States
U01 CA176152 / CA / NCI NIH HHS / United States
U01CA176152 / CA / NCI NIH HHS / United States