Identifying and targeting cancer dependencies with small molecules
Several protein kinase-targeting drugs are yielding high
clinical response rates when matched to cancer patients
with specific genomic alterations in their cancers. Several
other cancer drugs yield similarly high response rates
within a particular cancer lineage. These clinical successes
have prompted our efforts to identify more systematically
additional genetic and lineage context-dependent small-molecule sensitivities.
We have generated a novel ‘Informer Set’ of small-molecule probes and drugs that each selectively target a distinct node in cell circuitry and that collectively modulate a broad array of cell processes. By profiling the impact of this small-molecule collection on a panel of cancer cell lines for which extensive genetic characterizations are publicly available, we have generated a dataset that can be used to identify comprehensively relationships between genetic and lineage features of human cancer cell lines and small-molecule sensitivities.
The Cancer Therapeutics Response Portal v1 provides open access to the results obtained through quantitatively measuring the sensitivity of 242 genetically characterized cancer-cell lines to a 354-member ‘Informer Set’ of small-molecule probes and drugs. Statistically significant correlations identified between the genetic and lineage features of the cell lines and small-molecule sensitivities are accessible through the portal. With this dataset, users can mine for genetic correlations in a lineage-specific context and control for potential confounding factors. We anticipate continuing to expand the dataset in the portal, providing a living resource for the cancer-research community. We hope that the Portal can be used to develop novel therapeutic hypotheses and to accelerate future discovery of drugs matched to patients based on their cancer genotype and lineage.
CTRP v1 lists 76,703 connections to 185 compounds at a false-discovery rate q-value cutoff of q<0.01.
- 185 compounds X 242 CCLs
- pre-computed enrichment analysis and visualizations
- filter by lineage. CCLE mutation source, confounding factors
- 76,703 significant connections (q<0.01)
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- 481 compounds X 860 CCLs
- correlations to copy-number and gene-expression data
- mutation data integrate CCLE and Sanger/MGH calls
- correlation and enrichment analysis on-the-fly
- box-whisker visualization in addition to enrichment heatmaps
- drill-down to scatter plots and concentration-response curves
- flter by lineage/subtype, growth mode