A computational tool provides a systematic approach to determine the mechanisms of action of small molecules by examining correlations between basal gene expression and small-molecule sensitivity in cancer cell lines. Changes in cellular gene expression in response to small-molecule or genetic perturbations have yielded signatures that can connect unknown mechanisms of action (MoA) to ones previously established. We hypothesized that differential basal gene expression could be correlated with patterns of small-molecule sensitivity across many cell lines to illuminate the actions of compounds whose MoA are unknown. To test this idea, we correlated the sensitivity patterns of 481 compounds with ∼19,000 basal transcript levels across 823 different human cancer cell lines and identified selective outlier transcripts. This process yielded many novel mechanistic insights, including the identification of activation mechanisms, cellular transporters and direct protein targets. We found that ML239, originally identified in a phenotypic screen for selective cytotoxicity in breast cancer stem-like cells, most likely acts through activation of fatty acid desaturase 2 (FADS2). These data and analytical tools are available to the research community through the Cancer Therapeutics Response Portal.

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. Cancer Discov; 5(11); 1210–23. ©2015 AACR. See related commentary by Gray and Mills, p. 1130. This article is highlighted in the In This Issue feature, p. 1111

Knowledge of the full target space of bioactive substances, approved and investigational drugs as well as chemical probes, provides important insights into therapeutic potential and possible adverse effects. The existing compound-target bioactivity data resources are often incomparable due to non-standardized and heterogeneous assay types and variability in endpoint measurements. To extract higher value from the existing and future compound target-profiling data, we implemented an open-data web platform, named Drug Target Commons (DTC), which features tools for crowd-sourced compound-target bioactivity data annotation, standardization, curation, and intra-resource integration. We demonstrate the unique value of DTC with several examples related to both drug discovery and drug repurposing applications and invite researchers to join this community effort to increase the reuse and extension of compound bioactivity data.

Background Previously, we showed cancer cells rely on the MTH1 protein to prevent incorporation of otherwise deadly oxidised nucleotides into DNA and we developed MTH1 inhibitors which selectively kill cancer cells. Recently, several new and potent inhibitors of MTH1 were demonstrated to be non-toxic to cancer cells, challenging the utility of MTH1 inhibition as a target for cancer treatment. Material and methods Human cancer cell lines were exposed in vitro to MTH1 inhibitors or depleted of MTH1 by siRNA or shRNA. 8-oxodG was measured by immunostaining and modified comet assay. Thermal Proteome profiling, proteomics, cellular thermal shift assays, kinase and CEREP panel were used for target engagement, mode of action and selectivity investigations of MTH1 inhibitors. Effect of MTH1 inhibition on tumour growth was explored in BRAF V600E-mutated malignant melanoma patient derived xenograft and human colon cancer SW480 and HCT116 xenograft models. Results Here, we demonstrate that recently described MTH1 inhibitors, which fail to kill cancer cells, also fail to introduce the toxic oxidized nucleotides into DNA. We also describe a new MTH1 inhibitor TH1579, (Karonudib), an analogue of TH588, which is a potent, selective MTH1 inhibitor with good oral availability and demonstrates excellent pharmacokinetic and anti-cancer properties in vivo. Conclusion We demonstrate that in order to kill cancer cells MTH1 inhibitors must also introduce oxidized nucleotides into DNA. Furthermore, we describe TH1579 as a best-in-class MTH1 inhibitor, which we expect to be useful in order to further validate the MTH1 inhibitor concept.