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).

Summary The high rate of clinical response to protein kinase-targeting drugs matched to cancer patients with specific genomic alterations has prompted efforts to use cancer cell-line (CCL) profiling to identify additional biomarkers of small-molecule sensitivities. We have quantitatively measured the sensitivity of 242 genomically characterized CCLs to an Informer Set of 354 small molecules that target many nodes in cell circuitry, uncovering protein dependencies that: 1) associate with specific cancer-genomic alterations and 2) can be targeted by small molecules. We have created the Cancer Therapeutics Response Portal (www.broadinstitute.org/ctrp) to enable users to correlate genetic features to sensitivity in individual lineages and control for confounding factors of CCL profiling. We report a candidate dependency, associating activating mutations in the oncogene β-catenin with sensitivity to the Bcl2-family antagonist, navitoclax. The resource can be used to develop novel therapeutic hypotheses and accelerate discovery of drugs matched to patients by their cancer genotype and lineage.

Using a diverse collection of small molecules generated from a variety of sources, we measured protein-binding activities of each individual compound against each of 100 diverse (sequence-unrelated) proteins using small-molecule microarrays. We also analyzed structural features, including complexity, of the small molecules. We found that compounds from different sources (commercial, academic, natural) have different protein-binding behaviors and that these behaviors correlate with general trends in stereochemical and shape descriptors for these compound collections. Increasing the content of sp 3 -hybridized and stereogenic atoms relative to compounds from commercial sources, which comprise the majority of current screening collections, improved binding selectivity and frequency. The results suggest structural features that synthetic chemists can target when synthesizing screening collections for biological discovery. Because binding proteins selectively can be a key feature of high-value probes and drugs, synthesizing compounds having features identified in this study may result in improved performance of screening collections. S mall-molecule probe-and drug-discovery activities in academia and the pharmaceutical industry often begin with highthroughput screening. Many thousands of small molecules are tested with the expectation that each has potential as a discovery lead. Thus, assembling or synthesizing compound collections for small-molecule screening represents an important step in discovery success, particularly when selecting among compounds from a variety of synthetic and natural sources. Unbiased methods to evaluate the assay performance of compounds from different sources, and to relate performance to chemical structure (defined by computed structural properties) (1, 2), can provide guidance to one element of more valuable small-molecule screening collections.Comparative analyses between compounds often involve cheminformatic analysis of compound structures (3-5) or retrospective analysis of compound performance by mining the literature (6-8) or historical data (9, 10). For example, intermediate molecular complexity has been suggested as theoretically preferable for drug leads (11), and this relationship is supported by evidence mined from historical data (9). In this study, we performed unbiased comparisons of compounds from natural and synthetic sources by first identifying compounds with unknown activities and then exposing them to a common assay platform. We identified a compound collection comprising three subsets: (i) 6,152 compounds from commercial sources that are representative of many common screening collections (commercial compounds; CC); (ii) 6,623 compounds assembled from the academic synthetic chemistry community using, e.g., diversity-oriented synthesis (diverse compounds; DC); and (iii) 2,477 naturally occurring compounds (natural products; NP). We then (i) analyzed distributions of stereochemical and shape complexity for each set;(ii) measured protein-binding activities of each membe...