Joshua Bittker

An Interactive Resource to Identify Cancer Genetic and Lineage Dependencies Targeted by Small Molecules

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 (http://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 Bcl-2 family antagonist, navitoclax. The resource can be used to develop novel therapeutic hypotheses and to accelerate discovery of drugs matched to patients by their cancer genotype and lineage.

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

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.

Nucleic acid evolution and minimization by nonhomologous random recombination

We have developed a simple method for exploring nucleic acid sequence space by nonhomologous random recombination (NRR) that enables DNA fragments to randomly recombine in a length-controlled manner without the need for sequence homology. We compared the results of using NRR and error-prone PCR to evolve DNA aptamers that bind streptavidin. Starting with two parental sequences of modest avidin affinity, evolution using NRR resulted in aptamers with 15- to 20-fold higher affinity than the highest-affinity aptamers evolved using error-prone PCR, and 27- or 46-fold higher affinities than parental sequences derived using systematic evolution of ligands by exponential enrichment (SELEX). NRR also facilitates the identification of functional regions within evolved sequences. Inspection of a small number of NRR-evolved clones identified a 40-base DNA sequence, present in multiple copies in each clone, that binds streptavidin. Our findings suggest that NRR may enhance the effectiveness of nucleic acid evolution and the ease of identifying structure–activity relationships among evolved sequences.

Correlating chemical sensitivity and basal gene expression reveals mechanism of action

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.

Niche-based screening identifies small-molecule inhibitors of leukemia stem cells

Efforts to develop more effective therapies for acute leukemia may benefit from high-throughput screening systems that reflect the complex physiology of the disease, including leukemia stem cells (LSCs) and supportive interactions with the bone marrow microenvironment. The therapeutic targeting of LSCs is challenging because LSCs are highly similar to normal hematopoietic stem and progenitor cells (HSPCs) and are protected by stromal cells in vivo. We screened 14,718 compounds in a leukemia-stroma co-culture system for inhibition of cobblestone formation, a cellular behavior associated with stem-cell function. Among those compounds that inhibited malignant cells but spared HSPCs was the cholesterol-lowering drug lovastatin. Lovastatin showed anti-LSC activity in vitro and in an in vivo bone marrow transplantation model. Mechanistic studies demonstrated that the effect was on target, via inhibition of HMG-CoA reductase. These results illustrate the power of merging physiologically relevant models with high-throughput screening.

Advancing Biological Understanding and Therapeutics Discovery with Small-Molecule Probes

Small-molecule probes can illuminate biological processes and aid in the assessment of emerging therapeutic targets by perturbing biological systems in a manner distinct from other experimental approaches. Despite the tremendous promise of chemical tools for investigating biology and disease, small-molecule probes were unavailable for most targets and pathways as recently as a decade ago. In 2005, the NIH launched the decade-long Molecular Libraries Program with the intent of innovating in and broadening access to small-molecule science. This Perspective describes how novel small-molecule probes identified through the program are enabling the exploration of biological pathways and therapeutic hypotheses not otherwise testable. These experiences illustrate how small-molecule probes can help bridge the chasm between biological research and the development of medicines but also highlight the need to innovate the science of therapeutic discovery.

Toward performance-diverse small-molecule libraries for cell-based phenotypic screening using multiplexed high-dimensional profiling

Significance A large compound screening collection is usually constructed to be tested in many distinct assays, each one designed to find modulators of a different biological process. However, it is generally not known to what extent a compound collection actually contains molecules with distinct biological effects (or even any effect) until it has been tested for a couple of years. This study explores a cost-effective way of rapidly assessing the biological performance diversity of a screening collection in a single assay. By simultaneously measuring a large number of cellular features, unbiased profiling assays can distinguish compound effects with high resolution and thus measure performance diversity. We show that this approach could be used as a filtering strategy to build effective screening collections. High-throughput screening has become a mainstay of small-molecule probe and early drug discovery. The question of how to build and evolve efficient screening collections systematically for cell-based and biochemical screening is still unresolved. It is often assumed that chemical structure diversity leads to diverse biological performance of a library. Here, we confirm earlier results showing that this inference is not always valid and suggest instead using biological measurement diversity derived from multiplexed profiling in the construction of libraries with diverse assay performance patterns for cell-based screens. Rather than using results from tens or hundreds of completed assays, which is resource intensive and not easily extensible, we use high-dimensional image-based cell morphology and gene expression profiles. We piloted this approach using over 30,000 compounds. We show that small-molecule profiling can be used to select compound sets with high rates of activity and diverse biological performance.

Small-molecule inducers of insulin expression in pancreatic α-cells

High-content screening for small-molecule inducers of insulin expression identified the compound BRD7389, which caused α-cells to adopt several morphological and gene expression features of a β-cell state. Assay-performance profile analysis suggests kinase inhibition as a mechanism of action, and we show that biochemical and cellular inhibition of the RSK kinase family by BRD7389 is likely related to its ability induce a β-cell-like state. BRD7389 also increases the endocrine cell content and function of donor human pancreatic islets in culture.

Recent advances in the in vitro evolution of nucleic acids

Molecular evolution allows chemists and biologists to generate nucleic acids with tailor-made binding or catalytic activities. Recent examples of nucleic acid evolution in vitro provide insights into natural ribozyme evolution and also demonstrate potential applications of evolved DNA and RNA molecules. Efforts to expand the scope of nucleic acid evolution are also underway, including the development of novel methods for exploring nucleic acid sequence-space and the incorporation of non-natural chemical functionality into nucleic acid libraries.

The Drug Repurposing Hub: a next-generation drug library and information resource

To the Editor: Drug repurposing, the application of an existing therapeutic to a new disease indication, holds promise of rapid clinical impact at a lower cost than de novo drug development. So far, there has not been a systematic effort to identify such opportunities, limited in part by the lack of a comprehensive library of clinical compounds suitable for testing. To address this challenge, we hand-curated a collection of 4,707 compounds, experimentally confirmed their identities, and annotated them with literature-reported targets. The collection includes 3,422 drugs that are marketed around the world or that have been tested in human clinical trials. Compounds were obtained from more than 50 chemical vendors, and the purity of each sample was established. We have thus established a blueprint for others to easily assemble such a repurposing library, and we have created an online Drug Repurposing Hub (http:// www.broadinstitute.org/repurposing) that contains detailed annotation for each of the compounds. Repurposing is attractive and pragmatic, given the substantial cost and time requirements—on average, a decade or more—for drug development1. In addition, a large number of potential drugs never reach clinical testing. Moreover, fewer than 15% of compounds that enter clinical development ultimately receive approval, despite the majority of them being deemed safe2. For either approved or failed drugs for which safety has already been established, finding new indications can rapidly bring benefits to patients. Prior drug-repurposing successes span disease areas; examples include the cyclooxygenase inhibitor aspirin to treat coronary-artery disease, the phosphodiesterase inhibitor sildenafil to treat erectile dysfunction, and the antibiotic erythromycin for impaired gastric motility (Supplementary Table 1)3. Even drugs associated with troubling side effects merit reconsideration, as evidenced by the successful repurposing of the antiemetic thalidomide to treat multiple myeloma4. Risk-mediating measures for avoiding the potential teratogenicity of thalidomide and its derivatives are reasonable in patients with life-threatening cancer, whereas the use of these drugs to treat nausea remains unacceptable. Although the benefits of repurposing are clear, successes thus far have been mostly serendipitous. Systematic, large-scale repurposing efforts have not been possible owing to the lack of a definitive physical drug collection, the low quality of drug annotations, and insufficient readouts of drug activity from which new indications can be predicted. Recent technological advances have enabled a step change in our ability to assess drug activities comprehensively. For example, perturbational gene expression profiles can now be obtained at high throughput across multiple cell types5. Gene expression profiling has enabled recent repurposing discoveries, including sirolimus for glucocorticoid-resistant acute lymphocytic leukemia, topiramate for inflammatory-bowel disease, and imipramine for small-cell lung cancer. For cancer therapeutics, a recently developed assay known as PRISM, which uses barcoded cell lines, enables rapid testing of many drugs against a large number of cancer cell lines in pools6. Molecular features of the cell lines (for example, gene expression, mutation, or copy-number variation) can then be used to identify predictive biomarkers of drug sensitivity (Supplementary Table 2). Finally, morphologic changes in cells can be assessed using high-throughput microscopy and machine-learning approaches. Such imaging-based screening unexpectedly identified the cholesterol drug lovastatin as a potent inhibitor of leukemia stem cells. To take advantage of these advances in experimental methods, we sought to assemble a comprehensive library of drugs that have reached the clinic. Surprisingly, we found that no such chemical library of approved and clinical trial drugs is available for purchase. In particular, drugs that have been tested in clinical trials but did not reach approval are not readily accessible. Even obtaining a complete list of such drugs and their annotations is challenging. A prior effort led by the US National Institutes of Health (NIH) focused on drugs approved by the US Food and Drug Administration (FDA), but the library has few compounds that have yet to achieve FDA approval7. Some chemical vendors offer a subset of approved drugs, but most of these commercial libraries overlap in their content and include only a small fraction of the approximately 10,000 drugs that have reached the clinic in the United States and Europe. Given that no complete collection exists, we launched a three-step effort to create the Repurposing Library by (i) identifying and purchasing compounds; (ii) comprehensively annotating their known activities and clinical indications; and (iii) experimentally confirming drug identity and purity. We employed two approaches to identify clinical-drug structures for the Repurposing Library. First, we searched existing databases, both publicly accessible and proprietary, for clinically tested drugs and then manually integrated them to ensure sufficient drug coverage and chemical-structure reliability (Supplementary Table 3). Sources included DrugBank, the NCATS NCGC Pharmaceutical Collection (NPC), Thomson Reuters Integrity, Thomson Reuters Cortellis, and Citeline Pharmaprojects7–9. Second, we located marketed or approved ingredient lists from regulatory agencies worldwide, including the FDA. After structure standardization and the removal of duplicates, approximately 10,000 small-molecule drugs with disclosed structures were found to have reached clinical development. Most of these drugs are not widely available in commercial screening libraries. Through structure-matching (as opposed to relying on compound names), chemical suppliers were identified for 5,691 compounds (Fig. 1). Controlled substances, nonpharmaceutical substances, and redundant elemental formulations were not pursued further. To assemble the collection, we ultimately purchased 8,584 samples (representing 5,691 unique compounds) from 75 chemical vendors, at an average cost of