Integrative cancer pharmacogenomics to establish drug mechanism of action: drug repurposing

Accelerating drug discovery and repurposing by combining transcriptional signature connectivity with docking

We present an in silico approach for drug discovery, dubbed connectivity enhanced structure activity relationship (ceSAR). Building on the landmark LINCS library of transcriptional signatures of drug-like molecules and gene knockdowns, ceSAR combines cheminformatic techniques with signature concordance analysis to connect small molecules and their targets and further assess their biophysical compatibility using molecular docking. Candidate compounds are first ranked in a target structure-independent manner, using chemical similarity to LINCS analogs that exhibit transcriptomic concordance with a target gene knockdown. Top candidates are subsequently rescored using docking simulations and machine learning-based consensus of the two approaches. Using extensive benchmarking, we show that ceSAR greatly reduces false-positive rates, while cutting run times by multiple orders of magnitude and further democratizing drug discovery pipelines. We further demonstrate the utility of ceSAR by identifying and experimentally validating inhibitors of BCL2A1, an important antiapoptotic target in melanoma and preterm birth-associated inflammation.

Recent Advances in Cancer Drug Discovery Through the Use of Phenotypic Reporter Systems, Connectivity Mapping, and Pooled CRISPR Screening

Multi-omic approaches offer an unprecedented overview of the development, plasticity, and resistance of cancer. However, the translation from anti-cancer compounds identified in vitro to clinically active drugs have a notoriously low success rate. Here, we review how technical advances in cell culture, robotics, computational biology, and development of reporter systems have transformed drug discovery, enabling screening approaches tailored to clinically relevant functional readouts (e.g., bypassing drug resistance). Illustrating with selected examples of “success stories,” we describe the process of phenotype-based high-throughput drug screening to target malignant cells or the immune system. Second, we describe computational approaches that link transcriptomic profiling of cancers with existing pharmaceutical compounds to accelerate drug repurposing. Finally, we review how CRISPR-based screening can be applied for the discovery of mechanisms of drug resistance and sensitization. Overall, we explore how the complementary strengths of each of these approaches allow them to transform the paradigm of pre-clinical drug development.

Targeting the cell cycle in breast cancer: towards the next phase

Deregulation of the cell cycle is a hallmark of cancer that enables limitless cell division. To support this malignant phenotype, cells acquire molecular alterations that abrogate or bypass control mechanisms in signaling pathways and cellular checkpoints that normally function to prevent genomic instability and uncontrolled cell proliferation. Consequently, therapeutic targeting of the cell cycle has long been viewed as a promising anti-cancer strategy. Until recently, attempts to target the cell cycle for cancer therapy using selective inhibitors have proven unsuccessful due to intolerable toxicities and a lack of target specificity. However, improvements in our understanding of malignant cell-specific vulnerabilities has revealed a therapeutic window for preferential targeting of the cell cycle in cancer cells, and has led to the development of agents now in the clinic. In this review, we discuss the latest generation of cell cycle targeting anti-cancer agents for breast cancer, including approved CDK4/6 inhibitors, and investigational TTK and PLK4 inhibitors that are currently in clinical trials. In recognition of the emerging population of ER+ breast cancers with acquired resistance to CDK4/6 inhibitors we suggest new therapeutic avenues to treat these patients. We also offer our perspective on the direction of future research to address the problem of drug resistance, and discuss the mechanistic insights required for the successful implementation of these strategies.

The circadian gene Nr1d1 in the mouse nucleus accumbens modulates sociability and anxiety-related behaviour

Nuclear receptor subfamily 1, group D, member 1 (Nr1d1) (also known as Rev-erb alpha) has been linked to circadian rhythm regulation, mood-related behaviour and disorders associated with social deficits. Recent work from our laboratory found striking decreases in Nr1d1 in the nucleus accumbens (NAc) in the maternal condition and indirect evidence that Nr1d1 was interacting with numerous addiction and reward-related genes to modulate social reward. In this study, we applied our insights from the maternal state to nonparental adult mice to determine whether decreases in Nr1d1 expression in the NAc via adeno-associated viral (AAV) vectors and short hairpin RNA (shRNA)-mediated gene knockdown were sufficient to modulate social behaviours and mood-related behaviours. Knockdown of Nr1d1 in the NAc enhanced sociability and reduced anxiety, but did not affect depressive-like traits in female mice. In male mice, Nr1d1 knockdown had no significant behavioural effects. Microarray analysis of Nr1d1 knockdown in females identified changes in circadian rhythm and histone deacetylase genes and suggested possible drugs, including histone deacetylase inhibitors, that could mimic actions of Nr1d1 knockdown. Quantitative real-time PCR (qPCR) analysis confirmed expression upregulation of gene period circadian clock 1 (Per1) and period circadian clock 2 (Per2) with Nr1d1 knockdown. The evidence for roles for opioid-related genes opioid receptor, delta 1 (Oprd1) and preproenkephalin (Penk) was also found. Together, these results suggest that Nr1d1 in the NAc modulates sociability and anxiety-related behaviour in a sex-specific manner, and circadian, histone deacetylase and opioid-related genes may be involved in the expression of these behavioural phenotypes.