A combinatorial screen of the CLOUD uncovers a synergy targeting the androgen receptor

Abstract

Approved drugs are invaluable tools to study biochemical pathways, and further characterization of these compounds may lead to repurposing of single drugs or combinations. Here we describe a collection of 308 small molecules representing the diversity of structures and molecular targets of all FDA-approved chemical entities. The CeMM Library of Unique Drugs (CLOUD) covers prodrugs and active forms at pharmacologically relevant concentrations and is ideally suited for combinatorial studies. We screened pairwise combinations of CLOUD drugs for impairment of cancer cell viability and discovered a synergistic interaction between flutamide and phenprocoumon (PPC). The combination of these drugs modulates the stability of the androgen receptor (AR) and resensitizes AR-mutant prostate cancer cells to flutamide. Mechanistically, we show that the AR is a substrate for γ-carboxylation, a post-translational modification inhibited by PPC. Collectively, our data suggest that PPC could be repurposed to tackle resistance to antiandrogens in prostate cancer patients.

Repurposing screen identifies mebendazole as a clinical candidate to synergise with docetaxel for prostate cancer treatment

“…Drug repurposing may have a transformative impact on precision medicine, 21 fast-tracking novel treatment strategy using agents that would otherwise not be implicated by conventional approaches. Strategies for drug repurposing include a chemogenomic library in phenotypic screen, 22 in silico computational drug repositioning, 23 pairwise combinatorial screen of drugs against molecular targets of interest 24 and novel in vivo model systems such as zebrafish. 25 The use of cytotoxic docetaxel chemotherapy is well established in metastatic prostate cancer, but only results in a modest survival benefit.…”

Recent advances in combinatorial drug screening and synergy scoring

“…This method is amenable to high-throughput screening in vitro enabling the assessment of up to 6 different drug combinations in one 384 multi-well plate using and 8 × 8 dose matrix format. Recent studies utilized this methodology to identify combination partners to ibrutinib in hematological malignancies [ 20 ], explore novel drug combinations for Ewing Sarcoma [ 21 ] and for novel targeting approaches of androgen receptor signaling [ 22 ]. Importantly, small-scale or hypothesis-driven drug combinations can be tested in animal models of disease (e.g.…”

MatchMaker: A Deep Learning Framework for Drug Synergy Prediction

“…The data were obtained from https://drugcomb.fimm.fi/ (version v1.4, downloaded on Dec 2019). DrugComb curates highthroughput combinatorial drug screening data from four studies: (i) O'Neil dataset [21], (ii) Forcina dataset [22], (iii) NCI Almanac dataset [23], and (iv) Cloud dataset [24].…”