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Using a novel computational drug-repositioning approach (DrugPredict) to rapidly identify potent drug candidates for cancer treatment
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Using a novel computational drug-repositioning approach (DrugPredict) to rapidly identify potent drug candidates for cancer treatment
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Journal Article
Using a novel computational drug-repositioning approach (DrugPredict) to rapidly identify potent drug candidates for cancer treatment
2018
Overview
Computation-based drug-repurposing/repositioning approaches can greatly speed up the traditional drug discovery process. To date, systematic and comprehensive computation-based approaches to identify and validate drug-repositioning candidates for epithelial ovarian cancer (EOC) have not been undertaken. Here, we present a novel drug discovery strategy that combines a computational drug-repositioning system (DrugPredict) with biological testing in cell lines in order to rapidly identify novel drug candidates for EOC. DrugPredict exploited unique repositioning opportunities rendered by a vast amount of disease genomics, phenomics, drug treatment, and genetic pathway and uniquely revealed that non-steroidal anti-inflammatories (NSAIDs) rank just as high as currently used ovarian cancer drugs. As epidemiological studies have reported decreased incidence of ovarian cancer associated with regular intake of NSAIDs, we assessed whether NSAIDs could have chemoadjuvant applications in EOC and found that (i) NSAID Indomethacin induces robust cell death in primary patient-derived platinum-sensitive and platinum- resistant ovarian cancer cells and ovarian cancer stem cells and (ii) downregulation of β-catenin is partially driving effects of Indomethacin in cisplatin-resistant cells. In summary, we demonstrate that DrugPredict represents an innovative computational drug- discovery strategy to uncover drugs that are routinely used for other indications that could be effective in treating various cancers, thus introducing a potentially rapid and cost-effective translational opportunity. As NSAIDs are already in routine use in gynecological treatment regimens and have acceptable safety profile, our results will provide with a rationale for testing NSAIDs as potential chemoadjuvants in EOC patient trials.
Publisher
Nature Publishing Group UK,Nature Publishing Group
Subject
/ 13/31
/ 38/1
/ 38/39
/ 96/106
/ Analysis
/ Animals
/ Anti-Inflammatory Agents, Non-Steroidal - pharmacology
/ Anti-Inflammatory Agents, Non-Steroidal - therapeutic use
/ Carcinoma, Ovarian Epithelial
/ Chemotherapy, Adjuvant - methods
/ Computational Biology - methods
/ Drug Repositioning - methods
/ Female
/ Humans
/ Indomethacin - therapeutic use
/ Medicine
/ Mice
/ Neoplasms, Glandular and Epithelial - drug therapy
/ Neoplasms, Glandular and Epithelial - epidemiology
/ Neoplasms, Glandular and Epithelial - genetics
/ Nonsteroidal anti-inflammatory drugs
/ Oncology
/ Ovarian Neoplasms - drug therapy
/ Ovarian Neoplasms - epidemiology
/ Ovarian Neoplasms - genetics
/ Platinum
/ Sequence Homology, Nucleic Acid
