Computation-based drug repositioning approaches that automatically search vast amounts of genomic-chemical-phenotypic data for tens of thousands of drugs and diseases 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 High-grade serous ovarian cancer (HGSOC) have not been undertaken. Using a novel computational drug-repositioning platform (Drug-Predict) with HGSOC gene expression dataset from The Cancer Genome Atlas (TCGA) as the input, we have uncovered that Non-steroidal anti-inflammatory drugs (NSAIDs) could be potential candidates for Drug repositioning in HGSOC. Given that numerous epidemiological studies have shown that regular intake of NSAIDs in women is associated with decreased incidence of ovarian cancer, we assessed whether NSAIDs could have chemo-adjuvant applications in HGSOC and have identified Indomethacin as a novel chemo-adjuvant in HGSOC.

Indomethacin decreased survival of primary HGSOC tumor cells and interestingly, cisplatin resistant ovarian tumor cells (derived from primary HGSOC PDX models) exhibited significantly higher cell death upon Indomethacin treatment suggesting that Indomethacin could exert chemo-adjuvant effects in HGSOC. Accordingly, Indomethacin treatment induced chemo-sensitivity in cisplatin resistant HGSOC tumor cells and combo treatment with Indomethacin and cisplatin exerted synergistic cell death as compared to individual drugs alone. Furthermore, Indomethacin decreased stem-like properties and induced chemo-sensitivity in ALDHhigh cisplatin-resistant tumor-initiating cells (TICs) thus suggesting that the chemo-adjuvant effect of the drug is mediated by decrease in TIC properties in HGSOC cells. Mechanistically, we found that Indomethacin inhibits Wnt/β-catenin signaling by degrading β-catenin and β-catenin modulation inversely affected Indomethacin functioning in HGSOC.

Our study is the first report describing functional effects of an NSAID in patient-derived HGSOC models and demonstrates that combining novel computational predictions with experimental validation has potential in identifying viable drug candidates and moving them into patient trials efficiently and cost-effectively. Since NSAIDs are in routine clinical use in gynecological settings and have acceptable safety profile, this discovery provides with a potentially rapid and cost-effective translational opportunity for testing NSAIDs as chemo-adjuvants in patient trials in HGSOC.

Citation Format: Anil Belur Nagaraj, QuanQiu Wang, Olga Kovalenko, Peronne Joseph, Yang Chen, Rong Xu and Analisa DiFeo. PHARMACOLOGIC ANALYSIS OF HIGH–GRADE SEROUS OVARIAN CANCER TCGA DATASET IDENTIFIES A NOVEL CHEMO–ADJUVANT ROLE FOR NON–STEROIDAL ANTI–INFLAMMATORY DRUGS (NSAIDS) [abstract]. In: Proceedings of the 11th Biennial Ovarian Cancer Research Symposium; Sep 12-13, 2016; Seattle, WA. Philadelphia (PA): AACR; Clin Cancer Res 2017;23(11 Suppl):Abstract nr NTOC-081.