Abstract 5341: Data mining of PubChem bioassay data reveals OXPHOS inhibitors with anti-cancer activity

Abstract

Abstract High Grade Serous Ovarian Cancer (HGSOC) is a fatal disease that is typically detected at an advanced stage when there are limited modalities for effective treatment. Treatment efficacy against cancer is dependent on tumor metabolism and its adaptation for most therapies. Warburg effect is an important adaptation found in tumors where cells primarily catabolize glucose even in presence of sufficient oxygen and nutrients. Nevertheless, recent evidence suggests cells in tumor microenvironments remain dependent on mitochondrial ATP production via oxidative phosphorylation (OXPHOS). OXPHOS also represents a major metabolic pathway in cancer stem cells and tumor cells of relapse patients. Molecular signatures of glycolysis and OXPHOS are both detected in tumors. This points to the OXPHOS pathway as a potential therapeutic target in cancer. Here we apply a data mining approach to identify OXPHOS inhibitors to evaluate as candidates for therapies against HGSOC. High-Throughput Screening (HTS) on mechanistic targets like OXPHOS are cost prohibitive for academic laboratories. As an alternative, we deployed a data mining pipeline to find active chemical classes among 8415 available OXPHOS-related bioassays in the PubChem data repository. Active compound clusters frequently contain α,β-unsaturated carbonyl groups, which are also observed in both endogenous quinone electron carriers and atovaquone–a potent inhibitor of OXPHOS. Out of 312041 unique compounds tested in the assays, we selected 6 representative molecules from each of the 6 largest active chemical clusters to test for OXPHOS inhibition, ROS production, and reduced cancer cell proliferation. We assayed cell viability (MTT) to check for proliferation of human (OVCAR3, OVCAR5, OVISE) and mouse (ID8) ovarian cancer cells against 6 compounds, Oryzalin, Allylyestrenol, Esbiothrin, Lacidipine, Coumatetralyl, and CID929419 (MLS000713029), 72 h post treatment. ID8 and OVCAR5 significantly decreased cell proliferation after Lacidipine and Oryzalin treatment. Significant increase in intracellular ROS, a frequent consequence of OXPHOS inhibition, was observed in all cell lines after Lacidipine treatment. Elevated ROS was also observed in ID8 and OVISE cells after Esbiothrin treatment. To confirm OXPHOS inhibition as the mechanism of action, we performed Mito Stress Test on the Seahorse Analyzer and measured Oxygen Consumption Rate. Treatment with Oryzalin, Allylyestrenol, Esbiothrin, and Lacidipine significantly decreased basal respiration rate and ATP production in ID8 and OVCAR3 cells. This suggests that 4 of the 6 compound classes prioritized by the data mining pipeline inhibits OXPHOS in ovarian cancer cells. Thus, our pipeline provides an efficient alternative to HTS for identifying OXPHOS inhibitors. Next, we plan to test the in-vivo efficacy of these drugs against ovarian tumors in a mouse model and investigate their molecular mechanisms. Citation Format: Sejal T. Sharma, Liping Feng, Nicha Boonpattrawong, Lisa M. Barroilhet, Manish Patankar, Spencer S. Ericksen. Data mining of PubChem bioassay data reveals OXPHOS inhibitors with anti-cancer activity. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 5341.