Abstract 4408: CRISPR/Cas9 knockout and AI-based drug screening for novel gene targets in ovarian cancer chemoresistance
Authors: Jinjiang Wang, Jiaxi Li, Jiao Liu, Kit-Ying Chan, Ho-Sze Lee, Zhewei Zhang, Joseph Kwong, Tat-San Lau, Chi-Chiu Wang
Journal: Cancer Research (2025)

Introduction: Ovarian cancer, characterized by its heterogeneity and resistance to conventional therapies such as cisplatin (CDDP), presents a significant clinical challenge. To address these challenges, we combined genome-scale CRISPR/Cas9 knockout screening, single-cell-CRISPR Purterb RNA sequencing (scRNA-seq), and AI-driven virtual screening to identify novel chemoresistance mechanisms and evaluate potential therapeutic strategies. This integrated approach aims to reveal genetic determinants and actionable therapeutic targets to improve treatment outcomes. Methods: We performed genome-scale CRISPR/Cas9 knockout screening in ovarian cancer cell lines treated with CDDP, erastin, and a combination of elesclomol and copper (ES+Cu), identifying genes involved in drug resistance mechanisms. Differential gene candidates will be prioritized based on its strong association with resistance across the drug treatments. AI-based virtual screening will be employed to identify novel drugs targeting the candidates. Additionally, surviving cells from drug treatments will be subjected to scRNA-seq to reveal distinct cell cluster harboring resistance-related gene signatures. We also established ovarian cancer cell lines resistant to CDDP, erastin, and ES+Cu to validate the therapeutic targets and efficacy of the repurposed drugs in both resistant and wild-type cell lines. Results: CRISPR screening identified several key genes associated with drug resistance, with YTHDC2 emerging as a central target. Pathway analysis highlighted its role in regulating survival and proliferation in the context of drug-induced stress. AI-driven virtual screening pinpointed Proguanil, Calcipotriol, and Sildenafil as high-affinity binders to YTHDC2, suggesting their potential as targeted therapeutics. scRNA-seq analysis of resistant cancer cells identified key gene cluster with GADD45A and ZFAS1 associated with cisplatin resistance. Gene Ontology and STRING pathway analyses revealed their involvement in DNA damage response and apoptosis regulation. Drug-response assays demonstrated that Proguanil, Calcipotriol, and Sildenafil effectively suppressed cell proliferation in the resistant cell lines. These findings support their potential to overcome the chemotherapy resistance. Conclusion: This study integrates CRISPR-based screening, scRNA-seq, and virtual screening to provide the first comprehensive framework for addressing drug resistance in ovarian cancer. The identification of YTHDC2 as a key resistance-related gene and the validation of Proguanil, Calcipotriol, and Sildenafil as potential therapeutics underscore the translational potential. These findings offer new avenues for precision oncology, with the goal of improving outcomes for ovarian cancer patients. Citation Format: Jinjiang Wang, Jiaxi Li, Jiao Liu, Kit-Ying Chan, Ho-Sze Lee, Zhewei Zhang, Joseph Kwong, Tat-San Lau, Chi-Chiu Wang. CRISPR/Cas9 knockout and AI-based drug screening for novel gene targets in ovarian cancer chemoresistance [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 4408.