bioRxiv · 10.1101/2025.09.24.678351
Targeting RAD52 overcomes PARP inhibitor resistance in preclinical Brca2-deficient ovarian cancer model
Abstract
AbstractBRCA-mutated ovarian cancer commonly develops resistance to poly (ADP-ribose) polymerase (PARP) inhibitors. Here, we investigated the DNA repair protein RAD52 as a potential target to overcome resistance. In analysis of The Cancer Genome Atlas datasets and immunohistochemistry of tissue microarrays, elevated RAD52 expression correlated with poor overall survival in patients with high-grade serous ovarian cancers. We tested two PARP inhibitor-resistant Brca2-deficient mouse ovarian cancer models, ID8-OR and HGS2-OR. HGS2- OR cells had higher RAD52 expression than parental lines. Rad52 knockout or knockdown restored PARP inhibitor sensitivity in both models. In syngeneic mice, ID8-OR cells in which Rad52 was knocked out yielded lower tumor burden and longer overall survival than control cells. Rad52 depletion impaired single-strand annealing and homologous recombination and led to accumulation of DNA double-strand breaks after PARP inhibitor treatment. RNA sequencing demonstrated that PARP inhibitor treatment induced Polq expression in Brca2- and Rad52-deficient cells, suggesting a switch to microhomology-mediated end joining. Finally, the RAD52 inhibitor D-I03 synergized with a PARP inhibitor to reduce cell viability and tumor burden and prolong survival. Collectively, our findings establish RAD52 as a promising therapeutic target to overcome PARP inhibitor resistance in BRCA2-mutated ovarian cancer and offer mechanistic insights to inform future clinical strategies.
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Ota, Y., Gupta, V., Fashemi, B. E., Akande, M., Babu, P., Thuthika, P., Elizagaray, M. L., Sun, L., Sanders, B., Kuroki, L. M., McCourt, C. K., Hagemann, A. R., Hagemann, I. S., Thaker, P. H., Mutch, D. G., Powell, M. A., Hyrc, K., Verma, P., Krais, J., Bitler, B. G., Mullen, M. M., Khabele, D.. 2025-09-26. Targeting RAD52 overcomes PARP inhibitor resistance in preclinical Brca2-deficient ovarian cancer model. https://doi.org/10.1101/2025.09.24.678351
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