AUTHOR=Zhang Lanyue , Zhao Jiangnan , Su Chunyu , Wu Jianxi , Jiang Lai , Chi Hao , Wang Qin 

TITLE=Organoid models of ovarian cancer: resolving immune mechanisms of metabolic reprogramming and drug resistance

JOURNAL=Frontiers in Immunology

VOLUME=Volume 16 - 2025

YEAR=2025

URL=https://www.frontiersin.org/journals/immunology/articles/10.3389/fimmu.2025.1573686

DOI=10.3389/fimmu.2025.1573686

ISSN=1664-3224

ABSTRACT=Metabolic reprogramming is a hallmark of ovarian cancer, enabling tumor progression, immune evasion and drug resistance. The tumor microenvironment (TME) further shapes metabolic adaptations, enabling cancer cells to withstand hypoxia and nutrient deprivation. While organoid models provide a physiologically relevant platform for studying these processes, they still lack immune and vascular components, limiting their ability to fully recapitulate tumor metabolism and drug responses. In this study, we investigated the key metabolic mechanisms involved in ovarian cancer progression, focusing on glycolysis, lipid metabolism and amino acid metabolism. We integrated metabolomic analyses and drug sensitivity assays to explore metabolic-TME interactions using patient-derived, adult stem cell-derived and iPSC-derived organ tissues. Among these, we found that glycolysis, lipid metabolism and amino acid metabolism play a central role in tumor progression and chemotherapy resistance. We identified methylglyoxal (MGO)-mediated BRCA2 dysfunction as a driver of immune escape, a role for sphingolipid signaling in tumor proliferation and a role for kynurenine metabolism in CD8+ T cell suppression. In addition, PI3K/AKT/mTOR and Wnt/β-catenin pathways promote chemoresistance through metabolic adaptation. By elucidating the link between metabolic reprogramming and immune evasion, this study identifies key metabolic vulnerabilities and potential drug targets in ovarian cancer. Our findings support the development of metabolically targeted therapies and increase the utility of organoid-based precision medicine models.