Constructing an Ovarian Cancer Prognostic Model Based on Shared m6A Modifications and Cellular Senescence-Related Genes with Polycystic Ovary Syndrome

Background: Polycystic ovary syndrome (PCOS) and ovarian cancer (OV) are significant women's health concerns. This study aims to identify genes related to m6A modification and cellular senescence that are shared by PCOS and OV and to develop a prognostic model for OV outcomes. Methods: Transcriptomic datasets from GEO and TCGA were collected to identify differentially expressed genes (DEGs) associated with m6A modifications and cellular senescence in both PCOS and OV. We identified hub genes through WGCNA and assessed their prognostic significance. An OV prognostic model was developed and validated using multiple datasets, and correlations between risk scores and tumor immune microenvironment were evaluated. Drug sensitivity was predicted based on risk scores. qRT-PCR was performed to verify model gene alterations in OV cell lines. Results: We identified 73 DEGs that were common to both PCOS and OV, with eight genes associated with m6A modification and cellular senescence. WGCNA revealed 242 DEhub genes. A 19-gene prognostic model was established, exhibiting impressive efficacy with AUCs exceeding 0.7 for predicting OV patient survival. High-risk scores correlated with increased M0 macrophages and monocytes and decreased M1, CD8+ T cells, and T follicular helper cells. Drug sensitivity varied based on risk scores. Model gene alterations were verified in external OV datasets and OV cell lines. In external datasets, CXCR4 emerged as a key target gene of m6A modification. Conclusions: The derived 19-gene prognostic model offers potential avenues for risk assessment and personalized therapy in OV patients.