Whole-genome DNA methylation analysis reveals distinct subtype characteristics in epithelial ovarian cancer

Epithelial ovarian cancer (EOC) is characterized by high mortality, insidious onset, and pronounced heterogeneity, underscoring the critical need for effective biomarkers for early detection and subtype-specific diagnosis. While DNA methylation represents a stable epigenetic marker, prior studies have largely relied on profiling techniques with limited genomic coverage and have often overlooked subtype-specific differences essential for guiding treatment decisions. To address this, we performed whole-genome bisulfite sequencing on 44 normal ovarian tissues and 89 EOC tissues encompassing all five histological subtypes, integrated with transcriptome sequencing, to comprehensively evaluate the diagnostic and prognostic utility of DNA methylation across EOC subtypes. Our analyses revealed that genome-wide methylation profiles effectively distinguished normal from tumor tissues and captured the substantial heterogeneity inherent to EOC. Differentially methylated regions (DMRs) and differentially expressed genes were enriched in immune-related processes and epithelial differentiation, aligning with the increased proportions of epithelial and immune cells identified through deconvolution analysis. Subtype-specific DMRs further implicated hormonal pathways in endometrioid (EC) and clear cell (CCOC) carcinomas, and linked mucinous ovarian cancer (MOC) to fluid regulation. Integrative analysis of DMRs and cellular composition indicated that epithelial cells in high-grade serous (HG), low-grade serous (LG), and EC tumors most closely resembled fallopian tube, ovarian, and endometrial epithelial cells, respectively, whereas MOC and CCOC epithelial cells showed similarity to gastrointestinal and renal epithelia. Moreover, weighted gene co-expression network analysis identified epithelia-associated DMRs that achieved up to 90% specificity for subtype classification in internal validation and demonstrated prognostic relevance in independent public datasets. In conclusion, the subtype-specific DNA methylation markers identified in this study accurately reflect the distinct histological features of each EOC subtype and hold promise for application in subtype classification and prognosis prediction, thereby providing a scientific foundation for future clinical interventions in EOC.