Abstract
Background: Ovarian cancer remains the most lethal gynecological cancer, primarily due to its asymptomatic nature in early stages and consequent late diagnosis. Early detection improves survival, but current biomarkers lack sensitivity and specificity. Cell-free DNA (cfDNA) released from tumor cells captures tumor-associated epigenetic alterations and represents a promising source for minimally invasive biomarkers. Among these, aberrant DNA methylation occurs early in tumorigenesis and may reflect underlying disease biology. This study aimed to investigate genome-wide cfDNA methylation profiles in patients with ovarian cancer, benign ovarian conditions, and healthy controls to identify cancer-associated methylation patterns that may inform future biomarker development. Results: We performed genome-wide cfDNA methylation profiling using cell-free methylated DNA immunoprecipitation sequencing (cfMeDIP-seq) on plasma samples from 40 patients with high-grade serous ovarian carcinoma, 38 patients with benign ovarian conditions, and 38 healthy postmenopausal women. A total of 536 differentially methylated regions (DMRs) were identified between ovarian cancer and controls (n = 76), with 97% showing hypermethylation in ovarian cancer. DMRs were enriched in CpG islands and gene bodies and depleted in repetitive elements, consistent with known cancer-associated methylation patterns. Fifteen genes showed robust hypermethylation across analyses. These genes exhibited methylation across intronic, exonic, and upstream regulatory regions. Separate comparisons of ovarian cancer to each control group (benign and healthy) supported the reproducibility of these findings. Gene Ontology enrichment analysis revealed enrichment in gland development, embryonic morphogenesis, and endocrine regulation, suggesting biological relevance to ovarian tumorigenesis. Conclusions: This study identifies consistent cfDNA hypermethylation patterns in ovarian cancer, affecting genes involved in developmental regulation and hormone-related processes. Our findings underscore the potential of cfMeDIP-seq for detecting tumor-specific methylation signatures in plasma and highlight these 15 hypermethylated genes as biologically relevant targets for future studies on cfDNA methylation in ovarian cancer.