Epigenetic Mechanisms and Clinical Translation in Ovarian Cancer: From Molecular Pathways to Precision Therapy
Synopsis
This review systematically examines how DNA methylation, histone modifications, chromatin remodeling, and non-coding RNA networks drive chemoresistance and recurrence in ovarian cancer, summarizes clinical trial results of epigenetic agents (DNMT, HDAC, and EZH2 inhibitors) combined with PARP inhibitors or immunotherapy, and reviews biomarker advances based on circulating cfDNA methylation, circulating miRNAs, and AI-based liquid biopsy platforms, proposing a precision oncology framework for patient stratification and real-time monitoring of chemoresistance.
Epigenetic drivers of ovarian cancer progression, tumor plasticity, and chemotherapy resistance Epigenetic drivers of ovarian cancer progression, tumor plasticity, and chemotherapy resistance. Aberrant DNA methylation, histone modifications, and dysregulated ncRNAs cooperatively remodel transcriptional programs that govern DNA repair, apoptosis, EMT, stemness, and survival signaling. These alterations promote epigenetic plasticity and adaptive cell-state transitions, leading to the emergence of cancer stem-like cells and drug-tolerant persister populations. Persistence of these adaptive states contributes to MRD, intratumoral heterogeneity, platinum resistance, PARP inhibitor resistance, tumor recurrence, and metastatic progression. The therapeutic intervention layer highlights major epigenetic strategies, including DNMT, HDAC, and EZH2 inhibitors, as well as miRNA-based therapies and combination approaches with PARP inhibitors or immunotherapy, which may reverse resistance-associated chromatin states and restore treatment sensitivity.
PubMedInterpretation
The review proposes that epigenetic plasticity is a central driver of chemoresistance and recurrence in ovarian cancer: tumor cells can transition into drug-tolerant, stem-like states without permanent genetic changes, leading to minimal residual disease and eventual relapse. Unlike prior resistance models focused on genetic mutations, this work integrates DNA methylation, histone modifications, and ncRNA networks to emphasize reversible chromatin state transitions as the source of resistant phenotypes. Based on synthesis of multiple studies including variable methylation states of BRCA1 and MLH1, EZH2-mediated H3K27me3 silencing, and HDAC6 dependency in ARID1A-mutant tumors, representing narrative review-level evidence integration.
The review explicitly distinguishes BRCA1/2 genetic mutations, BRCA1 promoter methylation, and functional homologous recombination deficiency (HRD), noting their different clinical implications: epigenetic silencing may initially confer sensitivity to platinum and PARP inhibitors, while demethylation or restoration of DNA repair capacity may lead to acquired resistance. Distinguishes three commonly conflated concepts at the clinical decision-making level, providing a mechanistic framework for explaining relapse after initial response. Based on synthesis of multiple studies on the relationship between BRCA1 promoter methylation and platinum response, representing mechanistic discussion rather than a single trial conclusion.
The review summarizes clinical translation evidence for epigenetic agents: azacitidine plus carboplatin in platinum-resistant epithelial ovarian cancer achieved an overall response rate of 13.8% and median PFS of 3.7 months; decitabine priming followed by carboplatin achieved a 35% response rate and 10.2 months PFS in recurrent disease, accompanied by demethylation of MLH1, BRCA1, and HOXA11 promoters; DNMT inhibitor combined with PARP inhibitor reported median PFS of 19.1 months versus 5.5 months in the control arm. Consolidates scattered early-phase clinical trial data and emphasizes that these values should be viewed as biological activity signals rather than confirmed efficacy. From multiple Phase I/II small-cohort, single-arm, or non-biomarker-enriched trials, with the authors themselves cautioning about interpretation.
The review outlines advances in epigenetic biomarkers and AI liquid biopsy: an 11-gene plasma methylation panel achieved 79% sensitivity and 96% specificity; the ZNF154 cfDNA methylation EpiClass classifier achieved 91.7% sensitivity and 100% specificity; exosomal miR-1290 combined with CA-125 achieved AUC close to 0.97; AI-assisted cfDNA methylation analysis reported 100% sensitivity and 72–100% specificity. Juxtaposes methylation panels, circulating miRNAs, and AI multi-omics platforms to outline a technical roadmap for non-invasive diagnosis and real-time monitoring of chemoresistance. From multiple independent validation cohort studies, though the authors note that AI metrics may be affected by cohort size, case-control design, and lack of external validation.
Perspective
This article addresses epigenetic mechanisms and clinical translation in ovarian cancer (particularly epithelial ovarian cancer), intended for researchers and clinicians interested in resistance mechanisms, epigenetic drug trial design, and liquid biopsy biomarkers. Its framework provides a roadmap for biomarker-enriched trials, epigenetic state stratification, and dynamic cfDNA monitoring, but the cited efficacy data for epigenetic agents largely come from early-phase small-sample trials and require Phase II/III validation.
Readers should still watch: whether efficacy signals of epigenetic agents can be confirmed in biomarker-enriched randomized trials; analytical standardization, threshold setting, and cross-laboratory reproducibility of cfDNA methylation and circulating miRNA assays; performance of AI-assisted diagnostic metrics in diverse populations and prospective designs; and open questions regarding delivery, specificity, and long-term chromatin stability of CRISPR/dCas9 epigenome editing.