Abstract 5979: Identification of DNA methylation based prognostic subtype and signature in epithelial ovarian cancer

Abstract Background: Epithelial ovarian cancer (EOC) is a heterogeneous disease that exhibits different histological types, clinical characteristics, and molecular features. DNA methylation plays a crucial role in the development and progression of cancer and has been utilized for subtyping various tumors. This study focuses on classifying EOC based on DNA methylation and aims to characterize the disease through an integrated analysis of genomic, transcriptomic, and clinical data. Methods: Genome-wide DNA methylation profiling was performed on 137 EOC tumor tissues using Infinium MehylationEPIC array. Prognosis-related differentially methylated positions (DMPs) were identified through multivariate Cox proportional hazards regression models, and non-negative matrix factorization (NMF) approach was used to classify different subtypes. A prognosis prediction model was constructed using LASSO regression and nomogram was constructed. Results: Four methylation-based subtypes (MS1-MS4) were identified using 774 DMPs, showing significant differences in prognosis (P = 2.413 × 10-9).The MS1 group showed the best prognosis and the most favorable response to paclitaxel in combination with platinum-based chemotherapy. MS2 is characterized as an immune-excluded phenotype, while MS3 represents a metabolic subtype with a moderate prognosis as determined through differentially expressed genes and functional enrichment analysis. In contrast, MS4, recognized as a hypermethylated subtype, has the poorest prognosis and is marked by the highest methylation levels among the four subtypes. A four-DMP signature was developed to predict prognosis and methylation subtype, thereby enhancing clinical utility. Conclusion: Together, this study identified a novel molecular subtype of EOC, elucidating the heterogeneity of EOC from an epigenetic perspective and providinga new strategy for personalized treatment options for EOC patients. Citation Format: Wei Geng, Wei Liu, Lei Liu, Yuxin Chen, Dong Yang, Linqing Chai, Caiyun Huang, Lian Li. Identification of DNA methylation based prognostic subtype and signature in epithelial ovarian cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 5979.