Abstract 4122: Epigenetic biomarker identification of each stage during the progression of prostate cancer

Abstract Prostate cancer (PCa) heterogeneity is observed both across different patients and within the same patient during the progression of his disease. Although genetic profiling alone has not fully captured these complexities, epigenetic modifications may better characterize changes in bidirectional gene regulatory programs during PCa progression. In this study, we aimed to identify epigenetic biomarkers that may distinguish each stage of the disease. We thus focused our efforts on DNA methylation, the most extensively studied epigenetic mechanism, because it enables dynamic shifts in gene expression without altering the DNA sequence, often as a result of environmental and therapeutic pressures. To achieve our goal, we selected 24 formalin-fixed paraffin-embedded (FFPE) archival PCa specimens encompassing the full disease spectrum, from normal prostate tissue to aggressive states. This cohort includes indolent (N=8), high-grade non metastatic disease (N=4), aggressive/lethal disease (N=8), and adjacent normal tissues (N=4). DNA extracted from representative tissue sections was analyzed using the Infinium Methylation EPIC v2.0 array, followed by bioinformatic analyses: following standard beta-value calling and normalization, we applied unsupervised hierarchical clustering and found that the samples of each cohort clustered together. Then, differential methylation analysis identified 629 uniquely methylated CpG sites across the disease stages (Normal: 3 hypermethylated, 214 hypomethylated; Indolent: 4 hypermethylated, 1 hypomethylated; High-grade non-aggressive: 181 hypermethylated, 51 hypomethylated; Aggressive: 22 hypermethylated, 153 hypomethylated). We next took advantage that 422 of these identified differentially methylated sites (representing 67.1%) are also represented in previous versions of the bead array platforms (Illumina 450k and EPIC v1.0 arrays) and leveraged publicly available retrieved from TCGA and GEO databases to refine our pipeline, focusing on CpG sites consistently differentially methylated across disease stages. Based on our discovery set of well-characterized PCa specimens, ongoing analyses aim to incorporate over 100 additional public datasets to identify markers that reflect disease continuum. We anticipate that functional enrichment analysis of these datasets will also reveal candidate mechanisms involved in disease progression. Ultimately, this research seeks to lay the groundwork for a marker-informed approach to monitor PCa progression, establishing a basis for proactive strategies to manage and combat prostate cancer. Citation Format: Susan (Souzana) Logotheti, Konstantinos Mesiakaris, Konstantinos Lazaros, Efthalia Kontogianni, Eleni Panopoulou, Stavros Kontogiannis, Marcos R. Estecio, Rama Soundararajan, Christopher J. Logothetis, Aristidis G. Vrahatis, Vasiliki Tzelepi. Epigenetic biomarker identification of each stage during the progression of prostate 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 4122.