365. METHYLATION BIOMARKERS TO STRATIFY BARRETT’S ESOPHAGUS PATIENTS PROGRESSING AND NON-PROGRESSING TO ESOPHAGEAL ADENOCARCINOMA

Abstract Background Over the last forty years, North America and Europe have witnessed a notable surge in cases of esophageal adenocarcinoma (EAC). This malignancy typically arises from Barrett esophagus (BE), a condition characterized by the replacement of normal squamous epithelium with specialized metaplastic cells. Our study aims to identify specific methylation markers capable of distinguishing between BE patients that will and will not progress to EAC. Methods We conducted differential expression analysis on RNASeq public dataset GSE210647 to distinguish BE progressors from non-progressors. Reads were aligned to hg38 genome using STAR aligner, normalized and analyzed with DESeq2. Significant genes were selected by |log2 fold change| ≥ 0.2 and padj < 0.01. GO, pathway enrichment, and transcription factor (TF) network analyses were performed to uncover biological disparities. Integration with previous methylation data (N.R. Dehkordi et al., 292. Specific methylation markers associated with changes in gene expression distinguish EAC and sub-types of BE patients, ISDE 2023) allowed the identification of overlapping biomarkers, aiding in better discrimination between the two groups. Results Differential expression analysis of GSE210647 identified 2261 significative DEGs between BE progressors and non-progressors. Pathway enrichment analysis in BE progressors revealed significant associations with cellular morphogenesis and reprogramming, alongside the induction of the bile acid pathway, known for its implications in invasiveness and cancer stem cell expansion. TF network analysis identified key regulators such as TBX20, FOXS1, and ZNF454, shedding light on their roles in esophageal carcinogenesis. Among the 505 CpG markers acquired in prior analyses, 127 genomic regions were linked with overexpressed genes either in progressors or in non-progressors BE patients. Leveraging this marker panel, BE samples were stratified into discrete subtypes, aligning either with normal esophageal tissue or EAC, and suggesting a potential stratification by disease progression. Conclusions The integration of expression and methylation analyses allows the identification of key genomic and epigenomic loci able to distinguish BE patients progressing or not-progressing towards EAC. The identified biomarkers are pivotal for personalized risk assessment and for the design of targeted interventions, holding promises for enhanced surveillance protocols, refined early EAC detection approaches, and improved therapeutic strategies aimed at mitigating the risk of EAC development in BE population.