The role of epigenetic regulation in pancreatic ductal adenocarcinoma progression and drug response: an integrative genomic and pharmacological prognostic prediction model.

Background: Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal malignancy with poor prognosis. Epigenetic dysregulation plays a crucial role in PDAC progression, but its comprehensive landscape and clinical implications remain unclear. Methods: We integrated single-cell RNA sequencing, bulk RNA sequencing, and clinical data from multiple public databases. Single-cell analysis was performed using Seurat and hdWGCNA packages to reveal cell heterogeneity and epigenetic features. Weighted gene co-expression network analysis (WGCNA) identified key epigenetic modules. A machine learning-based prognostic model was constructed using multiple algorithms, including Lasso and Random Survival Forest. We further analyzed mutations, immune microenvironment, and drug sensitivity associated with the epigenetic risk score. Results: Single-cell analysis revealed distinct epigenetic patterns across different cell types in PDAC. WGCNA identified key modules associated with histone modifications and DNA methylation. Our machine learning model, based on 17 epigenetic genes, showed robust prognostic value (AUC >0.7 for 1-, 3-, and 5-year survival) and outperformed existing models. High-risk patients exhibited distinct mutation patterns, including higher frequencies of KRAS and TP53 mutations. Low-risk patients showed higher immune and stromal scores, with increased infiltration of CD8 Conclusion: Our study provides a comprehensive landscape of epigenetic regulation in PDAC at single-cell resolution and establishes a robust epigenetics-based prognostic model. The integration of epigenetic features with mutation profiles, immune microenvironment, and drug sensitivity offers new insights into PDAC heterogeneity and potential therapeutic strategies. These findings pave the way for personalized medicine in PDAC management and highlight the importance of epigenetic regulation in cancer research.