Identification of key genes and pathways in the following pancreatic ductal adenocarcinoma (PDAC) using integrated bioinformatics analysis

Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal cancer, and understanding its molecular mechanisms is critical for improving diagnosis and treatment. This study analyzed microarray datasets (GSE16515, GSE28730, GSE62165, and GSE91035) from the Gene Expression Omnibus to identify differentially expressed genes (DEGs) in PDAC. A total of 1917 upregulated and 1003 downregulated genes were identified across 323 PDAC and matched normal samples. Hierarchical clustering analysis revealed four distinct clusters, with Cluster 2 exhibiting higher gene expression changes. Further analysis identified 23 significantly upregulated genes, including AHNAK2, CDH3, CEACAM1, CEACAM5, COL10A1, FN1, KRT19, MMP11, and TRIM29. Functional enrichment analysis indicated that these genes were involved in processes such as cell adhesion, extracellular matrix (ECM) structural constituents, and receptor-ligand interactions. Key pathways included pancreatic secretion, protein digestion, absorption, and ECM-receptor interactions. Survival analysis revealed that high expression levels of AHNAK2, CDH3, CEACAM6, COL17A1, CXCL5, and others were associated with poor prognosis. Validation confirmed overexpression of these genes in PDAC tissues. These findings highlight the potential role of genes from the AHNAK2, Laminin family (LAMC2, LAMB3), and fibronectin (FN1) in PDAC progression. The study provides valuable insights into the molecular mechanisms underlying PDAC and identifies potential biomarkers for prognosis and therapeutic targets.