To elucidate the molecular mechanisms underlying the protective effects of selenium on pancreatic function in diabetes mellitus, we performed a comprehensive bioinformatics analysis of the GSE55636 dataset from the Gene Expression Omnibus (GEO). This dataset comprised pancreatic tissue samples from streptozotocin-induced diabetic mice, including three mice administered 0.8 mg/kg body weight sodium selenate (Na2SeO3, SS) and three matched controls. Our investigation revealed 838 differentially expressed genes (DEGs) in SS-treated pancreatic tissue, with 500 up-regulated and 338 down-regulated genes. Through protein-protein interaction (PPI) network analysis, we identified 20 hub genes (including FOS, PTGS2, CXCL1, IL5, CCL7, IRF1, PTPRC, EGR2, and CD80) exhibiting the highest connectivity scores. Gene Ontology (GO) enrichment analysis demonstrated these hub genes were predominantly associated with critical biological processes: Chromosomal segregation, Mitotic cell cycle regulation, Inflammatory response modulation, Immune system activation. KEGG pathway analysis further revealed their significant enrichment in key signaling pathways: TNF-α, NF-κB, MAPK, IL-17-mediated inflammation, Chemokine-mediated immune regulation. Notably, the identified pathways demonstrated strong associations with pancreatic β-cell survival, insulin secretion regulation, and oxidative stress mitigation. These findings systematically characterize the selenium-responsive molecular network in diabetic pancreatic tissue, providing novel insights into the nutrigenomic mechanisms of selenium's pancreatic protection. The 20 hub genes identified may serve as potential therapeutic targets for diabetes management through selenium supplementation.