Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal malignancies worldwide due to its ineffective diagnosis and poor prognosis. It is essential to identify differentially expressed genes (DEGs) in PDAC to gain new insights into its underlying molecular mechanisms, as well as identify potential diagnostic and therapeutic targets. We screened 135 DEGs from the GSE15417, GSE16515, and GSE28735 PDAC and normal pancreatic tissue microarray data sets, and identified 16 DEGs that were correlated with PDAC prognosis through the Kaplan-Meier survival analysis and log-rank tests. The Cancer Genome Atlas and Oncomine databases validated the expression levels of 16 candidate genes (SLC6A14, GPRC5A, IFI27, ERP27, SDR16C5, SIDT2, TCN1, COL12A1, MMP1, CEACAM6, DKK1, ITGA2, KRT19, PLAU, ANO1, and GABRP). Weighted gene coexpression network analysis (WGCNA) and protein and protein interaction (PPI) analysis identified three hub genes-ERP27, ITGA2, and MMP1-that are likely important in PDAC prognosis. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis demonstrated that they were enriched in functions of extracellular matrix organization, extracellular structure organization, and positive regulation of cell migration. Taken together, we identified three pivotal genes for PDAC, which can improve our understanding of its pathogenesis, progression, and prognosis.
Keywords: ERP27; ITGA2; MMP1; bioinformatic analysis; pancreatic ductal adenocarcinoma.