Abstract
Pancreatic ductal adenocarcinoma (PDAC) is the most common tumor subtype of pancreatic cancer, which exhibits poor patient prognosis due to the lack of effective biomarkers in the diagnosis and treatment. The present study aimed to identify the potential biomarkers of PDAC carcinogenesis and progression using three microarray datasets, GSE15471, GSE16515 and GSE28735, which were downloaded from the Gene Expression Omnibus database. The datasets were analyzed to screen out differentially expressed genes (DEGs) in PDAC tissues and adjacent normal tissues. A total of 143 DEGs were identified, including 132 upregulated genes and 11 downregulated genes. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes functional and signaling pathway enrichment analyses were performed on the DEGs, and the Search Tool for the Retrieval of Interacting Genes/Proteins database was used to construct a protein-protein interaction network. The main functions of DEGs include extracellular matrix degradation, and regulation of matrix metalloproteinase activity and the PI3K-Akt signaling pathway. The five hub genes were subsequently screened using Cytoscape software, and survival analysis demonstrated that abnormal expression levels of the hub genes was associated with poor disease-free survival and overall survival. Biological experiments were performed to confirm whether mesenchymal-to-epithelial transition (MET) factors promote the proliferation, migration and invasion of PDAC cells via the PI3K/AKT signaling pathway. In addition, six MET-targeted microRNAs (miRNAs) were identified, four of which had conserved binding sites with MET. Based on the signaling pathway enrichment analysis of these miRNAs, it is suggested that they can affect the progression of PDAC by targeting MET via the PI3K/AKT signaling pathway. In conclusion, the hub genes and miRNAs that were identified in the present study contribute to the molecular mechanisms of PDAC carcinogenesis and progression. They also provide candidate biomarkers for early diagnosis and treatment of patients with PDAC.
Keywords:
bioinformatics analysis; differentially expressed genes; microRNA; microarray; pancreatic ductal adenocarcinoma.