Identification and Integrated Analysis of Key Biomarkers for Diagnosis and Prognosis of Pancreatic Adenocarcinoma

Abstract

Objective To screen and identify key genes and pathways involved in the progression of pancreatic adenocarcinoma (PAAD) and to perform an integrated analysis. Methods GEO2R was commonly used to screen and identify differentially expressed genes (DEGs) in GSE15471, GSE16515, GSE28735 and GSE62165, and the GO and KEGG pathway analyses were performed with DAVID database. Then a proteinprotein interaction (PPI) network was constructed using a STRING database, and Cytoscape and GEPIA were used to identify the Hub genes. Finally, the mRNA levels of these Hub genes were quantitatively analyzed by RT-qPCR. Results We screened 181 uDEGs and 64 dDEGs, and the analysis results indicated that uDEGs and dDEGs were respectively enriched in cell component (CC), biological process (BP) and molecular functional (MF), and they were closely related to multiple signal pathways. Then, the top 25 genes with high degree score in DEGs were selected. And 8 genes could predict the poor prognosis of PAAD. RT-qPCR showed that these genes were differentially expressed in PAAD tissues. Conclusion MMP14, MMP1, MET, PLAU, ITGA2, KRT19, COL12A1 and ITGA3 are the key genes associated with the progress of pancreatic cancer.

Keywords

• bioinformatics analysis
• differentially expressed genes (degs)
• pancreatic adenocarcinoma