Identification of hub genes and analysis of prognostic values in pancreatic ductal adenocarcinoma by integrated bioinformatics methods
Abstract
Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal cancers in the world, and more molecular mechanisms should be illuminated to meet the urgent need of developing novel detection and therapeutic strategies. We analyzed the related microarray data to find the possible hub genes and analyzed their prognostic values using bioinformatics methods. The mRNA microarray datasets GSE62452, GSE15471, GSE102238, GSE16515, and GSE62165 were finally chosen and analyzed using GEO2R. The overlapping genes were found by Venn Diagrams, functional and pathway enrichment analyses were performed using the DAVID database, and the protein-protein interaction (PPI) network was constructed by STRING and Cytoscape. OncoLnc, which was linked to TCGA survival data, was used to investigate the prognostic values. In total, 179 differentially expressed genes (DEGs) were found in PDAC, among which, 130 were up-regulated genes and 49 were down-regulated. DAVID showed that the up-regulated genes were significantly enriched in extracellular matrix and structure organization, collagen catabolic and metabolic process, while the down-regulated genes were mainly involved in proteolysis, reactive oxygen species metabolic process, homeostatic process a...Continue Reading
References
A Novel MIF Signaling Pathway Drives the Malignant Character of Pancreatic Cancer by Targeting NR3C2
Prognostic relevance of molecular subtypes and master regulators in pancreatic ductal adenocarcinoma
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