A comprehensive analysis of candidate genes and pathways in pancreatic cancer

Abstract

The study aimed to dissect the molecular mechanism of pancreatic cancer by a range of bioinformatics approaches. Three microarray datasets (GSE32676, GSE21654, and GSE14245) were downloaded from Gene Expression Omnibus database. Differentially expressed genes (DEGs) with logarithm of fold change (|logFC|) >0.585 and p value <0.05 were identified between pancreatic cancer samples and normal controls. Transcription factors (TFs) were selected from the DEGs based on TRASFAC database. Gene ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses were performed for the DEGs using The Database for Annotation, Visualization and Integrated Discovery (p value <0.05), followed by construction of protein-protein interaction (PPI) network using Search Tool for the Retrieval of Interacting Genes software. Latent pathway identification analysis was applied to analyze the DEGs-related pathways crosstalk and the pathways with high weight value were included in the pathway crosstalk network using Cytoscape. Sixty-five DEGs were screened out. CCAAT/enhancer-binding protein delta (CEBPD), FBJ osteosarcoma oncogene B (FOSB), Stratifin (SFN), Krüppel-like factor 5 (KLF5), Pentraxin 3 (PTX3), and nuclear receptor subfamily 4, group A, member 3 (NR4A3) were important TFs. Interleukin-6 (IL-6) was the hub node of the PPI network. DEGs were significantly enriched in NOD-like receptor signaling pathway which was primarily interacted with inflammation and immune related pathways (cytosolic DNA-sensing, hematopoietic cell lineage, intestinal immune network for IgA production and chemokine pathways). The study suggested CEBPD, FOSB, SFN, KLF5, PTX3, NR4A3, IL-6, and NOD-like receptor pathways were involved in pancreatic cancer.