Identification of key pathways and candidate genes in pancreatic ductal adenocarcinoma using bioinformatics analysis

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Abstract

Pancreatic ductal adenocarcinoma (PDAC) is a malignant tumor with a high degree of malignancy that is difficult to diagnose and treat. The present study integrated PDAC cohort profile datasets to identify key candidate genes and pathways involved in the pathogenesis of the disease. The expression profiles of GSE28735 included 45 PDCA and matching pairs of adjacent non-tumor tissue. Differentially expressed genes (DEGs) were sorted and candidate genes and pathway enrichment were analyzed. A DEG-associated protein-protein interaction (PPI) network was constructed. A total of 424 DEGs were identified in PDAC, including 159 upregulated genes and 265 downregulated genes. Gene Ontology analysis results indicated that upregulated DEGs were significantly enriched in biological process, molecular function and cellular component categories. Kyoto Encyclopedia of Genes and Genomes pathway analysis demonstrated that the upregulated DEGs were enriched in ‘pancreatic secretion’, ‘protein digestion’ and ‘absorption’. Downregulated DEGs were enriched in ‘ECM-receptor inter-action’, ‘focal adhesion’ and ‘PI3K/AKT’ signaling pathways. The PPI network revealed that these genes were involved in significant pathways, including ‘ECM organization’ signaling pathways (Hippo signaling pathway, TGF-β signaling pathway, Hedgehog signaling pathway and Wnt signaling pathway), ‘serine-type peptidase activity’ signaling pathway (PI3K-Akt signaling pathway, TNF-α signaling pathway and Wnt signaling pathway) and ‘extracellular region’ signaling pathways (RTP signaling pathway, G protein-coupled receptor signaling pathway and RAS-RAF-MAPK signaling pathway). The identification of these candidate genes and pathways sheds light on the etiology and molecular mechanisms of PDAC and may guide the development of novel therapies for pancreatic cancer.

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He, Y., Liu, Y., Gong, J., Liu, C., Zhang, H., & Wu, H. (2019). Identification of key pathways and candidate genes in pancreatic ductal adenocarcinoma using bioinformatics analysis. Oncology Letters, 17(4), 3751–3764. https://doi.org/10.3892/ol.2019.10041

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