Identification of biomarkers and their functions in dasatinib‑resistant pancreatic cancer using bioinformatics analysis

Dasatinib is a tyrosine kinase inhibitor, which inhibits tumor proliferation by blocking SRC pathways and is considered as a potential treatment of various epithelial neoplasms, including pancreatic cancer. However, dasatinib efficacy is largely limited due to drug resistance. In the present study, bioinformatics strategies were used to investigate the potential mechanisms of dasatinib-resistance in pancreatic cancer. The gene expression profiles of the Panc0403, Panc0504, Panc1005 (dasatinib-sensitive), SU8686, MiaPaCa2 and Panc1 (acquired dasatinib-resistant) cell lines were obtained from the gene expression omnibus database. The differentially expressed genes (DEGs) were then selected using R software. In addition, gene ontology (GO) and pathway enrichment analysis were performed through the Database for Annotation, Visualization and Integrated Discovery. A protein-protein interaction (PPI) network was constructed and analyzed to determine the hub genes using the Search Tool for the Retrieval of Interacting Genes database. A total of 472 DEGs, including vimentin, transmembrane 4 l six family member 18 and S100 calcium binding protein P, were identified. Enrichment analysis by GO function demonstrated that DEGs were associated with extracellular components, signal regulation and binding factors. The analysis of the Kyoto Encyclopedia of Genes and Genomes demonstrated that several adenocarcinoma pathways were enriched, including the phosphoinositide 3-kinases/protein kinase B and mitogen-activated protein kinase signaling pathways. Some hub genes were highlighted following the PPI network construction, including Rac family small GTPase 1, laminin subunit alpha 3, integrin subunit beta 4, integrin subunit alpha 2, collagen type VI alpha 1 chain, collagen type I alpha 2 chain, arrestin beta 1 and synaptotagmin 1, which may be associated with pancreatic adenocarcinoma prognosis. A total of five out of eight hub genes were highly associated with the overall survival rate (P<0.05). In conclusion, the present study reported novel insights into the mechanisms of dasatinib resistance. Identification of these hub genes may be considered as potential novel treatment targets for dasatinib-resistance in pancreatic cancer.