Integrated Bioinformatics Analysis of Gene Expression Profiles for Potential Biomarker Identification Towards Early Therapeutic Intervention in Pancreatitis and Pancreatic Ductal Adenocarcinoma

Abstract

\n Pancreatic ductal adenocarcinoma (PDAC) is a malignancy associated with rapid progression and an abysmal prognosis. It has been reported that chronic pancreatitis can increase the risk of developing PDAC by 16-fold. Our study aims to identify the key genes and biochemical pathways mediating pancreatitis and PDAC. The gene expression datasets were retrieved from the EMBL-EBI ArrayExpress and NCBI GEO database. A total of 172 samples of normal pancreatic tissue, 68 samples of pancreatitis, and 306 samples of PDAC were used in this study. The differentially expressed genes (DEGs) identified were used to perform downstream analysis for ontology, interaction, and associated pathways. Furthermore, hub gene expression was validated using the GEPIA2 tool and survival analysis using the Kaplan-Meier (KM) plotter. The potential druggability of the hub genes identified was determined using the Drug-Gene Interaction Database (DGIdb). Our study identified a total of 45 genes found to have altered expression levels in both PDAC and pancreatitis. Over-representation analysis revealed that protein digestion and absorption pathway, ECM-receptor interaction pathway, PI3k-Akt signaling pathway, and proteoglycans in cancer pathways as significantly enriched. Module analysis revealed 15 hub genes with 92 edges, of which 14 were found to be in the druggable genome category. Through bioinformatics analysis, we identified key genes and biochemical pathways disrupted in pancreatitis and PDAC. The results can provide new insights into targeted therapy and intervening therapeutically at an earlier stage can be used as an effective strategy to decrease the incidence and severity of PDAC.