Deciphering the molecular crosstalk between type 2 diabetes and pancreatic cancer through cross-disease co-expression network analysis

Abstract

Multiple complex mechanisms link type 2 diabetes mellitus (T2DM) with the pathogenesis, development, and progression of pancreatic cancer (PC). This study aims to elucidate these complex relationships using crossdisease co-expression analysis of PC and T2DM. Transcriptomic data from peripheral blood samples of patients with pancreatic ductal adenocarcinoma (PDAC), PDAC patients with diabetes (DP), patients with diabetes mellitus (DM), and healthy controls were analyzed. Following differential expression analysis (DEA), four disease-specific gene co-expression networks were constructed using weighted gene co-expression network analysis (WGCNA). Pearson correlation analysis was then applied to identify modules significantly associated with each clinical trait. In the experimental phase, peripheral blood samples from 20 PDAC patients, 20 DP patients, 20 DM patients, and 20 healthy controls were included. The co-expression network analysis identified modules highly associated with PDAC, DP, and DM. Among the 11 overlapping genes shared between these modules, the high-confidence hub genes ACADVL, AGTRAP, and PADI4 were selected for quantitative real-time PCR (qPCR) validation. Comparative analysis of ACADVL expression among the four study groups showed significantly higher expression in the PDAC group than in the DM group (p < 0.01) and healthy controls (p < 0.0001). Similarly, ACADVL expression was significantly elevated in the DP group compared with the DM group (p < 0.01) and healthy controls (p < 0.0001). The survival analysis also suggests that high ACADVL expression is a favorable prognostic biomarker.