Dissecting lncRNA-mRNA regulatory network in type 2 diabetes as the risk factor of pancreatic cancer

Abstract 

Background:Emerging evidence supports the role of type 2 diabetes (T2D) mellitus as a risk factor for cancer progression. In this study, we investigated and identified biomarkers related to diabetes and pancreatic ductal adenocarcinoma (PDAC) using systems biology to understand better the molecular landscape of PDAC and its connections with T2D.

Methods: RNA-seq data related to blood samples of diabetes and pancreatic cancer were analyzed using bioinformatics tools in the Galaxy platform. After differential expression analysis using the DESeq2, the co-expression network associated with T2D and PDAC data was reconstructed using the WGCNA. Then, by visualizing the protein-protein interaction network in modules specifically related to T2D and PDAC, the key genes involved in these two diseases were identified, and their interaction network with long non-coding RNAs was reconstructed. Finally, the results of bioinformatics analysis were verified by qPCR in four groups, including T2D, PDAC, PDAC-T2D, and control groups.

Results: In this study, 1905 and 18,558 genes with significant differential expression were identified in the data of T2D and PDAC, respectively (|logFC| > 0.58, adj. p value < 0.05). The WGCNA showed 32 and 20 co-expression modules in diabetes and pancreatic cancer data, respectively. Among these, 303 genes were co-expressed, related to diabetes and pancreatic cancer. Based on the protein-protein interaction pattern, five hub genes were identified (using the CytoHubba Cytoscape plugin and the Maximal Clique Centrality (MCC) parameter). Finally, the co expression network was reconstructed between these five genes and other lncRNAs. The qPCR showed that the expression of the CEBPZ gene was significantly increased in the blood samples of the diabetic (log2FC = 1.163, adj. p value = 0.0006), pancreatic cancer (log2FC = 3.22, adj. p value < 0.0001), and pancreatic cancer-diabetic (log2FC = 2.73, adj. p value < 0.0001) groups compared to the control group.

Conclusion:For the first time, this study suggested that CEBPZ expression may serve as a diagnostic biomarker for assessing PDAC in individuals with T2D, given its differential expression in this specific cohort.