Identification of Key Genes Involved in Pancreatic Ductal Adenocarcinoma with Diabetes Mellitus Based on Gene Expression Profiling Analysis

This study aimed to identify key genes involved in the progression of diabetic pancreatic ductal adenocarcinoma (PDAC). Two gene expression datasets (GSE74629 and GSE15932) were obtained from Gene Expression Omnibus. Then, differentially expressed genes (DEGs) between diabetic PDAC and non-diabetic PDAC were identified, followed by a functional analysis. Subsequently, gene modules related to DM were extracted by weighed gene co-expression network analysis. The protein-protein interaction (PPI) network for genes in significant modules was constructed and functional analyses were also performed. After that, the optimal feature genes were screened by support vector machine (SVM) recursive feature elimination and SVM classification model was built. Finally, survival analysis was conducted to identify prognostic genes. The correlations between prognostic genes and other clinical factors were also analyzed. Totally, 1546 DEGs with consistent change tendencies were identified and functional analyses showed they were strongly correlated with metabolic pathways. Furthermore, there were two significant gene modules, in which RPS27A and UBA52 were key genes. Functional analysis of genes in two gene modules revealed that these genes primarily participated in oxidative phosphorylation pathway. Additionally, 21 feature genes were closely related with diabetic PDAC and the corresponding SVM classifier markedly distinguished diabetic PDAC from non-diabetic PDAC patients. Finally, decreased KIF22 and PYGL levels had good survival outcomes for PDAC. Four genes (RPS27A, UBA52, KIF22 and PYGL) might be involved in the pathogenesis of diabetic PDAC. Furthermore, KIF22 and PYGL acted as prognostic biomarkers for diabetic PDAC.