Prediction of Potential Drugs Targeting Acute Pancreatitis Based on the HLA-DR-Related Gene-Monocyte Infiltration Regulatory Network

Background: Acute pancreatitis (AP) is a common disease of acute abdominal pain, the incidence of which is increasing annually, but its pathogenesis remains incompletely understood. Methods: Gene expression profiles of AP were obtained from the Gene Expression Omnibus (GEO) database. R software was used to identify differentially expressed genes (DEGs) and perform functional analysis. The diagnostic value of HLA-DR-related genes was assessed by receiver operating characteristic (ROC) curves. Monocyte infiltration abundance in AP and normal groups was analyzed by Cibersort method, and the correlation between HLA-DR-related genes and monocyte abundance was analyzed. The modules highly correlated with HLA-DR-related genes were clarified by WGCNA modeling, and the core genes regulating HLA-DR were obtained by using LASSO regression. Finally, potential drugs targeting the above genes were analyzed by Enrichr database. Result: A Total of 3 HLA-DR-related genes (HLA-DRA, HLA-DRB1, and HLA-DRB5) were identified, which were negatively correlated with the severity of AP and had excellent disease diagnostic value (AUC = 0.761, 0.761, and 0.718), were were positively correlated with monocyte abundance. We identified 110 genes that positively regulate HLA-DR and 130 genes that negatively regulate HLA-DR. LASSO regression identified UCP2, GK, and SAMHD1 as the core nodes of the regulated genes. Compared with the normal group, UCP2 and SAMHD1 were reduced in AP, and the opposite was true for GK, and SAMHD1 had better sensitivity and specificity in diagnosing AP. Drug sensitivity analysis predicted 12 drugs acting on HLA-DRA, HLA-DRB1, and HLA-DRB5 and 8 drugs acting on UCP2, GK, and SAMHD1. Conclusion: We identified 3 HLA-DR-related genes (HLA-DRA, HLA-DRB1, and HLA-DRB5) and 3 coregulatory nodes (UCP2, GK, and SAMHD1), which were associated with AP severity and monocyte abundance. Based on these genes, we predicted 20 potential therapeutic agents for AP.