Construction and evaluation of a bladder cancer prognosis model based on super-enhancer-associated genes

Abstract Introduction Bladder cancer (BLCA) is a malignant tumour that occurs on the mucosa of the bladder. It accounts for the first place in the incidence of genitourinary tumours in China. BLCA is characterized by high recurrence rate and poor survival rate. There is still a research gap regarding super-enhancer-related genes (SERGs) in BLCA. Methods The The Cancer Genome Atlas Bladder Urothelial Carcinoma (TCGA-BLCA) and GSE31684 were subjected into this study. In addition, the Super-Enhancer Archive database was used to identify SERGs. Differential expression analysis was used to analyse the differentially expressed genes (DEGs) between the BLCA and control groups. The DEGs were overlapped with SERGs to get candidate genes in TCGA-BLCA, which were analyzed for Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG). Univariate Cox, Least Absolute Shrinkage and Selection Operator (Lasso) regression and multivariate Cox regression analyses were used to build the risk model for BLCA. Survival analyses and validation of the model were performed by Kaplan-Meier (K-M) curves and Receiver Operating Characteristic (ROC) curve, respectively. In addition, using the estimating relative subsets of RNA transcripts (CIBERSORT) algorithm, 22 immune cell proportions were calculated. The drug sensitivity was also analyzed in this study. Results First of all, based on the TCGA-BLCA, 70 DE-SERGs were yielded. A prognosis model based on MXRA7, PLEKHG4B and ATP2B4 was finally constructed. ROC curves revealed that the prognosis model was a good predictor of BLCA outcomes. Immune infiltration analysis revealed that risk score was positively associated with T cells CD4 memory resting, Mast cells resting and Macrophages M2 and negatively associated with Dendritic cells activated and T cells CD8. Besides, AZD8186, BMS-754,807, JQ1, KRAS (G12C) Inhibitor and NU7441 were the top five sensitivity drugs for BLCA. Conclusion Three genes (MXRA7, PLEKHG4B and ATP2B4) were identified to construct a SERG-related model in BLCA, which provides a basis for understanding BLCA pathogenesis and new insights into BLCA treatment.