A Novel Prognostic Model Based on Cuproptosis-Related Genes and Multi-Omics Analysis Predicts the Prognosis of Patients with Bladder Urothelial Carcinoma

Cuproptosis is a special form of cell death. Bladder cancer, especially Bladder Urothelial Carcinoma (BLCA), is one of the ten most common cancer types in the world. So far, the potential role of cuproptosis in BLCA is unclear. In the present study, we systematically evaluated the copper poisoning mediated patterns of 509 BLCA samples based on 19 validated copper poisoning related genes (CRGs) using data downloaded from the Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) database. Kaplan Meier method was used to analyze the overall survival rate (OS) of different risk groups. Gene Set Variation Analysis (GSVA) was used to study the functional differences between different cuproptosis clusters (CRG clusters). Single sample gene set enrichment analysis (ssGSEA) was used to explore the potential relationship between CRGclusters and immune status. We used GO (Gene Ontology) and KEGG (Kyoto Encyclopedia of Genes and Genomes) enrichment analysis to study various cellular biochemical processes. Finally, we established a prognostic model to predict patients’ survival outcomes and to further analyze the correlation between the predictive characteristics of BLCA patients and various treatment response. In this study, we derived two CRGclusters and geneclusters, and also established a model to quantify the risk score of individual BLCA patients, which was found to be closely associated with various clinical characteristics and could precisely predict the prognosis of BLCA patients. We believe that through our study, quantitative analysis of cuproptosis mediated patterns in a single sample may help to improve our understanding of the multi-omics characteristics of BLCA and guide future treatment regimens.