Construction of a Cuproptosis-Related lncRNA Prognostic Model for Bladder Urothelial Carcinoma and Screening of Potential Drugs

Abstract

Objective. This study aimed to analyze the cuproptosis-related long non-coding RNA (lncRNA) in patients with bladder urothelial carcinoma (BLCA), construct a prognostic model, and screen its potential drugs. Methods. The transcriptome expression and clinical and mutation burden data related to BLCA were downloaded from The Cancer Genome Atlas database. The prognostic lncRNAs were screened using univariate Cox and Lasso regression analyses, and then included in the multifactor risk ratio model. The risk score of each sample was calculated based on the prognostic model formula, and the patients were divided into high- and low-risk groups for survival difference analysis. Clinically relevant receiver operating characteristic (ROC) curve, C-index principal component analysis, and clinical data statistics were used to evaluate the predictive power of the model. The risk-differential lncRNAs were functionally enriched. We calculated the tumor mutation burden of risk lncRNAs, and survival and the Tumor Immune Dysfunction and Exclusion analyses for high- and low-risk groups. Finally, immunocorrelation analysis and potential drug screening were performed. Results. Eleven lncRNAs with independent prognostic significance were screened out to construct the prognostic model. Survival analysis showed a significant difference in survival between the high- and low-risk groups. The areas under the ROC curve at 1, 3, and 5 years were 0.711, 0.679, and 0.713, respectively. The discrimination between the lncRNA high- and low-risk groups in the constructed model was the most obvious. The risk-differential lncRNAs were closely related to immunity. The treatment drugs with high sensitivity were screened based on the IC50 value. Conclusion. The 11 cuproptosis-related lncRNAs may serve as molecular biomarkers and therapeutic targets for BLCA.