Research Paper Volume 14, Issue 23 pp 9715—9729

A risk score for the prognosis prediction of the muscle-invasive bladder cancer patients who received gemcitabine plus cisplatin chemotherapy


Figure 1. Workflow of this study. The clinical characteristics dataset, Drug treatment dataset, and transcriptome profiling dataset were downloaded from the BLCA (Bladder Urothelial Carcinoma) project of TCGA (The Cancer Genome Atlas). The study dataset contained complete information about 65 MIBC patients who received GC regimens, which was obtained by merging the clinical characteristics dataset, the Drug treatment dataset, and the transcriptome profiling dataset. Survival-associated genes were identified by univariate cox regression analysis. The KEGG enrichment analysis and the GO enrichment analysis were utilized to explore the molecular functions of the survival-associated genes. LASSO cox regression analysis was used to select special survival-associated genes. The individual risk score was calculated by multivariate cox regression analysis. Kaplan-Meier survival curve and log-rank test were employed to compare the OS of the high-risk and low-risk patients. To assess the risk score’s ability to predict prognosis, a time-dependent ROC plot was created. High-risk and low-risk MIBC patients’ average risk scores were compared. Risk score, gender, age at diagnosis, and AJCC pathological stage were all combined to create the nomogram. GSEA was utilized to explore key signal pathways for DEGs between high-risk and low-risk patients.