Bladder cancer (BCa) is the most common urological tumor, and most BCas are diagnosed at an advanced stage due to the lack of reliable diagnostic markers. In this study, transcriptomic and clinical data from BCa patients in the TCGA database were analyzed and all patients were randomly divided into a training group and a validation group. Univariate Cox regression analysis was performed to screen miRNAs significantly associated with BCa prognosis, followed by multivariate Cox regression analysis in the training group to establish a prognostic risk model for multiple miRNAs. The model was validated in the validation group and in the whole group and assessed using Norman plots. KEGG pathway and GO enrichment analyses were performed on possible target genes, and PPI networks were constructed. Finally, a prognostic model for 5-miRNA was successfully constructed. Multivariate Cox analysis showed that it had good predictive properties and could be used as a novel biomarker to predict prognosis and survival of BCa patients and may exert its biological function through IGF1.

膀胱癌（BCa）是最常见的泌尿系统肿瘤，由于缺乏可靠的诊断标志物，大多数 BCas 被诊断为晚期。本研究分析了TCGA数据库中BCa患者的转录组学和临床数据，并将所有患者随机分为训练组和验证组。对训练组进行单变量Cox回归分析筛选与BCa预后显着相关的miRNA，然后对训练组进行多变量Cox回归分析，建立多个miRNA的预后风险模型。该模型在验证组和整个组中得到验证，并使用诺曼图进行评估。对可能的靶基因进行KEGG通路和GO富集分析，构建PPI网络。最后，成功构建了5-miRNA的预后模型。多变量Cox分析表明，它具有良好的预测特性，可作为预测BCa患者预后和生存的新型生物标志物，并可能通过IGF1发挥其生物学功能。