Prognostic migrasome-associated long noncoding RNA model and tumor immune landscape in bladder cancer

Aim: This study aims to identify migrasome-associated long non-coding RNA (lncRNA) signatures for prognostic prediction and to analyze their correlation with tumor microenvironment (TME) features in bladder cancer. Methods: Data including transcriptome, mutation, and clinical profiles were obtained from TCGA. A total of 10 migrasome-related genes were used to screen co-expressed lncRNAs by Pearson correlation. Univariate Cox and LASSO-Cox regression analyses were performed for the selection of essential prognostic lncRNAs to construct a risk score model. Kaplan-Meier survival analysis, ROC curve, and nomogram were applied in model validation. The characteristics of TME were evaluated using ESTIMATE and CIBERSORT. Drug sensitivity was predicted using the oncoPredict algorithm. Results: A total of 808 lncRNAs associated with the migrasome were identified, and seven lncRNAs were selected to construct a prognostic model. The overall survival (OS) of individuals in the high-risk group was significantly shorter than that of those in the low-risk group in training, testing, and full datasets (all P < 0.001), with a 5-year AUC of 0.685. Multivariate analysis showed that the risk score was an independent prognostic factor (HR = 1.119, P < 0.001). Immune infiltration analysis revealed higher M0 macrophages but lower CD8+ T cell infiltration in the high-risk cohort (P < 0.05), while the stromal cell scores were significantly higher in high-risk patients (P < 0.001). High-risk patients had a lower tumor mutational burden (TMB) than low-risk patients (P = 0.00057). Drug sensitivity analysis indicated that nilotinib and KU-55933 may be potential drugs with significant differences in drug sensitivity between the two risk subgroups (P < 10-9). Conclusion: A 7-lncRNA signature serves as an effective predictor of bladder cancer prognosis, demonstrating a correlation with TME immune suppression and stromal activation. This discovery offers novel biomarkers for prognostic evaluation and the development of personalized therapy strategies.