Long non-coding RNAs to predict postoperative recurrence in muscle-invasive bladder cancer and to develop a new molecular classification system

Background: Reliable molecular markers are much needed for early prediction of recurrence in muscle-invasive bladder cancer (MIBC) patients. We aimed to build an lncRNA signature to improve recurrence prediction and lncRNA-based molecular classification of MIBC. Methods: LncRNAs of 320 MIBC patients from TCGA database were analyzed, and a nomogram was established. A molecular classification system was created, and immunotherapy, chemotherapy response prediction, immune score analysis, immunoinfiltration analysis, and mutational data analysis were conducted. Findings: An eight-lncRNA signature could classify the patients into high- and low-risk subgroups having significantly different DFS. Our samples validated that the 8 lncRNAs were related with DFS. The nomogram achieved a C-index of 0.719 (95% CI, 0.674–0.764). Time-dependent ROC analyses indicated the superior prognostic accuracy of nomograms for DFS prediction (0.76, 95% CI, 0.697–0.807). Further, four clusters with different DFS and molecular features were identified. The four clusters (median DFS = 11.8, 15.3, 17.9, and 18.9 months, respectively) showed a high frequency of TTN, fibroblast growth factor receptor-3, TP53, and TP53 mutations, respectively. They were enriched with macrophages M2, T cells CD8, macrophages M0, and macrophages M0, respectively. Clusters 2 and 3 demonstrated potential sensitivity to immunotherapy and insensitivity to chemotherapy, whereas cluster 4 showed potential insensitivity to immunotherapy and sensitivity to chemotherapy. Interpretation: Our lncRNA-based signature proved to be a reliable prognostic tool to determine postoperative recurrence in MIBC patients. We believe that the four molecular subtypes possess the potential to guide treatment. Funding Statement: The funding bodies can be found in Acknowledgement section. Declaration of Interests: The authors declare no potential conflicts of interest.