Comprehensive analysis of RNA methylation-related genes to identify molecular cluster for predicting prognosis and immune profiles in bladder cancer

m6A, m5C and m7G are common types of RNA methylation modifications that are widely involved in key mechanisms regulating malignancy. However, the role of RNA methylation-related genes in the immune microenvironment of bladder cancer (BLCA) remains elusive. In this study, we established RNA methylation molecular subtypes by analyzing the TCGA and GEO datasets. Risk model and nomogram were constructed by LASSO and multivariate Cox regression analysis and validated by external datasets. Genetic variations, functional enrichment analysis and immune cell infiltration were analyzed. The expression levels of hub genes were detected by real-time polymerase chain reaction (qRT-PCR) and immunohistochemistry (IHC). The effect of FN1 on cellular function was determined using experimental assays. Finally, we identified a 7-gene signature associated with BLCA prognosis. GSE19423 validated the predictive value of the risk model. The IMvigor210 data showed the model had promising predictive efficacy for BLCA immunotherapy. Significant differences in biological function, immune cell infiltration and drug sensitivity were observed between high- and low-risk groups. Furthermore, FN1 was upregulated in BLCA, as determined by qRT-PCR and IHC. Depletion of FN1 using siRNA impaired cell motility in T24 and 5637 cells. In conclusion, RNA methylation-related risk model can predict the prognosis, immune landscape and response to immunotherapy in BLCA. Among the 7-gene signature, FN1 is a pivotal gene that promotes the migration of bladder cancer cells.