A Novel Defined Risk Signature Based on Lactate-Related Genes can Predicts Prognosis of Bladder Cancer

Background: Lactate is an important carbon source for cell metabolism as well as a signaling molecule in normal, chronic inflammatory and cancer tissues. However, the relationship between lactate and bladder cancer (BLCA) has not been studied yet. Methods Expression profiles of the patients with bladder cancer from The Cancer Genome Atlas were divided into different clusters using non-negative matrix factorization clustering to obtain differentially expressed genes (DEGs). Univariate Cox analysis, Lasso-Cox analysis, Kaplan-Meier survival analysis, and time-dependent receiver operating characteristics curves were used to developed and validated a prognostic signature for the survival rate of patients. "CIBERSORT" and "ESTIMATE" algorithms were used to quantify the immunocyte content and evaluate tumor purity for different clusters and subgroups. Online tool "Tumor Immune Dysfunction and Exclusion" was used to predict the immune escape ability of patients in different scoring subgroups after immunotherapy. Results The different clusters according to the expression pattern of lactate-associated genes (LAGs) had significant differences in the survival rate and the tumor microenvironment. Besides, a risk signature constructed by DEGs based on different clusters and verified by the GSE32894 dataset could not only significantly distinguish between the prognosis and clinical features of patients with different scores but was also found to be related to the tumor microenvironment and immunotherapy. Finally, a high accuracy nomogram model was established. Conclusions Overall, this research has revealed the relationship between lactate and patient prognosis, tumor microenvironment, and immunotherapy, which may provide novel prognostic biomarkers for patients with BLCA.