Identification of taurine metabolism related subtypes in gliomas and construction of risk models to predict prognosis and immune microenvironment

Glioma is a prevalent and aggressive brain tumor, and taurine metabolism may play a crucial role in suppressing tumor progression. This research seeks to identify taurine metabolism-related glioma subtypes and develop a model to predict patient prognosis. By systematically integrating and analyzing transcriptomic data from the TCGA and CGGA databases, we identified taurine metabolism-related genes (TMRGs) and revealed molecular subtypes linked to taurine metabolism in glioma. Both univariate Cox regression and LASSO were employed to pinpoint prognostic signature genes, whose predictive significance was then confirmed. Additionally, we conducted a thorough immune profiling, analyzed tumor mutational burden, and compared drug sensitivity across different risk groups. This study successfully identified two molecular subtypes relate to taurine metabolism in glioma. The prognostic risk model based on nine key genes was then developed and independently validated. Receiver operating characteristic (ROC) curve analysis showed that the model exhibited high predictive accuracy in both the training and validation cohorts. Moreover, low-risk patients showed higher immune scores and more favorable clinical results. Moreover, drug sensitivity analysis of the nine signature genes identified potentially effective therapeutic agents. This study successfully identified glioma subtypes relate to taurine metabolism and established a prognostic model in view of key signature genes, offering novel insights for guiding glioma treatment strategies. This study systematically identified two subtypes associated with taurine metabolism in glioma and successfully established a prognostic risk assessment model. The study successfully identified nine characteristic genes, which can serve as prognostic indicators related to taurine metabolism in glioma. The study further identified ten potential drugs that interact with the characteristic genes through drug sensitivity analysis.