A signature constructed with circadian rhythm-related genes to predict the prognosis and therapy response for low-grade gliomas.

ABSTRACT: Recent studies suggest circadian rhythm-related genes are crucial for immune balance and potential therapeutic targets, but their role in low-grade gliomas (LGG) is not well understood. We analyzed their prognostic significance in glioma progression using predictive models. TCGA-LGG cohort data was analyzed utilizing univariate Cox regression and LASSO to create a strong prognostic model. Kaplan-Meier and ROC analyses validated the model's predictive accuracy, revealing significantly poorer survival outcomes in high-risk patients relative to those at low risk. Cox regression identified our gene signature as an independent prognosistic predictor. Decision curve analysis (DCA) and calibration supported the nomogram's predictive power. Further analyses, including gene alteration, functional e

SUBMITTER: Zhou Y 

PROVIDER: S-EPMC12748338 | biostudies-literature | 2025 Dec

REPOSITORIES: biostudies-literature