Comprehensive analysis of immune escape-related prognostic signature in high-grade glioma.

ABSTRACT:

Objective

High-grade glioma (HGG) is one of the most lethal malignancies. Immune escape is considered to be a reason for the failure of immunotherapy for HGG patients, and there is currently no immune escape-related prognostic model for glioma. Therefore, we explored the relationship between immune escape-related genes and the prognosis of patients with HGG.

Methods

This study combined 101 machine learning algorithms to determine the best immune escape-related prognostic model. Subsequently, the TCGA and CGGA cohorts were used to verify the effectiveness of the model. Subsequently, molecular docking, Mendelian randomization and other comprehensive analyses were performed on the model genes. Finally, the biology function of the signature gene was further verified via CCK-8, a

SUBMITTER: Ren C 

PROVIDER: S-EPMC12521732 | biostudies-literature | 2025 Oct

REPOSITORIES: biostudies-literature