Predicting Treatment Outcomes in Glioblastoma: A Risk Score Model for TMZ Resistance and Immune Checkpoint Inhibition.

ABSTRACT: Glioblastoma (GBM) presents significant therapeutic challenges due to its invasive nature and resistance to standard chemotherapy, i.e., temozolomide (TMZ). This study aimed to identify gene signatures that predict poor TMZ response and high PD-L1/PD-1 tumor expression, and explore potential sensitivity to alternative drugs. We analyzed The Cancer Genome Atlas (TCGA) biopsy data to identify differentially expressed genes (DEGs) linked to these characteristics. Among 33 upregulated DEGs, 5 were significantly correlated with overall survival. A risk score model was built using these 5 DEGs, classifying patients into low-, medium-, and high-risk groups. We assessed immune cell infiltration, immunosuppressive mediators, and epithelial-mesenchymal transition (EMT) markers in each group using co

SUBMITTER: Gonzalez N 

PROVIDER: S-EPMC12109283 | biostudies-literature | 2025 May

REPOSITORIES: biostudies-literature