A prognostic gene signature derived from aging-related genes predicts survival, immune landscape and therapy response in glioma.

ABSTRACT: Gliomas, the most common primary brain tumors, show diverse prognostic outcomes. Differences in gene expression between low-grade gliomas and glioblastoma and the role of aging-related genes highlight the need for robust prognostic models. The present study identified differentially expressed genes (DEGs) and developed a predictive risk model. Using The Cancer Genome Atlas (TCGA) and Chinese Glioma Genome Atlas (CGGA) datasets, 29 overlapping aging-related DEGs were identified (|LogFC|>1, adjusted P<0.05). Cox and LASSO regression analyses selected 8 genes for a risk scoring model, validated across datasets and subgroups. Functional and single-cell analyses explored immune microenvironments and drug sensitivities. Additionally, reverse transcription-quantitative PCR (RT-qPCR) was performed

SUBMITTER: Li Z 

PROVIDER: S-EPMC12679815 | biostudies-literature | 2026 Jan

REPOSITORIES: biostudies-literature