Abstract
BACKGROUND: Glioblastoma (GBM) is the most aggressive primary brain tumor with poor prognosis despite multimodal therapy. Understanding the molecular and genetic characteristics of GBM and the influence of anesthesia drugs on tumor behavior is crucial for developing new therapeutic strategies. METHODS: We analyzed RNA-seq data from The Cancer Genome Atlas (TCGA)-GBM cohort and a Gene Expression Omnibus (GEO) dataset (GSE179004) of GBM samples treated with propofol and sevoflurane. Differential expression analysis identified anesthesia-related genes (ARGs), and their prognostic relevance was assessed using Cox regression. Consensus clustering stratified GBM patients into subgroups with distinct survival outcomes, immune cell infiltration, and pathway activities. An ARGs-based prognostic model was developed using Lasso-Cox regression and validated across cohorts. The hub gene NDUFB2 was identified and validated using single-cell sequencing, drug sensitivity assessment, and spatial transcriptome analysis. NDUFB2 expression levels were experimentally verified in our GBM samples. RESULTS: ARGs were significantly differentially expressed between GBM and normal tissues, with NDUFB2 identified as a hub gene associated with poor prognosis. Consensus clustering divided GBM patients into two subgroups with significant survival differences. An 11-ARGs-based prognostic model was established, demonstrating strong correlation with overall survival. NDUFB2 was predominantly expressed in malignant cells and associated with decreased survival and drug sensitivity. CONCLUSIONS: Our study, based on an initial exploratory analysis of anesthesia-related genes (ARGs), highlights their potential prognostic significance in GBM. We propose NDUFB2 as a robust biomarker for prognosis and therapeutic response, supported by extensive validation. These findings offer insights into the molecular classification of GBM and suggest a possible impact of anesthesia drugs on tumor progression, warranting further validation in larger cohorts. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12885-025-15312-4.