Metabolic profiling of glioblastoma and identification of G0S2 as a metabolic target.

Introduction: Metabolic reprogramming is a hallmark of cancer, yet its role in glioma remains poorly understood. Gliomas are characterized by a highly immunosuppressive tumor microenvironment (TME) and poor prognosis. This study systematically explores the relationship between glioma metabolomics, tumor phenotype, and the immune microenvironment. Methods: Bulk RNA sequencing data were retrieved from the Chinese Glioma Genome Atlas (CGGA) and The Cancer Genome Atlas (TCGA). Single-cell gene set enrichment analysis (ssGSEA) was employed to quantify seven nutrient metabolic pathways and immune infiltration. Consensus clustering was applied to group gliomas based on metabolic gene expression, and survival analysis was performed to evaluate survival differences across these clusters. A predictive model was constructed and validated using our cohort. Finally, we knocked out G0S2 in glioma cells and performed RNA sequencing to investigate differentially activated pathways. Additionally, Results: Significant metabolic differences were identified between low-grade gliomas (LGG) and glioblastomas (GBM), with consistent findings across both databases. We found that LGGs and GBMs exhibit distinct metabolic patterns. Consensus clustering revealed three metabolic subgroups, with the C3 subgroup demonstrating poor survival and enhanced infiltration of immunosuppressive cells. The predictive model showed robust performance in forecasting the survival of glioma patients. Functional analysis identified G0S2 as a key metabolic regulator highly expressed in gliomas. G0S2 knockout activated the type I interferon signaling pathway, enhanced CD8 Conclusion: These findings provide a comprehensive analysis of glioma metabolic patterns and identify G0S2 as a promising therapeutic target.