Development and validation of a prognosis model for low-grade gliomas based on metabolic gene risk scoring and immune microenvironment interaction

This study constructed and validated a metabolism-driven prognostic model. The model enables prognostic stratification of LGG patients and links high-risk scores to metabolic dysregulation and an immunosuppressive microenvironment characterized by M2 macrophage enrichment, based on multi-omics data. Mechanistic exploration indicates this association is particularly pronounced in myeloid cells, predominantly within metabolism-related M2 macrophage subpopulations. Furthermore, computational analysis suggests differences in drug sensitivity between risk groups and identifies potential therapeutic compounds, providing clues for future exploration of therapeutic strategies targeting metabolic-immune interactions.