Integration of clinical and spatial data to explore lipid metabolism-related gene for predicting prognosis and immune microenvironment in gliomas

Abstract

Abstract Lipid metabolism is crucial to tumor growth and immune microenvironment as well as drug sensitivity in glioma. Identifying prognostic indicators of glioma and elucidating the mechanisms of glioma progression is for improving glioma patient prognosis. In this study, we investigated the role and prognostic value of metabolism-related genes in glioma by GEO, CGGA, and TCGA. Based on clinical data and transcriptome data, We found that the expression pattern of three major pathways of lipid metabolism is fatty acidhigh-phospholipidhigh-triglyceridelow, which is associated with better prognosis and immune infiltration. Using the related genes of these three pathways constructed a prognostic model, and the model showed stability and efficiency in the test set and validation set. In the spatial transcriptome of glioma patients, the microenvironment of the regions with high expression of risk gene CAV1 and SCD is in a state of hypoxia, EMT, and cell cycle arrest, and thus can be used as markers of metabolic reprogramming in the tumor microenvironment. In the high-risk group, M0 macrophages and M1 macrophages were significantly enriched, and the risk score was significantly correlated with gene mutation and methylation. screened the sensitive drugs corresponding to different risk genes. This study provided novel insights into the differential immune microenvironment with different metabolic expression patterns and highlighted the spatial and temporal synergy of tumor progression and metabolic reprogramming.