Purine metabolism-related gene expression signature predicts survival outcome and indicates immune microenvironment profile of gliomas.

ABSTRACT

Glioma is the most common malignant tumor in the central nervous system. The impact of metabolism on cancer development and the immune microenvironment landscape has recently gained broad attention. Purines are involved in multiple metabolic pathways. It has been proved that purine metabolism could regulate malignant biological behaviors and response to immune checkpoint inhibitors in multiple cancers. However, the relationship of purine metabolism with clinicopathological features and the immune landscape of glioma remains unclear. In this study, we explored the relationships between the expression of purine metabolism-related genes (PuMGs) and tumor features, including prognosis and microenvironment of glioma, based on analyses of 1,523 tumors from 4 public databases and our cohort. Consensus clustering based on 136 PuMGs classified the glioma patients into two clusters with significantly distinguished prognosis and immune microenvironment landscapes. Increased immune infiltration was associated with more aggressive gliomas. The prognostic Purine Metabolism-Related Genes Risk Signature (PuMRS), based on 11 critical PuMGs, stratified the patients into PuMRS low- and high-risk groups in the training set and was validated by validation sets from multiple cohorts. The high-risk group presented with significantly shorter overall survival, and further survival analysis demonstrated that the PuMRS was an independent prognostic factor in glioma. The nomogram combining PuMRS and other clinicopathological factors showed satisfactory accuracy in predicting glioma patients' prognosis. Furthermore, analyses of the tumor immune microenvironment suggested that higher PuMRS was correlated with increased immune cell infiltration and gene expression signatures of "hotË® tumors. Gliomas in the PuMRS high-risk group presented a higher expression level of multiple immune checkpoints, including PD-1 and PD-L1, and a better-predicted therapy response to immune checkpoint inhibitors. In conclusion, our study elucidated the relationship between the expression level of PuMGs and the aggressiveness of gliomas. Our study also endorsed the application of PuMRS to construct a new robust model for the prognosis evaluation of glioma patients. The correlations between the profiles of PuMGs expression and tumor immune microenvironment potentially provided guidance for immunotherapy in glioma.