Prognostic value of lactate metabolism-related gene expression signature in adult primary gliomas and its impact on the tumor immune microenvironment - Wang, Zhihao; Zhang, Shuxin; Li, Junhong; Yuan, Yunbo; Chen, Siliang; Zuo, Mingrong; Li, Wenhao; Feng, Wentao; Chen, Mina; Liu, Yanhui (Frontiers in Oncology, 2022)
Glioma is one of the most malignant intracerebral tumors, whose treatment means was limited and prognosis was unsatisfactory. Lactate metabolism patterns have been shown to be highly heterogenous among different tumors and produce diverse impact on the tumor microenvironment. To understand the characteristics and implications of lactate metabolism gene expression, we developed a lactate metabolism-related gene expression signature of gliomas based on RNA-sequencing data of a total of 965 patient samples from TCGA, CGGA, and our own glioma cohort. Sixty-three lactate metabolism-related genes (LMGs) were differentially expressed between glioma and normal brain tissue, and consensus clustering analysis identified two clusters distinct LMG expression patterns. The consensus clusters differed in prognosis, molecular characteristics and estimated immune microenvironment landscape involving immune checkpoint proteins T cell dysfunction and exclusion, as well as tumor purity. Univariate Cox regression and Least Absolute Shrinkage and Selection Operator (LASSO) Cox hazard regression was applied in determining of prognosis-related lactate metabolism genes (PRLMGs), on which prognostic lactate metabolism risk score (PLMRS) was constructed. The high PLMRS group was associated with significantly poorer patient outcome. A nomogram containing PLMRS and other independent prognostic variables was established with remarkable predictive performance on patient survival. Exploration on the somatic mutations and copy number variations of the high- and low-PLMRS groups demonstrated their distinct genetic background. Together, our results indicated that the expression signature of LMG was associated with the prognosis of glioma patients and influenced the activity of immune cells in the tumor microenvironment, which may serve as a potential biomarker for predicting response of gliomas to immunotherapy.