Development and Validation of a Tumor Mutation Burden–Related Immune Prognostic Model for Lower-Grade Glioma - Yin, Wen; Jiang, Xingjun; Tan, Jun; Xin, Zhaoqi; Zhou, Quanwei; Zhan, Chaohong; Fu, Xianyong; Wu, Zhaoping; Guo, Youwei; Jiang, Zhipeng; Ren, Caiping; Tang, Guihua (Frontiers in Oncology, 2020)
Tumor mutation burden (TMB) is a useful biomarker to predict prognosis and the efficacy of immune checkpoint inhibitors (ICIs). In this study, we aimed to explore the prognostic value of TMB and the potential association between TMB and immune infiltration in lower-grade gliomas (LGGs). The sSomatic mutation and RNA-sequencing (RNA-seq) data were downloaded from the Cancer Genome Atlas (TCGA) database. TMB was calculated and patients were divided into high- and low-TMB groups. After performing differential analysis conducted between high- and low-risk groups, we identified the 6 hub TMB and immune-related genes which that were correlated with overall survival in LGGs. Then, Gene Set Enrichment Analysis (GSEA) was performed to screen significantly enriched GO terms between the two groups. Moreover, an immune-related risk score system was developed by LASSO Cox analysis based on the 6 hub genes and was validated with the Chinese Glioma Genome Atlas (CGGA) dataset. By Using the TIMER database, we further systematically analyzed the relationships between the mutants of the 6 hub genes and immune infiltration levels, and as well as the relationships between the immune-related risk score system and the immune microenvironment in LGGs. The results showed that TMB was negatively correlated with OS and high TMB might inhibit the immune infiltration in LGGs. Furthermore, the risk score system could effectively stratify patients into low- and high-risk groups in both the training and validation datasets. Multivariate Cox analysis demonstrated that TMB was not an independent prognostic factor, but the risk score was. Higher infiltration of immune cells (B cells, CD4+ T cells, CD8+ T cells, neutrophils, macrophages and dendritic cells) and higher levels of immune check check-points (PD-1, CTLA-4, LAG-3, and TIM-3) was were found in the patients of in the high-risk group. Finally, a novel nomogram model was constructed and evaluated to estimate the overall survival of LGG patients. In summary, our study provided new insights into the immune infiltration of in the tumor microenvironment and immunotherapies for LGGs.