Abstract
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). Somatic 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 between high- and low-risk groups, we identified six hub TMB and immune-related genes that were correlated with overall survival in LGGs. Then, Gene Set Enrichment Analysis 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 six hub genes and was validated with the Chinese Glioma Genome Atlas dataset. Using the TIMER database, we further systematically analyzed the relationships between mutants of the six hub genes and immune infiltration levels, 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 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 checkpoints (PD-1, CTLA-4, LAG-3, and TIM-3) were found in patients 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 immune infiltration in the tumor microenvironment and immunotherapies for LGGs.
Highlights
Gliomas are the most common malignant tumors in the central nervous system [1]
The correlation between the six hub genes and the level of immune cell infiltration was analyzed in TIMER, and the results showed that the expression of BIRC5, GDF15, LTF, and TNFRSF11B were positively correlated with the infiltrating levels of immune cells, whereas the expression of CRLF1 and PRLHR were negatively correlated (Figure 6)
Great efforts have been made in neurosurgery, radiotherapy, and chemotherapy, the survival of lower-grade gliomas (LGGs) patients still ranges widely
Summary
Gliomas are the most common malignant tumors in the central nervous system [1]. Traditionally, gliomas are divided into grades I to IV, including astrocytoma, oligoastrocytoma, oligodendroglioma, and glioblastoma (GBM) [2, 3]. According to the updated classification system by the World Health Organization (WHO) in 2016, LGGs can be divided into three subtypes based on the mutation status of isocitrate dehydrogenase 1 (IDH1) and the codeletion status of 1p/19q, in which both tumor phenotypes and genotypes are considered [8]. This classification system of LGGs has been adopted for molecular diagnosis, the known molecular markers are currently very limited for explaining the prognosis of LGGs. further exploration of the genetic mechanism and identification of new biomarkers to predict the prognosis of LGGs is important to develop precise treatments
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