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Updated: Nov 9, 2025
Digital Spatial Profiling for Characterization of the Microenvironment in Adult-Type Diffusely Infiltrating Glioma
Published on: September 13, 2022
Comprehensive exploration of tumor mutational burden and immune infiltration in diffuse glioma
Kai Kang1, Fucun Xie2, Yijun Wu1
1Department of Radiation Oncology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.
Background:
Immune checkpoint inhibitors (ICIs) have been used as a novel treatment for diffuse gliomas, but the efficacy varies with patients, which may be associated with the tumor mutational burden (TMB) and immune infiltration. We aimed to explore the relationship between the two and their impacts on the prognosis.
Methods:
The data of the training set were downloaded from The Cancer Genome Atlas (TCGA). "DESeq2" R package was used for differential analysis and identification of differentially expressed genes (DEGs). A gene risk score model was constructed based on DEGs, and a nomogram was developed combined with clinical features. With the CIBERSORT algorithm, the relationship between TMB and immune infiltration was analyzed, and an immune risk score model was constructed. Two models were verification in the validation set downloaded from the Chinese Glioma Genome Atlas (CGGA).
Results:
Higher TMB was related to worse prognosis, older age, higher grade, and higher immune checkpoint expression. The gene risk score model was constructed based on BIRC5, SAA1, and TNFRSF11B, and their expressions were all negatively correlated with prognosis. The nomogram was developed combined with age and grade. The immune risk score model was constructed based on M0 macrophages, neutrophils, naïve CD4+ T cells, and activated mast cells. The proportions of the first two were higher in the high-TMB group and correlated with worse prognosis, while the latter two were precisely opposite.
Conclusions:
In diffuse gliomas, TMB was negatively correlated with prognosis. The association of immune infiltration with TMB and prognosis varied with the type of immune cells. The nomogram and risk score models can accurately predict prognosis. The results can help identify patients suitable for ICIs and potential therapeutic targets, thus improve the treatment of diffuse gliomas.
Insights
Tumor mutational burden (TMB) correlates negatively with diffuse glioma prognosis. Immune cell infiltration impacts TMB and outcomes, informing immunotherapy selection and target identification.
Area of Science:
- Neuro-oncology
- Immunology
- Genomics
Background:
- Immune checkpoint inhibitors (ICIs) show variable efficacy in diffuse gliomas.
- Tumor mutational burden (TMB) and immune infiltration are potential factors influencing ICI response.
Purpose of the Study:
- To investigate the relationship between TMB and immune infiltration in diffuse gliomas.
- To explore their combined impact on patient prognosis and potential for predicting ICI efficacy.
Main Methods:
- Differential gene expression analysis (DESeq2) and construction of a gene risk score model.
- Development of a nomogram incorporating clinical features.
- Analysis of TMB and immune infiltration using the CIBERSORT algorithm to build an immune risk score model.
- Validation of models using TCGA and CGGA datasets.
Main Results:
- Higher TMB correlated with worse prognosis, older age, higher tumor grade, and increased immune checkpoint expression.
- A gene risk score model (BIRC5, SAA1, TNFRSF11B) and a nomogram (age, grade) predicted prognosis.
- Immune risk score model identified M0 macrophages and neutrophils associated with high TMB and poor prognosis, while naïve CD4+ T cells and activated mast cells showed opposite correlations.
Conclusions:
- TMB is a negative prognostic factor in diffuse gliomas.
- Specific immune cell types differentially associate with TMB and prognosis.
- Developed models accurately predict diffuse glioma prognosis, aiding in patient stratification for ICIs and identifying therapeutic targets.
