Brain Tumor Res Treat.  2024 Oct;12(4):237-244. 10.14791/btrt.2024.0035.

The Inflammatory Characteristics of Symptomatic Glioma Associated With Poor Prognosis and Chemoresistance via Tumor Necrosis Factor Signaling Pathway

• Park J
• Kim D
• Sim J
• Kim YJ
• Cho K
• Moon JH
• Sung KS
• Yoo J
• Lim J

• KMID: 2561288
• DOI: http://doi.org/10.14791/btrt.2024.0035

Abstract

Background
Among gliomas, the most common primary malignant brain tumor, incidental gliomas account for 2.5%–5% of cases. The controversy over whether to pursue immediate treatment or adopt a wait-and-see approach remains, and more molecular and immunological evidence is needed for definitive treatment decisions.
Methods
Total RNA sequencing (RNA-seq) data and single cell RNA sequencing (scRNA-seq) data were retrospectively analyzed to compare the molecular and immunological tumor microenvironment differences between incidental glioma and symptomatic glioma samples. These were classified using symptom data from The Cancer Genome Atlas (TCGA) and public dataset.
Results
RNA-seq analysis of the GBMLGG dataset identified 343 genes upregulated in symp- tomatic glioma and 118 in incidental glioma, with 104 common genes upregulated in symptomatic glioma across both the TCGA and Chinese Glioma Genome Atlas (CGGA) datasets. Enrichment analysis revealed that these 104 genes in symptomatic glioma were significantly associated with immunological pathways. scRNA-seq analysis of glioma revealed 11 cell types, including T cells, myeloid cells, and oligodendrocytes, with the tumor necrosis factor (TNF) signaling pathway strongly influencing other cell types, particularly myeloid cells. Enrichment and survival analyses showed that TNF signaling is associated with temozolomide resistance and poorer prognosis in glioma patients.
Conclusion
The findings suggest that symptomatic glioma enhances inflammatory responses linked to poor prognosis and chemoresistance. This supports the hypothesis that immediate treatment of incidental glioma may improve patient outcomes over a wait-and-see approach.

Keyword

Glioma; Incidental discovery; Prognosis; Drug resistance; Neuroinflammation; Tumor necrosis factor.

Figure

• 

  Fig. 1 The flowchart of this study. DEG, differentially expressed gene.

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  Fig. 2 The result of DEG analysis. A: The volcano plot based on the result of DEG analysis. Blue is genes whose p-value is lower than 0.05, red is 0.01. B: The venn diagram based on significantly upregulated genes in symptomatic and incidental glioma with TCGA and CGGA data set. C: The dot plot of gene set enrichment analysis with commonly upregulated genes in symptomatic glioma. DEG, differentially expressed gene; TCGA, The Cancer Genome Atlas; CGGA, Chinese Glioma Genome Atlas; GO, Gene Ontology; KEGG, Kyoto Encyclopedia of Genes and Genomes.

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  Fig. 3 Immunological landscape of glioma. A: The uniform manifold approximation and projection (UMAP) plot as result of scRNA-seq analysis. AC-like is astrocyte like cells, OPC-like is oligodendrocyte progenitor cell like cells, MES-like is mesenchymal like cells, NPC-like is neural progenitor cell like cells. B: The feature plot of single cell gene set enrichment analysis (GSEA) score of four selected hallmark immunological terms. C: The result of significant immunological cell-to-cell interaction network.

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  Fig. 4 The association of TNF signaling pathway and poor prognosis of glioblastoma. A: The dot plot of significantly enriched pathways with genes whose expression is positively correlated with temozolomide resistance. B: The Kaplan-Meier curve of two groups divided by ssGSEA score. TNF, tumor necrosis factor; GO, Gene Ontology; KEGG, Kyoto Encyclopedia of Genes and Genomes; OS, overall survival; ssGSEA, single sample gene set enrichment analysis.

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