Identifying the Hub Genes of Glioma Peritumoral Brain Edema Using Bioinformatical Methods

Abstract

Glioma peritumoral brain edema (GPTBE) is a frequent complication in patients with glioma. The severity of peritumoral edema endangers patients' life and prognosis. However, there are still questions concerning the process of GPTBE formation and evolution. In this study, the patients were split into two groups based on edema scoring findings in the cancer imaging archive (TCIA) comprising 186 TCGA-LGG patients. Using mRNA sequencing data, differential gene (DEG) expression analysis was performed, comparing the two groups to find the key genes affecting GPTBE. A functional enrichment analysis of differentially expressed genes was performed. Then, a protein-protein interaction (PPI) network was established, and important genes were screened. Gene set variation analysis (GSVA) scores were calculated for major gene sets and comparatively correlated with immune cell infiltration. Overall survival (OS) was analyzed using the Kaplan-Meier curve. A total of 59 DEGs were found, with 10 of them appearing as important genes. DEGs were shown to be closely linked to inflammatory reactions. According to the network score, IL10 was in the middle of the network. The presence of the IL10 protein in glioma tissues was verified using the human protein atlas (HPA). Furthermore, the gene sets' GSVA scores were favorably linked with immune infiltration, particularly, with macrophages. The high-edema group had higher GSVA scores than the low-edema group. Finally, Kaplan-Meier analysis revealed no differences in OS between the two groups, and eight genes were found to be related to prognosis, whereas two genes were not. GPTBE is linked to the expression of inflammatory genes.

Keywords: data integration analysis; gene; glioma; inflammatory; peritumoral edema.

Figure 1

Differences in survival time and gene expression between the two groups. (A) Differentially expressed genes (DEGs). Genes with increasing expression were represented in red, whereas genes with decreased expression were represented in blue. (B) Ranking plot of DEGs. (C) Kaplan–Meier curves for the two groups.

Figure 2

Functional enrichment analysis of differentially expressed genes. (A–C) GO and KEGG analysis. (D,E) Protein interaction network diagram. The darker the template color, the greater the interaction score. (F) Heatmap of key genes with expression correlations.

Figure 3

Immunohistochemical image of IL10 on the HPA website. (A) Normal tissue. (B) Low-grade glioma. (C) High-grade glioma.

Figure 4

Survival analysis in relation to 10 key genes.

Figure 5

Immune cell infiltration analysis. (A) Correlation of immune infiltration based on the GSVA score. (B) GSVA scores were compared between groups. *: p value < 0.05; #: FDR < 0.05.