ArticleBrain sciences2022
Identifying the Hub Genes of Glioma Peritumoral Brain Edema Using Bioinformatical Methods.
Article in Brain sciences, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed, 8 citations in OpenAlex.
- Obstacles and Trials in Treating Primary Brain Tumors.International journal of molecular sciences · 2026Review
- Anlotinib treatment for refractory peritumoral brain edema in brain metastases.Discover oncology · 2026Article
- Current Pharmacotherapeutic Strategies in Diffuse Gliomas: Focus on Glioblastoma, IDH-Wildtype, and Emerging Targeted Therapies for IDH-Mutant Tumors.Pharmaceuticals (Basel, Switzerland) · 2026Review
- The Interaction Between Vasculogenic Mimicry and the Immune System: Mechanistic Insights and Dual Exploration in Cancer Therapy.Cell proliferation · 2025Review
- Clinicopathological Parameters and Immunohistochemical Profiles in Correlation with MRI Characteristics in Glioblastomas.International journal of molecular sciences · 2024Article
- Claudin and transmembrane receptor protein gene expressions are reversely correlated in peritumoral brain edema.Cancer medicine · 2024Article
- Peritumoral Edema in Gliomas: A Review of Mechanisms and Management.Biomedicines · 2023Review
- Ferroptosis and PPAR-gamma in the limelight of brain tumors and edema.Frontiers in oncology · 2023Review
Corrections and comments
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
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.
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