ArticleFrontiers in oncology2022
Construction of an immune-related gene signature for the prognosis and diagnosis of glioblastoma multiforme.
Article in Frontiers in oncology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed, 6 citations in OpenAlex.
- Identification of hsa-miR-144-3p as a novel immunotherapeutic target for glioblastoma based on disulfidptosis-related analysis.Discover oncology · 2026Article
- A manganese metabolism-related gene signature for prognosis prediction and immune microenvironment description of glioblastoma.Discover oncology · 2026Article
- FN1 Immunoregulation in Glioblastoma: Insights From Neutrophil-Centric Studies.Cancer science · 2025Article
- Prognostic Value of Pentraxin3 Protein Expression in Human Malignancies: A Systematic Review and Meta-Analysis.Cancers · 2024Review
- Article
- Identification and validation of a 17-gene signature to improve the survival prediction of gliomas.Frontiers in immunology · 2022Article
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Authors and funding
7 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Increasing evidence has suggested that inflammation is related to tumorigenesis and tumor progression. However, the roles of immune-related genes in the occurrence, development, and prognosis of glioblastoma multiforme (GBM) remain to be studied. Methods: The GBM-related RNA sequencing (RNA-seq), survival, and clinical data were acquired from The Cancer Genome Atlas (TCGA), Genotype-Tissue Expression (GTEx), Chinese Glioma Genome Atlas (CGGA), and Gene Expression Omnibus (GEO) databases. Immune-related genes were obtained from the Molecular Signatures Database (MSigDB). Differently expressed immune-related genes (DE-IRGs) between GBM and normal samples were identified. Prognostic genes associated with GBM were selected by Kaplan-Meier survival analysis, Least Absolute Shrinkage and Selection Operator (LASSO)-penalized Cox regression analysis, and multivariate Cox analysis. An immune-related gene signature was developed and validated in TCGA and CGGA databases separately. The Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed to explore biological functions of the signature. The correlation between immune cell infiltration and the signature was analyzed by single-sample gene set enrichment analysis (ssGSEA), and the diagnostic value was investigated. The gene set enrichment analysis (GSEA) was performed to explore the potential function of the signature genes in GBM, and the protein-protein interaction (PPI) network was constructed. Results: Three DE-IRGs [Pentraxin 3 ( Conclusion: The signature with three immune-related genes might be an independent prognostic factor for GBM patients and could be associated with the immune cell infiltration of GBM patients.
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