ArticleFrontiers in endocrinology2023
Construction of a telomere-related gene signature to predict prognosis and immune landscape for glioma.
Article in Frontiers in endocrinology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed, 5 citations in OpenAlex.
- Integrative Bulk and Single-Cell Transcriptome Profiling of Telomere-Related Genes Reveals a Robust Prognostic Signature and Immunotherapeutic Landscape in Neuroblastoma.Journal of Cancer · 2026Article
- Comprehensive analysis of telomere and aging-related signature for predicting prognosis and immunotherapy response in lung adenocarcinoma.Journal of cardiothoracic surgery · 2025Article
- The role of angiogenic growth factors in the immune microenvironment of glioma.Frontiers in oncology · 2023Review
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Authors and funding
5 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Glioma is one of the commonest malignant tumors of the brain. However, glioma present with a poor clinical prognosis. Therefore, specific detection markers and therapeutic targets need to be explored as a way to promote the survival rate of BC patients. Therefore, we need to search for quality immune checkpoints to support the efficacy of immunotherapy for glioma. Methods: We first recognized differentially expressed telomere-related genes (TRGs) and accordingly developed a risk model by univariate and multivariate Cox analysis. The accuracy of the model is then verified. We evaluated the variations in immune function and looked at the expression levels of immune checkpoint genes. Finally, to assess the anti-tumor medications often used in the clinical treatment of glioma, we computed the half inhibitory concentration of pharmaceuticals. Results: We finally identified nine TRGs and built a risk model. Through the validation of the model, we found good agreement between the predicted and observed values. Then, we found 633 differentially expressed genes between various risk groups to identify the various molecular pathways between different groups. The enrichment of CD4+ T cells, CD8+ T cells, fibroblasts, endothelial cells, macrophages M0, M1, and M2, mast cells, myeloid dendritic cells, and neutrophils was favorably correlated with the risk score, but the enrichment of B cells and NK cells was negatively correlated with the risk score. The expression of several immune checkpoint-related genes differed significantly across the risk groups. Finally, in order to create individualized treatment plans for diverse individuals, we searched for numerous chemotherapeutic medications for patients in various groups. Conclusion: The findings of this research provide evidence that TRGs may predict a patient's prognosis for glioma, assist in identifying efficient targets for glioma immunotherapy, and provide a foundation for an efficient, customized approach to treating glioma patients.
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