Construction of a telomere-related gene signature to predict prognosis and immune landscape for glioma

Qin Xie; Tingting Liu; Xiaole Zhang; Yanli Ding; Xiaoyan Fan

doi:10.3389/fendo.2023.1145722

Construction of a telomere-related gene signature to predict prognosis and immune landscape for glioma

Front Endocrinol (Lausanne). 2023 Jun 2:14:1145722. doi: 10.3389/fendo.2023.1145722. eCollection 2023.

Authors

Qin Xie¹, Tingting Liu², Xiaole Zhang¹, Yanli Ding¹, Xiaoyan Fan³

Affiliations

¹ Department of Neurosurgery, Hangzhou Ninth People's Hospital, Hangzhou, Zhejiang, China.
² Department of Endocrinology, Affiliated Haikou Hospital of Xiangya School of Central South University, Haikou, Hainan, China.
³ Intensive Care Unit, Hangzhou Ninth People's Hospital, Hangzhou, Zhejiang, China.

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.

Keywords: checkpoint; clinical treatment; glioma; immunotherapy; signature.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

B-Lymphocytes
Endothelial Cells*
Glioma* / genetics
Humans
Immunotherapy
Prognosis

Grants and funding

This work was supported by the Health Science and Technology Program of Hangzhou (A20220002) and the Hainan Provincial Natural Science Foundation of China (No. 822RC860).