Construction of a telomere-related gene signature to predict prognosis and immune landscape for glioma
BackgroundGlioma 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 qua...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2023-06-01
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| Series: | Frontiers in Endocrinology |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fendo.2023.1145722/full |
| _version_ | 1797809318801702912 |
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| author | Qin Xie Tingting Liu Xiaole Zhang Yanli Ding Xiaoyan Fan |
| author_facet | Qin Xie Tingting Liu Xiaole Zhang Yanli Ding Xiaoyan Fan |
| author_sort | Qin Xie |
| collection | DOAJ |
| description | BackgroundGlioma 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.MethodsWe 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.ResultsWe 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.ConclusionThe 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. |
| first_indexed | 2024-03-13T06:50:47Z |
| format | Article |
| id | doaj.art-a6b37fef68514407a83b90cd604abf94 |
| institution | Directory Open Access Journal |
| issn | 1664-2392 |
| language | English |
| last_indexed | 2024-03-13T06:50:47Z |
| publishDate | 2023-06-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Endocrinology |
| spelling | doaj.art-a6b37fef68514407a83b90cd604abf942023-06-07T15:41:49ZengFrontiers Media S.A.Frontiers in Endocrinology1664-23922023-06-011410.3389/fendo.2023.11457221145722Construction of a telomere-related gene signature to predict prognosis and immune landscape for gliomaQin Xie0Tingting Liu1Xiaole Zhang2Yanli Ding3Xiaoyan Fan4Department of Neurosurgery, Hangzhou Ninth People’s Hospital, Hangzhou, Zhejiang, ChinaDepartment of Endocrinology, Affiliated Haikou Hospital of Xiangya School of Central South University, Haikou, Hainan, ChinaDepartment of Neurosurgery, Hangzhou Ninth People’s Hospital, Hangzhou, Zhejiang, ChinaDepartment of Neurosurgery, Hangzhou Ninth People’s Hospital, Hangzhou, Zhejiang, ChinaIntensive Care Unit, Hangzhou Ninth People’s Hospital, Hangzhou, Zhejiang, ChinaBackgroundGlioma 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.MethodsWe 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.ResultsWe 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.ConclusionThe 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.https://www.frontiersin.org/articles/10.3389/fendo.2023.1145722/fullgliomasignatureimmunotherapycheckpointclinical treatment |
| spellingShingle | Qin Xie Tingting Liu Xiaole Zhang Yanli Ding Xiaoyan Fan Construction of a telomere-related gene signature to predict prognosis and immune landscape for glioma Frontiers in Endocrinology glioma signature immunotherapy checkpoint clinical treatment |
| title | Construction of a telomere-related gene signature to predict prognosis and immune landscape for glioma |
| title_full | Construction of a telomere-related gene signature to predict prognosis and immune landscape for glioma |
| title_fullStr | Construction of a telomere-related gene signature to predict prognosis and immune landscape for glioma |
| title_full_unstemmed | Construction of a telomere-related gene signature to predict prognosis and immune landscape for glioma |
| title_short | Construction of a telomere-related gene signature to predict prognosis and immune landscape for glioma |
| title_sort | construction of a telomere related gene signature to predict prognosis and immune landscape for glioma |
| topic | glioma signature immunotherapy checkpoint clinical treatment |
| url | https://www.frontiersin.org/articles/10.3389/fendo.2023.1145722/full |
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