■胶质瘤是大脑中最常见的恶性肿瘤之一。然而,神经胶质瘤临床预后较差。因此,需要探索特异性检测标志物和治疗靶点,以提高BC患者的生存率。因此,我们需要寻找高质量的免疫检查点,以支持神经胶质瘤免疫治疗的有效性。
■我们首先识别了差异表达的端粒相关基因(TRG),并因此通过单变量和多变量Cox分析开发了风险模型。然后验证了模型的准确性。我们评估了免疫功能的变化,并观察了免疫检查点基因的表达水平。最后,评估常用于临床治疗神经胶质瘤的抗肿瘤药物,我们计算了药物的半抑制浓度。
■我们最终确定了9个TRG,并建立了风险模型。通过对模型的验证,我们发现预测值和观测值之间有很好的一致性。然后,我们在不同风险组之间发现了633个差异表达基因,以确定不同组之间的不同分子途径.CD4+T细胞的富集,CD8+T细胞,成纤维细胞,内皮细胞,巨噬细胞M0,M1和M2,肥大细胞,髓样树突状细胞,中性粒细胞与风险评分有良好的相关性,但B细胞和NK细胞的富集与风险评分呈负相关。几个免疫检查点相关基因的表达在不同的风险组中显著不同。最后,为了为不同的个体制定个性化的治疗计划,我们为不同组的患者搜索了多种化疗药物.
■这项研究的结果提供了证据,证明TRGs可以预测患者的神经胶质瘤预后,协助确定胶质瘤免疫治疗的有效靶点,并为有效的,定制治疗胶质瘤患者的方法。
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.
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.
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.
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.