Zhang Yu, Yang Xin, Zhu Xiao-Lin, Wang Zhuang-Zhuang, Bai Hao, Zhang Jun-Jie, Hao Chun-Yan, Duan Hu-Bin
Department of Neurosurgery, First Hospital of Shanxi Medical University, Taiyuan, China.
Department of Geriatrics, First Hospital of Shanxi Medical University, Taiyuan, China.
Front Oncol. 2021 Apr 16;11:643159. doi: 10.3389/fonc.2021.643159. eCollection 2021.
Glioma is one of the most common malignancies in the central nervous system and has limited effective therapeutic options. Therefore, we sought to identify a suitable target for immunotherapy.
We screened prognostic genes for glioma in the CGGA database and GSE43378 dataset using survival analysis, receiver operating characteristic (ROC) curves, independent prognostic analysis, and clinical correlation analysis. The results were intersected with immune genes from the ImmPort database through Venn diagrams to obtain likely target genes. The target genes were validated as prognostically relevant immune genes for glioma using survival, ROC curve, independent prognostic, and clinical correlation analyses in samples from the CGGA database and GSE43378 dataset, respectively. We also constructed a nomogram using statistically significant glioma prognostic factors in the CGGA samples and verified their sensitivity and specificity with ROC curves. The functions, pathways, and co-expression-related genes for the glioma target genes were assessed using PPI networks, enrichment analysis, and correlation analysis. The correlation between target gene expression and immune cell infiltration in glioma and the relationship with the survival of glioma patients were investigated using the TIMER database. Finally, target gene expression in normal brain, low-grade glioma, and high-grade glioma tissues was detected using immunohistochemical staining.
We identified TNFRSF12A as the target gene. Satisfactory results from survival, ROC curve, independent prognosis, and clinical correlation analyses in the CGGA and GSE43378 samples verified that TNFRSF12A was significantly associated with the prognosis of glioma patients. A nomogram was constructed using glioma prognostic correlates, including TNFRSF12A expression, primary-recurrent-secondary (PRS) type, grade, age, chemotherapy, IDH mutation, and 1p19q co-deletion in CGGA samples with an AUC value of 0.860, which illustrated the accuracy of the prognosis prediction. The results of the TIMER analysis validated the significant correlation of TNFRSF12A with immune cell infiltration and glioma survival. The immunohistochemical staining results verified the progressive up-regulation of TNFRSF12A expression in normal brain, low-grade glioma, and high-grade glioma tissues.
We concluded that TNFRSF12A was a viable prognostic biomarker and a potential immunotherapeutic target for glioma.
胶质瘤是中枢神经系统最常见的恶性肿瘤之一,有效的治疗选择有限。因此,我们试图确定一个适合免疫治疗的靶点。
我们使用生存分析、受试者工作特征(ROC)曲线、独立预后分析和临床相关性分析,在CGGA数据库和GSE43378数据集中筛选胶质瘤的预后基因。通过维恩图将结果与来自ImmPort数据库的免疫基因进行交叉,以获得可能的靶基因。分别使用CGGA数据库和GSE43378数据集中样本的生存、ROC曲线、独立预后和临床相关性分析,将靶基因验证为胶质瘤的预后相关免疫基因。我们还使用CGGA样本中具有统计学意义的胶质瘤预后因素构建了列线图,并通过ROC曲线验证了其敏感性和特异性。使用蛋白质-蛋白质相互作用(PPI)网络、富集分析和相关性分析评估胶质瘤靶基因的功能、通路和共表达相关基因。使用TIMER数据库研究靶基因表达与胶质瘤中免疫细胞浸润的相关性以及与胶质瘤患者生存的关系。最后,使用免疫组织化学染色检测正常脑、低级别胶质瘤和高级别胶质瘤组织中靶基因的表达。
我们确定TNFRSF12A为靶基因。CGGA和GSE43378样本中的生存、ROC曲线、独立预后和临床相关性分析结果令人满意,证实TNFRSF12A与胶质瘤患者的预后显著相关。使用包括TNFRSF12A表达、原发-复发-继发(PRS)类型、级别、年龄、化疗、异柠檬酸脱氢酶(IDH)突变和1p19q共缺失等胶质瘤预后相关因素在CGGA样本中构建了列线图,AUC值为0.860,这说明了预后预测的准确性。TIMER分析结果验证了TNFRSF12A与免疫细胞浸润和胶质瘤生存的显著相关性。免疫组织化学染色结果证实了TNFRSF12A在正常脑、低级别胶质瘤和高级别胶质瘤组织中表达的逐渐上调。
我们得出结论,TNFRSF12A是一种可行的预后生物标志物,也是胶质瘤潜在的免疫治疗靶点。