Liu Yu-Qing, Wu Fan, Li Jing-Jun, Li Yang-Fang, Liu Xing, Wang Zheng, Chai Rui-Chao
Department of Molecular Neuropathology, Beijing Neurosurgical Institute, Beijing, China.
Chinese Glioma Genome Atlas Network, Beijing, China.
Front Oncol. 2019 Dec 17;9:1433. doi: 10.3389/fonc.2019.01433. eCollection 2019.
In the present study, we aimed to determine the candidate genes that may function as biomarkers to further distinguish patients with isocitrate dehydrogenase (IDH)-wildtype glioblastoma (GBM), which are heterogeneous with respect to clinical outcomes. We selected 41 candidate genes associated with overall survival (OS) using univariate Cox regression from IDH-wildtype GBM patients based on RNA sequencing (RNAseq) expression data from the Chinese Glioma Genome Atlas (CGGA, = 105) and The Cancer Genome Atlas (TCGA, = 139) cohorts. Next, a seven-gene-based risk signature was formulated according to Least Absolute Shrinkage and Selection Operator (LASSO) regression algorithm in the CGGA RNAseq database as a training set, while another 525 IDH-wildtype GBM patient TCGA datasets, consisting of RNA sequencing and microarray data, were used for validation. Patient survival in the low- and high-risk groups was calculated using Kaplan-Meier survival curve analysis and the log-rank test. Uni-and multivariate Cox regression analysis was used to assess the prognosis value. Gene oncology (GO) and gene set enrichment analysis (GSEA) were performed for the functional analysis of the seven-gene-based risk signature. We developed a seven-gene-based signature, which allocated each patient to a risk group (low or high). Patients in the high-risk group had dramatically shorter overall survival than their low-risk counterparts in three independent cohorts. Univariate and multivariate analysis showed that the seven-gene signature remained an independent prognostic factor. Moreover, the seven-gene risk signature exhibited a striking prognostic validity, with AUC of 78.4 and 73.9%, which was higher than for traditional "age" (53.7%, 62.4%) and "GBM sub-type" (57.7%, 52.9%) in the CGGA- and TCGA-RNAseq databases, respectively. Subsequent bioinformatics analysis predicted that the seven-gene signature was involved in the inflammatory response, immune response, cell adhesion, and apoptotic process. Our findings indicate that the seven-gene signature could be a potential prognostic biomarker. This study refined the current classification system of IDH-wildtype GBM and may provide a novel perspective for the research and individual therapy of IDH-wildtype GBM.
在本研究中，我们旨在确定可能作为生物标志物的候选基因，以进一步区分异柠檬酸脱氢酶（IDH）野生型胶质母细胞瘤（GBM）患者，这类患者的临床预后存在异质性。我们基于来自中国胶质瘤基因组图谱（CGGA，n = 105）和癌症基因组图谱（TCGA，n = 139）队列的RNA测序（RNAseq）表达数据，使用单变量Cox回归从IDH野生型GBM患者中选择了41个与总生存期（OS）相关的候选基因。接下来，在CGGA RNAseq数据库中根据最小绝对收缩和选择算子（LASSO）回归算法构建了一个基于七基因的风险特征作为训练集，同时使用另外525个由RNA测序和微阵列数据组成的IDH野生型GBM患者TCGA数据集进行验证。使用Kaplan-Meier生存曲线分析和对数秩检验计算低风险和高风险组患者的生存率。使用单变量和多变量Cox回归分析评估预后价值。对基于七基因的风险特征进行基因本体论（GO）和基因集富集分析（GSEA）以进行功能分析。我们构建了一个基于七基因的特征，将每位患者分配到一个风险组（低风险或高风险）。在三个独立队列中，高风险组患者的总生存期明显短于低风险组患者。单变量和多变量分析表明，七基因特征仍然是一个独立的预后因素。此外，七基因风险特征表现出显著的预后有效性，CGGA和TCGA-RNAseq数据库中的AUC分别为78.4%和73.9%，高于传统的“年龄”（53.7%，62.4%）和“GBM亚型”（57.7%，52.9%）。随后的生物信息学分析预测，七基因特征参与炎症反应、免疫反应、细胞粘附和凋亡过程。我们的研究结果表明，七基因特征可能是一种潜在的预后生物标志物。本研究完善了当前IDH野生型GBM的分类系统，可能为IDH野生型GBM的研究和个体化治疗提供新的视角。
