Zhang Chuan-Bao, Zhu Ping, Yang Pei, Cai Jin-Quan, Wang Zhi-Liang, Li Qing-Bin, Bao Zhao-Shi, Zhang Wei, Jiang Tao
Department of Molecular Neuropathology, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China.
Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.
Oncotarget. 2015 Nov 3;6(34):36643-51. doi: 10.18632/oncotarget.5421.
Anaplastic gliomas are characterized by variable clinical and genetic features, but there are few studies focusing on the substratification of anaplastic gliomas. To identify a more objective and applicable classification of anaplastic gliomas, we analyzed whole genome mRNA expression profiling of four independent datasets. Univariate Cox regression, linear risk score formula and receiver operating characteristic (ROC) curve were applied to derive a gene signature with best prognostic performance. The corresponding clinical and molecular information were further analyzed for interpretation of the different prognosis and the independence of the signature. Gene ontology (GO), Gene Set Variation Analysis (GSVA) and Gene Set Enrichment Analysis (GSEA) were performed for functional annotation of the differences. We found a three-gene signature, by applying which, the anaplastic gliomas could be divided into low risk and high risk groups. The two groups showed a high concordance with grade II and grade IV gliomas, respectively. The high risk group was more aggressive and complex. The three-gene signature showed diagnostic and prognostic value in anaplastic gliomas.
间变性胶质瘤具有多样的临床和遗传特征,但针对间变性胶质瘤分层的研究较少。为了确定一种更客观且适用的间变性胶质瘤分类方法,我们分析了四个独立数据集的全基因组mRNA表达谱。应用单变量Cox回归、线性风险评分公式和受试者工作特征(ROC)曲线来得出具有最佳预后性能的基因特征。进一步分析相应的临床和分子信息,以解释不同的预后情况以及该特征的独立性。进行基因本体(GO)、基因集变异分析(GSVA)和基因集富集分析(GSEA)以对差异进行功能注释。我们发现了一个三基因特征,通过应用该特征,可将间变性胶质瘤分为低风险组和高风险组。这两组分别与II级和IV级胶质瘤高度一致。高风险组更具侵袭性且更为复杂。该三基因特征在间变性胶质瘤中显示出诊断和预后价值。