IDH1
胶质瘤
异柠檬酸脱氢酶
医学
突变
内科学
生物
肿瘤科
胶质母细胞瘤
癌症研究
IDH2型
突变体
比例危险模型
生存分析
基因型
ATRX公司
队列
遗传学
等位基因
作者
Zhao Wang,Xiaomeng Liu,Zhaoshi Bao,Wei Zhang,Chuanbao Zhang,Tao Jiang
出处
期刊:Current Molecular Medicine
[Bentham Science]
日期:2018-03-09
卷期号:17 (7): 518-526
被引量:1
标识
DOI:10.2174/1566524018666180212151429
摘要
Background Isocitrate dehydrogenase (IDH) mutation is the initiating event that defines major clinical and prognostic classes of gliomas, but the potential mechanisms have not been well interpreted yet. The main objective of the current study was to better understand the underlying biology of IDH mutant gliomas as captured by gene expression profiles. Methods RNA sequencing data of WHO grade II-IV gliomas from the Chinese Glioma Genome Atlas (CGGA, N=325) were used to assess differentially expressed genes between IDH mutant and wild type gliomas and to construct a gene expression-based classifier to detect IDH mutant samples with high sensitivity and specificity. The classifier was validated in independent RNA sequencing data from the Cancer Genome Atlas (TCGA, N=699), and the prognostic value of the classifier was also assessed in the two datasets. Results A 58-gene-pair IDH mutation signature was developed by using the top scoring pairs algorithm. In CGGA dataset, 98.5% and 100% IDH mutant samples were also predicted to be mutant by gene expression based IDH status in grade II-III and grade IV gliomas, respectively. In TCGA dataset, the proportions were 99.8% and 100%, respectively. The signature remained to be a prognostic marker in multivariate cox analysis both in CGGA and TCGA datasets. Conclusion A characteristic gene expression signature is associated with and accurately predicts IDH mutation status. This suggests a common biology between these tumors and adds prognostic and biologic information that is not captured by the mutation status alone. These results may help in population stratification for clinical trials. As RNA-seq is more and more prevalent and cost-effective in glioma molecular diagnosis, this gene signature would provide a precise method to predict IDH mutation status with RNA-seq data.
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