The Eli and Edythe L. Broad Institute of Massachusetts Institute of Technology and Harvard University, Cambridge, MA 02142, USA.
Cancer Cell. 2010 Jan 19;17(1):98-110. doi: 10.1016/j.ccr.2009.12.020.
The Cancer Genome Atlas Network recently cataloged recurrent genomic abnormalities in glioblastoma multiforme (GBM). We describe a robust gene expression-based molecular classification of GBM into Proneural, Neural, Classical, and Mesenchymal subtypes and integrate multidimensional genomic data to establish patterns of somatic mutations and DNA copy number. Aberrations and gene expression of EGFR, NF1, and PDGFRA/IDH1 each define the Classical, Mesenchymal, and Proneural subtypes, respectively. Gene signatures of normal brain cell types show a strong relationship between subtypes and different neural lineages. Additionally, response to aggressive therapy differs by subtype, with the greatest benefit in the Classical subtype and no benefit in the Proneural subtype. We provide a framework that unifies transcriptomic and genomic dimensions for GBM molecular stratification with important implications for future studies.
癌症基因组图谱网络(The Cancer Genome Atlas Network)最近对胶质母细胞瘤(glioblastoma multiforme,GBM)中的复发性基因组异常进行了编目。我们描述了一种强大的基于基因表达的胶质母细胞瘤分子分类方法,将其分为神经前体细胞型、神经型、经典型和间质型,并整合多维基因组数据来建立体细胞突变和 DNA 拷贝数的模式。表皮生长因子受体(EGFR)、神经纤维瘤 1 型(NF1)和血小板衍生生长因子受体 A/异柠檬酸脱氢酶 1(PDGFRA/IDH1)的异常和基因表达分别定义了经典型、间质型和神经前体细胞型。正常脑细胞类型的基因特征显示出亚型与不同神经谱系之间的强烈关系。此外,不同亚型对侵袭性治疗的反应也不同,经典型亚型获益最大,神经前体细胞型则没有获益。我们提供了一个框架,将转录组和基因组维度统一起来,对胶质母细胞瘤进行分子分层,这对未来的研究具有重要意义。
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