Center for Comprehensive Informatics, Emory University, Atlanta, Georgia, United States of America.
PLoS One. 2010 Sep 3;5(9):e12548. doi: 10.1371/journal.pone.0012548.
The Cancer Genome Atlas Project (TCGA) has produced an extensive collection of '-omic' data on glioblastoma (GBM), resulting in several key insights on expression signatures. Despite the richness of TCGA GBM data, the absence of lower grade gliomas in this data set prevents analysis genes related to progression and the uncovering of predictive signatures. A complementary dataset exists in the form of the NCI Repository for Molecular Brain Neoplasia Data (Rembrandt), which contains molecular and clinical data for diffuse gliomas across the full spectrum of histologic class and grade. Here we present an investigation of the significance of the TCGA consortium's expression classification when applied to Rembrandt gliomas. We demonstrate that the proneural signature predicts improved clinical outcome among 176 Rembrandt gliomas that includes all histologies and grades, including GBMs (log rank test p = 1.16e-6), but also among 75 grade II and grade III samples (p = 2.65e-4). This gene expression signature was enriched in tumors with oligodendroglioma histology and also predicted improved survival in this tumor type (n = 43, p = 1.25e-4). Thus, expression signatures identified in the TCGA analysis of GBMs also have intrinsic prognostic value for lower grade oligodendrogliomas, and likely represent important differences in tumor biology with implications for treatment and therapy. Integrated DNA and RNA analysis of low-grade and high-grade proneural gliomas identified increased expression and gene amplification of several genes including GLIS3, TGFB2, TNC, AURKA, and VEGFA in proneural GBMs, with corresponding loss of DLL3 and HEY2. Pathway analysis highlights the importance of the Notch and Hedgehog pathways in the proneural subtype. This demonstrates that the expression signatures identified in the TCGA analysis of GBMs also have intrinsic prognostic value for low-grade oligodendrogliomas, and likely represent important differences in tumor biology with implications for treatment and therapy.
癌症基因组图谱计划(TCGA)已经生成了大量关于胶质母细胞瘤(GBM)的“组学”数据,这些数据为表达特征提供了一些重要的见解。尽管 TCGA GBM 数据非常丰富,但该数据集中缺乏低级别胶质瘤,这使得无法分析与进展相关的基因,并揭示预测性特征。以 NCI 分子脑肿瘤数据库(Rembrandt)的形式存在一个互补的数据集,其中包含弥漫性神经胶质瘤的分子和临床数据,涵盖了组织学和分级的全谱。在这里,我们研究了 TCGA 联盟的表达分类在 Rembrandt 神经胶质瘤中的应用意义。我们证明,在包括所有组织学和分级的 176 例 Rembrandt 神经胶质瘤中,神经前体细胞特征预示着更好的临床结局(对数秩检验,p=1.16e-6),但在 75 例 2 级和 3 级样本中也存在(p=2.65e-4)。这种基因表达特征在少突胶质细胞瘤组织学的肿瘤中更为丰富,也预示着这种肿瘤类型的生存改善(n=43,p=1.25e-4)。因此,在 TCGA 对 GBM 的分析中确定的表达特征对低级别少突胶质细胞瘤也具有内在的预后价值,并且可能代表着肿瘤生物学的重要差异,这对治疗和疗法具有重要意义。低级别和高级别神经前体细胞神经胶质瘤的整合 DNA 和 RNA 分析表明,在神经前体细胞 GBM 中,GLIS3、TGFB2、TNC、AURKA 和 VEGFA 等几个基因的表达和基因扩增增加,而 DLL3 和 HEY2 则相应减少。通路分析突出了 Notch 和 Hedgehog 通路在神经前体细胞亚群中的重要性。这表明,在 TCGA 对 GBM 的分析中确定的表达特征对低级别少突胶质细胞瘤也具有内在的预后价值,并且可能代表着肿瘤生物学的重要差异,这对治疗和疗法具有重要意义。