Intrinsic Gene Expression Profiles of Gliomas are a Better Predictor of Survival than Histology. Homo sapiens

Histological classification of gliomas guides treatment decisions. Because of the high interobserver variability, we aimed to improve classification by performing gene expression profiling on a large cohort of glioma samples of all histological subtypes and grades. The seven identified intrinsic molecular subtypes are different from histological subgroups and correlate better to patient survival. Our data indicate that distinct molecular subgroups clearly benefit from treatment. Specific genetic changes (EGFR amplification, IDH1 mutation, 1p/19q LOH) segregate in -and may drive- the distinct molecular subgroups. Our findings were validated on three large independent sample cohorts (TCGA, REMBRANDT, and GSE12907). We provide compelling evidence that expression profiling is a more accurate and objective method to classify gliomas than histology. Overall design: 276 glioma samples of all histology, 8 control samples

神经胶质瘤（glioma）的组织学分型是指导临床治疗决策的核心依据。鉴于该分型存在较高的观察者间变异（interobserver variability），本研究旨在通过对涵盖所有组织学亚型与分级的大型胶质瘤样本队列开展基因表达谱分析（gene expression profiling），优化胶质瘤的分类方案。本研究鉴定出7种固有分子亚型，这些亚型与组织学亚组存在显著差异，且与患者生存期的相关性更强。本研究数据表明，不同的分子亚组患者可从治疗中获得明确的临床获益。特定遗传改变（表皮生长因子受体扩增（EGFR amplification）、异柠檬酸脱氢酶1突变（IDH1 mutation）、1p/19q杂合性缺失（1p/19q LOH））在不同分子亚组中呈特征性分布，并可能驱动这些亚组的形成。本研究的结论已在三个大型独立样本队列（TCGA、REMBRANDT及GSE12907）中得到验证。本研究提供了充分且有力的证据，证明基因表达谱分析相较于组织学分型，是一种更为精准且客观的胶质瘤分类手段。实验整体设计：纳入涵盖所有组织学类型的276例胶质瘤样本与8例对照样本。