Abstract 808: Intrinsic gene expression profiles of gliomas are a better predictor of survival than histology

Abstract

Abstract Gliomas are the most common primary brain tumors with heterogeneous morphology and variable prognosis. Treatment decisions in patients rely mainly on histological classification and clinical parameters. However, differences between histological subclasses and grades are subtle, and classifying gliomas is subject to a large inter-observer variability. To improve current classification standards, we have performed gene expression profiling on a large cohort of glioma samples of all histological subtypes and grades. We identified seven distinct molecular subgroups that correlate with survival. These include two favorable prognostic subgroups (median survival >4.7 years), two with intermediate prognosis (median survival 1-4 years), two with poor prognosis (median survival <1 year), and one control group. The intrinsic molecular subtypes of glioma are different from histological subgroups and correlate better to patient survival. The prognostic value of molecular subgroups was validated on five independent sample cohorts (TCGA, REMBRANDT, GSE12907, GSE4271, and Li et al.). The power of intrinsic subtyping is demonstrated by its ability to identify a subset of prognostically favorable tumors within an external dataset that contains only histologically confirmed glioblastomas. Specific genetic changes (EGFR amplification, IDH1 mutation, 1p/19q LOH) segregate in distinct molecular subgroups. We identified a subgroup with molecular features associated with secondary glioblastoma, suggesting that different genetic changes drive gene expression profiles. Finally, we assessed response to treatment in molecular subgroups. Our data provides compelling evidence that expression profiling is a more accurate and objective method to classify gliomas than histological classification. Molecular classification therefore may aid diagnosis and can guide clinical decision making. Note: This abstract was not presented at the AACR 101st Annual Meeting 2010 because the presenter was unable to attend. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 808.