The Proneural Molecular Signature Is Enriched in Oligodendrogliomas and Predicts Improved Survival among Diffuse Gliomas

• Type of Material: Article
• Authors: Lee Cooper, Emory University; David Andrew Gutman, Emory University; Qi Long, Emory University; Brent Johnson, Emory University; Sharath R Cholleti, Emory University; Tahsin M Kurc, Emory University; Joel H Saltz, Emory University; Daniel J Brat, Emory University; Carlos S Moreno, Emory University
• Language: English
• Date: 2010-09-03
• Publisher: Public Library of Science
• Publication Version: Final Published Version
• Copyright Statement: © Cooper et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
• License: Creative Commons Attribution 4.0 International
• Final Published Version (URL): http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0012548
• Title of Journal or Parent Work: PLoS ONE
• Volume: 5
• Issue: 9
• Grant/Funding Information: This work was supported in part by contract S09-094 from the National Cancer Institute (NCI) administered through NCI Science Applications International Corporation (SAIC) Frederick campus, and the Center for Comprehensive Informatics, Emory University.; The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
• Research Categories: Chemistry, Biochemistry

Abstract

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.