The proneural molecular signature is enriched in oligodendrogliomas and predicts improved survival among diffuse gliomas.
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.
Cooper
Lee A D
LA
Center for Comprehensive Informatics, Emory University, Atlanta, Georgia, United States of America.
Gutman
David A
DA
Long
Qi
Q
Johnson
Brent A
BA
Cholleti
Sharath R
SR
Kurc
Tahsin
T
Saltz
Joel H
JH
Brat
Daniel J
DJ
Moreno
Carlos S
CS
D000328:Adult; D000368:Aged; D014408:Biomarkers, Tumor / Q000235:genetics; D001932:Brain Neoplasms / Q000235:genetics / Q000401:mortality* / Q000473:pathology; D030561:Databases, Nucleic Acid; D005260:Female; D020869:Gene Expression Profiling; D015972:Gene Expression Regulation, Neoplastic; D005910:Glioma / Q000235:genetics / Q000401:mortality* / Q000473:pathology; D006801:Humans; D008297:Male; D008875:Middle Aged; D009837:Oligodendroglioma / Q000235:genetics* / Q000401:mortality / Q000473:pathology; D020411:Oligonucleotide Array Sequence Analysis; D016019:Survival Analysis
D014408:Biomarkers, Tumor