Illuminating radiogenomic characteristics of glioblastoma multiforme through integration of MR imaging, messenger RNA expression, and DNA copy number variation.
OBJECTIVE
To perform a multilevel radiogenomics study to elucidate the glioblastoma multiforme (GBM) magnetic resonance (MR) imaging radiogenomic signatures resulting from changes in messenger RNA (mRNA) expression and DNA copy number variation (CNV).


METHODS
Radiogenomic analysis was performed at MR imaging in 23 patients with GBM in this retrospective institutional review board-approved HIPAA-compliant study. Six MR imaging features-contrast enhancement, necrosis, contrast-to-necrosis ratio, infiltrative versus edematous T2 abnormality, mass effect, and subventricular zone (SVZ) involvement-were independently evaluated and correlated with matched genomic profiles (global mRNA expression and DNA copy number profiles) in a significant manner that also accounted for multiple hypothesis testing by using gene set enrichment analysis (GSEA), resampling statistics, and analysis of variance to gain further insight into the radiogenomic signatures in patients with GBM.


RESULTS
GSEA was used to identify various oncogenic pathways with MR imaging features. Correlations between 34 gene loci were identified that showed concordant variations in gene dose and mRNA expression, resulting in an MR imaging, mRNA, and CNV radiogenomic association map for GBM. A few of the identified gene-to-trait associations include association of the contrast-to-necrosis ratio with KLK3 and RUNX3; association of SVZ involvement with Ras oncogene family members, such as RAP2A, and the metabolic enzyme TYMS; and association of vasogenic edema with the oncogene FOXP1 and PIK3IP1, which is a member of the PI3K signaling network.


CONCLUSIONS
Construction of an MR imaging, mRNA, and CNV radiogenomic association map has led to identification of MR traits that are associated with some known high-grade glioma biomarkers and association with genomic biomarkers that have been identified for other malignancies but not GBM. Thus, the traits and genes identified on this map highlight new candidate radiogenomic biomarkers for further evaluation in future studies.
From the Department of Radiological Sciences, UCLA School of Medicine, Box 951721, CHS 17-135, Los Angeles, CA 90095-1721 (N.J., M.D.K.); Institute for Stem Cell Biology and Regenerative Medicine, Stanford University, Palo Alto, Calif (M.D.); and Department of Radiation Oncology, University of Alabama at Birmingham School of Medicine, Birmingham, Ala (M.B.).
Neema
N
Jamshidi
Maximilian
M
Diehn
Markus
M
Bredel
Michael D
MD
Kuo
D000368:Aged; D001932:Brain Neoplasms / Q000175:diagnosis* / Q000235:genetics*; D056915:DNA Copy Number Variations; D005260:Female; D005909:Glioblastoma / Q000175:diagnosis* / Q000235:genetics*; D006801:Humans; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008297:Male; D008875:Middle Aged; D012333:RNA, Messenger / Q000235:genetics*; D012189:Retrospective Studies
D012333:RNA, Messenger