Research Papers:
Integrative radiogenomic analysis for multicentric radiophenotype in glioblastoma
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Abstract
Doo-Sik Kong1,2,3,4, Jinkuk Kim2,3,4, In-Hee Lee2,3,4, Sung Tae Kim5, Ho Jun Seol1, Jung-Il Lee1, Woong-Yang Park6, Gyuha Ryu7, Zichen Wang7, Avi Ma’ayan7, Do-Hyun Nam1,2,3,4
1Department of Neurosurgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea
2Samsung Biomedical Research Institute, Samsung Medical Center, Seoul, Korea
3Institute for Refractory Cancer Research, Samsung Medical Center, Seoul, Korea
4Samsung Advanced Institute of Technology, Samsung Electronics Co., Ltd., Seoul, Korea
5Department of Radiology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea
6Samsung Genome Institute, Samsung Medical Center, Seoul, Korea
7Department of Pharmacology and Systems Therapeutics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
Correspondence to:
Do-Hyun Nam, e-mail: [email protected]
Keywords: glioblastoma, radiogenomic, multicentric
Received: September 29, 2015 Accepted: January 18, 2016 Published: February 01, 2016
ABSTRACT
We postulated that multicentric glioblastoma (GBM) represents more invasiveness form than solitary GBM and has their own genomic characteristics. From May 2004 to June 2010 we retrospectively identified 51 treatment-naïve GBM patients with available clinical information from the Samsung Medical Center data registry. Multicentricity of the tumor was defined as the presence of multiple foci on the T1 contrast enhancement of MR images or having high signal for multiple lesions without contiguity of each other on the FLAIR image. Kaplan-Meier survival analysis demonstrated that multicentric GBM had worse prognosis than solitary GBM (median, 16.03 vs. 20.57 months, p < 0.05). Copy number variation (CNV) analysis revealed there was an increase in 11 regions, and a decrease in 17 regions, in the multicentric GBM. Gene expression profiling identified 738 genes to be increased and 623 genes to be decreased in the multicentric radiophenotype (p < 0.001). Integration of the CNV and expression datasets identified twelve representative genes: CPM, LANCL2, LAMP1, GAS6, DCUN1D2, CDK4, AGAP2, TSPAN33, PDLIM1, CLDN12, and GTPBP10 having high correlation across CNV, gene expression and patient outcome. Network and enrichment analyses showed that the multicentric tumor had elevated fibrotic signaling pathways compared with a more proliferative and mitogenic signal in the solitary tumors. Noninvasive radiological imaging together with integrative radiogenomic analysis can provide an important tool in helping to advance personalized therapy for the more clinically aggressive subset of GBM.
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