Download Abstract - Cancer Imaging Archive Wiki

Presentation Abstract
Title:
eP-94 - Radiogenogram: MR Imaging as a Screening Tool for Uncovering Novel
Genomic Drug Targets
Keywords: Glioblastoma; genomics; radiogenomics
Authors:
Colen, R. R.1·Sathyan, P.2·Jolesz, F. A.1·Zinn, P. O.2
1
Brigham and Women's Hospital, Boston, MA, 2M.D. Anderson Cancer Center,
Houston, TX.
Abstract
Body:
Purpose
To validate MRI as a screen tool to screen for glioblastoma genomic targets in order
for subsequent pharmaceutical development of therapeutic gene targets. Recent
genomic data are overwhelmingly vast; and, for the most part, clinical applicability
of such large discoveries remains indeterminate. Selecting a clinical meaningful
target to pursue after sifting through myriads of genomic data will not necessarily
result in a clinically applicable target for drug development; and, importantly, this
trial-and-error method is not cost-effective. Thus, these discoveries have resulted in
only limited advancements in GBM treatment.
Materials & Methods
We identified 78 treatment-naïve GBM patients from The Cancer Genome Atlas
(TCGA) who had both gene and microRNA expression profiles and pretreatment
MR neuroimaging. In each patient, a total of 13,628 genes (22,267 hybridization
probes) and 555 microRNAs (1,510 hybridization probes) were analyzed for
significance and differential fold regulation using Comparative Marker Selection
(Broad Institute, MIT, http://www.broadinstitute.org/cancer/software/genepattern/),
analyzed with Ingenuity Pathway Analysis (http://www.ingenuity.com), and then
associated with the imaging characteristics. Image data used in this research were
obtained from The Cancer Imaging Archive (http://cancerimagingarchive.net/)
sponsored by the Cancer Imaging Program, DCTD/NCI/NIH. Using 3D slicer
software 3.6 (http://www.slicer.org), FLAIR was used for segmentation of the
edema, and postcontrast T1-weighted imaging (T1WI) for segmentation of
enhancement (defined as tumor) and necrosis. Two neuroradiologists reviewed the
images in consensus. Affymetrix level 1 mRNA and Agilent level 2 microRNA data
were downloaded from the public TCGA dataportal (http://cancergenome.nih.gov/).
The Robust Multi-Array algorithm was used for normalization. The Kaplan Meier
method was used to calculate overall- and progression-free survival. Mean gene
expression across GBM subgroups was calculated using ANOVA and TukeyKramer tests. For gene and microRNA correlations we used R square statistics. All
calculations were performed in Microsoft Excel 2010 and JMP 9.01 (SAS Institute,
CA). In vitro and in vivo studies in mice were performed to confirm these genomic
targets.
Results
Our MRI screen identified top upregulated and down regulated genes and
microRNAs which were novel and not previously described in the literature. These
were concordant with the underlying biologic processes of edema/invasion,
necrosis, and enhancing tumor MRI phenotypes. Kaplan Meier analysis
demonstrated that these resulted in significantly decreased survival (P = 0.0008) and
shorter time to disease progression (P = 0.0009). In some cases, the gene expression
was a stronger prognostic variable than either molecular subtype (as defined by
Veerkak and colleagues) in the Cox proportional hazards ratio (P = 0.03). In vitro
and in vivo animal models as well as loss and gain of function models subsequently
confirmed the genomic target’s function which was concordant with the underlying
biologic processes measured by MRI.
Conclusion
MR imaging is an effective screening tool to uncover clinically meaningful genomic
targets that can be used in drug development of therapeutic targets for GBM
treatment. Furthermore, these might serve as better prognostic predictors than those
currently used.
American Society of Neuroradiology
2210 Midwest Road, Suite 207
Oak Brook, IL 60523-8205
Phone: (630) 574-0220
Fax: (630) 574-1740