Radiogenomics by Proton Magnetic Resonance Spectroscopy: Integrative Analysis of Metabolites and Genome-wide Expression in Glioblastomas
Dieter Henrik Heiland1, Thomas Lange2, Ralf Schwarzwald3, Dietmar Pfeifer4, Karl Egger3, Horst Urbach3, Astrid Weyerbrock1, and Irina Mader3

1Dept. of Neurosurgery, University Medical Center Freiburg, Freiburg, Germany, 2Dept. MR Physics, Dept. of Radiology, University Medical Center Freiburg, Freiburg, Germany, 3Dept. of Neuroradiology, University Medical Center Freiburg, Freiburg, Germany, 4Department of Hematology, Oncology and Stem Cell Transplantation, University Medical Center Freiburg, Freiburg, Germany

Synopsis

The purpose of this work was to search for a connection between metabolites observed by proton magnetic resonance spectroscopy of glioblastomas and tumor genetics. Two specific pathways could be identified, one belonging to NAA and discriminating an astroglial versus oligo/neural subgroup. Another one was related to Cr also distinguishing between two subgroups, one attributed to apoptosis and another one to the PI3K-AKT-mTOR signaling cascade.

Purpose

Connections between magnetic resonance imaging of glioblastomas and tumor genetics have previously been described 1, 2. A correlation between the choline concentration as measured with proton magnetic resonance spectroscopy (MRS) and a calcium-sensing receptor expression in breast cancer has also recently been shown 3. The purpose of this study was to find out whether metabolite concentrations obtained by proton MRS are also related to tumor genetics of glioblastomas.

Methods

Fifteen patients with glioblastomas receiving presurgical proton MRS (2D CSI, PRESS, TR=1.5s, TE=30ms, voxel size 1x1x1.5cm3) were investigated on a 3T system. Quantification was performed by LCModel 4, e.g. Figure 1, and ipsilateral/contralateral metabolite ratios were determined. Tumor samples were obtained at a predefined region (contrast-enhancing tumor, controlled by neuro-navigation). RNA was extracted and analyzed by gene-expression array (Affymetrix HuGene 2.0). Positively and negatively correlated genes (r>0.8, p<0.05) were extracted and unsupervised clustered to identify expression-based subgroups. Gene ontology analysis was performed and visualized in networks build by Cytoscape 2.0, Figure 2. Gene-set-enrichment analysis (GSEA) was performed to identify subgroup-specific pathway activation (Figures 3 and 4). All analysis was done in individually designed r-software based pipelines including bioconductor packages. As clinical data, the progression-free survival (PFS) was taken and analyzed by Kaplan-Meier statistics. All p-values given are corrected by false discovery rate.

Results

N-acetylaspartate [“NAA”, sum of (NAA +NAAG)] in contrast-enhancing tumor was positively correlated (r=0.45, p<0.05) to progression-free survival. Cluster analysis and Gene Set Enrichment Analysis (GSEA) identified an expression subgroup corresponding to lower NAA signal intensity. This subgroup had a significant enrichment of astroglial genes and pro-oncogenetic pathways as KRAS (p<0.01), JAK/STAT (p<0.01) and EGF (p<0.01). A subgroup with higher NAA signal intensities corresponding to gene expression showed a high enrichment of oligodendrocyte and neural signature genes and activation of pro-apoptotic pathways as p53 (p<0.001). Kaplan-Meier statistics of both subgroups with corresponding low/high NAA signal intensity showed significant PFS differences of both groups (p=0.01, Figure 3).

According to creatine (Cr) in contrast-enhancing tumor, two different subgroups of gene expression could be assigned. Lower Cr was accompanied by an activation of apoptosis, inflammation, and p53 as "the guardian of the genome", whereas higher Cr came along with MYK, PI3K-AKT-mTOR activation as response to necrosis. Survival analysis could not detect any significant difference (p=0.21, Figure 4).

Discussion

The fact that high levels of NAA correspond to an enrichment of oligo-neural genes is corroborated by the integrative work of Baslow showing oligodendrocytes as target of NAA in a tri-cellular metabolism pathway of NAA and NAAG 5.

Creatine comes into the brain by passing the blood-brain-barrier, where Cr transporters (CrT) are expressed and localized in the endothelial cells. Cr is actively transported into the extracellular space by neurons and oligodendrocytes (cells expressing CrT), but not by astrocytes. Besides this specific preference of cells, Cr is also thought to have a neuroprotective effect 6.

In conclusion, the gene expression of the investigated glioblastomas is mirrored by the metabolites NAA and Cr, and their abundance to neurons, oligodendrocytes and astrocytes.

Acknowledgements

The authors thank Mr. Hansjörg Mast for his help with the acquisition of the data.

References

1 Diehn, M., et al., Identification of noninvasive imaging surrogates for brain tumor gene-expression modules. Proc Natl Acad Sci U S A, 2008. 105(13): p. 5213-8.

2 Jamshidi, N., et al., Illuminating radiogenomic characteristics of glioblastoma multiforme through integration of MR imaging, messenger RNA expression, and DNA copy number variation. Radiology, 2014. 270(1): p. 1-2.

3 Baio, G., et al., Correlation between Choline Peak at MR Spectroscopy and Calcium-Sensing Receptor Expression Level in Breast Cancer: A Preliminary Clinical Study. Mol Imaging Biol, 2015. 17(4): p. 548-56.

4 Provencher, S.W., Estimation of metabolite concentrations from localized in vivo proton NMR spectra. Magn Reson Med, 1993. 30(6): p. 672-9.

5 Baslow, M.H., Evidence that the tri-cellular metabolism of N-acetylaspartate functions as the brain's "operating system": how NAA metabolism supports meaningful intercellular frequency-encoded communications. Amino Acids, 2010. 39(5): p. 1139-45.

6 Andres, R.H., et al., Functions and effects of creatine in the central nervous system. Brain Res Bull, 2008. 76(4): p. 329-43.

Figures

Exemplary spectrum and the tumor area where the spectrum was selected from (red star on the right image).

This gene ontology plot displays an overview of genes being significantly correlated with NAA (left) and Cr (right) and their affiliation to specific tasks, respectively.

In this integrative analysis, NAA metabolism and gene expression have been combined to identify specific pathways such as astroglial or oligo/neural. (a) Unsupervised cluster of gene expression, (b) Volcano plot to demonstrate different enrichment of signature genes, (c) Kaplan-Meier plot with progression-free survival.


This integrative analysis demonstrates the combination of the metabolism of Cr and a gene expression analysis that indicate different genetic pathways (apoptotic or AKT/PI3K). (a) Unsupervised cluster of gene expression, (b) Volcano plot with enrichment of pathway specific target genes, (c) Kaplan-Meier plot with progression free survival.



Proc. Intl. Soc. Mag. Reson. Med. 24 (2016)
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