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Classification of IDH and TP53 Mutational Subgroups of High-Grade Astrocytic Gliomas Based on Magnetic Resonance Spectroscopy at 3T1Institute of Biomedical Engineering, Bogazici University, Istanbul, Turkey, 2Department of Biomedical Device Technologies, Acibadem Mehmet Ali Aydinlar University, Istanbul, Turkey, 3Neuroradiology Research Center, Acıbadem Mehmet Ali Aydinlar University, Istanbul, Turkey, 4Department of Molecular Biology and Genetics, Acibadem Mehmet Ali Aydinlar University, Istanbul, Turkey, 5Department of Neurosurgery, Acibadem Mehmet Ali Aydinlar University, Istanbul, Turkey, 6Neuroradiology Research Center, Acibadem Mehmet Ali Aydinlar University, Istanbul, Turkey, 7Department of Radiology, Acibadem Mehmet Ali Aydinlar University, Istanbul, Turkey
Synopsis
The goal of this study is to define MR spectroscopic differences of high-grade astrocytic glioma subgroups classified by IDH and TP53 mutations at 3T. TP-53 mutated (TP53-mut) and TP53 wild-type (TP53-wt) gliomas had similar metabolic profiles. IDH mutation (IDH-mut) was the main factor contributing to the metabolic differences between IDH and TP53 mutational subgroups. IDH-mut/TP53-mut gliomas had lower Glyc (P=0.017), GSH (P=0.009), Glu (P=0.038), and Glx (P=0.002) than IDH-wt/TP53-mut gliomas. Gliomas who were IDH wild-type (IDH-wt) and TP53-mut had the highest Glu, Glyc, GSH, and Glx among all high-grade astrocytic gliomas, which might be indicators of poor overall survival.
PURPOSE
Isocitrate dehydrogenase (IDH), telomerase reverse transcriptase (TERT) promoter, and tumor protein p53 (TP53) mutations, and 1p/19q codeletion have been indicated as important biomarkers in determining glioma survival1-4. IDH mutant (IDH-mut) gliomas have better treatment response and longer survival than IDH-wild type (IDH-wt) tumors5, 6. On the other hand, TP53 is a tumor suppressor gene, whose mutation causes an accumulation of p53 protein on tumor site. TP53 mutation and 1p/19q codeletion are almost mutually exclusive, and they indicate astrocytic and oligodendroglial subtypes, respectively. Ogura et al. reported that p53 overexpression was not alone an indicator for predicting prognosis, but for glioblastoma multiforme (GBM) or anaplastic astrocytoma (AA) patients having IDH-1 wild type and negative O6-methylguanine DNA methyltransferase (MGMT) profiles, an overexpression of p53 was strongly associated with worse overall survival3. Magnetic resonance spectroscopy provides biomarkers of cellular metabolism, and previous studies have reported higher 2-hydroxyglutarate (2HG)7, 8, and lower glutamate (Glu)9 and glutathione (GSH)10 in IDH-mut gliomas than IDH-wt patients. The aim of this study is to define MR spectroscopic differences of astrocytic high-grade glioma groups classified by both IDH and TP53 mutations at 3T.METHODS
A total of 58 patients diagnosed with a glioblastoma multiforme (GBM) or anaplastic astrocytoma (AA) (40M/18F, mean age: 47.05±14.22 years, range: 20-74 years, 31 GBM, 27 AA) were scanned a day before surgery at a Siemens Tim Trio clinical 3T scanner (Erlangen, Germany) by using a 32-channel head coil. Magnetic resonance spectroscopy data was acquired from the solid tumor region excluding gross hemorrhage, edema and necrosis using a Point Resolved Spectroscopy (PRESS) sequence (TR=2000 ms, TE=30ms, 1024 points, 1200 Hz, voxel size= 10x10x10 mm3, NSA= 192, acquisition time=6.5 min). Nineteen MR spectroscopic peak concentrations, including glutamate (Glu), glutamine (Gln), glycine (Glyc), 2-hydroxyglutarate (2HG), glutathione (GSH), myo-inositol (Ins), and lactate (Lac), and six composite peak concentrations, including total choline (GPC+PCh, tCho), total creatine (Cr+PCr, tCr), glutamate-glutamine complex (Glx), and total NAA (NAA+NAAG, tNAA), were quantified for each spectrum using LCModel11. Any metabolite that was not quantifiable in more than 30% of the patients and any metabolite of a given spectrum with a Cramer-Rao lower bound (CRLB) of more than 30 were excluded from the analysis. IDH mutations and TP53 expression were determined using immunohistochemistry and minisequencing. A Kruskal-Wallis test followed by pairwise multiple comparison Tukey-Kramer test was used to identify statistically significant MR spectroscopic differences between the four IDH and TP53 mutational subgroups of gliomas (IDH-mut/TP53 mutant (TP53-mut), IDH-wt/TP53-mut, IDH-mut/TP53 wild type (TP53-wt), and IDH-wt/TP53-wt).RESULTS
Figure 1 shows short-TE PRESS data along with the LCModel results and IDH (d), Ki-67 (e), and hematoxylin and eosin (f) staining of a IDH-wt/TP53-wt GBM respectively. TP53-mut gliomas had lower tCr, tNAA, Glyc, and GSH, and higher Lac than TP53-wt gliomas, but none of these metabolic differences were statistically significant. Table 1 shows the metabolic differences between different subgroups of IDH mutation and p53 overexpression status in high-grade astrocytic gliomas. IDH-wt/TP53-mut gliomas had the highest Glu, Glyc, GSH, and Glx among all GBM or AA patients (P<0.05). These patients also had the highest Gln, but it was not statistically significant. In pairwise comparisons, IDH-mut/TP53-mut gliomas had a statistically significantly lower Glyc (P=0.017), GSH (P=0.009), Glu (P=0.038), and Glx (P=0.002) than IDH-wt/TP53-mut, and lower GSH (P=0.05) and Glx (P=0.037) than IDH-wt/TP53-wt gliomas. IDH-mut/TP53-wt gliomas had lower Glu (P=0.013) and Glx (P=0.021) than IDH-wt/TP53-mut gliomas.DISCUSSION
No metabolic differences were found between TP53 mutated and wild-type gliomas, indicating that IDH mutation was the main factor in metabolic differences between different TP53 and IDH mutational subgroups of high-grade astrocytic gliomas. Besides well-reported 2HG, our study indicated the importance of Glyc, GSH, Glu, and Glx in identification of IDH-mut gliomas. TP53 is a tumor suppressor gene, which is one of the first mutations identified in cancer. In our study, we have identified that IDH-wt GBM and AA patients having a p53 overexpression had the highest Glu, Glx, Glyc, and GSH, which might be indicators of poor overall survival in high-grade astrocytic gliomas.CONCLUSION
Short-TE MRS is a clinically useful tool in identifying metabolic profile differences between high-grade astrocytic glioma subgroups defined by IDH and TP53 mutations. Future studies will explore the utility of machine-learning algorithms for classifying these subgroups based on MRS profiles at 3T.Acknowledgements
This research was supported by TUBITAK 1003 grant 216S432.References
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