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. 2021 Feb:122:23-41.
doi: 10.1016/j.pnmrs.2020.11.001. Epub 2020 Dec 2.

Magnetic resonance spectroscopy for the study of cns malignancies

Affiliations

Magnetic resonance spectroscopy for the study of cns malignancies

Victor Ruiz-Rodado et al. Prog Nucl Magn Reson Spectrosc. 2021 Feb.

Abstract

Despite intensive research, brain tumors are amongst the malignancies with the worst prognosis; therefore, a prompt diagnosis and thoughtful assessment of the disease is required. The resistance of brain tumors to most forms of conventional therapy has led researchers to explore the underlying biology in search of new vulnerabilities and biomarkers. The unique metabolism of brain tumors represents one potential vulnerability and the basis for a system of classification. Profiling this aberrant metabolism requires a method to accurately measure and report differences in metabolite concentrations. Magnetic resonance-based techniques provide a framework for examining tumor tissue and the evolution of disease. Nuclear Magnetic Resonance (NMR) analysis of biofluids collected from patients suffering from brain cancer can provide biological information about disease status. In particular, urine and plasma can serve to monitor the evolution of disease through the changes observed in the metabolic profiles. Moreover, cerebrospinal fluid can be utilized as a direct reporter of cerebral activity since it carries the chemicals exchanged with the brain tissue and the tumor mass. Metabolic reprogramming has recently been included as one of the hallmarks of cancer. Accordingly, the metabolic rewiring experienced by these tumors to sustain rapid growth and proliferation can also serve as a potential therapeutic target. The combination of 13C tracing approaches with the utilization of different NMR spectral modalities has allowed investigations of the upregulation of glycolysis in the aggressive forms of brain tumors, including glioblastomas, and the discovery of the utilization of acetate as an alternative cellular fuel in brain metastasis and gliomas. One of the major contributions of magnetic resonance to the assessment of brain tumors has been the non-invasive determination of 2-hydroxyglutarate (2HG) in tumors harboring a mutation in isocitrate dehydrogenase 1 (IDH1). The mutational status of this enzyme already serves as a key feature in the clinical classification of brain neoplasia in routine clinical practice and pilot studies have established the use of in vivo magnetic resonance spectroscopy (MRS) for monitoring disease progression and treatment response in IDH mutant gliomas. However, the development of bespoke methods for 2HG detection by MRS has been required, and this has prevented the wider implementation of MRS methodology into the clinic. One of the main challenges for improving the management of the disease is to obtain an accurate insight into the response to treatment, so that the patient can be promptly diverted into a new therapy if resistant or maintained on the original therapy if responsive. The implementation of 13C hyperpolarized magnetic resonance spectroscopic imaging (MRSI) has allowed detection of changes in tumor metabolism associated with a treatment, and as such has been revealed as a remarkable tool for monitoring response to therapeutic strategies. In summary, the application of magnetic resonance-based methodologies to the diagnosis and management of brain tumor patients, in addition to its utilization in the investigation of its tumor-associated metabolic rewiring, is helping to unravel the biological basis of malignancies of the central nervous system.

Keywords: (13)C-tracing; Brain tumors; Hyperpolarization; MRS; Metabolomics.

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Conflict of interest statement

Declaration of Competing Interest The authors declare that there is no conflict of interest.

Figures

Fig. 1.
Fig. 1.
Workflow for metabolomics investigations of brain tumors. After sample (CSF, blood, urine) collection from patients or animal models the preparation steps are minimal, involving mixing the sample with D2O and a buffer, prior to transfer the sample to an NMR tube and the acquisition of the spectra. Analysis of tissue requires the mechanical homogenization of the specimen and subsequent extraction utilizing organic solvents to create a biphasic preparation after centrifugation. Both polar (upper phase) and organic (bottom phase) fractions are dried and reconstituted in a deuterated solvent. Alternatively, tissue can be directly inserted into the MAS rotor for spectral acquisition (MAS spectrum courtesy of Dr. Madhu Basetti, University of Cambridge). Spectra are then analyzed by quantifying the assigned metabolites or by bucketing of the spectra to generate datasets that can be employed for multivariate analysis. This approach usually involves the clustering of samples according to disease status or treatment based on their metabolic profiles, the search of dysregulated metabolites that can be utilized as biomarkers and the pathway analysis to assign the changes in metabolite levels to a specific metabolic route.
Fig. 2.
Fig. 2.
Investigation of metabolic rewiring in CNS malignancies. A, Key metabolic pathways involved in tumor metabolism. B, 13C tracing-based approaches to investigate the upregulation of glycolysis in cancer: blue colored circles denote the location of the 13C atoms in the substrates as well as in the subsequent metabolic products through glycolysis (blue) or pentose phosphate pathway (red). [1,2-13C]-glucose generates [2,3-13C]-lactate through glycolysis and [3-13C]-lactate if glucose-6P is diverted to the pentose phosphate pathway (PPP) by glucose-6P dehydrogenase, and once transformed into glyceraldehyde-3P, enters back into the glycolytic route. The contribution of each of those pathways to lactate formation can be quantified by comparing the areas under the resonance signals of lactate in a 13C spectrum, as the multiplet generated contains the information about the levels of both isotopologues. D, Analysis of the contribution of glucose and glutamine to 2HG synthesis in IDH1 mutant gliomas by examination of the resonances of C3 and C4 of 2HG from C3-13C-glutamine (orange circle) and C1-13C-glucose. E, Multiplet arising from 13C labeling of 2HG from TS603 cell line seeded in media containing [U-13C]-Glutamine and analyzed as described in [86]. 2HG structure with assignments displayed on top of the 13C spectrum [87]. F, Investigation of acetate contribution to the TCA through coadministration of [1,6-13C]-glucose (blue circles) and [1,2-13C]-acetate (green circles). (G) The multiplets attributable to incorporation of 13C into positions 3,4 and 5 (top) in both glutamine and glutamate C4 group serve to assign the specific contribution of each substrate (glucose and acetate) to the TCA. A 13C NMR GBM tumor spectrum after co-infusion is displayed. Chemical shift assignments can be found in the original article. Reproduced from [88] with permission.
Fig. 3.
Fig. 3.
Metabolic characterization of brain tumors by in vivo MRS. A, Mean and SD (vertical lines) of normalized STEAM (TE = 30 ms) spectra for normal white matter (n = 6), meningioma (n = 8), metastases (n = 6), astrocytoma grade II (n = 5), anaplastic astrocytoma (n = 7) and glioblastoma (n = 13). Reproduced with permission from [204]. B, Contrast-enhanced axial MR image demonstrating an enhancing mass in the left parietal lobe (top) and corresponding multivoxel imaging data displayed as color maps displaying the spatial distributions of (left-to-right) total choline (tCho), total creatine (tCr), and N-acetylaspartate (NAA). Figure taken from [205]. C, In vivo spectra from an IDH1-mutated oligodendroglioma, obtained with triple refocusing (left) and PRESS TE = 97 ms (right). LCModel outputs and spectra of 2HG, GABA, Glu, and Gln are also shown. The voxel size and scan time were identical between the scans (2 × 2 × 2 cm3 and 5 min). Spectra were normalized to STEAM TE = 13 ms water. Insets show magnified spectra between 2.1 and 2.5 ppm to highlight 2HG resonance signal. Reproduced with permission from [206]. D, 2D LASER-COSY spectra in vivo of an anaplastic astrocytoma patient with IDH1-R132C at 3 T. The 2D LASER-COSY shows at 4.02/1.91 ppm the Hα-Hβ cross peak of 2HG. Projections along both spectral dimensions through 2HG cross peak indicate the SNR and spectral quality. The single voxel (3 × 3 × 3 cm3, red rectangle) was placed on the FLAIR images to include most of the tumor mass. Reproduced with permission from [207]. E, 1D MEGA-LASER spectra in vivo of a secondary GBM with IDH1-R132H at 3 T. Two voxels (3 × 3 × 3 cm3 each) were placed in both brain hemispheres, symmetrically from the middle line. Reproduced with permission from [207].
Fig. 4.
Fig. 4.
Assessment of metabolic fluxes in brain tumors through hyperpolarized and deuterium MRSI. A, Comparison of the magnetization resulting from conventional experimentation and when samples are subjected to hyperpolarization. The increasing difference of nuclei between the energy states allows for a remarkable increment in the intensity of the resulting NMR signal. B, T2-weighted MRIs of BT142 (left) and U87 (right) tumor-bearing mice and positioning of tumor voxels (U87 red; BT142 blue). The tumor is circled in dashed lines. Corresponding stack plot of hyperpolarized 13C MR spectra obtained at 14.1 T following intravenous injection of hyperpolarized [1-13C]-pyruvate (δ = 172.9 ppm). Production of hyperpolarized [1-13C]-lactate could be detected in both tumor types at δ = 185 ppm, although the level of hyperpolarized [1-13C]-lactate was lower in BT142 tumors as compared to U87. The colored spectra represent the sum of the spectra over time (U87 red; BT142 blue). Reproduced with permission from [223]. C, Multivoxel MRS of a mouse model of glioma after infusion with hyperpolarized [1-13C]-pyruvate and the heatmaps displaying the levels of the metabolites of interest within the tumor area. D, Averaged 13C spectra of lactate and pyruvate in an aggressive model of glioma (top) and an indolent one (bottom) revealing how the most aggressive model presents a more active glycolytic pathway. Reproduced with permission from [224]. E, 2H-MRS investigations of tumor metabolism in a CNS tumor to examine the glycolytic activity in tissue (1 and 3) within the lesion as determined through MRI, (2) from normal-appearing occipital lobe, and (4) containing cerebrospinal fluid from the left lateral ventricle. Figure reproduced with permission from [225].

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