Ex-vivo HRMAS of adult brain tumours: metabolite quantification and assignment of tumour biomarkers

Abstract

BackgroundHigh-resolution magic angle spinning (HRMAS) NMR spectroscopy allows detailed metabolic analysis of whole biopsy samples for investigating tumour biology and tumour classification. Accurate biochemical assignment of small molecule metabolites that are "NMR visible" will improve our interpretation of HRMAS data and the translation of NMR tumour biomarkers to in-vivo studies.Results1D and 2D 1H HRMAS NMR was used to determine that 29 small molecule metabolites, along with 8 macromolecule signals, account for the majority of the HRMAS spectrum of the main types of brain tumour (astrocytoma grade II, grade III gliomas, glioblastomas, metastases, meningiomas and also lymphomas). Differences in concentration of 20 of these metabolites were statistically significant between these brain tumour types. During the course of an extended 2D data acquisition the HRMAS technique itself affects sample analysis: glycine, glutathione and glycerophosphocholine all showed small concentration changes; analysis of the sample after HRMAS indicated structural damage that may affect subsequent histopathological analysis.ConclusionsA number of small molecule metabolites have been identified as potential biomarkers of tumour type that may enable development of more selective in-vivo 1H NMR acquisition methods for diagnosis and prognosis of brain tumours.

Identifying malignant transformations in recurrent low grade gliomas using high resolution magic angle spinning spectroscopy

“…It is a non-destructive technique that can be applied to tissue prior to immunohistochemical analysis, thus providing a link between metabolite concentrations, pathology, and in vivo magnetic resonance imaging and spectroscopy. To this end, a large body of research tried to identify biomarkers for brain tumor characterization and typing using HRMAS [6, 7, 30–33]. The quest for biomarkers usually involves analyzing the behavior of single metabolites or ratios of two metabolites in different groups of patients, but does not exploit the relationship between large numbers of metabolites.…”

“…Moreover, HRMAS multivariate studies successfully revealed the status of tumor microheterogeneity [9, 13, 15, 17] and detected alterations in tumor metabolism before changes in morphology occurred [12]. These studies combined dimensionality reduction methods such as principal component analysis [14, 20, 22] and metabolite quantification [10, 14–17, 22, 30, 47] with the robust classification methods listed above. Many of the dimensionality reduction methods and classifiers employed combine the data in such a way that the extracted components lack physical meaning.…”

Mapping of Glycine Distributions in Gliomas

“…Increased concentrations of Gly have been detected in brain tumors using in vivo and ex vivo MR spectroscopy (2–8) and it has been proposed as a marker for grade IV glioma (6). However, in vivo studies have been limited, and the relative frequency of observation, distribution, association with other imaging measures, and potential value as a marker of glioma grade have not been demonstrated.…”

Detection of oncogenic IDH1 mutations using magnetic resonance spectroscopy of 2-hydroxyglutarate

“…This type of error is well documented for GABA, which poses similar problems (25). Indirect proof regarding the difficulty of D-2HG detection is provided by the fact that despite the high frequency of IDH1 mutations in glioma, high levels of D-2HG, and large number of MRS studies of brain tumors performed over the last 20 years (26)(27)(28), the existence of D-2HG was not reported in the cancer MRS literature until after it was discovered through genomic and ex vivo metabolomic analysis (1,2,13).…”