Metabolic analysis of human brain biopsies in a medical environment using HRMAS NMR

M. Piotto^1,2, G. Erb^1,7, K. Elbayed¹, J. Raya¹, A. Neuville³, M. Mohr³, D. Maitrot⁴, P. Kehrli⁴ , A. Imperiale⁷, R. Herbrecht⁷, A. Garillon⁷, F.-M. Moussallieh^1,7, M. Martínez-Bisbal⁶, D. Monleon⁵, O. Assemat², Bernardo Celda⁶ and I. Namer⁷

¹ULP/CNRS LC3-UMR 7177, Strasbourg, France
²Bruker Biospin, France
³Department of Pathology, Strasbourg University Hospitals, France
⁴Department of Neurosurgery, Strasbourg University Hospitals, France
⁵FIHCUV, Hospital Clínico Research Fundation, University of Valencia, Valencia, Spain
⁶Department of Physical Chemistry, University of Valencia, Burjassot, Valencia, Spain
⁷Department of Biophysics and Nuclear Medicine, Strasbourg University Hospitals, France

High Resolution Magic Angle Spinning (HRMAS) NMR (1) is a technique that allows the study of mobile molecules contained within heterogeneous substances. The domain of application of HRMAS is extremely diverse and includes the analysis of molecules obtained by solid phase synthesis, molecules in a membrane environment, swollen polymers, cells and biopsies. These compounds are characterized by a strong heterogeneity and a complex distribution of magnetic susceptibilities. The study of the small molecules contained in such samples is therefore hindered by a significant linebroadening of their NMR resonances. An efficient solution to reduce the linewidth in these systems is to rotate the sample at the magic angle (54.7°). Magic angle spinning allows to average out differences in magnetic susceptibilities and to obtain spectra whose quality approaches the resolution of liquid state NMR spectra (2).

A particularly promising field of application for HRMAS is the field of medical analysis. Using HRMAS, it becomes possible to identify a large fraction of the small metabolites contained in an intact human biopsy (3). Analyzing these metabolic data using multivariate statistical analysis techniques provides additional information that can improve the classification of various human cancers. This possibility is of particular value to the medical community since tumor typing and grading is a key element in the decision-making process that routinely takes place in a hospital leading to prognosis and therapeutic treatment. Today, this classification relies essentially on morphological criteria obtained through histopathological study of the biopsy. However, for certain types of human brain tumors, like oligodendrogliomas of low and high grades, this classification is not sufficiently reliable. The use of histopathological data by the neurosurgeon associated with metabolic data can potentially lead to a better prognosis and better therapeutic management of the patients affected by these cancers (4).

Metabolic analysis of human tumors can help tackle a variety of medical problems in a hospital. In particular, it can be of interest to correlate HRMAS results with information obtained from PET (Positron Emitted Tomography) examinations. This type of analysis allows correlating the fixation of glucose (¹⁸F-FDG) to the metabolism of tumor cells.

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