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High‐resolution magic angle spinning (HR MAS) nuclear magnetic resonance (NMR) spectroscopy is increasingly being used to study metabolite levels in human breast cancer tissue, assessing, for instance, correlations with prognostic factors, survival outcome or therapeutic response. However, the impact of intratumoral heterogeneity on metabolite levels in breast tumor tissue has not been studied comprehensively. More specifically, when biopsy material is analyzed, it remains questionable whether one biopsy is representative of the entire tumor. Therefore, multi‐core sampling (n = 6) of tumor tissue from three patients with breast cancer, followed by lipid (0.9‐ and 1.3‐ppm signals) and metabolite quantification using HR MAS 1H NMR, was performed, resulting in the quantification of 32 metabolites. The mean relative standard deviation across all metabolites for the six tumor cores sampled from each of the three tumors ranged from 0.48 to 0.74. This was considerably higher when compared with a morphologically more homogeneous tissue type, here represented by murine liver (0.16–0.20). Despite the seemingly high variability observed within the tumor tissue, a random forest classifier trained on the original sample set (training set) was, with one exception, able to correctly predict the tumor identity of an independent series of cores (test set) that were additionally sampled from the same three tumors and analyzed blindly. Moreover, significant differences between the tumors were identified using one‐way analysis of variance (ANOVA), indicating that the intertumoral differences for many metabolites were larger than the intratumoral differences for these three tumors. That intertumoral differences, on average, were larger than intratumoral differences was further supported by the analysis of duplicate tissue cores from 15 additional breast tumors. In summary, despite the observed intratumoral variability, the results of the present study suggest that the analysis of one, or a few, replicates per tumor may be acceptable, and supports the feasibility of performing reliable analyses of patient tissue. [ABSTRACT FROM AUTHOR]

High resolution magic-angle spinning (HR-MAS) nuclear magnetic resonance (NMR) spectroscopy is increasingly used for profiling of breast cancer tissue, delivering quantitative information for approximately 40 metabolites. One unique advantage of the method is that it can be used to analyse intact tissue, thereby requiring only minimal sample preparation. Importantly, since the method is non-destructive, it allows further investigations of the same specimen using for instance transcriptomics. Here, we discuss technical aspects critical for a successful analysis — including sample handling, measurement conditions, pulse sequences for one- and two dimensional analysis, and quantification methods - and summarize available studies, with a focus on significant associations of metabolite levels with clinically relevant parameters.

In this study, we report the chemical characterization of 47 tropical microalgae and cyanobacteria by HR-MAS. The generated data confirm the interest of HR-MAS as a rapid screening technique with the major advantage of its easiness. The sample is used as powder of freeze-dried microalgae without any extraction process before acquisition. The spectral fingerprints of strains are then tested as variables for a chemotaxonomy study to discriminate cyanobacteria and dinoflagellates. The individual factor map generated by PCA analysis succeeds in separating the two groups, essentially thanks to the presence of specific carbohydrates. Furthermore, more resolved signals enable to identify many osmolytes. More precisely the characteristics δ of 2- O -alpha- D -glucosylglycerol (GG) are observed in all 21 h-MAS spectra of tropical cyanobacteria. After specific extraction, complementary analysis by 1D and 2D-NMR spectroscopies validates the identification of this osmolyte. [ABSTRACT FROM AUTHOR]

Introduction: Metabolic profiling of intact tumor tissue by high-resolution magic angle spinning (HR MAS) MR spectroscopy (MRS) provides important biological information possibly useful for clinical diagnosis and development of novel treatment strategies. However, generation of high-quality data requires that sample handling from surgical resection until analysis is performed using systematically validated procedures. In this study, we investigated the effect of postsurgical freezing delay time on global metabolic profiles and stability of individual metabolites in intact tumor tissue. Materials and methods: Tumor tissue samples collected from two patient-derived breast cancer xenograft models (n = 3 for each model) were divided into pieces that were snap-frozen in liquid nitrogen at 0, 15, 30, 60, 90, and 120 min after surgical removal. In addition, one sample was analyzed immediately, representing the metabolic profile of fresh tissue exposed neither to liquid nitrogen nor to room temperature. We also evaluated the metabolic effect of prolonged spinning during the HR MAS experiments in biopsies from breast cancer patients (n = 14). All samples were analyzed by proton HR MAS MRS on a Bruker Avance DRX600 spectrometer, and changes in metabolic profiles were evaluated using multivariate analysis and linear mixed modeling. results: Multivariate analysis showed that the metabolic differences between the two breast cancer models were more prominent than variation caused by freezing delay time. No significant changes in levels of individual metabolites were observed in samples frozen within 30 min of resection. After this time point, levels of choline increased, whereas ascorbate, creatine, and glutathione (GS) levels decreased. Freezing had a significant effect on several metabolites but is an essential procedure for research and biobank purposes. Furthermore, four metabolites (glucose, glycine, glycerophosphocholine, and choline) were affected by prolonged HR MAS experiment time possibly caused by physical release of metabolites caused by spinning or due to structural degradation processes. conclusion: The MR metabolic profiles of tumor samples are reproducible and robust to variation in postsurgical freezing delay up to 30 min. [ABSTRACT FROM AUTHOR]

Breast cancer is a heterogeneous disease with a variable prognosis. Clinical factors provide some information about the prognosis of patients with breast cancer; however, there is a need for additional information to stratify patients for improved and more individualized treatment. The aim of this study was to examine the relationship between the metabolite profiles of breast cancer tissue and 5-year survival. Biopsies from breast cancer patients ( n = 98) were excised during surgery and analyzed by high-resolution magic angle spinning MRS. The data were analyzed by multivariate principal component analysis and partial least-squares discriminant analysis, and the findings of important metabolites were confirmed by spectral integration of the metabolite peaks. Predictions of 5-year survival using metabolite profiles were compared with predictions using clinical parameters. Based on the metabolite profiles, patients with estrogen receptor (ER)-positive breast cancer ( n = 71) were separated into two groups with significantly different survival rates ( p = 0.024). Higher levels of glycine and lactate were found to be associated with lower survival rates by both multivariate analyses and spectral integration, and are suggested as biomarkers for breast cancer prognosis. Similar metabolic differences were not observed for ER-negative patients, where survivors could not be separated from nonsurvivors. Predictions of 5-year survival of ER-positive patients using metabolite profiles gave better and more robust results than those using traditional clinical parameters. The results imply that the metabolic state of a tumor may provide additional information concerning breast cancer prognosis. Further studies should be conducted in order to evaluate the role of MR metabolomics as an additional clinical tool for determining the prognosis of patients with breast cancer. Copyright © 2012 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Abstract: Several investigations have recently reported the combined use of pulsed field gradient (PFG) with magic angle spinning (MAS) for the analysis of molecular mobility in heterogeneous materials. In contrast, little attention has been devoted so far to delimiting the role of the extra force field induced by sample rotation on the significance and reliability of self-diffusivity measurements. The main purpose of this work is to examine this phenomenon by focusing on pure liquids for which its impact is expected to be largest. Specifically, we show that self-diffusion coefficients can be accurately determined by PFG MAS NMR diffusion measurements in liquids, provided that specific experimental conditions are met. First, the methodology to estimate the gradient uniformity and to properly calibrate its absolute strength is briefly reviewed and applied on a MAS probe equipped with a gradient coil aligned along the rotor spinning axis, the so-called ‘magic angle gradient’ coil. Second, the influence of MAS on the outcome of PFG MAS diffusion measurements in liquids is investigated for two distinct typical rotors of different active volumes, 12 and 50μL. While the latter rotor led to totally unreliable results, especially for low viscosity compounds, the former allowed for the determination of accurate self-diffusion coefficients both for fast and slowly diffusing species. Potential implications of this work are the possibility to measure accurate self-diffusion coefficients of sample-limited mixtures or to avoid radiation damping interferences in NMR diffusion measurements. Overall, the outlined methodology should be of interest to anyone who strives to improve the reliability of MAS diffusion studies, both in homogeneous and heterogeneous media. [Copyright &y& Elsevier]

Abstract: This work presents a methodology for optimizing the precision, accuracy and sensitivity of quantitative solid state NMR measurements based on the external reference method. It is shown that the sample must be exclusively located within and completely span the coil region where the NMR response is directly proportional to the sample amount. We describe two methods to determine this “quantitative” coil volume, based on whether the probe is equipped or not with a gradient coil. In addition, to improve the sensitivity and the accuracy, an optimum rotor packing design is described, which allows the sample volume of the rotor to be matched to the quantitative coil volume. Experiments conducted on adamantane and NaCl, which are representative of a soft and hard material, respectively, show that one order of magnitude increase in experimental precision can be achieved with this methodology. Interestingly, the precision can be further improved by using the ERETIC™ method in order to compensate for most instrumental instabilities. [Copyright &y& Elsevier]

High resolution magic-angle spinning (HR-MAS) nuclear magnetic resonance (NMR) spectroscopy is increasingly used for profiling of breast cancer tissue, delivering quantitative information for approximately 40 metabolites. One unique advantage of the method is that it can be used to analyse intact tissue, thereby requiring only minimal sample preparation. Importantly, since the method is non-destructive, it allows further investigations of the same specimen using for instance transcriptomics. Here, we discuss technical aspects critical for a successful analysis—including sample handling, measurement conditions, pulse sequences for one- and two dimensional analysis, and quantification methods—and summarize available studies, with a focus on significant associations of metabolite levels with clinically relevant parameters. [ABSTRACT FROM AUTHOR]

High-resolution magic angle spinning (HR MAS) nuclear magnetic resonance (NMR) spectroscopy is increasingly being used to study metabolite levels in human breast cancer tissue, assessing, for instance, correlations with prognostic factors, survival outcome or therapeutic response. However, the impact of intratumoral heterogeneity on metabolite levels in breast tumor tissue has not been studied comprehensively. More specifically, when biopsy material is analyzed, it remains questionable whether one biopsy is representative of the entire tumor. Therefore, multi-core sampling (n = 6) of tumor tissue from three patients with breast cancer, followed by lipid (0.9- and 1.3-ppm signals) and metabolite quantification using HR MAS 1 H NMR, was performed, resulting in the quantification of 32 metabolites. The mean relative standard deviation across all metabolites for the six tumor cores sampled from each of the three tumors ranged from 0.48 to 0.74. This was considerably higher when compared with a morphologically more homogeneous tissue type, here represented by murine liver (0.16-0.20). Despite the seemingly high variability observed within the tumor tissue, a random forest classifier trained on the original sample set (training set) was, with one exception, able to correctly predict the tumor identity of an independent series of cores (test set) that were additionally sampled from the same three tumors and analyzed blindly. Moreover, significant differences between the tumors were identified using one-way analysis of variance (ANOVA), indicating that the intertumoral differences for many metabolites were larger than the intratumoral differences for these three tumors. That intertumoral differences, on average, were larger than intratumoral differences was further supported by the analysis of duplicate tissue cores from 15 additional breast tumors. In summary, despite the observed intratumoral variability, the results of the present study suggest that the analysis of one, or a few, replicates per tumor may be acceptable, and supports the feasibility of performing reliable analyses of patient tissue., (Copyright © 2017 John Wiley & Sons, Ltd.)

Introduction: Metabolic profiling of intact tumor tissue by high-resolution magic angle spinning (HR MAS) MR spectroscopy (MRS) provides important biological information possibly useful for clinical diagnosis and development of novel treatment strategies. However, generation of high-quality data requires that sample handling from surgical resection until analysis is performed using systematically validated procedures. In this study, we investigated the effect of postsurgical freezing delay time on global metabolic profiles and stability of individual metabolites in intact tumor tissue., Materials and Methods: Tumor tissue samples collected from two patient-derived breast cancer xenograft models (n = 3 for each model) were divided into pieces that were snap-frozen in liquid nitrogen at 0, 15, 30, 60, 90, and 120 min after surgical removal. In addition, one sample was analyzed immediately, representing the metabolic profile of fresh tissue exposed neither to liquid nitrogen nor to room temperature. We also evaluated the metabolic effect of prolonged spinning during the HR MAS experiments in biopsies from breast cancer patients (n = 14). All samples were analyzed by proton HR MAS MRS on a Bruker Avance DRX600 spectrometer, and changes in metabolic profiles were evaluated using multivariate analysis and linear mixed modeling., Results: Multivariate analysis showed that the metabolic differences between the two breast cancer models were more prominent than variation caused by freezing delay time. No significant changes in levels of individual metabolites were observed in samples frozen within 30 min of resection. After this time point, levels of choline increased, whereas ascorbate, creatine, and glutathione (GS) levels decreased. Freezing had a significant effect on several metabolites but is an essential procedure for research and biobank purposes. Furthermore, four metabolites (glucose, glycine, glycerophosphocholine, and choline) were affected by prolonged HR MAS experiment time possibly caused by physical release of metabolites caused by spinning or due to structural degradation processes., Conclusion: The MR metabolic profiles of tumor samples are reproducible and robust to variation in postsurgical freezing delay up to 30 min.