Metabolomic Analysis of Histological Composition Variability of High-Grade Serous Ovarian Cancer Using 1H HR MAS NMR Spectroscopy.

In this work, the HR MAS NMR (high-resolution magic-angle spinning nuclear magnetic resonance) spectroscopy technique was combined with standard histological examinations to investigate the metabolic features of high-grade serous ovarian cancer (HGSOC) with a special focus on the relation between a metabolic profile and a cancer cell fraction. The studied group consisted of 44 patients with HGSOC and 18 patients with benign ovarian tumors. Normal ovarian tissue was also excised from 13 control patients. The metabolic profiles of 138 tissue specimens were acquired on a Bruker Avance III 400 MHz spectrometer. The NMR spectra of the HGSOC samples could be discriminated from those acquired from the non-transformed tissue and were shown to depend on tumor purity. The most important features that differentiate the samples with a high fraction of cancer cells from the samples containing mainly fibrotic stroma are the increased intensities in the spectral regions corresponding to phosphocholine/glycerophosphocholine, phosphoethanolamine/serine, threonine, uridine nucleotides and/or uridine diphosphate (UDP) nucleotide sugars. Higher levels of glutamine, glutamate, acetate, lysine, alanine, leucine and isoleucine were detected in the desmoplastic stroma within the HGSOC lesions compared to the stroma of benign tumors. The HR MAS NMR analysis of the metabolic composition of the epithelial and stromal compartments within HGSOC contributes to a better understanding of the disease's biology.

Characterization of the metabolomic profile of renal cell carcinoma by high resolution magic angle spinning proton magnetic resonance spectroscopy.

BACKGROUND: Renal cell carcinoma (RCC) is a metabolic disease, with subtypes exhibiting aberrations in different metabolic pathways. Metabolomics may offer greater sensitivity for revealing disease biology. We investigated the metabolomic profile of RCC using high-resolution magic angle spinning (HRMAS) proton magnetic resonance spectroscopy (1HMRS). METHODS: Surgical tissue samples were obtained from our frozen tissue bank, collected from radical or partial nephrectomy. Specimens were fresh-frozen, then stored at -80 °C until analysis. Tissue HRMAS-1HMRS was performed. A MatLab-based curve fitting program was used to process the spectra to produce relative intensities for 59 spectral regions of interest (ROIs). Comparisons of the metabolomic profiles of various RCC histologies and benign tumors, angiomyolipoma, and oncocytoma, were performed. False discovery rates (FDR) were used from the response screening to account for multiple testing; ROIs with FDR p < 0.05 were considered potential predictors of RCC. Wilcoxon rank sum test was used to compare median 1HMRS relative intensities for those metabolites that may differentiate between RCC and benign tumor. Logistic regression determined odds ratios for risk of malignancy based on the abundance of each metabolite. RESULTS: Thirty-eight RCC (16 clear cell, 11 papillary, 11 chromophobe), 10 oncocytomas, 7 angiomyolipomas, and 13 adjacent normal tissue specimens (matched pairs) were analyzed. Candidate metabolites for predictors of malignancy based on FDR p-values include histidine, phenylalanine, phosphocholine, serine, phosphocreatine, creatine, glycerophosphocholine, valine, glycine, myo-inositol, scyllo-inositol, taurine, glutamine, spermine, acetoacetate, and lactate. Higher levels of spermine, histidine, and phenylalanine at 3.15 to 3.13 parts per million (ppm) were associated with decreased risk of RCC (OR 4 × 10-5, 95% CI 7.42 × 10-8, 0.02), while 2.84 to 2.82 ppm increased the risk of malignant pathology (OR 7158.67, 95% CI 6.3, 8.3 × 106). The specific metabolites characterizing this region remain to be identified. Tumor stage did not affect metabolomic profile of malignant tumors, suggesting that metabolites are dependent on histologic subtype. CONCLUSIONS: HRMAS-1HMRS identified metabolites that may predict RCC. We demonstrated that those in the 3.14 to 3.13 ppm ROI were present in lower levels in RCC, while higher levels of metabolites in the 2.84 to 2.82 ppm ROI were associated with substantially increased risk of RCC. Further research in a larger population is required to validate these findings.

Intracellular Fate of the Photosensitizer Chlorin e4 with Different Carriers and Induced Metabolic Changes Studied by 1H NMR Spectroscopy.

Porphyrinic photosensitizers (PSs) and their nano-sized polymer-based carrier systems are required to exhibit low dark toxicity, avoid side effects, and ensure high in vivo tolerability. Yet, little is known about the intracellular fate of PSs during the dark incubation period and how it is affected by nanoparticles. In a systematic study, high-resolution magic angle spinning NMR spectroscopy combined with statistical analyses was used to study the metabolic profile of cultured HeLa cells treated with different concentrations of PS chlorin e4 (Ce4) alone or encapsulated in carrier systems. For the latter, either polyvinylpyrrolidone (PVP) or the micelle-forming polyethylene glycol (PEG)-polypropylene glycol triblock copolymer Kolliphor P188 (KP) were used. Diffusion-edited spectra indicated Ce4 membrane localization evidenced by Ce4 concentration-dependent chemical shift perturbation of the cellular phospholipid choline resonance. The effect was also visible in the presence of KP and PVP but less pronounced. The appearance of the PEG resonance in the cell spectra pointed towards cell internalization of KP, whereas no conclusion could be drawn for PVP that remained NMR-invisible. Multivariate statistical analyses of the cell spectra (PCA, PLS-DA, and oPLS) revealed a concentration-dependent metabolic response upon exposure to Ce4 that was attenuated by KP and even more by PVP. Significant Ce4-concentration-dependent alterations were mainly found for metabolites involved in the tricarboxylic acid cycle and the phosphatidylcholine metabolism. The data underline the important protective role of the polymeric carriers following cell internalization. Moreover, to our knowledge, for the first time, the current study allowed us to trace intracellular PS localization on an atomic level by NMR methods.

High-resolution magic angle spinning NMR for intact biological specimen analysis: Initial discovery, recent developments, and future directions.

High-resolution magic angle spinning (HRMAS) NMR, an approach for intact biological material analysis discovered more than 25 years ago, has been advanced by many technical developments and applied to many biomedical uses. This article provides a history of its discovery, first by explaining the key scientific advances that paved the way for HRMAS NMR's invention, and then by turning to recent developments that have profited from applying and advancing the technique during the last 5 years. Developments aimed at directly impacting healthcare include HRMAS NMR metabolomics applications within studies of human disease states such as cancers, brain diseases, metabolic diseases, transplantation medicine, and adiposity. Here, the discussion describes recent HRMAS NMR metabolomics studies of breast cancer and prostate cancer, as well as of matching tissues with biofluids, multimodality studies, and mechanistic investigations, all conducted to better understand disease metabolic characteristics for diagnosis, opportune windows for treatment, and prognostication. In addition, HRMAS NMR metabolomics studies of plants, foods, and cell structures, along with longitudinal cell studies, are reviewed and discussed. Finally, inspired by the technique's history of discoveries and recent successes, future biomedical arenas that stand to benefit from HRMAS NMR-initiated scientific investigations are presented.

Maternal exposure to polystyrene microplastics alters placental metabolism in mice.

INTRODUCTION: The rapid growth in the worldwide use of plastics has resulted in a vast accumulation of microplastics in the air, soil and water. The impact of these microplastics on pregnancy and fetal development remains largely unknown. In pregnant mice, we recently demonstrated that exposure to micro- and nanoplastics throughout gestation resulted in significant fetal growth restriction. One possible explanation for reduced fetal growth is abnormal placental metabolism. OBJECTIVES: To evaluate the effect of maternal exposure to microplastics on placental metabolism. METHODS: In the present study, CD-1 pregnant mice were exposed to 5 µm polystyrene microplastics in filtered drinking water at one of four concentrations (0 ng/L (controls), 102 ng/L, 104 ng/L, 106 ng/L) throughout gestation (n = 7-11/group). At embryonic day 17.5, placental tissue samples were collected (n = 28-44/group). Metabolite profiles were determined using 1 H high-resolution magic angle spinning magnetic resonance spectroscopy. RESULTS: The relative concentration of lysine (p = 0.003) and glucose (p < 0.0001) in the placenta were found to decrease with increasing microplastic concentrations, with a significant reduction at the highest exposure concentration. Multivariate analysis identified shifts in the metabolic profile with MP exposure and pathway analysis identified perturbations in the biotin metabolism, lysine degradation, and glycolysis/gluconeogenesis pathways. CONCLUSION: Maternal exposure to microplastics resulted in significant alterations in placental metabolism. This study highlights the potential impact of microplastic exposure on pregnancy outcomes and that efforts should be made to minimize exposure to plastics, particularly during pregnancy.

High resolution magic angle spinning MRS in prostate cancer.

INTRODUCTION: Prostate cancer (PCa) is one of the leading causes of death among men worldwide. The current methods utilized to screen for prostate cancer may not have sufficient sensitivity in distinguishing aggressive from indolent diseases, which affect the quality of life of patients in the short and long term. The overdiagnosis of cases and overtreatment are prevalent due to the heterogeneity of the disease in terms of latent and progressive variants, as well as in the tissue types present in biopsy samples. METHODS: The purpose of this review is to discuss the potential clinical benefits of incorporating high-resolution magic angle spinning (HRMAS) magnetic resonance spectroscopy (MRS) modalities to overcome the current challenges in the diagnosis, prognostication, and monitoring of PCa.

Untargeted 2D NMR Metabolomics of [13C-methyl]Methionine-Labeled Tumor Models Reveals the Non-DNA Methylome and Provides Clues to Methyl Metabolism Shift during Tumor Progression.

For more than a decade, DNA and histone methylations have been the focus of extensive work, although their relationship with methyl group metabolism was overlooked. Recently, it has emerged that epigenetic methylations are influenced by methyl donor nutrient availability, cellular levels of S-adenosyl-methionine (SAM), and cytoplasmic methyltransferase activities. SAM-dependent methyltransferases methylate a wide range of targets, from small molecules to proteins and nucleic acids. However, few investigations of the global methylome of tumors have been performed. Here, untargeted NMR metabolomics of two mouse tumor models labeled with [13C-methyl]methionine were used to search for the NMR-visible set of cellular methyl acceptors denoted the global methylome. Tumor models were B16 melanoma cell cultures and B16 melanoma tumors, which may be considered as two stages of B16 tumor development. Based on 2D 1H-13C NMR spectra and orthogonal partial least squares discriminant analysis of spectra, our study revealed markedly different global methylomes for melanoma models. The methylome of B16 melanoma cell cultures was dominated by histone methylations, whereas that of B16 melanoma tumors was dominated by cytoplasmic small-molecule methylations. Overall, the technique gave access to the non-DNA methylome. Comparison of tumor models also exhibiting differential expression of aerobic glycolysis provided clues to a methyl metabolism shift during tumor progression.

Placental metabolite profiles in late gestation for healthy mice.

INTRODUCTION: During pregnancy, appropriate placental metabolism is essential for fetuses to reach their growth potential. However, metabolic mechanisms during pregnancy remain poorly understood. Determination of the levels of placental metabolites in healthy pregnancy and how they change throughout gestation is critical for understanding placental function. OBJECTIVE: To determine the effects of gestational age on placental metabolites using healthy pregnant mice. METHODS: In the present study, we collected placental tissue samples from healthy pregnant mice at three timepoints in late gestation (n = 16 placentas per gestational age). Metabolite profiles were determined using 1H high-resolution magic angle spinning magnetic resonance spectroscopy (HRMAS MRS). RESULTS: Using HRMAS MRS, we identified 14 metabolites in murine placental tissue samples. The relative concentration of 12 of the 14 metabolites remains unchanged throughout late gestation. Lysine was found to decrease significantly (p = 0.04) and glucose showed an inverted U-shape relationship (p = 0.03) with gestational age. CONCLUSION: This study demonstrated the feasibility of HRMAS MRS to determine relative metabolite concentrations in murine placental tissue. These findings establish baseline levels of placental tissue metabolite profiles and will serve as reference ranges for future studies using mouse models of fetal distress.

Screening human lung cancer with predictive models of serum magnetic resonance spectroscopy metabolomics.

The current high mortality of human lung cancer stems largely from the lack of feasible, early disease detection tools. An effective test with serum metabolomics predictive models able to suggest patients harboring disease could expedite triage patient to specialized imaging assessment. Here, using a training-validation-testing-cohort design, we establish our high-resolution magic angle spinning (HRMAS) magnetic resonance spectroscopy (MRS)-based metabolomics predictive models to indicate lung cancer presence and patient survival using serum samples collected prior to their disease diagnoses. Studied serum samples were collected from 79 patients before (within 5.0 y) and at lung cancer diagnosis. Disease predictive models were established by comparing serum metabolomic patterns between our training cohorts: patients with lung cancer at time of diagnosis, and matched healthy controls. These predictive models were then applied to evaluate serum samples of our validation and testing cohorts, all collected from patients before their lung cancer diagnosis. Our study found that the predictive model yielded values for prior-to-detection serum samples to be intermediate between values for patients at time of diagnosis and for healthy controls; these intermediate values significantly differed from both groups, with an F1 score = 0.628 for cancer prediction. Furthermore, values from metabolomics predictive model measured from prior-to-diagnosis sera could significantly predict 5-y survival for patients with localized disease.

Nanostructure and Molecular-Level Characterization of Aminoalkyl Methacrylate Copolymer and the Impact on Drug Solubilization Ability.

The effects of pH changes and saccharin (SAC) addition on the nanostructure and mobility of the cationic aminoalkyl methacrylate copolymer Eudragit E PO (EUD-E) and its drug solubilization ability were investigated. Small-angle X-ray scattering performed using synchrotron radiation and atomic force microscopy showed that the EUD-E nanostructure, which has a size of approximately several nanometers, changed from a random coil structure at low pH (pH 4.0-5.0) to a partially folded structure at high pH (pH 5.5-6.5). The EUD-E also formed a partially folded structure in a wide pH range of 4.5-6.5 when SAC was present, and the coil-to-globule transition was moderate with pH increase, compared with that when SAC was absent. The equilibrium solubility of the neutral drug naringenin (NAR) was enhanced in the EUD-E solution and further increased as the pH increased. The enlargement of the hydrophobic region of EUD-E in association with the coil-to-globule transition led to efficient solubilization of NAR. The interaction with SAC enhanced the mobility of the EUD-E chains in the hydrophobic region of EUD-E, resulting in changes in the drug-solubilizing ability. 1H high-resolution magic-angle spinning NMR measurements revealed that the solubilized NAR in the partially folded structure of EUD-E showed higher molecular mobility in the presence of SAC than in the absence of SAC. This study highlighted that solution pH and the presence of SAC significantly changed the drug solubilization ability of EUD-E, followed by changes in the EUD-E nanostructure, including its hydrophobic region.

Dysregulated Alanine as a Potential Predictive Marker of Glioma-An Insight from Untargeted HRMAS-NMR and Machine Learning Data.

Metabolic alterations play a crucial role in glioma development and progression and can be detected even before the appearance of the fatal phenotype. We have compared the circulating metabolic fingerprints of glioma patients versus healthy controls, for the first time, in a quest to identify a panel of small, dysregulated metabolites with potential to serve as a predictive and/or diagnostic marker in the clinical settings. High-resolution magic angle spinning nuclear magnetic resonance spectroscopy (HRMAS-NMR) was used for untargeted metabolomics and data acquisition followed by a machine learning (ML) approach for the analyses of large metabolic datasets. Cross-validation of ML predicted NMR spectral features was done by statistical methods (Wilcoxon-test) using JMP-pro16 software. Alanine was identified as the most critical metabolite with potential to detect glioma with precision of 1.0, recall of 0.96, and F1 measure of 0.98. The top 10 metabolites identified for glioma detection included alanine, glutamine, valine, methionine, N-acetylaspartate (NAA), γ-aminobutyric acid (GABA), serine, α-glucose, lactate, and arginine. We achieved 100% accuracy for the detection of glioma using ML algorithms, extra tree classifier, and random forest, and 98% accuracy with logistic regression. Classification of glioma in low and high grades was done with 86% accuracy using logistic regression model, and with 83% and 79% accuracy using extra tree classifier and random forest, respectively. The predictive accuracy of our ML model is superior to any of the previously reported algorithms, used in tissue- or liquid biopsy-based metabolic studies. The identified top metabolites can be targeted to develop early diagnostic methods as well as to plan personalized treatment strategies.

Metabolic Profiling of Suprachiasmatic Nucleus Reveals Multifaceted Effects in an Alzheimer's Disease Mouse Model.

BACKGROUND: Circadian rhythm disturbance is commonly observed in Alzheimer's disease (AD). In mammals, these rhythms are orchestrated by the superchiasmatic nucleus (SCN). Our previous study in the Tg2576 AD mouse model suggests that inflammatory responses, most likely manifested by low GABA production, may be one of the underlying perpetrators for the changes in circadian rhythmicity and sleep disturbance in AD. However, the mechanistic connections between SCN dysfunction, GABA modulation, and inflammation in AD is not fully understood. OBJECTIVE: To reveal influences of amyloid pathology in Tg2576 mouse brain on metabolism in SCN and to identify key metabolic sensors that couple SCN dysfunction with GABA modulation and inflammation. METHODS: High resolution magic angle spinning (HR-MAS) NMR in conjunction with multivariate analysis was applied for metabolic profiling in SCN of control and Tg2576 female mice. Immunohistochemical analysis was used to detect neurons, astrocytes, expression of GABA transporter 1 (GAT1) and Bmal1. RESULTS: Metabolic profiling revealed significant metabolic deficits in SCN of Tg2576 mice. Reductions in glucose, glutamate, GABA, and glutamine provide hints toward an impaired GABAergic glucose oxidation and neurotransmitter cycling in SCN of AD mice. In addition, decreased redox co-factor NADPH and glutathione support a redox disbalance. Immunohistochemical examinations showed low expression of the core clock protein, Bmal1, especially in activated astrocytes. Moreover, decreased expression of GAT1 in astrocytes indicates low GABA recycling in this cell type. CONCLUSION: Our results suggest that redox disbalance and compromised GABA signaling are important denominators and connectors between neuroinflammation and clock dysfunction in AD.

Study on release suppression of cinnamaldehyde from κ-carrageenan gel by HR-MASNMR and pulsed field gradient NMR (PFG-NMR).

Aiming toward the production and characterization of delicious and functional gel foods, this communication studies the flavor release from cinnamon-containing κ-carrageenan gel. Cinnamaldehyde, which provides the flavor of cinnamon, was released in a trace amount from the gel and detected by flame ionization detector gas chromatography. The retention of cinnamaldehyde in κ-carrageenan gel and the interaction between flavor and polysaccharide were investigated by high-resolution magic-angle spinning nuclear magnetic resonance (HR-MAS NMR) and pulsed-field gradient NMR (PFG NMR). The intact cinnamaldehyde in the gel was also observed by HR-MAS NMR. The relative mobility difference of the flavor and polysaccharide molecules was observed from the diffusion-ordered NMR spectrum of PFG NMR.

Understanding metabolomic characteristics of pancreatic ductal adenocarcinoma by HR-MAS NMR detection of pancreatic tissues.

Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal carcinomas due to an inefficient early diagnosis and a disastrous prognosis. High resolution magic angle spinning nuclear magnetic resonance (HR-MAS NMR) detection of pancreatic tissues would facilitate the understanding of metabolomic characteristics of PDAC and further its clinical diagnosis by in vivo magnetic resonance spectroscopy (MRS). Pancreatic tissues from PDAC patients and Sprague-Dawley (SD) rats model and corresponding controls were detected and comparatively analyzed with HR-MAS NMR-based metabolomic strategy in order to get the underlying biomechanism and diagnostic information of PDAC. According to the univariate and multivariate statistical analysis, eight shared characteristic metabolites by PDAC patients and rats, including glycerophosphocholine (GPC), lactate, myo-inositol, methanol, taurine, methylene of lipid (L-CH2), ß-glucose and phosphocholine (PC), were identified as potential biomarkers of PDAC. Especially, GPC, PC and myo-inositol demonstrated high levels in pancreatic tissue and kept consistent metabolic changes both in PDAC patients and rat models. The occurrence of PDAC mainly involved the aberrations in glycerophospholipid metabolism, galactose metabolism and taurine and hypotaurine metabolism. As an in vitro alternative technique of in vivo MRS, HR-MAS NMR provided good resolution and sensitivity, thus underpinning a potential translation to the in vivo MRS setting for noninvasive detection and monitoring of clinical PDAC. The metabolic differences caused in the different species not only enhance the understanding of metabolic reprogramming of PDAC but also promote the intercommunication of PDAC metabolomes between the different species.

Vibrio harveyi Infection Significantly Alters Amino Acid and Carbohydrate Metabolism in Whiteleg Shrimp, Litopenaeus vannamei.

Vibrio harveyi is one of the pathogens that threaten the shrimp farming industry. However, metabolic changes induced by V. harveyi infection in shrimp remain unknown. In this study, we first conducted high resolution-magic angle spinning (HR-MAS) nuclear magnetic resonance (NMR)-based metabolomics studies on gill, hepatopancreas, and haemolymph of V. harveyi-infected white leg shrimp, Litopenaeus vannamei. Using multivariate statistical analysis, we observed a clear separation between the early (3 and 9 h post-injection (hpi)) and late phases (24, 72 and 144 hpi) of the infection in all tissues. Moreover, metabolic changes in response to V. harveyi infection were faster in the haemolymph in the early phase and significantly changed in the late phase of the infection in the gills. Extensive changes were observed in the hepatopancreas, with 24 hpi being the turning point of progression from early to late phase infection in the hepatopancreas. V. harveyi infection increased the energy demand in L. vannamei and the amino acid and carbohydrate metabolism pathways also exhibited significant changes depending on the tissue. Thus, each tissue displayed different metabolic changes, depending on the progress of the infection.

General Guidelines for Sample Preparation Strategies in HR-µMAS NMR-based Metabolomics of Microscopic Specimens.

The study of the metabolome within tissues, organisms, cells or biofluids can be carried out by several bioanalytical techniques. Among them, nuclear magnetic resonance (NMR) is one of the principal spectroscopic methods. This is due to a sample rotation technique, high-resolution magic angle spinning (HR-MAS), which targets the analysis of heterogeneous specimens with a bulk sample mass from 5 to 10 mg. Recently, a new approach, high-resolution micro-magic angle spinning (HR-µMAS), has been introduced. It opens, for the first time, the possibility of investigating microscopic specimens (<500 µg) with NMR spectroscopy, strengthening the concept of homogeneous sampling in a heterogeneous specimen. As in all bioanalytical approaches, a clean and reliable sample preparation strategy is a significant component in designing metabolomics (or -omics, in general) studies. The sample preparation for HR-µMAS is consequentially complicated by the µg-scale specimen and has yet to be addressed. This report details the strategies for three specimen types: biofluids, fluid matrices and tissues. It also provides the basis for designing future µMAS NMR studies of microscopic specimens.

High-Resolution Magic Angle Spinning (HRMAS) NMR Methods in Metabolomics.

High-resolution magic angle spinning (HRMAS) NMR spectroscopy enables the evaluation of metabolite profiles of intact tissue with high spectral resolution. The ability to preserve the tissue after analysis permits subsequent histopathological examination and enables the analyses of correlations between tissue metabolites and pathologies, thus making HRMAS NMR spectroscopy a powerful tool in the metabolomics field. Improved methods for the elimination of spinning sidebands that appear at low spinning rates preserve the integrity of tissue structures better and allow measurement of delicate tissues, such as clinical biopsy core samples. In the metabolomics field, HRMAS NMR has been established as a valuable tool for both untargeted and targeted metabolite profiling. In this chapter, we present protocols to perform HRMAS NMR spectroscopy experiments, including sample preparation, acquisition procedures, measurement parameters, histopathological examination techniques, spectral processing, and metabolite quantification and statistical analyses.

Biomarker Discovery Using NMR-Based Metabolomics of Tissue.

NMR-based metabolomics has shown promise in the diagnosis of diseases as it enables identification and quantification of metabolic biomarkers. Using high-resolution magic-angle-spinning (HR-MAS) NMR spectroscopy, metabolic profiles from intact tissue specimens can be obtained with high spectral resolution. In addition, HR-MAS NMR requires minimal sample preparation and the sample is kept intact for subsequent analyses. In this chapter, we describe a typical protocol for NMR-based metabolomics of tissue samples. We cover all major steps ranging from tissue sample collection to determination of biomarkers, including experimental precautions taken to ensure reproducible and reliable reporting of data in the area of clinical application.

Quantitative NMR-Based Metabolomics on Tissue Biomarkers and Its Translation into In Vivo Magnetic Resonance Spectroscopy.

Nuclear magnetic resonance (NMR) spectroscopy is an established analytical platform for analyzing metabolic profiles of cells, tissues, and body fluids. There are several advantages in introducing an NMR-based study design into metabolomics studies, including a fast and comprehensive detection, characterization, and quantification of dozens of endogenous metabolites in a single NMR spectrum. Quantitative proton 1H-NMR is the most useful NMR-based platform for metabolomics. The frozen tissues can be analyzed noninvasively using a high-resolution magic angle spinning (HR-MAS) 1H-NMR spectroscopy; or several extraction techniques can be applied to detect additional metabolites using a conventional liquid-based NMR technique. In this chapter, we report on tissue collection, handling, extraction methods, and 1H-NMR acquisition protocols developed in the past decades for a precise and quantitative NMR-metabolomics approach. The NMR acquisition protocols (both HR-MAS and conventional 1H-NMR spectroscopy) and spectral analysis steps are also presented. Since NMR can be applied "in vivo" using horizontal bore MRI scanners, several in vivo sequences for localized 1H-MRS (magnetic resonance spectroscopy) are presented which can be directly applied for noninvasive detection of brain metabolites.

Glutamine to proline conversion is associated with response to glutaminase inhibition in breast cancer.

INTRODUCTION: Glutaminase inhibitors target cancer cells by blocking the conversion of glutamine to glutamate, thereby potentially interfering with anaplerosis and synthesis of amino acids and glutathione. The drug CB-839 has shown promising effects in preclinical experiments and is currently undergoing clinical trials in several human malignancies, including triple-negative breast cancer (TNBC). However, response to glutaminase inhibitors is variable and there is a need for identification of predictive response biomarkers. The aim of this study was to determine how glutamine is utilized in two patient-derived xenograft (PDX) models of breast cancer representing luminal-like/ER+ (MAS98.06) and basal-like/triple-negative (MAS98.12) breast cancer and to explore the metabolic effects of CB-839 treatment. EXPERIMENTAL: MAS98.06 and MAS98.12 PDX mice received CB-839 (200 mg/kg) or drug vehicle two times daily p.o. for up to 28 days (n = 5 per group), and the effect on tumor growth was evaluated. Expression of 60 genes and seven glutaminolysis key enzymes were determined using gene expression microarray analysis and immunohistochemistry (IHC), respectively, in untreated tumors. Uptake and conversion of glutamine were determined in the PDX models using HR MAS MRS after i.v. infusion of [5-13C] glutamine when the models had received CB-839 (200 mg/kg) or vehicle for 2 days (n = 5 per group). RESULTS: Tumor growth measurements showed that CB-839 significantly inhibited tumor growth in MAS98.06 tumors, but not in MAS98.12 tumors. Gene expression and IHC analysis indicated a higher proline synthesis from glutamine in untreated MAS98.06 tumors. This was confirmed by HR MAS MRS of untreated tumors demonstrating that MAS98.06 used glutamine to produce proline, glutamate, and alanine, and MAS98.12 to produce glutamate and lactate. In both models, treatment with CB-839 resulted in accumulation of glutamine. In addition, CB-839 caused depletion of alanine, proline, and glutamate ([1-13C] glutamate) in the MAS98.06 model. CONCLUSION: Our findings indicate that TNBCs may not be universally sensitive to glutaminase inhibitors. The major difference in the metabolic fate of glutamine between responding MAS98.06 xenografts and non-responding MAS98.12 xenografts is the utilization of glutamine for production of proline. We therefore suggest that addiction to proline synthesis from glutamine is associated with response to CB-839 in breast cancer. The effect of glutaminase inhibition in two breast cancer patient-derived xenograft (PDX) models. 13C HR MAS MRS analysis of tumor tissue from CB-839-treated and untreated models receiving 13C-labeled glutamine ([5-13C] Gln) shows that the glutaminase inhibitor CB-839 is causing an accumulation of glutamine (arrow up) in two PDX models representing luminal-like breast cancer (MAS98.06) and basal-like breast cancer (MAS98.12). In MAS98.06 tumors, CB-839 is in addition causing depletion of proline ([5-13C] Pro), alanine ([1-13C] Ala), and glutamate ([1-13C] Glu), which could explain why CB-839 causes tumor growth inhibition in MAS98.06 tumors, but not in MAS98.12 tumors.