Correlations between in vivo (1)H MRS and ex vivo (1)H HRMAS metabolite measurements in adult human gliomas

Closing the gap between in vivo and in vitro omics: using QA/QC to strengthen ex vivo NMR metabolomics

Metabolomics aims to achieve a global quantitation of the pool of metabolites within a biological system. Importantly, metabolite concentrations serve as a sensitive marker of both genomic and phenotypic changes in response to both internal and external stimuli. NMR spectroscopy greatly aids in the understanding of both in vitro and in vivo physiological systems and in the identification of diagnostic and therapeutic biomarkers. Accordingly, NMR is widely utilized in metabolomics and fluxomics studies due to its limited requirements for sample preparation and chromatography, its non-destructive and quantitative nature, its utility in the structural elucidation of unknown compounds, and, importantly, its versatility in the analysis of in vitro, in vivo, and ex vivo samples. This review provides an overview of the strengths and limitations of in vitro and in vivo experiments for translational research and discusses how ex vivo studies may overcome these weaknesses to facilitate the extrapolation of in vitro insights to an in vivo system. The application of NMR-based metabolomics to ex vivo samples, tissues, and biofluids can provide essential information that is close to a living system (in vivo) with sensitivity and resolution comparable to those of in vitro studies. The success of this extrapolation process is critically dependent on high-quality and reproducible data. Thus, the incorporation of robust quality assurance and quality control checks into the experimental design and execution of NMR-based metabolomics experiments will ensure the successful extrapolation of ex vivo studies to benefit translational medicine.

Cancer insights from magnetic resonance spectroscopy of cells and excised tumors

Multinuclear ex vivo magnetic resonance spectroscopy (MRS) of cancer cells, xenografts, human cancer tissue, and biofluids is a rapidly expanding field that is providing unique insights into cancer. Starting from the 1970s, the field has continued to evolve as a stand-alone technology or as a complement to in vivo MRS to characterize the metabolome of cancer cells, cancer-associated stromal cells, immune cells, tumors, biofluids and, more recently, changes in the metabolome of organs induced by cancers. Here, we review some of the insights into cancer obtained with ex vivo MRS and provide a perspective of future directions. Ex vivo MRS of cells and tumors provides opportunities to understand the role of metabolism in cancer immune surveillance and immunotherapy. With advances in computational capabilities, the integration of artificial intelligence to identify differences in multinuclear spectral patterns, especially in easily accessible biofluids, is providing exciting advances in detection and monitoring response to treatment. Metabolotheranostics to target cancers and to normalize metabolic changes in organs induced by cancers to prevent cancer-induced morbidity are other areas of future development.

In vivo macromolecule signals in rat brain 1 H-MR spectra at 9.4T: Parametrization, spline baseline estimation, and T2 relaxation times

PURPOSE

Reliable detection and fitting of macromolecules (MM) are crucial for accurate quantification of brain short-echo time (TE) ¹ H-MR spectra. An experimentally acquired single MM spectrum is commonly used. Higher spectral resolution at ultra-high field (UHF) led to increased interest in using a parametrized MM spectrum together with flexible spline baselines to address unpredicted spectroscopic components. Herein, we aimed to: (1) implement an advanced methodological approach for post-processing, fitting, and parametrization of 9.4T rat brain MM spectra; (2) assess the concomitant impact of the LCModel baseline and MM model (ie, single vs parametrized); and (3) estimate the apparent T₂ relaxation times for seven MM components.

METHODS

A single inversion recovery sequence combined with advanced AMARES prior knowledge was used to eliminate the metabolite residuals, fit, and parametrize 10 MM components directly from 9.4T rat brain in vivo ¹ H-MR spectra at different TEs. Monte Carlo simulations were also used to assess the concomitant influence of parametrized MM and DKNTMN parameter in LCModel.

RESULTS

A very stiff baseline (DKNTMN ≥ 1 ppm) in combination with a single MM spectrum led to deviations in metabolite concentrations. For some metabolites the parametrized MM showed deviations from the ground truth for all DKNTMN values. Adding prior knowledge on parametrized MM improved MM and metabolite quantification. The apparent T₂ ranged between 12 and 24 ms for seven MM peaks.

CONCLUSION

Moderate flexibility in the spline baseline was required for reliable quantification of real/experimental spectra based on in vivo and Monte Carlo data. Prior knowledge on parametrized MM improved MM and metabolite quantification.

Contribution of macromolecules to brain 1 H MR spectra: Experts' consensus recommendations

Proton MR spectra of the brain, especially those measured at short and intermediate echo times, contain signals from mobile macromolecules (MM). A description of the main MM is provided in this consensus paper. These broad peaks of MM underlie the narrower peaks of metabolites and often complicate their quantification but they also may have potential importance as biomarkers in specific diseases. Thus, separation of broad MM signals from low molecular weight metabolites enables accurate determination of metabolite concentrations and is of primary interest in many studies. Other studies attempt to understand the origin of the MM spectrum, to decompose it into individual spectral regions or peaks and to use the components of the MM spectrum as markers of various physiological or pathological conditions in biomedical research or clinical practice. The aim of this consensus paper is to provide an overview and some recommendations on how to handle the MM signals in different types of studies together with a list of open issues in the field, which are all summarized at the end of the paper.

Metabolic NMR mapping with microgram tissue biopsy

This study explores the potential of profiling a microgram-scale soft tissue biopsy by NMR spectroscopy. The important elements of high resolution and high sensitivity for the spectral data are achieved through a unique probe, HR-μMAS, which allowed comprehensive profiling to be performed on microgram tissue for the first time under MAS conditions. Thorough spatially resolved metabolic maps were acquired across a coronal brain slice of rat C6 gliomas, which rendered the delineation of the tumor lesion. The results present a unique ex vivo NMR possibility to analyze tissue pathology that cannot be fully explored by the conventional approach, HR-MAS and in vivo MRS. Aside from the capability of analyzing a small localized region to track its specific metabolism, it could also offer the possibility to carry out longitudinal investigations on live animals due to the feasibility of minimally invasive tissue excision.

Stop the rot. Enzyme inactivation at brain harvest prevents artifacts: A guide for preservation of the in vivo concentrations of brain constituents

Post-mortem metabolism is widely recognized to cause rapid and prolonged changes in the concentrations of multiple classes of compounds in brain, that is, they are labile. Post-mortem changes from levels in living brain include components of pathways of metabolism of glucose and energy compounds, amino acids, lipids, signaling molecules, neuropeptides, phosphoproteins, and proteins. Methods that stop enzyme activity at brain harvest were developed almost 50 years ago and have been extensively used in studies of brain functions and diseases. Unfortunately, these methods are not commonly used to harvest brain tissue for mass spectrometry-based metabolomic studies or for imaging mass spectrometry studies (IMS, also called mass spectrometry imaging, MSI, or matrix-assisted laser desorption/ionization-MSI, MALDI-MSI). Instead these studies commonly kill animals, decapitate, dissect out brain and regions of interest if needed, then 'snap' freeze the tissue to stop enzymatic activity after harvest, with post-mortem intervals typically ranging from ~0.5 to 3 min. To increase awareness of the importance of stopping metabolism at harvest and preventing the unnecessary complications of not doing so, this commentary provides examples of labile metabolites and the magnitudes of their post-mortem changes in concentrations during brain harvest. Brain harvest methods that stop metabolism at harvest eliminate post-mortem enzymatic activities and can improve characterization of normal and diseased brain. In addition, metabolomic studies would be improved by reporting absolute units of concentration along with normalized peak areas or fold changes. Then reported values can be evaluated and compared with the extensive neurochemical literature to help prevent reporting of artifactual data.

Optical and magnetic resonance imaging approaches for investigating the tumour microenvironment: state-of-the-art review and future trends

The tumour microenvironment (TME) strongly influences tumorigenesis and metastasis. Two of the most characterized properties of the TME are acidosis and hypoxia, both of which are considered hallmarks of tumours as well as critical factors in response to anticancer treatments. Currently, various imaging approaches exist to measure acidosis and hypoxia in the TME, including magnetic resonance imaging (MRI), positron emission tomography and optical imaging. In this review, we will focus on the latest fluorescent-based methods for optical sensing of cell metabolism and MRI as diagnostic imaging tools applied both in vitro and in vivo. The primary emphasis will be on describing the current and future uses of systems that can measure intra- and extra-cellular pH and oxygen changes at high spatial and temporal resolution. In addition, the suitability of these approaches for mapping tumour heterogeneity, and assessing response or failure to therapeutics will also be covered.

Hormone-Independent Mouse Mammary Adenocarcinomas with Different Metastatic Potential Exhibit Different Metabolic Signatures

The metabolic characteristics of metastatic and non-metastatic breast carcinomas remain poorly studied. In this work, untargeted Nuclear Magnetic Resonance (NMR) metabolomics was used to compare two medroxyprogesterone acetate (MPA)-induced mammary carcinomas lines with different metastatic abilities. Different metabolic signatures distinguished the non-metastatic (59-2-HI) and the metastatic (C7-2-HI) lines, with glucose, amino acid metabolism, nucleotide metabolism and lipid metabolism as the major affected pathways. Non-metastatic tumours appeared to be characterised by: (a) reduced glycolysis and tricarboxylic acid cycle (TCA) activities, possibly resulting in slower NADH biosynthesis and reduced mitochondrial transport chain activity and ATP synthesis; (b) glutamate accumulation possibly related to reduced glutathione activity and reduced mTORC1 activity; and (c) a clear shift to lower phosphoscholine/glycerophosphocholine ratios and sphingomyelin levels. Within each tumour line, metabolic profiles also differed significantly between tumours (i.e., mice). Metastatic tumours exhibited marked inter-tumour changes in polar compounds, some suggesting different glycolytic capacities. Such tumours also showed larger intra-tumour variations in metabolites involved in nucleotide and cholesterol/fatty acid metabolism, in tandem with less changes in TCA and phospholipid metabolism, compared to non-metastatic tumours. This study shows the valuable contribution of untargeted NMR metabolomics to characterise tumour metabolism, thus opening enticing opportunities to find metabolic markers related to metastatic ability in endocrine breast cancer.

Assessment of Overall Survival in Glioma Patients as Predicted by Metabolomic Criteria

Objective: We assess the efficacy of the metabolomic profile from glioma biopsies in providing estimates of postsurgical Overall Survival in glioma patients.

Methods: Tumor biopsies from 46 patients bearing gliomas, obtained neurosurgically in the period 1992–1998, were analyzed by high resolution ¹H magnetic resonance spectroscopy (HR- ¹H MRS), following retrospectively individual postsurgical Overall Survival up to 720 weeks.

Results: The Overall Survival profile could be resolved in three groups; Short (shorter than 52 weeks, n = 19), Intermediate (between 53 and 364 weeks, n = 19) or Long (longer than 365 weeks, n = 8), respectively. Classical histopathological analysis assigned WHO grades II–IV to every biopsy but notably, some patients with low grade glioma depicted unexpectedly Short Overall Survival, while some patients with high grade glioma, presented unpredictably Long Overall Survival. To explore the reasons underlying these different responses, we analyzed HR-¹H MRS spectra from acid extracts of the same biopsies, to characterize the metabolite patterns associated to OS predictions. Poor prognosis was found in biopsies with higher contents of alanine, acetate, glutamate, total choline, phosphorylcholine, and glycine, while more favorable prognosis was achieved in biopsies with larger contents of total creatine, glycerol-phosphorylcholine, and myo-inositol. We then implemented a multivariate analysis to identify hierarchically the influence of metabolomic biomarkers on OS predictions, using a Classification Regression Tree (CRT) approach. The CRT based in metabolomic biomarkers grew up to three branches and split into eight nodes, predicting correctly the outcome of 94.7% of the patients in the Short Overall Survival group, 78.9% of the patients in the Intermediate Overall Survival group, and 75% of the patients in the Long Overall Survival group, respectively.

Conclusion: Present results indicate that metabolic profiling by HR-¹H MRS improves the Overall Survival predictions derived exclusively from classical histopathological gradings, thus favoring more precise therapeutic decisions.

Short-acquisition-time JPRESS and its application to paediatric brain tumours

OBJECTIVE

To develop and assess a short-duration JPRESS protocol for detection of overlapping metabolite biomarkers and its application to paediatric brain tumours at 3 Tesla.

MATERIALS AND METHODS

The short-duration protocol (6 min) was optimised and compared for spectral quality to a high-resolution (38 min) JPRESS protocol in a phantom and five healthy volunteers. The 6-min JPRESS was acquired from four paediatric brain tumours and compared with short-TE PRESS.

RESULTS

Metabolite identification between the 6- and 38-min protocols was comparable in phantom and volunteer data. For metabolites with Cramer-Rao lower bounds > 50%, interpretation of JPRESS increased confidence in assignment of lactate, myo-Inositol and scyllo-Inositol. JPRESS also showed promise for the detection of glycine and taurine in paediatric brain tumours when compared to short-TE MRS.

CONCLUSION

A 6-min JPRESS protocol is well tolerated in paediatric brain tumour patients. Visual inspection of a 6-min JPRESS spectrum enables identification of a range of metabolite biomarkers of clinical interest.

Characterization of Brain Metabolism by Nuclear Magnetic Resonance

The noninvasive, quantitative ability of nuclear magnetic resonance (NMR) spectroscopy to characterize small molecule metabolites has long been recognized as a major strength of its application in biology. Numerous techniques exist for characterizing metabolism in living, excised, or extracted tissue, with a particular focus on 1 H-based methods due to the high sensitivity and natural abundance of protons. With the increasing use of high magnetic fields, the utility of in vivo 1 H magnetic resonance spectroscopy (MRS) has markedly improved for measuring specific metabolite concentrations in biological tissues. Higher fields, coupled with recent developments in hyperpolarization, also enable techniques for complimenting 1 H measurements with spectroscopy of other nuclei, such as 31 P and 13 C, and for combining measurements of metabolite pools with metabolic flux measurements. We compare ex vivo and in vivo methods for studying metabolism in the brain using NMR and highlight insights gained through using higher magnetic fields, the advent of dissolution dynamic nuclear polarization, and combining in vivo MRS and ex vivo NMR approaches.

Multivoxel 1H-MR Spectroscopy Biometrics for Preoprerative Differentiation Between Brain Tumors

We investigated multivoxel proton magnetic resonance spectroscopy (¹H-MRS) biometrics for preoperative differentiation and prognosis of patients with brain metastases (MET), low-grade glioma (LGG) and high-grade glioma (HGG). In total, 33 patients (HGG, 14; LGG, 9; and 10 MET) were included. ¹H-MRS imaging (MRSI) data were assessed and neurochemical profiles for metabolites N-acetyl aspartate (NAA) + NAAG(NAA), Cr + PCr(total creatine, tCr), Glu + Gln(Glx), lactate (Lac), myo-inositol(Ins), GPC + PCho(total choline, tCho), and total lipids, and macromolecule (tMM) signals were estimated. Metabolites were reported as absolute concentrations or ratios to tCho or tCr levels. Voxels of interest in an MRSI matrix were labeled according to tissue. Logistic regression, receiver operating characteristic, and Kaplan-Meier survival analysis was performed. Across HGG, LGG, and MET, average Ins/tCho was shown to be prognostic for overall survival (OS): low values (≤1.29) in affected hemisphere predicting worse OS than high values (>1.29), (log rank < 0.007). Lip/tCho and Ins/tCho combined showed 100% sensitivity and specificity for both HGG/LGG (P < .001) and LGG/MET (P < .001) measured in nonenhancing/contrast-enhancing lesional tissue. Combining tCr/tCho in perilesional edema with tCho/tCr and NAA/tCho from ipsilateral normal- appearing tissue yielded 100% sensitivity and 81.8% specificity (P < .002) for HGG/MET. Best single biomarker: Ins/tCho for HGG/LGG and total lipid/tCho for LGG/MET showed 100% sensitivity and 75% and 100% specificity, respectively. HGG/MET; NAA/tCho showed 75% sensitivity and 84.6% specificity. Multivoxel 1H-MRSI provides prognostic information for OS for HGG/LGG/MET and a multibiometric approach for differentiation may equal or outperform single biometrics.

Integrative metabolic and transcriptomic profiling of prostate cancer tissue containing reactive stroma

Reactive stroma is a tissue feature commonly observed in the tumor microenvironment of prostate cancer and has previously been associated with more aggressive tumors. The aim of this study was to detect differentially expressed genes and metabolites according to reactive stroma content measured on the exact same prostate cancer tissue sample. Reactive stroma was evaluated using histopathology from 108 fresh frozen prostate cancer samples gathered from 43 patients after prostatectomy (Biobank1). A subset of the samples was analyzed both for metabolic (n = 85) and transcriptomic alterations (n = 78) using high resolution magic angle spinning magnetic resonance spectroscopy (HR-MAS MRS) and RNA microarray, respectively. Recurrence-free survival was assessed in patients with clinical follow-up of minimum five years (n = 38) using biochemical recurrence (BCR) as endpoint. Multivariate metabolomics and gene expression analysis compared low (≤15%) against high reactive stroma content (≥16%). High reactive stroma content was associated with BCR in prostate cancer patients even when accounting for the influence of Grade Group (Cox hazard proportional analysis, p = 0.013). In samples with high reactive stroma content, metabolites and genes linked to immune functions and extracellular matrix (ECM) remodeling were significantly upregulated. Future validation of these findings is important to reveal novel biomarkers and drug targets connected to immune mechanisms and ECM in prostate cancer. The fact that high reactive stroma grading is connected to BCR adds further support for the clinical integration of this histopathological evaluation.

Microdosing, isotopic labeling, radiotracers and metabolomics: relevance in drug discovery, development and safety

This review discusses the use of stable (¹³C, ²D) or radioactive isotopes (¹⁴C, ¹¹C, ¹⁸F, ¹³¹I, ⁶⁴Cu, ⁶⁸Ga) incorporated into the molecular structure of new drug entities for the purpose of pharmacokinetic or -dynamic studies. Metabolite in safety testing requires the administration of pharmacologically active doses. In such studies, radiotracers find application mainly in preclinical animal investigations, whereby LC-MS/MS is used to identify metabolite structure and drug-related effects. In contrast, first-in-human metabolite studies have to be carried out at nonpharmacological doses not exceeding 100 μg (microdose), which is generally too low for metabolite detection by LC-MS/MS. This short-coming can be overcome by specific radio- or isotopic labeling of the drug of interest and measurements using accelerator mass spectroscopy, single-photon emission computed tomography and positron emission tomography. Such combined radioisotope-based approaches permit Phase 0, first-in-human metabolite study.

Applications of high-resolution magic angle spinning MRS in biomedical studies II-Human diseases

High-resolution magic angle spinning (HRMAS) MRS is a powerful method for gaining insight into the physiological and pathological processes of cellular metabolism. Given its ability to obtain high-resolution spectra of non-liquid biological samples, while preserving tissue architecture for subsequent histopathological analysis, the technique has become invaluable for biochemical and biomedical studies. Using HRMAS MRS, alterations in measured metabolites, metabolic ratios, and metabolomic profiles present the possibility to improve identification and prognostication of various diseases and decipher the metabolomic impact of drug therapies. In this review, we evaluate HRMAS MRS results on human tissue specimens from malignancies and non-localized diseases reported in the literature since the inception of the technique in 1996. We present the diverse applications of the technique in understanding pathological processes of different anatomical origins, correlations with in vivo imaging, effectiveness of therapies, and progress in the HRMAS methodology.

Exploration of human brain tumour metabolism using pairwise metabolite-metabolite correlation analysis (MMCA) of HR-MAS 1H NMR spectra

METHODS

We quantified 378 HRMAS 1H NMR spectra of human brain tumours (132 glioblastomas, 101 astrocytomas, 75 meningiomas, 37 oligodendrogliomas and 33 metastases) from the eTumour database and looked for metabolic interactions by metabolite-metabolite correlation analysis (MMCA).

RESULTS

All tumour types showed remarkably similar metabolic correlations. Lactate correlated positively with alanine, glutamate with glutamine; creatine + phosphocreatine (tCr) correlated positively with lactate, alanine and choline + phosphocholine + glycerophosphocholine (tCho), and tCho correlated positively with lactate; fatty acids correlated negatively with lactate, glutamate + glutamine (tGlut), tCr and tCho. Oligodendrogliomas had fewer correlations but they still fitted that pattern.

CONCLUSIONS

Possible explanations include (i) glycolytic tumour cells (the Warburg effect) generating pyruvate which is converted to lactate, alanine, glutamate and then glutamine; (ii) an association between elevated glycolysis and increased choline turnover in membranes; (iii) an increase in the tCr pool to facilitate phosphocreatine-driven glutamate uptake; (iv) lipid signals come from cytosolic lipid droplets in necrotic or pre-necrotic tumour tissue that has lower concentrations of anabolic and catabolic metabolites. Additional metabolite exchanges with host cells may also be involved. If tumours co-opt a standard set of biochemical mechanisms to grow in the brain, then drugs might be developed to disrupt those mechanisms.

Specific Metabolomics Adaptations Define a Differential Regional Vulnerability in the Adult Human Cerebral Cortex

Brain neurons offer diverse responses to stresses and detrimental factors during development and aging, and as a result of both neurodegenerative and neuropsychiatric disorders. This multiplicity of responses can be ascribed to the great diversity among neuronal populations. Here we have determined the metabolomic profile of three healthy adult human brain regions-entorhinal cortex, hippocampus, and frontal cortex-using mass spectrometry-based technologies. Our results show the existence of a lessened energy demand, mitochondrial stress, and lower one-carbon metabolism (particularly restricted to the methionine cycle) specifically in frontal cortex. These findings, along with the better antioxidant capacity and lower mTOR signaling also seen in frontal cortex, suggest that this brain region is especially resistant to stress compared to the entorhinal cortex and hippocampus, which are more vulnerable regions. Globally, our results show the presence of specific metabolomics adaptations in three mature, healthy human brain regions, confirming the existence of cross-regional differences in cell vulnerability in the human cerebral cortex.

Evaluation of Cancer Metabolomics Using ex vivo High Resolution Magic Angle Spinning (HRMAS) Magnetic Resonance Spectroscopy (MRS)

According to World Health Organization (WHO) estimates, cancer is responsible for more deaths than all coronary heart disease or stroke worldwide, serving as a major public health threat around the world. High resolution magic angle spinning (HRMAS) magnetic resonance spectroscopy (MRS) has demonstrated its usefulness in the identification of cancer metabolic markers with the potential to improve diagnosis and prognosis for the oncology clinic, due partially to its ability to preserve tissue architecture for subsequent histological and molecular pathology analysis. Capable of the quantification of individual metabolites, ratios of metabolites, and entire metabolomic profiles, HRMAS MRS is one of the major techniques now used in cancer metabolomic research. This article reviews and discusses literature reports of HRMAS MRS studies of cancer metabolomics published between 2010 and 2015 according to anatomical origins, including brain, breast, prostate, lung, gastrointestinal, and neuroendocrine cancers. These studies focused on improving diagnosis and understanding patient prognostication, monitoring treatment effects, as well as correlating with the use of in vivo MRS in cancer clinics.

The clinical utility of multimodal MR image-guided needle biopsy in cerebral gliomas

PURPOSE

Our aim was to evaluate the diagnostic value of multimodal Magnetic Resonance (MR) Image in the stereotactic biopsy of cerebral gliomas, and investigate its implications.

MATERIALS AND METHODS

Twenty-four patients with cerebral gliomas underwent (1)H Magnetic Resonance Spectroscopy ((1)H-MRS)- and intraoperative Magnetic Resonance Imaging (iMRI)-supported stereotactic biopsy, and 23 patients underwent only the preoperative MRI-guided biopsy. The diagnostic yield, morbidity and mortality rates were analyzed. In addition, 20 patients underwent subsequent tumor resection, thus the diagnostic accuracy of the biopsy was further evaluated.

RESULTS

The diagnostic accuracies of biopsies evaluated by tumor resection in the trial groups were better than control groups (92.3% and 42.9%, respectively, p = 0.031). The diagnostic yield in the trial groups was better than the control groups, but the difference was not statistically significant (100% and 82.6%, respectively, p = 0.05). The morbidity and mortality rates were similar in both groups.

CONCLUSIONS

Multimodal MR image-guided glioma biopsy is practical and valuable. This technique can increase the diagnostic accuracy in the stereotactic biopsy of cerebral gliomas. Besides, it is likely to increase the diagnostic yield but requires further validation.

Noninvasive detection of glutamate predicts survival in pediatric medulloblastoma

PURPOSE

Medulloblastoma is the most common malignant brain tumor occurring in childhood and is a significant cause of morbidity and mortality in pediatric oncology. More intense treatment strategies are recommended for patients displaying high-risk factors; however, considerable variation in outcome remains, indicating a need for improved predictive markers. In this study, 1H magnetic resonance spectroscopy (MRS) was used to investigate noninvasive molecular biomarkers of survival in medulloblastoma.

EXPERIMENTAL DESIGN

MRS was performed on a series of 35 biopsy-confirmed medulloblastoma cases. One case was excluded because of poor quality MRS. The prognostic value of MRS detectable biomarkers was investigated using Cox regression, retrospectively (N=15). A subsequent validation analysis (N=19) was also performed to reduce the chance of type I errors. Where available, high-resolution ex vivo MRS of biopsy tissue was used to confirm biomarker assignments.

RESULTS

The retrospective analysis revealed that creatine, glutamate, and glycine were markers of survival (P<0.01). The validation analysis showed that glutamate was a robust marker, with a hazard ration (HR) of 8.0 for the full dataset (P=0.0003, N=34). A good correlation between in vivo and ex vivo MRS glutamate/total-choline was found (P=0.001), validating the in vivo assignment. Ex vivo glutamate/total-choline was also associated with survival (P<0.01).

CONCLUSION

The identification of glutamate as a predictive biomarker of survival in pediatric medulloblastoma provides a clinically viable risk factor and highlights the importance of more detailed studies into the metabolism of this disease. Noninvasive biomarker detection using MRS may offer improved disease monitoring and potential for widespread use following multicenter validation.

Characterization of metabolites in infiltrating gliomas using ex vivo ¹H high-resolution magic angle spinning spectroscopy

Gliomas are routinely graded according to histopathological criteria established by the World Health Organization. Although this classification can be used to understand some of the variance in the clinical outcome of patients, there is still substantial heterogeneity within and between lesions of the same grade. This study evaluated image-guided tissue samples acquired from a large cohort of patients presenting with either new or recurrent gliomas of grades II-IV using ex vivo proton high-resolution magic angle spinning spectroscopy. The quantification of metabolite levels revealed several discrete profiles associated with primary glioma subtypes, as well as secondary subtypes that had undergone transformation to a higher grade at the time of recurrence. Statistical modeling further demonstrated that these metabolomic profiles could be differentially classified with respect to pathological grading and inter-grade conversions. Importantly, the myo-inositol to total choline index allowed for a separation of recurrent low-grade gliomas on different pathological trajectories, the heightened ratio of phosphocholine to glycerophosphocholine uniformly characterized several forms of glioblastoma multiforme, and the onco-metabolite D-2-hydroxyglutarate was shown to help distinguish secondary from primary grade IV glioma, as well as grade II and III from grade IV glioma. These data provide evidence that metabolite levels are of interest in the assessment of both intra-grade and intra-lesional malignancy. Such information could be used to enhance the diagnostic specificity of in vivo spectroscopy and to aid in the selection of the most appropriate therapy for individual patients.

¹H magnetic resonance spectroscopy: a review of the current literature and its potential utility in veterinary oncology

Advanced imaging of veterinary cancer patients has evolved in recent years and modalities once limited to human medicine have now been described for diagnostic purposes in veterinary medicine (positron emission tomography/computed tomography, single-photon emission computed tomography, whole body magnetic resonance imaging). Magnetic resonance spectroscopy (MRS) is a non-invasive and non-ionizing technique that is well described in the human medical literature and is most frequently used to evaluate the metabolic activity of tissues with questionable malignant transformation. Differentiation of neoplastic tissue from surrounding normal tissue is dependent on variations in cellular metabolism. Positive identification of malignancy can be made when neoplastic alterations are occurring at the cellular level prior to gross anatomic changes. This improved, early detection of cancer occurrence (or recurrence) can improve patient survival and direct medical therapy. MRS techniques are largely underutilized in veterinary medicine, with current research predominantly limited to the brain (both evaluation of normal and diseased tissue). Given the clinical utility of MRS in humans, the technique may also be useful in the staging of cancer in veterinary medicine.

Differentiating diffuse World Health Organization grade II and IV astrocytomas with ex vivo magnetic resonance spectroscopy

BACKGROUND

The prognosis and treatment of astrocytomas, which are primary brain tumors, vary depending on the grade of the tumor, necessitating a precise preoperative classification. Magnetic resonance spectroscopy (MRS) provides information about metabolites in tissues and is an emerging noninvasive tool to improve diagnostic accuracy in patients with intracranial neoplasia.

OBJECTIVE

To investigate whether ex vivo MRS could differentiate World Health Organization grade II (A-II) and IV astrocytomas (glioblastomas; GBM) and to correlate MR spectral profiles with clinical parameters.

METHODS

Patients with A-II and GBM (n = 58) scheduled for surgical resection were enrolled. Tumor specimens were collected during surgery and stored in liquid nitrogen before being analyzed with high-resolution magic angle spinning MRS. The tumors were histopathologically classified according to World Health Organization criteria as GBM (n = 48) and A-II (n = 10).

RESULTS

Multivariate analysis of ex vivo proton high-resolution magic angle spinning spectra MRS showed differences in the metabolic profiles of different grades of astrocytomas. A-II had higher levels of glycerophosphocholine and myo-inositol than GBM. The latter had more phosphocholine, glycine, and lipids. We observed a significant metabolic difference between recurrent and nonrecurrent GBM (P < .001). Primary GBM had more phosphocholine than recurrent GBM. A significant correlation (P < .001) between lipid and lactate signals and histologically estimated percentage of necrosis was observed in GBM. Spectral profiles were not correlated with age, survival, or magnetic resonance imaging-defined tumor volume.

CONCLUSION

Ex vivo MRS can differentiate astrocytomas based on their metabolic profiles.

Spatially matched in vivo and ex vivo MR metabolic profiles of prostate cancer -- investigation of a correlation with Gleason score

MR metabolic profiling of the prostate is promising as an additional diagnostic approach to separate indolent from aggressive prostate cancer. The objective of this study was to assess the relationship between the Gleason score and the metabolic biomarker (choline + creatine + spermine)/citrate (CCS/C) measured by ex vivo high-resolution magic angle spinning MRS (HR-MAS MRS) and in vivo MRSI, and to evaluate the correlation between in vivo- and ex vivo-measured metabolite ratios from spatially matched prostate regions. Patients (n = 13) underwent in vivo MRSI prior to radical prostatectomy. A prostate tissue slice was snap-frozen shortly after surgery and the locations of tissue samples (n = 40) collected for ex vivo HR-MAS were matched to in vivo MRSI voxels (n = 40). In vivo MRSI was performed on a 3T clinical MR system and ex vivo HR-MAS on a 14.1T magnet. Relative metabolite concentrations were calculated by LCModel fitting of in vivo spectra and by peak integration of ex vivo spectra. Spearman's rank correlations (ρ) between CCS/C from in vivo and ex vivo MR spectra, and with their corresponding Gleason score, were calculated. There was a strong positive correlation between the Gleason score and CCS/C measured both in vivo and ex vivo (ρ = 0.77 and ρ = 0.69, respectively; p < 0.001), and between in vivo and ex vivo metabolite ratios from spatially matched regions (ρ = 0.67, p < 0.001). Our data indicate that MR metabolic profiling is a potentially useful tool for the assessment of cancer aggressiveness. Moreover, the good correlation between in vivo- and ex vivo-measured CCS/C demonstrates that our method is able to bridge MRSI and HR-MAS molecular analysis.

Spermine and citrate as metabolic biomarkers for assessing prostate cancer aggressiveness

Separating indolent from aggressive prostate cancer is an important clinical challenge for identifying patients eligible for active surveillance, thereby reducing the risk of overtreatment. The purpose of this study was to assess prostate cancer aggressiveness by metabolic profiling of prostatectomy tissue and to identify specific metabolites as biomarkers for aggressiveness. Prostate tissue samples (n = 158, 48 patients) with a high cancer content (mean: 61.8%) were obtained using a new harvesting method, and metabolic profiles of samples representing different Gleason scores (GS) were acquired by high resolution magic angle spinning magnetic resonance spectroscopy (HR-MAS). Multivariate analysis (PLS, PLS-DA) and absolute quantification (LCModel) were used to examine the ability to predict cancer aggressiveness by comparing low grade (GS = 6, n = 30) and high grade (GS≥7, n = 81) cancer with normal adjacent tissue (n = 47). High grade cancer tissue was distinguished from low grade cancer tissue by decreased concentrations of spermine (p = 0.0044) and citrate (p = 7.73·10⁻⁴), and an increase in the clinically applied (total choline+creatine+polyamines)/citrate (CCP/C) ratio (p = 2.17·10⁻⁴). The metabolic profiles were significantly correlated to the GS obtained from each tissue sample (r = 0.71), and cancer tissue could be distinguished from normal tissue with sensitivity 86.9% and specificity 85.2%. Overall, our findings show that metabolic profiling can separate aggressive from indolent prostate cancer. This holds promise for the benefit of applying in vivo magnetic resonance spectroscopy (MRS) within clinical MR imaging investigations, and HR-MAS analysis of transrectal ultrasound-guided biopsies has a potential as an additional diagnostic tool.

Minimization of spectral pattern changes during HRMAS experiments at 37 degrees celsius by prior focused microwave irradiation

OBJECT

High-resolution magic angle spinning (HRMAS) magnetic resonance spectroscopy provides detailed metabolomic information from intact tissue. However, long acquisition times and high rotation speed may lead to timedependent spectral pattern changes, which may affect proper interpretation of results. We report a strategy to minimize those changes, even at physiological recording temperature.

MATERIALS AND METHODS

Glioblastoma(Gbm) tumours were induced in 12 mice by stereotactic injection of GL261 cells. Animals were sacrificed and tumours were removed and stored in liquid N2. Half of the samples were exposed to focused microwave (FMW) irradiation prior to HRMAS while the other half was not. Time-course experiments (374 min at 37°C, 9.4T, 3,000 Hz spinning rate) were carried out to monitor spectral pattern changes. Differences were assessed with Unianova test while post-HRMAS histopathology analysis was performed to assess tissue integrity.

RESULTS

Significant changes (up to 1.7 fold) were observed in samples without FMW irradiation in several spectral regions e.g. mobile lipids/lactate (0.90-1.30 ppm), acetate (1.90 ppm), N-acetyl aspartate (2.00 ppm), and Choline-containing compounds (3.19-3.25 ppm). No significant changes in the spectral pattern of FMW-irradiated samples were recorded.

CONCLUSION

We describe here a successful strategy to minimize spectral pattern changes in mouse Gbm samples using a FMW irradiation system.

Quantitative assessment of neurochemical changes in a rat model of long-term alcohol consumption as detected by in vivo and ex vivo proton nuclear magnetic resonance spectroscopy

The aim of present study was to quantitatively investigate the neurochemical profile of the frontal cortex region in a rat model of long-term alcohol consumption, by using in vivo proton magnetic resonance spectroscopy ((1)H-MRS) at 4.7 T and ex vivo(1)H high-resolution magic angle spinning (HR-MAS) technique at 11.7 T. Twenty male rats were divided into two groups and fed a liquid diet for 10 weeks. After 10 weeks, in vivo(1)H MRS spectra were acquired from the frontal cortex brain region. After in vivo(1)H MRS experiments, all animals were sacrificed and 20 frontal cortex tissue samples were harvested. All tissue examinations were performed with the 11.7 T HR-MAS spectrometer and high-resolution spectra were acquired. The in vivo and ex vivo spectra were quantified as absolute metabolite concentrations and normalized ratios of total signal-intensity (i.e., metabolitesNorm), respectively. The absolute quantifications of in vivo spectra showed significantly higher glycerophosphocholine plus phosphocholine (GPC+PCh) and lower myo-inositol (mIns) concentrations in ethanol-treated rats compared to controls. The quantifications of ex vivo spectra showed significantly higher PChNorm, ChoNorm and tChoNorm, and lower GPCNorm and mInsNorm ratio levels in ethanol-treated rats compared to controls. Our findings suggest that reduced mIns concentrations caused by the long-term alcohol consumption may lead to hypo-osmolarity syndrome and astrocyte hyponatremia. In addition, increased choline-containing compound concentrations may reflect an increased cell turnover rate of phosphatidylcholine and other phospholipids, indicating an adaptive mechanism. Therefore, these results might be utilized as key markers in chronic alcohol intoxication metabolism.

Magnetic resonance spectroscopy metabolite profiles predict survival in paediatric brain tumours

Background

Brain tumours cause the highest mortality and morbidity rate of all childhood tumour groups and new methods are required to improve clinical management. ¹H magnetic resonance spectroscopy (MRS) allows non-invasive concentration measurements of small molecules present in tumour tissue, providing clinically useful imaging biomarkers. The primary aim of this study was to investigate whether MRS detectable molecules can predict the survival of paediatric brain tumour patients.

Patients and methods

Short echo time (30 ms) single voxel ¹H MRS was performed on children attending Birmingham Children’s Hospital with a suspected brain tumour and 115 patients were included in the survival analysis. Patients were followed-up for a median period of 35 months and Cox-Regression was used to establish the prognostic value of individual MRS detectable molecules. A multivariate model of survival was also investigated to improve prognostic power.

Results

Lipids and scyllo-inositol predicted poor survival whilst glutamine and N-acetyl aspartate predicted improved survival (p < 0.05). A multivariate model of survival based on three MRS biomarkers predicted survival with a similar accuracy to histologic grading (p < 5e–5). A negative correlation between lipids and glutamine was found, suggesting a functional link between these molecules.

Conclusions

MRS detectable biomolecules have been identified that predict survival of paediatric brain tumour patients across a range of tumour types. The evaluation of these biomarkers in large prospective studies of specific tumour types should be undertaken. The correlation between lipids and glutamine provides new insight into paediatric brain tumour metabolism that may present novel targets for therapy.

MRS study of meningeal hemangiopericytoma and edema: a comparison with meningothelial meningioma

Intracranial hemangiopericytomas (HPCs) are rare tumors and their radiological appearance resembles that of meningiomas, especially meningothelial meningiomas. To increase the knowledge on the biochemical composition of this type of tumor for better diagnosis and prognosis, we performed a molecular study using ex vivo high resolution magic angle spinning (HR-MAS) magnetic resonance spectroscopy (MRS) perfomed on HPC and peritumoral edematous tissues. Moreover, to help in the discrimination between HPC and meningothelial meningioma we compared the ex vivo HR-MAS spectra of samples from one patient with HPC and 5 patients affected by meningothelial meningioma. Magnetic resonance imaging (MRI), in vivo localized single voxel 1H-MRS was also performed on the same patients prior to surgery and the in vivo and ex vivo MRS spectra were compared. We observed the presence of OH-butyrate, together with glucose in HPC and a low amount of N-acetylaspartate in the edema, that may reflect neuronal alteration responsible for associated epilepsy. Many differences between HPC and meningothelial meningioma were identified. The relative ratios of myo-inositol, glucose and gluthatione with respect to glutamate are higher in HPC compared to meningioma; whereas the relative ratios of creatine, glutamine, alanine, glycine and choline-containing compounds with respect to glutamate are lower in HPC compared to meningioma. These data will be useful to improve the interpretation of in vivo MRS spectra resulting in a more accurate diagnosis of these rare tumors.

In vivo characterization of several rodent glioma models by 1H MRS

The assessment of metabolites by (1)H MRS can provide information regarding glioma growth, and may be able to distinguish between different glioma models. Rat C6, 9 L/LacZ, F98 and RG2, and mouse GL261, cells were intracerebrally implanted into the respective rodents, and human U87 MG cells were implanted into athymic rats. Ethyl-nitrosourea induction was also used. Glioma metabolites [e.g. total choline (tCho), total creatine (tCr), N-acetylaspartate (NAA), lactate (Lac), glutamine (Gln), glutamate (Glu), aspartate (Asp), guanosine (Gua), mobile lipids and macromolecules (MMs)] were assessed from (1)H MRS using point-resolved spectroscopy (PRESS) [TE = 24 ms; TR = 2500 ms; variable pulse power and optimized relaxation delay (VAPOR) water suppression; 27-μL and 8-μL voxels in rats and mice, respectively] at 7 T. Alterations in metabolites (Totally Automatic Robust Quantitation in NMR, TARQUIN) in tumors were characterized by increases in lipids (Lip1.3: 8.8-54.5 mM for C6 and GL261) and decreases in NAA (1.3-2.0 mM for RG2, GL261 and C6) and tCr (0.8-4.0 mM for F98, RG2, GL261 and C6) in some models. F98, RG2, GL261 and C6 models all showed significantly decreased (p < 0.05) tCr, and RG2, GL261 and C6 models all exhibited significantly decreased (p < 0.05) NAA. The RG2 model showed significantly decreased (p < 0.05) Gln and Glu, the C6 model significantly decreased (p < 0.05) Asp, and the F98 and U87 models significantly decreased (p < 0.05) Gua, compared with controls. The GL261 model showed the greatest alterations in metabolites. (1)H MRS was able to differentiate the metabolic profiles in many of the seven rodent glioma models assessed. These models are considered to resemble certain characteristics of human glioblastomas, and this study may be helpful in selecting appropriate models.

Magnetic resonance spectroscopy of cancer metabolism and response to therapy

Magnetic resonance spectroscopy allows noninvasive in vivo measurements of biochemical information from living systems, ranging from cultured cells through experimental animals to humans. Studies of biopsies or extracts offer deeper insights by detecting more metabolites and resolving metabolites that cannot be distinguished in vivo. The pharmacokinetics of certain drugs, especially fluorinated drugs, can be directly measured in vivo. This review briefly describes these methods and their applications to cancer metabolism, including glycolysis, hypoxia, bioenergetics, tumor pH, and tumor responses to radiotherapy and chemotherapy.

High-resolution magic angle spinning NMR spectroscopy of human osteoarthritic cartilage

Osteoarthritis (OA) is a degenerative disease of the joints and results in changes in the biochemical composition of cartilage. Previous studies have been undertaken that have used high-resolution NMR spectroscopy to study the biochemical composition of porcine, canine and bovine cartilage. In the present study, high-resolution magical angle spinning (HR-MAS) NMR spectroscopy at 11.7 T has been used to characterize metabolites and detect differences in the spectral signature of human knee articular cartilage from non-OA healthy cadaver knees and samples acquired from severe OA patients at the time of total knee replacement surgery. A statistically significant difference in the alanine (1.47 p.p.m.), N-acetyl (2.04 p.p.m.), choline (3.25 p.p.m.) and glycine (3.55 p.p.m.) metabolite levels was observed between healthy and OA specimens. The results of the present study indicate that a decrease in the intensity of N-acetyl resonance occurs in the later stages of OA. A positive correlation of the N-acetyl levels as measured by (1)H HR-MAS NMR spectroscopy with the total proteoglycan content in the same cartilage specimens as measured by the glycosaminoglycan (GAG) assay was observed. This indicates that N-acetyl can serve as an important bio-marker of OA disease progression. A decrease in the alanine concentration in OA may be attributed to the degradation of the collagen framework with disease progression and eventual loss of the degradation products that are transported from cartilage into the synovial cavity.

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

OBJECTIVE

The objective of this study was to determine whether metabolic parameters derived from ex vivo analysis of tissue samples are predictive of biologic characteristics of recurrent low grade gliomas (LGGs). This was achieved by exploring the use of multivariate pattern recognition methods to generate statistical models of the metabolic characteristics of recurrent LGGs that correlate with aggressive biology and poor clinical outcome.

METHODS

Statistical models were constructed to distinguish between patients with recurrent gliomas that had undergone malignant transformation to a higher grade and those that remained grade 2. The pattern recognition methods explored in this paper include three filter-based feature selection methods (chi-square, gain ratio, and two-way conditional probability), a genetic search wrapper-based feature subset selection algorithm, and five classification algorithms (linear discriminant analysis, logistic regression, functional trees, support vector machines, and decision stump logit boost). The accuracy of each pattern recognition framework was evaluated using leave-one-out cross-validation and bootstrapping.

MATERIALS

The population studied included fifty-three patients with recurrent grade 2 gliomas. Among these patients, seven had tumors that transformed to grade 4, twenty-four had tumors that transformed to grade 3, and twenty-two had tumors that remained grade 2. Image-guided tissue samples were obtained from these patients using surgical navigation software. Part of each tissue sample was examined by a pathologist for histological features and for consistency with the tumor grade diagnosis. The other part of the tissue sample was analyzed with ex vivo nuclear magnetic resonance (NMR) spectroscopy.

RESULTS

Distinguishing between recurrent low grade gliomas that transformed to a higher grade and those that remained grade 2 was achieved with 96% accuracy, using areas of the ex vivo NMR spectrum corresponding to myoinositol, 2-hydroxyglutarate, hypo-taurine, choline, glycerophosphocholine, phosphocholine, glutathione, and lipid. Logistic regression and decision stump boosting models were able to distinguish between recurrent gliomas that transformed to a higher grade and those that did not with 100% training accuracy (95% confidence interval [93-100%]), 96% leave-one-out cross-validation accuracy (95% confidence interval [87-100%]), and 96% bootstrapping accuracy (95% confidence interval [95-97%]). Linear discriminant analysis, functional trees, and support vector machines were able to achieve leave-one-out cross-validation accuracy above 90% and bootstrapping accuracy above 85%. The three feature ranking methods were comparable in performance.

CONCLUSIONS

This study demonstrates the feasibility of using quantitative pattern recognition methods for the analysis of metabolic data from brain tissue obtained during the surgical resection of gliomas. All pattern recognition techniques provided good diagnostic accuracies, though logistic regression and decision stump boosting slightly outperform the other classifiers. These methods identified biomarkers that can be used to detect malignant transformations in individual low grade gliomas, and can lead to a timely change in treatment for each patient.

Ex vivo detection for chronic ethanol consumption-induced neurochemical changes in rats

The aim of this study was to quantitatively investigate the chronic ethanol-induced cerebral metabolic changes in various regions of the rat brain, using the proton high resolution magic angle spinning spectroscopy technique. The rats were divided into two groups (control group: N=11, ethanol-treated group: N=11) and fed with the liquid diets for 10 weeks. In each week, the mean intake volumes of liquid diet were measured. The brain tissues, including cerebellum (Cere), frontal cortex (FC), hippocampus (Hip), occipital cortex (OC) and thalamus (Thal), were harvested immediately after the end of experiments. The ex vivo proton spectra for the five brain regions were acquired with the Carr-Purcell-Meiboom-Gill (CPMG) pulse sequence at 500-MHz NMR spectrometer. All of the spectra were processed using the LCModel software, with simulated basis-set file, and the metabolite levels were referenced to total creatine. In the ethanol liquid diet group, there were significant increases in the metabolites ratio levels, as compared to control (Cere: alanine, glutathione, and N-acetlyaspartate; FC: phosphocholine and taurine; Hip: alanine, glutamine, and N-acetylaspartate; OC: glutamine; Thal: alanine, γ-aminobutyric acid, glutamate, glycerophosphocholine, phosphocholine, taurine, and free choline). However, in the ethanol liquid diet group, the myo-inositol levels of the OC were significantly lower. The present study demonstrates how chronic ethanol consumption affects cerebral metabolites in the chronic ethanol-treated rat. Therefore, this result could be useful to pursue clinical applications for quantitative diagnosis in human alcoholism.

MRS and MRSI guidance in molecular medicine: targeting and monitoring of choline and glucose metabolism in cancer

MRS and MRSI are valuable tools for the detection of metabolic changes in tumors. The currently emerging era of molecular medicine, which is shaped by molecularly targeted anticancer therapies combined with molecular imaging of the effects of such therapies, requires powerful imaging technologies that are able to detect molecular information. MRS and MRSI are such technologies that are able to detect metabolites arising from glucose and choline metabolism in noninvasive in vivo settings and at higher resolution in tissue samples. The roles played by MRS and MRSI in the diagnosis of different types of cancer, as well as in the early monitoring of the tumor response to traditional chemotherapies, are reviewed. The emerging roles of MRS and MRSI in the development and detection of novel targeted anticancer therapies that target oncogenic signaling pathways or markers in choline or glucose metabolism are discussed.

MR-visible lipids and the tumor microenvironment

MR-visible lipids or mobile lipids are defined as lipids that are observable using proton MRS in cells and tissues. These MR-visible lipids are composed of triglycerides and cholesterol esters that accumulate in neutral lipid droplets, where their MR visibility is conferred as a result of the increased molecular motion available in this unique physical environment. This review discusses the factors that lead to the biogenesis of MR-visible lipids in cancer cells and in other cell types, such as immune cells and fibroblasts. We focus on the accumulations of mobile lipids that are inducible in cultured cells by a number of stresses, including culture conditions, and in response to activating stimuli or apoptotic cell death induced by anticancer drugs. This is compared with animal tumor models, where increases in mobile lipids are observed in response to chemo- and radiotherapy, and to human tumors, where mobile lipids are observed predominantly in high-grade brain tumors and in regions of necrosis. Conducive conditions for mobile lipid formation in the tumor microenvironment are discussed, including low pH, oxygen availability and the presence of inflammatory cells. It is concluded that MR-visible lipids appear in cancer cells and human tumors as a stress response. Mobile lipids stored as neutral lipid droplets may play a role in the detoxification of the cell or act as an alternative energy source, especially in cancer cells, which often grow in ischemic/hypoxic environments. The role of MR-visible lipids in cancer diagnosis and the assessment of the treatment response in both animal models of cancer and human brain tumors is also discussed. Although technical limitations exist in the accurate detection of intratumoral mobile lipids, early increases in mobile lipids after therapeutic interventions may be useful as a potential biomarker for the assessment of treatment response in cancer.

Assessment of therapeutic response and treatment planning for brain tumors using metabolic and physiological MRI

MRI is routinely used for diagnosis, treatment planning and assessment of response to therapy for patients with glioma. Gliomas are spatially heterogeneous and infiltrative lesions that are quite variable in terms of their response to therapy. Patients classified as having low-grade histology have a median overall survival of 7 years or more, but need to be monitored carefully to make sure that their tumor does not upgrade to a more malignant phenotype. Patients with the most aggressive grade IV histology have a median overall survival of 12-15 months and often undergo multiple surgeries and adjuvant therapies in an attempt to control their disease. Despite improvements in the spatial resolution and sensitivity of anatomic images, there remain considerable ambiguities in the interpretation of changes in the size of the gadolinium-enhancing lesion on T(1) -weighted images as a measure of treatment response, and in differentiating between treatment effects and infiltrating tumor within the larger T(2) lesion. The planning of focal therapies, such as surgery, radiation and targeted drug delivery, as well as a more reliable assessment of the response to therapy, would benefit considerably from the integration of metabolic and physiological imaging techniques into routine clinical MR examinations. Advanced methods that have been shown to provide valuable data for patients with glioma are diffusion, perfusion and spectroscopic imaging. Multiparametric examinations that include the acquisition of such data are able to assess tumor cellularity, hypoxia, disruption of normal tissue architecture, changes in vascular density and vessel permeability, in addition to the standard measures of changes in the volume of enhancing and nonenhancing anatomic lesions. This is particularly critical for the interpretation of the results of Phase I and Phase II clinical trials of novel therapies, which are increasingly including agents that are designed to have anti-angiogenic and anti-proliferative properties as opposed to having a direct effect on tumor cell viability.

Rapid metabolic evolution in human prefrontal cortex

Human evolution is characterized by the rapid expansion of brain size and drastic increase in cognitive capabilities. It has long been suggested that these changes were accompanied by modifications of brain metabolism. Indeed, human-specific changes on gene expression or amino acid sequence were reported for a number of metabolic genes, but actual metabolite measurements in humans and apes have remained scarce. Here, we investigate concentrations of more than 100 metabolites in the prefrontal and cerebellar cortex in 49 humans, 11 chimpanzees, and 45 rhesus macaques of different ages using gas chromatography-mass spectrometry (GC-MS). We show that the brain metabolome undergoes substantial changes, both ontogenetically and evolutionarily: 88% of detected metabolites show significant concentration changes with age, whereas 77% of these metabolic changes differ significantly among species. Although overall metabolic divergence reflects phylogenetic relationships among species, we found a fourfold acceleration of metabolic changes in prefrontal cortex compared with cerebellum in the human lineage. These human-specific metabolic changes are paralleled by changes in expression patterns of the corresponding enzymes, and affect pathways involved in synaptic transmission, memory, and learning.

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

BACKGROUND

High-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.

RESULTS

1D 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.

CONCLUSIONS

A 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.