High-resolution magic angle spinning MRS of breast cancer tissue

Effects of intra- and post-operative ischemia on the metabolic profile of clinical liver tissue specimens monitored by NMR

Metabolomic profiles of tissues could greatly contribute to advancements in personalized medicine but are influenced by differences in adopted preanalytical procedures; nonhomogeneous pre- and post-excision ischemia times are potential sources of variability. In this study, we monitored the impact of ischemia on the metabolic profiles, acquired with high-resolution magic-angle-spinning (1)H NMR, of 162 human liver samples collected during and up to 6 h after routine surgery. The profiles changed significantly as a function of intraoperative warm ischemia (WI) and postresection cold ischemia (CI) time, with significant variations in the concentration of the same 16 metabolites. Therefore, a tight control of the preanalytical phase is essential for reliable metabolomic analyses of liver diseases. The NMR profiles provide a reliable "fingerprint" of ischemia and have predictive value: the best-performing predictive models are found to discriminate extreme time points of CI (0' vs 360 ') in the training set with cross-validation accuracy of ~90%; samples in the validation cohort can discriminate short (≤60') from long (≥180') CI with an accuracy of ~80%. For WI, the corresponding figures are 95.6 and 92%, respectively. Therefore, ischemia NMR profiles might become a tool for tissue quality control in biobanks.

Metabolic changes in psoriatic skin under topical corticosteroid treatment

Background

MR spectroscopy of intact biopsies can provide a metabolic snapshot of the investigated tissue. The aim of the present study was to explore the metabolic pattern of uninvolved skin, psoriatic skin and corticosteroid treated psoriatic skin.

Methods

The three types of skin biopsy samples were excised from patients with psoriasis (N = 10). Lesions were evaluated clinically, and tissue biopsies were excised and analyzed by one-dimensional ¹H MR spectroscopy. Relative levels were calculated for nine tissue metabolites. Subsequently, relative amounts of epidermis, dermis and subcutaneous tissue were scored by histopathological evaluation of HES stained sections.

Results

Seven out of 10 patients experienced at least 40% reduction in clinical score after corticosteroid treatment. Tissue biopsies from psoriatic skin contained lower levels of the metabolites myo-inositol and glucose, and higher levels of choline and taurine compared to uninvolved skin. In corticosteroid treated psoriatic skin, tissue levels of glucose, myo-inositol, GPC and glycine were increased, whereas choline was reduced, in patients with good therapeutic effect. These tissue levels are becoming more similar to metabolite levels in uninvolved skin.

Conclusion

This MR method demonstrates that metabolism in psoriatic skin becomes similar to that of uninvolved skin after effective corticosteroid treatment. MR profiling of skin lesions reflect metabolic alterations related to pathogenesis and treatment effects.

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.

Nuclear magnetic resonance spectroscopy is highly sensitive for lipid-soluble metabolites

Although the water-soluble metabolite profile of human mesenchymal stem cells is known, the lipid profile still needs further investigation. In this study, methanol-chloroform was used to extract pid-soluble metabolites and perchloric acid was used to extract water-soluble metabolites. Furthermore, a dual phase extraction method using methanol-chloroform and water was used to obtain both water and lipid fractions simultaneously. All metabolite extractions were analyzed on a 9.4T high-resolution nuclear magnetic resonance spectrometer. Metabolite resonance peaks were assigned in the acquired spectra according to the chemical shift, and the extraction efficiency of ferent methods was compared. Results showed that in the spectra of water-soluble extracts, major metabolites comprised low molecular weight metabolites, including lactate, acetic acid, fatty acids, threonine, glutamic acid, creatine, choline and its derivatives, while in the spectra of lipid-soluble extracts, most metabolites were assigned to fatty acids. Among the different extraction procedures, perchloric acid was more efficient in extracting water-soluble metabolites and methanol-chloroform was efficient in extracting organic components compared with the dual phase extraction method. Nuclear magnetic resonance spectroscopy showed that as low as 0.7 mg organic yield was enough to obtain clear resonance peaks, while about 6.0 mg water-soluble yield was needed to obtain relatively favorable spectral lines. These results show that the efficiency of extracting water and lipid fractions is higher using perchloric acid and methanol-chloroform compared with dual phase extraction and that nuclear magnetic resonance spectroscopy is highly sensitive for analyzing lipid-soluble extracts.

Therapeutic and preventive effects of methylene blue on Alzheimer's disease pathology in a transgenic mouse model

Methylene blue (MB) belongs to the phenothiazinium family. It has been used to treat a variety of human conditions and has beneficial effects on the central nervous system in rodents with and without brain alteration. The present study was designed to test whether chronic MB treatment taken after (therapeutic effect) or before (preventive effect) the onset of beta-amyloid pathology influences cognition in a transgenic mouse model (APP/PS1). In addition, the present study aims at revealing whether these behavioral effects might be related to brain alteration in beta-amyloid deposition. To this end, we conducted an in vivo study and compared two routes of drug administration, drinking water versus intraperitoneal injection. Results showed that transgenic mice treated with MB orally or following intraperitoneal injection were protected from cognitive impairments in a variety of social, learning, and exploratory tasks. Immunoreactive beta-amyloid deposition was significantly reduced in the hippocampus and adjacent cortex in MB-treated transgenic mice. Interestingly, these beneficial effects were observed independently of beta-amyloid load at the time of MB treatment. This suggests that MB treatment is beneficial at both therapeutic and preventive levels. Using solid-state High Resolution Magic Angle Spinning Nuclear Magnetic Resonance (HRMAS-NMR), we showed that MB administration after the onset of amyloid pathology significantly restored the concentration of two metabolites related to mitochondrial metabolism, namely alanine and lactate. We conclude that MB might be useful for the therapy and prevention of Alzheimer's disease. This article is part of the Special Issue entitled 'The Synaptic Basis of Neurodegenerative Disorders'.

A review of applications of metabolomics in cancer

Cancer is a devastating disease that alters the metabolism of a cell and the surrounding milieu. Metabolomics is a growing and powerful technology capable of detecting hundreds to thousands of metabolites in tissues and biofluids. The recent advances in metabolomics technologies have enabled a deeper investigation into the metabolism of cancer and a better understanding of how cancer cells use glycolysis, known as the “Warburg effect,” advantageously to produce the amino acids, nucleotides and lipids necessary for tumor proliferation and vascularization. Currently, metabolomics research is being used to discover diagnostic cancer biomarkers in the clinic, to better understand its complex heterogeneous nature, to discover pathways involved in cancer that could be used for new targets and to monitor metabolic biomarkers during therapeutic intervention. These metabolomics approaches may also provide clues to personalized cancer treatments by providing useful information to the clinician about the cancer patient’s response to medical interventions.

Metabolomics approach for predicting response to neoadjuvant chemotherapy for breast cancer

Breast cancer is a clinically heterogeneous disease, which necessitates a variety of treatments and leads to different outcomes. As an example, only some women will benefit from chemotherapy. Identifying patients who will respond to chemotherapy and thereby improve their long-term survival has important implications to treatment protocols and outcomes, while identifying non responders may enable these patients to avail themselves of other investigational approaches or other potentially effective treatments. In this study, serum metabolite profiling was performed to identify potential biomarker candidates that can predict response to neoadjuvant chemotherapy for breast cancer. Metabolic profiles of serum from patients with complete (n = 8), partial (n = 14) and no response (n = 6) to chemotherapy were studied using a combination of nuclear magnetic resonance (NMR) spectroscopy, liquid chromatography-mass spectrometry (LC-MS) and statistical analysis methods. The concentrations of four metabolites, three (threonine, isoleucine, glutamine) from NMR and one (linolenic acid) from LC-MS were significantly different when comparing response to chemotherapy. A prediction model developed by combining NMR and MS derived metabolites correctly identified 80% of the patients whose tumors did not show complete response to chemotherapy. These results show promise for larger studies that could result in more personalized treatment protocols for breast cancer patients.

Magnetic resonance in the detection of breast cancers of different histological types

Breast cancer incidence is increasing worldwide. Early detection is critical for long-term patient survival, as is monitoring responses to chemotherapy for management of the disease. Magnetic resonance imaging and spectroscopy (MRI/MRS) has gained in importance in the last decade for the diagnosis and monitoring of breast cancer therapy. The sensitivity of MRI/MRS for anatomical delineation is very high and the consensus is that MRI is more sensitive in detection than x-ray mammography. Advantages of MRS include delivery of biochemical information about tumor metabolism, which can potentially assist in the staging of cancers and monitoring responses to treatment. The roles of MRS and MRI in screening and monitoring responses to treatment of breast cancer are reviewed here. We rationalize how it is that different histological types of breast cancer are differentially detected and characterized by MR methods.

Feasibility of MR metabolomics for immediate analysis of resection margins during breast cancer surgery

In this study, the feasibility of high resolution magic angle spinning (HR MAS) magnetic resonance spectroscopy (MRS) of small tissue biopsies to distinguish between tumor and non-involved adjacent tissue was investigated. With the current methods, delineation of the tumor borders during breast cancer surgery is a challenging task for the surgeon, and a significant number of re-surgeries occur. We analyzed 328 tissue samples from 228 breast cancer patients using HR MAS MRS. Partial least squares discriminant analysis (PLS-DA) was applied to discriminate between tumor and non-involved adjacent tissue. Using proper double cross validation, high sensitivity and specificity of 91% and 93%, respectively was achieved. Analysis of the loading profiles from both principal component analysis (PCA) and PLS-DA showed the choline-containing metabolites as main biomarkers for tumor content, with phosphocholine being especially high in tumor tissue. Other indicative metabolites include glycine, taurine and glucose. We conclude that metabolic profiling by HR MAS MRS may be a potential method for on-line analysis of resection margins during breast cancer surgery to reduce the number of re-surgeries and risk of local recurrence.

2-hydroxyglutarate as a magnetic resonance biomarker for glioma subtyping

Mutations in the isocitrate dehydrogenase (IDH) genes are frequently found in gliomas and in a fraction of acute myeloid leukemia patients. This results in the production of an oncometabolite, 2-hydroxyglutarate (2-HG). Glioma patients harboring IDH mutations have a longer survival than their wild-type counterparts. 2-HG has been detected noninvasively in gliomas with IDH mutations using magnetic resonance spectroscopy (MRS), suggesting its potential clinical relevance for identifying glioma subtypes with better prognosis. In this paper, the recent developments in the MRS detection of the 2-HG in gliomas are reviewed, including the therapeutic potentials and translational values.

Metabolic profiles of brain metastases

Metastasis to the brain is a feared complication of systemic cancer, associated with significant morbidity and poor prognosis. A better understanding of the tumor metabolism might help us meet the challenges in controlling brain metastases. The study aims to characterize the metabolic profile of brain metastases of different origin using high resolution magic angle spinning (HR-MAS) magnetic resonance spectroscopy (MRS) to correlate the metabolic profiles to clinical and pathological information. Biopsy samples of human brain metastases (n = 49) were investigated. A significant correlation between lipid signals and necrosis in brain metastases was observed (p < 0.01), irrespective of their primary origin. The principal component analysis (PCA) showed that brain metastases from malignant melanomas cluster together, while lung carcinomas were metabolically heterogeneous and overlap with other subtypes. Metastatic melanomas have higher amounts of glycerophosphocholine than other brain metastases. A significant correlation between microscopically visible lipid droplets estimated by Nile Red staining and MR visible lipid signals was observed in metastatic lung carcinomas (p = 0.01), indicating that the proton MR visible lipid signals arise from cytoplasmic lipid droplets. MRS-based metabolomic profiling is a useful tool for exploring the metabolic profiles of metastatic brain tumors.

HR-MAS MR spectroscopy of breast cancer tissue obtained with core needle biopsy: correlation with prognostic factors

The purpose of this study was to examine the correlation between high-resolution magic angle spinning (HR-MAS) magnetic resonance (MR) spectroscopy using core needle biopsy (CNB) specimens and histologic prognostic factors currently used in breast cancer patients. After institutional review board approval and informed consent were obtained for this study, CNB specimens were collected from 36 malignant lesions in 34 patients. Concentrations and metabolic ratios of various choline metabolites were estimated by HR-MAS MR spectroscopy using CNB specimens. HR-MAS spectroscopic values were compared according to histopathologic variables [tumor size, lymph node metastasis, histologic grade, status of estrogens receptor (ER), progesterone receptor (PR), HER2 (a receptor for human epidermal growth factor), and Ki-67, and triple negativity]. Multivariate analysis was performed with Orthogonal Projections to Latent Structure-Discriminant Analysis (OPLS-DA). HR-MAS MR spectroscopy quantified and discriminated choline metabolites in all CNB specimens of the 36 breast cancers. Several metabolite markers [free choline (Cho), phosphocholine (PC), creatine (Cr), taurine, myo-inositol, scyllo-inositol, total choline (tCho), glycine, Cho/Cr, tCho/Cr, PC/Cr] on HR-MAS MR spectroscopy were found to correlate with histologic prognostic factors [ER, PR, HER2, histologic grade, triple negativity, Ki-67, poor prognosis]. OPLS-DA multivariate models were generally able to discriminate the status of histologic prognostic factors (ER, PR, HER2, Ki-67) and prognosis groups. Our study suggests that HR-MAS MR spectroscopy using CNB specimens can predict tumor aggressiveness prior to surgery in breast cancer patients. In addition, it may be helpful in the detection of reliable markers for breast cancer characterization.

Lactate and glycine-potential MR biomarkers of prognosis in estrogen receptor-positive breast cancers

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

Subtype-specific response to bevacizumab is reflected in the metabolome and transcriptome of breast cancer xenografts

Antiangiogenic therapy with bevacizumab has shown varying results in breast cancer clinical trials. Identifying robust biomarkers for selecting patients who may benefit from such treatment and for monitoring response is important for the future use of bevacizumab. Two established xenograft models representing basal-like and luminal-like breast cancer were used to study bevacizumab treatment response on the metabolic and gene expression levels. Tumor samples were obtained from mice treated with bevacizumab, doxorubicin or a combination of the two drugs, and high resolution magic angle spinning magnetic resonance spectroscopy and gene expression microarray analysis was performed. Combination treatment with bevacizumab showed the strongest growth inhibiting effect in basal-like tumors, and this was reflected by a significant change in the metabolomic and transcriptomic profiles. In the luminal-like xenografts, addition of bevacizumab did not improve the effect of doxorubicin. On the global transcriptomic level, the largest gene expression changes were observed for the most efficient treatment in both models. Glycerophosphocholine showed opposite response in the treated xenografts compared with untreated controls; lower in basal-like and higher in luminal-like tumors. Comparing combination therapy with doxorubicin monotherapy in basal-like xenografts, 14 genes showed significant differential expression, including very low density lipoprotein receptor (VLDLR) and hemoglobin, theta 1 (HBQ1). Bevacizumab-treated tumors were associated with a more hypoxic phenotype, while no evidence was found for associations between bevacizumab treatment and vascular invasion or tumor grade. This study underlines the importance of characterizing biological differences between subtypes of breast cancer to identify personalized biomarkers for improved patient stratification and evaluation of response to therapy.

Analysis of cancer tissues by means of spectroscopic methods

The personalized approach in cancer treatment stimulates the search for new analytical techniques, including spectroscopic methods such as Raman spectroscopy, mass spectrometry MALDI (matrix-assisted laser desorption/ionization) imaging and high-resolution magic angle spinning nuclear magnetic resonance (HR MAS NMR). The purpose of these studies is determination of metabolic profiles of cancer tissues, and their application in diagnostics and therapy of cancers. The review is mainly focused on application of HR MAS NMR technique. Qualitative and quantitative analysis of metabolites by means of this method is described for breast cancer tissues. In the near future HR MAS NMR in vitro studies of metabolic profiles combined with in vivo studies using MRI scanners may be applied as a new diagnostic tool.

NMR metabolomics of MTLn3E breast cancer cells identifies a role for CXCR4 in lipid and choline regulation

The alpha chemokine receptor CXCR4 is up-regulated in certain types of breast cancer. Truncation of the C-terminus of this receptor alters cell morphology and increases invasiveness and metastatic potential. Here, to better understand the effects of CXCR4 expression and truncation in breast cancer cells, we have used high resolution magic angle spinning (HR-MAS) NMR studies of rat breast carcinoma MtLn3E cells to characterize the metabolite complement of cells heterologously expressing human CXCR4 or its C-terminal truncation mutant, Δ34-CXCR4. Notable reductions in choline levels were detected when either cells expressing wild-type CXCR4 or Δ34-CXCR4 were compared with cells containing an empty expression vector. Cells expressing CXCR4-Δ34 had reduced lipid content when compared with either the wild-type CXCR4 expressing cells or those containing the empty expression vector. Taken together, our results show that distinct effects on the metabolite complement can be linked to either CXCR4 expression or CXCR4 regulation. The metabolite markers for these two effects identified in the present study can, in turn, be used to further investigate the role of CXCR4 in metastasis.

Use of 1H and 31P HRMAS to evaluate the relationship between quantitative alterations in metabolite concentrations and tissue features in human brain tumour biopsies

Quantitative multinuclear high-resolution magic angle spinning was performed in order to determine the tissue pH values of and the absolute metabolite concentrations in 33 samples of human brain tumour tissue. Metabolite concentrations were quantified by 1D (1)H and (31)P HRMAS using the electronic reference to in vivo concentrations (ERETIC) synthetic signal. (1)H-(1)H homonuclear and (1)H-(31)P heteronuclear correlation experiments enabled the direct assessment of the (1)H-(31)P spin systems for signals that suffered from overlapping in the 1D (1)H spectra, and linked the information present in the 1D (1)H and (31)P spectra. Afterwards, the main histological features were determined, and high heterogeneity in the tumour content, necrotic content and nonaffected tissue content was observed. The metabolite profiles obtained by HRMAS showed characteristics typical of tumour tissues: rather low levels of energetic molecules and increased concentrations of protective metabolites. Nevertheless, these characteristics were more strongly correlated with the total amount of living tissue than with the tumour cell contents of the samples alone, which could indicate that the sampling conditions make a significant contribution aside from the effect of tumour development in vivo. The use of methylene diphosphonic acid as a chemical shift and concentration reference for the (31)P HRMAS spectra of tissues presented important drawbacks due to its interaction with the tissue. Moreover, the pH data obtained from (31)P HRMAS enabled us to establish a correlation between the pH and the distance between the N(CH(3))(3) signals of phosphocholine and choline in (1)H spectra of the tissue in these tumour samples.

Diagnostic value of breast proton magnetic resonance spectroscopy at 1.5T in different histopathological types

The purpose of this study was to investigate the usefulness of quantitative proton magnetic resonance spectroscopy (¹H-MRS) for characterizing breast lesions at 1.5T, and to evaluate the diagnostic performance of in vivo breast ¹H-MRS using receiver operating characteristics (ROC) analysis. 112 patients (99 malignant and 13 benign tumors) who were scanned with the MRI/MRS protocol were included in this study. Choline-containing compounds (tCho) levels were measured and compared with histological findings. The measured tCho levels in this work had range of 0.08–9.99 mmol/kg from 65 (66%) of 99 patients with malignant tumors. Of the 13 benign lesions, ¹H-MRS detected one as false positive, with tCho level of 0.66 mmol/kg. The optimal tCho level cutoff point that yielded the highest accuracy was found to be >0.0 mmol/kg. The resulting sensitivity was 66% and specificity 92% for distinguishing benign from malignant lesions. The tCho levels were found to be higher in invasive cancer compared to ductal carcinoma in situ or benign lesions, possibly associated with more aggressive behavior or faster cell replication in invasive cancer. Quantitative in vivo   ¹H-MRS may provide useful information for characterizing histopatholoigical types in breast cancer.

Metabolomics of human breast cancer: new approaches for tumor typing and biomarker discovery

Breast cancer is the most common cancer in women worldwide, and the development of new technologies for better understanding of the molecular changes involved in breast cancer progression is essential. Metabolic changes precede overt phenotypic changes, because cellular regulation ultimately affects the use of small-molecule substrates for cell division, growth or environmental changes such as hypoxia. Differences in metabolism between normal cells and cancer cells have been identified. Because small alterations in enzyme concentrations or activities can cause large changes in overall metabolite levels, the metabolome can be regarded as the amplified output of a biological system. The metabolome coverage in human breast cancer tissues can be maximized by combining different technologies for metabolic profiling. Researchers are investigating alterations in the steady state concentrations of metabolites that reflect amplified changes in genetic control of metabolism. Metabolomic results can be used to classify breast cancer on the basis of tumor biology, to identify new prognostic and predictive markers and to discover new targets for future therapeutic interventions. Here, we examine recent results, including those from the European FP7 project METAcancer consortium, that show that integrated metabolomic analyses can provide information on the stage, subtype and grade of breast tumors and give mechanistic insights. We predict an intensified use of metabolomic screens in clinical and preclinical studies focusing on the onset and progression of tumor development.

Human umbilical mesenchymal stem cell and its adipogenic differentiation: Profiling by nuclear magnetic resonance spectroscopy

AIM

To study the metabolic profile of human umbilical mesenchymal stem cells (HUMSC) and adipogenic differentiation by nuclear magnetic resonance (NMR) spectroscopy.

METHODS

HUMSC isolated from human umbilical cord stroma were induced to adipocytes over 2 wk by adding dexamethasone, 3-isobutyl-1-methylxanthine, indomethacin, and insulin to the culture medium. Adipogenic differentiation was confirmed by Red O staining and transcription-polymerase chain reaction. Perchloric acid extracts of the HUMSCs and adipocytes (about 7 × 10(6)) were characterized for metabolites by using in vitro high resolution 9.4T NMR spectroscopy.

RESULTS

Several major metabolites, such as: choline, creatine, glutamate and myo-inositol, acetate, and some fatty acids/triglycerides, were observed in the MR spectroscopic pattern of HUMSCs and their adipogenic differentiation. HUMSCs are characterized by an unusually low number of NMR-detectable metabolites, high choline, acetate, glutamate and creatine content. However, the metabolic profiles of adipogenic differentiation demonstrated considerably higher methionine and fatty acids, and non-detectable creatine.

CONCLUSION

The biomarkers of HUMSCS and adipocytes were obtained and assigned. NMR spectroscopy will be a promising tool for monitoring stem cell differentiation.

In vivo proton magnetic resonance spectroscopy of breast cancer: a review of the literature

An emerging clinical modality called proton magnetic resonance spectroscopy ((1)H-MRS) enables the non-invasive in vivo assessment of tissue metabolism and is demonstrating applications in improving the specificity of MR breast lesion diagnosis and monitoring tumour responsiveness to neoadjuvant chemotherapies. Variations in the concentration of choline-based cellular metabolites, detectable with (1)H-MRS, have shown an association with malignant transformation of tissue in in vivo and in vitro studies. (1)H-MRS exists as an adjunct to the current routine clinical breast MR examination. This review serves as an introduction to the field of breast (1)H-MRS, discusses modern high-field strength and quantitative approaches and technical considerations, and reviews the literature with respect to the application of (1)H-MRS for breast cancer.

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.

Nuclear Magnetic Resonance as a Diagnostic Tool in Breast Cancer

The early detection and treatment of breast cancer is of direct benefit to patients. Magnetic resonance imaging (MRI) is a promising modality for detection, diagnosis, and staging of breast cancer. MRI enables two methods: the diffusion-weighted MRI (DW MRI) and the dynamic contrast enhanced MRI (DCE MRI). DW MRI reflects the diffusion of water molecules in the extracellular fluid space and allows the estimation of cellularity and tissue structure. The value of the diffusion of water in tissue is called the apparent diffusion coefficient (ADC). ADC values in malignant lesions are smaller than in benign tissue. DCE MRI yields appropriate pharmacokinetic data of physiological parameters that relate to tissue perfusion, microvascular vessel wall permeability and extracellular volume fraction. Gadolinium based contrast agent is usually used in breast DCE MRI diagnostics. Changes in the post-contrast signal intensity help to distinguish lesions according to characteristically enhanced accumulation of contrast agent. Malignant lesions are characterized by a faster and stronger signal enhancement than benign lesions which relate to their neoangiogenesis. Over the last few years, there has been appreciable interest in the use of magnetic resonance spectroscopy (MRS) for the non-invasive analysis of breast tisue metabolites. One of the spectroscopic hallmarks of the neoplastic process appears to be the presence of total choline signal in thein vivospectrum. Despite the fact that MRI and MRS achieve excellent results, they are still not so frequently used in comparison to mammography and breast ultrasound.

Predicting long-term survival and treatment response in breast cancer patients receiving neoadjuvant chemotherapy by MR metabolic profiling

PURPOSE

This study aimed to evaluate whether MR metabolic profiling can be used for prediction of long-term survival and monitoring of treatment response in locally advanced breast cancer patients during neoadjuvant chemotherapy (NAC).

METHODS

High resolution magic angle spinning (HR MAS) MR spectra of pre- and post-treatment biopsies from 33 patients were acquired. Tissue concentrations of choline-containing metabolites (tCho), glycine and taurine were assessed using electronic reference to access in vivo concentration (ERETIC) of the signal and receiver operating characteristic (ROC) curves was used to define their potential to predict patient survival and treatment response. The metabolite profiles obtained by HR MAS spectroscopy were related to long-term survival and treatment response by genetic algorithm partial least squares discriminant analysis (GA PLS-DA).

RESULTS

Different pre-treatment MR metabolic profiles characterized by higher levels of tCho and lower levels of lactate were observed in patients with long-term survival (≥5 years, survivors) compared to patients who died of cancer recurrence (<5 years, non-survivors). A significant decrease in glycerophosphocholine (GPC) post-treatment was associated with long-term survival (p = 0.046) and partial response (p = 0.014) to NAC. Long-term survival was best predicted by GPC using ROC analyses (sens. 66.7%, spec. 62.5%), while taurine had the best predictive value of treatment response (sens. 72.7%, spec. 63.2%). GA PLS-DA multivariate classification models successfully discriminated between survivors and non-survivors, resulting in 82.7% and 90.2% cross-validation (CV) classification accuracy, pre- and post-treatment, respectively. Classification of treatment response using GA PLS-DA was not successful for this patient cohort.

CONCLUSIONS

Our results demonstrate that HR MAS MR metabolic profiles consisting of important metabolic characteristics of breast cancer tumors could potentially assist the classification and prediction of long-term survival in locally advanced breast cancer patients, in addition to being used as an adjunct for evaluation of treatment response to NAC.

Prognostic value of metabolic response in breast cancer patients receiving neoadjuvant chemotherapy

BACKGROUND

Today's clinical diagnostic tools are insufficient for giving accurate prognosis to breast cancer patients. The aim of our study was to examine the tumor metabolic changes in patients with locally advanced breast cancer caused by neoadjuvant chemotherapy (NAC), relating these changes to clinical treatment response and long-term survival.

METHODS

Patients (n = 89) participating in a randomized open-label multicenter study were allocated to receive either NAC as epirubicin or paclitaxel monotherapy. Biopsies were excised pre- and post-treatment, and analyzed by high resolution magic angle spinning magnetic resonance spectroscopy (HR MAS MRS). The metabolite profiles were examined by paired and unpaired multivariate methods and findings of important metabolites were confirmed by spectral integration of the metabolite peaks.

RESULTS

All patients had a significant metabolic response to NAC, and pre- and post-treatment spectra could be discriminated with 87.9%/68.9% classification accuracy by paired/unpaired partial least squares discriminant analysis (PLS-DA) (p < 0.001). Similar metabolic responses were observed for the two chemotherapeutic agents. The metabolic responses were related to patient outcome. Non-survivors (< 5 years) had increased tumor levels of lactate (p = 0.004) after treatment, while survivors (≥ 5 years) experienced a decrease in the levels of glycine (p = 0.047) and choline-containing compounds (p ≤ 0.013) and an increase in glucose (p = 0.002) levels. The metabolic responses were not related to clinical treatment response.

CONCLUSIONS

The differences in tumor metabolic response to NAC were associated with breast cancer survival, but not to clinical response. Monitoring metabolic responses to NAC by HR MAS MRS may provide information about tumor biology related to individual prognosis.

13C high-resolution-magic angle spinning MRS reveals differences in glucose metabolism between two breast cancer xenograft models with different gene expression patterns

Tumor cells have increased glycolytic activity, and glucose is mainly used to form lactate and alanine, even when high concentrations of oxygen are present (Warburg effect). The purpose of the present study was to investigate glucose metabolism in two xenograft models representing basal-like and luminal-like breast cancer using (13) C high-resolution-magic angle spinning (HR-MAS) MRS and gene expression analysis. Tumor tissue was collected from two groups for each model: untreated mice (n=19) and a group of mice (n=16) that received an injection of [1-(13) C]-glucose 10 or 15 min before harvesting the tissue. (13) C HR-MAS MRS was performed on the tumor samples and differences in the glucose/alanine (Glc/Ala), glucose/lactate (Glc/Lac) and alanine/lactate (Ala/Lac) ratios between the models were studied. The expression of glycolytic genes was studied using tumor tissue from the same models. In the natural abundance MR spectra, a significantly lower Glc/Ala and Glc/Lac ratio (p<0.001) was observed in the luminal-like model compared with the basal-like model. In the labeled samples, the predominant glucose metabolites were lactate and alanine. Significantly lower Glc/Ala and Glc/Lac ratios were observed in the luminal-like model (p<0.05). Most genes contributing to glycolysis were expressed at higher levels in the luminal-like model (fdr<0.001). The lower Glc/Ala and Glc/Lac ratios and higher glycolytic gene expression observed in the luminal-like model indicates that the transformation of glucose to lactate and alanine occurred faster in this model than in the basal-like model, which has a growth rate several times faster than that of the luminal-like model. The results from the present study suggest that the tumor growth rate is not necessarily a determinant of glycolytic activity.

An HR-MAS MR metabolomics study on breast tissues obtained with core needle biopsy

BACKGROUND

Much research has been devoted to the development of new breast cancer diagnostic measures, including those involving high-resolution magic angle spinning (HR-MAS) magnetic resonance (MR) spectroscopic techniques. Previous HR-MAS MR results have been obtained from post-surgery samples, which limits their direct clinical applicability.

METHODOLOGY/PRINCIPAL FINDINGS

In the present study, we performed HR-MAS MR spectroscopic studies on 31 breast tissue samples (13 cancer and 18 non-cancer) obtained by percutaneous core needle biopsy. We showed that cancer and non-cancer samples can be discriminated very well with Orthogonal Projections to Latent Structure-Discriminant Analysis (OPLS-DA) multivariate model on the MR spectra. A subsequent blind test showed 69% sensitivity and 94% specificity in the prediction of the cancer status. A spectral analysis showed that in cancer cells, taurine- and choline-containing compounds are elevated. Our approach, additionally, could predict the progesterone receptor statuses of the cancer patients.

CONCLUSIONS/SIGNIFICANCE

HR-MAS MR metabolomics on intact breast tissues obtained by core needle biopsy may have a potential to be used as a complement to the current diagnostic and prognostic measures for breast cancers.

A metabolomic approach for diagnosis of experimental sepsis

BACKGROUND

The search for reliable diagnostic biomarkers of sepsis remains necessary. Assessment of global metabolic profiling using quantitative nuclear magnetic resonance (NMR)-based metabolomics offers an attractive modern methodology for fast and comprehensive determination of multiple circulating metabolites and for defining the metabolic phenotype of sepsis.

OBJECTIVE

To develop a novel NMR-based metabolomic approach for diagnostic evaluation of sepsis.

METHODS

Male Sprague-Dawley rats (weight 325-375 g) underwent cecal ligation and puncture (n = 14, septic group) or sham procedure (n = 14, control group) and 24 h later were euthanized. Lung tissue, bronchoalveolar lavage (BAL) fluid, and serum samples were obtained for (1)H NMR and high-resolution magic-angle spinning analysis. Unsupervised principal components analysis was performed on the processed spectra, and a predictive model for diagnosis of sepsis was constructed using partial least-squares discriminant analysis.

RESULTS

NMR-based metabolic profiling discriminated characteristics between control and septic rats. Characteristic metabolites changed markedly in septic rats as compared with control rats: alanine, creatine, phosphoethanolamine, and myoinositol concentrations increased in lung tissue; creatine increased and myoinositol decreased in BAL fluid; and alanine, creatine, phosphoethanolamine, and acetoacetate increased whereas formate decreased in serum. A predictive model for diagnosis of sepsis using these metabolites classified cases with sensitivity and specificity of 100%.

CONCLUSIONS

NMR metabolomic analysis is a potentially useful technique for diagnosis of sepsis. The concentrations of metabolites involved in energy metabolism and in the inflammatory response change in this model of sepsis.

In vivo NMR metabolic profiling of Fabrea salina reveals sequential defense mechanisms against ultraviolet radiation

Fabrea salina is a hypersaline ciliate that is known to be among the strongest ultraviolet (UV)-resistant microorganisms; however, the molecular mechanisms of this resistance are almost unknown. By means of in vivo NMR spectroscopy, we determined the metabolic profile of living F. salina cells exposed to visible light and to polychromatic UV-B + UV-A + Vis radiation for several different exposure times. We used unsupervised pattern-recognition analysis to compare these profiles and discovered some metabolites whose concentration changed specifically upon UV exposure and in a dose-dependent manner. This variation was interpreted in terms of a two-phase cell reaction involving at least two different pathways: an early response consisting of degradation processes, followed by a late response activating osmoprotection mechanisms. The first step alters the concentration of formate, acetate, and saturated fatty-acid metabolites, whereas the osmoprotection modifies the activity of betaine moieties and other functionally related metabolites. In the latter pathway, alanine, proline, and sugars suggest a possible incipient protein synthesis as defense and/or degeneration mechanisms. We conclude that NMR spectroscopy on in vivo cells is an optimal approach for investigating the effect of UV-induced stress on the whole metabolome of F. salina because it minimizes the invasiveness of the measurement.

H HRMAS NMR Derived Bio-markers Related to Tumor Grade, Tumor Cell Fraction, and Cell Proliferation in Prostate Tissue Samples

A high-resolution magic angle spinning NMR spectroscopic approach is presented for evaluating the occurrence, amount and aggressiveness of cancer in human prostate tissue samples. Using this technique, key metabolites in malignant and non-malignant samples (n = 149) were identified, and patterns of their relative abundance were analyzed by multivariate statistical methods. Ratios of various metabolites – including (glycerophophorylcholine + phosphorylcholine)/creatine, myo-inositol/scyllo-inositol, scyllo-inositol/creatine, choline/creatine, and citrate/creatine – correlated with: i) for non-malignant tissue samples, the distance to the nearest tumor and its Gleason score and; ii) the fraction of tumor cells present in the sample; and iii) tumor cell proliferation (Ki67 labelling index). This NMR-based approach allows the extraction of information that could be useful for developing novel diagnostic methods for prostate cancer.

Glycosidic intermediates identified in 1H MR spectra of intact tumour cells may contribute to the clarification of aspects of glycosylation pathways

The glycosylation process, through the addition of carbohydrates, is a major post-translational modification of proteins and glycolipids. Proteins may be glycosylated in either the secretory pathway leading to N-linked or O-linked glycoproteins or as nucleocytoplasmic glycosylation that targets only single proteins involving a single β-linked N-acetylglucosamine. In both cases, the key precursors are the uridine diphospho-N-acetylhexosamines synthesised by the hexosamine biosynthetic pathway. Furthermore, uridine diphospho-N-acetylglucosamine participates in the biosynthesis of sialic acid. In this work, we propose MRS for the detection of uridine diphospho-N-acetylhexosamines visible in high-resolution MR spectra of intact cells from different human tumours. Signals from the nucleotide and amino sugar moieties, including amide signals observed for the first time in whole cells, are assigned, also taking advantage of spectral changes that follow cell treatment with ammonium chloride. Finally, parallel changes in uridine diphospho-N-acetylhexosamines and glutamine pools, observed after pH changes induced by ammonium chloride in the different tumour cell lines, may provide more details on the glycosylation processes.

Metabolomics and surgical oncology: Potential role for small molecule biomarkers

Metabolomics, the newest of the "omics" sciences, has brought much excitement to the field of oncology as a potential new translational tool capable of bringing the molecular world of cancer care to the bedside. While still early in its development, metabolomics could alter the scope and role of surgery in the multidisciplinary treatment of cancer. This review examines potential roles of metabolomics in areas of early cancer detection, personalized therapeutics and tumorigenesis.

Metabolic profile of intact tissue from uterine leiomyomas using high-resolution magic-angle-spinning ¹H NMR spectroscopy

High-resolution magic-angle-spinning (HRMAS) one- and two-dimensional (1)H and (13)C NMR spectroscopy was used to study intact healthy (myometrium) and benign (leiomyoma) uterine tissues of 10 patients. Twenty-eight metabolites were detected and assigned in both types of tissue. Principal component analysis (PCA) was applied to a conventional water-suppressed (1)H HRMAS NMR spectrum, and two NMR spectral editing methods, namely Carr-Purcell- Meiboom-Gill (CPMG) spin-echo and diffusion-edited techniques, were used. Only the PCA of CPMG spectra resulted in a good differentiation between the two tissue types. The CPMG spin-echo spectra were also useful in indicating depleted levels of taurine in uterine leiomyomas, which were well correlated with the histopathological determination. In addition, statistical analysis revealed that most leiomyomas contained elevated concentrations of glutamate and glutamine. Our results suggest that HRMAS represents a valuable adjunct to histopathology to improve the diagnostic accuracy of uterine leiomyomas, whilst concomitantly reducing the diagnosis time.

Merging transcriptomics and metabolomics--advances in breast cancer profiling

BACKGROUND

Combining gene expression microarrays and high resolution magic angle spinning magnetic resonance spectroscopy (HR MAS MRS) of the same tissue samples enables comparison of the transcriptional and metabolic profiles of breast cancer. The aim of this study was to explore the potential of combining these two different types of information.

METHODS

Breast cancer tissue from 46 patients was analyzed by HR MAS MRS followed by gene expression microarrays. Two strategies were used to combine the gene expression and metabolic data; first using multivariate analyses to identify different groups based on gene expression and metabolic data; second correlating levels of specific metabolites to transcripts to suggest new hypotheses of connections between metabolite levels and the underlying biological processes. A parallel study was designed to address experimental issues of combining microarrays and HR MAS MRS.

RESULTS

In the first strategy, using the microarray data and previously reported molecular classification methods, the majority of samples were classified as luminal A. Three subgroups of luminal A tumors were identified based on hierarchical clustering of the HR MAS MR spectra. The samples in one of the subgroups, designated A2, showed significantly lower glucose and higher alanine levels than the other luminal A samples, suggesting a higher glycolytic activity in these tumors. This group was also enriched for genes annotated with Gene Ontology (GO) terms related to cell cycle and DNA repair. In the second strategy, the correlations between concentrations of myo-inositol, glycine, taurine, glycerophosphocholine, phosphocholine, choline and creatine and all transcripts in the filtered microarray data were investigated. GO-terms related to the extracellular matrix were enriched among the genes that correlated the most to myo-inositol and taurine, while cell cycle related GO-terms were enriched for the genes that correlated the most to choline. Additionally, a subset of transcripts was identified to have slightly altered expression after HR MAS MRS and was therefore removed from all other analyses.

CONCLUSIONS

Combining transcriptional and metabolic data from the same breast carcinoma sample is feasible and may contribute to a more refined subclassification of breast cancers as well as reveal relations between metabolic and transcriptional levels. See Commentary: http://www.biomedcentral.com/1741-7015/8/73.

Early detection of recurrent breast cancer using metabolite profiling

We report on the development of a monitoring test for recurrent breast cancer, using metabolite-profiling methods. Using a combination of nuclear magnetic resonance (NMR) and two-dimensional gas chromatography-mass spectrometry (GC×GC-MS) methods, we analyzed the metabolite profiles of 257 retrospective serial serum samples from 56 previously diagnosed and surgically treated breast cancer patients. One hundred sixteen of the serial samples were from 20 patients with recurrent breast cancer, and 141 samples were from 36 patients with no clinical evidence of the disease during ∼6 years of sample collection. NMR and GC×GC-MS data were analyzed by multivariate statistical methods to compare identified metabolite signals between the recurrence samples and those with no evidence of disease. Eleven metabolite markers (seven from NMR and four from GC×GC-MS) were shortlisted from an analysis of all patient samples by using logistic regression and 5-fold cross-validation. A partial least squares discriminant analysis model built using these markers with leave-one-out cross-validation provided a sensitivity of 86% and a specificity of 84% (area under the receiver operating characteristic curve = 0.88). Strikingly, 55% of the patients could be correctly predicted to have recurrence 13 months (on average) before the recurrence was clinically diagnosed, representing a large improvement over the current breast cancer-monitoring assay CA 27.29. To the best of our knowledge, this is the first study to develop and prevalidate a prediction model for early detection of recurrent breast cancer based on metabolic profiles. In particular, the combination of two advanced analytical methods, NMR and MS, provides a powerful approach for the early detection of recurrent breast cancer.

Hydrogel network formation revised: high-resolution magic angle spinning nuclear magnetic resonance as a powerful tool for measuring absolute hydrogel cross-link efficiencies

In the present work, high-resolution magic angle spinning (hr-MAS) NMR spectroscopy is applied as a straightforward nondestructive technique to quantify unreacted methacrylamide functionalities in cross-linked gelatin hydrogels. By adjusting several cross-linking parameters including the ultraviolet (UV) irradiation time and the photo-initiator concentration, the cross-linking degree can be easily varied. Remarkably, under all experimental conditions typically applied for hydrogel development, no more than 40% of the methacrylamide moieties present have reacted. The hr-MAS based approach to determine the cross-linking efficiency is shown to provide an innovative and more convenient alternative to the well-established classical techniques. In addition, the results obtained are in good correlation with mechanical analysis data.

Combined DCE-MRI and single-voxel 2D MRS for differentiation between benign and malignant breast lesions

Dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) and proton (1H) magnetic resonance spectroscopy (MRS) provide structural and biochemical information, including vascular volume, vascular permeability and tissue metabolism. In this study, we performed analysis of the enhancement characteristic from DCE-MRI and the biochemical information provided by two-dimensional (2D) Localized Correlated Spectroscopy (L-COSY) MRS to determine the sensitivity and specificity of using DCE-MRI alone compared to the combination with 2D MRS. The metabolite ratios from the 2D MRS spectra were analyzed using multivariate statistical analyses to determine a method capable of automatic separation of the patient cohort into malignant and benign lesions. A total of 24 lesions were studied with 21 diagnosed accurately using the enhancement characteristics alone resulting in sensitivity and specificity of 100% and 73%, respectively. Analysis of the 2D MRS data demonstrated a significant difference (p < 0.05) in 12 of 18 metabolite ratios analyzed for malignant compared to benign lesions. Previous research focused on utilizing the choline signal to noise ratio (SNR) as a marker for malignancy has been verified using 2D MRS in this study. Using Fisher's linear discriminant test using water (WAT)/olefinic fat diagonal (UFD), choline (CHO)/fat (FAT), CHO/UFD, and FAT/methyl fat (FMETD) as predictors the sensitivity and specificity increased to 92% and 100%, respectively. Using the Classification and Regression Tree (CART) statistical analysis the resulting sensitivity and specificity were 100% and 91%, respectively, with the most accurate predictor for differentiating malignant and benign determined to be FAT/FMETD. The cases within the study that presented a indeterminate diagnosis using DCE-MRI alone were able to be accurately diagnosed when the metabolic information from 2D MRS was incorporated. The results suggest improved breast cancer detection through the combination of morphological and enhancement information from DCE-MRI and metabolic information from 2D MRS.

Metabolic aggressiveness in benign meningiomas with chromosomal instabilities

Meningiomas are often considered benign tumors curable by surgery, but most recurrent meningiomas correspond to histologic benign tumors. Because alterations in chromosome 14 among others have suggested clinical aggressiveness and recurrence, determining both the molecular phenotype and the genetic profile may help distinguish tumors with aggressive metabolism. The aim of this study was to achieve higher specificity in the detection of meningioma subgroups by measuring chromosomal instabilities by fluorescence in situ hybridization and cytogenetics and metabolic phenotypes by high-resolution magic angle spinning spectroscopy. We studied 46 meningioma biopsies with these methodologies. Of these, 34 were of WHO grade 1 and 12 were of WHO grade 2. Genetic analysis showed a subgroup of histologic benign meningioma with chromosomal instabilities. The metabolic phenotype of this subgroup indicated an aggressive metabolism resembling that observed for atypical meningioma. According to the metabolic profiles, these tumors had increased energy demand, higher hypoxic conditions, increased membrane turnover and cell proliferation, and possibly increased resistance to apoptosis. Taken together, our results identify distinct metabolic phenotypes for otherwise benign meningiomas based on cytogenetic studies and global metabolic profiles of intact tumors. Measuring the metabolic phenotype of meningioma intact biopsies at the same time as histopathologic analysis may allow the early detection of clinically aggressive tumors.

Distinct choline metabolic profiles are associated with differences in gene expression for basal-like and luminal-like breast cancer xenograft models

Background

Increased concentrations of choline-containing compounds are frequently observed in breast carcinomas, and may serve as biomarkers for both diagnostic and treatment monitoring purposes. However, underlying mechanisms for the abnormal choline metabolism are poorly understood.

Methods

The concentrations of choline-derived metabolites were determined in xenografted primary human breast carcinomas, representing basal-like and luminal-like subtypes. Quantification of metabolites in fresh frozen tissue was performed using high-resolution magic angle spinning magnetic resonance spectroscopy (HR MAS MRS).

The expression of genes involved in phosphatidylcholine (PtdCho) metabolism was retrieved from whole genome expression microarray analyses.

The metabolite profiles from xenografts were compared with profiles from human breast cancer, sampled from patients with estrogen/progesterone receptor positive (ER+/PgR+) or triple negative (ER-/PgR-/HER2-) breast cancer.

Results

In basal-like xenografts, glycerophosphocholine (GPC) concentrations were higher than phosphocholine (PCho) concentrations, whereas this pattern was reversed in luminal-like xenografts. These differences may be explained by lower choline kinase (CHKA, CHKB) expression as well as higher PtdCho degradation mediated by higher expression of phospholipase A2 group 4A (PLA2G4A) and phospholipase B1 (PLB1) in the basal-like model. The glycine concentration was higher in the basal-like model. Although glycine could be derived from energy metabolism pathways, the gene expression data suggested a metabolic shift from PtdCho synthesis to glycine formation in basal-like xenografts. In agreement with results from the xenograft models, tissue samples from triple negative breast carcinomas had higher GPC/PCho ratio than samples from ER+/PgR+ carcinomas, suggesting that the choline metabolism in the experimental models is representative for luminal-like and basal-like human breast cancer.

Conclusions

The differences in choline metabolite concentrations corresponded well with differences in gene expression, demonstrating distinct metabolic profiles in the xenograft models representing basal-like and luminal-like breast cancer. The same characteristics of choline metabolite profiles were also observed in patient material from ER+/PgR+ and triple-negative breast cancer, suggesting that the xenografts are relevant model systems for studies of choline metabolism in luminal-like and basal-like breast cancer.

Molecular effects of diethanolamine exposure on Calanus finmarchicus (Crustacea: Copepoda)

Alkanolamines are surface-active chemicals used in a wide range of industrial, agricultural and pharmaceutical applications and products. Of particular interest is the use of alkanolamines such as diethanolamine (DEA) in the removal of CO(2) from natural gas and for CO(2) capture following fossil fuel combustion. Despite this widespread use, relatively little is known about the ecotoxicological impacts of these compounds. In an attempt to assess the potential effects of alkanolamines in the marine environment, a key species in the North Atlantic, the planktonic copepod Calanus finmarchicus, was studied for molecular effects following sublethal exposure to DEA. DEA-induced alterations in transcriptome and metabolome profiling were assessed using a suppression subtractive hybridization (SSH) gene library method and high resolution magic angle spinning nuclear magnetic resonance (HR-MAS NMR), respectively. Effects were observed on transcription of genes reportedly involved in lipid metabolism, antioxidant systems, metal binding, and amino acid and protein catabolism. These effects were accompanied by altered expression of fatty acid derivates, amino acids (threonine, methionine, glutamine, arginine, alanine and leucine) and cholines (choline, phosphocholine and glycerophosphocholine). Together, SSH and HR-MAS NMR offer complementary screening tools for the assessment of molecular responses of C. finmarchicus to DEA and can be used in the study of other chemicals and organisms. Concentration-response and time-response relationships between DEA exposure and single gene transcription were investigated using quantitative PCR. Specific relationships were found between DEA exposure and the transcription of genes involved in protein catabolism (ubiquitin-specific protease-7), metal ion homeostasis (ferritin) and defence against oxidative stress (gamma-glutamylcysteine synthase, glutathione synthase and Cu/Zn-superoxide dismutase). At the lowest alkanolamine concentration used in these experiments, which corresponded to 0.5% of the LC(50) concentration, no transcriptional effects were observed, giving information regarding the lower molecular effect level. Finally, similar transcription patterns were observed for a number of different genes following exposure to DEA, which indicates analogous mechanisms of toxicity and response.

Magnetic resonance metabolomics of intact tissue: a biotechnological tool in cancer diagnostics and treatment evaluation

Personalized medicine is increasingly important in cancer treatment for its role in staging and its potential to improve stratification of patients. Different types of molecules, genes, proteins, and metabolites are being extensively explored as potential biomarkers. This review discusses the major findings and potential of tissue metabolites determined by high-resolution magic angle spinning magnetic resonance spectroscopy for cancer detection, characterization, and treatment monitoring.

Short-term temperature effect on the HRMAS spectra of human brain tumor biopsies and their pattern recognition analysis

OBJECT

To investigate the effect of temperature (0 versus 37 degrees C) in the high-resolution magic angle spinning spectroscopy (HRMAS) pattern of human brain tumor biopsies and its influence in recognition-based tumor type prediction. This proof-of-principle study addressed the bilateral discrimination between meningioma (MM) and glioblastoma multiforme (GBM) cases.

MATERIALS AND METHODS

Forty-three tumor biopsy samples were collected (20 MM and 23 GBM), kept frozen and later analyzed at 0 degrees C and 37 degrees C by HRMAS. Post-HRMAS histopathology was used to validate the tumor type. Time-course experiments (100 min) at both temperatures were carried out to monitor HRMAS pattern changes. Principal component analysis and linear discriminant analysis were used for classifier development with a training set of 20 biopsies.

RESULTS

Temperature-dependent, spectral pattern changes mostly affected mobile lipids and choline-containing compounds resonances and were essentially reversible. Incubation of 3 MM and 3 GBM at 37 degrees C during 100 minutes produced irreversible pattern changes below 13% in a few resonances. Classification performance of an independent test set of 7 biopsies was 100% for the pulse-and-acquire, CPMG at echo times (TE) of 30 ms and 144 ms and Hahn Echo at TE 30 ms at 0 degrees C and 37 degrees C. The performance for Hahn Echo spectra at 136 ms was 83.3% at 0 degrees C and 100% at 37 degrees C.

CONCLUSION

The spectral pattern of mobile lipids changes reversibly with temperature. HRMAS demonstrated potential for automated brain tumor biopsy classification. No advantage was obtained when acquiring spectra at 37 degrees C with respect to 0 degrees C in most of the conditions used for the discrimination addressed.

Quantification of metabolites in breast cancer patients with different clinical prognosis using HR MAS MR spectroscopy

Absolute quantitative measures of breast cancer tissue metabolites can increase our understanding of biological processes. Electronic REference To access In vivo Concentrations (ERETIC) was applied to high resolution magic angle spinning MR spectroscopy (HR MAS MRS) to quantify metabolites in intact breast cancer samples. The ERETIC signal was calibrated using solutions of creatine and TSP. The largest relative errors of the ERETIC method were 8.4%, compared to 4.4% for the HR MAS MRS method using TSP as a standard. The same MR experimental procedure was applied to intact tissue samples from breast cancer patients with clinically defined good (n = 13) and poor (n = 16) prognosis. All samples were examined by histopathology for relative content of different tissue types and proliferation index (MIB-1) after MR analysis. The resulting spectra were analyzed by quantification of tissue metabolites (β-glucose, lactate, glycine, myo-inositol, taurine, glycerophosphocholine, phosphocholine, choline and creatine), by peak area ratios and by principal component analysis. We found a trend toward lower concentrations of glycine in patients with good prognosis (1.1 µmol/g) compared to patients with poor prognosis (1.9 µmol/g, p = 0.067). Tissue metabolite concentrations (except for β-glucose) were also found to correlate to the fraction of tumor, connective, fat or glandular tissue by Pearson correlation analysis. Tissue concentrations of β-glucose correlated to proliferation index (MIB-1) with a negative correlation factor (-0.45, p = 0.015), consistent with increased energy demand in proliferating tumor cells. By analyzing several metabolites simultaneously, either in ratios or by metabolic profiles analyzed by PCA, we found that tissue metabolites correlate to patients' prognoses and health status five years after surgery. This study shows that the diagnostic and prognostic potential in MR metabolite analysis of breast cancer tissue is greater when combining multiple metabolites (MR Metabolomics).

Multivariate modeling and prediction of breast cancer prognostic factors using MR metabolomics

Axillary lymph node status together with estrogen and progesterone receptor status are important prognostic factors in breast cancer. In this study, the potential of using MR metabolomics for prediction of these prognostic factors was evaluated. Biopsies from breast cancer patients (n = 160) were excised during surgery and analyzed by high resolution magic angle spinning MR spectroscopy (HR MAS MRS). The spectral data were preprocessed and variable stability (VAST) scaled, and training and test sets were generated using the Kennard-Stone and SPXY sample selection algorithms. The data were analyzed by partial least-squares discriminant analysis (PLS-DA), probabilistic neural networks (PNNs) and Bayesian belief networks (BBNs), and blind samples (n = 50) were predicted for verification. Estrogen and progesterone receptor status was successfully predicted from the MR spectra, and were best predicted by PLS-DA with a correct classification of 44 of 50 and 39 of 50 samples, respectively. Lymph node status was best predicted by BBN with 34 of 50 samples correctly classified, indicating a relationship between metabolic profile and lymph node status. Thus, MR profiles contain prognostic information that may be of benefit in treatment planning, and MR metabolomics may become an important tool for diagnosis of breast cancer patients.

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.