Stable isotope-assisted metabolomics in cancer research

Nitrogen isotopic composition as a gauge of tumor cell anabolism-to-catabolism ratio

Studies have suggested that cancerous tissue has a lower 15N/14N ratio than benign tissue. However, human data have been inconclusive, possibly due to constraints on experimental design. Here, we used high-sensitivity nitrogen isotope methods to assess the 15N/14N ratio of human breast, lung, and kidney cancer tissue at unprecedented spatial resolution. In lung, breast, and urothelial carcinoma, 15N/14N was negatively correlated with tumor cell density. The magnitude of 15N depletion for a given tumor cell density was consistent across different types of lung cancer, ductal in situ and invasive breast carcinoma, and urothelial carcinoma, suggesting similar elevations in the anabolism-to-catabolism ratio. However, tumor 15N depletion was higher in a more aggressive metaplastic breast carcinoma. These findings may indicate the ability of certain cancers to more effectively channel N towards growth. Our results support 15N/14N analysis as a potential tool for screening biopsies and assessing N metabolism in tumor cells.

Using mass spectrometry imaging to map fluxes quantitatively in the tumor ecosystem

Tumors are comprised of a multitude of cell types spanning different microenvironments. Mass spectrometry imaging (MSI) has the potential to identify metabolic patterns within the tumor ecosystem and surrounding tissues, but conventional workflows have not yet fully integrated the breadth of experimental techniques in metabolomics. Here, we combine MSI, stable isotope labeling, and a spatial variant of Isotopologue Spectral Analysis to map distributions of metabolite abundances, nutrient contributions, and metabolic turnover fluxes across the brains of mice harboring GL261 glioma, a widely used model for glioblastoma. When integrated with MSI, the combination of ion mobility, desorption electrospray ionization, and matrix assisted laser desorption ionization reveals alterations in multiple anabolic pathways. De novo fatty acid synthesis flux is increased by approximately 3-fold in glioma relative to surrounding healthy tissue. Fatty acid elongation flux is elevated even higher at 8-fold relative to surrounding healthy tissue and highlights the importance of elongase activity in glioma.

Distinct nitrogen isotopic compositions of healthy and cancerous tissue in mice brain and head&neck micro-biopsies

BACKGROUND

Cancerous cells can recycle metabolic ammonium for their growth. As this ammonium has a low nitrogen isotope ratio (15N/14N), its recycling may cause cancer tissue to have lower 15N/14N than surrounding healthy tissue. We investigated whether, within a given tissue type in individual mice, tumoral and healthy tissues could be distinguished based on their 15N/14N.

METHODS

Micro-biopsies of murine tumors and adjacent tissues were analyzed for 15N/14N using novel high-sensitivity methods. Isotopic analysis was pursued in Nude and C57BL/6 mice models with mature orthotopic brain and head&neck tumors generated by implantation of H454 and MEERL95 murine cells, respectively.

RESULTS

In the 7 mice analyzed, the brain tumors had distinctly lower 15N/14N than healthy neural tissue. In the 5 mice with head&neck tumors, the difference was smaller and more variable. This was at least partly due to infiltration of healthy head&neck tissue by tumor cells. However, it may also indicate that the 15N/14N difference between tumoral and healthy tissue depends on the nitrogen metabolism of the healthy organ in question.

CONCLUSIONS

The findings, coupled with the high sensitivity of the 15N/14N measurement method used here, suggest a new approach for micro-biopsy-based diagnosis of malignancy as well as an avenue for investigation of cancer metabolism.

Nuclear magnetic resonance (NMR)-based metabolomics for cancer research

Nuclear magnetic resonance (NMR) has emerged as an effective tool in various spheres of biomedical research, amongst which metabolomics is an important method for the study of various types of disease. Metabolomics has proved its stronghold in cancer research by the development of different NMR methods over time for the study of metabolites, thus identifying key players in the aetiology of cancer. A plethora of one-dimensional and two-dimensional NMR experiments (in solids, semi-solids and solution phases) are utilized to obtain metabolic profiles of biofluids, cell extracts and tissue biopsy samples, which can further be subjected to statistical analysis. Any alteration in the assigned metabolite peaks gives an indication of changes in metabolic pathways. These defined changes demonstrate the utility of NMR in the early diagnosis of cancer and provide further measures to combat malignancy and its progression. This review provides a snapshot of the trending NMR techniques and the statistical analysis involved in the metabolomics of diseases, with emphasis on advances in NMR methodology developed for cancer research.

Metabolomic signature of brain cancer

Despite advances in surgery and adjuvant therapy, brain tumors represent one of the leading causes of cancer-related mortality and morbidity in both adults and children. Gliomas constitute about 60% of all cerebral tumors, showing varying degrees of malignancy. They are difficult to treat due to dismal prognosis and limited therapeutics. Metabolomics is the untargeted and targeted analyses of endogenous and exogenous small molecules, which charact erizes the phenotype of an individual. This emerging "omics" science provides functional readouts of cellular activity that contribute greatly to the understanding of cancer biology including brain tumor biology. Metabolites are highly informative as a direct signature of biochemical activity; therefore, metabolite profiling has become a promising approach for clinical diagnostics and prognostics. The metabolic alterations are well-recognized as one of the key hallmarks in monitoring disease progression, therapy, and revealing new molecular targets for effective therapeutic intervention. Taking advantage of the latest high-throughput analytical technologies, that is, nuclear magnetic resonance (NMR) spectroscopy and mass spectrometry (MS), metabolomics is now a promising field for precision medicine and drug discovery. In the present report, we review the application of metabolomics and in vivo metabolic profiling in the context of adult gliomas and paediatric brain tumors. Analytical platforms such as high-resolution (HR) NMR, in vivo magnetic resonance spectroscopic imaging and high- and low-resolution MS are discussed. Moreover, the relevance of metabolic studies in the development of new therapeutic strategies for treatment of gliomas are reviewed.

Analysis of stable isotope assisted metabolomics data acquired by GC-MS

Stable isotope assisted metabolomics (SIAM) measures the abundance levels of metabolites in a particular pathway using stable isotope tracers (e.g., ¹³C, ¹⁸O and/or ¹⁵N). We report a method termed signature ion approach for analysis of SIAM data acquired on a GC-MS system equipped with an electron ionization (EI) ion source. The signature ion is a fragment ion in EI mass spectrum of a derivatized metabolite that contains all atoms of the underivatized metabolite, except the hydrogen atoms lost during derivatization. In this approach, GC-MS data of metabolite standards were used to recognize the signature ion from the EI mass spectra acquired from stable isotope labeled samples, and a linear regression model was used to deconvolute the intensity of overlapping isotopologues. A mixture score function was also employed for cross-sample chromatographic peak list alignment to recognize the chromatographic peaks generated by the same metabolite in different samples, by simultaneously evaluating the similarity of retention time and EI mass spectrum of two chromatographic peaks. Analysis of a mixture of 16 ¹³C-labeled and 16 unlabeled amino acids showed that the signature ion approach accurately identified and quantified all isotopologues. Analysis of polar metabolite extracts from cells respectively fed with uniform ¹³C-glucose and ¹³C-glutamine further demonstrated that this method can also be used to analyze the complex data acquired from biological samples.

Malonate as a ROS product is associated with pyruvate carboxylase activity in acute myeloid leukaemia cells

BACKGROUND

The role of anaplerotic nutrient entry into the Krebs cycle via pyruvate carboxylase has been the subject of increased scrutiny and in particular whether this is dysregulated in cancer. Here, we use a tracer-based NMR analysis involving high-resolution (1)H-(13)C-HSQC spectra to assess site-specific label incorporation into a range of metabolite pools, including malate, aspartate and glutamate in the acute myeloid leukaemia cell line K562. We also determine how this is affected following treatment with the redeployed drug combination of the lipid-regulating drug bezafibrate and medroxyprogesterone (BaP).

RESULTS

Using the tracer-based approach, we assessed the contribution of pyruvate carboxylase (PC) vs. pyruvate dehydrogenase (PDH) activity in the derivation of Krebs cycle intermediates. Our data show that PC activity is indeed high in K562 cells. We also demonstrate a branched entry to the Krebs cycle of K562 cells with one branch running counterclockwise using PC-derived oxaloacetate and the other clockwise from the PDH activity. Finally, we show that the PC activity of K562 cells exclusively fuels the ROS-induced decarboxylation of oxaloacetate to malonate in response to BaP treatment; resulting in further Krebs cycle disruption via depletion of oxaloacetate and malonate-mediated inhibition of succinate dehydrogenase (SDH) resulting in a twofold reduction of fumarate.

CONCLUSIONS

This study extends the interest in the PC activity in solid cancers to include leukaemias and further demonstrates the value of tracer-based NMR approaches in generating a more accurate picture of the flow of carbons and metabolites within the increasingly inappropriately named Krebs cycle. Moreover, our studies indicate that the PC activity in cancer cells can be exploited as an Achilles heel by using treatments, such as BaP, that elevate ROS production.

Metabolomics in rheumatic diseases: desperately seeking biomarkers

Metabolomics enables the profiling of large numbers of small molecules in cells, tissues and biological fluids. These molecules, which include amino acids, carbohydrates, lipids, nucleotides and their metabolites, can be detected quantitatively. Metabolomic methods, often focused on the information-rich analytical techniques of NMR spectroscopy and mass spectrometry, have potential for early diagnosis, monitoring therapy and defining disease pathogenesis in many therapeutic areas, including rheumatic diseases. By performing global metabolite profiling, also known as untargeted metabolomics, new discoveries linking cellular pathways to biological mechanisms are being revealed and are shaping our understanding of cell biology, physiology and medicine. These pathways can potentially be targeted to diagnose and treat patients with immune-mediated diseases.

Pyruvate carboxylase is critical for non-small-cell lung cancer proliferation

Anabolic biosynthesis requires precursors supplied by the Krebs cycle, which in turn requires anaplerosis to replenish precursor intermediates. The major anaplerotic sources are pyruvate and glutamine, which require the activity of pyruvate carboxylase (PC) and glutaminase 1 (GLS1), respectively. Due to their rapid proliferation, cancer cells have increased anabolic and energy demands; however, different cancer cell types exhibit differential requirements for PC- and GLS-mediated pathways for anaplerosis and cell proliferation. Here, we infused patients with early-stage non-small-cell lung cancer (NSCLC) with uniformly 13C-labeled glucose before tissue resection and determined that the cancerous tissues in these patients had enhanced PC activity. Freshly resected paired lung tissue slices cultured in 13C6-glucose or 13C5,15N2-glutamine tracers confirmed selective activation of PC over GLS in NSCLC. Compared with noncancerous tissues, PC expression was greatly enhanced in cancerous tissues, whereas GLS1 expression showed no trend. Moreover, immunohistochemical analysis of paired lung tissues showed PC overexpression in cancer cells rather than in stromal cells of tumor tissues. PC knockdown induced multinucleation, decreased cell proliferation and colony formation in human NSCLC cells, and reduced tumor growth in a mouse xenograft model. Growth inhibition was accompanied by perturbed Krebs cycle activity, inhibition of lipid and nucleotide biosynthesis, and altered glutathione homeostasis. These findings indicate that PC-mediated anaplerosis in early-stage NSCLC is required for tumor survival and proliferation.

Metabolomics in plants and humans: applications in the prevention and diagnosis of diseases

In the recent years, there has been an increase in the number of metabolomic approaches used, in parallel with proteomic and functional genomic studies. The wide variety of chemical types of metabolites available has also accelerated the use of different techniques in the investigation of the metabolome. At present, metabolomics is applied to investigate several human diseases, to improve their diagnosis and prevention, and to design better therapeutic strategies. In addition, metabolomic studies are also being carried out in areas such as toxicology and pharmacology, crop breeding, and plant biotechnology. In this review, we emphasize the use and application of metabolomics in human diseases and plant research to improve human health.

Conversion of 2-deoxyglucose-induced growth inhibition to cell death in normoxic tumor cells

BACKGROUND

Inhibition of glucose metabolism has recently become an attractive target for cancer treatment. Accordingly, since 2-deoxyglucose (2-DG) competes effectively with glucose, it has come under increasing scrutiny as a therapeutic agent. The initial response of tumor cells to 2-DG is growth inhibition, which is thought to conserve energy and consequently protect cells from its ATP-lowering effects as a glycolytic inhibitor. However, since 2-DG also mimics mannose and thereby interferes with N-linked glycosylation, the question is raised of how this sugar analog inhibits tumor cell growth and whether the mechanism by which it protects cells can be manipulated to convert 2-DG-induced growth inhibition to cell death.

METHODS

Cell growth and death were measured via counting viable and dead cells based on trypan blue exclusion. Markers of ATP reduction and the unfolded protein response (UPR) were detected by Western blot. Protein functions were manipulated through chemical compounds, siRNA and the use of gene-specific wild-type and knock-out mouse embryonic fibroblasts (MEFs).

RESULTS

At 2-DG concentrations that can be achieved in human plasma without causing significant side effects, we find (a) It induces growth inhibition predominantly by interference with glycosylation, which leads to accumulation of unfolded proteins in the endoplasmic reticulum activating the UPR; (b) Inhibition of PERK (but not ATF6 or IRE1), a major component of the UPR, leads to conversion of 2-DG-induced growth inhibition to cell death and (c) secondarily to PERK, inhibition of GCN2, a kinase that is activated in response to low intracellular glutamine, increases 2-DG's cytotoxic effects in PERK -/- MEFs.

CONCLUSIONS

Overall, these findings present a novel anticancer strategy that can be translated into therapeutic gain as they uncover the metabolic target PERK, and to a lesser degree GCN2, that when inhibited convert 2-DG's static effect to a toxic one in tumor cells growing under normoxia.

Asthma outcomes: biomarkers

BACKGROUND

Measurement of biomarkers has been incorporated within clinical research studies of asthma to characterize the population and associate the disease with environmental and therapeutic effects.

OBJECTIVE

National Institutes of Health institutes and federal agencies convened an expert group to propose which biomarkers should be assessed as standardized asthma outcomes in future clinical research studies.

METHODS

We conducted a comprehensive search of the literature to identify studies that developed and/or tested asthma biomarkers. We identified biomarkers relevant to the underlying disease process progression and response to treatment. We classified the biomarkers as either core (required in future studies), supplemental (used according to study aims and standardized), or emerging (requiring validation and standardization). This work was discussed at an National Institutes of Health-organized workshop convened in March 2010 and finalized in September 2011.

RESULTS

Ten measures were identified; only 1, multiallergen screening to define atopy, is recommended as a core asthma outcome. Complete blood counts to measure total eosinophils, fractional exhaled nitric oxide (Feno), sputum eosinophils, urinary leukotrienes, and total and allergen-specific IgE are recommended as supplemental measures. Measurement of sputum polymorphonuclear leukocytes and other analytes, cortisol measures, airway imaging, breath markers, and system-wide studies (eg, genomics, proteomics) are considered as emerging outcome measures.

CONCLUSION

The working group participants propose the use of multiallergen screening in all asthma clinical trials to characterize study populations with respect to atopic status. Blood, sputum, and urine specimens should be stored in biobanks, and standard procedures should be developed to harmonize sample collection for clinical trial biorepositories.

Stable isotope-resolved metabolomics and applications for drug development

Advances in analytical methodologies, principally nuclear magnetic resonance spectroscopy (NMR) and mass spectrometry (MS), during the last decade have made large-scale analysis of the human metabolome a reality. This is leading to the reawakening of the importance of metabolism in human diseases, particularly cancer. The metabolome is the functional readout of the genome, functional genome, and proteome; it is also an integral partner in molecular regulations for homeostasis. The interrogation of the metabolome, or metabolomics, is now being applied to numerous diseases, largely by metabolite profiling for biomarker discovery, but also in pharmacology and therapeutics. Recent advances in stable isotope tracer-based metabolomic approaches enable unambiguous tracking of individual atoms through compartmentalized metabolic networks directly in human subjects, which promises to decipher the complexity of the human metabolome at an unprecedented pace. This knowledge will revolutionize our understanding of complex human diseases, clinical diagnostics, as well as individualized therapeutics and drug response. In this review, we focus on the use of stable isotope tracers with metabolomics technologies for understanding metabolic network dynamics in both model systems and in clinical applications. Atom-resolved isotope tracing via the two major analytical platforms, NMR and MS, has the power to determine novel metabolic reprogramming in diseases, discover new drug targets, and facilitates ADME studies. We also illustrate new metabolic tracer-based imaging technologies, which enable direct visualization of metabolic processes in vivo. We further outline current practices and future requirements for biochemoinformatics development, which is an integral part of translating stable isotope-resolved metabolomics into clinical reality.

Enhancement of the capabilities of liquid chromatography-mass spectrometry with derivatization: general principles and applications

The integration of liquid chromatography-mass spectrometry (LC-MS) with derivatization is a relatively new and unique strategy that could add value and could enhance the capabilities of LC-MS-based technologies. The derivatization process could be carried out in various analytical steps, for example, sampling, storage, sample preparation, HPLC separation, and MS detection. This review presents an overview of derivatization-based LC-MS strategy over the past 10 years and covers both the general principles and applications in the fields of pharmaceutical and biomedical analysis, biomarker and metabolomic research, environmental analysis, and food-safety evaluation. The underlying mechanisms and theories for derivative reagent selection are summarized and highlighted to guide future studies.

A novel deconvolution method for modeling UDP-N-acetyl-D-glucosamine biosynthetic pathways based on (13)C mass isotopologue profiles under non-steady-state conditions

Background

Stable isotope tracing is a powerful technique for following the fate of individual atoms through metabolic pathways. Measuring isotopic enrichment in metabolites provides quantitative insights into the biosynthetic network and enables flux analysis as a function of external perturbations. NMR and mass spectrometry are the techniques of choice for global profiling of stable isotope labeling patterns in cellular metabolites. However, meaningful biochemical interpretation of the labeling data requires both quantitative analysis and complex modeling. Here, we demonstrate a novel approach that involved acquiring and modeling the timecourses of ¹³C isotopologue data for UDP-N-acetyl-D-glucosamine (UDP-GlcNAc) synthesized from [U-¹³C]-glucose in human prostate cancer LnCaP-LN3 cells. UDP-GlcNAc is an activated building block for protein glycosylation, which is an important regulatory mechanism in the development of many prominent human diseases including cancer and diabetes.

Results

We utilized a stable isotope resolved metabolomics (SIRM) approach to determine the timecourse of ¹³C incorporation from [U-¹³C]-glucose into UDP-GlcNAc in LnCaP-LN3 cells. ¹³C Positional isotopomers and isotopologues of UDP-GlcNAc were determined by high resolution NMR and Fourier transform-ion cyclotron resonance-mass spectrometry. A novel simulated annealing/genetic algorithm, called 'Genetic Algorithm for Isotopologues in Metabolic Systems' (GAIMS) was developed to find the optimal solutions to a set of simultaneous equations that represent the isotopologue compositions, which is a mixture of isotopomer species. The best model was selected based on information theory. The output comprises the timecourse of the individual labeled species, which was deconvoluted into labeled metabolic units, namely glucose, ribose, acetyl and uracil. The performance of the algorithm was demonstrated by validating the computed fractional ¹³C enrichment in these subunits against experimental data. The reproducibility and robustness of the deconvolution were verified by replicate experiments, extensive statistical analyses, and cross-validation against NMR data.

Conclusions

This computational approach revealed the relative fluxes through the different biosynthetic pathways of UDP-GlcNAc, which comprises simultaneous sequential and parallel reactions, providing new insight into the regulation of UDP-GlcNAc levels and O-linked protein glycosylation. This is the first such analysis of UDP-GlcNAc dynamics, and the approach is generally applicable to other complex metabolites comprising distinct metabolic subunits, where sufficient numbers of isotopologues can be unambiguously resolved and accurately measured.

ER stress modulates cellular metabolism

Changes in metabolic processes play a critical role in the survival or death of cells subjected to various stresses. In the present study, we have investigated the effects of ER (endoplasmic reticulum) stress on cellular metabolism. A major difficulty in studying metabolic responses to ER stress is that ER stress normally leads to apoptosis and metabolic changes observed in dying cells may be misleading. Therefore we have used IL-3 (interleukin 3)-dependent Bak-/-Bax-/- haemopoietic cells which do not die in the presence of the ER-stress-inducing drug tunicamycin. Tunicamycin-treated Bak-/-Bax-/- cells remain viable, but cease growth, arresting in G1-phase and undergoing autophagy in the absence of apoptosis. In these cells, we used NMR-based SIRM (stable isotope-resolved metabolomics) to determine the metabolic effects of tunicamycin. Glucose was found to be the major carbon source for energy production and anabolic metabolism. Following tunicamycin exposure, glucose uptake and lactate production are greatly reduced. Decreased 13C labelling in several cellular metabolites suggests that mitochondrial function in cells undergoing ER stress is compromised. Consistent with this, mitochondrial membrane potential, oxygen consumption and cellular ATP levels are much lower compared with untreated cells. Importantly, the effects of tunicamycin on cellular metabolic processes may be related to a reduction in cell-surface GLUT1 (glucose transporter 1) levels which, in turn, may reflect decreased Akt signalling. These results suggest that ER stress exerts profound effects on several central metabolic processes which may help to explain cell death arising from ER stress in normal cells.

Stable isotope-resolved metabolomics (SIRM) in cancer research with clinical application to nonsmall cell lung cancer

Metabolomics provides a readout of the state of metabolism in cells or tissue and their responses to external perturbations. For this reason, the approach has great potential in clinical diagnostics. Clinical metabolomics using stable isotope resolved metabolomics (SIRM) for pathway tracing represents an important new approach to obtaining metabolic parameters in human cancer subjects in situ. Here we provide an overview of the technology development of labeling from cells in culture and mouse models. The high throughput analytical methods NMR and mass spectrometry, especially Fourier transform ion cyclotron resonance, for analyzing the resulting metabolite isotopomers and isotopologues are described with examples of applications in cancer biology. Special technical considerations for clinical applications of metabolomics using stable isotope tracers are described. The whole process from concept to analysis will be exemplified by our on-going study of nonsmall cell lung cancer (NSCLC) metabolomics. This powerful new approach has already provided important new insights into metabolic adaptations in lung cancer cells, including the upregulation of anaplerosis via pyruvate carboxylation in NSCLC.

Profiling the effects of isocitrate dehydrogenase 1 and 2 mutations on the cellular metabolome

Point mutations of the NADP(+)-dependent isocitrate dehydrogenases 1 and 2 (IDH1 and IDH2) occur early in the pathogenesis of gliomas. When mutated, IDH1 and IDH2 gain the ability to produce the metabolite (R)-2-hydroxyglutarate (2HG), but the downstream effects of mutant IDH1 and IDH2 proteins or of 2HG on cellular metabolism are unknown. We profiled >200 metabolites in human oligodendroglioma (HOG) cells to determine the effects of expression of IDH1 and IDH2 mutants. Levels of amino acids, glutathione metabolites, choline derivatives, and tricarboxylic acid (TCA) cycle intermediates were altered in mutant IDH1- and IDH2-expressing cells. These changes were similar to those identified after treatment of the cells with 2HG. Remarkably, N-acetyl-aspartyl-glutamate (NAAG), a common dipeptide in brain, was 50-fold reduced in cells expressing IDH1 mutants and 8.3-fold reduced in cells expressing IDH2 mutants. NAAG also was significantly lower in human glioma tissues containing IDH mutations than in gliomas without such mutations. These metabolic changes provide clues to the pathogenesis of tumors associated with IDH gene mutations.

Bioactive food components and cancer-specific metabonomic profiles

Cancer cells possess unique metabolic signatures compared to normal cells, including shifts in aerobic glycolysis, glutaminolysis, and de novo biosynthesis of macromolecules. Targeting these changes with agents (drugs and dietary components) has been employed as strategies to reduce the complications associated with tumorigenesis. This paper highlights the ability of several food components to suppress tumor-specific metabolic pathways, including increased expression of glucose transporters, oncogenic tyrosine kinase, tumor-specific M2-type pyruvate kinase, and fatty acid synthase, and the detection of such effects using various metabonomic technologies, including liquid chromatography/mass spectrometry (LC/MS) and stable isotope-labeled MS. Stable isotope-mediated tracing technologies offer exciting opportunities for defining specific target(s) for food components. Exposures, especially during the early transition phase from normal to cancer, are critical for the translation of knowledge about food components into effective prevention strategies. Although appropriate dietary exposures needed to alter cellular metabolism remain inconsistent and/or ill-defined, validated metabonomic biomarkers for dietary components hold promise for establishing effective strategies for cancer prevention.

Uncovering the metabolomic fingerprint of breast cancer

Metabolomics, the study of metabolites and small intermediate molecules, may play a key role in further elucidation of breast cancer. This dynamic, simultaneous assessment of thousands of metabolites allows identification of the presence, concentration and fluxes of specific metabolites, and recognition of the critical metabolic pathways recruited in carcinogenesis. Studies of tumour cell and tissue allow focused analysis on the tumour, whilst studies of biofluids have the appeal of concurrent assessment of tumour and host. Elucidation of these metabolites and pathways may provide essential insights into both the intercellular environment and host/tumour interaction, allowing recognition of new biomarkers for diagnosis and prediction of outcome, new therapy targets and novel approaches for monitoring response and toxicity. Certainly, the field of metabolomics may evolve as a valuable, complementary clinical tool. In this review, current metabolomic data in breast cancer will be presented. The dominant metabolic pathways and metabolite disturbances associated with malignant transformation of breast cells will be outlined, leading to an overview of potential clinical implications for individuals with breast cancer.

Isotopomer analysis of lipid biosynthesis by high resolution mass spectrometry and NMR

We have coupled 2D-NMR and infusion FT-ICR-MS with computer-assisted assignment to profile 13C-isotopologues of glycerophospholipids (GPL) directly in crude cell extracts, resulting in very high information throughput of >3000 isobaric molecules in a few minutes. A mass accuracy of better than 1 ppm combined with a resolution of 100,000 at the measured m/z was required to distinguish isotopomers from other GPL structures. Isotopologue analysis of GPLs extracted from LCC2 breast cancer cells grown on [U-13C]-glucose provided a rich trove of information about the biosynthesis and turnover of the GPLs. The isotopologue intensity ratios from the FT-ICR-MS were accurate to approximately 1% or better based on natural abundance background, and depended on the signal-to-nose ratio. The time course of incorporation of 13C from [U-13C]-glucose into a particular phosphatidylcholine was analyzed in detail, to provide a quantitative measure of the sizes of glycerol, acetyl CoA and total GPL pools in growing LCC2 cells. Independent and complementary analysis of the positional 13C enrichment in the glycerol and fatty acyl chains obtained from high resolution 2D NMR was used to verify key aspects of the model. This technology enables simple and rapid sample preparation, has rapid analysis, and is generally applicable to unfractionated GPLs of almost any head group, and to mixtures of other classes of metabolites.

Prospects for clinical cancer metabolomics using stable isotope tracers

Metabolomics provides a readout of the state of metabolism in cells or tissue and their responses to external perturbations. For this reason, the approach has great potential in clinical diagnostics. For more than two decades, we have been using stable isotope tracer approaches to probe cellular metabolism in greater detail. The ability to enrich common compounds with rare isotopes such as carbon ((13)C) and nitrogen ((15)N) is the only practical means by which metabolic pathways can be traced, which entails following the fate of individual atoms from the source molecule to products via metabolic transformation. Changes in regulation of pathways are therefore captured by this approach, which leads to deeper understanding of the fundamental biochemistry of cells. Using lessons learned from pathways tracing in cells and organs, we have been applying this methodology to human cancer patients in a clinical setting. Here we review the methodologies and approaches to stable isotope tracing in cells, animal models and in humans subjects.

Rhabdomyosarcoma cells show an energy producing anabolic metabolic phenotype compared with primary myocytes

BACKGROUND

The functional status of a cell is expressed in its metabolic activity. We have applied stable isotope tracing methods to determine the differences in metabolic pathways in proliferating Rhabdomysarcoma cells (Rh30) and human primary myocytes in culture. Uniformly 13C-labeled glucose was used as a source molecule to follow the incorporation of 13C into more than 40 marker metabolites using NMR and GC-MS. These include metabolites that report on the activity of glycolysis, Krebs' cycle, pentose phosphate pathway and pyrimidine biosynthesis.

RESULTS

The Rh30 cells proliferated faster than the myocytes. Major differences in flux through glycolysis were evident from incorporation of label into secreted lactate, which accounts for a substantial fraction of the glucose carbon utilized by the cells. Krebs' cycle activity as determined by 13C isotopomer distributions in glutamate, aspartate, malate and pyrimidine rings was considerably higher in the cancer cells than in the primary myocytes. Large differences were also evident in de novo biosynthesis of riboses in the free nucleotide pools, as well as entry of glucose carbon into the pyrimidine rings in the free nucleotide pool. Specific labeling patterns in these metabolites show the increased importance of anaplerotic reactions in the cancer cells to maintain the high demand for anabolic and energy metabolism compared with the slower growing primary myocytes. Serum-stimulated Rh30 cells showed higher degrees of labeling than serum starved cells, but they retained their characteristic anabolic metabolism profile. The myocytes showed evidence of de novo synthesis of glycogen, which was absent in the Rh30 cells.

CONCLUSION

The specific 13C isotopomer patterns showed that the major difference between the transformed and the primary cells is the shift from energy and maintenance metabolism in the myocytes toward increased energy and anabolic metabolism for proliferation in the Rh30 cells. The data further show that the mitochondria remain functional in Krebs' cycle activity and respiratory electron transfer that enables continued accelerated glycolysis. This may be a common adaptive strategy in cancer cells.