Preclinical models for interrogating drug action in human cancers using Stable Isotope Resolved Metabolomics (SIRM)

Untargeted stable isotope-resolved metabolomics to assess the effect of PI3Kβ inhibition on metabolic pathway activities in a PTEN null breast cancer cell line

The combination of high-resolution LC-MS untargeted metabolomics with stable isotope-resolved tracing is a promising approach for the global exploration of metabolic pathway activities. In our established workflow we combine targeted isotopologue feature extraction with the non-targeted X¹³CMS routine. Metabolites, detected by X¹³CMS as differentially labeled between two biological conditions are subsequently integrated into the original targeted library. This strategy enables monitoring of changes in known pathways as well as the discovery of hitherto unknown metabolic alterations. Here, we demonstrate this workflow in a PTEN (phosphatase and tensin homolog) null breast cancer cell line (MDA-MB-468) exploring metabolic pathway activities in the absence and presence of the selective PI3Kβ inhibitor AZD8186. Cells were fed with [U-¹³C] glucose and treated for 1, 3, 6, and 24 h with 0.5 µM AZD8186 or vehicle, extracted by an optimized sample preparation protocol and analyzed by LC-QTOF-MS. Untargeted differential tracing of labels revealed 286 isotope-enriched features that were significantly altered between control and treatment conditions, of which 19 features could be attributed to known compounds from targeted pathways. Other 11 features were unambiguously identified based on data-dependent MS/MS spectra and reference substances. Notably, only a minority of the significantly altered features (11 and 16, respectively) were identified when preprocessing of the same data set (treatment vs. control in 24 h unlabeled samples) was performed with tools commonly used for label-free (i.e. w/o isotopic tracer) non-targeted metabolomics experiments (Profinder´s batch recursive feature extraction and XCMS). The structurally identified metabolites were integrated into the existing targeted isotopologue feature extraction workflow to enable natural abundance correction, evaluation of assay performance and assessment of drug-induced changes in pathway activities. Label incorporation was highly reproducible for the majority of isotopologues in technical replicates with a RSD below 10%. Furthermore, inter-day repeatability of a second label experiment showed strong correlation (Pearson R² > 0.99) between tracer incorporation on different days. Finally, we could identify prominent pathway activity alterations upon PI3Kβ inhibition. Besides pathways in central metabolism, known to be changed our workflow revealed additional pathways, like pyrimidine metabolism or hexosamine pathway. All pathways identified represent key metabolic processes associated with cancer metabolism and therapy.

Pharmacometabolomics reveals urinary diacetylspermine as a biomarker of doxorubicin effectiveness in triple negative breast cancer

Triple-negative breast cancer (TNBC) patients receive chemotherapy treatment, including doxorubicin, due to the lack of targeted therapies. Drug resistance is a major cause of treatment failure in TNBC and therefore, there is a need to identify biomarkers that determine effective drug response. A pharmacometabolomics study was performed using doxorubicin sensitive and resistant TNBC patient-derived xenograft (PDX) models to detect urinary metabolic biomarkers of treatment effectiveness. Evaluation of metabolite production was assessed by directly studying tumor levels in TNBC-PDX mice and human subjects. Metabolic flux leading to biomarker production was determined using stable isotope-labeled tracers in TNBC-PDX ex vivo tissue slices. Findings were validated in 12-h urine samples from control (n = 200), ER+/PR+ (n = 200), ER+/PR+/HER2+ (n = 36), HER2+ (n = 81) and TNBC (n = 200) subjects. Diacetylspermine was identified as a urine metabolite that robustly changed in response to effective doxorubicin treatment, which persisted after the final dose. Urine diacetylspermine was produced by the tumor and correlated with tumor volume. Ex vivo tumor slices revealed that doxorubicin directly increases diacetylspermine production by increasing tumor spermidine/spermine N¹-acetyltransferase 1 expression and activity, which was corroborated by elevated polyamine flux. In breast cancer patients, tumor diacetylspermine was elevated compared to matched non-cancerous tissue and increased in HER2+ and TNBC compared to ER+ subtypes. Urine diacetylspermine was associated with breast cancer tumor volume and poor tumor grade. This study describes a pharmacometabolomics strategy for identifying cancer metabolic biomarkers that indicate drug response. Our findings characterize urine diacetylspermine as a non-invasive biomarker of doxorubicin effectiveness in TNBC.

Nuclear Magnetic Resonance Spectroscopy in Clinical Metabolomics and Personalized Medicine: Current Challenges and Perspectives

Personalized medicine is probably the most promising area being developed in modern medicine. This approach attempts to optimize the therapies and the patient care based on the individual patient characteristics. Its success highly depends on the way the characterization of the disease and its evolution, the patient’s classification, its follow-up and the treatment could be optimized. Thus, personalized medicine must combine innovative tools to measure, integrate and model data. Towards this goal, clinical metabolomics appears as ideally suited to obtain relevant information. Indeed, the metabolomics signature brings crucial insight to stratify patients according to their responses to a pathology and/or a treatment, to provide prognostic and diagnostic biomarkers, and to improve therapeutic outcomes. However, the translation of metabolomics from laboratory studies to clinical practice remains a subsequent challenge. Nuclear magnetic resonance spectroscopy (NMR) and mass spectrometry (MS) are the two key platforms for the measurement of the metabolome. NMR has several advantages and features that are essential in clinical metabolomics. Indeed, NMR spectroscopy is inherently very robust, reproducible, unbiased, quantitative, informative at the structural molecular level, requires little sample preparation and reduced data processing. NMR is also well adapted to the measurement of large cohorts, to multi-sites and to longitudinal studies. This review focus on the potential of NMR in the context of clinical metabolomics and personalized medicine. Starting with the current status of NMR-based metabolomics at the clinical level and highlighting its strengths, weaknesses and challenges, this article also explores how, far from the initial “opposition” or “competition”, NMR and MS have been integrated and have demonstrated a great complementarity, in terms of sample classification and biomarker identification. Finally, a perspective discussion provides insight into the current methodological developments that could significantly raise NMR as a more resolutive, sensitive and accessible tool for clinical applications and point-of-care diagnosis. Thanks to these advances, NMR has a strong potential to join the other analytical tools currently used in clinical settings.

Innate immune activation by checkpoint inhibition in human patient-derived lung cancer tissues

Although Pembrolizumab-based immunotherapy has significantly improved lung cancer patient survival, many patients show variable efficacy and resistance development. A better understanding of the drug’s action is needed to improve patient outcomes. Functional heterogeneity of the tumor microenvironment (TME) is crucial to modulating drug resistance; understanding of individual patients’ TME that impacts drug response is hampered by lack of appropriate models. Lung organotypic tissue slice cultures (OTC) with patients’ native TME procured from primary and brain-metastasized (BM) non-small cell lung cancer (NSCLC) patients were treated with Pembrolizumab and/or beta-glucan (WGP, an innate immune activator). Metabolic tracing with ¹³C₆-Glc/¹³C₅,¹⁵N₂-Gln, multiplex immunofluorescence, and digital spatial profiling (DSP) were employed to interrogate metabolic and functional responses to Pembrolizumab and/or WGP. Primary and BM PD-1⁺ lung cancer OTC responded to Pembrolizumab and Pembrolizumab + WGP treatments, respectively. Pembrolizumab activated innate immune metabolism and functions in primary OTC, which were accompanied by tissue damage. DSP analysis indicated an overall decrease in immunosuppressive macrophages and T cells but revealed microheterogeneity in immune responses and tissue damage. Two TMEs with altered cancer cell properties showed resistance. Pembrolizumab or WGP alone had negligible effects on BM-lung cancer OTC but Pembrolizumab + WGP blocked central metabolism with increased pro-inflammatory effector release and tissue damage. In-depth metabolic analysis and multiplex TME imaging of lung cancer OTC demonstrated overall innate immune activation by Pembrolizumab but heterogeneous responses in the native TME of a patient with primary NSCLC. Metabolic and functional analysis also revealed synergistic action of Pembrolizumab and WGP in OTC of metastatic NSCLC.

FATTY ACID SYNTHESIS IS REQUIRED FOR BREAST CANCER BRAIN METASTASIS

Brain metastases are refractory to therapies that control systemic disease in patients with human epidermal growth factor receptor 2 (HER2+) breast cancer, and the brain microenvironment contributes to this therapy resistance. Nutrient availability can vary across tissues, therefore metabolic adaptations required for brain metastatic breast cancer growth may introduce liabilities that can be exploited for therapy. Here, we assessed how metabolism differs between breast tumors in brain versus extracranial sites and found that fatty acid synthesis is elevated in breast tumors growing in brain. We determine that this phenotype is an adaptation to decreased lipid availability in brain relative to other tissues, resulting in a site-specific dependency on fatty acid synthesis for breast tumors growing at this site. Genetic or pharmacological inhibition of fatty acid synthase (FASN) reduces HER2+ breast tumor growth in the brain, demonstrating that differences in nutrient availability across metastatic sites can result in targetable metabolic dependencies.

Comparing Stable Isotope Enrichment by Gas Chromatography with Time-of-Flight, Quadrupole Time-of-Flight, and Quadrupole Mass Spectrometry

Stable isotope tracers are applied for in vivo and in vitro studies to reveal the activity of enzymes and intracellular metabolic pathways. Most often, such tracers are used with gas chromatography coupled to mass spectrometry (GC-MS) owing to its ease of operation and reproducible mass spectral databases. Differences in isotope tracer performance of the classic GC-quadrupole MS instrument and newer time-of-flight instruments are not well studied. Here, we used three commercially available instruments for the analysis of identical samples from a stable isotope labeling study that used [U-13C6] d-glucose to investigate the metabolism of the bacterium Rothia mucilaginosa with respect to 29 amino acids and hydroxyl acids involved in primary metabolism. The prokaryote R. mucilaginosa belongs to the family of Micrococcaceae and is present and metabolically active in the airways and sputum of cystic fibrosis patients. Overall, all three GC-MS instruments (low-resolution GC-SQ MS, low-resolution GC-TOF MS, and high-resolution GC-QTOF MS) can be used to perform stable isotope tracing studies for glycolytic intermediates, tricarboxylic acid (TCA) metabolites, and amino acids, yielding similar biological results, with high-resolution GC-QTOF MS offering additional capabilities to identify the chemical structures of unknown compounds that might show significant isotope enrichments in biological studies.

Phospholipid dynamics in ex vivo lung cancer and normal lung explants

In cancer cells, metabolic pathways are reprogrammed to promote cell proliferation and growth. While the rewiring of central biosynthetic pathways is being extensively studied, the dynamics of phospholipids in cancer cells are still poorly understood. In our study, we sought to evaluate de novo biosynthesis of glycerophospholipids (GPLs) in ex vivo lung cancer explants and corresponding normal lung tissue from six patients by utilizing a stable isotopic labeling approach. Incorporation of fully ¹³C-labeled glucose into the backbone of phosphatidylethanolamine (PE), phosphatidylcholine (PC), and phosphatidylinositol (PI) was analyzed by liquid chromatography/mass spectrometry. Lung cancer tissue showed significantly elevated isotopic enrichment within the glycerol backbone of PE, normalized to its incorporation into PI, compared to that in normal lung tissue; however, the size of the PE pool normalized to the size of the PI pool was smaller in tumor tissue. These findings indicate enhanced PE turnover in lung cancer tissue. Elevated biosynthesis of PE in lung cancer tissue was supported by enhanced expression of the PE biosynthesis genes ETNK2 and EPT1 and decreased expression of the PC and PI biosynthesis genes CHPT1 and CDS2, respectively, in different subtypes of lung cancer in publicly available datasets. Our study demonstrates that incorporation of glucose-derived carbons into the glycerol backbone of GPLs can be monitored to study phospholipid dynamics in tumor explants and shows that PE turnover is elevated in lung cancer tissue compared to normal lung tissue.

Similarities and differences in metabolites of tongue cancer cells among two- and three-dimensional cultures and xenografts

Metabolic programming of cancer cells is an essential step in transformation and tumor growth. We established two-dimensional (2D) monolayer and three-dimensional (3D) cultures, the latter called a "tissueoid cell culture system", using four types of tongue cancer cell lines. We also undertook a comprehensive metabolome analysis of three groups that included xenografts created by transplanting the cell lines into nude mice. In addition, we undertook a functional analysis of the mitochondria, which plays a key role in cancer metabolism. Principal component analysis revealed the plots of the four cell lines to be much narrower in 2D culture than in 3D culture and xenograft groups. Moreover, compared to xenografts, the 2D culture had significantly lower levels of most metabolites. These results suggest that the unique characteristics of each cell disappeared in 2D culture, and a type of metabolism unique to monolayer culture took over. Conversely, ATP production, biomass synthesis, and maintenance of redox balance were shown in 3D culture using sufficient nutrients, which closely resembled the metabolic activity in the xenografts. However, there were several differences between the metabolic activity in the 3D culture and xenografts. In vivo, the cancer tissue had blood flow with stromal cells present around the cancer cells. In the xenografts, we detected metabolized and degraded products in the liver and other organs of the host mice. Furthermore, the 3D system did not show impairment of mitochondrial function in the cancer cells, suggesting that cancer cells produce energy simultaneously through mitochondria, as well as aerobic glycolysis.

Oral Gavage Delivery of Stable Isotope Tracer for In Vivo Metabolomics

Stable isotope-resolved metabolomics (SIRM) is a powerful tool for understanding disease. Advances in SIRM techniques have improved isotopic delivery and expanded the workflow from exclusively in vitro applications to in vivo methodologies to study systemic metabolism. Here, we report a simple, minimally-invasive and cost-effective method of tracer delivery to study SIRM in vivo in laboratory mice. Following a brief fasting period, we orally administered a solution of [U-13C] glucose through a blunt gavage needle without anesthesia, at a physiological dose commonly used for glucose tolerance tests (2 g/kg bodyweight). We defined isotopic enrichment in plasma and tissue at 15, 30, 120, and 240 min post-gavage. 13C-labeled glucose peaked in plasma around 15 min post-gavage, followed by period of metabolic decay and clearance until 4 h. We demonstrate robust enrichment of a variety of central carbon metabolites in the plasma, brain and liver of C57/BL6 mice, including amino acids, neurotransmitters, and glycolytic and tricarboxylic acid (TCA) cycle intermediates. We then applied this method to study in vivo metabolism in two distinct mouse models of diseases known to involve dysregulation of glucose metabolism: Alzheimer's disease and type II diabetes. By delivering [U-13C] glucose via oral gavage to the 5XFAD Alzheimer's disease model and the Lepob/ob type II diabetes model, we were able to resolve significant differences in multiple central carbon pathways in both model systems, thus providing evidence of the utility of this method to study diseases with metabolic components. Together, these data clearly demonstrate the efficacy and efficiency of an oral gavage delivery method, and present a clear time course for 13C enrichment in plasma, liver and brain of mice following oral gavage of [U-13C] glucose-data we hope will aid other researchers in their own 13C-glucose metabolomics study design.

Resolving Metabolic Heterogeneity in Experimental Models of the Tumor Microenvironment from a Stable Isotope Resolved Metabolomics Perspective

The tumor microenvironment (TME) comprises complex interactions of multiple cell types that determines cell behavior and metabolism such as nutrient competition and immune suppression. We discuss the various types of heterogeneity that exist in solid tumors, and the complications this invokes for studies of TME. As human subjects and in vivo model systems are complex and difficult to manipulate, simpler 3D model systems that are compatible with flexible experimental control are necessary for studying metabolic regulation in TME. Stable Isotope Resolved Metabolomics (SIRM) is a valuable tool for tracing metabolic networks in complex systems, but at present does not directly address heterogeneous metabolism at the individual cell level. We compare the advantages and disadvantages of different model systems for SIRM experiments, with a focus on lung cancer cells, their interactions with macrophages and T cells, and their response to modulators in the immune microenvironment. We describe the experimental set up, illustrate results from 3D cultures and co-cultures of lung cancer cells with human macrophages, and outline strategies to address the heterogeneous TME.

Metabolic reprogramming in tumors: Contributions of the tumor microenvironment

The genetic alterations associated with cell transformation are in large measure expressed in the metabolic phenotype as cancer cells proliferate and change their local environment, and prepare for metastasis. Qualitatively, the fundamental biochemistry of cancer cells is generally the same as in the untransformed cells, but the cancer cells produce a local environment, the TME, that is hostile to the stromal cells, and compete for nutrients. In order to proliferate, cells need sufficient nutrients, either those that cannot be made by the cells themselves, or must be made from simpler precursors. However, in solid tumors, the nutrient supply is often limiting given the potential for rapid proliferation, and the poor quality of the vasculature. Thus, cancer cells may employ a variety of strategies to obtain nutrients for survival, growth and metastasis. Although much has been learned using established cell lines in standard culture conditions, it is becoming clear from in vivo metabolic studies that this can also be misleading, and which nutrients are used for energy production versus building blocks for synthesis of macromolecules can vary greatly from tumor to tumor, and even within the same tumor. Here we review the operation of metabolic networks, and how recent understanding of nutrient supply in the TME and utilization are being revealed using stable isotope tracers in vivo as well as in vitro.

Inhibition of Anaplerotic Glutaminolysis Underlies Selenite Toxicity in Human Lung Cancer

Large clinical trials and model systems studies suggest that the chemical form of selenium dictates chemopreventive and chemotherapeutic efficacy. Selenite induces excess ROS production, which mediates autophagy and eventual cell death in non-small cell lung cancer adenocarcinoma A549 cells. As the mechanisms underlying these phenotypic effects are unclear, the clinical relevance of selenite for cancer therapy remains to be determined. The authors' previous stable isotope-resolved metabolomics and gene expression analysis showed that selenite disrupts glycolysis, the Krebs cycle, and polyamine metabolism in A549 cells, potentially through perturbed glutaminolysis, a vital anaplerotic process for proliferation of many cancer cells. Herein, the role of the glutaminolytic enzyme glutaminase 1 (GLS1) in selenite's toxicity in A549 cells and in patient-derived lung cancer tissues is investigated. Using [¹³ C₆ ]-glucose and [¹³ C₅ ,¹⁵ N₂ ]-glutamine tracers, selenite's action on metabolic networks is determined. Selenite inhibits glutaminolysis and glutathione synthesis by suppressing GLS1 expression, and blocks the Krebs cycle, but transiently activates pyruvate carboxylase activity. Glutamate supplementation partially rescues these anti-proliferative and oxidative stress activities. Similar metabolic perturbations and necrosis are observed in selenite-treated human patients' cancerous lung tissues ex vivo. The results support the hypothesis that GLS1 suppression mediates part of the anti-cancer activity of selenite both in vitro and ex vivo.

Preclinical Organotypic Models for the Assessment of Novel Cancer Therapeutics and Treatment

The immense costs in both financial terms and preclinical research effort that occur in the development of anticancer drugs are unfortunately not matched by a substantial increase in improved clinical therapies due to the high rate of failure during clinical trials. This may be due to issues with toxicity or lack of clinical effectiveness when the drug is evaluated in patients. Currently, much cancer research is driven by the need to develop therapies that can exploit cancer cell adaptations to conditions in the tumor microenvironment such as acidosis and hypoxia, the requirement for more-specific, targeted treatments, or the exploitation of 'precision medicine' that can target known genomic changes in patient DNA. The high attrition rate for novel anticancer therapies suggests that the preclinical methods used in screening anticancer drugs need improvement. This chapter considers the advantages and disadvantages of 3D organotypic models in both cancer research and cancer drug screening, particularly in the areas of targeted drugs and the exploitation of genomic changes that can be used for therapeutic advantage in precision medicine.

Metabolic Labeling of Cultured Mammalian Cells for Stable Isotope-Resolved Metabolomics: Practical Aspects of Tissue Culture and Sample Extraction

Stable isotope-resolved metabolomics (SIRM) methods are used increasingly by cancer researchers to probe metabolic pathways and identify vulnerabilities in cancer cells. Analytical and computational advances are being made constantly, but tissue culture and sample extraction procedures are often variable and not elaborated in the literature. This chapter discusses basic aspects of tissue culture practices as they relate to the use of stable isotope tracers and provides a detailed metabolic labeling and metabolite extraction procedure designed to maximize the amount of information that can be obtained from a single tracer experiment.

NMR and MS-based Stable Isotope-Resolved Metabolomics and Applications in Cancer Metabolism

There is considerable interest in defining metabolic reprogramming in human diseases, which is recognized as a hallmark of human cancer. Although radiotracers have a long history in specific metabolic studies, stable isotope-enriched precursors coupled with modern high resolution mass spectrometry and NMR spectroscopy have enabled systematic mapping of metabolic networks and fluxes in cells, tissues and living organisms including humans. These analytical platforms are high in information content, are complementary and cross-validating in terms of compound identification, quantification, and isotope labeling pattern analysis of a large number of metabolites simultaneously. Furthermore, new developments in chemoselective derivatization and in vivo spectroscopy enable tracking of labile/low abundance metabolites and metabolic kinetics in real-time. Here we review developments in Stable Isotope Resolved Metabolomics (SIRM) and recent applications in cancer metabolism using a wide variety of stable isotope tracers that probe both broad and specific aspects of cancer metabolism required for proliferation and survival.

Stable Isotope-Resolved Metabolomics Shows Metabolic Resistance to Anti-Cancer Selenite in 3D Spheroids versus 2D Cell Cultures

Conventional two-dimensional (2D) cell cultures are grown on rigid plastic substrates with unrealistic concentration gradients of O₂, nutrients, and treatment agents. More importantly, 2D cultures lack cell–cell and cell–extracellular matrix (ECM) interactions, which are critical for regulating cell behavior and functions. There are several three-dimensional (3D) cell culture systems such as Matrigel, hydrogels, micropatterned plates, and hanging drop that overcome these drawbacks but they suffer from technical challenges including long spheroid formation times, difficult handling for high throughput assays, and/or matrix contamination for metabolic studies. Magnetic 3D bioprinting (M3DB) can circumvent these issues by utilizing nanoparticles that enable spheroid formation and growth via magnetizing cells. M3DB spheroids have been shown to emulate tissue and tumor microenvironments while exhibiting higher resistance to toxic agents than their 2D counterparts. It is, however, unclear if and how such 3D systems impact cellular metabolic networks, which may determine altered toxic responses in cells. We employed a Stable Isotope-Resolved Metabolomics (SIRM) approach with ¹³C₆-glucose as tracer to map central metabolic networks both in 2D cells and M3DB spheroids formed from lung (A549) and pancreatic (PANC1) adenocarcinoma cells without or with an anti-cancer agent (sodium selenite). We found that the extent of ¹³C-label incorporation into metabolites of glycolysis, the Krebs cycle, the pentose phosphate pathway, and purine/pyrimidine nucleotide synthesis was largely comparable between 2D and M3DB culture systems for both cell lines. The exceptions were the reduced capacity for de novo synthesis of pyrimidine and sugar nucleotides in M3DB than 2D cultures of A549 and PANC1 cells as well as the presence of gluconeogenic activity in M3DB spheroids of PANC1 cells but not in the 2D counterpart. More strikingly, selenite induced much less perturbation of these pathways in the spheroids relative to the 2D counterparts in both cell lines, which is consistent with the corresponding lesser effects on morphology and growth. Thus, the increased resistance of cancer cell spheroids to selenite may be linked to the reduced capacity of selenite to perturb these metabolic pathways necessary for growth and survival.

LC-MS based cell metabolic profiling of tumor cells: a new predictive method for research on the mechanism of action of anticancer candidates

In the process of anticancer drug development, research on the mechanism of action remains a major obstacle. In the present study, a cell metabolic profiling based discriminatory model was designed to give general direction on anticancer candidate mechanisms. Firstly, ultra-performance liquid chromatography in tandem with high-definition mass spectrometry was applied to obtain a comprehensive metabolic view of 12 human tumor cells. Secondly, multivariate data analysis was used to assess the metabolites' variations, and 42 metabolites were identified as the main contributors to the discrimination of different groups. Then a metabolite-based prediction model was constructed for the first time and verified by cross validation (R 2 = 0.909 and Q 2 = 0.869) and a permutation test (R 2 = 0.0871 and Q 2 = -0.4360). To validate if the model can be applied for mechanism prediction, 4 independent sample sets were used to train the model and the data dots of different drugs were located in different regions. Finally, the model was applied to predict the anticancer mechanism of two natural compounds and the results were consistent with several other studies. Overall, this is the first experimental evidence which reveals that a metabolic profiling based prediction model has good performance in anticancer mechanism research, and thus it may be a new method for rapid mechanism screening.

Noninvasive liquid diet delivery of stable isotopes into mouse models for deep metabolic network tracing

Delivering isotopic tracers for metabolic studies in rodents without overt stress is challenging. Current methods achieve low label enrichment in proteins and lipids. Here, we report noninvasive introduction of ¹³C₆-glucose via a stress-free, ad libitum liquid diet. Using NMR and ion chromatography-mass spectrometry, we quantify extensive ¹³C enrichment in products of glycolysis, the Krebs cycle, the pentose phosphate pathway, nucleobases, UDP-sugars, glycogen, lipids, and proteins in mouse tissues during 12 to 48 h of ¹³C₆-glucose feeding. Applying this approach to patient-derived lung tumor xenografts (PDTX), we show that the liver supplies glucose-derived Gln via the blood to the PDTX to fuel Glu and glutathione synthesis while gluconeogenesis occurs in the PDTX. Comparison of PDTX with ex vivo tumor cultures and arsenic-transformed lung cells versus xenografts reveals differential glucose metabolism that could reflect distinct tumor microenvironment. We further found differences in glucose metabolism between the primary PDTX and distant lymph node metastases.

Exploring cancer metabolism using stable isotope-resolved metabolomics (SIRM)

Metabolic reprogramming is a hallmark of cancer. The changes in metabolism are adaptive to permit proliferation, survival, and eventually metastasis in a harsh environment. Stable isotope-resolved metabolomics (SIRM) is an approach that uses advanced approaches of NMR and mass spectrometry to analyze the fate of individual atoms from stable isotope-enriched precursors to products to deduce metabolic pathways and networks. The approach can be applied to a wide range of biological systems, including human subjects. This review focuses on the applications of SIRM to cancer metabolism and its use in understanding drug actions.

Beyond the paradigm: Combining mass spectrometry and nuclear magnetic resonance for metabolomics

Metabolomics is undergoing tremendous growth and is being employed to solve a diversity of biological problems from environmental issues to the identification of biomarkers for human diseases. Nuclear magnetic resonance (NMR) and mass spectrometry (MS) are the analytical tools that are routinely, but separately, used to obtain metabolomics data sets due to their versatility, accessibility, and unique strengths. NMR requires minimal sample handling without the need for chromatography, is easily quantitative, and provides multiple means of metabolite identification, but is limited to detecting the most abundant metabolites (⩾1μM). Conversely, mass spectrometry has the ability to measure metabolites at very low concentrations (femtomolar to attomolar) and has a higher resolution (∼10³-10⁴) and dynamic range (∼10³-10⁴), but quantitation is a challenge and sample complexity may limit metabolite detection because of ion suppression. Consequently, liquid chromatography (LC) or gas chromatography (GC) is commonly employed in conjunction with MS, but this may lead to other sources of error. As a result, NMR and mass spectrometry are highly complementary, and combining the two techniques is likely to improve the overall quality of a study and enhance the coverage of the metabolome. While the majority of metabolomic studies use a single analytical source, there is a growing appreciation of the inherent value of combining NMR and MS for metabolomics. An overview of the current state of utilizing both NMR and MS for metabolomics will be presented.

NMR-based Stable Isotope Resolved Metabolomics in systems biochemistry

Metabolism is the basic activity of live cells, and monitoring the metabolic state provides a dynamic picture of the cells or tissues, and how they respond to external changes, for in disease or treatment with drugs. NMR is an extremely versatile analytical tool that can be applied to a wide range of biochemical problems. Despite its modest sensitivity its versatility make it an ideal tool for analyzing biochemical dynamics both in vitro and in vivo, especially when coupled with its isotope editing capabilities, from which isotope distributions can be readily determined. These are critical for any analyses of flux in live organisms. This review focuses on the utility of NMR spectroscopy in metabolomics, with an emphasis on NMR applications in stable isotope-enriched tracer research for elucidating biochemical pathways and networks with examples from nucleotide biochemistry. The knowledge gained from this area of research provides a ready link to genomic, epigenomic, transcriptomic, and proteomic information to achieve systems biochemical understanding of living cells and organisms.