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Introduction: Stable isotope tracers have been increasingly used in preclinical cancer model systems, including cell culture and mouse xenografts, to probe the altered metabolism of a variety of cancers, such as accelerated glycolysis and glutaminolysis and generation of oncometabolites. Comparatively little has been reported on the fidelity of the different preclinical model systems in recapitulating the aberrant metabolism of tumors., Objectives: We have been developing several different experimental model systems for systems biochemistry analyses of non-small cell lung cancer (NSCLC 1 ) using patient-derived tissues to evaluate appropriate models for metabolic and phenotypic analyses., Methods: To address the issue of fidelity, we have carried out a detailed Stable Isotope-Resolved Metabolomics study of freshly resected tissue slices, mouse patient derived xenografts (PDXs), and cells derived from a single patient using both 13 C 6 -glucose and 13 C 5 , 15 N 2 -glutamine tracers., Results: Although we found similar glucose metabolism in the three models, glutamine utilization was markedly higher in the isolated cell culture and in cell culture-derived xenografts compared with the primary cancer tissue or direct tissue xenografts (PDX)., Conclusions: This suggests that caution is needed in interpreting cancer biochemistry using patient-derived cancer cells in vitro or in xenografts, even at very early passage, and that direct analysis of patient derived tissue slices provides the optimal model for ex vivo metabolomics. Further research is needed to determine the generality of these observations., (© 2024. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Stable isotope-resolved metabolomics delineates reprogrammed intersecting metabolic networks in human cancers. Knowledge gained from in vivo patient studies provides the "benchmark" for cancer models to recapitulate. It is particularly difficult to model patients' tumor microenvironment (TME) with its complex cell-cell/cell-matrix interactions, which shapes metabolic reprogramming crucial to cancer development/drug resistance. Patient-derived organotypic tissue cultures (PD-OTCs) represent a unique model that retains an individual patient's TME. PD-OTCs of non-small-cell lung cancer better recapitulated the in vivo metabolic reprogramming of patient tumors than the patient-derived tumor xenograft (PDTX), while enabling interrogation of immunometabolic response to modulators and TME-dependent resistance development. Patient-derived organoids (PDOs) are also good models for reconstituting TME-dependent metabolic reprogramming and for evaluating therapeutic responses. Single-cell based 'omics on combinations of PD-OTC and PDO models will afford an unprecedented understanding on TME dependence of human cancer metabolic reprogramming, which should translate into the identification of novel metabolic targets for regulating TME interactions and drug resistance., (Copyright © 2024 Cold Spring Harbor Laboratory Press; all rights reserved.)

Stable isotope-resolved metabolomics comprises a critical set of technologies that can be applied to a wide variety of systems, from isolated cells to whole organisms, to define metabolic pathway usage and responses to perturbations such as drugs or mutations, as well as providing the basis for flux analysis. As the diversity of stable isotope-enriched compounds is very high, and with newer approaches to multiplexing, the coverage of metabolism is now very extensive. However, as the complexity of the model increases, including more kinds of interacting cell types and interorgan communication, the analytical complexity also increases. Further, as studies move further into spatially resolved biology, new technical problems have to be overcome owing to the small number of analytes present in the confines of a single cell or cell compartment. Here, we review the overall goals and solutions made possible by stable isotope tracing and their applications to models of increasing complexity. Finally, we discuss progress and outstanding difficulties in high-resolution spatially resolved tracer-based metabolic studies.

Myeloid derived suppressor cells (MDSCs) are key regulators of immune responses and correlate with poor outcomes in hematologic malignancies. Here, we identify that MDSC mitochondrial fitness controls the efficacy of doxorubicin chemotherapy in a preclinical lymphoma model. Mechanistically, we show that triggering STAT3 signaling via β2-adrenergic receptor (β2-AR) activation leads to improved MDSC function through metabolic reprograming, marked by sustained mitochondrial respiration and higher ATP generation which reduces AMPK signaling, altering energy metabolism. Furthermore, induced STAT3 signaling in MDSCs enhances glutamine consumption via the TCA cycle. Metabolized glutamine generates itaconate which downregulates mitochondrial reactive oxygen species via regulation of Nrf2 and the oxidative stress response, enhancing MDSC survival. Using β2-AR blockade, we target the STAT3 pathway and ATP and itaconate metabolism, disrupting ATP generation by the electron transport chain and decreasing itaconate generation causing diminished MDSC mitochondrial fitness. This disruption increases the response to doxorubicin and could be tested clinically., (© 2024. The Author(s).)

Metabolic flexibility has emerged as a critical determinant of CD8+ T-cell antitumor activity, yet the mechanisms driving the metabolic flexibility of T cells have not been determined. In this study, we investigated the influence of the nuclear cap-binding complex (CBC) adaptor protein ARS2 on mature T cells. In doing so, we discovered a novel signaling axis that endows activated CD8+ T cells with flexibility of glucose catabolism. ARS2 upregulation driven by CD28 signaling reinforced splicing factor recruitment to pre-mRNAs and affected approximately one-third of T-cell activation-induced alternative splicing events. Among these effects, the CD28-ARS2 axis suppressed the expression of the M1 isoform of pyruvate kinase in favor of PKM2, a key determinant of CD8+ T-cell glucose utilization, interferon gamma production, and antitumor effector function. Importantly, PKM alternative splicing occurred independently of CD28-driven PI3K pathway activation, revealing a novel means by which costimulation reprograms glucose metabolism in CD8+ T cells., (© 2024. The Author(s).)

EZH2 (Enhancer of Zeste Homolog 2), a subunit of Polycomb Repressive Complex 2 (PRC2), catalyzes the trimethylation of histone H3 at lysine 27 (H3K27me3), which represses expression of genes. It also has PRC2-independent functions, including transcriptional coactivation of oncogenes, and is frequently overexpressed in lung cancers. Clinically, EZH2 inhibition can be achieved with the FDA-approved drug EPZ-6438 (tazemetostat). To realize the full potential of EZH2 blockade, it is critical to understand how cell-cell/cell-matrix interactions present in 3D tissue and cell culture systems influences this blockade in terms of growth-related metabolic functions. Here, we show that EZH2 suppression reduced growth of human lung adenocarcinoma A549 cells in 2D cultures but stimulated growth in 3D cultures. To understand the metabolic underpinnings, we employed [ 13 C 6 ]-glucose stable isotope-resolved metabolomics to determine the effect of EZH2 suppression on metabolic networks in 2D versus 3D A549 cultures. The Krebs cycle, neoribogenesis, γ-aminobutyrate metabolism, and salvage synthesis of purine nucleotides were activated by EZH2 suppression in 3D spheroids but not in 2D cells, consistent with the growth effect. Using simultaneous 2 H 7 -glucose + 13 C 5 , 15 N 2 -Gln tracers and EPZ-6438 inhibition of H3 trimethylation, we delineated the effects on the Krebs cycle, γ-aminobutyrate metabolism, gluconeogenesis, and purine salvage to be PRC2-dependent. Furthermore, the growth/metabolic effects differed for mouse Matrigel versus self-produced A549 extracellular matrix. Thus, our findings highlight the importance of the presence and nature of extracellular matrix in studying the function of EZH2 and its inhibitors in cancer cells for modeling the in vivo outcomes., Competing Interests: Conflict of interest The authors declare that they have no conflicts of interest with the contents of this article., (Copyright © 2023 The Authors. Published by Elsevier Inc. All rights reserved.)

Cell proliferation requires metabolic reprogramming to accommodate biosynthesis of new cell components, and similar alterations occur in cancer cells. However, the mechanisms linking the cell cycle machinery to metabolism are not well defined. Cyclin D1, along with its main partner cyclin-dependent kinase 4 (Cdk4), is a pivotal cell cycle regulator and driver oncogene that is overexpressed in many cancers. Here, we examine hepatocyte proliferation to define novel effects of cyclin D1 on biosynthetic metabolism. Metabolomic studies reveal that cyclin D1 broadly promotes biosynthetic pathways including glycolysis, the pentose phosphate pathway, and the purine and pyrimidine nucleotide synthesis in hepatocytes. Proteomic analyses demonstrate that overexpressed cyclin D1 binds to numerous metabolic enzymes including those involved in glycolysis and pyrimidine synthesis. In the glycolysis pathway, cyclin D1 activates aldolase and GAPDH, and these proteins are phosphorylated by cyclin D1/Cdk4 in vitro. De novo pyrimidine synthesis is particularly dependent on cyclin D1. Cyclin D1/Cdk4 phosphorylates the initial enzyme of this pathway, carbamoyl-phosphate synthetase 2, aspartate transcarbamylase, and dihydroorotase (CAD), and metabolomic analysis indicates that cyclin D1 depletion markedly reduces the activity of this enzyme. Pharmacologic inhibition of Cdk4 along with the downstream pyrimidine synthesis enzyme dihydroorotate dehydrogenase synergistically inhibits proliferation and survival of hepatocellular carcinoma cells. These studies demonstrate that cyclin D1 promotes a broad network of biosynthetic pathways in hepatocytes, and this model may provide insights into potential metabolic vulnerabilities in cancer cells., Competing Interests: Conflict of interest The authors declare that they have no conflicts of interest with the contents of this article., (Copyright © 2023 The Authors. Published by Elsevier Inc. All rights reserved.)

Robust and effective T cell immune surveillance and cancer immunotherapy require proper allocation of metabolic resources to sustain energetically costly processes, including growth and cytokine production. Here, we show that asparagine (Asn) restriction on CD8 + T cells exerted opposing effects during activation (early phase) and differentiation (late phase) following T cell activation. Asn restriction suppressed activation and cell cycle entry in the early phase while rapidly engaging the nuclear factor erythroid 2-related factor 2 (NRF2)-dependent stress response, conferring robust proliferation and effector function on CD8 + T cells during differentiation. Mechanistically, NRF2 activation in CD8 + T cells conferred by Asn restriction rewired the metabolic program by reducing the overall glucose and glutamine consumption but increasing intracellular nucleotides to promote proliferation. Accordingly, Asn restriction or NRF2 activation potentiated the T cell-mediated antitumoral response in preclinical animal models, suggesting that Asn restriction is a promising and clinically relevant strategy to enhance cancer immunotherapy. Our study revealed Asn as a critical metabolic node in directing the stress signaling to shape T cell metabolic fitness and effector functions., (© 2023. The Author(s).)

Past chemopreventive human trials on dietary selenium supplements produced controversial outcomes. They largely employed selenomethionine (SeM)-based diets. SeM was less toxic than selenite or methylseleninic acid (MSeA) to lung cancer cells. We thus investigated the toxic action of these Se agents in two non-small cell lung cancer (NSCLC) cell lines and ex vivo organotypic cultures (OTC) of NSCLC patient lung tissues. Stable isotope-resolved metabolomics (SIRM) using 13 C 6 -glucose and 13 C 5, 15 N 2 -glutamine tracers with gene knockdowns were employed to examine metabolic dysregulations associated with cell type- and treatment-dependent phenotypic changes. Inhibition of key anaplerotic processes, pyruvate carboxylation (PyC) and glutaminolysis were elicited by exposure to MSeA and selenite but not by SeM. They were accompanied by distinct anabolic dysregulation and reflected cell type-dependent changes in proliferation/death/cell cycle arrest. NSCLC OTC showed similar responses of PyC and/or glutaminolysis to the three agents, which correlated with tissue damages. Altogether, we found differential perturbations in anaplerosis-fueled anabolic pathways to underlie the distinct anti-cancer actions of the three Se agents, which could also explain the failure of SeM-based chemoprevention trials.

Metabolic networks are complex, intersecting, and composed of numerous enzyme-catalyzed biochemical reactions that transfer various molecular moieties among metabolites. Thus, robust reconstruction of metabolic networks requires metabolite moieties to be tracked, which cannot be readily achieved with mass spectrometry (MS) alone. We previously developed an Ion Chromatography-ultrahigh resolution-MS 1 /data independent-MS 2 method to track the simultaneous incorporation of the heavy isotopes 13 C and 15 N into the moieties of purine/pyrimidine nucleotides in mammalian cells. Ultrahigh resolution-MS 1 resolves and counts multiple tracer atoms in intact metabolites, while data independent-tandem MS (MS 2 ) determines isotopic enrichment in their moieties without concern for the numerous mass isotopologue source ions to be fragmented. Together, they enabled rigorous MS-based reconstruction of metabolic networks at specific enzyme levels. We have expanded this approach to trace the labeled atom fate of [ 13 C 6 ]-glucose in 3D A549 spheroids in response to the anticancer agent selenite and that of [ 13 C 5 , 15 N 2 ]-glutamine in 2D BEAS-2B cells in response to arsenite transformation. We deduced altered activities of specific enzymes in the Krebs cycle, pentose phosphate pathway, gluconeogenesis, and UDP-GlcNAc synthesis pathways elicited by the stressors. These metabolic details help elucidate the resistance mechanism of 3D versus 2D A549 cultures to selenite and metabolic reprogramming that can mediate the transformation of BEAS-2B cells by arsenite., Competing Interests: Conflict of interest The authors declare that they have no conflicts of interest with the contents of the article., (Copyright © 2022 The Authors. Published by Elsevier Inc. All rights reserved.)

Immunomodulatory (IM) metabolic reprogramming in macrophages (Mϕs) is fundamental to immune function. However, limited information is available for human Mϕs, particularly in response plasticity, which is critical to understanding the variable efficacy of immunotherapies in cancer patients. We carried out an in-depth analysis by combining multiplex stable isotope-resolved metabolomics with reversed phase protein array to map the dynamic changes of the IM metabolic network and key protein regulators in four human donors' Mϕs in response to differential polarization and M1 repolarizer β-glucan (whole glucan particles [WGPs]). These responses were compared with those of WGP-treated ex vivo organotypic tissue cultures (OTCs) of human non-small cell lung cancer. We found consistently enhanced tryptophan catabolism with blocked NAD + and UTP synthesis in M1-type Mϕs (M1-Mϕs), which was associated with immune activation evidenced by increased release of IL-1β/CXCL10/IFN-γ/TNF-α and reduced phagocytosis. In M2a-Mϕs, WGP treatment of M2a-Mϕs robustly increased glucose utilization via the glycolysis/oxidative branch of the pentose phosphate pathway while enhancing UDP- N -acetyl-glucosamine turnover and glutamine-fueled gluconeogenesis, which was accompanied by the release of proinflammatory IL-1β/TNF-α to above M1-Mϕ's levels, anti-inflammatory IL-10 to above M2a-Mϕ's levels, and attenuated phagocytosis. These IM metabolic responses could underlie the opposing effects of WGP, i.e., reverting M2- to M1-type immune functions but also boosting anti-inflammation. Variable reprogrammed Krebs cycle and glutamine-fueled synthesis of UTP in WGP-treated OTCs of human non-small cell lung cancer were observed, reflecting variable M1 repolarization of tumor-associated Mϕs. This was supported by correlation with IL-1β/TNF-α release and compromised tumor status, making patient-derived OTCs unique models for studying variable immunotherapeutic efficacy in cancer patients., (Copyright © 2022 by The American Association of Immunologists, Inc.)

Glycogen is a readily deployed intracellular energy storage macromolecule composed of branched chains of glucose anchored to the protein glycogenin. Although glycogen primarily occurs in the liver and muscle, it is found in most tissues, and its metabolism has been shown to be important in cancers and immune cells. Robust analysis of glycogen turnover requires stable isotope tracing plus a reliable means of quantifying total and labeled glycogen derived from precursors such as 13C6-glucose. Current methods for analyzing glycogen are time- and sample-consuming, at best semi-quantitative, and unable to measure stable isotope enrichment. Here we describe a microscale method for quantifying both intact and acid-hydrolyzed glycogen by ultra-high-resolution Fourier transform mass spectrometric (UHR-FTMS) and/or NMR analysis in stable isotope resolved metabolomics (SIRM) studies. Polar metabolites, including intact glycogen and their 13C positional isotopomer distributions, are first measured in crude biological extracts by high resolution NMR, followed by rapid and efficient acid hydrolysis to glucose under N2 in a focused beam microwave reactor, with subsequent analysis by UHR-FTMS and/or NMR. We optimized the microwave digestion time, temperature, and oxygen purging in terms of recovery versus degradation and found 10 min at 110−115 °C to give >90% recovery. The method was applied to track the fate of 13C6-glucose in primary human lung BEAS-2B cells, human macrophages, murine liver and patient-derived tumor xenograft (PDTX) in vivo, and the fate of 2H7-glucose in ex vivo lung organotypic tissue cultures of a lung cancer patient. We measured the incorporation of 13C6-glucose into glycogen and its metabolic intermediates, UDP-Glucose and glucose-1-phosphate, to demonstrate the utility of the method in tracing glycogen turnover in cells and tissues. The method offers a quantitative, sensitive, and convenient means to analyze glycogen turnover in mg amounts of complex biological materials.

Cellular metabolism has key roles in T cells differentiation and function. CD4 + T helper-1 (Th1), Th2, and Th17 subsets are highly glycolytic while regulatory T cells (Tregs) use glucose during expansion but rely on fatty acid oxidation for function. Upon uptake, glucose can enter pentose phosphate pathway (PPP) or be used in glycolysis. Here, we showed that blocking 6-phosphogluconate dehydrogenase (6PGD) in the oxidative PPP resulted in substantial reduction of Tregs suppressive function and shifts toward Th1, Th2, and Th17 phenotypes which led to the development of fetal inflammatory disorder in mice model. These in turn improved anti-tumor responses and worsened the outcomes of colitis model. Metabolically, 6PGD blocked Tregs showed improved glycolysis and enhanced non-oxidative PPP to support nucleotide biosynthesis. These results uncover critical role of 6PGD in modulating Tregs plasticity and function, which qualifies it as a novel metabolic checkpoint for immunotherapy applications., Competing Interests: SD, TC, RH, TF, PS No competing interests declared, (© 2021, Daneshmandi et al.)

S-Adenosylmethionine (SAM) and S-adenosylhomocysteine (SAH) are important metabolites in the one-carbon cycle that modulates cellular methylation required for proliferation and epigenetic regulation. Their concentrations, synthesis, and turnover are difficult to determine conveniently and reliably. We have developed such a method by coupling a simple and rapid purification scheme that efficiently captures both compounds, with high sensitivity, sample throughput direct infusion nanoelectrospray ultra-high-resolution Fourier transform mass spectrometry (DI-nESI-UHR-FTMS). This method is compatible with Stable Isotope-Resolved Metabolomic (SIRM) analysis of numerous other metabolites. The limits of detection for both SAM and SAH were <1 nM, and the linearity range was up to 1000 nM. The method was first illustrated for SAM/SAH analysis of mouse livers, and lung adenocarcinoma A549 cells. We then applied the method to track 13 C 1 -CH 3 -Met incorporation into SAM and 13 C 6 -glucose transformation into SAM and SAH via de novo synthesis. We further used the method to show the distinct effects on A549 and H1299 cells with treatment of anti-cancer methylseleninic acid (MSA), selenite, and selenomethionine, notably SAM depletion and increased SAM to SAH ratio by MSA, which implicates altered epigenetic regulation., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2021 Elsevier B.V. All rights reserved.)

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 13 C 6 -Glc/ 13 C 5 , 15 N 2 -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., Competing Interests: TF, HS, SD, AM, MP, TB, TP, DH, CW, AL None, RH none, (© 2021, Fan et al.)

Lipids comprise diverse classes of compounds that are important for the structure and properties of membranes, as high-energy fuel sources and as signaling molecules. Therefore, the turnover rates of these varied classes of lipids are fundamental to cellular function. However, their enormous chemical diversity and dynamic range in cells makes detailed analysis very complex. Furthermore, although stable isotope tracers enable the determination of synthesis and degradation of complex lipids, the numbers of distinguishable molecules increase enormously, which exacerbates the problem. Although LC-MS-MS (Liquid Chromatography-Tandem Mass Spectrometry) is the standard for lipidomics, NMR can add value in global lipid analysis and isotopomer distributions of intact lipids. Here, we describe new developments in NMR analysis for assessing global lipid content and isotopic enrichment of mixtures of complex lipids for two cell lines (PC3 and UMUC3) using both 13 C 6 glucose and 13 C 5 glutamine tracers.

Although T cell expansion depends on glycolysis, T effector cell differentiation requires signaling via the production of reactive oxygen species (ROS). Because the pentose phosphate pathway (PPP) regulates ROS by generating nicotinamide adenine dinucleotide phosphate (NADPH), we examined how PPP blockade affects T cell differentiation and function. Here, we show that genetic ablation or pharmacologic inhibition of the PPP enzyme 6-phosphogluconate dehydrogenase (6PGD) in the oxidative PPP results in the generation of superior CD8 + T effector cells. These cells have gene signatures and immunogenic markers of effector phenotype and show potent anti-tumor functions both in vitro and in vivo. In these cells, metabolic reprogramming occurs along with increased mitochondrial ROS and activated antioxidation machinery to balance ROS production against oxidative damage. Our findings reveal a role of 6PGD as a checkpoint for T cell effector differentiation/survival and evidence for 6PGD as an attractive metabolic target to improve tumor immunotherapy., Competing Interests: Declaration of interests V.A.B. has patents on the PD-1 pathway licensed by Bristol-Myers Squibb, Roche, Merck, EMD-Serono, Boehringer Ingelheim, AstraZeneca, Novartis, and Dako. The authors declare no other competing interests., (Published by Elsevier Inc.)

The metabolome comprises a complex network of interconnecting enzyme-catalyzed reactions that involve transfers of numerous molecular subunits. Thus, the reconstruction of metabolic networks requires metabolite substructures to be tracked. Subunit tracking can be achieved by tracing stable isotopes through metabolic transformations using NMR and ultrahigh -resolution (UHR)-mass spectrometry (MS). UHR-MS 1 readily resolves and counts isotopic labels in metabolites but requires tandem MS to help identify isotopic enrichment in substructures. However, it is challenging to perform chromatography-based UHR-MS 1 with its long acquisition time, while acquiring MS 2 data on many coeluting labeled isotopologues for each metabolite. We have developed an ion chromatography (IC)-UHR-MS 1 /data-independent(DI)-HR-MS 2 method to trace the fate of 13 C atoms from [ 13 C 6 ]-glucose ([ 13 C 6 ]-Glc) in 3D A549 spheroids in response to anticancer selenite and simultaneously 13 C/ 15 N atoms from [ 13 C 5 , 15 N 2 ]-glutamine ([ 13 C 5 , 15 N 2 ]-Gln) in 2D BEAS-2B cells in response to arsenite transformation. This method retains the complete isotopologue distributions of metabolites via UHR-MS 1 while simultaneously acquiring substructure label information via DI-MS 2 . These details in metabolite labeling patterns greatly facilitate rigorous reconstruction of multiple, intersecting metabolic pathways of central metabolism, which are illustrated here for the purine/pyrimidine nucleotide biosynthesis. The pathways reconstructed based on subunit-level isotopologue analysis further reveal specific enzyme-catalyzed reactions that are impacted by selenite or arsenite treatments.

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., Competing Interests: The authors declare no conflicts of interest.

Profound metabolic changes are characteristic of macrophages during classical activation and have been implicated in this phenotype. Here we demonstrate that nitric oxide (NO) produced by murine macrophages is responsible for TCA cycle alterations and citrate accumulation associated with polarization. 13 C tracing and mitochondrial respiration experiments map NO-mediated suppression of metabolism to mitochondrial aconitase (ACO2). Moreover, we find that inflammatory macrophages reroute pyruvate away from pyruvate dehydrogenase (PDH) in an NO-dependent and hypoxia-inducible factor 1α (Hif1α)-independent manner, thereby promoting glutamine-based anaplerosis. Ultimately, NO accumulation leads to suppression and loss of mitochondrial electron transport chain (ETC) complexes. Our data reveal that macrophages metabolic rewiring, in vitro and in vivo, is dependent on NO targeting specific pathways, resulting in reduced production of inflammatory mediators. Our findings require modification to current models of macrophage biology and demonstrate that reprogramming of metabolism should be considered a result rather than a mediator of inflammatory polarization.

Metabolism is a complex network of compartmentalized and coupled chemical reactions, which often involve transfers of sub structures of biomolecules, thus requiring metabolite sub structures to be tracked. Stable isotope resolved metabolomics (SIRM) enables pathways reconstruction, even among chemically identical metabolites, by tracking the provenance of stable isotope-labeled sub structures using NMR and ultrahigh resolution (UHR) MS. The latter can resolve and count isotopic labels in metabolites and can identify isotopic enrichment in substructures when operated in tandem MS mode. However, MS 2 is difficult to implement with chromatography-based UHR-MS due to lengthy MS 1 acquisition time that is required to obtain the molecular isotopologue count, which is further exacerbated by the numerous isotopologue source ions to fragment. We review here recent developments in tandem MS applications of SIRM to obtain more detailed information about isotopologue distributions in metabolites and their substructures.

Mass spectrometry (MS) is frequently used for proteomic and metabolomic profiling of biological samples. Data obtained by MS are often zero-inflated. Those zero values are called point mass values (PMVs). Zero values can be further grouped into biological PMVs and technical PMVs. The former type is caused by true absence of a compound and the later type is caused by a technical detection limit. Methods based on a mixture model have been developed to separate the two types of zeros and to perform differential abundance analysis comparing proteomic/metabolomic profiles between different groups of subjects. However, we notice that those methods may give unstable estimate of the model variance, and thus lead to false positive and false negative results when the number of non-zero values is small. In this paper, we propose a new differential abundance analysis method, DASEV, which uses an empirical Bayes shrinkage method to more robustly estimate the variance and enhance the accuracy of differential abundance analysis. Simulation studies and real data analysis show that DASEV substantially improves parameter estimation of the mixture model and outperforms current methods in identifying differentially abundant features.

Stable isotope-resolved metabolomics (SIRM), based on the analysis of biological samples from living cells incubated with artificial isotope enriched substrates, enables mapping the rates of biochemical reactions (metabolic fluxes). We developed software supporting a workflow of analysis of SIRM data obtained with mass spectrometry (MS). The evaluation of fluxes starting from raw MS recordings requires at least three steps of computer support: first, extraction of mass spectra of metabolites of interest, then correction of the spectra for natural isotope abundance, and finally, evaluation of fluxes by simulation of the corrected spectra using a corresponding mathematical model. A kinetic model based on ordinary differential equations (ODEs) for isotopomers of metabolites of the corresponding biochemical network supports the final part of the analysis, which provides a dynamic flux map.

We have implemented a linear ion trap (LIT)-based SIM-stitching method for ultra-high-resolution Fourier transform mass spectrometry (FTMS) that increases the S/N over a wide m/z range compared to non-segmented wide full-scan (WFS) spectra. Here we described an improved segmented spectral scan stitching method that was based on quadrupole mass filter (QMF)-SIM, which overcame previous limitations of ion signal loss in LIT. This allowed for accurate representation of isotopologue distributions, both at natural abundance and in stable isotope-resolved metabolomics (SIRM)-based experiments. We also introduced a new spectral binning method that provided more precise and resolution-independent bins for irreversibly noise-suppressed FTMS spectra. We demonstrated a substantial improvement in S/N and sensitivity (typically > 10-fold) for 13 C labeled lipid extracts of human macrophages grown as three-dimensional (3D) cell culture, with detection of an increased number of 13 C isotopologue ions. The method also enabled analysis of extracts from very limited biological samples., (Copyright © 2019 Elsevier B.V. All rights reserved.)

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 C 6 ]-glucose and [ 13 C 5 , 15 N 2 ]-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., (© 2019 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.)

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.

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., Competing Interests: The authors declare no conflict of interest., (© 2019 Chongqing Medical University. Production and hosting by Elsevier B.V.)

Nucleotide synthesis is essential to proliferating cells, but the preferred precursors for de novo biosynthesis are not defined in human cancer tissues. We have employed multiplexed stable isotope-resolved metabolomics to track the metabolism of [ 13 C 6 ]glucose, D 2 -glycine, [ 13 C 2 ]glycine, and D 3 -serine into purine nucleotides in freshly resected cancerous and matched noncancerous lung tissues from nonsmall cell lung cancer (NSCLC) patients, and we compared the metabolism with established NSCLC PC9 and A549 cell lines in vitro Surprisingly, [ 13 C 6 ]glucose was the best carbon source for purine synthesis in human NSCLC tissues, in contrast to the noncancerous lung tissues from the same patient, which showed lower mitotic indices and MYC expression. We also observed that D 3 -Ser was preferentially incorporated into purine rings over D 2 -glycine in both tissues and cell lines. MYC suppression attenuated [ 13 C 6 ]glucose, D 3 -serine, and [ 13 C 2 ]glycine incorporation into purines and reduced proliferation in PC9 but not in A549 cells. Using detailed kinetic modeling, we showed that the preferred use of glucose as a carbon source for purine ring synthesis in NSCLC tissues involves cytoplasmic activation/compartmentation of the glucose-to-serine pathway and enhanced reversed one-carbon fluxes that attenuate exogenous serine incorporation into purines. Our findings also indicate that the substrate for de novo nucleotide synthesis differs profoundly between cancer cell lines and fresh human lung cancer tissues; the latter preferred glucose to exogenous serine or glycine but not the former. This distinction in substrate utilization in purine synthesis in human cancer tissues should be considered when targeting one-carbon metabolism for cancer therapy., (© 2019 Fan et al.)

Background: Previous studies suggested that the metabolism is differently reprogrammed in the major subtypes of non-small cell lung cancer (NSCLC), squamous cell carcinomas (SCC) and adenocarcinomas (AdC). However, a comprehensive analysis of this differential metabolic reprogramming is lacking., Methods: Publicly available gene expression data from human lung cancer samples and cell lines were analysed. Stable isotope resolved metabolomics were performed on SCC and ADC tumours in human patients and in freshly resected tumour slices., Results: Analysis of multiple transcriptomics data from human samples identified a SCC-distinguishing enzyme gene signature. SCC tumours from patients infused with [U- 13 C]-glucose and SCC tissue slices incubated with stable isotope tracers demonstrated differential glucose and glutamine catabolism compared to AdCs or non-cancerous lung, confirming increased activity through pathways defined by the SCC metabolic gene signature. Furthermore, the upregulation of Notch target genes was a distinguishing feature of SCCs, which correlated with the metabolic signature. Notch and MYC-driven murine lung tumours recapitulated the SCC-distinguishing metabolic reprogramming. However, the differences between SCCs and AdCs disappear in established cell lines in 2D culture., Conclusions: Our data emphasise the importance of studying lung cancer metabolism in vivo. They also highlight potential targets for therapeutic intervention in SCC patients including differentially expressed enzymes that catalyse reactions in glycolysis, glutamine catabolism, serine, nucleotide and glutathione biosynthesis.

Stable isotope-resolved metabolomics (SIRM) is increasingly used among researchers for metabolic studies including amino acid metabolism. However, the classical GC- or HPLC-based methods for amino acid quantification do not meet the needs for multiplexed stable isotope-enriched analysis by ultrahigh-resolution Fourier transform mass spectrometry (UHR-FTMS). This is due to insufficient acquisition time during chromatographic separations and large dynamic range in concentrations of analytes, which compromises detection and quantification of the numerous metabolite isotopologues present in crude extracts. This chapter discusses a modified ethyl chloroformate derivatization method to enable rapid quantitative analysis of stable isotope-enriched amino acids using direct infusion ion introduction coupled with UHR-FTMS.

Lung cancer is the leading cause of cancer deaths in the United States. Patients with early stage lung cancer have the best prognosis with surgical removal of the tumor, but the disease is often asymptomatic until advanced disease develops, and there are no effective blood-based screening methods for early detection of lung cancer in at-risk populations. We have explored the lipid profiles of blood plasma exosomes using ultra high-resolution Fourier transform mass spectrometry (UHR-FTMS) for early detection of the prevalent non-small cell lung cancers (NSCLC). Exosomes are nanovehicles released by various cells and tumor tissues to elicit important biofunctions such as immune modulation and tumor development. Plasma exosomal lipid profiles were acquired from 39 normal and 91 NSCLC subjects (44 early stage and 47 late stage). We have applied two multivariate statistical methods, Random Forest (RF) and Least Absolute Shrinkage and Selection Operator (LASSO) to classify the data. For the RF method, the Gini importance of the assigned lipids was calculated to select 16 lipids with top importance. Using the LASSO method, 7 features were selected based on a grouped LASSO penalty. The Area Under the Receiver Operating Characteristic curve for early and late stage cancer versus normal subjects using the selected lipid features was 0.85 and 0.88 for RF and 0.79 and 0.77 for LASSO, respectively. These results show the value of RF and LASSO for metabolomics data-based biomarker development, which provide robust an independent classifiers with sparse data sets. Application of LASSO and Random Forests identifies lipid features that successfully distinguish early stage lung cancer patient from healthy individuals., (Copyright © 2018 Elsevier B.V. All rights reserved.)

Introduction: Direct injection Fourier-transform mass spectrometry (FT-MS) allows for the high-throughput and high-resolution detection of thousands of metabolite-associated isotopologues. However, spectral artifacts can generate large numbers of spectral features (peaks) that do not correspond to known compounds. Misassignment of these artifactual features creates interpretive errors and limits our ability to discern the role of representative features within living systems., Objectives: Our goal is to develop rigorous methods that identify and handle spectral artifacts within the context of high-throughput FT-MS-based metabolomics studies., Results: We observed three types of artifacts unique to FT-MS that we named high peak density (HPD) sites: fuzzy sites, ringing and partial ringing. While ringing artifacts are well-known, fuzzy sites and partial ringing have not been previously well-characterized in the literature. We developed new computational methods based on comparisons of peak density within a spectrum to identify regions of spectra with fuzzy sites. We used these methods to identify and eliminate fuzzy site artifacts in an example dataset of paired cancer and non-cancer lung tissue samples and evaluated the impact of these artifacts on classification accuracy and robustness., Conclusion: Our methods robustly identified consistent fuzzy site artifacts in our FT-MS metabolomics spectral data. Without artifact identification and removal, 91.4% classification accuracy was achieved on an example lung cancer dataset; however, these classifiers rely heavily on artifactual features present in fuzzy sites. Proper removal of fuzzy site artifacts produces a more robust classifier based on non-artifactual features, with slightly improved accuracy of 92.4% in our example analysis.

Iron-sulfur (Fe-S) clusters are ancient cofactors in cells and participate in diverse biochemical functions, including electron transfer and enzymatic catalysis. Although cell lines derived from individuals carrying mutations in the Fe-S cluster biogenesis pathway or siRNA-mediated knockdown of the Fe-S assembly components provide excellent models for investigating Fe-S cluster formation in mammalian cells, these experimental strategies focus on the consequences of prolonged impairment of Fe-S assembly. Here, we constructed and expressed dominant-negative variants of the primary Fe-S biogenesis scaffold protein iron-sulfur cluster assembly enzyme 2 (ISCU2) in human HEK293 cells. This approach enabled us to study the early metabolic reprogramming associated with loss of Fe-S-containing proteins in several major cellular compartments. Using multiple metabolomics platforms, we observed a ∼12-fold increase in intracellular citrate content in Fe-S-deficient cells, a surge that was due to loss of aconitase activity. The excess citrate was generated from glucose-derived acetyl-CoA, and global analysis of cellular lipids revealed that fatty acid biosynthesis increased markedly relative to cellular proliferation rates in Fe-S-deficient cells. We also observed intracellular lipid droplet accumulation in both acutely Fe-S-deficient cells and iron-starved cells. We conclude that deficient Fe-S biogenesis and acute iron deficiency rapidly increase cellular citrate concentrations, leading to fatty acid synthesis and cytosolic lipid droplet formation. Our findings uncover a potential cause of cellular steatosis in nonadipose tissues.

We investigated the toxicity of selenium (Se) to the soil invertebrates Folsomia candida (Collembola) and Enchytraeus crypticus (potworm). Studies were designed to generate ecotoxicological benchmarks for developing ecological soil screening levels (Eco-SSLs) for risk assessments of contaminated soils. For the present studies, we selected Sassafras sandy loam, an aerobic upland soil with soil characteristics (low levels of clay and organic matter, soil pH adjusted from 5.2 to 7.1) that support high relative bioavailability of the anionic Se species that is typically found in aerobic soil. The Se was amended into soil as sodium selenate, subjected to weathering and aging using 21 d of alternating cycles of air-drying/rehydration to 60% of the water-holding capacity of the Sassafras sandy loam soil, under ambient greenhouse conditions. Effective concentrations at 20 and 50% (EC20 and EC50) levels for production of juveniles (reproduction) were 4.7 and 10.9 mg of Se/kg of soil (dry mass basis), respectively, for Collembola, and 4.4 and 6.2 mg/kg, respectively, for the potworms. The data enabled the derivation of toxicity benchmarks, contributing to the development of a soil invertebrate-based Eco-SSL of 4.1 mg/kg for Se. Environ Toxicol Chem 2018;37:846-853. Published 2017 Wiley Periodicals Inc. on behalf of SETAC. This article is a US government work and, as such, is in the public domain in the United States of America., (Published 2017 Wiley Periodicals Inc. on behalf of SETAC. This article is a US government work and, as such, is in the public domain in the United States of America.)

Correction for 'Quantitative profiling of carbonyl metabolites directly in crude biological extracts using chemoselective tagging and nanoESI-FTMS' by Pan Deng, et al., Analyst, 2018, 143, 311-322.

The extensive range of chemical structures, wide range of abundances, and chemical instability of metabolites present in the metabolome pose major analytical challenges that are difficult to address with existing technologies. To address these issues, one approach is to target a subset of metabolites that share a functional group, such as ketones and aldehydes, using chemoselective tagging. Here we report a greatly improved chemoselective method for the quantitative analysis of hydrophilic and hydrophobic carbonyl-containing metabolites directly in biological samples. This method is based on direct tissue or cells extraction with simultaneous derivatization of stable and labile carbonylated metabolites using N-[2-(aminooxy)ethyl]-N,N-dimethyl-1-dodecylammonium (QDA) and 13 CD 3 labeled QDA. We combined innovations of direct quenching of biological sample with frozen derivatization conditions under the catalyst N,N-dimethyl-p-phenylenediamine, which facilitated the formation of oxime stable-isotope ion pairs differing by m/z 4.02188 while minimizing metabolite degradation. The resulting oximes were extracted by HyperSep C8 tips to remove interfering compounds, and the products were detected using nano-electrospray ionization interfaced with a Thermo Fusion mass spectrometer. The quaternary ammonium tagging greatly increased electrospray MS detection sensitivity and the signature ions pairs enabled simple identification of carbonyl compounds. The improved method showed the lower limits of quantification for carbonyl standards to be in the range of 0.20-2 nM, with linearity of R 2 > 0.99 over 4 orders of magnitude. We have applied the method to assign 66 carbonyls in mouse tumor tissues, many of which could not be assigned solely by accurate mass and tandem MS. Fourteen of the metabolites were quantified using authentic standards. We also demonstrated the suitability of this method for determining 13 C labeled isotopologues of carbonyl metabolites in 13 C 6 -glucose-based stable isotope-resolved metabolomic (SIRM) studies.

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 13 C 6 -glucose via a stress-free, ad libitum liquid diet. Using NMR and ion chromatography-mass spectrometry, we quantify extensive 13 C 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 13 C 6 -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.

Breast cancers vary by their origin and specific set of genetic lesions, which gives rise to distinct phenotypes and differential response to targeted and untargeted chemotherapies. To explore the functional differences of different breast cell types, we performed Stable Isotope Resolved Metabolomics (SIRM) studies of one primary breast (HMEC) and three breast cancer cells (MCF-7, MDAMB-231, and ZR75-1) having distinct genotypes and growth characteristics, using 13 C 6 -glucose, 13 C-1+2-glucose, 13 C 5 , 15 N 2 -Gln, 13 C 3 -glycerol, and 13 C 8 -octanoate as tracers. These tracers were designed to probe the central energy producing and anabolic pathways (glycolysis, pentose phosphate pathway, Krebs Cycle, glutaminolysis, nucleotide synthesis and lipid turnover). We found that glycolysis was not associated with the rate of breast cancer cell proliferation, glutaminolysis did not support lipid synthesis in primary breast or breast cancer cells, but was a major contributor to pyrimidine ring synthesis in all cell types; anaplerotic pyruvate carboxylation was activated in breast cancer versus primary cells. We also found that glucose metabolism in individual breast cancer cell lines differed between in vitro cultures and tumor xenografts, but not the metabolic distinctions between cell lines, which may reflect the influence of tumor architecture/microenvironment., (Copyright © 2017 International Metabolic Engineering Society. Published by Elsevier Inc. All rights reserved.)

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., (© 2017 by The American Society for Biochemistry and Molecular Biology, Inc.)

Amino acids have crucial roles in central metabolism, both anabolic and catabolic. To elucidate these roles, steady-state concentrations of amino acids alone are insufficient, as each amino acid participates in multiple pathways and functions in a complex network, which can also be compartmentalized. Stable Isotope-Resolved Metabolomics (SIRM) is an approach that uses atom-resolved tracking of metabolites through biochemical transformations in cells, tissues, or whole organisms. Using different elemental stable isotopes to label multiple metabolite precursors makes it possible to resolve simultaneously the utilization of these precursors in a single experiment. Conversely, a single precursor labeled with two (or more) different elemental isotopes can trace the allocation of e.g. C and N atoms through the network. Such dual-label experiments however challenge the resolution of conventional mass spectrometers, which must distinguish the neutron mass differences among different elemental isotopes. This requires ultrahigh resolution Fourier transform mass spectrometry (UHR-FTMS). When combined with direct infusion nano-electrospray ion source (nano-ESI), UHR-FTMS can provide rapid, global, and quantitative analysis of all possible mass isotopologues of metabolites. Unfortunately, very low mass polar metabolites such as amino acids can be difficult to analyze by current models of UHR-FTMS, plus the high salt content present in typical cell or tissue polar extracts may cause unacceptable ion suppression for sources such as nano-ESI. Here we describe a modified method of ethyl chloroformate (ECF) derivatization of amino acids to enable rapid quantitative analysis of stable isotope labeled amino acids using nano-ESI UHR-FTMS. This method showed excellent linearity with quantifiable limits in the low nanomolar range represented in microgram quantities of biological specimens, which results in extracts with total analyte abundances in the low to sub-femtomole range. We have applied this method to profile amino acids and their labeling patterns in 13 C and 2 H doubly labeled PC9 cell extracts, cancerous and non-cancerous tissue extracts from a lung cancer patient and their protein hydrolysates as well as plasma extracts from mice fed with a liquid diet containing 13 C 6 -glucose (Glc). The multi-element isotopologue distributions provided key insights into amino acid metabolism and intracellular pools in human lung cancer tissues in high detail. The 13 C labeling of Asp and Glu revealed de novo synthesis of these amino acids from 13 C 6 -Glc via the Krebs cycle, specifically the elevated level of 13 C 3 -labeled Asp and Glu in cancerous versus non-cancerous lung tissues was consistent with enhanced pyruvate carboxylation. In addition, tracking the fate of double tracers, ( 13 C 6 -Glc +  2 H 2 -Gly or 13 C 6 -Glc +  2 H 3 -Ser) in PC9 cells clearly resolved pools of Ser and Gly synthesized de novo from 13 C 6 -Glc ( 13 C 3 -Ser and 13 C 2 -Gly) versus Ser and Gly derived from external sources ( 2 H 3 -Ser, 2 H 2 -Gly). Moreover the complex 2 H labeling patterns of the latter were results of Ser and Gly exchange through active Ser-Gly one-carbon metabolic pathway in PC9 cells., (Copyright © 2017 Elsevier B.V. All rights reserved.)

Cancer and stromal cell metabolism is important for understanding tumor development, which highly depends on the tumor microenvironment (TME). Cell or animal models cannot recapitulate the human TME. We have developed an ex vivo paired cancerous (CA) and noncancerous (NC) human lung tissue approach to explore cancer and stromal cell metabolism in the native human TME. This approach enabled full control of experimental parameters and acquisition of individual patient's target tissue response to therapeutic agents while eliminating interferences from genetic and physiological variations. In this two-case study of non-small-cell lung cancer, we performed stable isotope-resolved metabolomic (SIRM) experiments on paired CA and NC lung tissues treated with a macrophage activator β-glucan and (13)C6-glucose, followed by ion chromatography-Fourier transform mass spectrometry (IC-FTMS) and nuclear magnetic resonance (NMR) analyses of (13)C-labeling patterns of metabolites. We demonstrated that CA lung tissue slices were metabolically more active than their NC counterparts, which recapitulated the metabolic reprogramming in CA lung tissues observed in vivo. We showed β-glucan-enhanced glycolysis, Krebs cycle, pentose phosphate pathway, antioxidant production, and itaconate buildup in patient UK021 with chronic obstructive pulmonary disease (COPD) and an abundance of tumor-associated macrophages (TAMs) but not in UK049 with no COPD and much less macrophage infiltration. This metabolic response of UK021 tissues was accompanied by reduced mitotic index, increased necrosis, and enhaced inducible nitric oxide synthase (iNOS) expression. We surmise that the reprogrammed networks could reflect β-glucan M1 polarization of human macrophages. This case study presents a unique opportunity for investigating metabolic responses of human macrophages to immune modulators in their native microenvironment on an individual patient basis.

Aims: In this review we compare the advantages and disadvantages of different model biological systems for determining the metabolic functions of cells in complex environments, how they may change in different disease states, and respond to therapeutic interventions., Background: All preclinical drug-testing models have advantages and drawbacks. We compare and contrast established cell, organoid and animal models with ex vivo organ or tissue culture and in vivo human experiments in the context of metabolic readout of drug efficacy. As metabolism reports directly on the biochemical state of cells and tissues, it can be very sensitive to drugs and/or other environmental changes. This is especially so when metabolic activities are probed by stable isotope tracing methods, which can also provide detailed mechanistic information on drug action. We have developed and been applying Stable Isotope-Resolved Metabolomics (SIRM) to examine metabolic reprogramming of human lung cancer cells in monoculture, in mouse xenograft/explant models, and in lung cancer patients in situ (Lane et al. 2011; T. W. Fan et al. 2011; T. W-M. Fan et al. 2012; T. W. Fan et al. 2012; Xie et al. 2014b; Ren et al. 2014a; Sellers et al. 2015b). We are able to determine the influence of the tumor microenvironment using these models. We have now extended the range of models to fresh human tissue slices, similar to those originally described by O. Warburg (Warburg 1923), which retain the native tissue architecture and heterogeneity with a paired benign versus cancer design under defined cell culture conditions. This platform offers an unprecedented human tissue model for preclinical studies on metabolic reprogramming of human cancer cells in their tissue context, and response to drug treatment (Xie et al. 2014a). As the microenvironment of the target human tissue is retained and individual patient's response to drugs is obtained, this platform promises to transcend current limitations of drug selection for clinical trials or treatments., Conclusions and Future Work: Development of ex vivo human tissue and animal models with humanized organs including bone marrow and liver show considerable promise for analyzing drug responses that are more relevant to humans. Similarly using stable isotope tracer methods with these improved models in advanced stages of the drug development pipeline, in conjunction with tissue biopsy is expected significantly to reduce the high failure rate of experimental drugs in Phase II and III clinical trials.

Obesity and its associated comorbidities (for example, diabetes mellitus and hepatic steatosis) contribute to approximately 2.5 million deaths annually and are among the most prevalent and challenging conditions confronting the medical profession. Neurotensin (NT; also known as NTS), a 13-amino-acid peptide predominantly localized in specialized enteroendocrine cells of the small intestine and released by fat ingestion, facilitates fatty acid translocation in rat intestine, and stimulates the growth of various cancers. The effects of NT are mediated through three known NT receptors (NTR1, 2 and 3; also known as NTSR1, 2, and NTSR3, respectively). Increased fasting plasma levels of pro-NT (a stable NT precursor fragment produced in equimolar amounts relative to NT) are associated with increased risk of diabetes, cardiovascular disease and mortality; however, a role for NT as a causative factor in these diseases is unknown. Here we show that NT-deficient mice demonstrate significantly reduced intestinal fat absorption and are protected from obesity, hepatic steatosis and insulin resistance associated with high fat consumption. We further demonstrate that NT attenuates the activation of AMP-activated protein kinase (AMPK) and stimulates fatty acid absorption in mice and in cultured intestinal cells, and that this occurs through a mechanism involving NTR1 and NTR3 (also known as sortilin). Consistent with the findings in mice, expression of NT in Drosophila midgut enteroendocrine cells results in increased lipid accumulation in the midgut, fat body, and oenocytes (specialized hepatocyte-like cells) and decreased AMPK activation. Remarkably, in humans, we show that both obese and insulin-resistant subjects have elevated plasma concentrations of pro-NT, and in longitudinal studies among non-obese subjects, high levels of pro-NT denote a doubling of the risk of developing obesity later in life. Our findings directly link NT with increased fat absorption and obesity and suggest that NT may provide a prognostic marker of future obesity and a potential target for prevention and treatment.

An important component of this methodology is to assess the role of the tumor microenvironment on tumor growth and survival. To tackle this problem, we have adapted the original approach of Warburg 1 , by combining thin tissue slices with Stable Isotope Resolved Metabolomics (SIRM) to determine detailed metabolic activity of human tissues. SIRM enables the tracing of metabolic transformations of source molecules such as glucose or glutamine over defined time periods, and is a requirement for detailed pathway tracing and flux analysis. In our approach, we maintain freshly resected tissue slices (both cancerous and non- cancerous from the same organ of the same subject) in cell culture media, and treat with appropriate stable isotope-enriched nutrients, e.g. 13 C 6 -glucose or 13 C 5 , 15 N 2 -glutamine. These slices are viable for at least 24 h, and make it possible to eliminate systemic influence on the target tissue metabolism while maintaining the original 3D cellular architecture. It is therefore an excellent pre-clinical platform for assessing the effect of therapeutic agents on target tissue metabolism and their therapeutic efficacy on individual patients 2,3 .

Tumor-associated macrophages (TAM) with an alternatively activated phenotype have been linked to tumor-elicited inflammation, immunosuppression, and resistance to chemotherapies in cancer, thus representing an attractive target for an effective cancer immunotherapy. In this study, we demonstrate that particulate yeast-derived β-glucan, a natural polysaccharide compound, converts polarized alternatively activated macrophages or immunosuppressive TAM into a classically activated phenotype with potent immunostimulating activity. This process is associated with macrophage metabolic reprograming with enhanced glycolysis, Krebs cycle, and glutamine utilization. In addition, particulate β-glucan converts immunosuppressive TAM via the C-type lectin receptor dectin-1-induced spleen tyrosine kinase-Card9-Erk pathway. Further in vivo studies show that oral particulate β-glucan treatment significantly delays tumor growth, which is associated with in vivo TAM phenotype conversion and enhanced effector T cell activation. Mice injected with particulate β-glucan-treated TAM mixed with tumor cells have significantly reduced tumor burden with less blood vascular vessels compared with those with TAM plus tumor cell injection. In addition, macrophage depletion significantly reduced the therapeutic efficacy of particulate β-glucan in tumor-bearing mice. These findings have established a new paradigm for macrophage polarization and immunosuppressive TAM conversion and shed light on the action mode of β-glucan treatment in cancer., (Copyright © 2015 by The American Association of Immunologists, Inc.)

NMR spectra of mixtures of metabolites extracted from cells or tissues are extremely complex, reflecting the large number of compounds that are present over a wide range of concentrations. Although multidimensional NMR can greatly improve resolution as well as improve reliability of compound assignments, lower abundance metabolites often remain hidden. We have developed a carbonyl-selective aminooxy probe that specifically reacts with free keto and aldehyde functions, but not carboxylates. By incorporating (15)N in the aminooxy functional group, (15)N-edited NMR was used to select exclusively those metabolites that contain a free carbonyl function while all other metabolites are rejected. Here, we demonstrate that the chemical shifts of the aminooxy adducts of ketones and aldehydes are very different, which can be used to discriminate between aldoses and ketoses, for example. Utilizing the 2-bond or 3-bond (15)N-(1)H couplings, the (15)N-edited NMR analysis was optimized first with authentic standards and then applied to an extract of the lung adenocarcinoma cell line A549. More than 30 carbonyl-containing compounds at NMR-detectable levels, six of which we have assigned by reference to our database. As the aminooxy probe contains a permanently charged quaternary ammonium group, the adducts are also optimized for detection by mass spectrometry. Thus, this sample preparation technique provides a better link between the two structural determination tools, thereby paving the way to faster and more reliable identification of both known and unknown metabolites directly in crude biological extracts., (Copyright © 2015 John Wiley & Sons, Ltd.)

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.