Stable isotope resolved metabolomics of lung cancer in a SCID mouse model

Metabolomics changes after exercise intervention reveal potential peripheral biomarkers in repeated methamphetamine exposure

Methamphetamine (MA) use disorder has become a global public health problem, and the peripheral mechanisms underlying exercise as a potential treatment for MA addiction are still not fully understood. This study aims to identify a plasma metabolic biomarker in MA-administered mice under exercise interventions. The peripheral plasma metabolic profiles of C57BL/6 J mice were quantified by ultra-high-performance liquid chromatography and tandem mass spectrometry metabolomics methods. The mice were randomized into saline control (C), MA model control (NE-MA) and MA model exercise intervention (E-MA) groups, and a conditioned place preference paradigm was used to assess drug reward. Anxiety-like behavior and cognitive behavior was evaluated using the open field and Y-maze tests. A total of 35 differential metabolites effectively distinguished between NE-MA and C groups. These metabolites are mainly involved in membrane lipid, energy, and amino acid metabolism. Compared with the NE-MA group, the expression of five reward-related metabolites in the E-MA group was reversed: l-tryptophan, niacinamide, uridine, 2'-deoxyuridine, and uric acid, which are involved in amino acid, energy, purine, and pyrimidine metabolism. Upregulation in uric acid and l-tryptophan levels was associated with improved anxiety-like behavior and cognitive function after exercise intervention. These metabolites may serve as markers of exercise intervention in MA addiction and deserve further study.

Metabolic Reprogramming in Human Cancer Patients and Patient-Derived Models

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.

How Early Can Pancreatic Tumors Be Detected Using NMR-Based Urine Metabolic Profiling? Identification of Early-Stage Biomarkers of Tumor Initiation and Progression in an Orthotopic Xenograft Mouse Model of Pancreatic Cancer

Background: Pancreatic cancer is the most lethal of all human cancers. The disease has no obvious symptoms in its early stages and in the majority of cases, the cancer goes undetected until it has advanced to the point that surgery is no longer a viable option or until it has metastasized to other organs. The absence of reliable and sensitive biomarkers for the early detection of pancreatic cancer contributes to the poor ability to detect the disease before it progresses to an untreatable stage. Objectives: Here, an orthotopic xenograft mouse model of pancreatic cancer was investigated to determine if urinary metabolic biomarkers could be identified and used to detect the early formation of pancreatic tumors. Methods: The orthotopic xenograft mouse model of pancreatic cancer was established by injecting human MiaPaCa-2 cells, derived from a male patient aged 65 years with pancreatic adenocarcinoma, into the pancreata of severe combined immunodeficient mice. Orthotopic pancreatic tumors, allowed to grow for eight weeks, were successfully established in the pancreata in 15 out of 20 mice. At the time of sacrifice, tumors were excised and histologically analyzed and the masses and volumes recorded. Urine samples were collected prior to injection, at one-week post injection, and every two weeks afterwards for eight weeks. Results: NMR-based metabolic profiling of the urine samples indicated that 31 metabolites changed significantly over the course of tumor initiation and growth. Longitudinal metabolic profiling analysis indicated an initial increase in activity of the metabolic pathways involved in energy production and/or cell synthesis by cancer cells as required to support tumor growth that was followed by a diminished difference between control and orthotopic mice associated with tumor senescence as the tumors reached 7-8 weeks post injection. Conclusions: The results indicate that NMR-based urinary metabolic profiling may be able to detect the earliest stages of pancreatic tumor initiation and growth, highlighting the potential for translation to human clinical studies.

NMR-Based Stable Isotope Tracing of Cancer Metabolism

NMR is widely used for metabolite profiling (metabolomics, metabonomics) particularly of various readily obtainable biofluids such as plasma and urine. It is especially valuable for stable isotope tracer studies to track metabolic pathways under control or perturbed conditions in a wide range of cell models as well as animal models and human subjects. NMR has unique properties for utilizing stable isotopes to edit or simplify otherwise complex spectra acquired in vitro and in vivo, while quantifying the level of enrichment at specific atomic positions in various metabolites (i.e., isotopomer distribution analysis).In this protocol, we give an overview with specific protocols for NMR-based stable isotope-resolved metabolomics, or SIRM, with a workflow from administration of isotope-enriched precursors, via sample preparation through to NMR data collection and reduction. We focus on indirect detection of common NMR-active stable isotopes including 13C, 15N, 31P, and 2H, using a variety of 1H-based two-dimensional experiments. We also include the application and analyses of multiplex tracer experiments.

Nanoparticle-based itaconate treatment recapitulates low-cholesterol/low-fat diet-induced atherosclerotic plaque resolution

Current pharmacologic treatments for atherosclerosis do not completely protect patients; additional protection can be achieved by dietary modifications, such as a low-cholesterol/low-fat diet (LCLFD), that mediate plaque stabilization and inflammation reduction. However, this lifestyle modification can be challenging for patients. Unfortunately, incomplete understanding of the underlying mechanisms has thwarted efforts to mimic the protective effects of a LCLFD. Here, we report that the tricarboxylic acid cycle intermediate itaconate (ITA), produced by plaque macrophages, is key to diet-induced plaque resolution. ITA is produced by immunoresponsive gene 1 (IRG1), which we observe is highly elevated in myeloid cells of vulnerable plaques and absent from early or stable plaques in mice and humans. We additionally report development of an ITA-conjugated lipid nanoparticle that accumulates in plaque and bone marrow myeloid cells, epigenetically reduces inflammation via H3K27ac deacetylation, and reproduces the therapeutic effects of LCLFD-induced plaque resolution in multiple atherosclerosis models.

Stable isotope-resolved metabolomics analyses of metabolic phenotypes reveal variable glutamine metabolism in different patient-derived models of non-small cell lung cancer from a single patient

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 (NSCLC1) 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 13C6-glucose and 13C5,15N2-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.

Challenges of Spatially Resolved Metabolism in Cancer Research

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.

Assessment of metabolic responses following silica nanoparticles in zebrafish models using 1H NMR analysis

Silica nanoparticles (SNPs) are widely explored as drug carriers, gene delivery vehicles, and as nanoparticles intended for bone and tissue engineering. SNPs are highly evident through various clinical trials for a wide range of biomedical applications. SNPs are biocompatible and promising nanoparticles for next-generation therapeutics. However, despite the well-established importance of SNPs, metabolomics methods for the SNPs remain elusive which renders its maximal clinical translation. We applied 1H nuclear magnetic resonance (1H NMR) spectroscopy to investigate the metabolomics profile in Zebrafish (Danio rerio) exposed to SNPs. Zebrafish were exposed to the SNPs (10.0, 25.0, and 50.0 μg/mL) for 72 h and whole-body samples were subjected for targeted profiling. Pattern recognition of 1H NMR spectral data depicted alterations in the metabolomic profiles between control and SNPs exposed zebrafish. We found that tryptophane, lysine, methionine, phenylalanine, tyrosine, sn-glycero-3-phosphocholine (G3PC), and o-phosphocholine were decreased. The metabolic expression of niacinamide, nicotinamide adenine dinucleotide (NAD+), citrate, adenosine triphosphate (ATP), and xanthine were increased in zebrafish with SNPs treatment. We are report for the first time on metabolite alterations and phenotypic expression in zebrafish via 1H NMR. These results demonstrate that SNPs can adversely affect the significant metabolic pathways involved in energy, amino acids, cellular membrane, lipids, and fatty acid metabolisms. Metabolomics profiling may be able to detect metabolic dysregulation in SNPs-treated zebrafish and establish a foundation for further toxicological studies.

Cyclin D1 extensively reprograms metabolism to support biosynthetic pathways in hepatocytes

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.

Differential Inhibition of Anaplerotic Pyruvate Carboxylation and Glutaminolysis-Fueled Anabolism Underlies Distinct Toxicity of Selenium Agents in Human Lung Cancer

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 13C6-glucose and 13C5,15N2-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.

Bayesian kinetic modeling for tracer-based metabolomic data

BACKGROUND

Stable Isotope Resolved Metabolomics (SIRM) is a new biological approach that uses stable isotope tracers such as uniformly [Formula: see text]-enriched glucose ([Formula: see text]-Glc) to trace metabolic pathways or networks at the atomic level in complex biological systems. Non-steady-state kinetic modeling based on SIRM data uses sets of simultaneous ordinary differential equations (ODEs) to quantitatively characterize the dynamic behavior of metabolic networks. It has been increasingly used to understand the regulation of normal metabolism and dysregulation in the development of diseases. However, fitting a kinetic model is challenging because there are usually multiple sets of parameter values that fit the data equally well, especially for large-scale kinetic models. In addition, there is a lack of statistically rigorous methods to compare kinetic model parameters between different experimental groups.

RESULTS

We propose a new Bayesian statistical framework to enhance parameter estimation and hypothesis testing for non-steady-state kinetic modeling of SIRM data. For estimating kinetic model parameters, we leverage the prior distribution not only to allow incorporation of experts' knowledge but also to provide robust parameter estimation. We also introduce a shrinkage approach for borrowing information across the ensemble of metabolites to stably estimate the variance of an individual isotopomer. In addition, we use a component-wise adaptive Metropolis algorithm with delayed rejection to perform efficient Monte Carlo sampling of the posterior distribution over high-dimensional parameter space. For comparing kinetic model parameters between experimental groups, we propose a new reparameterization method that converts the complex hypothesis testing problem into a more tractable parameter estimation problem. We also propose an inference procedure based on credible interval and credible value. Our method is freely available for academic use at https://github.com/xuzhang0131/MCMCFlux .

CONCLUSIONS

Our new Bayesian framework provides robust estimation of kinetic model parameters and enables rigorous comparison of model parameters between experimental groups. Simulation studies and application to a lung cancer study demonstrate that our framework performs well for non-steady-state kinetic modeling of SIRM data.

Ultrahigh resolution MS1/MS2-based reconstruction of metabolic networks in mammalian cells reveals changes for selenite and arsenite action

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-MS1/data independent-MS2 method to track the simultaneous incorporation of the heavy isotopes 13C and 15N into the moieties of purine/pyrimidine nucleotides in mammalian cells. Ultrahigh resolution-MS1 resolves and counts multiple tracer atoms in intact metabolites, while data independent-tandem MS (MS2) 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 [13C6]-glucose in 3D A549 spheroids in response to the anticancer agent selenite and that of [13C5,15N2]-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.

13C tracer analysis suggests extensive recycling of endogenous CO2 in vivo

Background

¹³C tracer analysis is increasingly used to monitor cellular metabolism in vivo and in intact cells, but data interpretation is still the key element to unveil the complexity of metabolic activities. The distinct ¹³C labeling patterns (e.g., M + 1 species in vivo but not in vitro) of metabolites from [U-¹³C]-glucose or [U-¹³C]-glutamine tracing in vivo and in vitro have been previously reported by multiple groups. However, the reason for the difference in the M + 1 species between in vivo and in vitro experiments remains poorly understood.

Methods

We have performed [U-¹³C]-glucose and [U-¹³C]-glutamine tracing in sarcoma-bearing mice (in vivo) and in cancer cell lines (in vitro). ¹³C enrichment of metabolites in cultured cells and tissues was determined by LC coupled with high-resolution mass spectrometry (LC-HRMS). All p-values are obtained from the Student’s t-test two-tailed using GraphPad Prism 8 unless otherwise noted.

Results

We observed distinct enrichment patterns of tricarboxylic acid cycle intermediates in vivo and in vitro. As expected, citrate M + 2 or M + 4 was the dominant mass isotopologue in vitro. However, citrate M + 1 was unexpectedly the dominant isotopologue in mice receiving [U-¹³C]-glucose or [U-¹³C]-glutamine infusion, but not in cultured cells. Our results are consistent with a model where the difference in M + 1 species is due to the different sources of CO₂ in vivo and in vitro, which was largely overlooked in the past. In addition, a time course study shows the generation of high abundance citrate M + 1 in plasma of mice as early as few minutes after [U-¹³C]-glucose infusion.

Conclusions

Altogether, our results show that recycling of endogenous CO₂ is substantial in vivo. The production and recycling of ¹³CO₂ from the decarboxylation of [U-¹³C]-glucose or [U-¹³C]-glutamine is negligible in vitro partially due to dilution by the exogenous HCO₃⁻/CO₂ source, but in vivo incorporation of endogenous ¹³CO₂ into M + 1 metabolites is substantial and should be considered. These findings provide a new paradigm to understand carbon atom transformations in vivo and should be taken into account when developing mathematical models to better reflect carbon flux.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40170-022-00287-8.

Metabolomics Work Flow and Analytics in Systems Biology

Metabolomics is an omics approach of systems biology that involves the development and assessment of large-scale, comprehensive biochemical analysis tools for metabolites in biological systems. This review describes the metabolomics workflow and provides an overview of current analytic tools used for the quantification of metabolic profiles. We explain analytic tools such as mass spectrometry (MS), nuclear magnetic resonance (NMR) spectroscopy, ionization techniques, and approaches for data extraction and analysis.

Targeted Oral Delivery of Paclitaxel Using Colostrum-Derived Exosomes

Simple Summary

Paclitaxel (PAC) is a widely used antitumor agent in the treatment of various early-stage and advanced cancers, including lung cancer. While efficacious, solvent-based PAC generally is not well tolerated and is associated with severe side effects. To overcome such limitations, naturally occurring nanocarriers such as exosomes are attracting great interest. In this paper, we show that tumor-targeted oral formulation of PAC, using bovine colostrum-derived exosomes, not only enhance therapeutic efficacy against orthotopic lung cancer but also mitigate or eliminate systemic and immunotoxicity of the conventional i.v. dosing. These data will leverage the advantages of bovine colostrum exosomes to advance the exosome-mediated targeted oral delivery of PAC as a therapeutic alternative to current therapies.

Abstract

Lung cancer is the leading cause of cancer-related deaths worldwide. Non-small-cell lung cancer (NSCLC) is the most common type accounting for 84% of all lung cancers. Paclitaxel (PAC) is a widely used drug in the treatment of a broad spectrum of human cancers, including lung. While efficacious, PAC generally is not well tolerated and its limitations include low aqueous solubility, and significant toxicity. To overcome the dose-related toxicity of solvent-based PAC, we utilized bovine colostrum-derived exosomes as a delivery vehicle for PAC for the treatment of lung cancer. Colostrum provided higher yield of exosomes and could be loaded with higher amount of PAC compared to mature milk. Exosomal formulation of PAC (ExoPAC) showed higher antiproliferative activity and inhibition of colony formation against A549 cells compared with PAC alone, and also showed antiproliferative activity against a drug-resistant variant of A549. To further enhance its efficacy, exosomes were attached with a tumor-targeting ligand, folic acid (FA). FA-ExoPAC given orally showed significant inhibition (>50%) of subcutaneous tumor xenograft while similar doses of PAC showed insignificant inhibition. In the orthotopic lung cancer model, oral dosing of FA-ExoPAC achieved greater efficacy (55% growth inhibition) than traditional i.v. PAC (24–32% growth inhibition) and similar efficacy as i.v. Abraxane (59% growth inhibition). The FA-ExoPAC given i.v. exceeded the therapeutic efficacy of Abraxane (76% growth inhibition). Finally, wild-type animals treated with p.o. ExoPAC did not show gross, systemic or immunotoxicity. Solvent-based PAC caused immunotoxicity which was either reduced or completely mitigated by its exosomal formulations. These studies show that a tumor-targeted oral formulation of PAC (FA-ExoPAC) significantly improved the overall efficacy and safety profile while providing a user-friendly, cost-effective alternative to bolus i.v. PAC and i.v. Abraxane.

NMR Analysis of Carboxylate Isotopomers of 13C-Metabolites by Chemoselective Derivatization with 15N-Cholamine

A substantial fraction of common metabolites contains carboxyl functional groups. Their ¹³C isotopomer analysis by nuclear magnetic resonance (NMR) is hampered by the low sensitivity of the ¹³C nucleus, the slow longitudinal relaxation for the lack of an attached proton, and the relatively low chemical shift dispersion of carboxylates. Chemoselective (CS) derivatization is a means of tagging compounds in a complex mixture via a specific functional group. ¹⁵N₁-cholamine has been shown to be a useful CS agent for carboxylates, producing a peptide bond that can be detected via ¹⁵N-attached H with high sensitivity in heteronuclear single quantum coherence experiments. Here, we report an improved method of derivatization and show how ¹³C-enrichment at the carboxylate and/or the adjacent carbon can be determined via one- and two-bond coupling of the carbons adjacent to the cholamine ¹⁵N atom in the derivatives. We have applied this method for the determination of ¹³C isotopomer distribution in the extracts of A549 cell culture and liver tissue from a patient-derived xenograft mouse.

NMR Methods for Determining Lipid Turnover via Stable Isotope Resolved Metabolomics

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 13C6 glucose and 13C5 glutamine tracers.

Exosome-mediated delivery of RNA and DNA for gene therapy

Gene therapy promises to revolutionize biomedicine and personalized medicine by modulating or compensating the expression of abnormal genes. The biggest obstacle for clinical application is the lack of an effective, non-immunogenic delivery system. We show that bovine colostrum exosomes and polyethyleneimine matrix (EPM) delivers short interfering RNA (siRNA) or plasmid DNA (pDNA) for effective gene therapy. KRAS, a therapeutic focus for many cancers, was targeted by EPM-delivered KRAS siRNA (siKRAS) and inhibited lung tumor growth (>70%) and reduced KRAS expression (50%-80%). Aberrant p53 is another therapeutic focus for many cancers. EPM-mediated introduction of wild-type (WT) p53 pDNA (pcDNA-p53) resulted in p53 expression in p53-null H1299 cells in culture, subcutaneous lung tumor, and tissues of p53-knockout mice. Additionally, chemo-sensitizing effects of paclitaxel were restored by exogenous WT p53 in lung cancer cells. Together, this novel EPM technology represents an effective 'platform' for delivery of therapeutic nucleic acids to treat human disease.

An Ion Chromatography-Ultrahigh-Resolution-MS1/Data-Independent High-Resolution MS2 Method for Stable Isotope-Resolved Metabolomics Reconstruction of Central Metabolic Networks

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-MS¹ 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-MS¹ with its long acquisition time, while acquiring MS² data on many coeluting labeled isotopologues for each metabolite. We have developed an ion chromatography (IC)-UHR-MS¹/data-independent(DI)-HR-MS² method to trace the fate of ¹³C atoms from [¹³C₆]-glucose ([¹³C₆]-Glc) in 3D A549 spheroids in response to anticancer selenite and simultaneously ¹³C/¹⁵N atoms from [¹³C₅,¹⁵N₂]-glutamine ([¹³C₅,¹⁵N₂]-Gln) in 2D BEAS-2B cells in response to arsenite transformation. This method retains the complete isotopologue distributions of metabolites via UHR-MS¹ while simultaneously acquiring substructure label information via DI-MS². 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.

NMR-Based Metabolomics

Nuclear magnetic resonance (NMR) spectroscopy is a major analytical method used in the growing field of metabolomics. Although NMR is relatively less sensitive than mass spectrometry, this analytical platform has numerous characteristics including its high reproducibility and quantitative abilities, its nonselective and noninvasive nature, and the ability to identify unknown metabolites in complex mixtures and trace the downstream products of isotope labeled substrates ex vivo, in vivo, or in vitro. Metabolomic analysis of highly complex biological mixtures has benefitted from the advances in both NMR data acquisition and analysis methods. Although metabolomics applications span a wide range of disciplines, a majority has focused on understanding, preventing, diagnosing, and managing human diseases. This chapter describes NMR-based methods relevant to the rapidly expanding metabolomics field.

Chronic cold exposure enhances glucose oxidation in brown adipose tissue

The cultured brown adipocytes can oxidize glucose in vitro, but it is still not fully clear whether brown adipose tissue (BAT) could completely oxidize glucose in vivo. Although positron emission tomography (PET) with ¹⁸F‐fluorodeoxyglucose (¹⁸F‐FDG) showed a high level of glucose uptake in the activated BAT, the non‐metabolizable ¹⁸F‐FDG cannot fully demonstrate intracellular glucose metabolism. Through in vivo [U‐¹³C]glucose tracing, here we show that chronic cold exposure dramatically activates glucose oxidation in BAT and the browning/beiging subcutaneous white adipose tissue (sWAT). Specifically, chronic cold exposure enhances glucose flux into the mitochondrial TCA cycle. Metabolic flux analysis models that β3‐adrenergic receptor (β3‐AR) agonist significantly enhances the flux of mitochondrial pyruvate uptake through mitochondrial pyruvate carrier (MPC) in the differentiated primary brown adipocytes. Furthermore, in vivo MPC inhibition blocks cold‐induced glucose oxidation and impairs body temperature maintenance in mice. Together, mitochondrial pyruvate uptake and oxidation serve an important energy source in the chronic cold exposure activated BAT and beige adipose tissue, which supports a role for glucose oxidation in brown fat thermogenesis.

Fumarate hydratase-deficient renal cell carcinoma cells respond to asparagine by activation of the unfolded protein response and stimulation of the hexosamine biosynthetic pathway

Background

The loss-of-function mutation of fumarate hydratase (FH) is a driver of hereditary leiomyomatosis and renal cell carcinoma (HLRCC). Fumarate accumulation results in activation of stress-related mechanisms leading to upregulation of cell survival-related genes. To better understand how cells compensate for the loss of FH in HLRCC, we determined the amino acid nutrient requirements of the FH-deficient UOK262 cell line (UOK262) and its FH-repleted control (UOK262WT).

Methods

We determined growth rates and survival of cell lines in response to amino acid depletion and supplementation. RNAseq was used to determine the transcription changes contingent on Asn and Gln supplementation, which was further followed with stable isotope resolved metabolomics (SIRM) using both [U- ¹³C,¹⁵N] Gln and Asn.

Results

We found that Asn increased the growth rate of both cell lines in vitro. Gln, but not Asn, increased oxygen consumption rates and glycolytic reserve of both cell lines. Although Asn was taken up by the cells, there was little evidence of Asn-derived label in cellular metabolites, indicating that Asn was not catabolized. However, Asn strongly stimulated Gln labeling of uracil and precursors, uridine phosphates and hexosamine metabolites in the UOK262 cells and to a much lesser extent in the UOK262WT cells, indicating an activation of the hexosamine biosynthetic pathway (HBP) by Asn. Asn in combination with Gln, but not Asn or Gln alone, stimulated expression of genes associated with the endoplasmic reticulum (ER) stress and the unfolded protein response (UPR) in UOK262 to a greater extent than in FH-restored cells. The changes in expression of these genes were confirmed by RT-PCR, and the stimulation of the UPR was confirmed orthogonally by demonstration of an increase in spliced XBP1 (sXBP1) in UOK262 cells under these conditions. Asn exposure also increased both the RNA and protein expression of the HBP regulator GFPT2, which is a transcriptional target of sXBP1.

Conclusions

Asn in the presence of Gln induces an ER stress response in FH-deficient UOK262 cells and stimulates increased synthesis of UDP-acetyl glycans indicative of HBP activity. These data demonstrate a novel effect of asparagine on cellular metabolism in FH-deficient cells that could be exploited therapeutically.

Loss of CLN3, the gene mutated in juvenile neuronal ceroid lipofuscinosis, leads to metabolic impairment and autophagy induction in retinal pigment epithelium

Juvenile neuronal ceroid lipofuscinosis (JNCL, aka. juvenile Batten disease or CLN3 disease) is a lysosomal storage disease characterized by progressive blindness, seizures, cognitive and motor failures, and premature death. JNCL is caused by mutations in the Ceroid Lipofuscinosis, Neuronal 3 (CLN3) gene, whose function is unclear. Although traditionally considered a neurodegenerative disease, CLN3 disease displays eye-specific effects: Vision loss not only is often one of the earliest symptoms of JNCL, but also has been reported in non-syndromic CLN3 disease. Here we described the roles of CLN3 protein in maintaining healthy retinal pigment epithelium (RPE) and normal vision. Using electroretinogram, fundoscopy and microscopy, we showed impaired visual function, retinal autofluorescent lesions, and RPE disintegration and metaplasia/hyperplasia in a Cln3 ~ 1 kb-deletion mouse model [1] on C57BL/6J background. Utilizing a combination of biochemical analyses, RNA-Seq, Seahorse XF bioenergetic analysis, and Stable Isotope Resolved Metabolomics (SIRM), we further demonstrated that loss of CLN3 increased autophagic flux, suppressed mTORC1 and Akt activities, enhanced AMPK activity, and up-regulated gene expression of the autophagy-lysosomal system in RPE-1 cells, suggesting autophagy induction. This CLN3 deficiency induced autophagy induction coincided with decreased mitochondrial oxygen consumption, glycolysis, the tricarboxylic acid (TCA) cycle, and ATP production. We also reported for the first time that loss of CLN3 led to glycogen accumulation despite of impaired glycogen synthesis. Our comprehensive analyses shed light on how loss of CLN3 affect autophagy and metabolism. This work suggests possible links among metabolic impairment, autophagy induction and lysosomal storage, as well as between RPE atrophy/degeneration and vision loss in JNCL.

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.

Applications of Chromatography-Ultra High-Resolution MS for Stable Isotope-Resolved Metabolomics (SIRM) Reconstruction of Metabolic Networks

Metabolism is a complex network of compartmentalized and coupled chemical reactions, which often involve transfers of substructures of biomolecules, thus requiring metabolite substructures to be tracked. Stable isotope resolved metabolomics (SIRM) enables pathways reconstruction, even among chemically identical metabolites, by tracking the provenance of stable isotope-labeled substructures 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, MS2 is difficult to implement with chromatography-based UHR-MS due to lengthy MS1 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.

Loss of Rb1 Enhances Glycolytic Metabolism in Kras-Driven Lung Tumors In Vivo

Dysregulated metabolism is a hallmark of cancer cells and is driven in part by specific genetic alterations in various oncogenes or tumor suppressors. The retinoblastoma protein (pRb) is a tumor suppressor that canonically regulates cell cycle progression; however, recent studies have highlighted a functional role for pRb in controlling cellular metabolism. Here, we report that loss of the gene encoding pRb (Rb1) in a transgenic mutant Kras-driven model of lung cancer results in metabolic reprogramming. Our tracer studies using bolus dosing of [U-¹³C]-glucose revealed an increase in glucose carbon incorporation into select glycolytic intermediates. Consistent with this result, Rb1-depleted tumors exhibited increased expression of key glycolytic enzymes. Interestingly, loss of Rb1 did not alter mitochondrial pyruvate oxidation compared to lung tumors with intact Rb1. Additional tracer studies using [U-¹³C,¹⁵N]-glutamine and [U-¹³C]-lactate demonstrated that loss of Rb1 did not alter glutaminolysis or utilization of circulating lactate within the tricarboxylic acid cycle (TCA) in vivo. Taken together, these data suggest that the loss of Rb1 promotes a glycolytic phenotype, while not altering pyruvate oxidative metabolism or glutamine anaplerosis in Kras-driven lung tumors.

APOE alters glucose flux through central carbon pathways in astrocytes

The Apolipoprotein E (APOE) gene is a major genetic risk factor associated with Alzheimer's disease (AD). APOE encodes for three main isoforms in humans (E2, E3, and E4). Homozygous E4 individuals have more than a 10-fold higher risk for developing late-onset AD, while E2 carriers are protected. A hallmark of AD is a reduction in cerebral glucose metabolism, alluding to a strong metabolic component in disease onset and progression. Interestingly, E4 individuals display a similar regional pattern of cerebral glucose hypometabolism decades prior to disease onset. Mapping this metabolic landscape may help elucidate the underlying biological mechanism of APOE-associated risk for AD. Efficient metabolic coupling of neurons and glia is necessary for proper neuronal function, and disruption in glial energy distribution has been proposed to contribute to neuronal cell death and AD pathology. One important function of astrocytes - canonically the primary source of apolipoprotein E in the brain - is to provide metabolic substrates (lactate, lipids, amino acids and neurotransmitters) to neurons. Here we investigate the effects of APOE on astrocyte glucose metabolism in vitro utilizing scintillation proximity assays, stable isotope tracer metabolomics, and gene expression analyses. Glucose uptake is impaired in E4 astrocytes relative to E2 or E3 with specific alterations in central carbon metabolism. Using stable isotope labeled glucose [U-¹³C] allowed analyses of astrocyte-specific deep metabolic networks affected by APOE, and provided insight to the effects downstream of glucose uptake. Enrichment of ¹³C in early steps of glycolysis was lowest in E4 astrocytes (highest in E2), while synthesis of lactate from glucose was highest in E4 astrocytes (lowest in E2). We observed an increase in glucose flux through the pentose phosphate pathway (PPP), with downstream increases in gluconeogenesis, lipid, and de novo nucleotide biosynthesis in E4 astrocytes. There was also a marked increase in ¹³C enrichment in the TCA cycle of E4 astrocytes - whose substrates were also incorporated into biosynthetic pathways at a higher rate. Pyruvate carboxylase (PC) and pyruvate dehydrogenase (PDH) are the two main enzymes controlling pyruvate entry to the TCA cycle. PC gene expression is increased in E4 astrocytes and the activity relative to PDH was also increased, compared to E2 or E3. Decreased enrichment in the TCA cycle of E2 and E3 astrocytes is suggestive of increased oxidation and non-glucose derived anaplerosis, which could be fueling mitochondrial ATP production. Conversely, E4 astrocytes appear to increase carbon flux into the TCA cycle to fuel cataplerosis. Together, these data demonstrate clear APOE isoform-specific effects on glucose utilization in astrocytes, including E4-associated increases in lactate synthesis, PPP flux, and de novo biosynthesis pathways.

Software Supporting a Workflow of Quantitative Dynamic Flux Maps Estimation in Central Metabolism from SIRM Experimental Data

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.

Air pollution-derived particulate matter dysregulates hepatic Krebs cycle, glucose and lipid metabolism in mice

Exposure to ambient air particulate matter (PM2.5) is well established as a risk factor for cardiovascular and pulmonary disease. Both epidemiologic and controlled exposure studies in humans and animals have demonstrated an association between air pollution exposure and metabolic disorders such as diabetes. Given the central role of the liver in peripheral glucose homeostasis, we exposed mice to filtered air or PM2.5 for 16 weeks and examined its effect on hepatic metabolic pathways using stable isotope resolved metabolomics (SIRM) following a bolus of 13C6-glucose. Livers were analyzed for the incorporation of 13C into different metabolic pools by IC-FTMS or GC-MS. The relative abundance of 13C-glycolytic intermediates was reduced, suggesting attenuated glycolysis, a feature found in diabetes. Decreased 13C-Krebs cycle intermediates suggested that PM2.5 exposure led to a reduction in the Krebs cycle capacity. In contrast to decreased glycolysis, we observed an increase in the oxidative branch of the pentose phosphate pathway and 13C incorporations suggestive of enhanced capacity for the de novo synthesis of fatty acids. To our knowledge, this is one of the first studies to examine 13C6-glucose utilization in the liver following PM2.5 exposure, prior to the onset of insulin resistance (IR).

Challenges and Opportunities in Cancer Metabolomics

Challenges in metabolomics for a given spectrum of disease are more or less comparable, ranging from the accurate measurement of metabolite abundance, compound annotation, identification of unknown constituents, and interpretation of untargeted and analysis of high throughput targeted metabolomics data leading to the identification of biomarkers. However, metabolomics approaches in cancer studies specifically suffer from several additional challenges and require robust ways to sample the cells and tissues in order to tackle the constantly evolving cancer landscape. These constraints include, but are not limited to, discriminating the signals from given cell types and those that are cancer specific, discerning signals that are systemic and confounded, cell culture-based challenges associated with cell line identities and media standardizations, the need to look beyond Warburg effects, citrate cycle, lactate metabolism, and identifying and developing technologies to precisely and effectively sample and profile the heterogeneous tumor environment. This review article discusses some of the current and pertinent hurdles in cancer metabolomics studies. In addition, it addresses some of the most recent and exciting developments in metabolomics that may address some of these issues. The aim of this article is to update the oncometabolomics research community about the challenges and potential solutions to these issues.

Quantification of Isotopologues of Amino Acids by Multiplexed Stable Isotope-Resolved Metabolomics Using Ultrahigh-Resolution Mass Spectrometry Coupled with Direct Infusion

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.

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 Metabolomic Differences between Hormone-Responsive and Triple-Negative Breast Cancer Cell Lines

Purpose

To conduct an exploratory study to identify mechanisms that differentiate Luminal A (BT474 and MCF-7) and triple-negative (MDA-MB-231 and MDA-MB-468) breast cancer (BCa) cell lines to potentially provide novel therapeutic targets based on differences in energy utilization.

Methods

Cells were cultured in media containing either [U-¹³C]-glucose or [U-¹³C]-glutamine for 48 hours. Conditioned media and cellular extracts were analyzed by ¹H and ¹³C NMR spectroscopy.

Results

MCF-7 cells consumed the most glucose, producing the most lactate, demonstrating the greatest Warburg effect-associated energy utilization. BT474 cells had the highest tricarboxylic acid cycle (TCA) activity. The majority of energy utilization patterns in MCF-7 cells were more similar to MDA-MB-468 cells, while the patterns for BT474 cells were more similar to MDA-MB-231 cells. Compared to the Luminal A cell lines, TNBC cell lines consumed more glutamine and less glucose. BT474 and MDA-MB-468 cells produced high amounts of ¹³C-glycine from media [U-¹³C]-glucose which was integrated into glutathione, indicating de novo synthesis.

Conclusions

Stable isotopic resolved metabolomics using ¹³C substrates provided mechanistic information about energy utilization that was difficult to interpret using ¹H data alone. Overall, cell lines that have different hormone receptor status have different energy utilization requirements, even if they are classified by the same clinical BCa subtype; and these differences offer clues about optimizing treatment strategies.

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.

A review of metabolism-associated biomarkers in lung cancer diagnosis and treatment

INTRODUCTION

Lung cancer continues to be the leading cause of cancer-related mortality worldwide. Early detection has proven essential to extend survival. Genomic and proteomic advances have provided impetus to the effort dedicated to detect and diagnose the disease at an earlier stage. Recently, the study of metabolites associated with tumor formation and progression has inaugurated the era of cancer metabolomics to aid in this effort.

OBJECTIVES

This review summarizes recent work regarding novel metabolites with the potential to serve as biomarkers for early lung tumor detection, evaluation of disease progression, and prediction of patient outcomes.

METHOD

We compare the metabolite profiling of cancer patients with that of healthy individuals, and the metabolites identified in tissue and biofluid samples and their usefulness as lung cancer biomarkers. We discuss metabolite alterations in tumor versus paired non-tumor lung tissues, as well as metabolite alterations in different stages of lung cancers and their usefulness as indicators of disease progression and overall survival. We evaluate metabolite dysregulation in different types of lung cancers, and those associated with lung cancer versus other lung diseases. We also examine metabolite differences between lung cancer patients and smokers/risk-factor individuals.

RESULT

Although an extensive list of metabolites has been evaluated to distinguish between these cases, refinement of methods is further required for adequate patient diagnosis.

CONCLUSION

We conclude that with technological advancement, metabolomics may be able to replace more invasive and costly diagnostic procedures while also providing the means to more effectively tailor treatment to patient-specific tumors.

Preclinical evaluation of novel fatty acid synthase inhibitors in primary colorectal cancer cells and a patient-derived xenograft model of colorectal cancer

Fatty Acid Synthase (FASN), a key enzyme of de novo lipogenesis, is upregulated in many cancers including colorectal cancer (CRC); increased FASN expression is associated with poor prognosis. Potent FASN inhibitors (TVBs) developed by 3-V Biosciences demonstrate anti-tumor activity in vitro and in vivo and a favorable tolerability profile in a Phase I clinical trial.

However, CRC characteristics associated with responsiveness to FASN inhibition are not fully understood. We evaluated the effect of TVB-3664 on tumor growth in nine CRC patient-derived xenografts (PDXs) and investigated molecular and metabolic changes associated with CRC responsiveness to FASN inhibition.

CRC cells and PDXs showed a wide range of sensitivity to FASN inhibition. TVB-3664 treatment showed significant response (reduced tumor volume) in 30% of cases. Anti-tumor effect of TVB-3664 was associated with a significant decrease in a pool of adenine nucleotides and alterations in lipid composition including a significant reduction in fatty acids and phospholipids and an increase in lactosylceramide and sphingomyelin in PDXs sensitive to FASN inhibition. Moreover, Akt, Erk1/2 and AMPK were major oncogenic pathways altered by TVBs.

In summary, we demonstrated that novel TVB inhibitors show anti-tumor activity in CRC and this activity is associated with a decrease in activation of Akt and Erk1/2 oncogenic pathways and significant alteration of lipid composition of tumors. Further understanding of genetic and metabolic characteristics of tumors susceptible to FASN inhibition may enable patient selection and personalized medicine approaches in CRC.

Current and future perspectives of functional metabolomics in disease studies-A review

Functional metabolomics is a new concept, which studies the functions of metabolites and related enzymes focused on metabolomics. It overcomes the shortcomings of traditional discovery metabolomics of mainly relying on literatures for biological interpretation. Functional metabolomics has many advantages. Firstly, the functional roles of metabolites and related metabolic enzymes are focused. Secondly, the in vivo and in vitro experiments are conducted to validate the metabolomics findings, therefore, increasing the reliability of metabolomics study and producing the new knowledge. Thirdly, functional metabolomics can be used by biologists to investigate functions of metabolites, and related genes and proteins. In this review, we summarize the analytical, biological and clinical platforms used in functional metabolomics studies. Recent progresses of functional metabolomics in cancer, metabolic diseases and biological phenotyping are reviewed, and future development is also predicted. Because of the tremendous advantages of functional metabolomics, it will have a bright future.

Non-invasive diagnosis of papillary thyroid microcarcinoma: a NMR-based metabolomics approach

Papillary thyroid microcarcinoma (PTMC) is a subtype of papillary thyroid carcinoma (PTC). Because its diameter is less than 10 mm, diagnosing it accurately is difficult with traditional methods such as image examinations and FNA (Fine Needle Aspiration). Investigating the metabolic changes induced by PTMC may enhance the understanding of its pathogenesis and provide important information for a new diagnosis method and treatment plan. In this study, high resolution magic angle spin (HRMAS) spectroscopy and ¹H-nuclear magnetic resonance (¹H-NMR) spectroscopy were used to screen metabolic changes in thyroid tissues and plasma from PTMC patients respectively. The results revealed reduced levels of fatty acids and elevated levels of several amino acids (phenylalanine, tyrosine, lactate, serine, cystine, lysine, glutamine/glutamate, taurine, leucine, alanine, isoleucine and valine) in thyroid tissues, as well as reduced levels of amino acids such as valine, tyrosine, proline, lysine, leucine and elevated levels of glucose, mannose, pyruvate and 3-hydroxybutyrate in plasma, are involved in the metabolic alterations in PTMC. In addition, a receiver operating characteristic (ROC) curve model for PTMC prediction was able to classify cases with good sensitivity and specificity using 9 significant changed metabolites in plasma. This work illustrates that the NMR-based metabolomics approach is capable of providing more sensitive diagnostic results and more systematic therapeutic information for PTMC.

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.

Nanoformulated copper/zinc superoxide dismutase exerts differential effects on glucose vs lipid homeostasis depending on the diet composition possibly via altered AMPK signaling

Evidence suggests that superoxide dismutase 1 (SOD1) promotes glucose vs lipid metabolism depending on the diet type. We recently reported that nanoformulated SOD1 (Nano) improved lipid metabolism without altering glucose homeostasis in high-fat (HF) diet-fed mice. Here, we sought to determine the effects and potential mechanisms of Nano in modulating glucose and lipid homeostasis in mice fed a normal chow diet (CD) vs HF diet. Mice were fed a CD or a HF diet (45%) for 10 wk and injected with Nano once every 2 days for 15 days. The fasting glucose level was lower (P < 0.05) in CD + Nano-treated mice compared to control. Conversely, blood glucose was not altered but serum triglycerides were lower in HF + Nano-treated mice. Genes involved in fatty acid synthesis were reduced by Nano in the skeletal muscle of CD but not of HF diet-fed mice. Adenosine monophosphate-activated protein kinase (AMPK), which promotes both glucose and lipid metabolism depending on the fuel availability, is activated by Nano in CD-fed mice. Moreover, Nano increased phosphorylation of ACC, a downstream target of AMPK, in both CD and HF diet-fed mice. Nano increased mitochondrial respiration in C2C12 myocytes in the presence of glucose or fatty acid, and this effect is inhibited by Compound C, an AMPK inhibitor. Our data suggest that Nano promotes glucose and lipid metabolism in CD and HF diet-fed mice, respectively, and this effect is mediated partly via AMPK signaling.

Probing the metabolic phenotype of breast cancer cells by multiple tracer stable isotope resolved metabolomics

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 13C6-glucose, 13C-1+2-glucose, 13C5,15N2-Gln, 13C3-glycerol, and 13C8-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.

Glucose Catabolism in Liver Tumors Induced by c-MYC Can Be Sustained by Various PKM1/PKM2 Ratios and Pyruvate Kinase Activities

Different pyruvate kinase isoforms are expressed in a tissue-specific manner, with pyruvate kinase M2 (PKM2) suggested to be the predominant isoform in proliferating cells and cancer cells. Because of differential regulation of enzymatic activities, PKM2, but not PKM1, has been thought to favor cell proliferation. However, the role of PKM2 in tumorigenesis has been recently challenged. Here we report that increased glucose catabolism through glycolysis and increased pyruvate kinase activity in c-MYC-driven liver tumors are associated with increased expression of both PKM1 and PKM2 isoforms and decreased expression of the liver-specific isoform of pyruvate kinase, PKL. Depletion of PKM2 at the time of c-MYC overexpression in murine livers did not affect c-MYC-induced tumorigenesis and resulted in liver tumor formation with decreased pyruvate kinase activity and decreased catabolism of glucose into alanine and the Krebs cycle. An increased PKM1/PKM2 ratio by ectopic PKM1 expression further decreased glucose flux into serine biosynthesis and increased flux into lactate and the Krebs cycle, resulting in reduced total levels of serine. However, these changes also did not affect c-MYC-induced liver tumor development. These results suggest that increased expression of PKM2 is not required to support c-MYC-induced tumorigenesis in the liver and that various PKM1/PKM2 ratios and pyruvate kinase activities can sustain glucose catabolism required for this process. Cancer Res; 77(16); 4355-64. ©2017 AACR.

Glycolytic reprogramming through PCK2 regulates tumor initiation of prostate cancer cells

Tumor-initiating cells (TICs) play important roles in tumor progression and metastasis. Identifying the factors regulating TICs may open new avenues in cancer therapy. Here, we show that TIC-enriched prostate cancer cell clones use more glucose and secrete more lactate than TIC-low clones. We determined that elevated levels of phosphoenolpyruvate carboxykinase isoform 2 (PCK2) are critical for the metabolic switch and the maintenance of TICs in prostate cancer. Information from prostate cancer patient databases revealed that higher PCK2 levels correlated with more aggressive tumors and lower survival rates. PCK2 knockdown resulted in low TIC numbers, increased cytosolic acetyl-CoA and cellular protein acetylation. Our data suggest PCK2 promotes tumor initiation by lowering acetyl-CoA level through reducing the mitochondrial tricarboxylic acid (TCA) cycle. Thus, PCK2 is a potential therapeutic target for aggressive prostate tumors.

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.

Snail reprograms glucose metabolism by repressing phosphofructokinase PFKP allowing cancer cell survival under metabolic stress

Dynamic regulation of glucose flux between aerobic glycolysis and the pentose phosphate pathway (PPP) during epithelial–mesenchymal transition (EMT) is not well-understood. Here we show that Snail (SNAI1), a key transcriptional repressor of EMT, regulates glucose flux toward PPP, allowing cancer cell survival under metabolic stress. Mechanistically, Snail regulates glycolytic activity via repression of phosphofructokinase, platelet (PFKP), a major isoform of cancer-specific phosphofructokinase-1 (PFK-1), an enzyme involving the first rate-limiting step of glycolysis. The suppression of PFKP switches the glucose flux towards PPP, generating NADPH with increased metabolites of oxidative PPP. Functionally, dynamic regulation of PFKP significantly potentiates cancer cell survival under metabolic stress and increases metastatic capacities in vivo. Further, knockdown of PFKP rescues metabolic reprogramming and cell death induced by loss of Snail. Thus, the Snail-PFKP axis plays an important role in cancer cell survival via regulation of glucose flux between glycolysis and PPP.

Cancer cell survival under metabolic stress is a critical step for metastasis. Here, the authors show that under glucose deprivation, Snail, a key regulator of the metastatic process, promotes survival by diverting glucose to the pentose phosphate pathway through repression of phosphofructokinase PFKP.

Hepatocellular carcinoma redirects to ketolysis for progression under nutrition deprivation stress

Cancer cells are known for their capacity to rewire metabolic pathways to support survival and proliferation under various stress conditions. Ketone bodies, though produced in the liver, are not consumed in normal adult liver cells. We find here that ketone catabolism or ketolysis is re-activated in hepatocellular carcinoma (HCC) cells under nutrition deprivation conditions. Mechanistically, 3-oxoacid CoA-transferase 1 (OXCT1), a rate-limiting ketolytic enzyme whose expression is suppressed in normal adult liver tissues, is re-induced by serum starvation-triggered mTORC2-AKT-SP1 signaling in HCC cells. Moreover, we observe that enhanced ketolysis in HCC is critical for repression of AMPK activation and protects HCC cells from excessive autophagy, thereby enhancing tumor growth. Importantly, analysis of clinical HCC samples reveals that increased OXCT1 expression predicts higher patient mortality. Taken together, we uncover here a novel metabolic adaptation by which nutrition-deprived HCC cells employ ketone bodies for energy supply and cancer progression.

Combination therapy with BPTES nanoparticles and metformin targets the metabolic heterogeneity of pancreatic cancer

Targeting glutamine metabolism via pharmacological inhibition of glutaminase has been translated into clinical trials as a novel cancer therapy, but available drugs lack optimal safety and efficacy. In this study, we used a proprietary emulsification process to encapsulate bis-2-(5-phenylacetamido-1,2,4-thiadiazol-2-yl)ethyl sulfide (BPTES), a selective but relatively insoluble glutaminase inhibitor, in nanoparticles. BPTES nanoparticles demonstrated improved pharmacokinetics and efficacy compared with unencapsulated BPTES. In addition, BPTES nanoparticles had no effect on the plasma levels of liver enzymes in contrast to CB-839, a glutaminase inhibitor that is currently in clinical trials. In a mouse model using orthotopic transplantation of patient-derived pancreatic tumor tissue, BPTES nanoparticle monotherapy led to modest antitumor effects. Using the HypoxCR reporter in vivo, we found that glutaminase inhibition reduced tumor growth by specifically targeting proliferating cancer cells but did not affect hypoxic, noncycling cells. Metabolomics analyses revealed that surviving tumor cells following glutaminase inhibition were reliant on glycolysis and glycogen synthesis. Based on these findings, metformin was selected for combination therapy with BPTES nanoparticles, which resulted in significantly greater pancreatic tumor reduction than either treatment alone. Thus, targeting of multiple metabolic pathways, including effective inhibition of glutaminase by nanoparticle drug delivery, holds promise as a novel therapy for pancreatic cancer.

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

BACKGROUND

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

RESULTS

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

CONCLUSIONS

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

Metabolomics Analysis of Hormone-Responsive and Triple-Negative Breast Cancer Cell Responses to Paclitaxel Identify Key Metabolic Differences

To date, no targeted therapies are available to treat triple negative breast cancer (TNBC), while other breast cancer subtypes are responsive to current therapeutic treatment. Metabolomics was conducted to reveal differences in two hormone receptor-negative TNBC cell lines and two hormone receptor-positive Luminal A cell lines. Studies were conducted in the presence and absence of paclitaxel (Taxol). TNBC cell lines had higher levels of amino acids, branched-chain amino acids, nucleotides, and nucleotide sugars and lower levels of proliferation-related metabolites like choline compared with Luminal A cell lines. In the presence of paclitaxel, each cell line showed unique metabolic responses, with some similarities by type. For example, in the Luminal A cell lines, levels of lactate and creatine decreased while certain choline metabolites and myo-inositol increased with paclitaxel. In the TNBC cell lines levels of glutamine, glutamate, and glutathione increased, whereas lysine, proline, and valine decreased in the presence of drug. Profiling secreted inflammatory cytokines in the conditioned media demonstrated a greater response to paclitaxel in the hormone-positive Luminal cells compared with a secretion profile that suggested greater drug resistance in the TNBC cells. The most significant differences distinguishing the cell types based on pathway enrichment analyses were related to amino acid, lipid and carbohydrate metabolism pathways, whereas several biological pathways were differentiated between the cell lines following treatment.

High-mass-resolution MALDI mass spectrometry imaging of metabolites from formalin-fixed paraffin-embedded tissue

Formalin-fixed and paraffin-embedded (FFPE) tissue specimens are the gold standard for histological examination, and they provide valuable molecular information in tissue-based research. Metabolite assessment from archived tissue samples has not been extensively conducted because of a lack of appropriate protocols and concerns about changes in metabolite content or chemical state due to tissue processing. We present a protocol for the in situ analysis of metabolite content from FFPE samples using a high-mass-resolution matrix-assisted laser desorption/ionization fourier-transform ion cyclotron resonance mass spectrometry imaging (MALDI-FT-ICR-MSI) platform. The method involves FFPE tissue sections that undergo deparaffinization and matrix coating by 9-aminoacridine before MALDI-MSI. Using this platform, we previously detected ∼1,500 m/z species in the mass range m/z 50-1,000 in FFPE samples; the overlap compared with fresh frozen samples is 72% of m/z species, indicating that metabolites are largely conserved in FFPE tissue samples. This protocol can be reproducibly performed on FFPE tissues, including small samples such as tissue microarrays and biopsies. The procedure can be completed in a day, depending on the size of the sample measured and raster size used. Advantages of this approach include easy sample handling, reproducibility, high throughput and the ability to demonstrate molecular spatial distributions in situ. The data acquired with this protocol can be used in research and clinical practice.