bims-mascan Biomed News
on Mass spectrometry in cancer research
Issue of 2022‒10‒16
29 papers selected by
Giovanny Rodriguez Blanco
University of Edinburgh

  1. Front Oncol. 2022 ;12 988626
      Malignant growth is defined by multiple aberrant cellular features, including metabolic rewiring, inactivation of tumor suppressors and the activation of oncogenes. Even though these features have been described as separate hallmarks, many studies have shown an extensive mutual regulatory relationship amongst them. On one hand, the change in expression or activity of tumor suppressors and oncogenes has extensive direct and indirect effects on cellular metabolism, activating metabolic pathways required for malignant growth. On the other hand, the tumor microenvironment and tumor intrinsic metabolic alterations result in changes in intracellular metabolite levels, which directly modulate the protein modification of oncogenes and tumor suppressors at both epigenetic and post-translational levels. In this mini-review, we summarize the crosstalk between tumor suppressors/oncogenes and metabolism-induced protein modifications at both levels and explore the impact of metabolic (micro)environments in shaping these.
    Keywords:  metabolites; oncogenic signaling; post-translational modification; tumor microenvironment; tumor suppressor gene
  2. Xenobiotica. 2022 Oct 13. 1-28
      Understanding compound metabolism in early drug discovery aids medicinal chemistry in designing molecules with improved safety and ADME properties. While advancements in metabolite prediction brings increasedconfidence, structural decisions require experimental data. In vitro metabolism studies using liquid chromatography and high-resolution mass spectrometry (LC-MS) are generally resource intensive and performed on very few compounds, limiting the chemical space that can be examined.Here, we describe a novel metabolism strategy increasing compound throughput using residual in vitro clearance samples conducted at drug concentrations of 0.5 µM. Analysis by robust UHPLC separation and accurate-mass MS detection ensures major metabolites are identified from a single injection. In silico prediction (parent cLogD) tailors chromatographic conditions, with data-dependent MS/MS targeting predicted metabolites. Software-assisted data mining, structure elucidation and automatic reporting are used.Confidence in the globally-aligned workflow is demonstrated with sixteen marketed drugs. The approach is now implemented routinely across our laboratories. To date, the success rate for identification of at least one major metabolite is 85%. The utility of these data has been demonstrated across multiple projects, allowing earlier medicinal chemistry decisions to increase efficiency and impact of the design-make-test cycle; thus improving the translatability of early in vitro metabolism data.
    Keywords:  biotransformation; chemical design; datamining software; drug discovery; high-resolution mass spectrometry (HRMS) ; high-throughput; in silico prediction; in vitro translatability; intrinsic clearance; quan-qual
  3. J Biol Chem. 2022 Oct 09. pii: S0021-9258(22)01029-8. [Epub ahead of print] 102586
      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 (IC)-ultrahigh resolution (UHR)-MS1/data independent (DI)-MS2 method to track the simultaneous incorporation of the heavy isotopes 13C and 15N into the moieties of purine/pyrimidine nucleotides in mammalian cells. UHR-MS1 resolves and counts multiple tracer atoms in intact metabolites while DI-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 anti-cancer 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 N-acetylglucosamine 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 BEAS2B cells by arsenite.
    Keywords:  Selenite; [(13)C(5),(15)N(2)]-glutamine; [(13)C(6)]-glucose; arsenite; metabolic pathway reconstruction; positional isotopologues; stable isotope resolved metabolomics (SIRM)
  4. Expert Rev Proteomics. 2022 Oct 11.
      INTRODUCTION: As a consequence of excellent sensitivity, nano-flow liquid chromatography tandem mass spectrometry (LC-MS/MS) is the mainstay in proteome research; however, this often comes at the expense of limited throughput and robustness. In contrast, micro-flow LC-MS/MS enables high-throughput, robustness, quantitative reproducibility, and precision, while still retaining a moderate degree of sensitivity. Such features ensures that this is an attractive technology for a wide range of proteomic applications. In particular, large-scale projects involving the analysis of hundreds to thousands of samples.AREAS COVERED: This review summarizes the history of chromatographic separation in discovery proteomics with a focus on micro-flow LC-MS/MS, discusses the current state-of-the-art, highlights advances in column development and instrumentation, and provides guidance on which LC flow range best supports different types of proteomic applications.
    EXPERT OPINION: Micro-flow LC-MS/MS will replace nano-flow LC-MS/MS in many proteomic applications, particularly when sample quantities are not limited and when sample cohorts are large. Examples include clinical analyses of human body fluids or tissues, drug discovery and chemical biology investigations, plus systems biology projects across all kingdoms of life. When combined with rapid and sensitive mass spectrometers, intelligent data acquisition, and informatics approaches, it will soon become possible to analyze large cohorts of more than 10,000 samples in a comprehensive and fully-quantitative fashion.
    Keywords:  micro-flow LC-MS/MS; nano-flow LC-MS/MS; protein identification; protein quantification; proteomics
  5. Methods Mol Biol. 2023 ;2553 417-439
      Computational cell metabolism models seek to provide metabolic explanations of cell behavior under different conditions or following genetic alterations, help in the optimization of in vitro cell growth environments, or predict cellular behavior in vivo and in vitro. In the extremes, mechanistic models can include highly detailed descriptions of a small number of metabolic reactions or an approximate representation of an entire metabolic network. To date, all mechanistic models have required details of individual metabolic reactions, either kinetic parameters or metabolic flux, as well as information about extracellular and intracellular metabolite concentrations. Despite the extensive efforts and the increasing availability of high-quality data, required in vivo data are not available for the majority of known metabolic reactions; thus, mechanistic models are based primarily on ex vivo kinetic measurements and limited flux information. Machine learning approaches provide an alternative for derivation of functional dependencies from existing data. The increasing availability of metabolomic and lipidomic data, with growing feature coverage as well as sample set size, is expected to provide new data options needed for derivation of machine learning models of cell metabolic processes. Moreover, machine learning analysis of longitudinal data can lead to predictive models of cell behaviors over time. Conversely, machine learning models trained on steady-state data can provide descriptive models for the comparison of metabolic states in different environments or disease conditions. Additionally, inclusion of metabolic network knowledge in these analyses can further help in the development of models with limited data.This chapter will explore the application of machine learning to the modeling of cell metabolism. We first provide a theoretical explanation of several machine learning and hybrid mechanistic machine learning methods currently being explored to model metabolism. Next, we introduce several avenues for improving these models with machine learning. Finally, we provide protocols for specific examples of the utilization of machine learning in the development of predictive cell metabolism models using metabolomic data. We describe data preprocessing, approaches for training of machine learning models for both descriptive and predictive models, and the utilization of these models in synthetic and systems biology. Detailed protocols provide a list of software tools and libraries used for these applications, step-by-step modeling protocols, troubleshooting, as well as an overview of existing limitations to these approaches.
    Keywords:  Hybrid modeling; Lipidomics, Flux analysis; Machine learning; Metabolism modeling; Metabolomics
  6. J Pharm Biomed Anal. 2022 Nov 30. pii: S0731-7085(22)00411-3. [Epub ahead of print]221 114990
      Non-small cell lung cancer (NSCLC) is the most common type of malignant tumor of the lung with poor prognosis. Currently, there is still no effective strategy for diagnosing lung cancer from the perspective of multiple biomarkers containing both polar and nonpolar molecules. In order to explore the pathological changes of NSCLC at the endogenous molecule levels, and further establish the strategy for identifying and monitoring drug efficacy of NSCLC, targeted metabolomics and lipidomics studies were established with NSCLC patients. Polar metabolites including 21 amino acids, 7 purines, 6 tricarboxylic acid (TCA) cycle metabolites, and nonpolar lipids like phosphatidylcholine (PC), phosphatidylethanolamine (PE), lysophosphatidylcholine (LPC), lysophosphatidylethanolamine (LPE), sphingomyelin (SM), and ceramide (Cer), diacylglycerol (DG), triacylglycerol (TG), were quantitatively determined based on LC-MS/MS, taking into account their metabolism were significantly concerned with the occurrence of lung cancer in previous study. As a result, 14 polar metabolites and 16 lipids were prominently altered in the plasma of NSCLC patients, among which, after multivariate statistical analysis, LPC 18:0 (sn-2), L-Phenylalanine (Phe), oxaloacetic acid (OAA) and xanthine (XA) were screened out as potential small molecules and lipid biomarkers for NSCLC. Furthermore, a new strategy for formulating equation of NSCLC identification was proposed and clinical utility was successfully evaluated through Kangai injection treatment to NSCLC patients. Taking together, this study investigated the pathological changes of NSCLC from the perspective of endogenous polar and nonpolar molecules, and shed a light on identification of NSCLC.
    Keywords:  Biomarker; Lipidomics; Metabolomics; Non-small cell lung cancer; Pathological changes
  7. Int J Mol Sci. 2022 Sep 21. pii: 11052. [Epub ahead of print]23(19):
      The dynamic crosstalk between the different components of the tumor microenvironment is critical to determine cancer progression, metastatic dissemination, tumor immunity, and therapeutic responses. Angiogenesis is critical for tumor growth, and abnormal blood vessels contribute to hypoxia and acidosis in the tumor microenvironment. In this hostile environment, cancer and stromal cells have the ability to alter their metabolism in order to support the high energetic demands and favor rapid tumor proliferation. Recent advances have shown that tumor endothelial cell metabolism is reprogrammed, and that targeting endothelial metabolic pathways impacts developmental and pathological vessel sprouting. Therefore, the use of metabolic antiangiogenic therapies to normalize the blood vasculature, in combination with immunotherapies, offers a clinical niche to treat cancer.
    Keywords:  metabolic reprogramming; tumor angiogenesis; tumor endothelial cell metabolism; tumor microenvironment
  8. STAR Protoc. 2022 Oct 13. pii: S2666-1667(22)00649-9. [Epub ahead of print]3(4): 101769
      We describe a protocol for measuring phospholipid class and fatty acid composition in the budding yeast Saccharomyces cerevisiae using a liquid chromatography-mass spectrometry (LC-MS)-based approach. We compile a mass spectral-retention time library verified for major phospholipids in the budding yeast and showcase the profiling process of phospholipid compositions in mutants with defective syntheses of phosphatidylethanolamine (PE) and phosphatidylcholine (PC). We further provide methods for extracting and quantifying phospholipids in mammalian systems. For complete details on the use and execution of this protocol, please refer to Fang et al. (2022).
    Keywords:  Cell biology; Mass spectrometry; Metabolomics; Model organisms
  9. Int J Mass Spectrom. 2022 Nov;pii: 116920. [Epub ahead of print]481
      Cellular heterogeneity is commonly investigated using single-cell genomics and transcriptomics to investigate biological questions such as disease mechanism, therapeutic screening, and genomic and transcriptomic diversity between cellular populations and subpopulations at the cellular level. Single-cell mass spectrometry (MS)-based proteomics enables the high-throughput examination of protein expression at the single-cell level with wide applicability, and with spatial and temporal resolution, applicable to the study of cellular development, disease, effect of treatment, etc. The study of single-cell proteomics has lagged behind genomics and transcriptomics largely because proteins from single-cell samples cannot be amplified as DNA and RNA can using well established techniques such as PCR. Therefore, analytical methods must be robust, reproducible, and sensitive enough to detect the very small amount of protein within a single cell. To this end, nearly every step of the proteomics process has been extensively altered and improved to facilitate the proteomics analysis of single cells including cell counting and sorting, lysis, protein digestion, sample cleanup, separation, MS data acquisition, and data analysis. Here, we have reviewed recent advances in single-cell protein separation using nano reversed phase liquid chromatography (nRPLC) and capillary electrophoresis (CE) to inform application driven selection of separation techniques in the laboratory setting.
    Keywords:  Single-cell proteomics; capillary electrophoresis mass spectrometry; reversed-phase liquid chromatography
  10. Methods Mol Biol. 2023 ;2553 265-274
      The explosion of the "omics" era has introduced a growing number of sets and tools that facilitate molecular interrogation of the metabolome. These include various bioinformatics and pharmacogenomics resources that can be utilized independently or collectively to facilitate metabolic engineering across disease, clinical oncology, and understanding of molecular changes across larger systems. This review provides starting points for accessing publicly available data and computational tools that support assessment of metabolic profiles and metabolic regulation, providing both a depth-and-breadth approach toward understanding the metabolome. We focus in particular on pathway databases and tools, which provide in-depth analysis of metabolic pathways, which is at the heart of metabolic engineering.
    Keywords:  Bioinformatics; Databases; High throughput; Metabolic engineering; Metabolomics; Omics; Pharmacogenomics; Software
  11. Anal Chem. 2022 Oct 11.
      Octadecanoids are broadly defined as oxylipins (i.e., lipid mediators) derived from 18-carbon fatty acids. In contrast to the well-studied eicosanoids, there is a lack of analytical methods for octadecanoids, hampering further investigations in the field. We developed an integrated workflow combining chiral separation by supercritical fluid chromatography (SFC) and reversed-phase liquid chromatography (LC) coupled to tandem mass spectrometry detection for quantification of a broad panel of octadecanoids. The platform includes 70 custom-synthesized analytical and internal standards to extend the coverage of the octadecanoid synthetic pathways. A total of 103 octadecanoids could be separated by chiral SFC and complex enantioseparations could be performed in <13 min, while the achiral LC method separated 67 octadecanoids in 13.5 min. The LC method provided a robust complementary approach with greater sensitivity relative to the SFC method. Both methods were validated in solvent and surrogate matrix in terms of linearity, lower limits of quantification (LLOQ), recovery, accuracy, precision, and matrix effects. Instrumental linearity was good for both methods (R2 > 0.995) and LLOQ ranged from 0.03 to 6.00 ng/mL for SFC and 0.01 to 1.25 ng/mL for LC. The average accuracy in the solvent and surrogate matrix ranged from 89 to 109% in SFC and from 106 to 220% in LC, whereas coefficients of variation (CV) were <14% (at medium and high concentrations) and 26% (at low concentrations). Validation in the surrogate matrix showed negligible matrix effects (<16% for all analytes), and average recoveries ranged from 71 to 83%. The combined methods provide a platform to investigate the biological activity of octadecanoids and expand our understanding of these little-studied compounds.
  12. J Am Soc Mass Spectrom. 2022 Oct 11.
      While various mass spectrometric approaches have been applied to lipid analysis, unraveling the extensive structural diversity of lipids remains a significant challenge. Notably, these approaches often fail to differentiate between isomeric lipids─a challenge that is particularly acute for branched-chain fatty acids (FAs) that often share similar (or identical) mass spectra to their straight-chain isomers. Here, we utilize charge-switching strategies that combine ligated magnesium dications with deprotonated fatty acid anions. Subsequent activation of these charge inverted anions yields mass spectra that differentiate anteiso-branched- from straight-chain and iso-branched-chain FA isomers with the predictable fragmentation enabling de novo assignment of anteiso branch points. The application of these charge-inversion chemistries in both gas- and solution-phase modalities is demonstrated to assign the position of anteiso-methyl branch-points in FAs and, with the aid of liquid chromatography, can be extended to de novo assignment of additional branching sites via predictable fragmentation patterns as methyl branching site(s) move closer to the carboxyl carbon. The gas-phase approach is shown to be compatible with top-down structure elucidation of complex lipids such as phosphatidylcholines, while the integration of solution-phase charge-inversion with reversed phase liquid chromatography enables separation and unambiguous identification of FA structures within isomeric mixtures. Taken together, the presented charge-switching MS-based technique, in combination with liquid chromatography, enables the structural identification of branched-chain FA without the requirement of authentic methyl-branched FA reference standards.
  13. Cells. 2022 Sep 22. pii: 2956. [Epub ahead of print]11(19):
      Glioblastoma WHO IV (GBM), the most common primary brain tumor in adults, is a heterogenous malignancy that displays a reprogrammed metabolism with various fuel sources at its disposal. Tumor cells primarily appear to consume glucose to entertain their anabolic and catabolic metabolism. While less effective for energy production, aerobic glycolysis (Warburg effect) is an effective means to drive biosynthesis of critical molecules required for relentless growth and resistance to cell death. Targeting the Warburg effect may be an effective venue for cancer treatment. However, past and recent evidence highlight that this approach may be limited in scope because GBM cells possess metabolic plasticity that allows them to harness other substrates, which include but are not limited to, fatty acids, amino acids, lactate, and acetate. Here, we review recent key findings in the literature that highlight that GBM cells substantially reprogram their metabolism upon therapy. These studies suggest that blocking glycolysis will yield a concomitant reactivation of oxidative energy pathways and most dominantly beta-oxidation of fatty acids.
    Keywords:  TCA cycle; glioblastoma; glycolysis; metabolism; oxidative phosphorylation (OXPHOS)
  14. Int J Mol Sci. 2022 Oct 03. pii: 11721. [Epub ahead of print]23(19):
      Oncogenic K-ras is often activated in pancreatic ductal adenocarcinoma (PDAC) due to frequent mutation (&gt;90%), which drives multiple cellular processes, including alterations in lipid metabolism associated with a malignant phenotype. However, the role and mechanism of the altered lipid metabolism in K-ras-driven cancer remains poorly understood. In this study, using human pancreatic epithelial cells harboring inducible K-rasG12D (HPNE/K-rasG12D) and pancreatic cancer cell lines, we found that the expression of phospholipase A2 group IIA (PLA2G2A) was upregulated by oncogenic K-ras. The elevated expression of PLA2G2A was also observed in pancreatic cancer tissues and was correlated with poor survival of PDAC patients. Abrogation of PLA2G2A by siRNA or by pharmacological inhibition using tanshinone I significantly increased lipid peroxidation, reduced fatty acid synthase (FASN) expression, and impaired mitochondrial function manifested by a decrease in mitochondrial transmembrane potential and a reduction in ATP production, leading to the inhibition of cancer cell proliferation. Our study suggests that high expression of PLA2G2A induced by oncogenic K-ras promotes cancer cell survival, likely by reducing lipid peroxidation through its ability to facilitate the removal of polyunsaturated fatty acids from lipid membranes by enhancing the de novo fatty acid synthesis and energy metabolism to support cancer cell proliferation. As such, PLA2G2A might function as a downstream mediator of K-ras and could be a potential therapeutic target.
    Keywords:  K-ras; PLA2G2A; fatty acid synthesis; lipid metabolism; mitochondria; pancreatic cancer; phospholipase; tanshinone I
  15. Cancers (Basel). 2022 Sep 27. pii: 4696. [Epub ahead of print]14(19):
      The objective of this review is to explore the metabolomic environment of epithelial ovarian cancer that contributes to chemoresistance and to use this knowledge to identify possible targets for therapeutic intervention. The Warburg effect describes increased glucose uptake and lactate production in cancer cells. In ovarian cancer, we require a better understanding of how cancer cells reprogram their glycogen metabolism to overcome their nutrient deficient environment and become chemoresistant. Glucose metabolism in ovarian cancer cells has been proposed to be influenced by altered fatty acid metabolism, oxidative phosphorylation, and acidification of the tumor microenvironment. We investigate several markers of altered metabolism in ovarian cancer including hypoxia-induced factor 1, VEGF, leptin, insulin-like growth factors, and glucose transporters. We also discuss the signaling pathways involved with these biomarkers including PI3K/AKT/mTOR, JAK/STAT and OXPHOS. This review outlines potential metabolic targets to overcome chemoresistance in ovarian cancer. Continued research of the metabolic changes in ovarian cancer is needed to identify and target these alterations to improve treatment approaches.
    Keywords:  PI3K/AKT/mTOR; fatty acid oxidation; glucose; glycolysis; insulin; leptin; metabolism; metabolomics; ovarian cancer; oxidative phosphorylation
  16. Oncogene. 2022 Oct 10.
      Metabolism must be tightly regulated to fulfil the dynamic requirements of cancer cells during proliferation, migration, stemness and differentiation. Src is a node of several signals involved in many of these biological processes, and it is also an important regulator of cell metabolism. Glucose uptake, glycolysis, the pentose-phosphate pathway and oxidative phosphorylation are among the metabolic pathways that can be regulated by Src. Therefore, this oncoprotein is in an excellent position to coordinate and finely tune cell metabolism to fuel the different cancer cell activities. Here, we provide an up-to-date summary of recent progress made in determining the role of Src in glucose metabolism as well as the link of this role with cancer cell metabolic plasticity and tumour progression. We also discuss the opportunities and challenges facing this field.
  17. Chronobiol Int. 2022 Oct 09. 1-9
      Mechanistic studies are needed to understand how rotating shift work perturbs metabolic processing. We collected plasma samples (n = 196) from 49 males, rotating car factory shift workers at the beginning and end of a night-shift (22:00-06:00 h) and day-shift (06:00 h-14:00 h). Samples underwent targeted LC-MS/MS metabolomics and concentrations of 130 metabolites were log2-transformed and pareto-scaled. An elastic net selected the most influential metabolites for linear mixed models examining within-person variation in metabolite levels at night-shift end (06:00 h) compared to day-shift start (06:00 h). Quantitative enrichment analysis explored differentially enriched biological pathways between sample time points. We included 20 metabolites (amino acids, biogenic amines, acylcarnitines, glycerophospholipids) in mixed models. Night-shift was associated with changes in concentrations of arginine (geometric mean ratio [GMR] 2.30, 95%CI 1.25, 4.23), glutamine (GMR 2.22, 95%CI 1.53, 3.24), kynurenine (GMR 3.22, 95%CI 1.05, 9.87), lysoPC18:2 (GMR 1.86, 95%CI 1.11, 3.11), lysoPC20:3 (GMR 2.48, 95%CI 1.05, 5.83), PCaa34:2 (GMR 2.27, 95%CI 1.16, 4.44), and PCae38:5 (GMR 1.66, 95%CI 1.02, 2.68). Tryptophan metabolism, glutathione metabolism, alanine metabolism, glycine and serine metabolism, and urea cycle were pathways differing between shifts. Night shift work was associated with changes in metabolites and the perturbation of metabolic and biochemical pathways related to a variety of health outcomes.
    Keywords:  Circadian; metabolism; metabolomics; occupational health; rotating shift work; shift worker
  18. Cancer Res. 2022 Oct 10. pii: CAN-21-4369. [Epub ahead of print]
      Obesity induces numerous physiological changes that can impact cancer risk and patient response to therapy. Obese patients with cervical cancer have been reported to have superior outcomes following chemoradiation, suggesting that free fatty acids (FFAs) might enhance response to radiation. Here, using preclinical models, we show that mono- and diunsaturated FFAs (uPPAs) radiosensitize cervical cancer through a novel p53-dependent mechanism. UFFAs signaled through PPARγ and p53 to promote lipid uptake, storage, and metabolism after radiation. Stable isotope labeling confirmed that cervical cancer cells increase both catabolic and anabolic oleate metabolism in response to radiation, with associated increases in dependence on mitochondrial fatty acid oxidation for survival. In vivo, supplementation with exogenous oleate suppressed tumor growth in xenografts after radiation, an effect which could be partially mimicked in tumors from high fat diet-induced obese mice. These results suggest that supplementation with uFFAs may improve tumor responses to radiation therapy, particularly in p53 wild type tumors.
  19. Acc Chem Res. 2022 Oct 10.
      ConspectusThe structural boundaries of living cells are composed of numerous membrane-forming lipids. Lipids not only are crucial for the cellular compartmentalization but also are involved in cell signaling as well as energy storage. Abnormal lipid levels have been linked to severe human diseases such as cancer, multiple sclerosis, neurodegenerative diseases, as well as lysosomal storage disorders. Given their biological significance, there is immense interest in studying lipids and their effect on cells. However, limiting factors include the low solubility of lipids, their structural complexity, and the challenge of using genetic techniques to directly manipulate lipid structure. Current methods to study lipids rely mostly on lipidomics, which analyzes the composition of lipid extracts using mass spectrometry. Although, these efforts have successfully catalogued and profiled a great number of lipids in cells, many aspects about their exact functional role and subcellular distribution remain enigmatic.In this Account, we outline how our laboratory developed and applied different bioconjugation strategies to study the role of lipids and lipid modifications in cells. Inspired by our ongoing work on developing lipid bioconjugation strategies to generate artificial cell membranes, we developed a ceramide synthesis method in live cells using a salicylaldehyde ester that readily reacts with sphingosine in form of a traceless ceramide ligation. Our study not only confirmed existing knowledge about the association of ceramides with cell death, but also gave interesting new findings about the structure-function relationship of ceramides in apoptosis. Our initial efforts led us to investigate probes that detect endogenous sphingolipids using live cell imaging. We describe the development of a fluorogenic probe that reacts chemoselectively with sphingosine in living cells, enabling the detection of elevated endogenous levels of this biomarker in human disease. Building on our interest in the fluorescence labeling of lipids, we have also explored the use of bioorthogonal reactions to label chemically synthesized lipid probes. We discuss the development of photocaged dihydrotetrazine lipids, where the initiation of the bioorthogonal reaction can be triggered by visible light, allowing for live cell modification of membranes with spatiotemporal control.Finally, proteins are often post-translationally modified by lipids, which have important effects on protein subcellular localization and function. Controlling lipid modifications with small molecule probes could help reveal the function of lipid post-translational modifications and could potentially inspire novel therapeutic strategies. We describe how our previous studies on synthetic membrane formation inspired us to develop an amphiphilic cysteine derivative that depalmitoylates membrane-bound S-acylated proteins in live cells. Ultimately, we applied this amphiphile mediated depalmitoylation (AMD) in studies investigating the palmitoylation of cancer relevant palmitoylated proteins in healthy and diseased cells.
  20. Redox Biol. 2022 Oct 03. pii: S2213-2317(22)00268-3. [Epub ahead of print]57 102496
      Lysyl-oxidase like-2 (LOXL2) regulates extracellular matrix remodeling and promotes tumor invasion and metastasis. Altered metabolism is a core hallmark of cancer, however, it remains unclear whether and how LOXL2 contributes to tumor metabolism. Here, we found that LOXL2 and its catalytically inactive L2Δ13 splice variant boost glucose metabolism of esophageal tumor cells, facilitate tumor cell proliferation and promote tumor development in vivo. Consistently, integrated transcriptomic and metabolomic analysis of a knock-in mouse model expressing L2Δ13 gene revealed that LOXL2/L2Δ13 overexpression perturbs glucose and lipid metabolism. Mechanistically, we identified aldolase A, glyceraldehyde-3-phosphate dehydrogenase and enolase as glycolytic proteins that interact physically with LOXL2 and L2Δ13. In the case of aldolase A, LOXL2/L2Δ13 stimulated its mobilization from the actin cytoskeleton to enhance aldolase activity during malignant transformation. Using stable isotope labeling of amino acids in cell culture (SILAC) followed by proteomic analysis, we identified LOXL2 and L2Δ13 as novel deacetylases that trigger metabolic reprogramming. Both LOXL2 and L2Δ13 directly catalyzed the deacetylation of aldolase A at K13, resulting in enhanced glycolysis which subsequently reprogramed tumor metabolism and promoted tumor progression. High level expression of LOXL2/L2Δ13 combined with decreased acetylation of aldolase-K13 predicted poor clinical outcome in patients with esophageal cancer. In summary, we have characterized a novel molecular mechanism that mediates the pro-tumorigenic activity of LOXL2 independently of its classical amine oxidase activity. These findings may enable the future development of therapeutic agents targeting the metabolic machinery via LOXL2 or L2Δ13. HIGHLIGHT OF THE STUDY: LOXL2 and its catalytically inactive isoform L2Δ13 function as new deacetylases to promote metabolic reprogramming and tumor progression in esophageal cancer by directly activating glycolytic enzymes such as aldolase A.
    Keywords:  Aldolase; Deacetylation; Glycolysis; Lysyl oxidase-like 2; Tumorigenesis
  21. Cancer Metab. 2022 Oct 12. 10(1): 16
      BACKGROUND: Metabolomics is a potential means for biofluid-based lung cancer detection. We conducted a non-targeted, data-driven assessment of plasma from early-stage non-small cell lung cancer (ES-NSCLC) cases versus cancer-free controls (CFC) to explore and identify the classes of metabolites for further targeted metabolomics biomarker development.METHODS: Plasma from 250 ES-NSCLC cases and 250 CFCs underwent ultra-high-performance liquid chromatography/quadrupole time-of-flight mass spectrometry (UHPLC-QTOF-MS) in positive and negative electrospray ionization (ESI) modes. Molecular feature extraction, formula generation, and find-by-ion tools annotated metabolic entities. Analysis was restricted to endogenous metabolites present in ≥ 80% of samples. Unsupervised hierarchical cluster analysis identified clusters of metabolites. The metabolites with the strongest correlation with the principal component of each cluster were included in logistic regression modeling to assess discriminatory performance with and without adjustment for clinical covariates.
    RESULTS: A total of 1900 UHPLC-QTOF-MS assessments identified 1667 and 2032 endogenous metabolites in the ESI-positive and ESI-negative modes, respectively. After data filtration, 676 metabolites remained, and 12 clusters of metabolites were identified from each ESI mode. Multivariable logistic regression using the representative metabolite from each cluster revealed effective classification of cases from controls with overall diagnostic accuracy of 91% (ESI positive) and 94% (ESI negative). Metabolites of interest identified for further targeted analysis include the following: 1b, 3a, 12a-trihydroxy-5b-cholanoic acid, pyridoxamine 5'-phosphate, sphinganine 1-phosphate, gamma-CEHC, 20-carboxy-leukotriene B4, isodesmosine, and 18-hydroxycortisol.
    CONCLUSIONS: Plasma-based metabolomic detection of early-stage NSCLC appears feasible. Further metabolomics studies targeting phospholipid, steroid, and fatty acid metabolism are warranted to further develop noninvasive metabolomics-based detection of early-stage NSCLC.
    Keywords:  Early detection; Early-stage non-small cell lung cancer; Non-targeted metabolomics; Plasma metabolomics
  22. Nutrients. 2022 Sep 25. pii: 3984. [Epub ahead of print]14(19):
      Lipids affect cartilage growth, injury, and regeneration in diverse ways. Diet and metabolism have become increasingly important as the prevalence of obesity has risen. Proper lipid supplementation in the diet contributes to the preservation of cartilage function, whereas excessive lipid buildup is detrimental to cartilage. Lipid metabolic pathways can generate proinflammatory substances that are crucial to the development and management of osteoarthritis (OA). Lipid metabolism is a complicated metabolic process involving several regulatory systems, and lipid metabolites influence different features of cartilage. In this review, we examine the current knowledge about cartilage growth, degeneration, and regeneration processes, as well as the most recent research on the significance of lipids and their metabolism in cartilage, including the extracellular matrix and chondrocytes. An in-depth examination of the involvement of lipid metabolism in cartilage metabolism will provide insight into cartilage metabolism and lead to the development of new treatment techniques for metabolic cartilage damage.
    Keywords:  cartilage; cholesterol; fatty acid; lipid metabolism; osteoarthritis; phospholipid
  23. J Cancer Res Clin Oncol. 2022 Oct 12.
      PURPOSE: Extracellular vesicles (EV) secreted from cancer cells are present in various biological fluids, carrying distinctly different cellular components compared to normal cells, and have great potential to be used as markers for disease initiation, progression, and response to treatment. This under-utilised tool provides insights into a better understanding of prostate cancer.METHODS: EV from serum and urine of healthy men and castration-resistant prostate cancer (CRPC) patients were isolated and characterised by transmission electron microscopy, particle size analysis, and western blot. Proteomic and cholesterol liquid chromatography-mass spectrometry (LC-MS) analyses were conducted.
    RESULTS: There was a successful enrichment of small EV/exosomes isolated from serum and urine. EV derived from biological fluids of CRPC patients had significant differences in composition when compared with those from healthy controls. Analysis of matched serum and urine samples from six prostate cancer patients revealed specific EV proteins common in both types of biological fluid for each patient.
    CONCLUSION: Some of the EV proteins identified from our analyses have potential to be used as CRPC markers. These markers may depict a pattern in cancer progression through non-invasive sample collection.
    Keywords:  Cancer markers; Cholesterol; Extracellular vesicles; Liquid biopsy; Prostate cancer; Proteomic
  24. Biomed Pharmacother. 2022 Oct 10. pii: S0753-3322(22)01145-3. [Epub ahead of print]156 113756
      Metabolic alterations play a key role in promoting tumor initiation and progression, leading to extensive tumor heterogeneity and adaptability. Thus, targeting abnormal metabolic processes is a promising novel approach for cancer treatment. Numerous pharmacological studies have indicated that many traditional Chinese medicines possess remarkable antitumor activities. Ginsenosides, the main bioactive ingredients of Panax and other types of ginseng, exert beneficial antitumor effects, in addition to the anti-inflammation, anti-oxidant, and anti-fatigue effects. Recently, considerable attention has been paid to the regulation of cancer cell metabolism by ginsenosides. Here, we summarize the structural characteristics and classification of ginsenosides, their antitumor mechanisms, recent progress and the achievements of ginsenoside research in modulating cancer cell metabolism, including the diverse metabolic processes and their regulatory processes, as well as the opportunities and challenges of strategies targeting metabolic vulnerabilities. This review provides novel perspectives on the potential applications of ginsenosides that exert antitumor effects by reshaping cancer metabolism.
    Keywords:  Antitumor activity; Cancer; Cell metabolism; Ginsenosides; Mechanism
  25. Front Physiol. 2022 ;13 992679
      Amino acids have recently emerged as important regulators of osteoblast differentiation and bone formation. Osteoblasts require a continuous supply of amino acids to sustain biomass production to fuel cell proliferation, osteoblast differentiation and bone matrix production. We recently identified proline as an essential amino acid for bone development by fulfilling unique synthetic demands that are associated with osteoblast differentiation. Osteoblasts rely on the amino acid transporter SLC38A2 to provide proline to fuel endochondral ossification. Despite this, very little is known about the function or substrates of SLC38A2 during bone homeostasis. Here we demonstrate that the neutral amino acid transporter SLC38A2 is expressed in osteoblast lineage cells and provides proline and alanine to osteoblast lineage cells. Genetic ablation of SLC38A2 using Prrx1Cre results in decreased bone mass in both male and female mice due to a reduction in osteoblast numbers and bone forming activity. Decreased osteoblast numbers are attributed to impaired proliferation and osteogenic differentiation of skeletal stem and progenitor cells. Collectively, these data highlight the necessity of SLC38A2-mediated proline and alanine uptake during postnatal bone formation and bone homeostasis.
    Keywords:  Alanine (Ala); Amino acid; Osteoblast (OB); bone; proline
  26. J Clin Invest. 2022 Oct 13. pii: e157302. [Epub ahead of print]
      Metabolic reprogramming is an important cancer hallmark. However, the mechanisms driving metabolic phenotypes of cancer cells are unclear. Here, we showed that the interferon (IFN)-inducible protein, viperin, drives metabolic alteration in cancer cells. Viperin was observed in various types of cancer and inversely correlated with the survival rate of patients with gastric, lung, breast, renal, pancreatic, or brain cancer. By generating viperin knockdown or stably expressing cancer cells, we showed that viperin, but not a mutant lacking its iron-sulfur cluster-binding motif, increased lipogenesis and glycolysis via inhibition of fatty acid β-oxidation in cancer cells. In the tumor microenvironment, deficiency of fatty acids and oxygen as well as production of IFNs upregulated viperin expression via the PI3K/AKT/mTOR/HIF-1α and JAK/STAT pathways. Moreover, viperin was primarily expressed in cancer stem-like cells (CSCs) and functioned to promote metabolic reprogramming and enhance CSC properties, thereby facilitating tumor growth in xenograft mouse models. Collectively, our data indicate that viperin-mediated metabolic alteration drives the metabolic phenotype and progression of cancer.
    Keywords:  Cancer; Fatty acid oxidation; Glucose metabolism; Metabolism; Oncology
  27. J Chromatogr A. 2022 Sep 23. pii: S0021-9673(22)00721-X. [Epub ahead of print]1683 463529
      In this article, a serially connected dual column liquid chromatography-tandem mass spectrometry (LC-MS/MS) method is described for the simultaneous separation and enantioseparation of proteinogenic amino acids. For this purpose, different achiral and chiral stationary phases (CSP) and mobile phase compositions have been tested. As a result of the optimization studies, the best enatioseparation for amino acids were achieved with a combination of zwitterionic and crown ether stationary phases using a gradient of two mobile phases: A (water:TFA 99.5:0.5, % v/v) and B (acetonitrile:ethanol:TFA 85:15:0.5, % v/v/v). The developed method provided simultaneous enantioseparation of all proteinogenic amino acids under this study including isomeric and isobaric ones except for proline. The method was successfully applied to human lung adenocarcinoma cells (A549) and healthy human lung epithelial cells (BEAS-2B) cultivated with d-amino acid containing cocktails in order to evaluate d-amino acids transfer rate in normal and cancer lines. Thed/l amino acid ratios were different in cancer and normal cell lines cultivated as mentioned above for aspartic acid, cysteine, methionine, phenylalanine, and serine.
    Keywords:  Chiral crown ether; Dual column; Enantioseparation; Native amino acids; ZIC-HILIC
  28. J Pharm Biomed Anal. 2022 Oct 07. pii: S0731-7085(22)00513-1. [Epub ahead of print]222 115092
      Metabolite detection from complex biological samples faces challenges due to interference from endogenous substrates and the inherent limitation of multiple subsequent tandem scanning rates of instruments. Here, a new integrated approach based on gas-phase fractionation with a staggered mass range (sGPF) and a liquid chromatography-tandem mass spectrometry (LC-MS/MS) molecular network was developed to accelerate the data processing of the targeted and untargeted constituents absorbed in rats after oral administration of the traditional Chinese medicine (TCM) prescription Gui Ling Ji (GLJ). Compared with three conventional acquisition methods, sGPF at 3, 5, and 7 mass fractions could enhance MS/MS coverage with an increased MS/MS triggering rate of 29.4-206.2% over data-dependent acquisition (DDA), fast DDA and gas-phase fractionation. A mass range fraction setting of five optimized the performance. Based on the similar diagnostic fragment ions and characteristic neutral loss behaviors in the DDA-MS/MS spectrum, an initial molecular network of GLJ was created with the help of the global natural products social molecular networking (GNPS) platform. Furthermore, to remove the endogenous interference nodes, Cytoscape software was adopted to produce a clean and concise molecular network of prototype compounds and their corresponding metabolites. Using this strategy, a total of 210 compounds, including 59 prototype constituents and 151 metabolites, was unambiguously or tentatively identified in GLJ. This first systematic metabolic study of GLJ in vivo elucidated the potential pharmacodynamic basis of GLJ in clinical treatment. More importantly, this work can serve as a practical example and establish a guide for rapidly identifying TCM metabolites in biological matrices.
    Keywords:  Gas phase fractionation with staggered mass range; Gui Ling Ji; LC-MS/MS molecular network; Metabolites
  29. Int J Mol Sci. 2022 Sep 21. pii: 11072. [Epub ahead of print]23(19):
      Non-alcoholic fatty liver disease (NAFLD) is the most common chronic liver disease in children and is associated with overweight and insulin resistance (IR). Almost nothing is known about in vivo alterations of liver metabolism in NAFLD, especially in the early stages of non-alcoholic steatohepatitis (NASH). Here, we used a complex mathematical model of liver metabolism to quantify the central hepatic metabolic functions of 71 children with biopsy-proven NAFLD. For each patient, a personalized model variant was generated based on enzyme abundances determined by mass spectroscopy. Our analysis revealed statistically significant alterations in the hepatic carbohydrate, lipid, and ammonia metabolism, which increased with the degree of obesity and severity of NAFLD. Histologic features of NASH and IR displayed opposing associations with changes in carbohydrate and lipid metabolism but synergistically decreased urea synthesis in favor of the increased release of glutamine, a driver of liver fibrosis. Taken together, our study reveals already significant alterations in the NASH liver of pediatric patients, which, however, are differently modulated by the simultaneous presence of IR.
    Keywords:  histology; liver tissue; mathematical modeling; plasma profile; proteomics