bims-mascan Biomed News
on Mass spectrometry in cancer research
Issue of 2020–04–05
33 papers selected by
Giovanny Rodriguez Blanco, The Beatson Institute for Cancer Research



  1. Methods Mol Biol. 2020 ;2116 125-137
      Mass spectrometry based proteomics allows for the identification and quantification of protein and phosphorylation site abundance on a proteome wide scale. Here we describe the metabolic labeling of cultured Trypanosoma brucei cells in either the bloodstream or procyclic life cycle stage using stable isotope labeling of amino acids in cell culture (SILAC), and the production of samples suitable for analysis by liquid chromatography tandem mass spectrometry. The protocols require little specialist equipment, and they typically enable quantification of over 4500 proteins and 9000 phosphorylation sites.
    Keywords:  High pH reverse phase; Phosphoproteomics; Proteomics; SILAC; Trypanosoma brucei
    DOI:  https://doi.org/10.1007/978-1-0716-0294-2_10
  2. Zhongguo Zhong Yao Za Zhi. 2020 Feb;45(3): 636-644
      In this paper, ultra-high-performance liquid chromatography coupled with quadrupole time-of-flight tandem mass spectrometry(UHPLC-Q-TOF-MS)-based metabolomics approach was used to explore the mechanism of Danggui Buxue Tang(DBT) in treating type 2 diabetes mellitus(T2 DM). T2 DM mice model was induced by high-sugar and high-fat fodder and streptozotocin(STZ). The routine indexes such as body weight, blood glucose, plasma insulin, IL-6 and related organ indexes were determined. The UHPLC-Q-TOF-MS technique was used to analyze the metabolism profile of serum samples between the control group and model group, and multiple statistical analysis methods including principal component analysis(PCA) and orthogonal partial least squares discriminant analysis(OPLS-DA) were used to screen and identify biomarkers. Metabolic profiling revealed 16 metabolites as the most potential biomarkers distinguishing mice in model group from those in control group. The metabolomics pathway analysis(MetPA) was used to investigate the underlying metabolic pathways. Seven major metabolic pathways such the valine, leucine and isoleucine biosynthesis, glycerophospholipid metabolism, primary bile acid biosynthesis, taurine and hypotaurine metabolism, phenylalanine metabolism, fatty acid metabolism and biosynthesis of unsaturated fatty acid. Eleven metabolites such as taurocholic acid and palmitic acid were down-regulated in T2 DM mice, and five metabolites such as L-leucine and leukotriene E4 were up-regulated. Moreover, the sixteen biomar-kers of each administration group had a trend of returning to mice in control group. The significantly-altered metabolite levels indicated that DBT can improve the progression of type 2 diabetes by increasing insulin sensitivity, regulating sugar and lipid metabolism disorders, and relieving inflammation.
    Keywords:  Danggui Buxue Tang; UHPLC-Q-TOF-MS; metabolomics; type 2 diabetes
    DOI:  https://doi.org/10.19540/j.cnki.cjcmm.20191105.202
  3. Anal Bioanal Chem. 2020 Mar 31.
      The application of mass spectrometry imaging (MSI) for the study of spatiotemporal alterations of the metabolites in tumors has brought a number of significant biological results. At present, metabolite profiling based on MSI is typically performed on frozen tissue sections; however, the majority of clinical specimens need to be fixed in tissue fixative to avoid autolysis and to preserve antigenicity. In this study, we present the global impacts of different fixatives on the MS imaging of gastric cancer tissue metabolites. The MSI performances of 17 kinds of metabolites, such as amino acids, polyamines, cholines, organic acids, polypeptides, nucleotides, nucleosides, nitrogen bases, cholesterols, fatty acids, and phospholipids, in untreated, 10% formalin-, 4% paraformaldehyde-, acetone-, and 95% ethanol-fixed gastric cancer tissues were thoroughly explored for the first time. Furthermore, we also investigated the spatial expressions of 6 metabolic enzymes, namely, GLS, FASN, CHKA, PLD2, cPLA2, and EGFR, closely related to tumor-associated metabolites. Immunohistochemical staining carried out on the same tissue sections' which have undergone MSI analysis' suggests that enzymatic characterization is feasible after metabolite imaging. Combining the spatial signatures of metabolites and pathway-related metabolic enzymes in heterogeneous tumor tissues offers an insight to understand the complex tumor metabolism. Graphical abstract.
    Keywords:  Mass spectrometry imaging; Metabolic enzyme; Metabolites; Tissue fixative; Tumor metabolic reprogramming
    DOI:  https://doi.org/10.1007/s00216-020-02562-3
  4. Anal Chim Acta. 2020 Apr 29. pii: S0003-2670(20)30253-1. [Epub ahead of print]1108 79-88
      Faecal metabolomics markedly emerged in clinical as well as analytical chemistry through the unveiling of aberrations in metabolic signatures as reflection of variance in gut (patho)physiology and beyond. Logistic hurdles, however, hinder the analysis of stool samples immediately following collection, inferring the need of biobanking. Yet, the optimum way of storing stool material remains to be determined, in order to conserve an accurate snapshot of the metabolome and circumvent artifacts regarding the disease and parameter(s) under observation. To address this problem, this study scrutinised the impact of freeze-thaw cycling, storage duration, temperature and aerobicity, thereby using ultra-high performance liquid chromatography-high-resolution mass spectrometry (UPLC-HRMS)-based polar metabolomics and lipidomics methodologies for faecal metabolomics. Both targeted (n > 400) and untargeted approaches were implemented to assess storage effects on individual chemical classes of metabolites as well as the faecal fingerprint. In general, recommendations are that intact stool samples should be divided into aliquots, lyophilised and stored at -80 °C for a period no longer than 18 weeks, and avoiding any freeze-thawing. The first preservation week exerted the most decisive impact regarding storage temperature, i.e. 12.1% and 6.4% of the polar metabolome experienced a shift at -20 °C and at -80 °C, respectively, whereas 8.6% and 7.9% was observed to be changed significantly for the lipidome. In addition, aside from the negligible impact of aerobicity, the polar metabolome appeared to be more dependent on the storage conditions applied compared to the lipidome, which emerged as the more stable fraction when assessing the storage duration for 25 weeks. If the interest would greatly align with particular chemical classes, such as branched-chain amino acids or short-chain fatty acids, specific storage duration recommendations are reported. The provided insights on the stability of the faecal metabolome may contribute to a more reasoned design of experiments in biomarker detection or pathway elucidation within the field of faecal metabolomics.
    Keywords:  Faecal fingerprinting; Lipidomics; Metabolomics; Sample storage; Ultra-high performance liquid chromatography-high-resolution mass spectrometry
    DOI:  https://doi.org/10.1016/j.aca.2020.02.046
  5. Anal Bioanal Chem. 2020 Apr 02.
      Lipidomics analysis for large-scale studies aiming at the identification and quantification of natural lipidomes is often performed using LC-MS-based data acquisition. However, the choice of suitable LC-MS method for accurate lipid quantification remains a matter of debate. Here, we performed the systematic comparison between two HRAM-MS-based quantification workflows based on HILIC and RPLC MS by quantifying 191 lipids from five lipid classes in human blood plasma using deuterated standards in the "one ISTD-per-lipid class" approach. Lipid quantification was performed considering all necessary isotopic corrections, and obtained correction factors are illustrated. Concentrations of lipids in NIST® SRM® 1950 human blood plasma determined by the two methods were comparable for most of the studied lipid species except for highly unsaturated phosphatidylcholines (PC). A comparison of lipid concentrations to consensus values determined in a previously published multi-laboratory study illustrated possible "overestimation" of concentrations for these highly unsaturated lipids by HILIC MS. We evaluated the influence of lipid loading amounts as well as the difference between quantified lipid and internal standard concentrations on the HILIC MS quantification results. We conclude that both HILIC and RPLC HRAM-MS workflows can be equally used for accurate lysophosphatidylcholine (LPC), lysophosphatidylethanolamine (LPE), phosphatidylcholine (PC), phosphatidylethanolamine (PE), and sphingomyelin (SM) lipid quantification, despite significant differences in the concentration of highly unsaturated PC lipids which need to be addressed by establishing response factors to account for the differences in degree of lipid unsaturation. Graphical.
    Keywords:  HILIC; Human blood plasma; Lipidomics; Mass spectrometry; Quantification; RPLC; UHPLC
    DOI:  https://doi.org/10.1007/s00216-020-02576-x
  6. Cancers (Basel). 2020 Apr 01. pii: E852. [Epub ahead of print]12(4):
      Immune checkpoint inhibitor (ICI) therapy has shown extraordinary promise at treating cancers otherwise resistant to treatment. However, for ICI therapy to be effective, it must overcome the metabolic limitations of the tumor microenvironment. Tumor metabolism has long been understood to be highly dysregulated, with potent immunosuppressive effects. Moreover, T cell activation and longevity within the tumor microenvironment are intimately tied to T cell metabolism and are required for the long-term efficacy of ICI therapy. We discuss in this review the intersection of metabolic competition in the tumor microenvironment, T cell activation and metabolism, the roles of tumor cell metabolism in immune evasion, and the impact of host metabolism in determining immune surveillance and ICI therapy outcomes. We also discussed the effects of obesity and calorie restriction-two important systemic metabolic perturbations that impact intrinsic metabolic pathways in T cells as well as cancer cells.
    Keywords:  calorie restriction; cancer; immune checkpoint inhibition; metabolism; obesity
    DOI:  https://doi.org/10.3390/cancers12040852
  7. Metabolites. 2020 Mar 27. pii: E128. [Epub ahead of print]10(4):
      Lack of standardized applications of bioinformatics and statistical approaches for pre- and postprocessing of global metabolomic profiling data sets collected using high-resolution mass spectrometry platforms remains an inadequately addressed issue in the field. Several publications now recognize that data analysis outcome variability is caused by different data treatment approaches. Yet, there is a lack of interlaboratory reproducibility studies that have looked at the contribution of data analysis techniques toward variability/overlap of results. The goal of our study was to identify the contribution of data pre- and postprocessing methods on metabolomics analysis results. We performed urinary metabolomics from samples obtained from mice exposed to 5 Gray of external beam gamma rays and those exposed to sham irradiation (control group). The data files were made available to study participants for comparative analysis using commonly used bioinformatics and/or biostatistics approaches in their laboratories. The participants were asked to report back the top 50 metabolites/features contributing significantly to the group differences. Herein we describe the outcome of this study which suggests that data preprocessing is critical in defining the outcome of untargeted metabolomic studies.
    Keywords:  data preprocessing; metabolomics; “omics” analyses
    DOI:  https://doi.org/10.3390/metabo10040128
  8. Int J Mol Sci. 2020 Mar 31. pii: E2436. [Epub ahead of print]21(7):
      Melanoma is the most aggressive type of skin cancer, leading to metabolic rewiring and enhancement of metastatic transformation. Efforts to improve its early and accurate diagnosis are largely based on preclinical models and especially cell lines. Hence, we herein present a combinational Nuclear Magnetic Resonance (NMR)- and Ultra High Performance Liquid Chromatography-High-Resolution Tandem Mass Spectrometry (UHPLC-HRMS/MS)-mediated untargeted metabolomic profiling of melanoma cells, to landscape metabolic alterations likely controlling metastasis. The cell lines WM115 and WM2664, which belong to the same patient, were examined, with WM115 being derived from a primary, pre-metastatic, tumor and WM2664 clonally expanded from lymph-node metastases. Metabolite samples were analyzed using NMR and UHPLC-HRMS. Multivariate statistical analysis of high resolution NMR and MS (positive and negative ionization) results was performed by Principal Component Analysis (PCA), Partial Least Squares-Discriminant Analysis (PLS-DA) and Orthogonal Partial Least Squares-Discriminant Analysis (OPLS-DA), while metastasis-related biomarkers were determined on the basis of VIP lists, S-plots and Student's t-tests. Receiver Operating Characteristic (ROC) curves of NMR and MS data revealed significantly differentiated metabolite profiles for each cell line, with WM115 being mainly characterized by upregulated levels of phosphocholine, choline, guanosine and inosine. Interestingly, WM2664 showed notably increased contents of hypoxanthine, myo-inositol, glutamic acid, organic acids, purines, pyrimidines, AMP, ADP, ATP and UDP(s), thus indicating the critical roles of purine, pyrimidine and amino acid metabolism during human melanoma metastasis.
    Keywords:  MS; NMR; biomarker; cancer; melanoma; metabolomics; metastasis
    DOI:  https://doi.org/10.3390/ijms21072436
  9. Cancer Drug Resist. 2020 ;3(1):
      Breast cancer is one of the leading causes of death in women in the United States. In general, patients with breast cancer undergo surgical resection of the tumor and/or receive drug treatment to kill or suppress the growth of cancer cells. In this regard, small molecule kinase inhibitors serve as an important class of drugs used in clinical and research settings. However, the development of resistance to these compounds, in particular HER2 and CDK4/6 inhibitors, often limits durable clinical responses to therapy. Emerging evidence indicates that PI3K/AKT/mTOR pathway hyperactivation is one of the most prominent mechanisms of resistance to many small molecule inhibitors as it bypasses upstream growth factor receptor inhibition. Importantly, the PI3K/AKT/mTOR pathway also plays a pertinent role in regulating various aspects of cancer metabolism. Recent studies from our lab and others have demonstrated that altered lipid metabolism mediates the development of acquired drug resistance to HER2-targeted therapies in breast cancer, raising an interesting link between reprogrammed kinase signaling and lipid metabolism. It appears that, upon development of resistance to HER2 inhibitors, breast cancer cells rewire lipid metabolism to somehow circumvent the inhibition of kinase signaling. Here, we review various mechanisms of resistance observed for kinase inhibitors and discuss lipid metabolism as a potential therapeutic target to overcome acquired drug resistance.
    Keywords:  Drug resistance; HER2; lipid metabolism; small molecule inhibitor; tyrosine kinase
    DOI:  https://doi.org/10.20517/cdr.2019.100
  10. Clin Chim Acta. 2020 Mar 31. pii: S0009-8981(20)30145-5. [Epub ahead of print]
       BACKGROUND: Pancreatic cancer (PC) is the fourth leading cause of cancer death because of its subtle clinical symptoms in the early stage. To discover particular serum metabolites as potential biomarkers to differentiate pancreatic carcinoma from begin diseases (BD) is on urgent demand.
    METHOD: To comprehensively analyze serum metabolites obtained from 14 patients with PC, 10 patients with BD and 10 healthy individuals (normal control, NC), we separated the metabolites using both reversed-phase liquid chromatography (RPLC) and hydrophilic interaction liquid chromatography (HILIC), and the data were acquired on a high-resolution quadrupole time-of-flight mass spectrometer operated in the negative (ESI-) and positive (ESI+) electrospray ionization modes, respectively. Differential metabolites were selected by univariate (Student's t test) and multivariate (orthogonal partial least squares-discriminant analysis (OPLS-DA)) statistics. Sequential window acquisition of all theoretical spectra (SWATH) analysis was further utilized to validate metabolites which we have found in the discovery stage. The receiver operator characteristics (ROC) curve analysis was performed to evaluate predictive clinical usefulness of 8 metabolites.
    RESULTS: A total of 8 metabolites including taurocholic acid, glycochenodexycholic acid, glycocholic acid, L-glutamine, glutamic acid, L-phenylalanine, L-tryptophan, and L-arginine were identified and relatively quantified as differential metabolites for discriminating PC, BD and NC. The 8 metabolites and their combination discriminated PC from BD and NC with well-performed area under the curve (AUC) values, sensitivity and specificity.
    CONCLUSION: Bile acids (especially taurocholic acid) performed to be potential biomarkers to diagnose PC. And other amino acid (such as L-glutamine, glutamic acid, L-phenylalanine, L-tryptophan, and L-arginine) in the serum samples of PC might provide a sensitive, blood-borne diagnostic signature for the presence of PC or its precursor lesions.
    Keywords:  Biomarker; LC-MS/MS; Metabolomics; Pancreatic cancer
    DOI:  https://doi.org/10.1016/j.cca.2020.03.043
  11. Metabolites. 2020 Mar 31. pii: E135. [Epub ahead of print]10(4):
      Metabolomics analysis generates vast arrays of data, necessitating comprehensive workflows involving expertise in analytics, biochemistry and bioinformatics in order to provide coherent and high-quality data that enable discovery of robust and biologically significant metabolic findings. In this protocol article, we introduce notame, an analytical workflow for non-targeted metabolic profiling approaches, utilizing liquid chromatography-mass spectrometry analysis. We provide an overview of lab protocols and statistical methods that we commonly practice for the analysis of nutritional metabolomics data. The paper is divided into three main sections: the first and second sections introducing the background and the study designs available for metabolomics research and the third section describing in detail the steps of the main methods and protocols used to produce, preprocess and statistically analyze metabolomics data and, finally, to identify and interpret the compounds that have emerged as interesting.
    Keywords:  LC–MS; computational statistical; mass spectrometry; metabolic profiling; metabolomics; pathway analysis; supervised learning; unsupervised learning
    DOI:  https://doi.org/10.3390/metabo10040135
  12. Nat Cell Biol. 2020 Mar 30.
      SLC7A11-mediated cystine uptake is critical for maintaining redox balance and cell survival. Here we show that this comes at a significant cost for cancer cells with high levels of SLC7A11. Actively importing cystine is potentially toxic due to its low solubility, forcing cancer cells with high levels of SLC7A11 (SLC7A11high) to constitutively reduce cystine to the more soluble cysteine. This presents a significant drain on the cellular NADPH pool and renders such cells dependent on the pentose phosphate pathway. Limiting glucose supply to SLC7A11high cancer cells results in marked accumulation of intracellular cystine, redox system collapse and rapid cell death, which can be rescued by treatments that prevent disulfide accumulation. We further show that inhibitors of glucose transporters selectively kill SLC7A11high cancer cells and suppress SLC7A11high tumour growth. Our results identify a coupling between SLC7A11-associated cystine metabolism and the pentose phosphate pathway, and uncover an accompanying metabolic vulnerability for therapeutic targeting in SLC7A11high cancers.
    DOI:  https://doi.org/10.1038/s41556-020-0496-x
  13. Metabolites. 2020 Mar 26. pii: E126. [Epub ahead of print]10(4):
      One of the most widely used strategies for metabolite annotation in untargeted LCMS is based on the analysis of MSn spectra acquired using data-dependent acquisition (DDA), where precursor ions are sequentially selected from MS scans based on user-selected criteria. However, the number of MSn spectra that can be acquired during a chromatogram is limited and a trade-off between analytical speed, sensitivity and coverage must be ensured. In this research, we compare four different strategies for automated MS2 DDA, which can be easily implemented in the frame of standard QA/QC workflows for untargeted LC-MS. These strategies consist of (i) DDA in the MS working range; (ii) iterated DDA split into several m/z intervals; (iii) dynamic iterated DDA of (pre)selected potentially informative features; and (iv) dynamic iterated DDA of (pre)annotated metabolic features using a reference database. Their performance was assessed using the analysis of human milk samples as model example by comparing the percentage of LC-MS features selected as the precursor ion for MS2, the number, and class of annotated features, the speed and confidence of feature annotation, and the number of LC runs required.
    Keywords:  data dependent acquisition; human milk; liquid chromatography–mass spectrometry; peak annotation
    DOI:  https://doi.org/10.3390/metabo10040126
  14. Mass Spectrom Rev. 2020 Mar 31.
      The boost of research output in lipidomics during the last decade is tightly linked to improved instrumentation in mass spectrometry. Associated with this trend is the shift from low resolution-toward high-resolution lipidomics platforms. This review article summarizes the state of the art in the lipidomics field with a particular focus on the merits of high mass resolution. Following some theoretical considerations on the benefits of high mass resolution in lipidomics, it starts with a historical perspective on lipid analysis by sector instruments and moves further to today's instrumental approaches, including shotgun lipidomics, liquid chromatography-mass spectrometry, matrix-assisted laser desorption ionization-time-of-flight, and imaging lipidomics. Subsequently, several data processing and data analysis software packages are critically evaluated with all their pros and cons. Finally, this article emphasizes the importance and necessity of quality standards as the field evolves from its pioneering phase into a mature and robust omics technology and lists various initiatives for improving the applicability of lipidomics. © 2020 The Authors. Mass Spectrometry Reviews published by John Wiley & Sons Ltd.
    Keywords:  chromatography; high mass resolution; lipidomics; mass spectrometry
    DOI:  https://doi.org/10.1002/mas.21627
  15. Sci Rep. 2020 Mar 27. 10(1): 5576
      Lipids play a significant role in regulation of health and disease. To enhance our understanding of the role of lipids in regulation of lifespan and healthspan additional studies are required. Here, UHPLC-MS/MS lipidomics was used to measure dynamic changes in lipid composition as a function of age and gender in genetically identical male and female Daphnia magna with different average lifespans. We demonstrate statistically significant age-related changes in triglycerides (TG), diglycerides (DG), phosphatidylcholine, phosphatidylethanolamine, ceramide and sphingomyelin lipid groups, for example, in males, 17.04% of TG lipid species decline with age whilst 37.86% increase in relative intensity with age. In females, 23.16% decrease and 25.31% increase in relative intensity with age. Most interestingly, the rate and direction of change can differ between genetically identical female and male Daphnia magna, which could be the cause and/or the consequence of the different average lifespans between the two genetically identical genders. This study provides a benchmark dataset to understand how lipids alter as a function of age in genetically identical female and male species with different average lifespan and ageing rate.
    DOI:  https://doi.org/10.1038/s41598-020-62476-z
  16. Nat Chem Biol. 2020 Mar 30.
      We recently described glutathione peroxidase 4 (GPX4) as a promising target for killing therapy-resistant cancer cells via ferroptosis. The onset of therapy resistance by multiple types of treatment results in a stable cell state marked by high levels of polyunsaturated lipids and an acquired dependency on GPX4. Unfortunately, all existing inhibitors of GPX4 act covalently via a reactive alkyl chloride moiety that confers poor selectivity and pharmacokinetic properties. Here, we report our discovery that masked nitrile-oxide electrophiles, which have not been explored previously as covalent cellular probes, undergo remarkable chemical transformations in cells and provide an effective strategy for selective targeting of GPX4. The new GPX4-inhibiting compounds we describe exhibit unexpected proteome-wide selectivity and, in some instances, vastly improved physiochemical and pharmacokinetic properties compared to existing chloroacetamide-based GPX4 inhibitors. These features make them superior tool compounds for biological interrogation of ferroptosis and constitute starting points for development of improved inhibitors of GPX4.
    DOI:  https://doi.org/10.1038/s41589-020-0501-5
  17. Methods Mol Biol. 2020 ;2116 645-653
      Reliable determination of protein complex composition or changes to protein levels in whole cells is challenging. Despite the multitude of methods now available for labeling, analysis, and the statistical processing of data, this large variety is of itself an issue: Which approach is most appropriate, where do you set cutoffs, and what is the most cost-effective strategy? One size does not fit all for such work, but some guidelines can help in terms of reducing cost, improving data quality, and ultimately advancing investigations. Here we describe two protocols and algorithms for facile sample preparation for mass spectrometric analysis, robust data processing, and considerations of how to interpret large proteomic datasets in a productive and robust manner.
    Keywords:  Data presentation; MaxQuant; Proteomics; SDS-PAGE; Sample preparation; Trypanosoma
    DOI:  https://doi.org/10.1007/978-1-0716-0294-2_38
  18. Mol Cell Proteomics. 2020 Mar 31. pii: mcp.RA119.001792. [Epub ahead of print]
      In bottom-up mass spectrometry-based proteomics, relative protein quantification is often achieved with data-dependent acquisition (DDA), data-independent acquisition (DIA), or selected reaction monitoring (SRM). These workflows quantify proteins by summarizing the abundances of all the spectral features of the protein (e.g., precursor ions, transitions or fragments) in a single value per protein per run. When abundances of some features are inconsistent with the overall protein profile (for technological reasons such as interferences, or for biological reasons such as post-translational modifications), the protein-level summaries and the downstream conclusions are undermined. We propose a statistical approach that automatically detects spectral features with such inconsistent patterns. The detected features can be separately investigated, and if necessary removed from the dataset. We evaluated the proposed approach on a series of benchmark controlled mixtures and biological investigations with DDA, DIA and SRM data acquisitions. The results demonstrated that it can facilitate and complement manual curation of the data. Moreover, it can improve the estimation accuracy, sensitivity and specificity of detecting differentially abundant proteins, and reproducibility of conclusions across different data processing tools. The approach is implemented as an option in the open-source R-based software MSstats.
    Keywords:  Bioinformatics; Biostatistics; Computational Biology; Label-free quantification; Mass Spectrometry; Multiple reaction monitoring; Quantification; Selected reaction monitoring; Statistics; Targeted mass spectrometry
    DOI:  https://doi.org/10.1074/mcp.RA119.001792
  19. Anal Chem. 2020 Mar 30.
      Metabolite and lipid profilings usually need two liquid chromatography-mass spectrometry (LC-MS) methods due to great polarity difference. Pseudotargeted metabolomics method has emerged as a novel approach integrating the advantages of nontargeted and targeted methods. Here, we aim to establish a comprehensive method for metabolome and lipidome by using parallel column-based two-dimensional LC (PC-2DLC)-MS and pseudotargeted approach. To simultaneously extract as many polar metabolites and nonpolar lipids as possible, we systematically optimized the sample pretreatment process, and isopropanol/methanol (3:1, v/v) and isopropanol/water (7:3, v/v) were selected as the extraction and reconstitution solvents, respectively. The detected triglycerides have significantly increased after the sample pretreatment optimization. Then, PC-2DLC coupled with Triple TOF MS was applied to analyze a mixed sample from serum, urine and liver tissue matrices. The multiple reaction monitoring (MRM) transitions of metabolome and lipidome were defined according to the "MRM-Ion Pair Finder" software and lipidomics MRM-transition database, respectively. After verified by QTRAP MS in the scheduled MRM mode, 1609 potential metabolites and lipids corresponding to 1294 MRM transitions, and 847 potential metabolites and lipids corresponding to 687 MRM transitions were detected in positive and negative ion modes, respectively. They range about 30 orders of magnitude in octanol/water partition coefficient. Pseudotargeted 2DLC-MS method was validated to have good analytical characteristics. As a proof of applicability, sera from Type 2 diabetic patients were investigated by the established method. The results indicated that the pseudotargeted 2DLC-MS method is reliable, repeatable and can be used in the metabolomics study.
    DOI:  https://doi.org/10.1021/acs.analchem.0c00372
  20. J Clin Med. 2020 Mar 21. pii: E863. [Epub ahead of print]9(3):
       BACKGROUND: Multiple sclerosis (MS) is a chronic immunemediated disease of the central nervous system with a highly variable clinical presentation and disease progression. In this study, we investigate the metabolomics profile of patients affected by relapsing-remitting MS (RRMS)and primary progressive MS (PPMS), in order to find potential biomarkers to distinguish between the two forms.
    METHODS: Cerebrospinal Fluid CSF and blood samples of 34 patients (RRMS n = 22, PPMS n = 12) were collected. Nuclear magnetic resonance (1H-NMR) and mass spectrometry (coupled with a gas chromatography and liquid chromatography) were used as analytical techniques. Subsequently, a multivariate statistical analysis was performed; the resulting significant variables underwent U-Mann-Whitney test and correction for multiple comparisons. Receiver Operating Characteristic ROC curves were built and the pathways analysis was conducted.
    RESULTS: The analysis of the serum and the CSF of the two classes, allowed the identification of several altered metabolites (lipids, biogenic amines, and amino acids). The pathways analysis indicated the following pathways were affected: Glutathione metabolism, nitrogen metabolism, glutamine-glutamate metabolism, arginine-ornithine metabolism, phenylalanine, tyrosine and tryptophan biosynthesis etc. Conclusion: The analysis allowed the identification of a set of metabolites able to classify RRMS and PPMS patients, each of whom express different patterns of metabolites in the two biofluids.
    Keywords:  biomarkers; mass spectrometry; metabolomics; multiple sclerosis; nuclear magnetic resonance; pathways analysis
    DOI:  https://doi.org/10.3390/jcm9030863
  21. Br J Surg. 2020 Apr 04.
      Probe electrospray ionization mass spectrometry (PESI-MS) is an ambient ionization-based mass spectrometry method that surpasses the original electrospray ionization technique in features such as the rapidity of analysis, simplicity of the equipment and procedure, and lower cost. This study found that the PESI-MS system with machine learning has the potential to establish a lipid-based diagnosis of breast cancer with higher accuracy, using a simpler approach. Rapid MS for breast cancer.
    DOI:  https://doi.org/10.1002/bjs.11613
  22. Metabolomics. 2020 Mar 28. 16(4): 45
       INTRODUCTION: The design of training programs for football players is not straightforward due to intra- and inter-individual variability that leads to different physiological responses under similar training loads.
    OBJECTIVE: To study the association between the external load, defined by variables obtained using electronic performance tracking systems (EPTS), and the urinary metabolome as a surrogate of the metabolic adaptation to training.
    METHODS: Urine metabolic and EPTS data from 80 professional football players collected in an observational longitudinal study were analyzed by ultra-performance liquid chromatography coupled to electrospray ionization quadrupole time-of-flight mass spectrometry and assessed by partial least squares (PLS) regression.
    RESULTS: PLS models identified steroid hormone metabolites, hypoxanthine metabolites, acetylated amino acids, intermediates in phenylalanine metabolism, tyrosine, tryptophan metabolites, and riboflavin among the most relevant variables associated with external load. Metabolic network analysis identified enriched pathways including steroid hormone biosynthesis and metabolism of tyrosine and tryptophan. The ratio of players showing a deviation from the PLS model of adaptation to exercise was higher among those who suffered a muscular lesion compared to those who did not.
    CONCLUSIONS: There was a significant association between the external load and the urinary metabolic profile, with alteration of biochemical pathways associated with long-term adaptation to training. Future studies should focus on the validation of these findings and the development of metabolic models to identify professional football players at risk of developing muscular injuries.
    Keywords:  EPTS; External load; Football; Internal load; Metabolomics; Sports; Training
    DOI:  https://doi.org/10.1007/s11306-020-01668-0
  23. Hepatology. 2020 Apr 01.
      Intracellular lipolysis is an enzymatic pathway responsible for the catabolism of triglycerides (TGs) that is complemented by lipophagy as autophagic breakdown of lipid droplets. The hydrolytic cleavage of TGs generates free fatty acids (FFAs), which can serve as energy substrates, precursors for lipid synthesis and mediators in cell signaling. Despite the fundamental and physiological importance of FFAs, an oversupply can trigger lipotoxicity with impaired membrane function, ER stress, mitochondrial dysfunction, cell death and inflammation. Conversely, impaired release of FFAs and other lipid mediators can also disrupt key cellular signaling functions that regulate metabolism and inflammatory processes. This review will focus on specific functions of intracellular lipases in lipid partitioning, covering basic and translational findings in the context of liver disease. In addition, the clinical relevance of genetic mutations in human disease and potential novel therapeutic opportunities will be discussed.
    Keywords:  ATGL/PNPLA2; HSL; MGL; NAFLD; NASH; PNPLA3; fibrosis; lipid metabolism; lipotoxicity; nuclear receptors; patatin-like phospholipases
    DOI:  https://doi.org/10.1002/hep.31250
  24. Biomed Pharmacother. 2020 Mar 29. pii: S0753-3322(20)30300-0. [Epub ahead of print]127 110108
      Ferroptosis is a newly discovered type of cell death triggered by intracellular phospholipid peroxidation that is morphologically, biologically and genetically distinct from other types of cell death. Ferroptosis is classified as regulated necrosis and is more immunogenic than apoptosis. To date, compelling evidence indicates that ferroptosis plays an important role in inflammation, and several antioxidants functioning as ferroptosis inhibitors have been shown to exert anti-inflammatory effects in experimental models of certain diseases. Our review provides an overview of the link between ferroptosis and inflammation; a better understanding of the mechanisms underlying ferroptosis and inflammation may hasten the development of promising therapeutic strategies involving ferroptosis inhibitors to address inflammation.
    Keywords:  Anti-inflammatory; Ferroptosis; Inflammation
    DOI:  https://doi.org/10.1016/j.biopha.2020.110108
  25. Cell Mol Gastroenterol Hepatol. 2020 Mar 24. pii: S2352-345X(20)30036-9. [Epub ahead of print]
      
    DOI:  https://doi.org/10.1016/j.jcmgh.2020.03.001
  26. Int J Mol Sci. 2020 Mar 26. pii: E2279. [Epub ahead of print]21(7):
      Over the last decades a renewed interest in n-3 very long polyunsaturated fatty acids (PUFAs), derived mainly from fish oils in the human diet, has been observed because of their potential effects against cancer diseases, including breast carcinoma. These n-3 PUFAs mainly consist of eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) that, alone or in combination with anticancer agents, induce cell cycle arrest, autophagy, apoptosis, and tumor growth inhibition. A large number of molecular targets of n-3 PUFAs have been identified and multiple mechanisms appear to underlie their antineoplastic activities. Evidence exists that EPA and DHA also elicit anticancer effects by the conversion to their corresponding ethanolamide derivatives in cancer cells, by binding and activation of different receptors and distinct signaling pathways. Other conjugates with serotonin or dopamine have been found to exert anti-inflammatory activities in breast tumor microenvironment, indicating the importance of these compounds as modulators of tumor epithelial/stroma interplay. The objective of this review is to provide a general overview and an update of the current n-3 PUFA derivative research and to highlight intriguing aspects of the potential therapeutic benefits of these low-toxicity compounds in breast cancer treatment and care.
    Keywords:  breast cancer; cannabinoid receptors; omega−3 polyunsaturated fatty acid amides; omega−3 polyunsaturated fatty acid conjugates; omega−3 polyunsaturated fatty acid derivatives; omega−3 polyunsaturated fatty acids; peroxisome proliferator-activated receptor gamma
    DOI:  https://doi.org/10.3390/ijms21072279
  27. Metabolomics. 2020 Apr 03. 16(4): 46
       INTRODUCTION: Consensus in sample preparation for untargeted human fecal metabolomics is lacking.
    OBJECTIVES: To obtain sample preparation with broad metabolite coverage for high-throughput LC-MS.
    METHODS: Extraction solvent, solvent ratio and fresh frozen-vs-lyophilized samples were evaluated by metabolite feature quality.
    RESULTS: Methanol at 5 mL per g wet feces provided a wide metabolite coverage with optimal balance between signal intensity and saturation for both fresh frozen and lyophilized samples. Lyophilization did not affect SCFA and is recommended because of convenience in normalizing to dry matter.
    CONCLUSION: The suggested sample preparation is simple, efficient and suitable for large-scale human fecal metabolomics.
    Keywords:  Fecal sample; Freeze-drying; Method optimization; Short-chain fatty acids; Untargeted fecal metabolomics; XCMS
    DOI:  https://doi.org/10.1007/s11306-020-01669-z
  28. Cells. 2020 Mar 27. pii: E812. [Epub ahead of print]9(4):
      Myelin is critical for the proper function of the nervous system and one of the most complex cell-cell interactions of the body. Myelination allows for the rapid conduction of action potentials along axonal fibers and provides physical and trophic support to neurons. Myelin contains a high content of lipids, and the formation of the myelin sheath requires high levels of fatty acid and lipid synthesis, together with uptake of extracellular fatty acids. Recent studies have further advanced our understanding of the metabolism and functions of myelin fatty acids and lipids. In this review, we present an overview of the basic biology of myelin lipids and recent insights on the regulation of fatty acid metabolism and functions in myelinating cells. In addition, this review may serve to provide a foundation for future research characterizing the role of fatty acids and lipids in myelin biology and metabolic disorders affecting the central and peripheral nervous system.
    Keywords:  Schwann cell; fatty acid; lipid; myelin; oligodendrocyte
    DOI:  https://doi.org/10.3390/cells9040812
  29. Clin Chem Lab Med. 2020 Mar 25. pii: /j/cclm.ahead-of-print/cclm-2020-0177/cclm-2020-0177.xml. [Epub ahead of print]
      Background Appropriate monitoring of tobacco smoking is extremely important in several areas of medicine, e.g. management of chronic obstructive pulmonary disease (COPD), epidemiological surveys, and allocation of heart or lung transplants. The major metabolite of nicotine is cotinine that is increasingly used as a laboratory parameter for assessing tobacco smoke exposure. Methods Creatinine and cotinine were analyzed simultaneously in urine by ultra-high-performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) in one run within 3 min using a biphenyl column. For quantification, the respective stable-isotope-labeled standards were used. Results Detuning and measuring a natural isotope of creatinine as precursor and product ion allowed a simultaneous quantification of creatinine and cotinine. The method revealed robust validation results. For both analytes, inaccuracy and imprecision of the quality control and external quality assessment (EQA) samples were ≤-11.1%. Conclusions One essential novelty of the method presented here is the simultaneous quantification of creatinine and cotinine covered by one analytical method. Despite the very different natural concentrations of creatinine and cotinine, this allows the immediate reporting of the cotinine-to-creatinine ratio without the need for a separate creatinine analysis.
    Keywords:  UHPLC-MS/MS; cotinine; creatinine; tobacco smoking exposure; urine
    DOI:  https://doi.org/10.1515/cclm-2020-0177
  30. Cell Chem Biol. 2020 Mar 24. pii: S2451-9456(20)30081-7. [Epub ahead of print]
      Over the past five decades, thanatology has come to include the study of how individual cells in our bodies die appropriately and inappropriately in response to physiological and pathological stimuli. Morphological and biochemical criteria have been painstakingly established to create clarity around definitions of distinct types of cell death and mechanisms for their activation. Among these, ferroptosis has emerged as a unique, oxidative stress-induced cell death pathway with implications for diseases as diverse as traumatic brain injury, hemorrhagic stroke, Alzheimer's disease, cancer, renal ischemia, and heat stress in plants. In this review, I highlight some of the formative studies that fostered its recognition in the nervous system and describe how chemical biological tools have been essential in defining events necessary for its execution. Finally, I discuss emerging opportunities for antiferroptotic agents as therapeutic agents in neurological diseases.
    Keywords:  ATF4; Chac1; Erk signaling; HIF prolyl hydroxylases; N-acetylcysteine; Nrf-2; Trib3; adaptaquin; c-Myc; cystine transport; ferroptosis; glutathione; glutathione peroxidase-4; iron; mithramycin; reactive lipid species; transglutaminase
    DOI:  https://doi.org/10.1016/j.chembiol.2020.03.007
  31. Cancer Med. 2020 Mar 31.
      Androgen deprivation therapy (ADT) is the main treatment strategy for men with metastatic prostate cancer (PC). However, ADT is associated with various metabolic disturbances, including impaired glucose tolerance, insulin resistance and weight gain, increasing risk of diabetes and cardiovascular death. Much remains unknown about the metabolic pathways and disturbances altered by ADT and the mechanisms. We assessed the metabolomic effects of ADT in the serum of 20 men receiving ADT. Sera collected before (baseline), 3 and 6 months after initiation of ADT was used for the metabolomics and lipidomics analyses. The ADT-associated metabolic changes were identified by univariable and multivariable statistical analysis, ANOVA, and Pearson correlation. We found multiple key changes. First, ADT treatments reduced the steroid synthesis as reflected by the lower androgen sulfate and other steroid hormones. Greater androgen reduction was correlated with higher serum glucose levels, supporting the diabetogenic role of ADT. Second, ADT consistently decreased the 3-hydroxybutyric acid and ketogenesis. Third, many acyl-carnitines were reduced, indicating the effects on the fatty acid metabolism. Fourth, ADT was associated with a corresponding reduction in 3-formyl indole (a.k.a. indole-3-carboxaldehyde), a microbiota-derived metabolite from the dietary tryptophan. Indole-3-carboxaldehyde is an agonist for the aryl hydrocarbon receptor and regulates the mucosal reactivity and inflammation. Together, these ADT-associated metabolomic analyses identified reduction in steroid synthesis and ketogenesis as prominent features, suggesting therapeutic potential of restricted ketogenic diets, though this requires formal testing. ADT may also impact the microbial production of indoles related to the immune pathways. Future research is needed to determine the functional impact and underlying mechanisms to prevent ADT-linked comorbidities and diabetes risk.
    Keywords:  3-formyl indole; 3-hydroxybutyric acid; ADT; androgen sulfate; indole-3-carboxaldehyde; ketogenesis; lipidomics; metabolomics; prostate cancer
    DOI:  https://doi.org/10.1002/cam4.3016