bims-mascan Biomed News
on Mass spectrometry in cancer research
Issue of 2020‒09‒27
27 papers selected by
Giovanny Rodriguez Blanco
University of Edinburgh


  1. Cell Metab. 2020 Sep 16. pii: S1550-4131(20)30483-6. [Epub ahead of print]
    Liu S, Dai Z, Cooper DE, Kirsch DG, Locasale JW.
      The nutritional source for catabolism in the tricarboxylic acid (TCA) cycle is a fundamental question in metabolic physiology. Limited by data and mathematical analysis, controversy exists. Using isotope-labeling data in vivo across several experimental conditions, we construct multiple models of central carbon metabolism and develop methods based on metabolic flux analysis (MFA) to solve for the preferences of glucose, lactate, and other nutrients used in the TCA cycle. We show that in nearly all circumstances, glucose contributes more than lactate as a substrate to the TCA cycle. This conclusion is verified in different animal strains from different studies and different administrations of 13C glucose, and is extended to multiple tissue types. Thus, this quantitative analysis of organismal metabolism defines the relative contributions of nutrient fluxes in physiology, provides a resource for analysis of in vivo isotope tracing data, and concludes that glucose is the major nutrient used in mammals.
    Keywords:  TCA cycle; glucose metabolism; isotope tracing; lactate; liver metabolism; metabolic flux analysis; mitochondrial metabolism; multi-tissue modeling; parameter sensitivity analysis; quantitative biology; systems biology
    DOI:  https://doi.org/10.1016/j.cmet.2020.09.005
  2. Cell Metab. 2020 Sep 16. pii: S1550-4131(20)30479-4. [Epub ahead of print]
    Forte D, García-Fernández M, Sánchez-Aguilera A, Stavropoulou V, Fielding C, Martín-Pérez D, López JA, Costa ASH, Tronci L, Nikitopoulou E, Barber M, Gallipoli P, Marando L, Fernández de Castillejo CL, Tzankov A, Dietmann S, Cavo M, Catani L, Curti A, Vázquez J, Frezza C, Huntly BJ, Schwaller J, Méndez-Ferrer S.
      Like normal hematopoietic stem cells, leukemic stem cells depend on their bone marrow (BM) microenvironment for survival, but the underlying mechanisms remain largely unknown. We have studied the contribution of nestin+ BM mesenchymal stem cells (BMSCs) to MLL-AF9-driven acute myeloid leukemia (AML) development and chemoresistance in vivo. Unlike bulk stroma, nestin+ BMSC numbers are not reduced in AML, but their function changes to support AML cells, at the expense of non-mutated hematopoietic stem cells (HSCs). Nestin+ cell depletion delays leukemogenesis in primary AML mice and selectively decreases AML, but not normal, cells in chimeric mice. Nestin+ BMSCs support survival and chemotherapy relapse of AML through increased oxidative phosphorylation, tricarboxylic acid (TCA) cycle activity, and glutathione (GSH)-mediated antioxidant defense. Therefore, AML cells co-opt energy sources and antioxidant defense mechanisms from BMSCs to survive chemotherapy.
    Keywords:  OXPHOS; TCA cycle; acute myeloid leukemia; antioxidant; bone marrow mesenchymal stem cells; chemotherapy; glutathione; hematopoietic stem cell niche; metabolic adaptation; microenvironment
    DOI:  https://doi.org/10.1016/j.cmet.2020.09.001
  3. Adv Clin Chem. 2020 ;pii: S0065-2423(20)30021-4. [Epub ahead of print]99 147-191
    Alves S, Paris A, Rathahao-Paris E.
      Today, metabolomics is becoming an indispensable tool to get a more comprehensive analysis of complex living systems, providing insights on multiple aspects of physiology. Although its application in large scale population-based studies is very challenging due to the processing of large sample sets as well as the complexity of data information, its potential to characterize human health is well recognized. Technological advances in metabolomics pave the way for the efficient biomarker discovery of disease etiology, diagnosis and prognosis. Here, different steps of the metabolomics workflow, particularly mass spectrometry-based approaches, are discussed to demonstrate the potential of metabolomics to address biological questioning in human health. First an overview of metabolomics is provided with its interest in human health studies. Analytical development and advances in mass spectrometry instrumentation and computational tools are discussed regarding their application limits. Advancing metabolomics for applicability in human health and large-scale studies is presented and discussed in conclusion.
    Keywords:  Data mining; Human health; Large-scale studies; Mass spectrometry; Metabolite identification; Metabolomics; Sample preparation
    DOI:  https://doi.org/10.1016/bs.acc.2020.02.009
  4. Open Biol. 2020 Sep;10(9): 200187
    Varner EL, Trefely S, Bartee D, von Krusenstiern E, Izzo L, Bekeova C, O'Connor RS, Seifert EL, Wellen KE, Meier JL, Snyder NW.
      Lysine lactoylation is a recently described protein post-translational modification (PTM). However, the biochemical pathways responsible for this acylation remain unclear. Two metabolite-dependent mechanisms have been proposed: enzymatic histone lysine lactoylation derived from lactoyl-coenzyme A (lactoyl-CoA, also termed lactyl-CoA), and non-enzymatic lysine lactoylation resulting from acyl-transfer via lactoyl-glutathione. While the former has precedent in the form of enzyme-catalysed lysine acylation, the lactoyl-CoA metabolite has not been previously quantified in mammalian systems. Here, we use liquid chromatography-high-resolution mass spectrometry (LC-HRMS) together with a synthetic standard to detect and validate the presence of lactoyl-CoA in cell and tissue samples. Conducting a retrospective analysis of data from previously analysed samples revealed the presence of lactoyl-CoA in diverse cell and tissue contexts. In addition, we describe a biosynthetic route to generate 13C315N1-isotopically labelled lactoyl-CoA, providing a co-eluting internal standard for analysis of this metabolite. We estimate lactoyl-CoA concentrations of 1.14 × 10-8 pmol per cell in cell culture and 0.0172 pmol mg-1 tissue wet weight in mouse heart. These levels are similar to crotonyl-CoA, but between 20 and 350 times lower than predominant acyl-CoAs such as acetyl-, propionyl- and succinyl-CoA. Overall our studies provide the first quantitative measurements of lactoyl-CoA in metazoans, and provide a methodological foundation for the interrogation of this novel metabolite in biology and disease.
    Keywords:  LC-HRMS; high resolution; lactoyl-CoA; lactyl-CoA; metabolism
    DOI:  https://doi.org/10.1098/rsob.200187
  5. Cancer Cell. 2020 Sep 15. pii: S1535-6108(20)30426-8. [Epub ahead of print]
    Gabitova-Cornell L, Surumbayeva A, Peri S, Franco-Barraza J, Restifo D, Weitz N, Ogier C, Goldman AR, Hartman TR, Francescone R, Tan Y, Nicolas E, Shah N, Handorf EA, Cai KQ, O'Reilly AM, Sloma I, Chiaverelli R, Moffitt RA, Khazak V, Fang CY, Golemis EA, Cukierman E, Astsaturov I.
      Oncogenic transformation alters lipid metabolism to sustain tumor growth. We define a mechanism by which cholesterol metabolism controls the development and differentiation of pancreatic ductal adenocarcinoma (PDAC). Disruption of distal cholesterol biosynthesis by conditional inactivation of the rate-limiting enzyme Nsdhl or treatment with cholesterol-lowering statins switches glandular pancreatic carcinomas to a basal (mesenchymal) phenotype in mouse models driven by KrasG12D expression and homozygous Trp53 loss. Consistently, PDACs in patients receiving statins show enhanced mesenchymal features. Mechanistically, statins and NSDHL loss induce SREBP1 activation, which promotes the expression of Tgfb1, enabling epithelial-mesenchymal transition. Evidence from patient samples in this study suggests that activation of transforming growth factor β signaling and epithelial-mesenchymal transition by cholesterol-lowering statins may promote the basal type of PDAC, conferring poor outcomes in patients.
    Keywords:  TGF-β signaling; cholesterol metabolism; epithelial-to-mesenchymal transition; pancreatic cancer
    DOI:  https://doi.org/10.1016/j.ccell.2020.08.015
  6. EMBO Rep. 2020 Sep 23. e50635
    Altea-Manzano P, Cuadros AM, Broadfield LA, Fendt SM.
      Nutrients are indispensable resources that provide the macromolecular building blocks and energy requirements for sustaining cell growth and survival. Cancer cells require several key nutrients to fulfill their changing metabolic needs as they progress through stages of development. Moreover, both cell-intrinsic and microenvironment-influenced factors determine nutrient dependencies throughout cancer progression-for which a comprehensive characterization remains incomplete. In addition to the widely studied role of genetic alterations driving cancer metabolism, nutrient use in cancer tissue may be affected by several factors including the following: (i) diet, the primary source of bodily nutrients which influences circulating metabolite levels; (ii) tissue of origin, which can influence the tumor's reliance on specific nutrients to support cell metabolism and growth; (iii) local microenvironment, which dictates the accessibility of nutrients to tumor cells; (iv) tumor heterogeneity, which promotes metabolic plasticity and adaptation to nutrient demands; and (v) functional demand, which intensifies metabolic reprogramming to fuel the phenotypic changes required for invasion, growth, or survival. Here, we discuss the influence of these factors on nutrient metabolism and dependence during various steps of tumor development and progression.
    Keywords:  cancer metabolism; diet; microenvironment; nutrients; tumor heterogeneity
    DOI:  https://doi.org/10.15252/embr.202050635
  7. Respir Res. 2020 Sep 21. 21(1): 242
    Liu D, Meister M, Zhang S, Vong CI, Wang S, Fang R, Li L, Wang PG, Massion P, Ji X.
      BACKGROUND: Chronic obstructive pulmonary disease (COPD) is the third leading cause of death in the United States with no effective treatment. The current diagnostic method, spirometry, does not accurately reflect the severity of COPD disease status. Therefore, there is a pressing unmet medical need to develop noninvasive methods and reliable biomarkers to detect early stages of COPD. Lipids are the fundamental components of cell membranes, and dysregulation of lipids was proven to be associated with COPD. Lipidomics is a comprehensive approach to all the pathways and networks of cellular lipids in biological systems. It is widely used for disease diagnosis, biomarker identification, and pathology disorders detection relating to lipid metabolism.METHODS: In the current study, a total of 25 serum samples were collected from 5 normal control subjects and 20 patients with different stages of COPD according to the global initiative for chronic obstructive lung disease (GOLD) (GOLD stages I ~ IV, 5 patients per group). After metabolite extraction, lipidomic analysis was performed using electrospray ionization mass spectrometry (ESI-MS) to detect the serum lipid species. Later, the comparisons of individual lipids were performed between controls and patients with COPD. Orthogonal projections to latent structures discriminant analysis (OPLS-DA) and receiver operating characteristic (ROC) analysis were utilized to test the potential biomarkers. Finally, correlations between the validated lipidomic biomarkers and disease stages, age, FEV1% pack years and BMI were evaluated.
    RESULTS: Our results indicate that a panel of 50 lipid metabolites including phospholipids, sphingolipids, glycerolipids, and cholesterol esters can be used to differentiate the presence of COPD. Among them, 10 individual lipid species showed significance (p < 0.05) with a two-fold change. In addition, lipid ratios between every two lipid species were also evaluated as potential biomarkers. Further multivariate data analysis and receiver operating characteristic (ROC: 0.83 ~ 0.99) analysis suggest that four lipid species (AUC:0.86 ~ 0.95) and ten lipid ratios could be potential biomarkers for COPD (AUC:0.94 ~ 1) with higher sensitivity and specificity. Further correlation analyses indicate these potential biomarkers were not affected age, BMI, stages and FEV1%, but were associated with smoking pack years.
    CONCLUSION: Using lipidomics and statistical methods, we identified unique lipid signatures as potential biomarkers for diagnosis of COPD. Further validation studies of these potential biomarkers with large population may elucidate their roles in the development of COPD.
    Keywords:  Biomarkers; Chronic obstructive pulmonary disease (COPD); Lipidomics; OPLS-DA; Receiver operating characteristic
    DOI:  https://doi.org/10.1186/s12931-020-01507-9
  8. Life Sci. 2020 Sep 22. pii: S0024-3205(20)31242-X. [Epub ahead of print] 118489
    Cheng F, Wen Z, Feng X, Wang X, Chen Y.
      AIMS: Cervical cancer (CC) is a common tumor of women worldwide. Here, we conducted a non-targeted lipidomic study to discover novel lipid biomarkers for early-stage CC.MAIN METHODS: The lipidomic analysis of 71 samples in discovery set and 72 samples in validation set were performed by coupling ultra-high-pressure liquid chromatography (UHPLC) with quadrupole time-of-flight tandem mass spectrometry (Q-TOF-MS). Lipids with variable importance (VIP) values greater than 1, adj. p < 0.05 (the adjusted p value obtained from false discovery rate correction) and fold change (FC) higher than 1.5 were reserved as potential biomarkers. Subsequently, receiver operating characteristic (ROC) curve and binary logistic regression were implemented to assess the diagnostic potential of these biomarkers and to acquire the best biomarker combination.
    KEY FINDINGS: A lipid biomarker panel, including phosphatidylcholine (PC, PC 14:0/18:2) and phosphatidylethanolamine (PE, PE 15:1e/22:6 and PE 16:1e/18:2), was established. This panel was effective in distinguishing between CC and non-CC (squamous intraepithelial lesions [SIL] and healthy controls) within the area under the ROC curve (AUC), sensitivity, and specificity reaching 0.966, 0.952, and 0.860 for discovery set and 0.961, 0.920, and 0.915 for external validation set. Furthermore, this panel was also capable of discriminating early-stage CC from SIL with AUC, sensitivity, and specificity reaching 0.946, 0.952, and 0.800 for discovery set and 0.956, 0.960, and 0.815 for external validation set.
    SIGNIFICANCE: The combination of PC 14:0/18:2, PE 15:1e/22:6, and PE 16:1e/18:2 could serve as a promising serum biomarker for discriminating early-stage CC from SIL and healthy subjects.
    Keywords:  Biomarkers; Cervical cancer; Lipidomic; Serum; Squamous intraepithelial lesions
    DOI:  https://doi.org/10.1016/j.lfs.2020.118489
  9. Curr Protein Pept Sci. 2020 Sep 21.
    Rotello RJ, Veenstra TD.
      In the current omics-age of research, major developments have been made in technologies that attempt to survey the entire repertoire of genes, transcripts, proteins, and metabolites present within a cell. While genomics has led to a dramatic increase in our understanding of such things as disease morphology and how organisms respond to medications, it is critical to obtain information at the proteome level since proteins carry out most of the functions within the cell. The primary tool for obtaining proteome-wide information on proteins within the cell is mass spectrometry (MS). While it has historically been associated with the protein identification, developments over the past couple of decades have made MS a robust technology for protein quantitation as well. Identifying quantitative changes in proteomes is complicated by its dynamic nature and the inability of any technique to guarantee complete coverage of every protein within a proteome sample. Fortunately, the combined development of sample preparation and MS methods have made it capable to quantitatively compare many thousands of proteins obtained from cells and organisms.
    Keywords:  Quantitation; SWATH-MS; isotope labeling; mass spectrometry; proteomics; subtractive proteomics
    DOI:  https://doi.org/10.2174/1389203721666200921153513
  10. Oncogene. 2020 Sep 25.
    Peng H, Wang Y, Luo W.
      Metabolic reprogramming fulfils increased nutrient demands and regulates numerous oncogenic processes in tumors, leading to tumor malignancy. Branched-chain amino acids (BCAAs, i.e., valine, leucine, and isoleucine) function as nitrogen donors to generate macromolecules such as nucleotides and are indispensable for human cancer cell growth. The cell-autonomous and non-autonomous roles of altered BCAA metabolism have been implicated in cancer progression and the key proteins in the BCAA metabolic pathway serve as possible prognostic and diagnostic biomarkers in human cancers. Here we summarize how BCAA metabolic reprogramming is regulated in cancer cells and how it influences cancer progression.
    DOI:  https://doi.org/10.1038/s41388-020-01480-z
  11. Anal Chem. 2020 Sep 24.
    Chavez JD, Keller A, Mohr JP, Bruce JE.
      Chemical cross-linking with mass spectrometry (XL-MS) has emerged as a useful tool for the large scale study of protein structures and interactions from complex biological samples including intact cells and tissues. Quantitative XL-MS (qXL-MS) provides unique information on protein conformational and interaction changes resulting from perturbations such as drug treatment and disease state. Previous qXL-MS studies relied on incorporation of stable isotopes into the cross-linker (primarily deuterium) or metabolic labeling with SILAC. Here, we introduce isobaric quantitative Protein Interaction Reporter (iqPIR) technology which utilizes stable isotopes selectively incorporated into the cross-linker design, allowing for isobaric cross-linked peptide pairs originat-ing from different samples to display distinct quantitative isotope signatures in tandem mass spectra. This enables improved quan-titation of cross-linked peptide levels from proteome-wide samples due to the reduced complexity of tandem mass spectra relative to MS1 spectra. In addition, because of the isotope incorporation in the reporter and the residual components of the cross-linker that remain on released peptides, each fragmentation spectrum can offer multiple independent opportunities and therefore, im-proved confidence for quantitative assessment of cross-linker pair level. Finally, in addition to providing information on solvent accessibility of lysine sites, dead end iqPIR cross-linked products can provide protein abundance and/or lysine site modification level information all from a single in vivo cross-linking experiment.
    DOI:  https://doi.org/10.1021/acs.analchem.0c03128
  12. Methods Mol Biol. 2021 ;2221 165-191
    Foxa GE, Liu Y, Turner LM, Robling AG, Yang T, Williams BO.
      Our laboratories have used genetically engineered mouse models (GEMMs) to assess genetic contributions to skeletal diseases such as osteoporosis and osteoarthritis. Studies on the genetic contributions to OA are often done by assessing how GEMMs respond to surgical methods that induce symptoms modeling OA. Here, we will describe protocols outlining the induction of experimental OA in mice as well as detailed descriptions of methods for analyzing skeletal phenotypes using micro-computerized tomography and skeletal histomorphometry.
    Keywords:  Histomorphometry; Osteoarthritis; microCT
    DOI:  https://doi.org/10.1007/978-1-0716-0989-7_11
  13. J Proteome Res. 2020 Sep 24.
    Tian S, Wang C, Li Y, Bao X, Zhang Y, Tang T.
      SlyA is an important transcriptional regulator in Salmonella Typhimurium (S. typhimurium). Numerous reports have indicated the impact of SlyA on the virulence of S. typhimurium. Less information regarding the role of SlyA in cell metabolism of S. typhimurium is available. To close this gap, we compared the growth kenitics of a S. typhimurium wild type strain to a slyA deletion mutant strain. The data suggested that the cell growth of S. typhimurium was impaired when slyA abolished, indicating that SlyA might affect the cell metabolism of S. typhimurium. To determine the role of SlyA in cell metabolism, we analyzed the metabolite profiles of S. typhimurium in the presence or absence of slyA, using gas chromatography coupled with tandem mass spectrometry (GC-MS-MS). With the aim of appropriately interpreting the results obtained from metabolomics, a transcriptomic analysis on both the wildtype S. typhimurium and the slyA deletion mutant was performed. The metabolome data indicated that several glycolysis and lipid metabolism-associated pathways, including the turnover of glycerolipid, pyruvate, butanoate and glycerophospholipid, were affected in the absence of slyA. In addition, the mRNA levels of several genes associated with glycolysis and lipid turnover were downregulated when slyA was deleted, including pagP, fadL, mgtB, iacp and yciA. Collectively, these evidences suggested that SlyA affects the glycolysis and lipid turnover of S. typhimurium at transcriptional level. The raw data of metabolomics is available in Metabolights database with access number of MTBLS1858. The raw data of transcriptome is available in SRA database with access number of PRJNA656165.
    DOI:  https://doi.org/10.1021/acs.jproteome.0c00281
  14. BMC Med Inform Decis Mak. 2020 Sep 24. 20(Suppl 9): 223
    Chen X, Zhu Y, Jijiwa M, Nasu M, Ai J, Dai S, Jiang B, Zhang J, Huang G, Deng Y.
      BACKGROUND: Prostate cancer is a very common and highly fatal in men. Current non-invasive detection methods like serum biomarker are unsatisfactory. Biomarkers with high accuracy for diagnostic of prostate cancer are urgently needed. Many lipid species have been found related to various cancers. The purpose of our study is to explore the diagnostic value of lipids for prostate cancer.RESULTS: Using triple quadruple liquid chromatography electrospray ionization tandem mass spectrometry, we performed lipidomics profiling of 367 lipids on a total 114 plasma samples from 30 patients with prostate cancer, 38 patients with benign prostatic hyperplasia (BPH), and 46 male healthy controls to evaluate the lipids as potential biomarkers in the diagnosis of prostate cancer. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway database was used to construct the potential mechanism pathway. After statistical analysis, five lipids were identified as a panel of potential biomarkers for the detection of prostate cancer between prostate cancer group and the BPH group; the sensitivity, specificity, and area under curve (AUC) of the combination of these five lipids were 73.3, 81.6%, and 0.800, respectively. We also identified another panel of five lipids in distinguishing between prostate cancer group and the control group with predictive values of sensitivity at 76.7%, specificity at 80.4%, and AUC at 0.836, respectively. The glycerophospholipid metabolism pathway of the selected lipids was considered as the target pathway.
    CONCLUSIONS: Our study indicated that the identified plasma lipid biomarkers have potential in the diagnosis of prostate cancer.
    Keywords:  Diagnosis; LC-ESI-MS/MS; Lipidomics; Metabolic pathway; Prostate cancer
    DOI:  https://doi.org/10.1186/s12911-020-01242-7
  15. Metabolites. 2020 Sep 21. pii: E378. [Epub ahead of print]10(9):
    Hemmer S, Manier SK, Fischmann S, Westphal F, Wagmann L, Meyer MR.
      The evaluation of liquid chromatography high-resolution mass spectrometry (LC-HRMS) raw data is a crucial step in untargeted metabolomics studies to minimize false positive findings. A variety of commercial or open source software solutions are available for such data processing. This study aims to compare three different data processing workflows (Compound Discoverer 3.1, XCMS Online combined with MetaboAnalyst 4.0, and a manually programmed tool using R) to investigate LC-HRMS data of an untargeted metabolomics study. Simple but highly standardized datasets for evaluation were prepared by incubating pHLM (pooled human liver microsomes) with the synthetic cannabinoid A-CHMINACA. LC-HRMS analysis was performed using normal- and reversed-phase chromatography followed by full scan MS in positive and negative mode. MS/MS spectra of significant features were subsequently recorded in a separate run. The outcome of each workflow was evaluated by its number of significant features, peak shape quality, and the results of the multivariate statistics. Compound Discoverer as an all-in-one solution is characterized by its ease of use and seems, therefore, suitable for simple and small metabolomic studies. The two open source solutions allowed extensive customization but particularly, in the case of R, made advanced programming skills necessary. Nevertheless, both provided high flexibility and may be suitable for more complex studies and questions.
    Keywords:  A-CHMINACA; LC-HRMS; data processing; feature detection; untargeted metabolomics
    DOI:  https://doi.org/10.3390/metabo10090378
  16. Nat Metab. 2020 Sep 21.
    de Kivit S, Mensink M, Hoekstra AT, Berlin I, Derks RJE, Both D, Aslam MA, Amsen D, Berkers CR, Borst J.
      Following activation, conventional T (Tconv) cells undergo an mTOR-driven glycolytic switch. Regulatory T (Treg) cells reportedly repress the mTOR pathway and avoid glycolysis. However, here we demonstrate that human thymus-derived Treg (tTreg) cells can become glycolytic in response to tumour necrosis factor receptor 2 (TNFR2) costimulation. This costimulus increases proliferation and induces a glycolytic switch in CD3-activated tTreg cells, but not in Tconv cells. Glycolysis in CD3-TNFR2-activated tTreg cells is driven by PI3-kinase-mTOR signalling and supports tTreg cell identity and suppressive function. In contrast to glycolytic Tconv cells, glycolytic tTreg cells do not show net lactate secretion and shuttle glucose-derived carbon into the tricarboxylic acid cycle. Ex vivo characterization of blood-derived TNFR2hiCD4+CD25hiCD127lo effector T cells, which were FOXP3+IKZF2+, revealed an increase in glucose consumption and intracellular lactate levels, thus identifying them as glycolytic tTreg cells. Our study links TNFR2 costimulation in human tTreg cells to metabolic remodelling, providing an additional avenue for drug targeting.
    DOI:  https://doi.org/10.1038/s42255-020-00271-w
  17. World J Hepatol. 2020 Aug 27. 12(8): 436-450
    Kartsoli S, Kostara CE, Tsimihodimos V, Bairaktari ET, Christodoulou DK.
      Non-alcoholic fatty liver disease (NAFLD), the most common chronic liver disorder in Western countries, comprises steatosis to nonalcoholic steatohepatitis (NASH), with the latter having the potential to progress to cirrhosis. The transition from isolated steatosis to NASH is still poorly understood, but lipidomics approach revealed that the hepatic lipidome is extensively altered in the setting of steatosis and steatohepatitis and these alterations correlate with disease progression. Recent data suggest that both quantity and quality of the accumulated lipids are involved in pathogenesis of NAFLD. Changes in glycerophospholipid, sphingolipid, and fatty acid composition have been described in both liver biopsies and plasma of patients with NAFLD, implicating that specific lipid species are involved in oxidative stress, inflammation, and cell death. In this article, we summarize the findings of main human lipidomics studies in NAFLD and delineate the currently available information on the pathogenetic role of each lipid class in lipotoxicity and disease progression.
    Keywords:  Ceramides; Fatty acids; Lipidomics; Lipotoxicity; Non-alcoholic fatty liver disease; Non-alcoholic steatohepatitis
    DOI:  https://doi.org/10.4254/wjh.v12.i8.436
  18. Nat Metab. 2020 Sep 21.
    Linke V, Overmyer KA, Miller IJ, Brademan DR, Hutchins PD, Trujillo EA, Reddy TR, Russell JD, Cushing EM, Schueler KL, Stapleton DS, Rabaglia ME, Keller MP, Gatti DM, Keele GR, Pham D, Broman KW, Churchill GA, Attie AD, Coon JJ.
      Despite the crucial roles of lipids in metabolism, we are still at the early stages of comprehensively annotating lipid species and their genetic basis. Mass spectrometry-based discovery lipidomics offers the potential to globally survey lipids and their relative abundances in various biological samples. To discover the genetics of lipid features obtained through high-resolution liquid chromatography-tandem mass spectrometry, we analysed liver and plasma from 384 diversity outbred mice, and quantified 3,283 molecular features. These features were mapped to 5,622 lipid quantitative trait loci and compiled into a public web resource termed LipidGenie. The data are cross-referenced to the human genome and offer a bridge between genetic associations in humans and mice. Harnessing this resource, we used genome-lipid association data as an additional aid to identify a number of lipids, for example gangliosides through their association with B4galnt1, and found evidence for a group of sex-specific phosphatidylcholines through their shared locus. Finally, LipidGenie's ability to query either mass or gene-centric terms suggests acyl-chain-specific functions for proteins of the ABHD family.
    DOI:  https://doi.org/10.1038/s42255-020-00278-3
  19. Hum Cell. 2020 Sep 26.
    Swayden M, Bekdash A, Fakhoury I, El-Atat O, Borjac-Natour J, El-Sibai M, Abi-Habib RJ.
      Deregulating cellular energetics by reprogramming metabolic pathways, including arginine metabolism, is critical for cancer cell onset and survival. Drugs that target the specific metabolic requirements of cancer cells have emerged as promising targeted cancer therapeutics. In this study, we investigate the therapeutic potential of targeting colon cancer cells using arginine deprivation induced by a pegylated cobalt-substituted recombinant human Arginase I [HuArgI (Co)-PEG5000]. Four colon cancer cell lines were tested for their sensitivity to [HuArgI (Co)-PEG5000] as well as for their mechanism of cell death following arginine deprivation. All four cell lines were sensitive to arginine deprivation induced by [HuArgI (Co)-PEG5000]. All cells expressed ASS1 and were rescued from arginine deprivation-induced cytotoxicity by the addition of excess L-citrulline, indicating they are partially auxotrophic for arginine. Mechanistically, cells treated with [HuArgI (Co)-PEG5000] were negative for AnnexinV and lacked caspase activation. Further investigation revealed that arginine deprivation leads to a marked and prolonged activation of autophagy in both Caco-2 and T84 cell lines. Finally, we show that [HuArgI (Co)-PEG5000] causes cell death by sustained activation of autophagy as evidenced by the decrease in cell cytotoxicity upon treatment with chloroquine, an autophagy inhibitor. Altogether, these data demonstrate that colon cancer cells are partially auxotrophic for arginine and sensitive to [HuArgI (Co)-PEG5000]-induced arginine deprivation. They also show that the activation of autophagy does not play protective roles but rather, induces cytotoxicity and leads to cell death.
    Keywords:  Arginine auxotrophy; Autophagy; Colorectal cancer; [HuArgI (co)-PEG5000]
    DOI:  https://doi.org/10.1007/s13577-020-00437-4
  20. J Proteome Res. 2020 Sep 25.
    Guerra ÂR, Soares BIG, Freire CSR, Silvestre AJD, Duarte MF, Duarte IF.
      In this work, untargeted metabolomics was used to unveil the impact of a Eucalyptus (E. nitens) lipophilic outer bark extract on the metabolism of triple negative breast cancer (TNBC) and non-tumour breast cells. Integrative analysis of culture medium, intracellular polar metabolites and cellular lipids provided a comprehensive picture of cells metabolic adaptations, which enabled several hypotheses about the metabolic targets and pathways affected to be proposed. One of the most marked effects in MDA-MB-231 breast cancer cells, upon 48h incubation with the E. nitens extract (15 µg/mL), comprised enhancement of the NAD+/NADH ratio, likely reflecting a shift to mitochondrial respiration, which appeared to be fuelled by amino acids and fatty acids resulting from hydrolysis of neutral lipids (triglycerides and cholesteryl esters). Contrastingly, in MCF-10A breast epithelial cells, the E. nitens extract appeared to intensify glycolysis and the TCA cycle (resulting in decreased NAD+/NADH ratio) and had no effect on the cells lipid composition. This knowledge contributes to improve current understanding of the biological activity of E. nitens bark extracts, and is potentially useful to promote their development in the field of TNBC anticancer therapy.
    DOI:  https://doi.org/10.1021/acs.jproteome.0c00559
  21. Cancer Metab. 2020 ;8 20
    Tait-Mulder J, Hodge K, Sumpton D, Zanivan S, Vazquez A.
      Background: Mitochondrial serine catabolism to formate induces a metabolic switch to a hypermetabolic state with high rates of glycolysis, purine synthesis and pyrimidine synthesis. While formate is a purine precursor, it is not clear how formate induces pyrimidine synthesis.Methods: Here we combine phospho-proteome and metabolic profiling to determine how formate induces pyrimidine synthesis.
    Results: We discover that formate induces phosphorylation of carbamoyl phosphate synthetase (CAD), which is known to increase CAD enzymatic activity. Mechanistically, formate induces mechanistic target of rapamycin complex 1 (mTORC1) activity as quantified by phosphorylation of its targets S6, 4E-BP1, S6K1 and CAD. Treatment with the allosteric mTORC1 inhibitor rapamycin abrogates CAD phosphorylation and pyrimidine synthesis induced by formate. Furthermore, we show that the formate-dependent induction of mTOR signalling and CAD phosphorylation is dependent on an increase in purine synthesis.
    Conclusions: We conclude that formate activates mTORC1 and induces pyrimidine synthesis via the mTORC1-dependent phosphorylation of CAD.
    DOI:  https://doi.org/10.1186/s40170-020-00228-3
  22. Nat Rev Cancer. 2020 Sep 21.
    Möller A, Lobb RJ.
      Cancer-derived extracellular vesicles (EVs) are regarded as having promising potential to be used as therapeutics and disease biomarkers. Mechanistically, EVs have been shown to function in most, if not all, steps of cancer progression. Cancer EVs, including small EVs (sEVs), contain unique biomolecular cargo, consisting of protein, nucleic acid and lipids. Through progress in the identification of this specific cargo, cancer biomarkers have been identified and developed, opening up novel and interesting opportunities for cancer diagnosis and prognosis. Intriguingly, we still lack a comprehensive understanding of the cancer-specific pathways that govern EV biogenesis in cancer cells. Filling this knowledge gap will rapidly improve cancer EV biomarkers, as it will also allow discrimination of the procancer and anticancer actions of those EVs. Even more promising is uncovering therapeutically targetable, tumour-specific EV pathways and content, which will generate novel classes of cancer therapies. This Review highlights the progress the cancer sEV field has made in the areas of biomarker discovery and validation as well as sEV-based therapeutics, highlights the challenges we are facing and identifies gaps in our knowledge, which currently prevent us from developing the full potential of sEVs in cancer diagnostic and therapy.
    DOI:  https://doi.org/10.1038/s41568-020-00299-w
  23. Metabolites. 2020 Sep 19. pii: E375. [Epub ahead of print]10(9):
    Panzenboeck L, Troppmair N, Schlachter S, Koellensperger G, Hartler J, Rampler E.
      Glycosyl inositol phospho ceramides (GIPCs) are the major sphingolipids on earth, as they account for a considerable fraction of the total lipids in plants and fungi, which in turn represent a large portion of the biomass on earth. Despite their obvious importance, GIPC analysis remains challenging due to the lack of commercial standards and automated annotation software. In this work, we introduce a novel GIPC glycolipidomics workflow based on reversed-phase ultra-high pressure liquid chromatography coupled to high-resolution mass spectrometry. For the first time, automated GIPC assignment was performed using the open-source software Lipid Data Analyzer (LDA), based on platform-independent decision rules. Four different plant samples (salad, spinach, raspberry, and strawberry) were analyzed and the results revealed 64 GIPCs based on accurate mass, characteristic MS2 fragments and matching retention times. Relative quantification using lactosyl ceramide for internal standardization revealed GIPC t18:1/h24:0 as the most abundant species in all plants. Depending on the plant sample, GIPCs contained mainly amine, N-acetylamine or hydroxyl residues. Most GIPCs revealed a Hex-HexA-IPC core and contained a ceramide part with a trihydroxylated t18:0 or a t18:1 long chain base and hydroxylated fatty acid chains ranging from 16 to 26 carbon atoms in length (h16:0-h26:0). Interestingly, four GIPCs containing t18:2 were observed in the raspberry sample, which was not reported so far. The presented workflow supports the characterization of different plant samples by automatic GIPC assignment, potentially leading to the identification of new GIPCs. For the first time, automated high-throughput profiling of these complex glycolipids is possible by liquid chromatography-high-resolution tandem mass spectrometry and subsequent automated glycolipid annotation based on decision rules.
    Keywords:  GIPC; LC-MS; Lipid Data Analyzer; automated annotation; glycolipidomics; glycosyl inositol phospho ceramides; high-resolution mass spectrometry; lipidomics; sphingolipids; ultra-high pressure liquid chromatography
    DOI:  https://doi.org/10.3390/metabo10090375
  24. Cancer Metab. 2020 ;8 19
    Sharma N, Bhushan A, He J, Kaushal G, Bhardwaj V.
      Pancreatic ductal adenocarcinoma (PDAC) is one of the most malignant forms of cancer. Lack of effective treatment options and drug resistance contributes to the low survival among PDAC patients. In this study, we investigated the metabolic alterations in pancreatic cancer cells that do not respond to the EGFR inhibitor erlotinib. We selected erlotinib-resistant pancreatic cancer cells from MiaPaCa2 and AsPC1 cell lines. Metabolic profiling of erlotinib-resistant cells revealed a significant downregulation of glycolytic activity and reduced level of glycolytic metabolites compared to the sensitive cells. The resistant cells displayed elevated expression of the pentose phosphate pathway (PPP) enzymes involved in ROS regulation and nucleotide biosynthesis. The enhanced PPP elevated cellular NADPH/NADP+ ratio and protected the cells from reactive oxygen species (ROS)-induced damage. Inhibition of PPP using 6-aminonicotinamide (6AN) elevated ROS levels, induced G1 cell cycle arrest, and sensitized resistant cells to erlotinib. Genetic studies identified elevated PPP enzyme glucose-6-phosphate dehydrogenase (G6PD) as an important contributor to erlotinib resistance. Mechanistically, our data showed that upregulation of inhibitor of differentiation (ID1) regulates G6PD expression in resistant cells thus contributing to altered metabolic phenotype and reduced response to erlotinib. Together, our results highlight an underlying role of tumor metabolism in PDAC drug response and identify G6PD as a target to overcome drug resistance.
    Keywords:  Erlotinib resistance; Metabolic reprogramming; Pancreatic cancer
    DOI:  https://doi.org/10.1186/s40170-020-00226-5
  25. Front Oncol. 2020 ;10 1561
    Birkeland ES, Koch LM, Dechant R.
      To adjust cell growth and proliferation to changing environmental conditions or developmental requirements, cells have evolved a remarkable network of signaling cascades that integrates cues from cellular metabolism, growth factor availability and a large variety of stresses. In these networks, cellular information flow is mostly mediated by posttranslational modifications, most notably phosphorylation, or signaling molecules such as GTPases. Yet, a large body of evidence also implicates cytosolic pH (pHc) as a highly conserved cellular signal driving cell growth and proliferation, suggesting that pH-dependent protonation of specific proteins also regulates cellular signaling. In mammalian cells, pHc is regulated by growth factor derived signals and responds to metabolic cues in response to glucose stimulation. Importantly, high pHc has also been identified as a hall mark of cancer, but mechanisms of pH regulation in cancer are only poorly understood. Here, we discuss potential mechanisms of pH regulation with emphasis on metabolic signals regulating pHc by Na+/H+-exchangers. We hypothesize that elevated NHE activity and pHc in cancer are a direct consequence of the metabolic adaptations in tumor cells including enhanced aerobic glycolysis, generally referred to as the Warburg effect. This hypothesis not only provides an explanation for the growth advantage conferred by a switch to aerobic glycolysis beyond providing precursors for accumulation of biomass, but also suggests that treatments targeting pH regulation as a potential anti-cancer therapy may effectively target the result of altered tumor cell metabolism.
    Keywords:  Na+/H+-exchanger; aerobic glycolysis; cytosolic pH; growth and proliferation; metabolism
    DOI:  https://doi.org/10.3389/fonc.2020.01561
  26. J Proteome Res. 2020 Sep 25.
    Zhang R, Engel AL, Wang Y, Li B, Shen W, Gillies MC, Chao JR, Du J.
      Mitochondrial respiration in mammalian cells not only generates ATP to meet their own energy needs but also couples with biosynthetic pathways to produce metabolites that can be exported to support neighboring cells. However, how defects in mitochondrial respiration influence these biosynthetic and exporting pathways remains poorly understood. Mitochondrial dysfunction in retinal pigment epithelium (RPE) cells is an emerging contributor to the death of their neighboring photoreceptors in degenerative retinal diseases including age-related macular degeneration. In this study, we used targeted-metabolomics and 13C tracing to investigate how inhibition of mitochondrial respiration influences the intracellular and extracellular metabolome. We found inhibition of mitochondrial respiration strikingly influenced both the intracellular and extracellular metabolome in primary RPE cells. Intriguingly, the extracellular metabolic changes sensitively reflected the intracellular changes. These changes included substantially enhanced glucose consumption and lactate production; reduced release of pyruvate, citrate, and ketone bodies; and massive accumulation of multiple amino acids and nucleosides. In conclusion, these findings reveal a metabolic signature of nutrient consumption and release in mitochondrial dysfunction in RPE cells. Testing medium metabolites provides a sensitive and noninvasive method to assess mitochondrial function in nutrient utilization and transport.
    Keywords:  amino acids; glucose; ketone bodies; metabolism; metabolites; mitochondrial respiration; nucleotides; retinal pigment epithelium
    DOI:  https://doi.org/10.1021/acs.jproteome.0c00690
  27. Bioanalysis. 2020 Sep 25.
    de Jong KA, van Breugel SJ, Hillebrand MJ, Rosing H, Huitema AD, Beijnen JH.
      Therapeutic monoclonal antibodies (mAbs) are rapidly taking over the treatment of many malignancies, and an astonishing number of mAbs is in development. This causes a high demand for quantification of mAbs in biomatrices both for measuring therapeutic mAb concentrations and to support pharmacokinetics and pharmacodynamics studies. Conventionally, ligand-binding assays are used for these purposes, but LC-MS is gaining popularity. Although intact (top-down) and subunit (middle-down) mAb quantification is reported, signature peptide (bottom-up) quantification is currently most advantageous. This review provides an overview of the reported bottom-up mAb quantification methods in biomatrices as well as general recommendations regarding signature peptide and internal standard selection, reagent use and optimization of digestion in bottom-up quantification methods.
    Keywords:  bottom-up; mass spectrometry; monoclonal antibodies; oncology; sample preparation; signature peptide
    DOI:  https://doi.org/10.4155/bio-2020-0204