bims-mascan Biomed News
on Mass spectrometry in cancer research
Issue of 2020‒08‒02
twenty papers selected by
Giovanny Rodriguez Blanco
University of Edinburgh
  1. Lipids and cancer: Emerging roles in pathogenesis, diagnosis and therapeutic intervention.
  2. Targeting metabolic vulnerabilities of cancer: Small molecule inhibitors in clinic.
  3. Generating Proteomic Big Data for Precision Medicine.
  4. Dynamic Flux Analysis: An Experimental Approach of Fluxomics.
  5. Strategies to enable large-scale proteomics for reproducible research.
  6. Comparative Untargeted Metabolomics Analysis of the Psychostimulants 3,4-Methylenedioxy-Methamphetamine (MDMA), Amphetamine, and the Novel Psychoactive Substance Mephedrone after Controlled Drug Administration to Humans.
  7. Analytical challenges of shotgun lipidomics at different resolution of measurements.
  8. Purine metabolism regulates DNA repair and therapy resistance in glioblastoma.
  9. The hepatocyte clock and feeding control chronophysiology of multiple liver cell types.
  10. Phytochemical Targeting of STAT3 Orchestrated Lipid Metabolism in Therapy-Resistant Cancers.
  11. Cholesterol as an Endogenous Ligand of ERRα Promotes ERRα-Mediated Cellular Proliferation and Metabolic Target Gene Expression in Breast Cancer Cells.
  12. Value of Urine Peptides in Assessing Kidney and Cardiovascular Disease.
  13. Dihydroxyacetone phosphate signals glucose availability to mTORC1.
  14. Lipid composition of the cancer cell membrane.
  15. Metabolomic and transcriptomic signatures of prenatal excessive methionine support nature rather than nurture in schizophrenia pathogenesis.
  16. Metabolic perturbations prior to hepatocellular carcinoma diagnosis - Findings from a prospective observational cohort study.
  17. Regulation of cancer cell glucose metabolism is determinant for cancer cell fate after melatonin administration.
  18. Evaluating a targeted multiple reaction monitoring approach to global untargeted lipidomic analyses of human plasma.
  19. Long-chain fatty acyl-CoA esters regulate metabolism via allosteric control of AMPK β1 isoforms.
  20. Quantification of common and planar bile acids aids in tissues and cultured cells.
  1. Adv Drug Deliv Rev. 2020 Jul 22. pii: S0169-409X(20)30097-1. [Epub ahead of print]
    Lipids and cancer: Emerging roles in pathogenesis, diagnosis and therapeutic intervention.
    Lisa Butler, Ylenia Perone, Jonas Dehairs, Leslie E Lupien, Vincent de Laat, Ali Talebi, Massimo Loda, William B Kinlaw, Johannes V Swinnen.
      With the advent of effective tools to study lipids, including mass spectrometry-based lipidomics, lipids are emerging as central players in cancer biology. Lipids function as essential building blocks for membranes, serve as fuel to drive energy-demanding processes and play a key role as signaling molecules and as regulators of numerous cellular functions. Not unexpectedly, cancer cells, as well as other cell types in the tumor microenvironment, exploit various ways to acquire lipids and extensively rewire their metabolism as part of a plastic and context-dependent metabolic reprogramming that is driven by both oncogenic and environmental cues. The resulting changes in the fate and composition of lipids help cancer cells to thrive in a changing microenvironment by supporting key oncogenic functions and cancer hallmarks, including cellular energetics, promoting feedforward oncogenic signaling, resisting oxidative and other stresses, regulating intercellular communication and immune responses. Supported by the close connection between altered lipid metabolism and the pathogenic process, specific lipid profiles are emerging as unique disease biomarkers, with diagnostic, prognostic and predictive potential. Multiple pre-clinical studies illustrate the translational promise of exploiting lipid metabolism in cancer, and critically, have shown context dependent actionable vulnerabilities that can be rationally targeted, particularly in combinatorial approaches. Moreover, lipids themselves can be used as membrane disrupting agents or as key components of nanocarriers of various therapeutics. With a number of pre-clinical compounds and strategies that are approaching clinical trials, we are at the doorstep of exploiting a hitherto underappreciated hallmark of cancer and promising target in the oncologist's strategy to combat cancer.
    Keywords:  De novo lipogenesis; Fatty acid synthesis; Fatty acids; Lipid droplets; Lipid uptake; Lipidomics; Membrane lipids; Reactive oxygen species
    DOI:  https://doi.org/10.1016/j.addr.2020.07.013
  2. Cancer Rep (Hoboken). 2019 Feb;2(1): e1131
    Targeting metabolic vulnerabilities of cancer: Small molecule inhibitors in clinic.
    Satyendra C Tripathi, Johannes F Fahrmann, Jody V Vykoukal, Jennifer B Dennison, Samir M Hanash.
      BACKGROUND: Altered cell metabolism is an established hallmark of cancer. Advancement in our understanding of dysregulated cellular metabolism has aided drastically in identifying metabolic vulnerabilities that can be exploited therapeutically. Indeed, this knowledge has led to the development of a multitude of agents targeting various aspects of tumor metabolism.RECENT FINDINGS: The intent of this review is to provide insight into small molecule inhibitors that target tumor metabolism and that are currently being explored in active clinical trials as either preventive, stand-alone, or adjuvant therapies for various malignancies. For each inhibitor, we outline the mechanism (s) of action, preclinical/clinical findings, and limitations. Sections are divided into three aspects based on the primary target of the small molecule inhibitor (s): those that impact (1) cancer cells directly, (2) immune cells present in the tumor microenvironment, or (3) both cancer cells and immune cells. We highlight small molecule targeting of metabolic pathways including de novo fatty acid synthesis, NAD+ biosynthesis, 2-hydroxyglutarate biosynthesis, polyamine metabolism, the kynurenine pathway, as well as glutamine and arginine metabolism.
    CONCLUSIONS: Use of small molecule inhibitors aimed at exploiting tumor metabolic vulnerabilities continues to be an active area of research. Identifying metabolic dependencies specific to cancer cells and/or constituents of the tumor microenvironment is a viable area of therapeutic intervention that holds considerable clinical potential.
    Keywords:  cancer; clinical trials; metabolic vulnerability; metabolism; small molecule inhibitors; targeted therapy
    DOI:  https://doi.org/10.1002/cnr2.1131
  3. Proteomics. 2020 Jul 29. e1900358
    Generating Proteomic Big Data for Precision Medicine.
    Yue Liang, Fangfei Zhang, Rui Sun, Yaoting Sun, Chunhui Yuan, Yi Zhu, Tiannan Guo.
      Here we reason that the complexity of medical problems and proteome science might be tackled effectively with deep learning (DL) technology. However, deployment of DL for proteomics data requires the acquisition of data sets from large number of samples. Based on the success of DL in medical imaging classification, proteome data from thousands of samples are arguably the minimal input for DL. Contemporary proteomics is turning high-throughput thanks to the rapid progresses of sample preparation and liquid chromatography mass spectrometry (LC-MS) methods. In particular, data-independent acquisition (DIA) now enables generation of hundreds to thousands of quantitative proteome maps from clinical specimens in clinical cohorts with only limited sample amounts in clinical cohorts. Upheavals in the design of large-scale clinical proteomics studies might be required to generate proteomic big data and deploy DL to tackle complex medical problems. This article is protected by copyright. All rights reserved.
    Keywords:  Clinical cohort; Data-independent acquisition; Deep learning; High-throughput proteomics; Precision medicine; Proteomic big data
    DOI:  https://doi.org/10.1002/pmic.201900358
  4. Methods Mol Biol. 2020 ;2096 179-196
    Dynamic Flux Analysis: An Experimental Approach of Fluxomics.
    Wei Xiong, Huaiguang Jiang, PinChing Maness.
      Metabolic flux analysis represents an essential perspective to understand cellular physiology and offers quantitative information to guide pathway engineering. A valuable approach for experimental elucidation of metabolic flux is dynamic flux analysis, which estimates the relative or absolute flow rates through a series of metabolic intermediates in a given pathway. It is based on kinetic isotope labeling experiments, liquid chromatography-mass spectrometry (LC-MS), and computational analysis that relate kinetic isotope trajectories of metabolites to pathway activity. Herein, we illustrate the mathematic principles underlying the dynamic flux analysis and mainly focus on describing the experimental procedures for data generation. This protocol is exemplified using cyanobacterial metabolism as an example, for which reliable labeling data for central carbon metabolites can be acquired quantitatively. This protocol is applicable to other microbial systems as well and can be readily adapted to address different metabolic processes.
    Keywords:  Cell harvesting; Dynamic flux analysis; Experimental metabolomics; Isotope tracer; LC-MS; Metabolic flux; Quenching
    DOI:  https://doi.org/10.1007/978-1-0716-0195-2_14
  5. Nat Commun. 2020 Jul 30. 11(1): 3793
    Strategies to enable large-scale proteomics for reproducible research.
    Rebecca C Poulos, Peter G Hains, Rohan Shah, Natasha Lucas, Dylan Xavier, Srikanth S Manda, Asim Anees, Jennifer M S Koh, Sadia Mahboob, Max Wittman, Steven G Williams, Erin K Sykes, Michael Hecker, Michael Dausmann, Merridee A Wouters, Keith Ashman, Jean Yang, Peter J Wild, Anna deFazio, Rosemary L Balleine, Brett Tully, Ruedi Aebersold, Terence P Speed, Yansheng Liu, Roger R Reddel, Phillip J Robinson, Qing Zhong.
      Reproducible research is the bedrock of experimental science. To enable the deployment of large-scale proteomics, we assess the reproducibility of mass spectrometry (MS) over time and across instruments and develop computational methods for improving quantitative accuracy. We perform 1560 data independent acquisition (DIA)-MS runs of eight samples containing known proportions of ovarian and prostate cancer tissue and yeast, or control HEK293T cells. Replicates are run on six mass spectrometers operating continuously with varying maintenance schedules over four months, interspersed with ~5000 other runs. We utilise negative controls and replicates to remove unwanted variation and enhance biological signal, outperforming existing methods. We also design a method for reducing missing values. Integrating these computational modules into a pipeline (ProNorM), we mitigate variation among instruments over time and accurately predict tissue proportions. We demonstrate how to improve the quantitative analysis of large-scale DIA-MS data, providing a pathway toward clinical proteomics.
    DOI:  https://doi.org/10.1038/s41467-020-17641-3
  6. Metabolites. 2020 Jul 27. pii: E306. [Epub ahead of print]10(8):
    Comparative Untargeted Metabolomics Analysis of the Psychostimulants 3,4-Methylenedioxy-Methamphetamine (MDMA), Amphetamine, and the Novel Psychoactive Substance Mephedrone after Controlled Drug Administration to Humans.
    Andrea E Steuer, Daria Kaelin, Martina I Boxler, Lisa Eisenbeiss, Friederike Holze, Patrick Vizeli, Joanna Czerwinska, Paul I Dargan, Vincenzo Abbate, Matthias E Liechti, Thomas Kraemer.
      Psychoactive stimulants are a popular drug class which are used recreationally. Over the last decade, large numbers of new psychoactive substances (NPS) have entered the drug market and these pose a worldwide problem to human health. Metabolomics approaches are useful tools for simultaneous detection of endogenous metabolites affected by drug use. They allow identification of pathways or characteristic metabolites, which might support the understanding of pharmacological actions or act as indirect biomarkers of consumption behavior or analytical detectability. Herein, we performed a comparative metabolic profiling of three psychoactive stimulant drugs 3,4-methylenedioxymethamphetamine (MDMA), amphetamine and the NPS mephedrone by liquid chromatography-high resolution mass spectrometry (LC-HRMS) in order to identify common pathways or compounds. Plasma samples were obtained from controlled administration studies to humans. Various metabolites were identified as increased or decreased based on drug intake, mainly belonging to energy metabolism, steroid biosynthesis and amino acids. Linoleic acid and pregnenolone-sulfate changed similarly in response to intake of all drugs. Overall, mephedrone produced a profile more similar to that of amphetamine than MDMA in terms of affected energy metabolism. These data can provide the basis for further in-depth targeted metabolome studies on pharmacological actions and search for biomarkers of drug use.
    Keywords:  LC-HRMS; MDMA; amphetamine; mephedrone; psychoactive stimulants; untargeted metabolomics
    DOI:  https://doi.org/10.3390/metabo10080306
  7. Trends Analyt Chem. 2019 Dec;pii: 115697. [Epub ahead of print]121
    Analytical challenges of shotgun lipidomics at different resolution of measurements.
    Jianing Wang, Xianlin Han.
      The essence of shotgun lipidomics is to maintain consistency of the chemical environment of lipid samples during mass spectrometry acquisition. This strategy is suitable for large-scale quantitative analysis. This strategy also allows sufficient time to collect data to improve the signal-to-noise ratio. The initial approach of shotgun lipidomics was the electrospray ionization (ESI)-based direct infusion mass spectrometry strategy. With development of mass spectrometry for small molecules, shotgun lipidomics methods have been extended to matrix-assisted laser desorption/ionization mass spectrometry (MALDI MS) and ambient mass spectrometry, including MS imaging methods. Furthermore, the object of analysis has extended from organ and body fluid levels to tissue and cell levels with technological developments. In this article, we summarize the status and technical challenges of shotgun lipidomics at different resolution of measurements from the mass spectrometry perspective.
    Keywords:  High resolution mass spectrometry; Lipidomics; Mass spectrometry imaging; Shotgun lipidomics; Single-cell analysis
    DOI:  https://doi.org/10.1016/j.trac.2019.115697
  8. Nat Commun. 2020 Jul 30. 11(1): 3811
    Purine metabolism regulates DNA repair and therapy resistance in glioblastoma.
    Weihua Zhou, Yangyang Yao, Andrew J Scott, Kari Wilder-Romans, Joseph J Dresser, Christian K Werner, Hanshi Sun, Drew Pratt, Peter Sajjakulnukit, Shuang G Zhao, Mary Davis, Barbara S Nelson, Christopher J Halbrook, Li Zhang, Francesco Gatto, Yoshie Umemura, Angela K Walker, Maureen Kachman, Jann N Sarkaria, Jianping Xiong, Meredith A Morgan, Alnawaz Rehemtualla, Maria G Castro, Pedro Lowenstein, Sriram Chandrasekaran, Theodore S Lawrence, Costas A Lyssiotis, Daniel R Wahl.
      Intratumoral genomic heterogeneity in glioblastoma (GBM) is a barrier to overcoming therapy resistance. Treatments that are effective independent of genotype are urgently needed. By correlating intracellular metabolite levels with radiation resistance across dozens of genomically-distinct models of GBM, we find that purine metabolites, especially guanylates, strongly correlate with radiation resistance. Inhibiting GTP synthesis radiosensitizes GBM cells and patient-derived neurospheres by impairing DNA repair. Likewise, administration of exogenous purine nucleosides protects sensitive GBM models from radiation by promoting DNA repair. Neither modulating pyrimidine metabolism nor purine salvage has similar effects. An FDA-approved inhibitor of GTP synthesis potentiates the effects of radiation in flank and orthotopic patient-derived xenograft models of GBM. High expression of the rate-limiting enzyme of de novo GTP synthesis is associated with shorter survival in GBM patients. These findings indicate that inhibiting purine synthesis may be a promising strategy to overcome therapy resistance in this genomically heterogeneous disease.
    DOI:  https://doi.org/10.1038/s41467-020-17512-x
  9. Science. 2020 Jul 30. pii: eaba8984. [Epub ahead of print]
    The hepatocyte clock and feeding control chronophysiology of multiple liver cell types.
    Dongyin Guan, Ying Xiong, Trang Minh Trinh, Yang Xiao, Wenxiang Hu, Chunjie Jiang, Pieterjan Dierickx, Cholsoon Jang, Joshua D Rabinowitz, Mitchell A Lazar.
      Most cells of the body contain molecular clocks, but the requirement of peripheral clocks for rhythmicity, and their effects on physiology, are not well understood. Here we show that deletion of core clock components REV-ERBα and β in adult mouse hepatocytes disrupted diurnal rhythms of a subset of liver genes and altered the diurnal rhythm of de novo lipogenesis. Liver function is also influenced by non-hepatocytic cells, and the loss of hepatocyte REV-ERBs remodeled the rhythmic transcriptomes and metabolomes of multiple cell types within the liver. Finally, alteration of food availability demonstrated the hierarchy of the cell-intrinsic hepatocyte clock mechanism and the feeding environment. Together, these studies reveal previously unsuspected roles of the hepatocyte clock in the physiological coordination of nutritional signals and cell-cell communication controlling rhythmic metabolism.
    DOI:  https://doi.org/10.1126/science.aba8984
  10. Biomolecules. 2020 Jul 28. pii: E1118. [Epub ahead of print]10(8):
    Phytochemical Targeting of STAT3 Orchestrated Lipid Metabolism in Therapy-Resistant Cancers.
    Carmen Tse, Ashleigh Warner, Rufaik Farook, James G Cronin.
      Lipids are critical for maintaining homeostasis and cellular metabolism. However, the dysregulation of lipid metabolism contributes to the pathogenesis of chronic inflammatory diseases and is a hallmark of several cancer types. Tumours exist in a microenvironment of poor vascularization-depleted oxygen and restricted nutrients. Under these conditions, tumours have been shown to increasingly depend on the metabolism of fatty acids for sustained proliferation and survival. Signal transducer and activator of transcription 3 (STAT3) plays a key role in cellular processes such as cell growth, apoptosis and lipid metabolism. Aberrant STAT3 activity, as seen in several cancer types, is associated with tumour progression and malignancy, in addition to propagating crosstalk between tumour cells and the microenvironment. Furthermore, STAT3-regulated lipid metabolism is critical for cancer stem cell self-renewal and therapy resistance. Plant-derived compounds known as phytochemicals are a potential source for novel cancer therapeutic drugs. Dietary phytochemicals are known to modulate key cellular signalling pathways involved in lipid homeostasis and metabolism, including the STAT3 signalling pathways. Targeting STAT3 orchestrated lipid metabolism has shown therapeutic promise in human cancer models. In this review, we summarize the antitumour activity of phytochemicals with an emphasis placed on their effect on STAT3-regulated lipid metabolism and their role in abrogating therapy resistance.
    Keywords:  STAT3; cancer; lipids; phytochemical
    DOI:  https://doi.org/10.3390/biom10081118
  11. Cells. 2020 Jul 23. pii: E1765. [Epub ahead of print]9(8):
    Cholesterol as an Endogenous Ligand of ERRα Promotes ERRα-Mediated Cellular Proliferation and Metabolic Target Gene Expression in Breast Cancer Cells.
    Faegheh Ghanbari, Sylvie Mader, Anie Philip.
      Breast cancer is the 2nd leading cause of cancer-related death among women. Increased risk of breast cancer has been associated with high dietary cholesterol intake. However, the underlying mechanisms are not known. The nuclear receptor, estrogen-related receptor alpha (ERRα), plays an important role in breast cancer cell metabolism, and its overexpression has been linked to poor survival. Here we identified cholesterol as an endogenous ligand of ERRα by purification from human pregnancy serum using a GST-ERRα affinity column and liquid chromatography-tandem mass spectrometry (LC-MS/MS). We show that cholesterol interacts with ERRα and induces its transcriptional activity in estrogen receptor positive (ER+) and triple negative breast cancer (TNBC) cells. In addition, we show that cholesterol enhances ERRα-PGC-1α interaction, induces ERRα expression itself, augments several metabolic target genes of ERRα, and increases cell proliferation and migration in both ER+ and TNBC cells. Furthermore, the stimulatory effect of cholesterol on metabolic gene expression, cell proliferation, and migration requires the ERRα pathway. These findings provide a mechanistic explanation for the increased breast cancer risk associated with high dietary cholesterol and possibly the pro-survival effect of statins in breast cancer patients, highlighting the clinical relevance of lowering cholesterol levels in breast cancer patients overexpressing ERRα.
    Keywords:  breast cancer; cholesterol; estrogen related receptor α; human pregnancy serum; statins
    DOI:  https://doi.org/10.3390/cells9081765
  12. Proteomics Clin Appl. 2020 Jul 25. e2000027
    Value of Urine Peptides in Assessing Kidney and Cardiovascular Disease.
    Agnieszka Latosinska, Justyna Siwy, Stanislas Faguer, Joachim Beige, Harald Mischak, Joost P Schanstra.
      Urinary peptides gained significant attention as potential biomarkers especially in the context of kidney and cardiovascular disease. In this manuscript the recent literature since 2015 on urinary peptide investigation in human kidney and cardiovascular disease is reviewed. The technology most commonly used in this context is capillary electrophoresis coupled mass spectrometry, in part owed to the large database available and the well-defined dataspace. Several studies based on over 1000 subjects were reported in the recent past, especially examining CKD273, a classifier for assessment of chronic kidney disease based on 273 urine peptides. Interestingly, the most abundant urinary peptides are generally collagen fragments, which may have gone undetected for some time as they are typically modified via proline hydroxylation. The data available suggest that urinary peptides specifically depict inflammation and fibrosis, and may serve as a non-invasive tool to assess fibrosis, which appears to be a key driver in kidney and cardiovascular disease. The recent successful completion of the first urinary peptide guided intervention trial, PRIORITY, is expected to further spur clinical application of urinary peptidomics, aiming especially at early detection of chronic diseases, prediction of progression and prognosis of drug response. This article is protected by copyright. All rights reserved.
    Keywords:  biomarker; cardiovascular disease; kidney disease; peptide; urine
    DOI:  https://doi.org/10.1002/prca.202000027
  13. Nat Metab. 2020 Jul 27.
    Dihydroxyacetone phosphate signals glucose availability to mTORC1.
    Jose M Orozco, Patrycja A Krawczyk, Sonia M Scaria, Andrew L Cangelosi, Sze Ham Chan, Tenzin Kunchok, Caroline A Lewis, David M Sabatini.
      The mechanistic target of rapamycin complex 1 (mTORC1) kinase regulates cell growth by setting the balance between anabolic and catabolic processes. To be active, mTORC1 requires the environmental presence of amino acids and glucose. While a mechanistic understanding of amino acid sensing by mTORC1 is emerging, how glucose activates mTORC1 remains mysterious. Here, we used metabolically engineered human cells lacking the canonical energy sensor AMP-activated protein kinase to identify glucose-derived metabolites required to activate mTORC1 independent of energetic stress. We show that mTORC1 senses a metabolite downstream of the aldolase and upstream of the GAPDH-catalysed steps of glycolysis and pinpoint dihydroxyacetone phosphate (DHAP) as the key molecule. In cells expressing a triose kinase, the synthesis of DHAP from DHA is sufficient to activate mTORC1 even in the absence of glucose. DHAP is a precursor for lipid synthesis, a process under the control of mTORC1, which provides a potential rationale for the sensing of DHAP by mTORC1.
    DOI:  https://doi.org/10.1038/s42255-020-0250-5
  14. J Bioenerg Biomembr. 2020 Jul 26.
    Lipid composition of the cancer cell membrane.
    Wojciech Szlasa, Iga Zendran, Aleksandra Zalesińska, Mounir Tarek, Julita Kulbacka.
      Cancer cell possesses numerous adaptations to resist the immune system response and chemotherapy. One of the most significant properties of the neoplastic cells is the altered lipid metabolism, and consequently, the abnormal cell membrane composition. Like in the case of phosphatidylcholine, these changes result in the modulation of certain enzymes and accumulation of energetic material, which could be used for a higher proliferation rate. The changes are so prominent, that some lipids, such as phosphatidylserines, could even be considered as the cancer biomarkers. Additionally, some changes of biophysical properties of cell membranes lead to the higher resistance to chemotherapy, and finally to the disturbances in signalling pathways. Namely, the increased levels of certain lipids, like for instance phosphatidylserine, lead to the attenuation of the immune system response. Also, changes in lipid saturation prevent the cells from demanding conditions of the microenvironment. Particularly interesting is the significance of cell membrane cholesterol content in the modulation of metastasis. This review paper discusses the roles of each lipid type in cancer physiology. The review combined theoretical data with clinical studies to show novel therapeutic options concerning the modulation of cell membranes in oncology.
    Keywords:  Cancer cells; Lipid membrane; Membrane composition
    DOI:  https://doi.org/10.1007/s10863-020-09846-4
  15. Commun Biol. 2020 Jul 30. 3(1): 409
    Metabolomic and transcriptomic signatures of prenatal excessive methionine support nature rather than nurture in schizophrenia pathogenesis.
    Siwei Chen, Wedad Alhassen, Ryan Yoshimura, Angele De Silva, Geoffrey W Abbott, Pierre Baldi, Amal Alachkar.
      The imbalance of prenatal micronutrients may perturb one-carbon (C1) metabolism and increase the risk for neuropsychiatric disorders. Prenatal excessive methionine (MET) produces in mice behavioral phenotypes reminiscent of human schizophrenia. Whether in-utero programming or early life caregiving mediate these effects is, however, unknown. Here, we show that the behavioral deficits of MET are independent of the early life mother-infant interaction. We also show that MET produces in early life profound changes in the brain C1 pathway components as well as glutamate transmission, mitochondrial function, and lipid metabolism. Bioinformatics analysis integrating metabolomics and transcriptomic data reveal dysregulations of glutamate transmission and lipid metabolism, and identify perturbed pathways of methylation and redox reactions. Our transcriptomics Linkage analysis of MET mice and schizophrenia subjects reveals master genes involved in inflammation and myelination. Finally, we identify potential metabolites as early biomarkers for neurodevelopmental defects and suggest therapeutic targets for schizophrenia.
    DOI:  https://doi.org/10.1038/s42003-020-01124-8
  16. Int J Cancer. 2020 Jul 31.
    Metabolic perturbations prior to hepatocellular carcinoma diagnosis - Findings from a prospective observational cohort study.
    Magdalena Stepien, Pekka Keski-Rahkonen, Agneta Kiss, Nivonirina Robinot, Talita Duarte-Salles, Neil Murphy, Gabriel Perlemuter, Vivian Viallon, Anne Tjønneland, Agnetha Linn Rostgaard-Hansen, Christina C Dahm, Kim Overvad, Marie-Christine Boutron-Ruault, Francesca Romana Mancini, Yahya Mahamat-Saleh, Krasimira Aleksandrova, Rudolf Kaaks, Tilman Kühn, Antonia Trichopoulou, Anna Karakatsani, Salvatore Panico, Rosario Tumino, Domenico Palli, Giovanna Tagliabue, Alessio Naccarati, Roel C H Vermeulen, H Bas Bueno-de-Mesquita, Elisabete Weiderpass, Guri Skeie, J Ramón Quirós, Eva Ardanaz, Olatz Mokoroa, Núria Sala, Maria-Jose Sánchez, José María Huerta, Anna Winkvist, Sophia Harlid, Bodil Ohlsson, Klas Sjöberg, Julie A Schmidt, Nick Wareham, Kay-Tee Khaw, Pietro Ferrari, Joseph A Rothwell, Marc Gunter, Elio Riboli, Augustin Scalbert, Mazda Jenab.
      Hepatocellular carcinoma (HCC) development entails changes in liver metabolism. Current knowledge on metabolic perturbations in HCC is derived mostly from case-control designs, with sparse information from prospective cohorts. Our objective was to apply comprehensive metabolite profiling to detect metabolites whose serum concentrations are associated with HCC development, using biological samples from within the prospective EPIC cohort (>520 000 participants,), where we identified 129 HCC cases matched 1:1 to controls. We conducted high resolution untargeted liquid chromatography-mass spectrometry based metabolomics on serum samples collected at recruitment prior to cancer diagnosis. Multivariable conditional logistic regression was applied controlling for dietary habits, alcohol consumption, smoking, body size, hepatitis infection and liver dysfunction. Corrections for multiple comparisons were applied. Of 9206 molecular features detected, 220 discriminated HCC cases from controls. Detailed feature annotation revealed 92 metabolites associated with HCC risk; 14 of which were unambiguously identified using pure reference standards. Positive HCC risk associations were observed for N1-acetylspermidine, isatin, p-hydroxyphenyllactic acid, tyrosine, sphingosine, L,L-cyclo(leucylprolyl), glycochenodeoxycholic acid, glycocholic acid, and 7-methylguanine. Inverse risk associations were observed for retinol, dehydroepiandrosterone sulfate, glycerophosphocholine, γ-carboxyethyl hydroxychroman, and creatine. Discernible differences for these metabolites were observed between cases and controls up to 10 years prior to diagnosis. Our observations highlight the diversity of metabolic perturbations involved in HCC development and replicate previous observations (metabolism of bile acids, amino acids, phospholipids) made in Asian and Scandinavian populations. These findings emphasize the role of metabolic pathways associated with steroid metabolism and immunity and specific dietary and environmental exposures in HCC development. This article is protected by copyright. All rights reserved.
    Keywords:  hepatocellular carcinoma; prospective observational cohort; untargeted metabolomics
    DOI:  https://doi.org/10.1002/ijc.33236
  17. J Cell Physiol. 2020 Jul 29.
    Regulation of cancer cell glucose metabolism is determinant for cancer cell fate after melatonin administration.
    Carmen Rodríguez, Noelia Puente-Moncada, Russel J Reiter, Ana M Sánchez-Sánchez, Federico Herrera, Jezabel Rodríguez-Blanco, Cristina Duarte-Olivenza, María Turos-Cabal, Isaac Antolín, Vanesa Martín.
      Several oncogenic pathways plus local microenvironmental conditions, such as hypoxia, converge on the regulation of cancer cells metabolism. The major metabolic alteration consists of a shift from oxidative phosphorylation as the major glucose consumer to aerobic glycolysis, although most of cancer cells utilize both pathways to a greater or lesser extent. Aerobic glycolysis, together with the directly related metabolic pathways such as the tricarboxylic acid cycle, the pentose phosphate pathway, or gluconeogenesis are currently considered as therapeutic targets in cancer research. Melatonin has been reported to present numerous antitumor effects, which result in a reduced cell growth. This is achieved with both low and high concentrations with no relevant side effects. Indeed, high concentrations of this indolamine reduce proliferation of cancer types resistant to low concentrations and induce cell death in some types of tumors. Previous work suggest that regulation of glucose metabolism and other related pathways play an important role in the antitumoral effects of high concentration of melatonin. In the present review, we analyze recent work on the regulation by such concentrations of this indolamine on aerobic glycolysis, gluconeogenesis, the tricarboxylic acid cycle and the pentose phosphate pathways of cancer cells.
    Keywords:  TCA cycle; aerobic glycolysis; gluconeogenesis; melatonin cytotoxicity; pentose phosphate pathway; tumor metabolism
    DOI:  https://doi.org/10.1002/jcp.29886
  18. Rapid Commun Mass Spectrom. 2020 Aug 01. e8911
    Evaluating a targeted multiple reaction monitoring approach to global untargeted lipidomic analyses of human plasma.
    Mostafa J Khan, Simona G Codreanu, Sandeep Goyal, Phillip A Wages, Santosh K K Gorti, Mackenzie J Pearson, Isabel Uribe, Stacy D Sherrod, John A McLean, Ned A Porter, Renã A S Robinson.
      RATIONALE: The Lipidyzer platform was recently updated on a SCIEX 6500+ QTRAP mass spectrometer and offers a targeted lipidomics assay including 1150 different lipids. We evaluated this targeted approach using human plasma samples and compared the results against a global untargeted lipidomics method using a high-resolution Q Exactive-HF Orbitrap mass spectrometer.METHODS: Lipids from human plasma samples (N=5) were extracted using a modified Bligh-Dyer approach. A global untargeted analysis was performed using a Thermo Orbitrap Q Exactive-HF mass spectrometer, followed by data analysis using Progenesis QI software. MRM-based targeted analysis was performed using a QTRAP 6500+ mass spectrometer, followed by data analysis using Sciex OS software. The samples were injected on 3 separate days to assess reproducibility for both approaches.
    RESULTS: Overall, 465 lipids were identified from 11 lipid classes in both approaches, of which: 159 were similar between the methods, 168 lipids were unique to the MRM approach, and 138 lipids were unique to the untargeted approach. Phosphocholine and phosphoethanolamine species were the most commonly identified using the untargeted approach, while triglyceride species were the most commonly identified using the targeted MRM approach. The targeted MRM approach had more consistent relative abundances across the 3 days than the untargeted approach. Overall, the coefficient of variation for inter-day comparisons across all lipid classes was ~23% for the untargeted approach, and ~9% for the targeted MRM approach.
    CONCLUSIONS: The targeted MRM approach identified similar numbers of lipids to a conventional untargeted approach, but had better representation of 11 lipid classes commonly identified by both approaches. Based on the separation methods employed, the conventional untargeted approach could better detect PC and SM lipid classes. The targeted MRM approach had lower inter-day variability than the untargeted approach when tested using a small group of plasma samples. These studies highlight the advantages in using targeted MRM approaches for human plasma lipidomics analysis.
    DOI:  https://doi.org/10.1002/rcm.8911
  19. Nat Metab. 2020 Jul 27.
    Long-chain fatty acyl-CoA esters regulate metabolism via allosteric control of AMPK β1 isoforms.
    Stephen L Pinkosky, John W Scott, Eric M Desjardins, Brennan K Smith, Emily A Day, Rebecca J Ford, Christopher G Langendorf, Naomi X Y Ling, Tracy L Nero, Kim Loh, Sandra Galic, Ashfaqul Hoque, William J Smiles, Kevin R W Ngoei, Michael W Parker, Yan Yan, Karsten Melcher, Bruce E Kemp, Jonathan S Oakhill, Gregory R Steinberg.
      Long-chain fatty acids (LCFAs) play important roles in cellular energy metabolism, acting as both an important energy source and signalling molecules1. LCFA-CoA esters promote their own oxidation by acting as allosteric inhibitors of acetyl-CoA carboxylase, which reduces the production of malonyl-CoA and relieves inhibition of carnitine palmitoyl-transferase 1, thereby promoting LCFA-CoA transport into the mitochondria for β-oxidation2-6. Here we report a new level of regulation wherein LCFA-CoA esters per se allosterically activate AMP-activated protein kinase (AMPK) β1-containing isoforms to increase fatty acid oxidation through phosphorylation of acetyl-CoA carboxylase. Activation of AMPK by LCFA-CoA esters requires the allosteric drug and metabolite site formed between the α-subunit kinase domain and the β-subunit. β1 subunit mutations that inhibit AMPK activation by the small-molecule activator A769662, which binds to the allosteric drug and metabolite site, also inhibit activation by LCFA-CoAs. Thus, LCFA-CoA metabolites act as direct endogenous AMPK β1-selective activators and promote LCFA oxidation.
    DOI:  https://doi.org/10.1038/s42255-020-0245-2
  20. J Lipid Res. 2020 Jul 22. pii: jlr.D120000726. [Epub ahead of print]
    Quantification of common and planar bile acids aids in tissues and cultured cells.
    Stephanie J Shiffka, Jace Jones, Linhao Li, Ann M Farese, Thomas J MacVittie, Hongbing Wang, Peter W Swaan, Maureen A Kane.
      Bile acids (BAs) have been established as ubiquitous regulatory molecules implicated in a large variety of healthy and pathological processes. However, the scope of BA heterogeneity is often underrepresented in current literature. This is due in part to inadequate detection methods, which fail to distinguish the individual constituents of the BA pool. Thus, the primary aim of this study was to develop a method that would allow the simultaneous analysis of specific C24 BA species, and to apply that method to biological systems of interest. Herein, we describe the generation and validation of an LC-MS/MS assay for quantification of numerous BAs in a variety of cell systems and relevant biofluids and tissue. These studies included the first baseline level assessment for planar BAs, including allocholic acid, in cell lines, biofluids, and tissue in a nonhuman primate (NHP) laboratory animal, Macaca mulatta, in healthy conditions. These results indicate that immortalized cell lines make poor models for the study of bile acid synthesis and metabolism, whereas human primary hepatocytes represent a promising alternative model system. We also characterized the BA pool of M. mulatta in detail. Our results support the use of NHP models for the study of BA metabolism and pathology in lieu of murine models. Moreover, the method developed here can be applied to the study of common and planar C24 BA species in other systems.
    Keywords:  Bile; Bile acids and salts; Bile acids and salts/Biosynthesis; Bile acids and salts/Metabolism; Mass spectrometry; hepatocytes; liver; planar bile acids; plasma; quantitation
    DOI:  https://doi.org/10.1194/jlr.D120000726
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