bims-mascan Biomed News
on Mass spectrometry in cancer research
Issue of 2020‒07‒19
eighteen papers selected by
Giovanny Rodriguez Blanco
University of Edinburgh
  1. Large-scale targeted metabolomics method for metabolite profiling of human samples.
  2. Peroxisome Metabolism in Cancer.
  3. Metabolite AutoPlotter - an application to process and visualise metabolite data in the web browser.
  4. Extraction of Lipids from Liquid Biological Samples for High-Throughput Lipidomics.
  5. MSstatsTMT: Statistical detection of differentially abundant proteins in experiments with isobaric labeling and multiple mixtures.
  6. The Pentose Phosphate Pathway Dynamics in Cancer and Its Dependency on Intracellular pH.
  7. Analysis of a Nuclear Intrinsically Disordered Proteome.
  8. Ferroptosis in Liver Diseases: An Overview.
  9. Machine learning of serum metabolic patterns encodes early-stage lung adenocarcinoma.
  10. PHD3 Loss Promotes Exercise Capacity and Fat Oxidation in Skeletal Muscle.
  11. Untargeted Profiling of Bile Acids and Lysophospholipids Identifies the Lipid Signature Associated with Glycemic Outcome in an Obese Non-Diabetic Clinical Cohort.
  12. Correction of isobaric overlap resulting from sodiated ions in lipidomics.
  13. Lipidomics profiling of skin surface lipids in senile pruritus.
  14. Glutaminases regulate glutathione and oxidative stress in cancer.
  15. Dietary Lipids Induce Ferroptosis in Caenorhabditiselegans and Human Cancer Cells.
  16. Determination of mono-unsaturated fatty acid isomers in biological systems by modelling MS3 product ion patterns.
  17. ITLN1 modulates invasive potential and metabolic reprogramming of ovarian cancer cells in omental microenvironment.
  18. Mass spectrometric quantification of urinary 6-sulfatoxymelatonin: age-dependent excretion and biological variation.
  1. Anal Chim Acta. 2020 Aug 15. pii: S0003-2670(20)30605-X. [Epub ahead of print]1125 144-151
    Large-scale targeted metabolomics method for metabolite profiling of human samples.
    Guodong Cao, Zhengbo Song, Yanjun Hong, Zhiyi Yang, Yuanyuan Song, Zhongjian Chen, Zhaobin Chen, Zongwei Cai.
      Targeted metabolomics has significant advantages for quantification but suffers from reduced metabolite coverage. In this study, we developed a large-scale targeted metabolomics method and expanded its applicability to various human samples. This approach initially involved unbiased identification of metabolites in human cells, tissues and body fluids using ultra high-performance liquid chromatography (UHPLC) coupled to high-resolution Orbitrap mass spectrometry (MS). Targeted metabolomics method was established with utility of UHPLC-triple quadrupole MS, which enables targeted profiling of over 400 biologically important metabolites (e.g., amino acids, sugars, nucleotides, dipeptides, coenzymes, and fatty acids), covering 92 metabolic pathways (e.g., Krebs cycle, glycolysis, amino acids metabolism, ammonia recycling, and one-carbon metabolism). The present method displayed better sensitivity, repeatability and linearity than the Orbitrap MS-based untargeted metabolomics approach and demonstrated excellent performance in lung cancer biomarker discovery, in which 107 differential metabolites were able to discriminate between carcinoma and adjacent normal tissues, implicating the Warburg effect, alteration of redox state, and nucleotide metabolism of lung cancer. This new method is flexible and expandable and offers many advantages for metabolomics analysis, such as wide metabolite coverage, good repeatability and linearity and excellent capability in biomarker discovery, making it useful for both basic and clinical metabolic research.
    Keywords:  Biomarker discovery; Human samples; Mass spectrometry; Targeted metabolomics
    DOI:  https://doi.org/10.1016/j.aca.2020.05.053
  2. Cells. 2020 Jul 14. pii: E1692. [Epub ahead of print]9(7):
    Peroxisome Metabolism in Cancer.
    Jung-Ae Kim.
      Peroxisomes are metabolic organelles involved in lipid metabolism and cellular redoxbalance. Peroxisomal function is central to fatty acid oxidation, ether phospholipid synthesis, bile acidsynthesis, and reactive oxygen species homeostasis. Human disorders caused by genetic mutations inperoxisome genes have led to extensive studies on peroxisome biology. Peroxisomal defects are linkedto metabolic dysregulation in diverse human diseases, such as neurodegeneration and age-relateddisorders, revealing the significance of peroxisome metabolism in human health. Cancer is a diseasewith metabolic aberrations. Despite the critical role of peroxisomes in cell metabolism, the functionaleects of peroxisomes in cancer are not as well recognized as those of other metabolic organelles,such as mitochondria. In addition, the significance of peroxisomes in cancer is less appreciated thanit is in degenerative diseases. In this review, I summarize the metabolic pathways in peroxisomesand the dysregulation of peroxisome metabolism in cancer. In addition, I discuss the potential ofinactivating peroxisomes to target cancer metabolism, which may pave the way for more eectivecancer treatment.
    Keywords:  ROS homeostasis; cancer metabolism; cancer target; ether phospholipid synthesis; fatty acid oxidation; peroxisome
    DOI:  https://doi.org/10.3390/cells9071692
  3. Cancer Metab. 2020 ;8 15
    Metabolite AutoPlotter - an application to process and visualise metabolite data in the web browser.
    Matthias Pietzke, Alexei Vazquez.
      Background: Metabolomics is gaining popularity as a standard tool for the investigation of biological systems. Yet, parsing metabolomics data in the absence of in-house computational scientists can be overwhelming and time-consuming. As a consequence of manual data processing, the results are often not analysed in full depth, so potential novel findings might get lost.Methods: To tackle this problem, we developed Metabolite AutoPlotter, a tool to process and visualise quantified metabolite data. Other than with bulk data visualisations, such as heat maps, the aim of the tool is to generate single plots for each metabolite. For this purpose, it reads as input pre-processed metabolite-intensity tables and accepts different experimental designs, with respect to the number of metabolites, conditions and replicates. The code was written in the R-scripting language and wrapped into a shiny application that can be run online in a web browser on https://mpietzke.shinyapps.io/autoplotter.
    Results: We demonstrate the main features and the ease of use with two different metabolite datasets, for quantitative experiments and for stable isotope tracing experiments. We show how the plots generated by the tool can be interactively modified with respect to plot type, colours, text labels and the shown statistics. We also demonstrate the application towards 13C-tracing experiments and the seamless integration of natural abundance correction, which facilitates the better interpretation of stable isotope tracing experiments. The output of the tool is a zip-file containing one single plot for each metabolite as well as restructured tables that can be used for further analysis.
    Conclusion: With the help of Metabolite AutoPlotter, it is now possible to simplify data processing and visualisation for a wide audience. High-quality plots from complex data can be generated in a short time by pressing a few buttons. This offers dramatic improvements over manual analysis. It is significantly faster and allows researchers to spend more time interpreting the results or to perform follow-up experiments. Further, this eliminates potential copy-and-paste errors or tedious repetitions when things need to be changed. We are sure that this tool will help to improve and speed up scientific discoveries.
    Keywords:  Automatic; Graphs; Metabolites; Metabolomics; Plots; Processing; Visualisation
    DOI:  https://doi.org/10.1186/s40170-020-00220-x
  4. Molecules. 2020 Jul 13. pii: E3192. [Epub ahead of print]25(14):
    Extraction of Lipids from Liquid Biological Samples for High-Throughput Lipidomics.
    Samuel Furse, Adam J Watkins, Albert Koulman.
      Extraction of the lipid fraction is a key part of acquiring lipidomics data. High-throughput lipidomics, the extraction of samples in 96w plates that are then run on 96 or 384w plates, has particular requirements that mean special development work is needed to fully optimise an extraction method. Several methods have been published as suitable for it. Here, we test those methods using four liquid matrices: milk, human serum, homogenised mouse liver and homogenised mouse heart. In order to determine the difference in performance of the methods as objectively as possible, we used the number of lipid variables identified, the total signal strength and the coefficient of variance to quantify the performance of the methods. This showed that extraction methods with an aqueous component were generally better than those without for these matrices. However, methods without an aqueous fraction in the extraction were efficient for milk samples. Furthermore, a mixture containing a chlorinated solvent (dichloromethane) appears to be better than an ethereal solvent (tert-butyl methyl ether) for extracting lipids. This study suggests that a 3:1:0.005 mixture of dichloromethane, methanol and triethylammonium chloride, with an aqueous wash, is the most efficient of the currently reported methods for high-throughput lipid extraction and analysis. Further work is required to develop non-aqueous extraction methods that are both convenient and applicable to a broad range of sample types.
    Keywords:  lipid extraction; lipid metabolism; lipidomics
    DOI:  https://doi.org/10.3390/molecules25143192
  5. Mol Cell Proteomics. 2020 Jul 17. pii: mcp.RA120.002105. [Epub ahead of print]
    MSstatsTMT: Statistical detection of differentially abundant proteins in experiments with isobaric labeling and multiple mixtures.
    Ting Huang, Meena Choi, Manuel Tzouros, Sabrina Golling, Nikhil Janak Pandya, Balazs Banfai, Tom Dunkley, Olga Vitek.
      Tandem mass tag (TMT)  is a multiplexing technology widely-used in proteomic research. It enables relative quantification of proteins from multiple biological samples in a single mass spectrometry run with high efficiency and high throughput. However, experiments often require more biological replicates or conditions than can be accommodated by a single run, and involve multiple TMT mixtures and multiple runs. Such larger-scale experiments combine sources of biological and technical variation in patterns that are complex, unique to TMT-based workflows, and challenging for the downstream statistical analysis. These patterns cannot be adequately characterized by statistical methods designed for other technologies, such as label-free proteomics or transcriptomics. This manuscript proposes a general statistical approach for relative protein quantification in mass spectrometry-based experiments with TMT labeling. It is applicable to experiments with multiple conditions, multiple biological replicate runs and multiple technical replicate runs, and unbalanced designs. It is based on a flexible family of linear mixed-effects models that handle complex patterns of technical artifacts and missing values. The approach is implemented in MSstatsTMT, a freely available open-source R/Bioconductor package compatible with data processing tools such as Proteome Discoverer, MaxQuant, OpenMS and SpectroMine. Evaluation on a controlled mixture, simulated datasets, and three biological investigations with diverse designs demonstrated that MSstatsTMT balanced the sensitivity and the specificity of detecting differentially abundant proteins, in particular in large-scale experiments with multiple biological mixtures.
    Keywords:  Bioinformatics software; Hypothesis Testing; Mass Spectrometry; Mathematical Modeling; Multiple Mixtures; Protein Quantification; Quantification; Statistics; TMT
    DOI:  https://doi.org/10.1074/mcp.RA120.002105
  6. Metabolites. 2020 Jul 11. pii: E285. [Epub ahead of print]10(7):
    The Pentose Phosphate Pathway Dynamics in Cancer and Its Dependency on Intracellular pH.
    Khalid O Alfarouk, Samrein B M Ahmed, Robert L Elliott, Amanda Benoit, Saad S Alqahtani, Muntaser E Ibrahim, Adil H H Bashir, Sari T S Alhoufie, Gamal O Elhassan, Christian C Wales, Laurent H Schwartz, Heyam S Ali, Ahmed Ahmed, Patrick F Forde, Jesus Devesa, Rosa A Cardone, Stefano Fais, Salvador Harguindey, Stephan J Reshkin.
      The Pentose Phosphate Pathway (PPP) is one of the key metabolic pathways occurring in living cells to produce energy and maintain cellular homeostasis. Cancer cells have higher cytoplasmic utilization of glucose (glycolysis), even in the presence of oxygen; this is known as the "Warburg Effect". However, cytoplasmic glucose utilization can also occur in cancer through the PPP. This pathway contributes to cancer cells by operating in many different ways: (i) as a defense mechanism via the reduced form of nicotinamide adenine dinucleotide phosphate (NADPH) to prevent apoptosis, (ii) as a provision for the maintenance of energy by intermediate glycolysis, (iii) by increasing genomic material to the cellular pool of nucleic acid bases, (iv) by promoting survival through increasing glycolysis, and so increasing acid production, and (v) by inducing cellular proliferation by the synthesis of nucleic acid, fatty acid, and amino acid. Each step of the PPP can be upregulated in some types of cancer but not in others. An interesting aspect of this metabolic pathway is the shared regulation of the glycolytic and PPP pathways by intracellular pH (pHi). Indeed, as with glycolysis, the optimum activity of the enzymes driving the PPP occurs at an alkaline pHi, which is compatible with the cytoplasmic pH of cancer cells. Here, we outline each step of the PPP and discuss its possible correlation with cancer.
    Keywords:  cancer; enzyme; metabolism; pH; redox
    DOI:  https://doi.org/10.3390/metabo10070285
  7. Methods Mol Biol. 2020 ;2175 181-196
    Analysis of a Nuclear Intrinsically Disordered Proteome.
    Bozena Skupien-Rabian, Urszula Jankowska, Sylwia Kedracka-Krok.
      Intrinsically disordered proteins (IDPs) play crucial roles in cell functioning, although they do not possess defined three-dimensional architecture. They are highly abundant in the cell nucleus, and the vast majority of transcription factors (TFs) contain extended regions of intrinsic disorder. IDPs do not respond to denaturing conditions in a standard manner, and this can be used for their separation from structured proteins. Here we describe a protocol for the isolation and characterization of nuclear IDPs in which heat treatment is used for enrichment of IDPs in samples. The whole workflow comprises the following steps: nuclei isolation from HEK293 (human embryonic kidney) cells, protein extraction, enrichment of IDPs, sample preparation for mass spectrometric analysis, liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis, in silico assessment of protein disorder, and Gene Ontology analysis.
    Keywords:  Intrinsically disordered proteins; Nuclear proteome; Nuclear subproteome; Transcription factors
    DOI:  https://doi.org/10.1007/978-1-0716-0763-3_13
  8. Int J Mol Sci. 2020 Jul 11. pii: E4908. [Epub ahead of print]21(14):
    Ferroptosis in Liver Diseases: An Overview.
    Martina Maria Capelletti, Hana Manceau, Hervé Puy, Katell Peoc'h.
      Ferroptosis is an iron-dependent form of cell death characterized by intracellular lipid peroxide accumulation and redox imbalance. Ferroptosis shows specific biological and morphological features when compared to the other cell death patterns. The loss of lipid peroxide repair activity by glutathione peroxidase 4 (GPX4), the presence of redox-active iron and the oxidation of polyunsaturated fatty acid (PUFA)-containing phospholipids are considered as distinct fingerprints of ferroptosis. Several pathways, including amino acid and iron metabolism, ferritinophagy, cell adhesion, p53, Keap1/Nrf2 and phospholipid biosynthesis, can modify susceptibility to ferroptosis. Through the decades, various diseases, including acute kidney injury; cancer; ischemia-reperfusion injury; and cardiovascular, neurodegenerative and hepatic disorders, have been associated with ferroptosis. In this review, we provide a comprehensive analysis of the main biological and biochemical mechanisms of ferroptosis and an overview of chemicals used as inducers and inhibitors. Then, we report the contribution of ferroptosis to the spectrum of liver diseases, acute or chronic. Finally, we discuss the use of ferroptosis as a therapeutic approach against hepatocellular carcinoma, the most common form of primary liver cancer.
    Keywords:  cell death; ferroptosis; iron metabolism; liver
    DOI:  https://doi.org/10.3390/ijms21144908
  9. Nat Commun. 2020 Jul 16. 11(1): 3556
    Machine learning of serum metabolic patterns encodes early-stage lung adenocarcinoma.
    Lin Huang, Lin Wang, Xiaomeng Hu, Sen Chen, Yunwen Tao, Haiyang Su, Jing Yang, Wei Xu, Vadanasundari Vedarethinam, Shu Wu, Bin Liu, Xinze Wan, Jiatao Lou, Qian Wang, Kun Qian.
      Early cancer detection greatly increases the chances for successful treatment, but available diagnostics for some tumours, including lung adenocarcinoma (LA), are limited. An ideal early-stage diagnosis of LA for large-scale clinical use must address quick detection, low invasiveness, and high performance. Here, we conduct machine learning of serum metabolic patterns to detect early-stage LA. We extract direct metabolic patterns by the optimized ferric particle-assisted laser desorption/ionization mass spectrometry within 1 s using only 50 nL of serum. We define a metabolic range of 100-400 Da with 143 m/z features. We diagnose early-stage LA with sensitivity~70-90% and specificity~90-93% through the sparse regression machine learning of patterns. We identify a biomarker panel of seven metabolites and relevant pathways to distinguish early-stage LA from controls (p < 0.05). Our approach advances the design of metabolic analysis for early cancer detection and holds promise as an efficient test for low-cost rollout to clinics.
    DOI:  https://doi.org/10.1038/s41467-020-17347-6
  10. Cell Metab. 2020 Jul 09. pii: S1550-4131(20)30318-1. [Epub ahead of print]
    PHD3 Loss Promotes Exercise Capacity and Fat Oxidation in Skeletal Muscle.
    Haejin Yoon, Jessica B Spinelli, Elma Zaganjor, Samantha J Wong, Natalie J German, Elizabeth C Randall, Afsah Dean, Allen Clermont, Joao A Paulo, Daniel Garcia, Hao Li, Olivia Rombold, Nathalie Y R Agar, Laurie J Goodyear, Reuben J Shaw, Steven P Gygi, Johan Auwerx, Marcia C Haigis.
      Rapid alterations in cellular metabolism allow tissues to maintain homeostasis during changes in energy availability. The central metabolic regulator acetyl-CoA carboxylase 2 (ACC2) is robustly phosphorylated during cellular energy stress by AMP-activated protein kinase (AMPK) to relieve its suppression of fat oxidation. While ACC2 can also be hydroxylated by prolyl hydroxylase 3 (PHD3), the physiological consequence thereof is poorly understood. We find that ACC2 phosphorylation and hydroxylation occur in an inverse fashion. ACC2 hydroxylation occurs in conditions of high energy and represses fatty acid oxidation. PHD3-null mice demonstrate loss of ACC2 hydroxylation in heart and skeletal muscle and display elevated fatty acid oxidation. Whole body or skeletal muscle-specific PHD3 loss enhances exercise capacity during an endurance exercise challenge. In sum, these data identify an unexpected link between AMPK and PHD3, and a role for PHD3 in acute exercise endurance capacity and skeletal muscle metabolism.
    Keywords:  Prolyl hydroxylase 3; acetyl-CoA carboxylase 2 modification; exercise capacity; fat catabolism
    DOI:  https://doi.org/10.1016/j.cmet.2020.06.017
  11. Biomolecules. 2020 Jul 15. pii: E1049. [Epub ahead of print]10(7):
    Untargeted Profiling of Bile Acids and Lysophospholipids Identifies the Lipid Signature Associated with Glycemic Outcome in an Obese Non-Diabetic Clinical Cohort.
    Nicolas Christinat, Armand Valsesia, Mojgan Masoodi.
      The development of high throughput assays for assessing lipid metabolism in metabolic disorders, especially in diabetes research, nonalcoholic fatty liver disease (NAFLD), and nonalcoholic steatohepatitis (NASH), provides a reliable tool for identifying and characterizing potential biomarkers in human plasma for early diagnosis or prognosis of the disease and/or responses to a specific treatment. Predicting the outcome of weight loss or weight management programs is a challenging yet important aspect of such a program's success. The characterization of potential biomarkers of metabolic disorders, such as lysophospholipids and bile acids, in large human clinical cohorts could provide a useful tool for successful predictions. In this study, we validated an LC-MS method combining the targeted and untargeted detection of these lipid species. Its potential for biomarker discovery was demonstrated in a well-characterized overweight/obese cohort subjected to a low-caloric diet intervention, followed by a weight maintenance phase. Relevant markers predicting successful responses to the low-caloric diet intervention for both weight loss and glycemic control improvements were identified. The response to a controlled weight loss intervention could be best predicted using the baseline concentration of three lysophospholipids (PC(22:4/0:0), PE(17:1/0:0), and PC(22:5/0:0)). Insulin resistance on the other hand could be best predicted using clinical parameters and levels of circulating lysophospholipids and bile acids. Our approach provides a robust tool not only for research purposes, but also for clinical practice, as well as designing new clinical interventions or assessing responses to specific treatment. Considering this, it presents a step toward personalized medicine.
    Keywords:  bile acids; glycemic control; lipidomics; liquid chromatography; lysophospholipids; mass spectrometry; weight loss
    DOI:  https://doi.org/10.3390/biom10071049
  12. Anal Chem. 2020 Jul 16.
    Correction of isobaric overlap resulting from sodiated ions in lipidomics.
    Marcus Höring, Kim Ekroos, Paul R S Baker, Lisa Connell, Sonja C Stadler, Ralph Burkhardt, Gerhard Liebisch.
      Lipidomic analyses aim for absolute quantification of lipid species profiles in biological samples. In the past years, mass spectrometry (MS) methods based on high resolution accurate masses (HRAM) have increasingly been applied to identify and quantify lipid species on MS-level. This strategy requires consideration of isobaric overlaps which may also result from various adduct ions. Generally applied solvent additives favor the formation of protonated and ammoniated ions in positive ion mode, yet sodiated ions are also frequently observed. These sodiated ions interfere with protonated ions of the species of the same lipid class with two additional CH2 and three double bonds (Δm/z = 0.0025) and the first isotopic peak overlaps with ammoniated ions of a species with one additional CH2 and four double bonds (Δm/z = 0.0057). In this work, we present an algorithm based on the sodiated to protonated/ammoniated adduct ion ratios of applied internal standards to correct for these interferences. We could demonstrate that these ratios differ significantly between lipid classes but are neither affected by chain length nor number of double bonds within a lipid class. Finally, the algorithm is demonstrated for correcting human serum samples analyzed by Fourier-Transform mass spectrometry (FTMS). Here, the application of sodium correction sig-nificantly reduced overestimations and misidentifications.
    DOI:  https://doi.org/10.1021/acs.analchem.0c02408
  13. Lipids Health Dis. 2020 Jul 16. 19(1): 171
    Lipidomics profiling of skin surface lipids in senile pruritus.
    Xiaolei Ma, Lulu Lu, Zheng Zhao, Mingru Cai, Na Gao, Gangwen Han.
      BACKGROUND: Senile pruritus is common, yet its etiology remains unknown. Aging-associated skin barrier defects and skin surface lipid (SSL) alterations have been postulated to play important roles in its occurrence. In the present study, the lipidomic profiles of SSLs in elderly patients were examined to better understand the potential causes of senile pruritus.METHODS: Transepidermal water loss (TEWL) was evaluated to assess the skin barrier function. The Ameliorated Kawashima Itch Scale score was used to measure the pruritus severity. Liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS) and multivariate data analysis were employed to investigate SSL alterations.
    RESULTS: The results showed that senile pruritus patients had higher TEWL values than control subjects (13.13 ± 4.28 versus 6.71 ± 2.45, p < 0.01). LC-MS/MS revealed significant differences in the lipidomic profiles and identified 81 species of SSLs that differed between the two groups. Compared with control subjects, senile pruritus patients had increased levels of ceramides (Cers), diacylglycerols, fatty acids, phosphatidylcholines, phosphatidylethanolamines, phytosphingosines, sphingosines, diacylceryl-3-O-carboxyhydroxymethylcholine, diacylglyceryl trimethylhomoserine, and unsaturated free fatty acids, but decreased levels of triacylglycerol. Cer-EOS, Cer-NDS, and Cer-NS were positively correlated with TEWL value (p < 0.05). Pruritus severity score was positively correlated with sphingomyelin, Cer-NP, Cer-AS, Cer-NDS, and Cer-NS, but negatively correlated with Cer-BS, Cer-EODS, Cer-EOS, and Cer-AP.
    CONCLUSIONS: The present study indicated that patients with senile pruritus have impaired skin barrier function and altered SSL composition. Certain SSL species identified in this study may be potential targets for future studies on the pathogenesis of senile pruritus.
    TRIAL REGISTRATION: Peking University International Hospital (Number: YN2018QN04 ; date: January 2019).
    Keywords:  Lipidomics; Senile pruritus; Skin barrier function; Skin surface lipids; Sphingolipids, ceramides; Triacylglycerol
    DOI:  https://doi.org/10.1186/s12944-020-01347-y
  14. Arch Toxicol. 2020 Jul 18.
    Glutaminases regulate glutathione and oxidative stress in cancer.
    José M Matés, José A Campos-Sandoval, Juan de Los Santos-Jiménez, Javier Márquez.
      Targeted therapies against cancer have improved both survival and quality of life of patients. However, metabolic rewiring evokes cellular mechanisms that reduce therapeutic mightiness. Resistant cells generate more glutathione, elicit nuclear factor erythroid 2-related factor 2 (NRF2) activation, and overexpress many anti-oxidative genes such as superoxide dismutase, catalase, glutathione peroxidase, and thioredoxin reductase, providing stronger antioxidant capacity to survive in a more oxidative environment due to the sharp rise in oxidative metabolism and reactive oxygen species generation. These changes dramatically alter tumour microenvironment and cellular metabolism itself. A rational design of therapeutic combination strategies is needed to flatten cellular homeostasis and accomplish a drop in cancer development. Context-dependent glutaminase isoenzymes show oncogenic and tumour suppressor properties, being mainly associated to MYC and p53, respectively. Glutaminases catalyze glutaminolysis in mitochondria, regulating oxidative phosphorylation, redox status and cell metabolism for tumour growth. In addition, the substrate and product of glutaminase reaction, glutamine and glutamate, respectively, can work as signalling molecules moderating redox and bioenergetic pathways in cancer. Novel synergistic approaches combining glutaminase inhibition and redox-dependent modulation are described in this review. Pharmacological or genetic glutaminase regulation along with oxidative chemotherapy can help to improve the design of combination strategies that escalate the rate of therapeutic success in cancer patients.
    Keywords:  GLS; GLS2; MYC; NRF2; Reactive oxygen species; p53
    DOI:  https://doi.org/10.1007/s00204-020-02838-8
  15. Dev Cell. 2020 Jun 30. pii: S1534-5807(20)30498-6. [Epub ahead of print]
    Dietary Lipids Induce Ferroptosis in Caenorhabditiselegans and Human Cancer Cells.
    Marcos A Perez, Leslie Magtanong, Scott J Dixon, Jennifer L Watts.
      Dietary lipids impact development, homeostasis, and disease, but links between specific dietary fats and cell fates are poorly understood. Ferroptosis is an iron-dependent form of nonapoptotic cell death associated with oxidized polyunsaturated phospholipids. Here, we show that dietary ingestion of the polyunsaturated fatty acid (PUFA) dihomogamma-linolenic acid (DGLA; 20:3n-6) can trigger germ-cell ferroptosis and sterility in the nematode Caenorhabditis elegans. Exogenous DGLA is also sufficient to induce ferroptosis in human cells, pinpointing this omega-6 PUFA as a conserved metabolic instigator of this lethal process. In both C. elegans and human cancer cells, ether-lipid synthesis protects against ferroptosis. These results establish C. elegans as a powerful animal model to study the induction and modulation of ferroptosis by dietary fats and indicate that endogenous ether lipids act to prevent this nonapoptotic cell fate.
    Keywords:  ferroptosis; germ cells; polyunsaturated fatty acids
    DOI:  https://doi.org/10.1016/j.devcel.2020.06.019
  16. J Am Soc Mass Spectrom. 2020 Jul 17.
    Determination of mono-unsaturated fatty acid isomers in biological systems by modelling MS3 product ion patterns.
    Johan Lillja, Kyle D Duncan, Ingela Lanekoff.
      Unsaturated free fatty acids are natively present in biological samples as isomers, where double bonds can be situated on different carbons in the acyl chain. While these isomers can have different actions and impact on biological systems, they are inherently difficult to identify and differentiate by mass spectrometry alone. To address this challenge, several techniques for derivatization of the double bond or metal cationization at the carboxylic group have yielded diagnostic product ions for the respective isomer in tandem mass spectrometry. However, diagnostic product ions do not necessarily reflect quantitative isomeric ratios since fatty acid isomers have different ionization and fragmentation efficiencies. Here, we introduce a simple and rapid approach to predict the quantitative ratio of isomeric mono-unsaturated fatty acids. Specifically, empirically derived MS3 product ion patterns from fatty acid silver adducts are modelled using a stepwise linear model. This model is then applied to predict the proportion oleic and vaccenic acid in chemically complex samples at individual concentrations between 0.45 and 5.25 µM, with an average accuracy and precision below 2 and 5 mol%, respectively. We show that by simply including silver ions in the electrospray solvent, isomeric ratios are rapidly predicted in neat standards, rodent plasma, and tissue extract. In addition, we use the method to directly map isomeric ratios in tissue sections using nanospray desorption electrospray ionization MS3 imaging without any sample preparation or modification to the instrumental setup. Ultimately, this approach provides a simple and rapid solution to differentiate mono-unsaturated fatty acids using commonly available commercial mass spectrometers without any instrumental modifications.
    DOI:  https://doi.org/10.1021/jasms.0c00194
  17. Nat Commun. 2020 Jul 15. 11(1): 3546
    ITLN1 modulates invasive potential and metabolic reprogramming of ovarian cancer cells in omental microenvironment.
    Chi-Lam Au-Yeung, Tsz-Lun Yeung, Abhinav Achreja, Hongyun Zhao, Kay-Pong Yip, Suet-Ying Kwan, Michaela Onstad, Jianting Sheng, Ying Zhu, Dodge L Baluya, Ngai-Na Co, Angela Rynne-Vidal, Rosemarie Schmandt, Matthew L Anderson, Karen H Lu, Stephen T C Wong, Deepak Nagrath, Samuel C Mok.
      Advanced ovarian cancer usually spreads to the omentum. However, the omental cell-derived molecular determinants modulating its progression have not been thoroughly characterized. Here, we show that circulating ITLN1 has prognostic significance in patients with advanced ovarian cancer. Further studies demonstrate that ITLN1 suppresses lactotransferrin's effect on ovarian cancer cell invasion potential and proliferation by decreasing MMP1 expression and inducing a metabolic shift in metastatic ovarian cancer cells. Additionally, ovarian cancer-bearing mice treated with ITLN1 demonstrate marked decrease in tumor growth rates. These data suggest that downregulation of mesothelial cell-derived ITLN1 in the omental tumor microenvironment facilitates ovarian cancer progression.
    DOI:  https://doi.org/10.1038/s41467-020-17383-2
  18. Clin Chem Lab Med. 2020 Jul 16. pii: /j/cclm.ahead-of-print/cclm-2020-0455/cclm-2020-0455.xml. [Epub ahead of print]
    Mass spectrometric quantification of urinary 6-sulfatoxymelatonin: age-dependent excretion and biological variation.
    Martijn van Faassen, Anna van der Veen, Sonja van Ockenburg, Helma de Jong, Elisabeth G E de Vries, Ido P Kema.
      Objectives Regulators of circadian rhythm, including melatonin, influence fundamental biological processes. Measuring the melatonin metabolite 6-sulfatoxymelatonin in urine can estimate melatonin production. 6-sulfatoxymelatonin is mainly analyzed by immunoassays, but these methods are hampered by cross-reactivity and poor reproducibility when used to analyze small molecules. Therefore, we validated a high-throughput liquid chromatography with tandem mass spectrometry (LC-MS/MS) method to quantify 6-sulfatoxymelatonin in urine. We evaluated age-dependent 24-h excretion of 6-sulfatoxymelatonin into urine and the biological variation of urinary excretion in healthy individuals. Methods The online solid phase extraction method combined with LC-MS/MS was validated according to international guidelines, and used to measure the excretion of 6-sulfatoxymelatonin into urine of 240 healthy individuals. Biological variation of 6-sulfatoxymelatonin excretion was examined in 10 healthy individuals. Results Urinary 6-sulfatoxymelatonin results were well within the validation criteria (interassay coefficient of variation: <5.4%, quantification limit: 0.2 nmol/L). There was an age-related decrease in 6-sulfatoxymelatonin excretion into 24-h urine [F(5, 234)=13.9; p<0.001]. Within-subject variation of 6-sulfatoxymelatonin was 39.2% in day urine, 15.1% in night urine, and 12.2% in 24-h urine. Between-subject variation was 39.1% in day urine, 37.9% in night urine, and 36.8% in 24-h urine. Conclusions This MS-based method enables straightforward, reproducible, and sensitive quantification of 6-sulfatoxymelatonin in urine. Urinary 6-sulfatoxymelatonin levels decreased with age. Biological variation of 6-sulfatoxymelatonin excretion into urine was high between subjects and lower within subjects, indicating that repeated measurements of 6-sulfatoxymelatonin in 24-h urine are needed in future studies.
    Keywords:  6-sulfatoxymelatonin; biological variation; melatonin; tandem mass spectrometry; urine
    DOI:  https://doi.org/10.1515/cclm-2020-0455
This page is being maintained by Thomas Krichel. It was last updated on 2021‒07‒23 at 10:21:05.