bims-mascan Biomed News
on Mass spectrometry in cancer research
Issue of 2020–05–17
twenty-one papers selected by
Giovanny Rodriguez Blanco, The Beatson Institute for Cancer Research
  1. The impact of extracellular fatty acids and oxygen tension on lipid synthesis and assembly in pancreatic cancer cells.
  2. Triple Negative Breast Cancer Detection Using LC-MS/MS Lipidomic Profiling.
  3. Reproducible molecular networking of untargeted mass spectrometry data using GNPS.
  4. JUMPm: A Tool for Large-Scale Identification of Metabolites in Untargeted Metabolomics.
  5. Quantification of fat-soluble vitamins and their metabolites in biological matrices: an updated review.
  6. An Innovative Lipidomic Workflow to Investigate the Lipid Profile in a Cystic Fibrosis Cell Line.
  7. Omega-3 Polyunsaturated Fatty Acids and Lung Cancer: nutrition or Pharmacology?
  8. BIOMEX: an interactive workflow for (single cell) omics data interpretation and visualization.
  9. The DNA methylation landscape of human cancer organoids available at the American type culture collection.
  10. Lipid biosignature of breast cancer tissues by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry.
  11. Metabolic effects of PCSK9 inhibition with Evolocumab in subjects with elevated Lp(a).
  12. MicroRNA In Situ Hybridization in Paraffin-Embedded Cultured Cells.
  13. Retip: retention time prediction for compound annotation in untargeted metabolomics.
  14. Arginine deprivation: a potential therapeutic for cancer cell metastasis? A review.
  15. 21-plex DiLeu isobaric tags for high-throughput quantitative proteomics.
  16. Metabolite Identification of Therapeutic Peptides and Proteins by Top-down Differential Mass Spectrometry and Metabolite Database Matching.
  17. Longitudinal metabolomics in dried bloodspots yields profiles informing newborn screening for succinic semialdehyde dehydrogenase deficiency.
  18. Adipose triglyceride lipase activity regulates cancer cell proliferation via AMP-kinase and mTOR signaling.
  19. Acetyl-CoA synthetase 3 promotes bladder cancer cell growth under metabolic stress.
  20. Emerging Mechanisms and Disease Relevance of Ferroptosis.
  21. Profiling of Cholesteryl Esters by Coupling Charge Tagging Paternò-Büchi Reaction and Liquid Chromatography-Mass Spectrometry.
  1. ACS Chem Biol. 2020 May 12.
    The impact of extracellular fatty acids and oxygen tension on lipid synthesis and assembly in pancreatic cancer cells.
    Daniel P Downes, Natalie A Daurio, David G McLaren, Paul Carrington, Stephen F Previs, Katharine B Williams.
      Lipid oxidation and biosynthesis are crucial for cell survival, especially for rapidly proliferating cancer cells in a heterogeneous metabolic environment. Storage of high energy lipid reservoirs competitively advantages the cancer cell over non-neoplastic tissue. Disrupting lipid biosynthetic processes, through modulation of fatty acid (FA) esterification or de novo lipogenesis (DNL), is of interest in drug discovery. Mimicking the in vivo environment in vitro is also vital for testing the efficacy of potential drug compounds. We present here a stable isotope tracer-based approach for examining the impact of exogenous FA and oxygen tension on the pathways that affect lipid biosynthesis, including the rates of metabolic flux. By applying tandem mass spectrometry (MS/MS) analyses, to studies using parallel tracers, we characterized the impact of FA bioavailability on the positional enrichment within specific lipids. Our observations suggest that adding bioavailable FA as a carbon source preferentially biases the cellular metabolism away from DNL and towards esterification of free fatty acid pools. Additionally, we have found that this FA addition, under hypoxic conditions, led to biased increase in the total triglyceride pool (nearly 5-fold, as compared to phospholipids), regardless of the isotope tracer utilized. We discuss the implications of this metabolic flexibility on studies that aim to characterize apparent drug efficacy.
    DOI:  https://doi.org/10.1021/acschembio.0c00219
  2. J Proteome Res. 2020 May 13.
    Triple Negative Breast Cancer Detection Using LC-MS/MS Lipidomic Profiling.
    Ryan Eghlimi, Xiaojian Shi, Jonathan Hrovat, Bowei Xi, Haiwei Gu.
      Breast cancer (BC) is a heterogeneous malignancy that is responsible for a great portion of female cancer cases and cancer-related deaths in the United States. In comparison to other major BC subtypes, triple negative breast cancer (TNBC) presents with a relatively low survival rate and a high rate of metastasis. This has led to a strong, though largely unmet, need for more sensitive and specific methods of early stage TNBC (ES-TNBC) detection to combat its high-grade pathology and relatively low survival rate. The current study employs a liquid chromatography-tandem mass spectrometry assay capable of targeted, highly specific and sensitive detection of lipids to propose two diagnostic biomarker panels for TNBC/ES-TNBC. Using this approach, 110 lipids were reliably detected in 166 human plasma samples, 45 controls and 121 BC (96 non-TNBC and 25 TNBC) subjects. Univariate and multivariate analyses allowed the construction and application of a 19-lipid biomarker panel capable of distinguishing TNBC (and ES-TNBC) from controls, as well as, a 5-lipid biomarker panel capable of differentiating TNBC from non-TNBC and ES-TNBC from ES-non-TNBC. Receiver operating characteristic curves with notable classification performances were generated from the biomarker panels according to their orthogonal partial least squares-discrimination analysis models. TNBC was distinguished from controls with an area under the receiving operating characteristic curve (AUROC) = 0.93, sensitivity = 0.96, specificity = 0.76, and ES-TNBC from controls with an AUROC = 0.96, sensitivity = 0.95, and specificity = 0.89. TNBC was differentiated from non-TNBC with an AUROC = 0.88, sensitivity = 0.88, specificity = 0.79, and ES-TNBC from ES-non-TNBC with an AUROC = 0.95, sensitivity = 0.95, and specificity = 0.87. A pathway enrichment analysis between TNBC and controls also revealed significant disturbances in choline metabolism, sphingolipid signaling, and glycerophospholipid metabolism. To the best of our knowledge, this is the first study to propose a diagnostic lipid biomarker panel for TNBC detection. All raw mass spectrometry data have been deposited to MassIVE (dataset identifier: MSV000085324).
    DOI:  https://doi.org/10.1021/acs.jproteome.0c00038
  3. Nat Protoc. 2020 May 13.
    Reproducible molecular networking of untargeted mass spectrometry data using GNPS.
    Allegra T Aron, Emily C Gentry, Kerry L McPhail, Louis-Félix Nothias, Mélissa Nothias-Esposito, Amina Bouslimani, Daniel Petras, Julia M Gauglitz, Nicole Sikora, Fernando Vargas, Justin J J van der Hooft, Madeleine Ernst, Kyo Bin Kang, Christine M Aceves, Andrés Mauricio Caraballo-Rodríguez, Irina Koester, Kelly C Weldon, Samuel Bertrand, Catherine Roullier, Kunyang Sun, Richard M Tehan, Cristopher A Boya P, Martin H Christian, Marcelino Gutiérrez, Aldo Moreno Ulloa, Javier Andres Tejeda Mora, Randy Mojica-Flores, Johant Lakey-Beitia, Victor Vásquez-Chaves, Yilue Zhang, Angela I Calderón, Nicole Tayler, Robert A Keyzers, Fidele Tugizimana, Nombuso Ndlovu, Alexander A Aksenov, Alan K Jarmusch, Robin Schmid, Andrew W Truman, Nuno Bandeira, Mingxun Wang, Pieter C Dorrestein.
      Global Natural Product Social Molecular Networking (GNPS) is an interactive online small molecule-focused tandem mass spectrometry (MS2) data curation and analysis infrastructure. It is intended to provide as much chemical insight as possible into an untargeted MS2 dataset and to connect this chemical insight to the user's underlying biological questions. This can be performed within one liquid chromatography (LC)-MS2 experiment or at the repository scale. GNPS-MassIVE is a public data repository for untargeted MS2 data with sample information (metadata) and annotated MS2 spectra. These publicly accessible data can be annotated and updated with the GNPS infrastructure keeping a continuous record of all changes. This knowledge is disseminated across all public data; it is a living dataset. Molecular networking-one of the main analysis tools used within the GNPS platform-creates a structured data table that reflects the molecular diversity captured in tandem mass spectrometry experiments by computing the relationships of the MS2 spectra as spectral similarity. This protocol provides step-by-step instructions for creating reproducible, high-quality molecular networks. For training purposes, the reader is led through a 90- to 120-min procedure that starts by recalling an example public dataset and its sample information and proceeds to creating and interpreting a molecular network. Each data analysis job can be shared or cloned to disseminate the knowledge gained, thus propagating information that can lead to the discovery of molecules, metabolic pathways, and ecosystem/community interactions.
    DOI:  https://doi.org/10.1038/s41596-020-0317-5
  4. Metabolites. 2020 May 12. pii: E190. [Epub ahead of print]10(5):
    JUMPm: A Tool for Large-Scale Identification of Metabolites in Untargeted Metabolomics.
    Xusheng Wang, Ji-Hoon Cho, Suresh Poudel, Yuxin Li, Drew R Jones, Timothy I Shaw, Haiyan Tan, Boer Xie, Junmin Peng.
      Metabolomics is increasingly important for biomedical research, but large-scale metabolite identification in untargeted metabolomics is still challenging. Here, we present Jumbo Mass spectrometry-based Program of Metabolomics (JUMPm) software, a streamlined software tool for identifying potential metabolite formulas and structures in mass spectrometry. During database search, the false discovery rate is evaluated by a target-decoy strategy, where the decoys are produced by breaking the octet rule of chemistry. We illustrated the utility of JUMPm by detecting metabolite formulas and structures from liquid chromatography coupled tandem mass spectrometry (LC-MS/MS) analyses of unlabeled and stable-isotope labeled yeast samples. We also benchmarked the performance of JUMPm by analyzing a mixed sample from a commercially available metabolite library in both hydrophilic and hydrophobic LC-MS/MS. These analyses confirm that metabolite identification can be significantly improved by estimating the element composition in formulas using stable isotope labeling, or by introducing LC retention time during a spectral library search, which are incorporated into JUMPm functions. Finally, we compared the performance of JUMPm and two commonly used programs, Compound Discoverer 3.1 and MZmine 2, with respect to putative metabolite identifications. Our results indicate that JUMPm is an effective tool for metabolite identification of both unlabeled and labeled data in untargeted metabolomics.
    Keywords:  algorithm; database search; mass spectrometry; metabolite formula; metabolite identification; metabolite structure; metabolome; metabolomics; software; yeast
    DOI:  https://doi.org/10.3390/metabo10050190
  5. Bioanalysis. 2020 May 15.
    Quantification of fat-soluble vitamins and their metabolites in biological matrices: an updated review.
    Yuning Zhang, Veenu Bala, Zhihao Mao, Yashpal S Chhonker, Daryl J Murry.
      Fat-soluble vitamins (FSVs) are micronutrients essential in maintaining normal physiological function, metabolism and human growth. Ongoing increased awareness regarding FSVs concentrations and their impact on human growth along with disease progression warrant the need of developing selective and sensitive analytical methods. LC-MS/MS is currently the method of choice for accurate quantitation of FSVs. However, there are multiple approaches for extraction, separation and calibration of FSVs in biological matrices. This review discusses recent Liquid chromatography-tandem mass spectrometry methods for the simultaneous quantification of FSVs in biological matrices and summarizes sample pretreatment procedures, chromatographic conditions and calibration approaches. Current challenges and clinical applications in various disease states are also highlighted.
    Keywords:  biological samples; fat-soluble vitamins ; high performance liquid chromatography; liquid chromatography-tandem mass spectrometry
    DOI:  https://doi.org/10.4155/bio-2020-0069
  6. Cells. 2020 May 12. pii: E1197. [Epub ahead of print]9(5):
    An Innovative Lipidomic Workflow to Investigate the Lipid Profile in a Cystic Fibrosis Cell Line.
    Michele Dei Cas, Aida Zulueta, Alessandra Mingione, Anna Caretti, Riccardo Ghidoni, Paola Signorelli, Rita Paroni.
      Altered lipid metabolism has been associated to cystic fibrosis disease, which is characterized by chronic lung inflammation and various organs dysfunction. Here, we present the validation of an untargeted lipidomics approach based on high-resolution mass spectrometry aimed at identifying those lipid species that unequivocally sign CF pathophysiology. Of n.13375 mass spectra recorded on cystic fibrosis bronchial epithelial airways epithelial cells IB3, n.7787 presented the MS/MS data, and, after software and manual validation, the final number of annotated lipids was restricted to n.1159. On these lipids, univariate and multivariate statistical approaches were employed in order to select relevant lipids for cellular phenotype discrimination between cystic fibrosis and HBE healthy cells. In cystic fibrosis IB3 cells, a pervasive alteration in the lipid metabolism revealed changes in the classes of ether-linked phospholipids, cholesterol esters, and glycosylated sphingolipids. Through functions association, it was evidenced that lipids variation involves the moiety implicated in membrane composition, endoplasmic reticulum, mitochondria compartments, and chemical and biophysical lipids properties. This study provides a new perspective in understanding the pathogenesis of cystic fibrosis and strengthens the need to use a validated mass spectrometry-based lipidomics approach for the discovery of potential biomarkers and perturbed metabolism.
    Keywords:  OMICS; biomarker; cell structure; cystic fibrosis; lipidomics; membrane composition; sphingolipid; untargeted analysis
    DOI:  https://doi.org/10.3390/cells9051197
  7. Nutr Cancer. 2020 May 12. 1-21
    Omega-3 Polyunsaturated Fatty Acids and Lung Cancer: nutrition or Pharmacology?
    Owen M Vega, Shaheen Abkenari, Zhen Tong, Austin Tedman, Sara Huerta-Yepez.
      Omega-3 polyunsaturated fatty acid (ω-3 PUFA) supplements for chemoprevention of different types of cancer including lung cancer has been investigated in recent years. ω-3 PUFAs are considered immunonutrients, commonly used in the nutritional therapy of cancer patients. ω-3 PUFAs play essential roles in cell signaling and in cell structure and fluidity of membranes. They participate in the resolution of inflammation and have anti-inflammatory effects. Lung cancer patients suffer complications, such as anorexia-cachexia syndrome, pain and depression. The European Society for Clinical Nutrition and Metabolism (ESPEN) 2017 guidelines for cancer patients only discuss the use of ω-3 PUFAs for cancer-cachexia treatment, leaving aside other cancer-related complications that could potentially be managed by ω-3 PUFAs. This review aims to elucidate whether the effects of ω-3 PUFAs in lung cancer is supplementary, pharmacological or both. In addition, clinical studies, evidence in cell lines and animal models suggest how ω-3 PUFAs induce anticancer effects. ω-3 PUFAs and their metabolites are suggested to modulate pivotal pathways underlying the progression or complications of lung cancer, indicating that this is a promising field to be explored. Further investigation is still required to analyze the benefits of ω-3 PUFAs as supplementation or pharmacological treatment in lung cancer.
    DOI:  https://doi.org/10.1080/01635581.2020.1761408
  8. Nucleic Acids Res. 2020 May 11. pii: gkaa332. [Epub ahead of print]
    BIOMEX: an interactive workflow for (single cell) omics data interpretation and visualization.
    Federico Taverna, Jermaine Goveia, Tobias K Karakach, Shawez Khan, Katerina Rohlenova, Lucas Treps, Abhishek Subramanian, Luc Schoonjans, Mieke Dewerchin, Guy Eelen, Peter Carmeliet.
      The amount of biological data, generated with (single cell) omics technologies, is rapidly increasing, thereby exacerbating bottlenecks in the data analysis and interpretation of omics experiments. Data mining platforms that facilitate non-bioinformatician experimental scientists to analyze a wide range of experimental designs and data types can alleviate such bottlenecks, aiding in the exploration of (newly generated or publicly available) omics datasets. Here, we present BIOMEX, a browser-based software, designed to facilitate the Biological Interpretation Of Multi-omics EXperiments by bench scientists. BIOMEX integrates state-of-the-art statistical tools and field-tested algorithms into a flexible but well-defined workflow that accommodates metabolomics, transcriptomics, proteomics, mass cytometry and single cell data from different platforms and organisms. The BIOMEX workflow is accompanied by a manual and video tutorials that provide the necessary background to navigate the interface and get acquainted with the employed methods. BIOMEX guides the user through omics-tailored analyses, such as data pretreatment and normalization, dimensionality reduction, differential and enrichment analysis, pathway mapping, clustering, marker analysis, trajectory inference, meta-analysis and others. BIOMEX is fully interactive, allowing users to easily change parameters and generate customized plots exportable as high-quality publication-ready figures. BIOMEX is open source and freely available at https://www.vibcancer.be/software-tools/biomex.
    DOI:  https://doi.org/10.1093/nar/gkaa332
  9. Epigenetics. 2020 May 12. 1-11
    The DNA methylation landscape of human cancer organoids available at the American type culture collection.
    Ricky Joshi, Manuel Castro De Moura, David Piñeyro, Damiana Alvarez-Errico, Carles Arribas, Manel Esteller.
      One caveat in cancer research is the dependence of certain experimental systems that might not really reflect the properties of the primary tumours. The recent irruption of 3D cultured cells termed organoids could render a better representation of the original tumour sample. However, every laboratory has its own protocol and tissue-provider to establish these cancer models, preventing further dissemination and validation of the obtained data. To address this problem, the Human Cancer Models Initiative (HCMI) has selected the American Type Culture Collection (ATCC) to make available organoid models to the scientific community. In this regard, no epigenetic information is available for these samples and, overall, the DNA methylation profiles of human cancer organoids are largely unknown. Herein, we provide the DNA methylation landscape of 25 human cancer organoids available at the ATCC using a microarray that interrogates more than 850,000 CpG sites. We observed that the studied organoids retain the epigenetic setting of their original primary cancer type; that exhibit a DNA methylation landscape characteristic of transformed tissues excluding an overgrowth of normal-matched cells; and that are closer to the DNA methylation profiles of the corresponding primary tumours than to established 2D cell lines. Most importantly, the obtained DNA methylation results are freely available to everyone for further data mining. Thus, our findings support from the epigenetic standpoint that the ATCC human cancer organoids recapitulate many of the features of the disorder in the patient and are excellent tools to be shared among investigators for further tumour biology research.
    Keywords:  DNA methylation; Organoids; cancer; cell lines; epigenetics; microarray; primary tumours; validation
    DOI:  https://doi.org/10.1080/15592294.2020.1762398
  10. Breast Cancer Res Treat. 2020 May 15.
    Lipid biosignature of breast cancer tissues by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry.
    Catarina L Silva, Rosa Perestrelo, Ivo Sousa-Ferreira, Filipa Capelinha, José S Câmara, Marijana Petković.
       PURPOSE: One of the hallmarks of cancer cells is the demand of supply for the synthesis of new membranes involved in cell proliferation and lipids have an important role in cellular structure, signaling pathways and progression of cancer. In this sense, lipid studies have become an essential tool allowing the establishment of signatures associated with breast cancer (BC). In this regard, some metabolic processes including proteins, nucleic acids and lipid synthesis are enhanced as part of cancer-associated metabolic reprogramming, as a requirement for cell growth and proliferation.
    METHODS: Pairwise samples of breast active carcinoma (BAC) and breast cancer-free tissues were collected from n = 28 patients and analyzed by MALDI-TOF MS.
    RESULTS: Major lipid species are identified in the MALDI-TOF mass spectra, with certain phosphatidylinositols (PIs) detectable only in BAC. Statistical analysis revealed significant differences (p < 0.05) between ratios lysophosphatidylcholine (LPC) 16:0/phosphatidylcholine (PC) 16:0_18:2 between AC and CF groups as well as for BC stages II and III. The ratio PC 16:0_18:2/PC16:0_18:1 was statistically different between AC and CF groups. The one-way ANOVA revealed that there are no statistical differences among BC stages (I, II and III) within AC group. Comparing BC stages, the significance impact increased (p < 0.05) with stage.
    CONCLUSION: The obtained data revealed MALDI-TOF MS as a powerful tool to explore lipid signatures and the enzyme activity associated with BC and possibly establish novel disease markers.
    Keywords:  Breast cancer; Glycerophosphocholine; Lipids; MALDI-TOF MS; Tissue
    DOI:  https://doi.org/10.1007/s10549-020-05672-9
  11. Lipids Health Dis. 2020 May 11. 19(1): 91
    Metabolic effects of PCSK9 inhibition with Evolocumab in subjects with elevated Lp(a).
    Xiang Zhang, Lotte C A Stiekema, Erik S G Stroes, Albert K Groen.
       BACKGROUND: Epidemiological studies substantiated that subjects with elevated lipoprotein(a) [Lp(a)] have a markedly increased cardiovascular risk. Inhibition of proprotein convertase subtilisin/kexin type 9 (PCSK9) lowers both LDL cholesterol (LDL-C) as well as Lp(a), albeit modestly. Effects of PCSK9 inhibition on circulating metabolites such as lipoprotein subclasses, amino acids and fatty acids remain to be characterized.
    METHODS: We performed nuclear magnetic resonance (NMR) metabolomics on plasma samples derived from 30 individuals with elevated Lp(a) (> 150 mg/dL). The 30 participants were randomly assigned into two groups, placebo (N = 14) and evolocumab (N = 16). We assessed the effect of 16 weeks of evolocumab 420 mg Q4W treatment on circulating metabolites by running lognormal regression analyses, and compared this to placebo. Subsequently, we assessed the interrelationship between Lp(a) and 14 lipoprotein subclasses in response to treatment with evolocumab, by running multilevel multivariate regression analyses.
    RESULTS: On average, evolocumab treatment for 16 weeks resulted in a 17% (95% credible interval: 8 to 26%, P < 0.001) reduction of circulating Lp(a), coupled with substantial reduction of VLDL, IDL and LDL particles as well as their lipid contents. Interestingly, increasing concentrations of baseline Lp(a) were associated with larger reduction in triglyceride-rich VLDL particles after evolocumab treatment.
    CONCLUSIONS: Inhibition of PCSK9 with evolocumab markedly reduced VLDL particle concentrations in addition to lowering LDL-C. The extent of reduction in VLDL particles depended on the baseline level of Lp(a). Our findings suggest a marked effect of evolocumab on VLDL metabolism in subjects with elevated Lp(a).
    TRIAL REGISTRATION: Clinical trial registration information is registered at ClinicalTrials.gov on April 14, 2016 with the registration number NCT02729025.
    Keywords:  Evolocumab; Lipoprotein(a); Metabolomics; PCSK9 antibodies; VLDL
    DOI:  https://doi.org/10.1186/s12944-020-01280-0
  12. Methods Mol Biol. 2020 ;2148 99-110
    MicroRNA In Situ Hybridization in Paraffin-Embedded Cultured Cells.
    Jaslin P James, Laura Johnsen, Trine Møller, Boye Schnack Nielsen.
      MicroRNA-21 (miR-21) is one of the most abundant microRNAs in cancer tissues and is considered a strong prognostic biomarker. In situ hybridization (ISH) analyses using locked nucleic acid (LNA) probes have shown that miR-21 is expressed in stromal fibroblastic cells and in subsets of cancer cells. Image analysis of the miR-21 ISH signal has shown that increased expression estimate is associated with poor prognosis in colon cancer. However, assessment of the ISH signal by image analysis to obtain quantitative estimates has been done in retrospective studies without normalization of the expression estimates to reference parameters. The ISH signal output is sensitive to several experimental parameters, including hybridization temperature, probe concentration, and pretreatment, and therefore improved standardized procedures are warranted. We considered the use of paraffin-embedded cultured cells (PECCs) as reference standards that potentially can accompany staining of clinical cancer samples. We found that the cancer cell lines HT-29, CACO-2, and HeLa cells express miR-21 when measured by ISH, and used those cell lines to obtain PECCs. In this methods chapter we present a fixation and embedding procedure to obtain PECCs suitable for microRNA ISH and a double-fluorescence protocol to stain microRNAs together with protein markers in the PECCs.
    Keywords:  Double immunofluorescence; HT-29 cells; In situ hybridization; LNA; miR-21; microRNA
    DOI:  https://doi.org/10.1007/978-1-0716-0623-0_6
  13. Anal Chem. 2020 May 10.
    Retip: retention time prediction for compound annotation in untargeted metabolomics.
    Paolo Bonini, Tobias Kind, Hiroshi Tsugawa, Dinesh Kumar Barupal, Oliver Fiehn.
      Unidentified peaks remain a major problem in untargeted metabolomics by LC-MS/MS. Confidence in peak annotations increases by combining MS/MS matching and retention time. We here show how retention times can be predicted from molecular structures. Two large, publicly available datasets were used for model training in machine learning: the Fiehn hydrophilic interaction liquid chromatography dataset (HILIC) of 981 primary metabolites and biogenic amines, and the RIKEN Plant Specialized Metabolome Annotation (PlaSMA) database of 852 secondary metabolites that uses reversed-phase liquid chromatography (RPLC). Five different machine learning algorithms have been integrated into the Retip R package: the random forest, Bayesian-regularized neural network, XGBoost, light gradient-boosting machine (LightGBM) and Keras algorithms for building the retention time prediction models. A complete workflow for retention time prediction was developed in R. It can be freely downloaded from the GitHub repository (https://www.retip.app). Keras outperformed other machine learning algorithms in the test set with minimum overfitting, verified by small error differences between training, test and validation sets. Keras yielded a mean absolute error (MAE) of 0.78 minutes for HILIC and 0.57 minutes for RPLC. Retip is integrated into the mass spectrometry software tools MS-DIAL and MS-FINDER, allowing a complete compound annotation workflow. In a test application on mouse blood plasma samples, we found a 68% reduction in the number of candidate structures when searching all isomers in MS-FINDER compound identification software. Retention time prediction increases the identification rate in liquid chromatography and subsequently leads to an improved biological interpretation of metabolomics data.
    DOI:  https://doi.org/10.1021/acs.analchem.9b05765
  14. Cancer Cell Int. 2020 ;20 150
    Arginine deprivation: a potential therapeutic for cancer cell metastasis? A review.
    Houssam Al-Koussa, Nour El Mais, Hiba Maalouf, Ralph Abi-Habib, Mirvat El-Sibai.
      Arginine is a semi essential amino acid that is used in protein biosynthesis. It can be obtained from daily food intake or synthesized in the body through the urea cycle using l-citrulline as a substrate. Arginine has a versatile role in the body because it helps in cell division, wound healing, ammonia disposal, immune system, and hormone biosynthesis. It is noteworthy that l-arginine is the precursor for the biosynthesis of nitric oxide (NO) and polyamines. In the case of cancer cells, arginine de novo synthesis is not enough to compensate for their high nutritional needs, forcing them to rely on extracellular supply of arginine. In this review, we will go through the importance of arginine deprivation as a novel targeting therapy by discussing the different arginine deprivation agents and their mechanism of action. We will also focus on the factors that affect cell migration and on the influence of arginine on metastases through polyamine and NO.
    Keywords:  Arginase; Arginine; Cell migration; Rho-GTPases
    DOI:  https://doi.org/10.1186/s12935-020-01232-9
  15. Anal Chem. 2020 May 13.
    21-plex DiLeu isobaric tags for high-throughput quantitative proteomics.
    Dustin C Frost, Yu Feng, Lingjun Li.
      Isobaric tags enable multiplexed quantitative analysis of many biological samples in a single LC-MS/MS experiment. As a cost-effective alternative to expensive commercial isobaric tagging reagents, we developed our own custom N,N-dimethyl leucine 'DiLeu' isobaric tags for quantitative proteomics. Here, we present a new generation of DiLeu tags that achieves 21-plex quantification in high-resolution HCD MS/MS spectra via distinct reporter ions that differ in mass from each other by a minimum of 3 mDa. The 21-plex set retains the compact tag structure and existing isotopologues of the 12-plex set but includes nine new reporter variants formulated with unique configurations of 13C, 15N, and 2H stable isotopes, each synthesized in-house via a stepwise N-monomethylation synthesis strategy using readily available reagents. Thus, multiplexing capacity is expanded significantly while preserving the performance and low cost of the previous implementation. We show that 21-plex DiLeu tags generate strong reporter ions following HCD fragmentation of labeled peptides acquired on Orbitrap platforms at a minimum of 60,000 resolving power (at 400 m/z), and we demonstrate accurate 21-plex quantification of labeled K562 human cell line protein digests via single-shot nanoLC-MS/MS analysis on a Q Exactive HF system.
    DOI:  https://doi.org/10.1021/acs.analchem.0c00473
  16. Anal Chem. 2020 May 13.
    Metabolite Identification of Therapeutic Peptides and Proteins by Top-down Differential Mass Spectrometry and Metabolite Database Matching.
    Xiang Yu, Arthur Fridman, Ansuman Bagchi, Shiyao Xu, Kristen A Kwasnjuk, Ping Lu, Mark T Cancilla.
      As metabolism impacts the efficacy and safety of therapeutic peptides and proteins (TPPs), understanding of the metabolic fate of TPPs is critical for their preclinical and clinical development. Despite the continued increase of new TPPs entering clinical trials, the metabolite identification (MetID) of these emerging modalities remains challenging. In the present study, we report an analytical workflow for MetID of TPPs. Using insulin detemir as an example, we demonstrated that top-down differential mass spectrometry (dMS) was able to distinguish and discover metabolites from complex biological matrices. For structural interpretation, we developed an algorithm to generate a complete and non-redundant theoretical metabolite database for a TPP of any topology (e.g. branched, multi-cyclic etc.). Candidate structures of a metabolite were obtained by matching the monoisotopic mass of a dMS feature to the theoretical metabolite database. Finally, the MS/MS sequence tags enabled unambiguous characterization of metabolite structures when isobaric/isomeric candidates were present. This platform is widely applicable to TPPs with complex structures and will ultimately guide the structural optimization of TPPs in pharmaceutical development.
    DOI:  https://doi.org/10.1021/acs.analchem.0c00652
  17. JIMD Rep. 2020 May;53(1): 29-38
    Longitudinal metabolomics in dried bloodspots yields profiles informing newborn screening for succinic semialdehyde dehydrogenase deficiency.
    Madalyn Brown, Coleman Turgeon, Piero Rinaldo, Ana Pop, Gajja S Salomons, Jean-Baptiste Roullet, K Michael Gibson.
      Analyses of 19 amino acids, 38 acylcarnitines, and 3 creatine analogues (https://clir.mayo.edu) were implemented to test the hypothesis that succinic semialdehyde dehydrogenase deficiency (SSADHD) could be identified in dried bloodspots (DBS) using currently available newborn screening methodology. The study population included 17 post-newborn SSADHD DBS (age range 0.8-38 years; median, 8.2 years; 10 M; controls, 129-353 age-matched individuals, mixed gender) and 10 newborn SSADHD DBS (including first and second screens from 3 of 7 patients). Low (informative) markers in post-newborn DBS included C2- and C4-OH carnitines, ornithine, histidine and creatine, with no gender differences. For newborn DBS, informative markers included C2-, C3-, C4- and C4-OH carnitines, creatine and ornithine. Of these, only creatine demonstrated a significant change with age, revealing an approximate 4-fold decrease. We conclude that quantitation of short-chain acylcarnitines, creatine, and ornithine provides a newborn DBS profile with potential as a first tier screening tool for early detection of SSADHD. This first tier evaluation can be readily verified using a previously described second tier liquid chromatography-tandem mass spectrometry method for γ-hydroxybutyric acid in the same DBS. More extensive evaluation of this first/second tier screening approach is needed in a larger population.
    Keywords:  acylcarnitines; amino acids; creatine; dried bloodspots; newborn screening; succinic semialdehyde dehydrogenase deficiency
    DOI:  https://doi.org/10.1002/jmd2.12075
  18. Biochim Biophys Acta Mol Cell Biol Lipids. 2020 May 10. pii: S1388-1981(20)30129-3. [Epub ahead of print] 158737
    Adipose triglyceride lipase activity regulates cancer cell proliferation via AMP-kinase and mTOR signaling.
    Hao Xie, Christoph Heier, Benedikt Kien, Paul W Vesely, Zhiyuan Tang, Veronika Sexl, Gabriele Schoiswohl, Isabelle Strießnig-Bina, Gerald Hoefler, Rudolf Zechner, Martina Schweiger.
      Aberrant fatty acid (FA) metabolism is a hallmark of proliferating cells, including untransformed fibroblasts or cancer cells. Lipolysis of intracellular triglyceride (TG) stores by adipose triglyceride lipase (ATGL) provides an important source of FAs serving as energy substrates, signaling molecules, and precursors for membrane lipids. To investigate if ATGL-mediated lipolysis impacts cell proliferation, we modified ATGL activity in murine embryonic fibroblasts (MEFs) and in five different cancer cell lines to determine the consequences on cell growth and metabolism. Genetic or pharmacological inhibition of ATGL in MEFs causes impaired FA oxidation, decreased ROS production, and a substrate switch from FA to glucose leading to decreased AMPK-mTOR signaling and higher cell proliferation rates. ATGL expression in these cancer cells is low when compared to MEFs. Additional ATGL knockdown in cancer cells did not significantly affect cellular lipid metabolism or cell proliferation whereas the ectopic overexpression of ATGL increased lipolysis and reduced proliferation. In contrast to ATGL silencing, pharmacological inhibition of ATGL by Atglistatin© impeded the proliferation of diverse cancer cell lines, which points at an ATGL-independent effect. Our data indicate a crucial role of ATGL-mediated lipolysis in the regulation of cell proliferation. The observed low ATGL activity in cancer cells may represent an evolutionary selection process and mechanism to sustain high cell proliferation rates. As the increasing ATGL activity decelerates proliferation of five different cancer cell lines this may represent a novel therapeutic strategy to counteract uncontrolled cell growth.
    Keywords:  ATGL; Cancer; Lipid; Lipolysis; Proliferation
    DOI:  https://doi.org/10.1016/j.bbalip.2020.158737
  19. Oncogenesis. 2020 May 12. 9(5): 46
    Acetyl-CoA synthetase 3 promotes bladder cancer cell growth under metabolic stress.
    Jianhao Zhang, Hongjian Duan, Zhipeng Feng, Xinwei Han, Chaohui Gu.
      Cancer cells adapt to nutrient-deprived tumor microenvironment during progression via regulating the level and function of metabolic enzymes. Acetyl-coenzyme A (AcCoA) is a key metabolic intermediate that is crucial for cancer cell metabolism, especially under metabolic stress. It is of special significance to decipher the role acetyl-CoA synthetase short chain family (ACSS) in cancer cells confronting metabolic stress. Here we analyzed the generation of lipogenic AcCoA in bladder cancer cells under metabolic stress and found that in bladder urothelial carcinoma (BLCA) cells, the proportion of lipogenic AcCoA generated from glucose were largely reduced under metabolic stress. Our results revealed that ACSS3 was responsible for lipogenic AcCoA synthesis in BLCA cells under metabolic stress. Interestingly, we found that ACSS3 was required for acetate utilization and histone acetylation. Moreover, our data illustrated that ACSS3 promoted BLCA cell growth. In addition, through analyzing clinical samples, we found that both mRNA and protein levels of ACSS3 were dramatically upregulated in BLCA samples in comparison with adjacent controls and BLCA patients with lower ACSS3 expression were entitled with longer overall survival. Our data revealed an oncogenic role of ACSS3 via regulating AcCoA generation in BLCA and provided a promising target in metabolic pathway for BLCA treatment.
    DOI:  https://doi.org/10.1038/s41389-020-0230-3
  20. Trends Cell Biol. 2020 Jun;pii: S0962-8924(20)30054-4. [Epub ahead of print]30(6): 478-490
    Emerging Mechanisms and Disease Relevance of Ferroptosis.
    Brent R Stockwell, Xuejun Jiang, Wei Gu.
      Cell death is an essential feature of development in multicellular organisms, a critical driver of degenerative diseases, and can be harnessed for treating some cancers. Understanding the mechanisms governing cell death is critical for addressing its role in disease. Similarly, metabolism is essential for normal energy and biomolecule production, and goes awry in many diseases. Metabolism and cell death are tightly linked in the phenomenon of ferroptosis, a form of regulated cell death driven by peroxidation of phospholipids. Glutathione peroxidase 4 (GPX4) uses glutathione to protect cells from ferroptosis by eliminating phospholipid peroxides. Recent data have revealed glutathione/GPX4-independent axes for suppressing ferroptosis, and insight into the regulation of iron and mitochondria in ferroptosis. Ferroptosis has recently been implicated in multiple diseases, and functions as a tumor suppression mechanism. Ferroptosis induction is a promising approach in treating several conditions, including neoplastic diseases. Here, we summarize these recent advances.
    Keywords:  ferroptosis; iron; lipid peroxidation; metabolism; ubiquinone, cancer
    DOI:  https://doi.org/10.1016/j.tcb.2020.02.009
  21. Anal Chem. 2020 May 15.
    Profiling of Cholesteryl Esters by Coupling Charge Tagging Paternò-Büchi Reaction and Liquid Chromatography-Mass Spectrometry.
    Xiaobo Xie, Jing Zhao, Miao Lin, Jinlan Zhang, Yu Xia.
      The profile of cholesteryl esters (CEs) is increasingly used in metabolic disease monitoring due to the roles of CE in regulating the cholesterol level. While electrospray ionization-tandem mass spectrometry is routinely applied for the identification and quantitation of CE, it has a limitation of not being able to provide the location of carbon-carbon double bond (C = C) within unsaturated fatty acyls. In this study, we paired offline 2-acetylpyridine (2-AP) Paternò-Büchi (PB) reaction and reversed-phase liquid chromatography tandem mass spectrometry (RPLC-MS/MS) to achieve highly sensitive and structural informative CE analysis from complex mixtures. The 2-AP PB reactions of CE standards provided 20-30% conversion but resulted in enhanced ion signal relative to that of intact CE detected as ammonium adduct ions. MS/MS of 2-AP derivatized CE via collision-induced dissociation produced two abundant diagnostic ions for each C = C in a fatty acyl, leading to both sensitive identification and quantitation of C = C location isomers. Twelve saturated and twenty-seven unsaturated CEs were profiled in pooled human plasma; of the latter group, relative quantitation of 6 groups of C=C location isomers was achieved. A dehydrocholesteryl ester, DHE 18:2(Δ9,12), was confidently differentiated from co-existing compositional isomers: CE 18:3 (Δ9,12,15) and CE 18:3 (Δ6,9,12). The above results represented improved CE coverage at C = C location level than those reported by gas-chromatography MS or acetone PB-MS/MS methods.
    DOI:  https://doi.org/10.1021/acs.analchem.0c01241
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