bims-mascan Biomed News
on Mass spectrometry in cancer research
Issue of 2020‒01‒12
thirty-four papers selected by
Giovanny Rodriguez Blanco
The Beatson Institute for Cancer Research


  1. Commun Biol. 2019 Jul 31. 2(1): 281
    Chen RR, Yung MMH, Xuan Y, Zhan S, Leung LL, Liang RR, Leung THY, Yang H, Xu D, Sharma R, Chan KKL, Ngu SF, Ngan HYS, Chan DW.
      Ovarian cancer is an intra-abdominal tumor in which the presence of ascites facilitates metastatic dissemination, and associated with poor prognosis. However, the significance of metabolic alterations in ovarian cancer cells in the ascites microenvironment remains unclear. Here we show ovarian cancer cells exhibited increased aggressiveness in ascites microenvironment via reprogramming of lipid metabolism. High lipid metabolic activities are found in ovarian cancer cells when cultured in the ascites microenvironment, indicating a metabolic shift from aerobic glycolysis to β-oxidation and lipogenesis. The reduced AMP-activated protein kinase (AMPK) activity due to the feedback effect of high energy production led to the activation of its downstream signaling, which in turn, enhanced the cancer growth. The combined treatment of low toxic AMPK activators, the transforming growth factor beta-activated kinase 1 (TAK1) and fatty acid synthase (FASN) inhibitors synergistically impair oncogenic augmentation of ovarian cancer. Collectively, targeting lipid metabolism signaling axis impede ovarian cancer peritoneal metastases.
    DOI:  https://doi.org/10.1038/s42003-019-0508-1
  2. J Biol Chem. 2019 Dec 30. pii: jbc.RA119.011471. [Epub ahead of print]
    Joly JH, Delfarah A, Phung PS, Parrish S, Graham NA.
      Metabolic reprogramming in cancer cells can increase their dependence on metabolic substrates such as glucose. As such, the vulnerability of cancer cells to glucose deprivation creates an attractive opportunity for therapeutic intervention. Because it is not possible to starve tumors of glucose in vivo, here we sought to identify the mechanisms in glucose deprivation-induced cancer cell death and then designed inhibitor combinations to mimic glucose deprivation-induced cell death. Using metabolomic profiling, we found that cells undergoing glucose deprivation-induced cell death exhibited dramatic accumulation of intracellular L-cysteine and its oxidized dimer, L-cystine, and depletion of the antioxidant glutathione. Building on this observation, we show that glucose deprivation-induced cell death is driven not by lack of glucose, but rather by L-cystine import. Following glucose deprivation, the import of L-cystine and its subsequent reduction to L-cysteine depleted both NADPH and glutathione pools, thereby allowing toxic accumulation of reactive oxygen species. Consistent with this model, we found that the glutamate/cystine antiporter xCT is required for increased sensitivity to glucose deprivation. We searched for glycolytic enzymes whose expression is essential for survival of cancer cells with high xCT expression and identified glucose transporter type 1 (GLUT1). Testing a drug combination that co-targeted GLUT1 and glutathione synthesis, we found that this combination induces synthetic lethal cell death in high xCT-expressing cell lines susceptible to glucose deprivation. These results indicate that co-targeting GLUT1 and glutathione synthesis may offer a potential therapeutic approach for targeting tumors dependent on glucose for survival.
    Keywords:  L-cystine; NADPH; SLC7A11; Warburg effect; cancer biology; glucose metabolism; metabolomics; redox regulation
    DOI:  https://doi.org/10.1074/jbc.RA119.011471
  3. Commun Biol. 2019 Sep 03. 2(1): 325
    Rontogianni S, Synadaki E, Li B, Liefaard MC, Lips EH, Wesseling J, Wu W, Altelaar M.
      Extracellular vesicles (EVs) are a potential source of disease-associated biomarkers for diagnosis. In breast cancer, comprehensive analyses of EVs could yield robust and reliable subtype-specific biomarkers that are still critically needed to improve diagnostic routines and clinical outcome. Here, we show that proteome profiles of EVs secreted by different breast cancer cell lines are highly indicative of their respective molecular subtypes, even more so than the proteome changes within the cancer cells. Moreover, we detected molecular evidence for subtype-specific biological processes and molecular pathways, hyperphosphorylated receptors and kinases in connection with the disease, and compiled a set of protein signatures that closely reflect the associated clinical pathophysiology. These unique features revealed in our work, replicated in clinical material, collectively demonstrate the potential of secreted EVs to differentiate between breast cancer subtypes and show the prospect of their use as non-invasive liquid biopsies for diagnosis and management of breast cancer patients.
    DOI:  https://doi.org/10.1038/s42003-019-0570-8
  4. Anal Bioanal Chem. 2020 Jan 04.
    Yang L, Nie H, Zhao F, Song S, Meng Y, Bai Y, Liu H.
      A novel online two-dimensional supercritical fluid chromatography/reversed-phase liquid chromatography-triple-quadrupole mass spectrometry (2D SFC/RPLC-QQQ MS) method based on a vacuum solvent evaporation interface was developed for lipid profiling in human plasma, in which lipid classes were separated by the first-dimension SFC and different lipid molecular species were further separated by the second-dimension RPLC. All separation condition parameters were carefully optimized, and their influence on the chromatographic behavior of lipids is discussed. Finally, the recoveries of 11 lipid standards were all more than 88% for the interface. Besides, the limit of detection for these lipid standards was on the order of nanograms per milliliter, and the relative standard deviations of the peak area and retention time ranged from 1.54% to 19.85% and from 0.00% to 0.10%, respectively. The final 2D SFC/RPLC-QQQ MS method allowed the identification of 370 endogenous lipid species from ten lipid classes, including diacylglycerol, triacylglycerol, ceramide, glucosylceramide, galactosylceramide, lactosylceramide, sphingomyelin, acylcarnitine, phosphatidylcholine, and lysophosphatidylethanolamine, in human plasma within 38 min, which was used for screening potential lipid biomarkers in breast cancer. The 2D SFC/RPLC-QQQ MS method is a potentially useful tool for in-depth studies focused on complex lipid metabolism and biomarker discovery. Graphical Abstract.
    Keywords:  Lipidomics; Mass spectrometry; Supercritical fluid chromatography; Two-dimensional
    DOI:  https://doi.org/10.1007/s00216-019-02242-x
  5. Anal Bioanal Chem. 2020 Jan 06.
    Vavrušová A, Vrkoslav V, Plavka R, Bosáková Z, Cvačka J.
      Fatty acid esters of long-chain hydroxy fatty acids or (O-acyl)-hydroxy fatty acids (OAHFAs) were identified for the first time in vernix caseosa and characterized using chromatography and mass spectrometry. OAHFAs were isolated from the total lipid extract by a two-step semipreparative TLC. The general structure of OAHFAs was established using high-resolution and tandem mass spectrometry of intact lipids and their transesterification and derivatization products. Two isomeric lipid classes were identified: O-acyl esters of ω-hydroxy fatty acids (ωOAHFA) and O-acyl esters of α-hydroxy fatty acids (αOAHFAs). To the best of our knowledge, αOAHFAs have never been detected in any biological sample before. Chromatographic separation and identification of OAHFAs species were achieved using non-aqueous reversed-phase HPLC coupled to electrospray ionization hybrid linear ion trap-Orbitrap mass spectrometry. The lipid species were detected as deprotonated molecules, and their structures were elucidated using data-dependent fragmentation in the negative ion mode. More than 400 OAHFAs were identified in this way. The most abundant ωOAHFAs species were 28:0/ω-18:2, 29:0/ω-18:2, 30:0/ω-18:2, 32:0/ω-18:2, and 30:0/ω-18:3, while αOAHFAs comprised saturated species 21:0/α-24:0, 22:0/α-24:0, 23:0/α-24:0, 24:0/α-24:0, and 26:0/α-24:0. OAHFAs were estimated to account for approximately 0.04% of vernix caseosa lipids. Graphical Abstract.
    Keywords:  Amphiphilic lipids; Lipidomics; Mass spectrometry; Skin lipids; Vernix caseosa
    DOI:  https://doi.org/10.1007/s00216-019-02348-2
  6. Anal Chem. 2020 Jan 08.
    Cong Y, Liang Y, Motamedchaboki K, Huguet R, Truong T, Zhao R, Shen Y, Lopez-Ferrer D, Zhu Y, Kelly RT.
      Single-cell proteomics can provide unique insights into biological processes by resolving heterogeneity that is obscured by bulk measurements. Gains in the overall sensitivity and proteome coverage through improvements in sample processing and analysis increase the information content obtained from each cell, particularly for less abundant proteins. Here we report on improved single-cell proteome coverage through the combination of the previously developed Nanodroplet Processing in One Pot for Trace Samples (nanoPOTS) platform with further miniaturization of liquid chromatography (LC) separations and implementation of an ultrasensitive latest-generation mass spectrometer. Following nanoPOTS sample preparation, protein digests from single cells were separated using a 20-µm-i.d. in-house-packed nanoLC column. Separated peptides were ionized using an etched fused silica emitter capable of stable operation at the ~20 nL/min flow rate provided by the LC separation. Ultrasensitive LC-MS analysis was achieved using the Orbitrap Eclipse Tribrid mass spectrometer. An average of 362 protein groups were identified by MS/MS from single HeLa cells, and 874 protein groups were identified using the Match Between Runs (MBR) feature of MaxQuant. This represents a >70% increase in label-free proteome coverage for single cells relative to previous efforts using larger-bore (30-µm-i.d.) LC columns coupled to a previous-generation mass spectrometer (Orbitrap Fusion Lumos).
    DOI:  https://doi.org/10.1021/acs.analchem.9b04631
  7. Nat Commun. 2020 Jan 07. 11(1): 52
    Affronti HC, Rowsam AM, Pellerite AJ, Rosario SR, Long MD, Jacobi JJ, Bianchi-Smiraglia A, Boerlin CS, Gillard BM, Karasik E, Foster BA, Moser M, Wilton JH, Attwood K, Nikiforov MA, Azabdaftari G, Pili R, Phillips JG, Casero RA, Smiraglia DJ.
      Prostatic luminal epithelial cells secrete high levels of acetylated polyamines into the prostatic lumen, sensitizing them to perturbations of connected metabolic pathways. Enhanced flux is driven by spermidine/spermine N1-acetyltransferase (SSAT) activity, which acetylates polyamines leading to their secretion and drives biosynthetic demand. The methionine salvage pathway recycles one-carbon units lost to polyamine biosynthesis to the methionine cycle to overcome stress. Prostate cancer (CaP) relies on methylthioadenosine phosphorylase (MTAP), the rate-limiting enzyme, to relieve strain. Here, we show that inhibition of MTAP alongside SSAT upregulation is synergistic in androgen sensitive and castration recurrent CaP models in vitro and in vivo. The combination treatment increases apoptosis in radical prostatectomy ex vivo explant samples. This unique high metabolic flux through polyamine biosynthesis and connected one carbon metabolism in CaP creates a metabolic dependency. Enhancing this flux while simultaneously targeting this dependency in prostate cancer results in an effective therapeutic approach potentially translatable to the clinic.
    DOI:  https://doi.org/10.1038/s41467-019-13950-4
  8. Anal Biochem. 2020 Jan 03. pii: S0003-2697(19)31070-X. [Epub ahead of print] 113558
    Andraos S, Goy M, Albert BB, Kussmann M, Thorstensen EB, O'Sullivan JM.
      Amino acids (AAs) and one-carbon (1-C) metabolism compounds are involved in a range of key metabolic pathways, and mediate numerous health and disease processes in the human body. Previous assays have quantified a limited selection of these compounds and typically require extensive manual handling. Here, we describe the robotic automation of an analytical method for the simultaneous quantification of 37 1-C metabolites, amino acids, and precursors using reversed-phase ultra-high-pressure liquid chromatography coupled with tandem mass spectrometry (UHPLC/MS-MS). Compound extraction from human plasma was tested manually before being robotically automated. The final automated analytical panel was validated on human plasma samples. Our automated and multiplexed method holds promise for application to large cohort studies.
    DOI:  https://doi.org/10.1016/j.ab.2019.113558
  9. Metabolomics. 2020 Jan 10. 16(1): 11
    Zhang G, Zhang J, DeHoog RJ, Pennathur S, Anderton CR, Venkatachalam MA, Alexandrov T, Eberlin LS, Sharma K.
      INTRODUCTION: Diabetic kidney disease (DKD) is the most prevalent complication in diabetic patients, which contributes to high morbidity and mortality. Urine and plasma metabolomics studies have been demonstrated to provide valuable insights for DKD. However, limited information on spatial distributions of metabolites in kidney tissues have been reported.OBJECTIVES: In this work, we employed an ambient desorption electrospray ionization-mass spectrometry imaging (DESI-MSI) coupled to a novel bioinformatics platform (METASPACE) to characterize the metabolome in a mouse model of DKD.
    METHODS: DESI-MSI was performed for spatial untargeted metabolomics analysis in kidneys of mouse models (F1 C57BL/6J-Ins2Akita male mice at 17 weeks of age) of type 1 diabetes (T1D, n = 5) and heathy controls (n = 6).
    RESULTS: Multivariate analyses (i.e., PCA and PLS-DA (a 2000 permutation test: P < 0.001)) showed clearly separated clusters for the two groups of mice on the basis of 878 measured m/z's in kidney cortical tissues. Specifically, mice with T1D had increased relative abundances of pseudouridine, accumulation of free polyunsaturated fatty acids (PUFAs), and decreased relative abundances of cardiolipins in cortical proximal tubules when compared with healthy controls.
    CONCLUSION: Results from the current study support potential key roles of pseudouridine and cardiolipins for maintaining normal RNA structure and normal mitochondrial function, respectively, in cortical proximal tubules with DKD. DESI-MSI technology coupled with METASPACE could serve as powerful new tools to provide insight on fundamental pathways in DKD.
    Keywords:  DESI-MSI; Diabetic kidney disease; Lipid metabolism; Renal proximal tubule
    DOI:  https://doi.org/10.1007/s11306-020-1637-8
  10. Nat Commun. 2020 Jan 07. 11(1): 36
    Nie H, Ju H, Fan J, Shi X, Cheng Y, Cang X, Zheng Z, Duan X, Yi W.
      Many cancer cells display enhanced glycolysis and suppressed mitochondrial metabolism. This phenomenon, known as the Warburg effect, is critical for tumor development. However, how cancer cells coordinate glucose metabolism through glycolysis and the mitochondrial tricarboxylic acid (TCA) cycle is largely unknown. We demonstrate here that phosphoglycerate kinase 1 (PGK1), the first ATP-producing enzyme in glycolysis, is reversibly and dynamically modified with O-linked N-acetylglucosamine (O-GlcNAc) at threonine 255 (T255). O-GlcNAcylation activates PGK1 activity to enhance lactate production, and simultaneously induces PGK1 translocation into mitochondria. Inside mitochondria, PGK1 acts as a kinase to inhibit pyruvate dehydrogenase (PDH) complex to reduce oxidative phosphorylation. Blocking T255 O-GlcNAcylation of PGK1 decreases colon cancer cell proliferation, suppresses glycolysis, enhances the TCA cycle, and inhibits tumor growth in xenograft models. Furthermore, PGK1 O-GlcNAcylation levels are elevated in human colon cancers. This study highlights O-GlcNAcylation as an important signal for coordinating glycolysis and the TCA cycle to promote tumorigenesis.
    DOI:  https://doi.org/10.1038/s41467-019-13601-8
  11. Nat Commun. 2020 Jan 09. 11(1): 157
    Bian Y, Zheng R, Bayer FP, Wong C, Chang YC, Meng C, Zolg DP, Reinecke M, Zecha J, Wiechmann S, Heinzlmeir S, Scherr J, Hemmer B, Baynham M, Gingras AC, Boychenko O, Kuster B.
      Nano-flow liquid chromatography tandem mass spectrometry (nano-flow LC-MS/MS) is the mainstay in proteome research because of its excellent sensitivity but often comes at the expense of robustness. Here we show that micro-flow LC-MS/MS using a 1 × 150 mm column shows excellent reproducibility of chromatographic retention time (<0.3% coefficient of variation, CV) and protein quantification (<7.5% CV) using data from >2000 samples of human cell lines, tissues and body fluids. Deep proteome analysis identifies >9000 proteins and >120,000 peptides in 16 h and sample multiplexing using tandem mass tags increases throughput to 11 proteomes in 16 h. The system identifies >30,000 phosphopeptides in 12 h and protein-protein or protein-drug interaction experiments can be analyzed in 20 min per sample. We show that the same column can be used to analyze >7500 samples without apparent loss of performance. This study demonstrates that micro-flow LC-MS/MS is suitable for a broad range of proteomic applications.
    DOI:  https://doi.org/10.1038/s41467-019-13973-x
  12. Metabolomics. 2020 Jan 10. 16(1): 12
    Balgoma D, Zelleroth S, Grönbladh A, Hallberg M, Pettersson C, Hedeland M.
      INTRODUCTION: The abuse of anabolic androgenic steroids (AASs) is a source of public concern because of their adverse effects. Supratherapeutic doses of AASs are known to be hepatotoxic and regulate the lipoproteins in plasma by modifying the metabolism of lipids in the liver, which is associated with metabolic diseases. However, the effect of AASs on the profile of lipids in plasma is unknown.OBJECTIVES: To describe the changes in the plasma lipidome exerted by AASs and to discuss these changes in the light of previous research about AASs and de novo lipogenesis in the liver.
    METHODS: We treated male Wistar rats with supratherapeutic doses of nandrolone decanoate and testosterone undecanoate. Subsequently, we isolated the blood plasma and performed lipidomics analysis by liquid chromatography-high resolution mass spectrometry.
    RESULTS: Lipid profiling revealed a decrease of sphingolipids and glycerolipids with palmitic, palmitoleic, stearic, and oleic acids. In addition, lipid profiling revealed an increase in free fatty acids and glycerophospholipids with odd-numbered chain fatty acids and/or arachidonic acid.
    CONCLUSION: The lipid profile presented herein reports the imprint of AASs on the plasma lipidome, which mirrors the downregulation of de novo lipogenesis in the liver. In a broader perspective, this profile will help to understand the influence of androgens on the lipid metabolism in future studies of diseases with dysregulated lipogenesis (e.g. type 2 diabetes, fatty liver disease, and hepatocellular carcinoma).
    Keywords:  Androgen receptor; Androgens; Estrogen receptors; Lipidomics; Liver X receptors
    DOI:  https://doi.org/10.1007/s11306-019-1632-0
  13. EBioMedicine. 2020 Jan 06. pii: S2352-3964(19)30825-4. [Epub ahead of print]51 102610
    Xia S, Pan Y, Liang Y, Xu J, Cai X.
      In most cases, sorafenib-resistant HCC cells exhibit significant mesenchymal phenotype and stemness features. In this context, tumor cells might undergo cell fate transition in response to sorafenib or other targeted drugs in the presence or absence of genetic mutations. Therefore, understanding the major characteristics of drug-resistant cells state helps to discover new treatments that overcome drug resistance. To note, little is known about the metabolic or microenvironmental aspects of the certain tumor cell states beyond the genome. This review mainly focuses on the underlying mechanisms of acquired sorafenib resistance based on CSCs and EMT models, which explain tumor heterogeneity and have been considered the major cause of secondary sorafenib resistance. In particular, it discusses how the tumor microenvironment and tumor metabolism regulate cell stemness, mesenchymal state, and sorafenib resistance through epigenetic regulations, and provides reliable targets that might have synergetic effect with sorafenib.
    Keywords:  Cancer stem cells; Epithelial-mesenchymal transition; Hypoxia; Sorafenib resistance; Tumor metabolism; Tumor microenvironment
    DOI:  https://doi.org/10.1016/j.ebiom.2019.102610
  14. Front Oncol. 2019 ;9 1404
    Pedroza-Torres A, Romero-Córdoba SL, Justo-Garrido M, Salido-Guadarrama I, Rodríguez-Bautista R, Montaño S, Muñiz-Mendoza R, Arriaga-Canon C, Fragoso-Ontiveros V, Álvarez-Gómez RM, Hernández G, Herrera LA.
      Dysregulated metabolism is a common feature of cancer cells and is considered a hallmark of cancer. Altered tumor-metabolism confers an adaptive advantage to cancer cells to fulfill the high energetic requirements for the maintenance of high proliferation rates, similarly, reprogramming metabolism confers the ability to grow at low oxygen concentrations and to use alternative carbon sources. These phenomena result from the dysregulated expression of diverse genes, including those encoding microRNAs (miRNAs) which are involved in several metabolic and tumorigenic pathways through its post-transcriptional-regulatory activity. Further, the identification of key actionable altered miRNA has allowed to propose novel targeted therapies to modulated tumor-metabolism. In this review, we discussed the different roles of miRNAs in cancer cell metabolism and novel miRNA-based strategies designed to target the metabolic machinery in human cancer.
    Keywords:  microRNAs; regulation; reprogramming metabolism; therapeutic targets; tumor cell metabolism
    DOI:  https://doi.org/10.3389/fonc.2019.01404
  15. J Biol Chem. 2019 Dec 30. pii: jbc.RA119.009899. [Epub ahead of print]
    Zheng X, Jia Y, Qiu L, Zeng X, Xu L, Wei M, Huang C, Liu C, Chen L, Han J.
      Lysophosphatidic acid receptor 6 (LPAR6) is a G protein-coupled receptor that plays critical roles in cellular morphology and hair growth. Although LPAR6 overexpression is also critical for cancer cell proliferation, its role in liver cancer tumorigenesis and the underlying mechanism are poorly understood. Here, using liver cancer and matched paracancerous tissues, as well as functional assays including cell proliferation, quantitative real-time PCR, RNA-Seq and ChIP assays, we report that LPAR6 expression is controlled by a mechanism whereby hepatocyte growth factor (HGF) suppresses liver cancer growth. We show that high LPAR6 expression promotes cell proliferation in liver cancer. More importantly, we find that LPAR6 is transcriptionally down-regulated by HGF treatment and that its transcriptional suppression depends on nuclear receptor coactivator 3 (NCOA3). We note that enrichment of NCOA3, which has histone acetyltransferase activity, is associated with histone 3 Lys-27 acetylation (H3K27ac) at the LPAR6 locus in response to HGF treatment, indicating that NCOA3 transcriptionally regulates LPAR6 through the HGF signaling cascade. Moreover, depletion of either LPAR6 or NCOA3 significantly inhibited tumor cell growth in vitro and in vivo (in mouse tumor xenograft assays), similar to the effect of the HGF treatment. Collectively, our findings indicate an epigenetic link between LPAR6 and HGF signaling in liver cancer cells, and suggest that LPAR6 can serve as a biomarker and new strategy for therapeutic interventions for managing liver cancer.
    Keywords:  G protein-coupled receptor (GPCR); cell signaling; epigenetics; hepatocellular carcinoma; hepatocyte growth factor/scatter factor (HGF/SF); histone acetyltransferase; lysophosphatidic acid receptor 6 (LPAR6); nuclear receptor coactivator 3 (NCOA3); transcription
    DOI:  https://doi.org/10.1074/jbc.RA119.009899
  16. Mol Metab. 2020 Jan;pii: S2212-8778(19)30934-2. [Epub ahead of print]31 36-44
    Wang Y, Kwon H, Su X, Wondisford FE.
      OBJECTIVE: Fasting results in major metabolic changes including a switch from glycogenolysis to gluconeogenesis to maintain glucose homeostasis. However, the relationship between the length of fasting and the relative contribution of gluconeogenic substrates remains unclear. We investigated the relative contribution of glycogen, lactate, and glycerol in glucose production of male C57BL/6 J-albino mice after 6, 12, and 18 h of fasting.METHODS: We used non-perturbative infusions of 13C3 lactate, 13C3 glycerol, and 13C6 glucose combined with liquid chromatography mass spectrometry and metabolic flux analysis to study the contribution of substrates in gluconeogenesis (GNG).
    RESULTS: During infusion studies, both lactate and glycerol significantly label about 60% and 30-50% glucose carbon, respectively, but glucose labels much more lactate (∼90%) than glycerol carbon (∼10%). Our analyses indicate that lactate, but not glycerol is largely recycled during all fasting periods such that lactate is the largest direct contributor to GNG via the Cori cycle but a minor source of new glucose carbon (overall contribution). In contrast, glycerol is not only a significant direct contributor to GNG but also the largest overall contributor to GNG regardless of fasting length. Prolonged fasting decreases both the whole body turnover rate of glucose and lactate but increases that of glycerol, indicating that the usage of glycerol in GNG become more significant with longer fasting.
    CONCLUSION: Collectively, these findings suggest that glycerol is the dominant overall contributor of net glucose carbon in GNG during both short and prolonged fasting.
    Keywords:  Fasting; Gluconeogenesis; Glycerol; Metabolic flux analysis; Substrate contribution
    DOI:  https://doi.org/10.1016/j.molmet.2019.11.005
  17. Metab Eng Commun. 2020 Jun;10 e00120
    Dange MC, Mishra V, Mukherjee B, Jaiswal D, Merchant MS, Prasannan CB, Wangikar PP.
      13C Metabolic Flux Analysis (13C-MFA) involves the quantification of isotopic enrichment in cellular metabolites and fitting the resultant data to the metabolic network model of the organism. Coverage and resolution of the resultant flux map depends on the total number of metabolites and fragments in which 13C enrichment can be quantified accurately. Experimental techniques for tracking 13C enrichment are evolving rapidly and large volumes of data are now routinely generated through the use of Liquid Chromatography coupled with High-Resolution Mass Spectrometry (HR-LC/MS). Therefore, the current manuscript is focused on the challenges in high-throughput analyses of such large datasets. Current 13C-MFA studies often have to rely on the targeted quantification of a small subset of metabolites, thereby leaving a large fraction of the data unexplored. A number of public domain software tools have been reported in recent years for the untargeted quantitation of isotopic enrichment. However, the suitability of their application across diverse datasets has not been investigated. Here, we test the software tools X13CMS, DynaMet, geoRge, and HiResTEC with three diverse datasets. The tools provided a global, untargeted view of 13C enrichment in metabolites in all three datasets and a much-needed automation in data analysis. Some inconsistencies were observed in results obtained from the different tools, which could be partially ascribed to the lack of baseline separation and potential mass conflicts. After removing the false positives manually, isotopic enrichment could be quantified reliably in a large repertoire of metabolites. Of the software tools explored, geoRge and HiResTEC consistently performed well for the untargeted analysis of all datasets tested.
    Keywords:  13C metabolic flux analysis; Cyanobacteria; Methanolicus; Reticulocytes; Synechococcus sp. PCC 7002; Untargeted analysis
    DOI:  https://doi.org/10.1016/j.mec.2019.e00120
  18. PLoS One. 2020 ;15(1): e0227455
    Mohamed A, Collins J, Jiang H, Molendijk J, Stoll T, Torta F, Wenk MR, Bird RJ, Marlton P, Mollee P, Markey KA, Hill MM.
      BACKGROUND: Multiple myeloma (MM) is a hematological malignancy characterized by the clonal expansion of malignant plasma cells. Though durable remissions are possible, MM is considered incurable, with relapse occurring in almost all patients. There has been limited data reported on the lipid metabolism changes in plasma cells during MM progression. Here, we evaluated the feasibility of concurrent lipidomics and proteomics analyses from patient plasma cells, and report these data on a limited number of patient samples, demonstrating the feasibility of the method, and establishing hypotheses to be evaluated in the future.METHODS: Plasma cells were purified from fresh bone marrow aspirates using CD138 microbeads. Proteins and lipids were extracted using a bi-phasic solvent system with methanol, methyl tert-butyl ether, and water. Untargeted proteomics, untargeted and targeted lipidomics were performed on 7 patient samples using liquid chromatography-mass spectrometry. Two comparisons were conducted: high versus low risk; relapse versus newly diagnosed. Proteins and pathways enriched in the relapsed group was compared to a public transcriptomic dataset from Multiple Myeloma Research Consortium reference collection (n = 222) at gene and pathways level.
    RESULTS: From one million purified plasma cells, we were able to extract material and complete untargeted (~6000 and ~3600 features in positive and negative mode respectively) and targeted lipidomics (313 lipids), as well as untargeted proteomics analysis (~4100 reviewed proteins). Comparative analyses revealed limited differences between high and low risk groups (according to the standard clinical criteria), hence we focused on drawing comparisons between the relapsed and newly diagnosed patients. Untargeted and targeted lipidomics indicated significant down-regulation of phosphatidylcholines (PCs) in relapsed MM. Although there was limited overlap of the differential proteins/transcripts, 76 significantly enriched pathways in relapsed MM were common between proteomics and transcriptomics data. Further evaluation of transcriptomics data for lipid metabolism network revealed enriched correlation of PC, ceramide, cardiolipin, arachidonic acid and cholesterol metabolism pathways to be exclusively correlated among relapsed but not in newly-diagnosed patients.
    CONCLUSIONS: This study establishes the feasibility and workflow to conduct integrated lipidomics and proteomics analyses on patient-derived plasma cells. Potential lipid metabolism changes associated with MM relapse warrant further investigation.
    DOI:  https://doi.org/10.1371/journal.pone.0227455
  19. Cell Stress. 2019 Dec 10. 4(1): 9-23
    Cucchi D, Camacho-Muñoz D, Certo M, Pucino V, Nicolaou A, Mauro C.
      Recent advances in immunology and cancer research show that fatty acids, their metabolism and their sensing have a crucial role in the biology of many different cell types. Indeed, they are able to affect cellular behaviour with great implications for pathophysiology. Both the catabolic and anabolic pathways of fatty acids present us with a number of enzymes, receptors and agonists/antagonists that are potential therapeutic targets, some of which have already been successfully pursued. Fatty acids can affect the differentiation of immune cells, particularly T cells, as well as their activation and function, with important consequences for the balance between anti- and pro-inflammatory signals in immune diseases, such as rheumatoid arthritis, psoriasis, diabetes, obesity and cardiovascular conditions. In the context of cancer biology, fatty acids mainly provide substrates for energy production, which is of crucial importance to meet the energy demands of these highly proliferating cells. Fatty acids can also be involved in a broader transcriptional programme as they trigger signals necessary for tumorigenesis and can confer to cancer cells the ability to migrate and generate distant metastasis. For these reasons, the study of fatty acids represents a new research direction that can generate detailed insight and provide novel tools for the understanding of immune and cancer cell biology, and, more importantly, support the development of novel, efficient and fine-tuned clinical interventions. Here, we review the recent literature focusing on the involvement of fatty acids in the biology of immune cells, with emphasis on T cells, and cancer cells, from sensing and binding, to metabolism and downstream effects in cell signalling.
    Keywords:  T cells; cancer cells; cancer immunology; fatty acids; immune cells; metastasis
    DOI:  https://doi.org/10.15698/cst2020.01.209
  20. Front Oncol. 2019 ;9 1373
    de la Cruz López KG, Toledo Guzmán ME, Sánchez EO, García Carrancá A.
      Continuous proliferation of tumor cells requires constant adaptations of energy metabolism to rapidly fuel cell growth and division. This energetic adaptation often comprises deregulated glucose uptake and lactate production in the presence of oxygen, a process known as the "Warburg effect." For many years it was thought that the Warburg effect was a result of mitochondrial damage, however, unlike this proposal tumor cell mitochondria maintain their functionality, and is essential for integrating a variety of signals and adapting the metabolic activity of the tumor cell. The mammalian/mechanistic target of rapamycin complex 1 (mTORC1) is a master regulator of numerous cellular processes implicated in proliferation, metabolism, and cell growth. mTORC1 controls cellular metabolism mainly by regulating the translation and transcription of metabolic genes, such as peroxisome proliferator activated receptor γ coactivator-1 α (PGC-1α), sterol regulatory element-binding protein 1/2 (SREBP1/2), and hypoxia inducible factor-1 α (HIF-1α). Interestingly it has been shown that mTORC1 regulates mitochondrial metabolism, thus representing an important regulator in mitochondrial function. Here we present an overview on the role of mTORC1 in the regulation of mitochondrial functions in cancer, considering new evidences showing that mTORC1 regulates the translation of nucleus-encoded mitochondrial mRNAs that result in an increased ATP mitochondrial production. Moreover, we discuss the relationship between mTORC1 and glutaminolysis, as well as mitochondrial metabolites. In addition, mitochondrial fission processes regulated by mTORC1 and its impact on cancer are discussed. Finally, we also review the therapeutic efficacy of mTORC1 inhibitors in cancer treatments, considering its use in combination with other drugs, with particular focus on cellular metabolism inhibitors, that could help improve their anti neoplastic effect and eliminate cancer cells in patients.
    Keywords:  cancer; mTORC1; mitochondria; mitochondrial functions; therapy
    DOI:  https://doi.org/10.3389/fonc.2019.01373
  21. Cancers (Basel). 2020 Jan 01. pii: E111. [Epub ahead of print]12(1):
    Tea MN, Poonnoose SI, Pitson SM.
      Glioblastoma (GBM) is the most commonly diagnosed malignant brain tumor in adults. The prognosis for patients with GBM remains poor and largely unchanged over the last 30 years, due to the limitations of existing therapies. Thus, new therapeutic approaches are desperately required. Sphingolipids are highly enriched in the brain, forming the structural components of cell membranes, and are major lipid constituents of the myelin sheaths of nerve axons, as well as playing critical roles in cell signaling. Indeed, a number of sphingolipids elicit a variety of cellular responses involved in the development and progression of GBM. Here, we discuss the role of sphingolipids in the pathobiology of GBM, and how targeting sphingolipid metabolism has emerged as a promising approach for the treatment of GBM.
    Keywords:  ceramide; glioblastoma; sphingolipid; sphingosine 1-phosphate
    DOI:  https://doi.org/10.3390/cancers12010111
  22. Cancer Res. 2020 Jan 07. pii: canres.3574.2018. [Epub ahead of print]
    Santoro AL, Drummond RD, da Silva IT, Ferreira SS, Juliano L, Vendramini PH, Lemos MBDC, Eberlin MN, Andrade VP.
      Clinically meaningful molecular subtypes for classification of breast cancers have been established, however, initiation and progression of these subtypes remain poorly understood. The recent development of desorption electrospray ionization-mass spectrometry imaging (DESI-MSI) facilitates the convergence of analytical chemistry and traditional pathology, allowing chemical profiling with minimal tissue pre-treatment in frozen samples. Here we characterized the chemical composition of molecular subtypes of breast cancer with DESI-MSI. Regions of interest (ROI) were identified, including invasive breast cancer (IBC), ductal carcinoma in situ (DCIS), and adjacent benign tissue (ABT), and metabolomic profiles at 200μm elaborated using Biomap software and the Lasso method. Top ions identified in IBC regions included polyunsaturated fatty acids, deprotonated glycerophospholipids and sphingolipids. Highly saturated lipids, as well as antioxidant molecules [(taurine (m/z 124.0068), uric acid (m/z 167.0210), ascorbic acid (m/z 175.0241), and glutathione (m/z 306.0765)], were able to distinguish IBC form ABT. Moreover, luminal B and triple-negative subtypes showed more complex lipid profiles compared to Luminal A and HER-2 subtypes. DCIS and IBC were distinguished based on cell signaling and apoptosis-related ions [fatty acids (341.2100 and 382.3736 m/z) and glycerophospholipids (PE(P-16:0/22:6, m/z 746.5099, and PS(38:3), m/z 812.5440)]. In summary, DESI-MSI identified distinct lipid composition between DCIS and IBC and across molecular subtypes of breast cancer with potential implications for breast cancer pathogenesis.
    DOI:  https://doi.org/10.1158/0008-5472.CAN-18-3574
  23. Int J Oncol. 2020 Jan 10.
    Feng Y, Tang Y, Mao Y, Liu Y, Yao D, Yang L, Garson K, Vanderhyden BC, Wang Q.
      Ovarian cancer is the fifth most common type of cancer afflicting women and frequently presents at a late stage with a poor prognosis. While paired box 2 (PAX2) expression is frequently lost in high‑grade serous ovarian cancer, it is expressed in a subset of ovarian tumors and may play a role in tumorigenesis. This study investigated the expression of PAX2 in ovarian cancer. The expression of PAX2 in a murine allograft model of ovarian cancer, the RM model, led to a more rapidly growing cell line both in vitro and in vivo. This finding was in accordance with the shorter progression‑free survival observed in patients with a higher PAX2 expression, as determined in this study cohort by immunohistochemistry. iTRAQ‑based proteomic profiling revealed that proteins involved in fatty acid metabolism and oxidative phosphorylation were found to be upregulated in RM tumors expressing PAX2. The expression of two key fatty acid metabolic genes was also found to be upregulated in PAX2‑expressing human ovarian cancer samples. The analysis of existing datasets also indicated that a high expression of key enzymes in fatty acid metabolism was associated with a shorter progression‑free survival time in patients with serous ovarian cancer. Thus, on the whole, the findings of this study indicate that PAX2 may promote ovarian cancer progression, involving fatty acid metabolic reprograming.
    DOI:  https://doi.org/10.3892/ijo.2020.4958
  24. Expert Rev Proteomics. 2020 Jan 09. 1-15
    Cao WQ, Liu MQ, Kong SY, Wu MX, Huang ZZ, Yang PY.
      Introduction: Glycomics, which aims to define the glycome of a biological system to better assess the biological attributes of the glycans, has attracted increasing interest. However, the complexity and diversity of glycans present challenging barriers to glycome definition. Technological advances are major drivers in glycomics.Areas covered: This review summarizes the main methods and emphasizes the most recent advances in mass spectrometry-based methods regarding glycomics following the general workflow in glycomic analysis.Expert opinion: Recent mass spectrometry-based technological advances have significantly lowered the barriers in glycomics. The field of glycomics is moving toward both generic and precise analysis.
    Keywords:  Glycomics; Mass spectrometry-based analysis; Technological advances
    DOI:  https://doi.org/10.1080/14789450.2020.1708199
  25. Anal Chem. 2020 Jan 08.
    Fang Z, Wang R, Zhao H, Yao H, Ouyang J, Zhang X.
      Discrimination of cancer cells at single-cell metabolic level is crucial for early diagnosis. However, some cancer cells share similar metabolic information with normal cells, which make it difficult to be distinguished using mass spectrometry. Here-in, we propose a method by treating osteosarcoma cells and normal human osteoblasts with mannose as a stimulant, which greatly promote the metabolic discrimination of osteosarcoma cells at single-cell level. The low PMI (mannose 6-phosphate isomerase) level of both osteosarcoma cell lines comparing to normal human osteoblasts is the reason of abnormal metabolic pathway of two osteosarcoma cell lines with mannose treatment. We also found that the level of hexoses-6P in osteosarcoma cells significantly increased after mannose treatment, while no such increasement was found in normal human osteoblast. The proposed method is very meaningful for early diagnosis of cancer.
    DOI:  https://doi.org/10.1021/acs.analchem.9b04773
  26. Cancers (Basel). 2019 Dec 30. pii: E90. [Epub ahead of print]12(1):
    Lyssiotis CA, Nagrath D.
      Metabolic programs are rewired in tumors to support growth, progression, and immune evasion. A wealth of work in the past decade has delineated how these metabolic rearrangements are facilitated by signaling pathways downstream of oncogene activation and tumor suppressor loss. More recently, this field has expanded to include metabolic interactions among the diverse cell types that exist within a tumor and how this impacts the immune system. In this special issue, 17 review articles discuss these phenomena, and, alongside four original research manuscripts, the vulnerabilities associated with deregulated metabolic programming are highlighted and examined.
    Keywords:  amino acids; cancer associated fibroblasts; cancer metabolism; carbohydrates; iron; lipids; nucleotides; reactive oxygen species; redox; tumor microenvironment
    DOI:  https://doi.org/10.3390/cancers12010090
  27. Cell Stress. 2020 Jan 03. 4(1): 24-26
    Venkateswaran N, Conacci-Sorrell M.
      Tryptophan is one of the eight essential amino acids that must be obtained from the diet. Interestingly, tryptophan is the least abundant amino acid in most proteins, a large portion of cellular tryptophan is converted into metabolites of the serotonin and kynurenine pathways. In a recent study, (Venkateswaran, Lafita-Navarro et al., 2019, Genes Dev), we discovered that colon cancer cells display greater uptake and processing of tryptophan than normal colonic cells and tissues. This process is mediated by the oncogenic transcription factor MYC that promotes the expression of the tryptophan importers SLC1A5 and SLC7A5 and the tryptophan metabolizing enzyme AFMID. The metabolism of tryptophan in colon cancer cells generates kynurenine, a biologically active metabolite necessary to maintain continuous cell proliferation. Our results indicate that kynurenine functions as an oncometabolite, at least in part, by activating the transcription factor AHR, which then regulates growth promoting genes in cancer cells. We propose that blocking kynurenine production or activity can be an efficient approach to specifically limit the growth of colon cancer cells. Here, we describe our findings and new questions for future studies targeted at understanding AHR-independent function of kynurenine, as well as interfering with the enzyme AFMID as a new strategy to target the kynurenine pathway.
    Keywords:  AHR; IDO1; MYC; TDO2; colon cancer; kynurenine; tryptophan
    DOI:  https://doi.org/10.15698/cst2020.01.210
  28. FASEB J. 2020 Jan;34(1): 303-315
    Kľučková K, Thakker A, Vettore L, Escribano-Gonzalez C, Hindshaw RL, Tearle JLE, Goncalves J, Kaul B, Lavery GG, Favier J, Tennant DA.
      Mutations in succinate dehydrogenase (SDH) lead to the development of tumors in a restricted subset of cell types, including chromaffin cells and paraganglia. The molecular basis for this specificity is currently unknown. We show that loss of SDH activity in a chromaffin cell model does not perturb complex I function, retaining the ability to oxidize NADH within the electron transport chain. This activity supports continued oxidation of substrates within the tricarboxylic acid (TCA) cycle. However, due to the block in the TCA cycle at SDH, the high glutamine oxidation activity is only maintained through an efflux of succinate. We also show that although the mitochondria of SDH-deficient cells are less active per se, their higher mass per cell results in an overall respiratory rate that is comparable with wild-type cells. Finally, we observed that when their mitochondria are uncoupled, SDH-deficient cells are unable to preserve their viability, suggesting that the mitochondrial metabolic network is unable to compensate when exposed to additional stress. We therefore show that in contrast to models of SDH deficiency based on epithelial cells, a chromaffin cell model retains aspects of metabolic "health," which could form the basis of cell specificity of this rare tumor type.
    Keywords:  electron transport chain; metabolism; mitochondria; pheochromocytoma; succinate dehydrogenase
    DOI:  https://doi.org/10.1096/fj.201901456R
  29. Mass Spectrom Rev. 2020 Jan 05.
    Cui JJ, Wang LY, Tan ZR, Zhou HH, Zhan X, Yin JY.
      Personalized drug therapy aims to provide tailored treatment for individual patient. Mass spectrometry (MS) is revolutionarily involved in this area because MS is a rapid, customizable, cost-effective, and easy to be used high-throughput method with high sensitivity, specificity, and accuracy. It is driving the formation of a new field, MS-based personalized drug therapy, which currently mainly includes five subfields: therapeutic drug monitoring (TDM), pharmacogenomics (PGx), pharmacomicrobiomics, pharmacoepigenomics, and immunopeptidomics. Gas chromatography-MS (GC-MS) and liquid chromatography-MS (LC-MS) are considered as the gold standard for TDM, which can be used to optimize drug dosage. Matrix-assisted laser desorption ionization-time of flight-MS (MALDI-TOF-MS) significantly improves the capability of detecting biomacromolecule, and largely promotes the application of MS in PGx. It is becoming an indispensable tool for genotyping, which is used to discover and validate genetic biomarkers. In addition, MALDI-TOF-MS also plays important roles in identity of human microbiome whose diversity can explain interindividual differences of drug response. Pharmacoepigenetics is to study the role of epigenetic factors in individualized drug treatment. MS can be used to discover and validate pharmacoepigenetic markers (DNA methylation, histone modification, and noncoding RNA). For the emerging cancer immunotherapy, personalized cancer vaccine has effective immunotherapeutic activity in the clinic. MS-based immunopeptidomics can effectively discover and screen neoantigens. This article systematically reviewed MS-based personalized drug therapy in the above mentioned five subfields. © 2020 Wiley Periodicals, Inc. Mass Spec Rev.
    Keywords:  cancer immunotherapy; immunopeptidomics; mass spectrometry; personalized drug therapy; pharmacoepigenomics; pharmacogenomics (PGx); pharmacomicrobiomics; precision medicine; therapeutic drug monitoring (TDM)
    DOI:  https://doi.org/10.1002/mas.21620
  30. Chembiochem. 2020 Jan 10.
    Bush JT, Chan MC, Mohammed S, Schofield C.
      The hypoxia-inducible factors (HIFs) are key transcription factors in determining cellular responses involving alterations in protein levels in response to limiting oxygen availability in animal cells. 2-Oxoglurate dependent oxygenases play key roles in regulating HIF levels and its transcriptional activity. We describe MS-based proteomics studies employing a lysine demethylation-based approach in which we compared the results of treating human breast cancer MCF-7 cells with hypoxia or a cell-penetrating derivative (dimethyl N-oxalylglycine) of the stable 2OG analogue N-oxalylglycine. The proteomic results are consistent with reported transcriptomic analyses and support the proposed key roles of 2OG dependent HIF prolyl- and asparaginyl-hydroxylases in the hypoxic response. Differences between the data sets for hypoxia and DMOG may reflect context-dependent effects or HIF-independent effects of DMOG.
    Keywords:  EGLN, factor inhibiting HIF(FIH), proteomics, oxygen; hypoxia, 2-oxoglutarate; α-ketoglutarate oxygenases, hypoxia inducible factor (HIF) prolyl- and asparaginyl-hydroxylases, PHDs
    DOI:  https://doi.org/10.1002/cbic.201900719
  31. Cancer Metab. 2020 ;8 1
    Nelson BS, Lin L, Kremer DM, Sousa CM, Cotta-Ramusino C, Myers A, Ramos J, Gao T, Kovalenko I, Wilder-Romans K, Dresser J, Davis M, Lee HJ, Nwosu ZC, Campit S, Mashadova O, Nicolay BN, Tolstyka ZP, Halbrook CJ, Chandrasekaran S, Asara JM, Crawford HC, Cantley LC, Kimmelman AC, Wahl DR, Lyssiotis CA.
      Background: Metabolic programs in cancer cells are influenced by genotype and the tissue of origin. We have previously shown that central carbon metabolism is rewired in pancreatic ductal adenocarcinoma (PDA) to support proliferation through a glutamate oxaloacetate transaminase 1 (GOT1)-dependent pathway.Methods: We utilized a doxycycline-inducible shRNA-mediated strategy to knockdown GOT1 in PDA and colorectal cancer (CRC) cell lines and tumor models of similar genotype. These cells were analyzed for the ability to form colonies and tumors to test if tissue type impacted GOT1 dependence. Additionally, the ability of GOT1 to impact the response to chemo- and radiotherapy was assessed. Mechanistically, the associated specimens were examined using a combination of steady-state and stable isotope tracing metabolomics strategies and computational modeling. Statistics were calculated using GraphPad Prism 7. One-way ANOVA was performed for experiments comparing multiple groups with one changing variable. Student's t test (unpaired, two-tailed) was performed when comparing two groups to each other. Metabolomics data comparing three PDA and three CRC cell lines were analyzed by performing Student's t test (unpaired, two-tailed) between all PDA metabolites and CRC metabolites.
    Results: While PDA exhibits profound growth inhibition upon GOT1 knockdown, we found CRC to be insensitive. In PDA, but not CRC, GOT1 inhibition disrupted glycolysis, nucleotide metabolism, and redox homeostasis. These insights were leveraged in PDA, where we demonstrate that radiotherapy potently enhanced the effect of GOT1 inhibition on tumor growth.
    Conclusions: Taken together, these results illustrate the role of tissue type in dictating metabolic dependencies and provide new insights for targeting metabolism to treat PDA.
    Keywords:  CRC; Colorectal cancer; Fluxomics; Metabolomics; NADPH; PDA; Pancreatic cancer; Redox; Stable isotope tracing
    DOI:  https://doi.org/10.1186/s40170-019-0202-2
  32. Metabolomics. 2020 Jan 10. 16(1): 14
    Albóniga OE, González O, Alonso RM, Xu Y, Goodacre R.
      INTRODUCTION: Several software packages containing diverse algorithms are available for processing Liquid Chromatography-Mass Spectrometry (LC-MS) chromatographic data and within these deconvolution packages different parameters settings can lead to different outcomes. XCMS is the most widely used peak picking and deconvolution software for metabolomics, but the parameter selection can be hard for inexpert users. To solve this issue, the automatic optimization tools such as Isotopologue Parameters Optimization (IPO) can be extremely helpful.OBJECTIVES: To evaluate the suitability of IPO as a tool for XCMS parameters optimization and compare the results with those manually obtained by an exhaustive examination of the LC-MS characteristics and performance.
    METHODS: Raw HPLC-TOF-MS data from two types of biological samples (liver and plasma) analysed in both positive and negative electrospray ionization modes from three groups of piglets were processed with XCMS using parameters optimized following two different approaches: IPO and Manual. The outcomes were compared to determine the advantages and disadvantages of using each method.
    RESULTS: IPO processing produced the higher number of repeatable (%RSD < 20) and significant features for all data sets and allowed the different piglet groups to be distinguished. Nevertheless, on multivariate level, similar clustering results were obtained by Principal Component Analysis (PCA) when applied to IPO and manual matrices.
    CONCLUSION: IPO is a useful optimization tool that helps in choosing the appropriate parameters. It works well on data with a good LC-MS performance but the lack of such adequate data can result in unrealistic parameter settings, which might require further investigation and manual tuning. On the contrary, manual selection criteria requires deeper knowledge on LC-MS, programming language and XCMS parameter interpretation, but allows a better fine-tuning of the parameters, and thus more robust deconvolution.
    Keywords:  Data treatment; IPO; LC–MS; Metabolomics; XCMS
    DOI:  https://doi.org/10.1007/s11306-020-1636-9
  33. Nat Methods. 2020 Jan;17(1): 24
    Singh A.
      
    DOI:  https://doi.org/10.1038/s41592-019-0710-6