bims-mascan Biomed News
on Mass spectrometry in cancer research
Issue of 2020‒10‒25
eighteen papers selected by
Giovanny Rodriguez Blanco
University of Edinburgh


  1. Molecules. 2020 Oct 20. pii: E4831. [Epub ahead of print]25(20):
    Li J, Eu JQ, Kong LR, Wang L, Lim YC, Goh BC, Wong ALA.
      Targeting altered tumour metabolism is an emerging therapeutic strategy for cancer treatment. The metabolic reprogramming that accompanies the development of malignancy creates targetable differences between cancer cells and normal cells, which may be exploited for therapy. There is also emerging evidence regarding the role of stromal components, creating an intricate metabolic network consisting of cancer cells, cancer-associated fibroblasts, endothelial cells, immune cells, and cancer stem cells. This metabolic rewiring and crosstalk with the tumour microenvironment play a key role in cell proliferation, metastasis, and the development of treatment resistance. In this review, we will discuss therapeutic opportunities, which arise from dysregulated metabolism and metabolic crosstalk, highlighting strategies that may aid in the precision targeting of altered tumour metabolism with a focus on combinatorial therapeutic strategies.
    Keywords:  cancer cell metabolism; immunotherapy; metabolic reprogramming; targeted therapy; tumour microenvironment
    DOI:  https://doi.org/10.3390/molecules25204831
  2. Nutrients. 2020 Oct 19. pii: E3188. [Epub ahead of print]12(10):
    Quillen EE, Beavers DP, O'Brien Cox A, Furdui CM, Lee J, Miller RM, Wu H, Beavers KM.
      Inter-individual response to dietary interventions remains a major challenge to successful weight loss among older adults. This study applied metabolomics technology to identify small molecule signatures associated with a loss of fat mass and overall weight in a cohort of older adults on a nutritionally complete, high-protein diet. A total of 102 unique metabolites were measured using liquid chromatography-mass spectrometry (LC-MS) for 38 adults aged 65-80 years randomized to dietary intervention and 36 controls. Metabolite values were analyzed in both baseline plasma samples and samples collected following the six-month dietary intervention to consider both metabolites that could predict the response to diet and those that changed in response to diet or weight loss.Eight metabolites changed over the intervention at a nominally significant level: D-pantothenic acid, L-methionine, nicotinate, aniline, melatonin, deoxycarnitine, 6-deoxy-L-galactose, and 10-hydroxydecanoate. Within the intervention group, there was broad variation in the achieved weight-loss and dual-energy x-ray absorptiometry (DXA)-defined changes in total fat and visceral adipose tissue (VAT) mass. Change in the VAT mass was significantly associated with the baseline abundance of α-aminoadipate (p = 0.0007) and an additional mass spectrometry peak that may represent D-fructose, myo-inositol, mannose, α-D-glucose, allose, D-galactose, D-tagatose, or L-sorbose (p = 0.0001). This hypothesis-generating study reflects the potential of metabolomic biomarkers for the development of personalized dietary interventions.
    Keywords:  aging; body composition; heterogeneity; metabolomics; weight loss
    DOI:  https://doi.org/10.3390/nu12103188
  3. Rev Physiol Biochem Pharmacol. 2020 Oct 17.
    Petan T.
      Lipid droplets have a unique structure among organelles consisting of a dense hydrophobic core of neutral lipids surrounded by a single layer of phospholipids decorated with various proteins. Often labeled merely as passive fat storage repositories, they in fact have a remarkably dynamic life cycle. Being formed within the endoplasmic reticulum membrane, lipid droplets rapidly grow, shrink, traverse the cytosol, and engage in contacts with other organelles to exchange proteins and lipids. Their lipid and protein composition changes dynamically in response to cellular states and nutrient availability. Remarkably, their biogenesis is induced when cells experience various forms of nutrient, energy, and redox imbalances, including lipid excess and complete nutrient deprivation. Cancer cells are continuously exposed to nutrient and oxygen fluctuations and have the capacity to switch between alternative nutrient acquisition and metabolic pathways in order to strive even during severe stress. Their supply of lipids is ensured by a series of nutrient uptake and scavenging mechanisms, upregulation of de novo lipid synthesis, repurposing of their structural lipids via enzymatic remodeling, or lipid recycling through autophagy. Importantly, most of these pathways of lipid acquisition converge at lipid droplets, which combine different lipid fluxes and control their usage based on specific cellular needs. It is thus not surprising that lipid droplet breakdown is an elaborately regulated process that occurs via a complex interplay of neutral lipases and autophagic degradation. Cancer cells employ lipid droplets to ensure energy production and redox balance, modulate autophagy, drive membrane synthesis, and control its composition, thereby minimizing stress and fostering tumor progression. As regulators of (poly)unsaturated fatty acid trafficking, lipid droplets are also emerging as modulators of lipid peroxidation and sensitivity to ferroptosis. Clearly, dysregulated lipid droplet turnover may also be detrimental to cancer cells, which should provide potential therapeutic opportunities in the future. In this review, we explore how lipid droplets consolidate lipid acquisition and trafficking pathways in order to match lipid supply with the requirements for cancer cell survival, growth, and metastasis.
    Keywords:  Autophagy; Cancer; Fatty acid; Ferroptosis; Lipid droplets; Metabolism; Stress
    DOI:  https://doi.org/10.1007/112_2020_51
  4. Mol Cell Proteomics. 2020 Oct 19. pii: mcp.RA120.002150. [Epub ahead of print]
    Guo Z, Pan F, Peng L, Tian S, Jiao J, Liao L, Lu C, Zhai G, Wu Z, Dong H, Xu X, Wu J, Chen P, Bai X, Lin D, Xu LY, Li EM, Zhang K.
      Esophageal squamous cell cancer (ESCC) is an aggressive malignancy with poor therapeutic outcomes. However, the alterations in proteins and post-translational modifications (PTMs) leading to the pathogenesis of ESCC remains unclear. Here, we provide the comprehensive characterization of the proteome, phosphorylome, lysine acetylome and succinylome for ESCC and matched control cells using quantitative proteomic approach. We identify abnormal protein and post-translational modification (PTM) pathways, including significantly downregulated lysine succinylation sites in cancer cells. Focusing on hyposuccinylation, we reveal that this altered PTM was enriched on enzymes of metabolic pathways inextricably linked with cancer metabolism. Importantly, ESCC malignant behaviors such as cell migration are inhibited once the level of succinylation was restored in vitro or in vivo This effect was further verified by mutations to disrupt succinylation sites in candidate proteins. Meanwhile, we found that succinylation has a negative regulatory effect on histone methylation to promote cancer migration. Finally, hyposuccinylation is confirmed in primary ESCC specimens. Our findings together demonstrate that lysine succinylation may alter ESCC metabolism and migration, providing new insights into the functional significance of PTM in cancer biology.
    Keywords:  Acetylation*; Cancer Biology*; Cell Migration; Cell biology*; Esophageal Squamous Cell Cancer; Histones*; Lysine succinylation; Mass Spectrometry; Post-translational modifications*; Proteomics; SILAC; post-translational modifications
    DOI:  https://doi.org/10.1074/mcp.RA120.002150
  5. Metabolites. 2020 Oct 16. pii: E415. [Epub ahead of print]10(10):
    Correia MSP, Lin W, Aria AJ, Jain A, Globisch D.
      Metabolomics analysis of biological samples is widely applied in medical and natural sciences. Assigning the correct chemical structure in the metabolite identification process is required to draw the correct biological conclusions and still remains a major challenge in this research field. Several metabolite tandem mass spectrometry (MS/MS) fragmentation spectra libraries have been developed that are either based on computational methods or authentic libraries. These libraries are limited due to the high number of structurally diverse metabolites, low commercial availability of these compounds, and the increasing number of newly discovered metabolites. Phase II modification of xenobiotics is a compound class that is underrepresented in these databases despite their importance in diet, drug, or microbiome metabolism. The O-sulfated metabolites have been described as a signature for the co-metabolism of bacteria and their human host. Herein, we have developed a straightforward chemical synthesis method for rapid preparation of sulfated metabolite standards to obtain mass spectrometric fragmentation pattern and retention time information. We report the preparation of 38 O-sulfated alcohols and phenols for the determination of their MS/MS fragmentation pattern and chromatographic properties. Many of these metabolites are regioisomers that cannot be distinguished solely by their fragmentation pattern. We demonstrate that the versatility of this method is comparable to standard chemical synthesis. This comprehensive metabolite library can be applied for co-injection experiments to validate metabolites in different human sample types to explore microbiota-host co-metabolism, xenobiotic, and diet metabolism.
    Keywords:  chemical synthesis; metabolomics; microbiome; phase II metabolism; structure validation; sulfated metabolites
    DOI:  https://doi.org/10.3390/metabo10100415
  6. iScience. 2020 Oct 23. 23(10): 101569
    Wu X, Geng F, Cheng X, Guo Q, Zhong Y, Cloughesy TF, Yong WH, Chakravarti A, Guo D.
      Recently, lipid metabolism reprogramming has been further evidenced in malignancies via the observation of large amounts of lipid droplets (LDs) in human tumors, including in glioblastoma (GBM), the most lethal primary brain tumor. However, the role played by LDs in tumor cells remains unknown. Here, we show that triglycerides (TG), the major components of LDs, serve as a critical energy reservoir to support GBM cell survival. TG/LDs rapidly diminished in GBM cells upon glucose reduction, whereas inhibiting fatty acid oxidation or autophagy resulted in the accumulation of TG/LDs and strongly potentiated GBM cell death. Immunofluorescence imaging and time-lapse videos showed that LDs are hydrolyzed by autophagy to release free fatty acids that mobilize into mitochondria for energy production. Our study demonstrates that autophagy-mediated hydrolysis of TG/LDs maintains energy homeostasis and GBM survival upon glucose reduction, suggesting that limiting TG/LDs utilization might be necessary upon treating GBM.
    Keywords:  Cancer; Cell Biology; Cellular Physiology
    DOI:  https://doi.org/10.1016/j.isci.2020.101569
  7. Oncogene. 2020 Oct 20.
    Zhang Q, Zhou W, Yu S, Ju Y, To SKY, Wong AST, Jiao Y, Poon TCW, Tam KY, Lee LTO.
      As a result of the hostile microenvironment, metabolic alterations are required to enable the malignant growth of cancer cells. To understand metabolic reprogramming during metastasis, we conducted shotgun proteomic analysis of highly metastatic (HM) and non-metastatic (NM) ovarian cancer cells. The results suggest that the genes involved in fatty-acid (FA) metabolism are upregulated, with consequent increases of phospholipids with relatively short FA chains (myristic acid, MA) in HM cells. Among the upregulated proteins, ACSL1 expression could convert the lipid profile of NM cells to that similar of HM cells and make them highly aggressive. Importantly, we demonstrated that ACSL1 activates the AMP-activated protein kinase and Src pathways via protein myristoylation and finally enhances FA beta oxidation. Patient samples and tissue microarray data also suggested that omentum metastatic tumours have higher ACSL1 expression than primary tumours and a strong association with poor clinical outcome. Overall, our data reveal that ACSL1 enhances cancer metastasis by regulating FA metabolism and myristoylation.
    DOI:  https://doi.org/10.1038/s41388-020-01516-4
  8. Cell Death Discov. 2020 ;6 104
    Burke L, Guterman I, Palacios Gallego R, Britton RG, Burschowsky D, Tufarelli C, Rufini A.
      The metabolism of the non-essential amino acid L-proline is emerging as a key pathway in the metabolic rewiring that sustains cancer cells proliferation, survival and metastatic spread. Pyrroline-5-carboxylate reductase (PYCR) and proline dehydrogenase (PRODH) enzymes, which catalyze the last step in proline biosynthesis and the first step of its catabolism, respectively, have been extensively associated with the progression of several malignancies, and have been exposed as potential targets for anticancer drug development. As investigations into the links between proline metabolism and cancer accumulate, the complexity, and sometimes contradictory nature of this interaction emerge. It is clear that the role of proline metabolism enzymes in cancer depends on tumor type, with different cancers and cancer-related phenotypes displaying different dependencies on these enzymes. Unexpectedly, the outcome of rewiring proline metabolism also differs between conditions of nutrient and oxygen limitation. Here, we provide a comprehensive review of proline metabolism in cancer; we collate the experimental evidence that links proline metabolism with the different aspects of cancer progression and critically discuss the potential mechanisms involved.
    Keywords:  Cancer; Cancer metabolism
    DOI:  https://doi.org/10.1038/s41420-020-00341-8
  9. Mol Omics. 2020 Oct 20.
    Yuan W, Wang J, Zhang Y, Lu H.
      Lipid-derived electrophile (LDE) modifications, which are covalent modifications of proteins by endogenous LDEs, are essential types of protein posttranslational modifications. LDE modifications alter the protein structure and regulate their biological processes in cells. LDE modifications of proteins are also closely associated with several diseases and function as potential biomarkers for clinical diagnosis. The crucial step in studying the LDE modifications is to enrich the LDE modified proteins/peptides from complex biological samples with high efficiency and high selectivity and quantify modified proteins/peptides with high accuracy. In this review, we summarize the recent progress in MS-based proteomic technologies to globally identify and quantify LDE modified proteomes, mainly focusing on discussing the qualitative and quantitative technologies.
    DOI:  https://doi.org/10.1039/d0mo00099j
  10. Cell Death Differ. 2020 Oct 23.
    Wang K, Zhang Z, Tsai HI, Liu Y, Gao J, Wang M, Song L, Cao X, Xu Z, Chen H, Gong A, Wang D, Cheng F, Zhu H.
      Ferroptosis, a form of iron-dependent cell death driven by cellular metabolism and iron-dependent lipid peroxidation, has been implicated as a tumor-suppressor function for cancer therapy. Recent advance revealed that the sensitivity to ferroptosis is tightly linked to numerous biological processes, including metabolism of amino acid and the biosynthesis of glutathione. Here, by using a high-throughput CRISPR/Cas9-based genetic screen in HepG2 hepatocellular carcinoma cells to search for metabolic proteins inhibiting ferroptosis, we identified a branched-chain amino acid aminotransferase 2 (BCAT2) as a novel suppressor of ferroptosis. Mechanistically, ferroptosis inducers (erastin, sorafenib, and sulfasalazine) activated AMPK/SREBP1 signaling pathway through iron-dependent ferritinophagy, which in turn inhibited BCAT2 transcription. We further confirmed that BCAT2 as the key enzyme mediating the metabolism of sulfur amino acid, regulated intracellular glutamate level, whose activation by ectopic expression specifically antagonize system Xc- inhibition and protected liver and pancreatic cancer cells from ferroptosis in vitro and in vivo. On the contrary, direct inhibition of BCAT2 by RNA interference, or indirect inhibition by blocking system Xc- activity, triggers ferroptosis. Finally, our results demonstrate the synergistic effect of sorafenib and sulfasalazine in downregulating BCAT2 expression and dictating ferroptotic death, where BCAT2 can also be used to predict the responsiveness of cancer cells to ferroptosis-inducing therapies. Collectively, these findings identify a novel role of BCAT2 in ferroptosis, suggesting a potential therapeutic strategy for overcoming sorafenib resistance.
    DOI:  https://doi.org/10.1038/s41418-020-00644-4
  11. Front Med. 2020 Oct 19.
    Zhang D, Xu X, Ye Q.
      Breast cancer is one of the most common malignancies that seriously threaten women's health. In the process of the malignant transformation of breast cancer, metabolic reprogramming and immune evasion represent the two main fascinating characteristics of cancer and facilitate cancer cell proliferation. Breast cancer cells generate energy through increased glucose metabolism. Lipid metabolism contributes to biological signal pathways and forms cell membranes except energy generation. Amino acids act as basic protein units and metabolic regulators in supporting cell growth. For tumor-associated immunity, poor immunogenicity and heightened immunosuppression cause breast cancer cells to evade the host's immune system. For the past few years, the complex mechanisms of metabolic reprogramming and immune evasion are deeply investigated, and the genes involved in these processes are used as clinical therapeutic targets for breast cancer. Here, we review the recent findings related to abnormal metabolism and immune characteristics, regulatory mechanisms, their links, and relevant therapeutic strategies.
    Keywords:  breast cancer; cancer stem cells; immunity; metabolism
    DOI:  https://doi.org/10.1007/s11684-020-0793-6
  12. iScience. 2020 Sep 25. 23(9): 101535
    Tanosaki S, Tohyama S, Fujita J, Someya S, Hishiki T, Matsuura T, Nakanishi H, Ohto-Nakanishi T, Akiyama T, Morita Y, Kishino Y, Okada M, Tani H, Soma Y, Nakajima K, Kanazawa H, Sugimoto M, Ko MSH, Suematsu M, Fukuda K.
      The role of lipid metabolism in human pluripotent stem cells (hPSCs) is poorly understood. We have used large-scale targeted proteomics to demonstrate that undifferentiated hPSCs express different fatty acid (FA) biosynthesis-related enzymes, including ATP citrate lyase and FA synthase (FASN), than those expressed in hPSC-derived cardiomyocytes (hPSC-CMs). Detailed lipid profiling revealed that inhibition of FASN resulted in significant reduction of sphingolipids and phosphatidylcholine (PC); moreover, we found that PC was the key metabolite for cell survival in hPSCs. Inhibition of FASN induced cell death in undifferentiated hPSCs via mitochondria-mediated apoptosis; however, it did not affect cell survival in hPSC-CMs, neurons, or hepatocytes as there was no significant reduction of PC. Furthermore, we did not observe tumor formation following transplantation of FASN inhibitor-treated cells. Our findings demonstrate the importance of de novo FA synthesis in the survival of undifferentiated hPSCs and suggest applications for FASN inhibition in regenerative medicine.
    Keywords:  Biological Sciences; Cell Biology; Metabolic Flux Analysis; Metabolomics; Proteomics; Stem Cells Research
    DOI:  https://doi.org/10.1016/j.isci.2020.101535
  13. Anal Chim Acta. 2020 Nov 01. pii: S0003-2670(20)30887-4. [Epub ahead of print]1136 115-124
    Chen X, Yin Y, Zhou Z, Li T, Zhu ZJ.
      Lipids are an important class of biomolecules, and play many essential functions in biology. Ion mobility-mass spectrometry (IM-MS) has emerged as a promising technology for lipidomics by providing a holistic and multi-dimensional characterization of lipid structures. However, the lipid identification using the multi-dimensional match (i.e., MS1, retention time, collision cross section, and MS/MS spectra) gives multiple lipid candidates, and often over-reports the structural information. Here, we developed a lipid identification strategy that integrated library-based match and rule-based refinement for accurate lipid structural elucidation in IM-MS based lipidomics. The new strategy took the advantage of multi-dimensional information for high-coverage identification, while it also utilized the fragmentation rules to determine the accurate structural information. We demonstrated that the combined strategy accurately determined the lipid structures as lipid species level, fatty acyl level, or fatty acyl position level for different lipid classes in the lipid standard mixture and various biological samples. The combined strategy efficiently reduced the redundancy and improved the accuracy for different lipid classes, and identified a total of 440-960 lipid species in various biological samples. Finally, we performed quantitative lipidomics analysis of NIST SRM 1950 human plasma using IM-MS technology. The measured concentrations of most quantified lipids (>80%) were highly consistent with values reported from other independent laboratories. In summary, the developed lipid identification strategy allowed for the accurate identification of lipid structures, and facilitated accurate lipid quantification in IM-MS based untargeted lipidomics.
    Keywords:  Ion mobility-mass spectrometry; Library-based 4D match; Lipidomics; Quantification; Rule-based refinement
    DOI:  https://doi.org/10.1016/j.aca.2020.08.048
  14. Signal Transduct Target Ther. 2020 Oct 19. 5(1): 242
    Yang E, Wang X, Gong Z, Yu M, Wu H, Zhang D.
      Metabolic reprogramming is reported to be one of the hallmarks of cancer, which is an adaptive mechanism by which fast-growing cancer cells adapt to their increasing energy demands. Recently, extracellular vesicles (EVs) known as exosomes have been recognized as crucial signaling mediators in regulating the tumor microenvironment (TME). Meanwhile, the TME is a highly heterogeneous ecosystem incorporating cancer cells, fibroblasts, adipocytes, endothelial cells, mesenchymal stem cells, and extracellular matrix. Accumulated evidence indicates that exosomes may transfer biologically functional molecules to the recipient cells, which facilitate cancer progression, angiogenesis, metastasis, drug resistance, and immunosuppression by reprogramming the metabolism of cancer cells and their surrounding stromal cells. In this review, we present the role of exosomes in the TME and the underlying mechanism of how exosomes exacerbate tumor development through metabolic reprogramming. In addition, we will also discuss the potential role of exosomes targeting metabolic process as biomarkers for tumor diagnosis and prognosis, and exosomes-mediated metabolic reprogramming as potential targets for cancer therapy. Furthermore, a better understanding of the link between exosomes and metabolic reprogramming, and their impact on cancer progression, would provide novel insights for cancer prevention and treatment in the future.
    DOI:  https://doi.org/10.1038/s41392-020-00359-5
  15. Molecules. 2020 Oct 21. pii: E4864. [Epub ahead of print]25(20):
    Guo R, Chen Y, Borgard H, Jijiwa M, Nasu M, He M, Deng Y.
      Lipids are essential components of cell structure and play important roles in signal transduction between cells and body metabolism. With the continuous development and innovation of lipidomics technology, many studies have shown that the relationship between lipids and cancer is steadily increasing, involving cancer occurrence, proliferation, migration, and apoptosis. Breast cancer has seriously affected the safety and quality of life of human beings worldwide and has become a significant public health problem in modern society, with an especially high incidence among women. Therefore, the issue has inspired scientific researchers to study the link between lipids and breast cancer. This article reviews the research progress of lipidomics, the biological characteristics of lipid molecules, and the relationship between some lipids and cancer drug resistance. Furthermore, this work summarizes the lipid molecules related to breast cancer diagnosis and prognosis, and then it clarifies their impact on the occurrence and development of breast cancer The discussion revolves around the current research hotspot long-chain non-coding RNAs (lncRNAs), summarizes and explains their impact on tumor lipid metabolism, and provides more scientific basis for future cancer research studies.
    Keywords:  breast cancer; diagnosis; drug resistance; lipidomics; lipids; lncRNAs; prognosis
    DOI:  https://doi.org/10.3390/molecules25204864
  16. Cell Death Differ. 2020 Oct 20.
    Krassikova L, Zhang B, Nagarajan D, Queiroz AL, Kacal M, Samakidis E, Vakifahmetoglu-Norberg H, Norberg E.
      Cancer cells undergo complex metabolic alterations. The mechanisms underlying the tuning of cancer metabolism are under active investigation. Here, we identify the uncharacterized deubiquitinase JOSD2 as a positive regulator of cancer cell proliferation by displaying comprehensive effects on glucose catabolism. We found that JOSD2 directly controls a metabolic enzyme complex that includes Aldolase A, Phosphofructokinase-1 and Phosphoglycerate dehydrogenase, in vitro and in vivo. Further, JOSD2 expression, but not a catalytically inactive mutant, deubiquitinates and stabilizes the enzyme complex, thereby enhancing their activities and the glycolytic rate. This represents a selective JOSD2 feature that is not shared among other Machado-Joseph disease DUBs or observed in nontransformed cells. JOSD2 deficiency displays cytostatic effects and reduces glycolysis in a broad spectrum of tumor cells of distinct origin and its expression correlates with poor prognosis in non-small cell lung cancer. Overall, our study provides evidence for a previously unknown biological mechanism in which JOSD2 integrates glucose and serine metabolism with potential therapeutic implications.
    DOI:  https://doi.org/10.1038/s41418-020-00639-1
  17. J Agric Food Chem. 2020 Oct 19.
    Fushimi T, Izumi Y, Takahashi M, Hata K, Murano Y, Bamba T.
      Several studies in hepatocyte cell lines reported that medium-chain fatty acids (MCFAs) with 6-12 carbons showed different metabolic properties from long-chain fatty acids (LCFAs). However, these studies reported unclear effects of different fatty acid molecules on hepatocyte metabolism. This study is aimed to capture the metabolic kinetics of MCFA assimilation in AML12 cells treated with octanoic acid (FA 8:0), decanoic acid (FA 10:0), or lauric acid (FA12:0) [LCFA; oleic acid (FA 18:1)] via metabolic profiling and dynamic metabolome analysis with 13C-labeling. The concentrations of total ketone bodies in the media of cells treated with FA 8:0 or FA 10:0 were 3.22- or 3.69-fold higher than those obtained with FA 18:1 treatment, respectively. FA 12:0 treatment did not significantly increase ketone body levels compared to DMSO treatment (control), whereas FA 12:0 treatment increased intracellular triacylglycerol (TG) levels 15.4 times compared to the control. Metabolic profiles of FA 12:0-treated samples differed from those of the FA 8:0-treated and FA 10:0-treated samples, suggesting that metabolic assimilation of MCFAs differed significantly depending on the MCFA type. Furthermore, the dynamic metabolome analysis clearly revealed that FA 8:0 was rapidly and quantitatively oxidized to acetyl-CoA and assimilated into ketone bodies, citrate cycle intermediates, and glucogenic amino acids but not readily into TGs.
    Keywords:  hepatocytes; ketone bodies; medium-chain fatty acids; metabolic turnover analysis; metabolome analysis
    DOI:  https://doi.org/10.1021/acs.jafc.0c04723
  18. Metabolomics. 2020 Oct 21. 16(11): 117
    Chetnik K, Petrick L, Pandey G.
      INTRODUCTION: Despite the availability of several pre-processing software, poor peak integration remains a prevalent problem in untargeted metabolomics data generated using liquid chromatography high-resolution mass spectrometry (LC-MS). As a result, the output of these pre-processing software may retain incorrectly calculated metabolite abundances that can perpetuate in downstream analyses.OBJECTIVES: To address this problem, we propose a computational methodology that combines machine learning and peak quality metrics to filter out low quality peaks.
    METHODS: Specifically, we comprehensively and systematically compared the performance of 24 different classifiers generated by combining eight classification algorithms and three sets of peak quality metrics on the task of distinguishing reliably integrated peaks from poorly integrated ones. These classifiers were compared to using a residual standard deviation (RSD) cut-off in pooled quality-control (QC) samples, which aims to remove peaks with analytical error.
    RESULTS: The best performing classifier was found to be a combination of the AdaBoost algorithm and a set of 11 peak quality metrics previously explored in untargeted metabolomics and proteomics studies. As a complementary approach, applying our framework to peaks retained after filtering by 30% RSD across pooled QC samples was able to further distinguish poorly integrated peaks that were not removed from filtering alone. An R implementation of these classifiers and the overall computational approach is available as the MetaClean package at https://CRAN.R-project.org/package=MetaClean .
    CONCLUSION: Our work represents an important step forward in developing an automated tool for filtering out unreliable peak integrations in untargeted LC-MS metabolomics data.
    Keywords:  Machine learning; Metabolomics; Peak integration; Pre-processing; Quality control; Untargeted
    DOI:  https://doi.org/10.1007/s11306-020-01738-3