bims-mascan Biomed News
on Mass spectrometry in cancer research
Issue of 2024‒08‒04
fifteen papers selected by
Giovanny Rodriguez Blanco, University of Edinburgh
  1. Data acquisition approaches for single cell proteomics.
  2. Stable isotope-resolved metabolomics analyses of metabolic phenotypes reveal variable glutamine metabolism in different patient-derived models of non-small cell lung cancer from a single patient.
  3. Fragment correlation mass spectrometry: Determining the structures of biopolymers in a complex mixture without isolating individual components.
  4. Isotope dilution with isotopically labeled biomass: An effective alternative for quantitative metabolomics.
  5. Efficient derivatization-free monitoring of glycosyltransferase reactions via flow injection analysis-mass spectrometry for rapid sugar analytics.
  6. Simulated LC-MS Data Set for Assessing the Metabolomics Data Processing Pipeline Implemented into MVAPACK.
  7. Reproducible MS/MS library cleaning pipeline in matchms.
  8. Acetyl-CoA: An interplay between metabolism and epigenetics in cancer.
  9. High-Throughput Metabolomics using 96-plex Isotope Tagging.
  10. ASCT2 is a major contributor to serine uptake in cancer cells.
  11. Concatemer Assisted Stoichiometry Analysis (CASA): targeted mass spectrometry for protein quantification.
  12. Sequence-to-sequence translation from mass spectra to peptides with a transformer model.
  13. A robust method for measuring aminoacylation through tRNA-Seq.
  14. Integrative protocol for quantifying cholesterol-related sterols in human serum samples and building decision support systems.
  15. Etomoxir-carnitine, a novel pharmaco-metabolite of etomoxir, inhibits phospholipases A2 and mitochondrial respiration.
  1. Proteomics. 2024 Aug 01. e2400022
    Data acquisition approaches for single cell proteomics.
    Gautam Ghosh, Ariana E Shannon, Brian C Searle.
      Single-cell proteomics (SCP) aims to characterize the proteome of individual cells, providing insights into complex biological systems. It reveals subtle differences in distinct cellular populations that bulk proteome analysis may overlook, which is essential for understanding disease mechanisms and developing targeted therapies. Mass spectrometry (MS) methods in SCP allow the identification and quantification of thousands of proteins from individual cells. Two major challenges in SCP are the limited material in single-cell samples necessitating highly sensitive analytical techniques and the efficient processing of samples, as each biological sample requires thousands of single cell measurements. This review discusses MS advancements to mitigate these challenges using data-dependent acquisition (DDA) and data-independent acquisition (DIA). Additionally, we examine the use of short liquid chromatography gradients and sample multiplexing methods that increase the sample throughput and scalability of SCP experiments. We believe these methods will pave the way for improving our understanding of cellular heterogeneity and its implications for systems biology.
    Keywords:  data dependent acquisition; data independent acquisition; mass spectrometry; multiplex; proteomics; single cell
    DOI:  https://doi.org/10.1002/pmic.202400022
  2. Metabolomics. 2024 Jul 27. 20(4): 87
    Stable isotope-resolved metabolomics analyses of metabolic phenotypes reveal variable glutamine metabolism in different patient-derived models of non-small cell lung cancer from a single patient.
    Connor J Kinslow, Michael Bousamra Ll, Yihua Cai, Jun Yan, Pawel K Lorkiewicz, Ahmad Al-Attar, Jinlian Tan, Richard M Higashi, Andrew N Lane, Teresa W-M Fan.
      INTRODUCTION: Stable isotope tracers have been increasingly used in preclinical cancer model systems, including cell culture and mouse xenografts, to probe the altered metabolism of a variety of cancers, such as accelerated glycolysis and glutaminolysis and generation of oncometabolites. Comparatively little has been reported on the fidelity of the different preclinical model systems in recapitulating the aberrant metabolism of tumors.OBJECTIVES: We have been developing several different experimental model systems for systems biochemistry analyses of non-small cell lung cancer (NSCLC1) using patient-derived tissues to evaluate appropriate models for metabolic and phenotypic analyses.
    METHODS: To address the issue of fidelity, we have carried out a detailed Stable Isotope-Resolved Metabolomics study of freshly resected tissue slices, mouse patient derived xenografts (PDXs), and cells derived from a single patient using both 13C6-glucose and 13C5,15N2-glutamine tracers.
    RESULTS: Although we found similar glucose metabolism in the three models, glutamine utilization was markedly higher in the isolated cell culture and in cell culture-derived xenografts compared with the primary cancer tissue or direct tissue xenografts (PDX).
    CONCLUSIONS: This suggests that caution is needed in interpreting cancer biochemistry using patient-derived cancer cells in vitro or in xenografts, even at very early passage, and that direct analysis of patient derived tissue slices provides the optimal model for ex vivo metabolomics. Further research is needed to determine the generality of these observations.
    Keywords:  Cancer metabolism; Non-small cell lung cancer; Patient-derived xenografts; Preclinical models; Primary cell culture; Stable isotope-resolved metabolomics
    DOI:  https://doi.org/10.1007/s11306-024-02126-x
  3. Proc Natl Acad Sci U S A. 2024 Aug 06. 121(32): e2409676121
    Fragment correlation mass spectrometry: Determining the structures of biopolymers in a complex mixture without isolating individual components.
    Yangjie Li, Guy Cavet, Richard N Zare, Taran Driver.
      Fragment correlation mass spectrometry correlates ion pairs generated from the same fragmentation pathway, achieved by covariance mapping of tandem mass spectra generated with an unmodified linear ion trap without preseparation. We enable the identification of different precursors at different charge states in a complex mixture from a large isolation window, empowering an analytical approach for data-independent acquisition. The method resolves and matches isobaric fragments, internal ions, and disulfide bond fragments. We suggest that this method represents a major advance for analyzing structures of biopolymers in mixtures.
    Keywords:  covariance mapping; data-independent acquisition; fragment correlation; proteomics; tandem mass spectrometry
    DOI:  https://doi.org/10.1073/pnas.2409676121
  4. Anal Chim Acta. 2024 Aug 22. pii: S0003-2670(24)00710-4. [Epub ahead of print]1318 342909
    Isotope dilution with isotopically labeled biomass: An effective alternative for quantitative metabolomics.
    Veronika Fitz, Lisa Panzenboeck, Harald Schoeny, Elisabeth Foels, Gunda Koellensperger.
      BACKGROUND: State-of-the-art quantitative metabolomics relies on isotope dilution using internal standards (IS) derived from fully 13C labeled biomass. By spiking samples and external standards with known amounts of IS, the spike characterization demands are kept to a minimum. In fact, it is sufficient to experimentally assess the isotopic enrichment of the IS. This study develops the yeast derived IS toolbox further, (1) by characterizing the concentration levels of hydrophilic metabolites in a yeast fermentation batch and (2) by exploring the analytical figures of merit of one-point IS versus multipoint external calibration using IS, the established gold-standard for quantitative metabolomics.RESULTS: Independent reverse isotope dilution experiments using different chromatographic methods over a period of several months, delivered a list of 83 13C-labeled metabolites with fully characterized concentration and their uncertainty, covering 5 orders of magnitude, from the nanomolar to the low millimolar range. The 13C-labeled yeast-derived IS showed excellent intermediate stability with 92 % of molecules showing inter-method RSDs ≤30 % (75 % of molecules showed RSDs ≤15 %) over a timeframe of five months. One-point internal standardization with the characterized labeled biomass achieved figures of merit equivalent to multipoint calibrations for the majority of metabolites.
    SIGNIFICANCE: The proposed calibration workflow rationalizes time and standard expenditure and is particularly beneficial for laboratories dealing with wide-target assays and small analysis batches. The present assessment serves as a seminal study for further developments of the concept towards absolute quantification from archive high-resolution MS data of U13C-biomass-spiked samples and the implementation of quick biomass recalibration with each experiment, promising seamless transition between internal standards derived from different fermentation batches.
    Keywords:  Absolute quantification; Internal standardization; Isotope dilution; Isotopically labeled biomass; Liquid chromatography-mass spectrometry; Metabolomics
    DOI:  https://doi.org/10.1016/j.aca.2024.342909
  5. Anal Bioanal Chem. 2024 Aug 03.
    Efficient derivatization-free monitoring of glycosyltransferase reactions via flow injection analysis-mass spectrometry for rapid sugar analytics.
    Ulrich Thiele, Chantal Crocoll, André Tschöpe, Carla Drayß, Frank Kirschhöfer, Michael Nusser, Gerald Brenner-Weiß, Matthias Franzreb, Katharina Bleher.
      The widespread application of enzymes in industrial chemical synthesis requires efficient process control to maintain high yields and purity. Flow injection analysis-electrospray ionization-mass spectrometry (FIA-ESI-MS) offers a promising solution for real-time monitoring of these enzymatic processes, particularly when handling challenging compounds like sugars and glycans, which are difficult to quickly analyze using liquid chromatography-mass spectrometry due to their physical properties or the requirement for a derivatization step beforehand. This study compares the performance of FIA-MS with traditional hydrophilic interaction liquid chromatography (HILIC)-ultra high-performance liquid chromatography (UHPLC)-mass spectrometry (MS) setups for the monitoring of the enzymatic synthesis of N-acetyllactosamine (LacNAc) using beta-1,4-galactosyltransferase. Our results show that FIA-MS, without prior chromatographic separation or derivatization, can quickly generate accurate mass spectrometric data within minutes, contrasting with the lengthy separations required by LC-MS methods. The rapid data acquisition of FIA-MS enables effective real-time monitoring and adjustment of the enzymatic reactions. Furthermore, by eliminating the derivatization step, this method offers the possibility of being directly coupled to a continuously operated reactor, thus providing a rapid on-line methodology for glycan synthesis as well.
    Keywords:  Derivatization-free; Enzymatic reaction monitoring; FIA-MS; Sugar
    DOI:  https://doi.org/10.1007/s00216-024-05457-9
  6. Anal Chem. 2024 Jul 30.
    Simulated LC-MS Data Set for Assessing the Metabolomics Data Processing Pipeline Implemented into MVAPACK.
    Christopher P Jurich, Micah J Jeppesen, Isin T Sakallioglu, Aline De Lima Leite, Joseph D Yesselman, Robert Powers.
      Metabolomics commonly relies on using one-dimensional (1D) 1H NMR spectroscopy or liquid chromatography-mass spectrometry (LC-MS) to derive scientific insights from large collections of biological samples. NMR and MS approaches to metabolomics require, among other issues, a data processing pipeline. Quantitative assessment of the performance of these software platforms is challenged by a lack of standardized data sets with "known" outcomes. To resolve this issue, we created a novel simulated LC-MS data set with known peak locations and intensities, defined metabolite differences between groups (i.e., fold change > 2, coefficient of variation ≤ 25%), and different amounts of added Gaussian noise (0, 5, or 10%) and missing features (0, 10, or 20%). This data set was developed to improve benchmarking of existing LC-MS metabolomics software and to validate the updated version of our MVAPACK software, which added gas chromatography-MS and LC-MS functionality to its existing 1D and two-dimensional NMR data processing capabilities. We also included two experimental LC-MS data sets acquired from a standard mixture andMycobacterium smegmatiscell lysates since a simulated data set alone may not capture all the unique characteristics and variability of real spectra needed to assess software performance properly. Our simulated and experimental LC-MS data sets were processed with the MS-DIAL and XCMSOnline software packages and our MVAPACK toolkit to showcase the utility of our data sets to benchmark MVAPACK against community standards. Our results demonstrate the enhanced objectivity and clarity of software assessment that can be achieved when both simulated and experimental data are employed since distinctly different software performances were observed with the simulated and experimental LC-MS data sets. We also demonstrate that the performance of MVAPACK is equivalent to or exceeds existing LC-MS software programs while providing a single platform for processing and analyzing both NMR and MS data sets.
    DOI:  https://doi.org/10.1021/acs.analchem.3c04979
  7. J Cheminform. 2024 Jul 29. 16(1): 88
    Reproducible MS/MS library cleaning pipeline in matchms.
    Niek F de Jonge, Helge Hecht, Michael Strobel, Mingxun Wang, Justin J J van der Hooft, Florian Huber.
      Mass spectral libraries have proven to be essential for mass spectrum annotation, both for library matching and training new machine learning algorithms. A key step in training machine learning models is the availability of high-quality training data. Public libraries of mass spectrometry data that are open to user submission often suffer from limited metadata curation and harmonization. The resulting variability in data quality makes training of machine learning models challenging. Here we present a library cleaning pipeline designed for cleaning tandem mass spectrometry library data. The pipeline is designed with ease of use, flexibility, and reproducibility as leading principles.Scientific contributionThis pipeline will result in cleaner public mass spectral libraries that will improve library searching and the quality of machine-learning training datasets in mass spectrometry. This pipeline builds on previous work by adding new functionality for curating and correcting annotated libraries, by validating structure annotations. Due to the high quality of our software, the reproducibility, and improved logging, we think our new pipeline has the potential to become the standard in the field for cleaning tandem mass spectrometry libraries.
    Keywords:  Library cleaning; Mass spectrometry; Metabolomics; Metadata; Python Package
    DOI:  https://doi.org/10.1186/s13321-024-00878-1
  8. Front Mol Med. 2022 ;2 1044585
    Acetyl-CoA: An interplay between metabolism and epigenetics in cancer.
    Yang Hao, Qin Yi, Xu XiaoWu, Chen WeiBo, Zu GuangChen, Chen XueMin.
      Due to its high mortality and severe economic burden, cancer has become one of the most difficult medical problems to solve today. As a key node in metabolism and the main producer of energy, acetyl-coenzyme A (acetyl-CoA) plays an important role in the invasion and migration of cancer. In this review, we discuss metabolic pathways involving acetyl-CoA, the targeted therapy of cancer through acetyl-CoA metabolic pathways and the roles of epigenetic modifications in cancer. In particular, we emphasize that the metabolic pathway of acetyl-CoA exerts a great impact in cancer; this process is very different from normal cells due to the "Warburg effect". The concentration of acetyl-CoA is increased in the mitochondria of cancer cells to provide ATP for survival, hindering the growth of normal cells. Therefore, it may be possible to explore new feasible and more effective treatments through the acetyl-CoA metabolic pathway. In addition, a growing number of studies have shown that abnormal epigenetic modifications have been shown to play contributing roles in cancer formation and development. In most cancers, acetyl-CoA mediated acetylation promotes the growth of cancer cells. Thus, acetylation biomarkers can also be detected and serve as potential cancer prediction and prognostic markers.
    Keywords:  acetyl-CoA; cancer; epigenetics; histone acetylation; metabolism
    DOI:  https://doi.org/10.3389/fmmed.2022.1044585
  9. Anal Chem. 2024 Jul 31.
    High-Throughput Metabolomics using 96-plex Isotope Tagging.
    Michael R Armbruster, Scott F Grady, Kevin Cho, Gary J Patti, Benjamin J Bythell, Christopher K Arnatt, James L Edwards.
      Liquid chromatography-mass spectrometry (LC-MS) based metabolomics suffers from extended duty cycles and matrix-dependent quantitation. Chemical tags with 96 unique masses are reported, which alleviate the metabolomic workflow bottleneck and allow for absolute quantitation. A metabolic screen for carboxylic acids was performed on mammalian cells deprived of various nutrients and showed 24% RSD and analysis of 288 samples in 2 h.
    DOI:  https://doi.org/10.1021/acs.analchem.4c02279
  10. Cell Rep. 2024 Jul 26. pii: S2211-1247(24)00881-7. [Epub ahead of print]43(8): 114552
    ASCT2 is a major contributor to serine uptake in cancer cells.
    Kelly O Conger, Christopher Chidley, Mete Emir Ozgurses, Huiping Zhao, Yumi Kim, Svetlana E Semina, Philippa Burns, Vipin Rawat, Lina Lietuvninkas, Ryan Sheldon, Issam Ben-Sahra, Jonna Frasor, Peter K Sorger, Gina M DeNicola, Jonathan L Coloff.
      The non-essential amino acid serine is a critical nutrient for cancer cells due to its diverse biosynthetic functions. While some tumors can synthesize serine de novo, others are auxotrophic and therefore reliant on serine uptake. Importantly, despite several transporters being known to be capable of transporting serine, the transporters that mediate serine uptake in cancer cells are not known. Here, we characterize the amino acid transporter ASCT2 (SLC1A5) as a major contributor to serine uptake in cancer cells. ASCT2 is well known as a glutamine transporter in cancer, and our work demonstrates that serine and glutamine compete for uptake through ASCT2. We further show that ASCT2-mediated serine uptake is essential for purine nucleotide biosynthesis and that estrogen receptor α (ERα) promotes serine uptake by directly activating SLC1A5 transcription. Collectively, our work defines an additional important role for ASCT2 as a serine transporter in cancer and evaluates ASCT2 as a potential therapeutic target.
    Keywords:  ASCT2; CP: Cancer; ERα; SLC1A5; amino acid uptake; breast cancer; cancer metabolism; diet; purine biosynthesis; serine starvation; serine transporter
    DOI:  https://doi.org/10.1016/j.celrep.2024.114552
  11. bioRxiv. 2024 Jul 27. pii: 2024.07.26.605382. [Epub ahead of print]
    Concatemer Assisted Stoichiometry Analysis (CASA): targeted mass spectrometry for protein quantification.
    Jiaxi Cai, Yun Quan, Cindy Yuxuan Zhang, Ziyi Wang, Stephen M Hinshaw, Huilin Zhou, Raymond T Suhandynata.
      Large multi-protein machines are central to multiple biological processes. However, stoichiometric determination of protein complex subunits in their native states presents a significant challenge. This study addresses the limitations of current tools in accuracy and precision by introducing concatemer-assisted stoichiometry analysis (CASA). CASA leverages stable isotope-labeled concatemers and liquid chromatography parallel reaction monitoring mass spectrometry (LC-PRM-MS) to achieve robust quantification of proteins with sub-femtomole sensitivity. As a proof-of-concept, CASA was applied to study budding yeast kinetochores. Stoichiometries were determined for ex vivo reconstituted kinetochore components, including the canonical H3 nucleosomes, centromeric (Cse4 CENP-A ) nucleosomes, centromere proximal factors (Cbf1 and CBF3 complex), inner kinetochore proteins (Mif2 CENP-C , Ctf19 CCAN complex), and outer kinetochore proteins (KMN network). Absolute quantification by CASA revealed Cse4 CENP-A as a cell-cycle controlled limiting factor for kinetochore assembly. These findings demonstrate that CASA is applicable for stoichiometry analysis of multi-protein assemblies.Summary: This study presents Concatemer-Assisted Stoichiometry Analysis (CASA) to address a common challenge in cell biological research: quantifying the number of each protein subunit in a native protein complex.
    DOI:  https://doi.org/10.1101/2024.07.26.605382
  12. Nat Commun. 2024 Jul 30. 15(1): 6427
    Sequence-to-sequence translation from mass spectra to peptides with a transformer model.
    Melih Yilmaz, William E Fondrie, Wout Bittremieux, Carlo F Melendez, Rowan Nelson, Varun Ananth, Sewoong Oh, William Stafford Noble.
      A fundamental challenge in mass spectrometry-based proteomics is the identification of the peptide that generated each acquired tandem mass spectrum. Approaches that leverage known peptide sequence databases cannot detect unexpected peptides and can be impractical or impossible to apply in some settings. Thus, the ability to assign peptide sequences to tandem mass spectra without prior information-de novo peptide sequencing-is valuable for tasks including antibody sequencing, immunopeptidomics, and metaproteomics. Although many methods have been developed to address this problem, it remains an outstanding challenge in part due to the difficulty of modeling the irregular data structure of tandem mass spectra. Here, we describe Casanovo, a machine learning model that uses a transformer neural network architecture to translate the sequence of peaks in a tandem mass spectrum into the sequence of amino acids that comprise the generating peptide. We train a Casanovo model from 30 million labeled spectra and demonstrate that the model outperforms several state-of-the-art methods on a cross-species benchmark dataset. We also develop a version of Casanovo that is fine-tuned for non-enzymatic peptides. Finally, we demonstrate that Casanovo's superior performance improves the analysis of immunopeptidomics and metaproteomics experiments and allows us to delve deeper into the dark proteome.
    DOI:  https://doi.org/10.1038/s41467-024-49731-x
  13. Elife. 2024 Jul 30. pii: RP91554. [Epub ahead of print]12
    A robust method for measuring aminoacylation through tRNA-Seq.
    Kristian Davidsen, Lucas B Sullivan.
      Current methods to quantify the fraction of aminoacylated tRNAs, also known as the tRNA charge, are limited by issues with either low throughput, precision, and/or accuracy. Here, we present an optimized charge transfer RNA sequencing (tRNA-Seq) method that combines previous developments with newly described approaches to establish a protocol for precise and accurate tRNA charge measurements. We verify that this protocol provides robust quantification of tRNA aminoacylation and we provide an end-to-end method that scales to hundreds of samples including software for data processing. Additionally, we show that this method supports measurements of relative tRNA expression levels and can be used to infer tRNA modifications through reverse transcription misincorporations, thereby supporting multipurpose applications in tRNA biology.
    Keywords:  Whitfeld reaction; aminoacylation; biochemistry; chemical biology; human; small-RNA sequencing; tRNA; tRNA stability; tRNA-Seq
    DOI:  https://doi.org/10.7554/eLife.91554
  14. STAR Protoc. 2024 Jul 31. pii: S2666-1667(24)00378-2. [Epub ahead of print]5(3): 103213
    Integrative protocol for quantifying cholesterol-related sterols in human serum samples and building decision support systems.
    Eva Kočar, Sonja Katz, Žiga Pušnik, Cene Skubic, Tadeja Režen, Vitor A P Martins Dos Santos, Miha Mraz, Miha Moškon, Damjana Rozman.
      The growing interest in clinical diagnostics has recently focused on metabolic biomarkers. Here, we present a protocol for sample preparation, extraction of cholesterol-related sterols, and quantification of 10 sterols in human blood serum samples using targeted liquid chromatography-tandem mass spectrometry (LC-MS/MS). We also describe steps of machine learning techniques to develop novel decision-making systems that offer potential benefits in disease monitoring and surveillance by measuring metabolic pathways. For complete details on the use and execution of this protocol, please refer to Kočar et al.1 and Skubic et al.2.
    Keywords:  Computer sciences; Metabolism; Molecular Biology
    DOI:  https://doi.org/10.1016/j.xpro.2024.103213
  15. J Lipid Res. 2024 Jul 31. pii: S0022-2275(24)00116-0. [Epub ahead of print] 100611
    Etomoxir-carnitine, a novel pharmaco-metabolite of etomoxir, inhibits phospholipases A2 and mitochondrial respiration.
    Sung Ho Moon, Xinping Liu, Christopher M Jenkins, Beverly Gibson Dilthey, Gary J Patti, Richard W Gross.
      Mitochondrial fatty acid oxidation serves as an essential process for cellular survival, differentiation, proliferation, and energy metabolism. Numerous studies have utilized etomoxir (ETO) for the irreversible inhibition of carnitine palmitoylcarnitine transferase 1 (CPT1) which catalyzes the rate-limiting step for mitochondrial long-chain fatty acid β-oxidation to examine the bioenergetic roles of mitochondrial fatty acid metabolism in many tissues in multiple diverse disease states. Herein, we demonstrate that intact mitochondria robustly metabolize etomoxir to etomoxir-carnitine (ETO-carnitine) prior to nearly complete etomoxir-mediated inhibition of CPT1. The novel pharmaco-metabolite, ETO-carnitine, was conclusively identified by accurate mass, fragmentation patterns, and isotopic fine structure. On the basis of these data, ETO-carnitine was successfully differentiated from isobaric structures (e.g., 3-hydroxy-C18:0 carnitine and 3-hydroxy-C18:1 carnitine). Mechanistically, generation of ETO-carnitine from mitochondria required exogenous Mg2+, ATP or ADP, CoASH, and L-carnitine indicating that thioesterification by long-chain acyl-CoA synthetase to form ETO-CoA precedes its conversion to ETO-carnitine by CPT1. CPT1-dependent generation of ETO-carnitine was substantiated by an orthogonal approach using ST1326 (a CPT1 inhibitor) which effectively inhibits mitochondrial ETO-carnitine production. Surprisingly, purified ETO-carnitine potently inhibited calcium-independent PLA2γ and PLA2β as well as mitochondrial respiration independent of CPT1. Robust production and release of ETO-carnitine from HepG2 cells incubated in the presence of ETO was also demonstrated. Collectively, this study identifies the chemical mechanism for the biosynthesis of a novel pharmaco-metabolite of etomoxir, ETO-carnitine, that is generated by CPT1 in mitochondria and likely impacts multiple downstream (non-CPT1 related) enzymes and processes in multiple subcellular compartments.
    Keywords:  Lipidomics; Lipids/Chemistry; Lipolysis and fatty acid metabolism; carnitine palmitoyltransferase (CPT); etomoxir; etomoxir-carnitine; mitochondria; off-target effects; pharmaco-metabolite; phospholipases A(2)
    DOI:  https://doi.org/10.1016/j.jlr.2024.100611
This page is being maintained by Thomas Krichel. It was last updated on 2024‒08‒12 at 15:26.