bims-mascan Biomed News
on Mass spectrometry in cancer research
Issue of 2023–07–16
twenty papers selected by
Giovanny Rodriguez Blanco, University of Edinburgh



  1. Nat Commun. 2023 07 12. 14(1): 4154
      Liquid chromatography (LC) coupled with data-independent acquisition (DIA) mass spectrometry (MS) has been increasingly used in quantitative proteomics studies. Here, we present a fast and sensitive approach for direct peptide identification from DIA data, MSFragger-DIA, which leverages the unmatched speed of the fragment ion indexing-based search engine MSFragger. Different from most existing methods, MSFragger-DIA conducts a database search of the DIA tandem mass (MS/MS) spectra prior to spectral feature detection and peak tracing across the LC dimension. To streamline the analysis of DIA data and enable easy reproducibility, we integrate MSFragger-DIA into the FragPipe computational platform for seamless support of peptide identification and spectral library building from DIA, data-dependent acquisition (DDA), or both data types combined. We compare MSFragger-DIA with other DIA tools, such as DIA-Umpire based workflow in FragPipe, Spectronaut, DIA-NN library-free, and MaxDIA. We demonstrate the fast, sensitive, and accurate performance of MSFragger-DIA across a variety of sample types and data acquisition schemes, including single-cell proteomics, phosphoproteomics, and large-scale tumor proteome profiling studies.
    DOI:  https://doi.org/10.1038/s41467-023-39869-5
  2. bioRxiv. 2023 Jun 29. pii: 2023.06.26.546628. [Epub ahead of print]
      Combined multi-omics analysis of proteomics, polar metabolomics, and lipidomics requires separate liquid chromatography-mass spectrometry (LC-MS) platforms for each omics layer. This requirement for different platforms limits throughput and increases costs, preventing the application of mass spectrometry-based multi-omics to large scale drug discovery or clinical cohorts. Here, we present an innovative strategy for simultaneous multi-omics analysis by direct infusion (SMAD) using one single injection without liquid chromatography. SMAD allows quantification of over 9,000 metabolite m/z features and over 1,300 proteins from the same sample in less than five minutes. We validated the efficiency and reliability of this method and then present two practical applications: mouse macrophage M1/M2 polarization and high throughput drug screening in human 293T cells. Finally, we demonstrate relationships between proteomic and metabolomic data are discovered by machine learning.
    DOI:  https://doi.org/10.1101/2023.06.26.546628
  3. J Biomol Tech. 2023 07 01. pii: 3fc1f5fe.1972c438. [Epub ahead of print]34(2):
      Multiple reaction monitoring (MRM) profiling is a strategy for the exploratory analysis of small molecules and lipids by direct sample injection, ie, without the use of chromatographic separation. It is based on instrument methods that comprise a list of ion transitions (MRMs), in which the precursor ion is the expected ionized m/z of the lipid at its species level, ie, the description of lipid class and number of carbon and double bonds in the fatty acid chain(s), and the product ion is a fragment expected for the lipid class or for the fatty acid neutral loss. The Lipid Maps database is expanding constantly, and therefore the MRM-profiling methods associated with this database need to be continuously updated. Here, we provide a comprehensive overview and the key references for the MRM-profiling methodology and workflow, followed by a step-by-step approach to build MRM-profiling instrument acquisition methods for class-based lipid exploratory analysis based on the Lipid Maps database. The detailed workflow includes (1) importing the list of lipids from the database; (2) for a given class, combining isomeric lipids described at full structural level into 1 entry to obtain the neutral mass at species level; (3) attributing the standard Lipid Maps abbreviated nomenclature for the lipid at its species level; (4) predicting the ionized precursor ions; and (5) adding the expected product ion. We also describe how to simulate the precursor ion for the suspect screening of modified lipids using lipid oxidation and their expected product ions as an example. After determining the MRMs, information about collision energy, dwell time, and other instrument parameters are added to finalize the acquisition method. As an example of final method output, we describe the format for Agilent MassHunter v.B.06 and provide the parameters in which optimization can be performed by lipid class using one or more lipid standards.
    Keywords:  MRM profiling; direct injection analysis; exploratory analysis; lipids
    DOI:  https://doi.org/10.7171/3fc1f5fe.1972c438
  4. Nat Commun. 2023 07 11. 14(1): 4113
      Significant challenges remain in the computational processing of data from liquid chomratography-mass spectrometry (LC-MS)-based metabolomic experiments into metabolite features. In this study, we examine the issues of provenance and reproducibility using the current software tools. Inconsistency among the tools examined is attributed to the deficiencies of mass alignment and controls of feature quality. To address these issues, we develop the open-source software tool asari for LC-MS metabolomics data processing. Asari is designed with a set of specific algorithmic framework and data structures, and all steps are explicitly trackable. Asari compares favorably to other tools in feature detection and quantification. It offers substantial improvement in computational performance over current tools, and it is highly scalable.
    DOI:  https://doi.org/10.1038/s41467-023-39889-1
  5. J Lipid Res. 2023 Jul 10. pii: S0022-2275(23)00083-4. [Epub ahead of print] 100410
      In-depth structural characterization of lipids provides a new means to investigate lipid metabolism. In this study, we have conducted deep profiling of total fatty acids (FAs) from RAW 264.7 macrophages by utilizing charge-tagging Paterno-B u¨chi derivatization of carbon-carbon double bond (C=C) and reversed-phase liquid chromatography-tandem mass spectrometry. A series of FAs exhibiting unusual site(s) of unsaturation was unearthed, with their identities being confirmed by observing anticipated compositional alterations upon desaturase inhibition. The data reveal that FADS2 Δ6-desaturation can generate n-11 C=C in the odd-chain monounsaturated fatty acids (MUFAs) as well as n-10 and n-12 families of even-chain MUFAs. SCD1 Δ9-desaturation yields n-6, n-8, and n-10 of odd-chain MUFAs, as well as n-5, n-7, and n-9 families of even-chain MUFAs. Besides n-3 and n-6 families of polyunsaturated fatty acids (PUFAs), the presence of n-7 and n-9 families of PUFAs indicates that the n-7 and n-9 isomers of FA 18:1 can be utilized as substrates for further desaturation and elongation. The n-7 and n-9 families of PUFAs identified in RAW 264.7 macrophages are noteworthy because their C=C modifications are achieved exclusively via de novo lipogenesis. Our discovery outlines the metabolic plasticity in fatty acid desaturation which constitutes an unexplored rewiring in RAW264.7 macrophages.
    Keywords:  Paternò–Büchi reaction; RAW 264.7 macrophage; Unsaturated fatty acids; double bond location isomers; mass spectrometry
    DOI:  https://doi.org/10.1016/j.jlr.2023.100410
  6. Cell Rep Methods. 2023 06 26. 3(6): 100479
      Mass spectrometry (MS)-based immunopeptidomics is an attractive antigen discovery method with growing clinical implications. However, the current experimental approach to extract HLA-restricted peptides requires a bulky sample source, which remains a challenge for obtaining clinical specimens. We present an innovative workflow that requires a low sample volume, which streamlines the immunoaffinity purification (IP) and C18 peptide cleanup on a single microfluidics platform with automated liquid handling and minimal sample transfers, resulting in higher assay sensitivity. We also demonstrate how the state-of-the-art data-independent acquisition (DIA) method further enhances the depth of tandem MS spectra-based peptide sequencing. Consequently, over 4,000 and 5,000 HLA-I-restricted peptides were identified from as few as 0.2 million RA957 cells and a melanoma tissue of merely 5 mg, respectively. We also identified multiple immunogenic tumor-associated antigens and hundreds of peptides derived from non-canonical protein sources. This workflow represents a powerful tool for identifying the immunopeptidome of sparse samples.
    Keywords:  automation; data-independent acquisition; immunopeptidome; mass spectrometry; microfluidics; sample preparation
    DOI:  https://doi.org/10.1016/j.crmeth.2023.100479
  7. Nutrients. 2023 Jun 25. pii: 2879. [Epub ahead of print]15(13):
      Cancer cells cannot proliferate and survive unless they obtain sufficient levels of the 20 proteinogenic amino acids (AAs). Unlike normal cells, cancer cells have genetic and metabolic alterations that may limit their capacity to obtain adequate levels of the 20 AAs in challenging metabolic environments. However, since normal diets provide all AAs at relatively constant levels and ratios, these potentially lethal genetic and metabolic defects are eventually harmless to cancer cells. If we temporarily replace the normal diet of cancer patients with artificial diets in which the levels of specific AAs are manipulated, cancer cells may be unable to proliferate and survive. This article reviews in vivo studies that have evaluated the antitumor activity of diets restricted in or supplemented with the 20 proteinogenic AAs, individually and in combination. It also reviews our recent studies that show that manipulating the levels of several AAs simultaneously can lead to marked survival improvements in mice with metastatic cancers.
    Keywords:  anticancer activity; arginine; artificial diets; asparagine; cancer metabolism; cysteine; essential amino acids; glutamine; in vivo; leucine; methionine; mice; non-essential amino acids; restriction; serine
    DOI:  https://doi.org/10.3390/nu15132879
  8. Nat Commun. 2023 07 12. 14(1): 4132
      Post-translational modifications are an area of great interest in mass spectrometry-based proteomics, with a surge in methods to detect them in recent years. However, post-translational modifications can introduce complexity into proteomics searches by fragmenting in unexpected ways, ultimately hindering the detection of modified peptides. To address these deficiencies, we present a fully automated method to find diagnostic spectral features for any modification. The features can be incorporated into proteomics search engines to improve modified peptide recovery and localization. We show the utility of this approach by interrogating fragmentation patterns for a cysteine-reactive chemoproteomic probe, RNA-crosslinked peptides, sialic acid-containing glycopeptides, and ADP-ribosylated peptides. We also analyze the interactions between a diagnostic ion's intensity and its statistical properties. This method has been incorporated into the open-search annotation tool PTM-Shepherd and the FragPipe computational platform.
    DOI:  https://doi.org/10.1038/s41467-023-39828-0
  9. Methods Mol Biol. 2023 ;2695 181-193
      Limited knowledge has been reported regarding the performance of plasma metabolomics for predicting lung cancer prognosis. In this chapter, we compared the plasma metabolomics of lung cancer patients with differential disease-free survival (DFS, <3 years vs. >4 years) using liquid chromatography-mass spectrometry. We identified 29 survival-related aqueous metabolites but no lipid metabolites. Amino acids and organic acids constitute the majority of these metabolites. The metabolic pathways of these metabolites were cysteine and methionine metabolism and arginine biosynthesis. The Cox proportional hazards regression models confirmed the predictive values of 18 metabolites for DFS, while the phosphocholine and xanthine showed independent predictive values. Regarding cancer phenotypes, thelephoric acid, phosphocholine, inosine, 3-hydroxyanthranilic acid, hypoxanthine, xanthine, and 4-hydroxybenzoic acid showed good correction with lymph node metastasis. Taken together, plasma metabolomics is a powerful tool for identifying prognostic metabolites of lung cancer.
    Keywords:  Lung cancer; Metabolites; Plasma metabolomic; Prognosis
    DOI:  https://doi.org/10.1007/978-1-0716-3346-5_12
  10. J Biomol Tech. 2023 07 01. pii: 3fc1f5fe.9b78d780. [Epub ahead of print]34(2):
      Despite the advantages of fewer missing values by collecting fragment ion data on all analytes in the sample as well as the potential for deeper coverage, the adoption of data-independent acquisition (DIA) in proteomics core facility settings has been slow. The Association of Biomolecular Resource Facilities conducted a large interlaboratory study to evaluate DIA performance in proteomics laboratories with various instrumentation. Participants were supplied with generic methods and a uniform set of test samples. The resulting 49 DIA datasets act as benchmarks and have utility in education and tool development. The sample set consisted of a tryptic HeLa digest spiked with high or low levels of 4 exogenous proteins. Data are available in MassIVE MSV000086479. Additionally, we demonstrate how the data can be analyzed by focusing on 2 datasets using different library approaches and show the utility of select summary statistics. These data can be used by DIA newcomers, software developers, or DIA experts evaluating performance with different platforms, acquisition settings, and skill levels.
    Keywords:  data-independent acquisition; label-free quantification; proteomics; spike-in quantification
    DOI:  https://doi.org/10.7171/3fc1f5fe.9b78d780
  11. Cells. 2023 Jul 03. pii: 1765. [Epub ahead of print]12(13):
      Metabolism not only produces energy necessary for the cell but is also a key regulator of several cellular functions, including pluripotency and self-renewal. Nucleotide sugars (NSs) are activated sugars that link glucose metabolism with cellular functions via protein N-glycosylation and O-GlcNAcylation. Thus, understanding how different metabolic pathways converge in the synthesis of NSs is critical to explore new opportunities for metabolic interference and modulation of stem cell functions. Tracer-based metabolomics is suited for this challenge, however chemically-defined, customizable media for stem cell culture in which nutrients can be replaced with isotopically labeled analogs are scarcely available. Here, we established a customizable flux-conditioned E8 (FC-E8) medium that enables stem cell culture with stable isotopes for metabolic tracing, and a dedicated liquid chromatography mass-spectrometry (LC-MS/MS) method targeting metabolic pathways converging in NS biosynthesis. By 13C6-glucose feeding, we successfully traced the time-course of carbon incorporation into NSs directly via glucose, and indirectly via other pathways, such as glycolysis and pentose phosphate pathways, in induced pluripotent stem cells (hiPSCs) and embryonic stem cells. Then, we applied these tools to investigate the NS biosynthesis in hiPSC lines from a patient affected by deficiency of phosphoglucomutase 1 (PGM1), an enzyme regulating the synthesis of the two most abundant NSs, UDP-glucose and UDP-galactose.
    Keywords:  O-GlcNAcylation; PGM1 deficiency; glycosylation; induced pluripotent stem cells; mass spectrometry-based isotopic tracing; nucleotide sugar metabolism
    DOI:  https://doi.org/10.3390/cells12131765
  12. Sci China Life Sci. 2023 Jul 11.
      Stearoyl-CoA desaturase 1 (SCD1) converts saturated fatty acids to monounsaturated fatty acids. The expression of SCD1 is increased in many cancers, and the altered expression contributes to the proliferation, invasion, sternness and chemoresistance of cancer cells. Recently, more evidence has been reported to further support the important role of SCD1 in cancer, and the regulation mechanism of SCD1 has also been focused. Multiple factors are involved in the regulation of SCD1, including metabolism, diet, tumor microenvironment, transcription factors, non-coding RNAs, and epigenetics modification. Moreover, SCD1 is found to be involved in regulating ferroptosis resistance. Based on these findings, SCD1 has been considered as a potential target for cancer treatment. However, the resistance of SCD1 inhibition may occur in certain tumors due to tumor heterogeneity and metabolic plasticity. This review summarizes recent advances in the regulation and function of SCD1 in tumors and discusses the potential clinical application of targeting SCD1 for cancer treatment.
    Keywords:  ER stress; SCD1; cancer metabolism; cancer therapy; drug resistance; fatty acid; ferroptosis; lipid metabolism
    DOI:  https://doi.org/10.1007/s11427-023-2352-9
  13. Adv Exp Med Biol. 2023 ;1415 37-42
      The molecular characterization of extracellular deposits is crucial to understanding the clinical progression of AMD. Liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis is a powerful analytical discovery tool capable of identifying lipids in an untargeted manner. NanoLC-MS/MS is an analytical tool capable of identifying lipids with high sensitivity and minimum sample usage. Hence, the purpose of this study was to compare retina lipid identification from RPE-choroid samples using high flow LC-MS/MS and nanoLC-MS/MS. Manually dissected paraformaldehyde-fixed human donor tissues sections were used for LC-MS/MS and nanoLC-MS/MS analysis. Lipids were extracted with MeOH/MTBE/CHCl3 (MMC) and were analyzed by LC-MS/MS and nanoLC-MS/MS using negative and positive ionization modes. Untargeted lipidomics using LC-MS/MS identified 215 lipids from 4 lipid classes and 15 subclasses. We observed a 78% increase in lipid identifications using nanoLC-MS/MS with lipid numbers totaling 384. The nanoLC-MS/MS method is expected to provide extensive lipid identifications from small retina samples, e.g., from drusen and drusenoid deposits in aged and AMD eyes, and could help elucidate how lipids are involved in extracellular deposit formation in AMD.
    Keywords:  Age-related macular degeneration; Fixed; LC-MS/MS; Lipids; NanoLC-MS/MS; RPE; Retina
    DOI:  https://doi.org/10.1007/978-3-031-27681-1_6
  14. J Mass Spectrom. 2023 Jul;58(7): e4958
      Quantification of pharmaceutical compounds using matrix-assisted laser desorption/ionization (MALDI) mass spectrometry (MS) is an alternative to traditional liquid chromatography (LC)-MS techniques. Benefits of MALDI-based approaches include rapid analysis times for liquid samples and imaging mass spectrometry capabilities for tissue samples. As in most quantification experiments, the use of internal standards can compensate for spot-to-spot and shot-to-shot variability associated with MALDI sampling. However, the lack of chromatographic separation in traditional MALDI analyses results in diminished peak capacity due to the chemical noise background, which can be detrimental to the dynamic range and limit of detection of these approaches. These issues can be mitigated by using a hybrid mass spectrometer equipped with a quadrupole mass filter (QMF) that can be used to fractionate ions based on their mass-to-charge ratios. When the masses of the analytes and internal standards are sufficiently disparate in mass, it can be beneficial to effect multiple narrow mass isolation windows using the QMF, as opposed to a single wide mass isolation window, to minimize chemical noise while allowing for internal standard normalization. Herein, we demonstrate a MALDI MS quantification workflow incorporating multiple sequential mass isolation windows enabled on a QMF, which divides the total number of MALDI laser shots into multiple segments (i.e., one segment for each mass isolation window). This approach is illustrated through the quantitative analysis of the pharmaceutical compound enalapril in human plasma samples as well as the simultaneous quantification of three pharmaceutical compounds (enalapril, ramipril, and verapamil). Results show a decrease in the limit of detection, relative standard deviations below 10%, and accuracy above 85% for drug quantification using multiple mass isolation windows. This approach has also been applied to the quantification of enalapril in brain tissue from a rat dosed in vitro. The average concentration of enalapril determined by imaging mass spectrometry is in agreement with the concentration determined by LC-MS, giving an accuracy of 104%.
    Keywords:  imaging mass spectrometry; ion isolation; pharmaceutical; quantification
    DOI:  https://doi.org/10.1002/jms.4958
  15. J Proteome Res. 2023 Jul 13.
      Thermal proteome profiling (TPP) provides a powerful approach to studying proteome-wide interactions of small therapeutic molecules and their target and off-target proteins, complementing phenotypic-based drug screens. Detecting differences in thermal stability due to target engagement requires high quantitative accuracy and consistent detection. Isobaric tandem mass tags (TMTs) are used to multiplex samples and increase quantification precision in TPP analysis by data-dependent acquisition (DDA). However, advances in data-independent acquisition (DIA) can provide higher sensitivity and protein coverage with reduced costs and sample preparation steps. Herein, we explored the performance of different DIA-based label-free quantification approaches compared to TMT-DDA for thermal shift quantitation. Acute myeloid leukemia cells were treated with losmapimod, a known inhibitor of MAPK14 (p38α). Label-free DIA approaches, and particularly the library-free mode in DIA-NN, were comparable of TMT-DDA in their ability to detect target engagement of losmapimod with MAPK14 and one of its downstream targets, MAPKAPK3. Using DIA for thermal shift quantitation is a cost-effective alternative to labeled quantitation in the TPP pipeline.
    Keywords:  acute myeloid leukemia (AML); data-dependent acquisition (DDA); data-independent acquisition (DIA); hybrid library; spectral library; tandem mass tag (TMT); target deconvolution; thermal proteome profiling (TPP)
    DOI:  https://doi.org/10.1021/acs.jproteome.3c00111
  16. Cell Rep Methods. 2023 06 26. 3(6): 100511
      The identification of tumor-specific antigens (TSAs) is critical for developing effective cancer immunotherapies. Mass spectrometry (MS)-based immunopeptidomics has emerged as a powerful tool for identifying TSAs as physical molecules. However, current immunopeptidomics platforms face challenges in measuring low-abundance TSAs in a precise, sensitive, and reproducible manner from small needle-tissue biopsies (<1 mg). Inspired by recent advances in single-cell proteomics, microfluidics technology offers a promising solution to these limitations by providing improved isolation of human leukocyte antigen (HLA)-associated peptides with higher sensitivity. In this context, we highlight the challenges in sample preparation and the rationale for developing microfluidics technology in immunopeptidomics. Additionally, we provide an overview of promising microfluidic methods, including microchip pillar arrays, valved-based systems, droplet microfluidics, and digital microfluidics, and discuss the latest research on their application in MS-based immunopeptidomics and single-cell proteomics.
    Keywords:  HLA; MHC; immunopeptidomics; mass spectrometry; microfluidics; peptide; single-cell proteomics
    DOI:  https://doi.org/10.1016/j.crmeth.2023.100511
  17. Cancers (Basel). 2023 Jul 03. pii: 3473. [Epub ahead of print]15(13):
      Advanced prostate cancer represents the fifth leading cause of cancer death in men worldwide. Although androgen-receptor signaling is the major driver of the disease, evidence is accumulating that disease progression is supported by substantial metabolic changes. Alterations in de novo lipogenesis and fatty acid catabolism are consistently reported during prostate cancer development and progression in association with androgen-receptor signaling. Therefore, the term "lipogenic phenotype" is frequently used to describe the complex metabolic rewiring that occurs in prostate cancer. However, a new scenario has emerged in which lactate may play a major role. Alterations in oncogenes/tumor suppressors, androgen signaling, hypoxic conditions, and cells in the tumor microenvironment can promote aerobic glycolysis in prostate cancer cells and the release of lactate in the tumor microenvironment, favoring immune evasion and metastasis. As prostate cancer is composed of metabolically heterogenous cells, glycolytic prostate cancer cells or cancer-associated fibroblasts can also secrete lactate and create "symbiotic" interactions with oxidative prostate cancer cells via lactate shuttling to sustain disease progression. Here, we discuss the multifaceted role of lactate in prostate cancer progression, taking into account the influence of the systemic metabolic and gut microbiota. We call special attention to the clinical opportunities of imaging lactate accumulation for patient stratification and targeting lactate metabolism.
    Keywords:  biomarkers; lactate; metabolic imaging; monocarboxylate transporters; prostate cancer; tumor microenvironment
    DOI:  https://doi.org/10.3390/cancers15133473
  18. Methods Mol Biol. 2023 ;2690 255-267
      Protein-protein interactions (PPIs) are the physical interactions formed among proteins. These interactions are primarily functional, i.e., they arise from specific biomolecular events, and each interaction interface serves a specific purpose. A significant number of methods have been developed for protein interactions in the field of proteomics in the last decade. Advanced mass spectrometry technology significantly contributed to the development of these methods. The rapid advancement of groundbreaking MS technology has greatly aided the mapping of protein interaction from large-data sets comprehensively. This chapter describes the affinity purification (AP) mass spectrometry (MS)-based methods combined with chemical cross-linking (XL) of protein complexes. This chapter includes sample preparation methods involving cell culture, cell treatments with ligands, drugs, and cross-linkers, protein extractions, affinity purification, sodium dodecyl sulfate (SDS) polyacrylamide gel separation, in-solution or in-gel digestion, liquid-chromatography, and mass spectrometry analysis of samples (LC-MS/MS). Application of a cleavable cross-linker, dual cleavable cross-linking technology (DUCCT) in combination with the affinity purification (AP) method has also been described. Methods for data analysis using unmodified and cross-linked peptide analysis are discussed.
    Keywords:  AP-MS; Cross-linking; Mass spectrometry; Protein; Proteomics; SDS polyacrylamide gel technique; protein interactions
    DOI:  https://doi.org/10.1007/978-1-0716-3327-4_22
  19. Methods Mol Biol. 2023 ;2690 299-310
      Affinity purification coupled to mass spectrometry (AP-MS) is a powerful method to analyze protein-protein interactions (PPIs). The AP-MS approach provides an unbiased analysis of the entire protein complex and is useful to identify indirect interactors. However, reliable protein identification from the complex AP-MS experiments requires appropriate control of false identifications and rigorous statistical analysis. Another challenge that can arise from AP-MS analysis is to distinguish bona fide interacting proteins from the non-specifically bound endogenous proteins or the "background contaminants" that co-purified by the bait experiments. In this chapter, we will first describe the protocol for performing in-solution trypsinization for the samples from the AP experiment followed by LC-MS/MS analysis. We will then detail the MaxQuant workflow for protein identification and quantification for the PPI data derived from the AP-MS experiment. Finally, we describe the CRAPome interface to process the data by filtering against contaminant lists, score the interactions and visualize the protein interaction networks.
    Keywords:  Affinity purification; CRAPome; In-solution digestion; Mass spectrometry; MaxQuant
    DOI:  https://doi.org/10.1007/978-1-0716-3327-4_25
  20. Front Oncol. 2023 ;13 1110235
      Short-chain fatty acids (SCFAs) are the main metabolites produced by bacterial fermentation of non-digestible carbohydrates in the gastrointestinal tract. They can be seen as the major flow of carbon from the diet, through the microbiome to the host. SCFAs have been reported as important molecules responsible for the regulation of intestinal homeostasis. Moreover, these molecules have a significant impact on the immune system and are able to affect inflammation, cardiovascular diseases, diabetes type II, or oncological diseases. For this purpose, SCFAs could be used as putative biomarkers of various diseases, including cancer. A potential diagnostic value may be offered by analyzing SCFAs with the use of advanced analytical approaches such as gas chromatography (GC), liquid chromatography (LC), or capillary electrophoresis (CE) coupled with mass spectrometry (MS). The presented review summarizes the importance of analyzing SCFAs from clinical and analytical perspective. Current advances in the analysis of SCFAs focused on sample pretreatment, separation strategy, and detection methods are highlighted. Additionally, it also shows potential areas for the development of future diagnostic tools in oncology and other varieties of diseases based on targeted metabolite profiling.
    Keywords:  biomarker; cancer; capillary electrophoresis; chromatography; mass spectrometry; separation methods; short-chain fatty acids
    DOI:  https://doi.org/10.3389/fonc.2023.1110235