bims-mascan Biomed News
on Mass spectrometry in cancer research
Issue of 2024‒04‒07
twenty papers selected by
Giovanny Rodriguez Blanco, University of Edinburgh

  1. Biochim Biophys Acta Mol Cell Biol Lipids. 2024 Mar 31. pii: S1388-1981(24)00041-6. [Epub ahead of print] 159491
      Inborn errors of metabolism (IEM) represent a heterogeneous group of more than 1800 rare disorders, many of which are causing significant childhood morbidity and mortality. More than 100 IEM are linked to dyslipidaemia, but yet our knowledge in connecting genetic information with lipidomic data is limited. Stable isotope tracing studies of the lipid metabolism (STL) provide insights on the dynamic of cellular lipid processes and could thereby facilitate the delineation of underlying metabolic (patho)mechanisms. This mini-review focuses on principles as well as technical limitations of STL and describes potential clinical applications by discussing recently published STL focusing on IEM.
    Keywords:  Flux studies; Lipids; Mass spectrometry; Metabolism; Rare diseases
  2. ArXiv. 2024 Mar 22. pii: arXiv:2403.15076v1. [Epub ahead of print]
      Lipidomics generates large data that makes manual annotation and interpretation challenging. Lipid chemical and structural diversity with structural isomers further complicates annotation. Although, several commercial and open-source software for targeted lipid identification exists, it lacks automated method generation workflows and integration with statistical and bioinformatics tools. We have developed the Comprehensive Lipidomic Automated Workflow (CLAW) platform with integrated workflow for parsing, detailed statistical analysis and lipid annotations based on custom multiple reaction monitoring (MRM) precursor and product ion pair transitions. CLAW contains several modules including identification of carbon-carbon double bond position(s) in unsaturated lipids when combined with ozone electrospray ionization (OzESI)-MRM methodology. To demonstrate the utility of the automated workflow in CLAW, large-scale lipidomics data was collected with traditional and OzESI-MRM profiling on biological and non-biological samples. Specifically, a total of 1497 transitions organized into 10 MRM-based mass spectrometry methods were used to profile lipid droplets isolated from different brain regions of 18-24 month-old Alzheimer's disease mice and age-matched wild-type controls. Additionally, triacyclglycerols (TGs) profiles with carbon-carbon double bond specificity were generated from canola oil samples using OzESI-MRM profiling. We also developed an integrated language user interface with large language models using artificially intelligent (AI) agents that permits users to interact with the CLAW platform using a chatbot terminal to perform statistical and bioinformatic analyses. We envision CLAW pipeline to be used in high-throughput lipid structural identification tasks aiding users to generate automated lipidomics workflows ranging from data acquisition to AI agent-based bioinformatic analysis.
  3. Anal Chem. 2024 Mar 30.
      High-throughput mass spectrometry (MS) has witnessed rapid advancements and has found extensive applications across various disciplines. It enables the fast and accurate analysis of large sample sets, delivering a 10-fold or greater enhancement in analytical throughput when compared to conventional LC-MS methods. However, the signal duration in these high-throughput MS technologies is typically confined to a narrow range, presenting challenges for workflows demanding prolonged signal durations. In this study, we introduce a method that enables precise modulation of the signal duration on an acoustic ejection mass spectrometry (AEMS) system while ensuring high signal reproducibility. This flexibility allows for simultaneous and precise analysis of a significantly greater number of MS/MS transitions in high-throughput MS environments. Additionally, it offers a unique approach for parameter optimization and method development with minimal sample volume requirements. This advancement enhances the efficiency of MS-based analyses across diverse applications and facilitates broader utilization of MS technologies in high-throughput settings, including data-dependent acquisition (DDA) and data-independent acquisition (DIA).
  4. bioRxiv. 2024 Mar 13. pii: 2024.03.12.584702. [Epub ahead of print]
      Glycans modify protein, lipid, and even RNA molecules to form the regulatory outer coat on cells called the glycocalyx. The changes in glycosylation have been linked to the initiation and progression of many diseases. Thus, while the significance of glycosylation is well established, a lack of accessible methods to characterize glycans has hindered the ability to understand their biological functions. Mass spectrometry (MS)-based methods have generally been at the core of most glycan profiling efforts; however, modern data-independent acquisition (DIA), which could increase sensitivity and simplify workflows, has not been benchmarked for analyzing glycans. Herein, we developed a DIA-based glycomic workflow, termed GlycanDIA, to identify and quantify glycans with high sensitivity and accuracy. The GlycanDIA workflow combined higher energy collisional dissociation (HCD)-MS/MS and staggered windows for glycomic analysis, which facilitates the sensitivity in identification and the accuracy in quantification compared to conventional data-dependent acquisition (DDA)-based glycomics. To facilitate its use, we also developed a generic search engine, GlycanDIA Finder, incorporating an iterative decoy searching for confident glycan identification and quantification from DIA data. The results showed that GlycanDIA can distinguish glycan composition and isomers from N-glycans, O-glycans, and human milk oligosaccharides (HMOs), while it also reveals information on low-abundant modified glycans. With the improved sensitivity, we performed experiments to profile N-glycans from RNA samples, which have been underrepresented due to their low abundance. Using this integrative workflow to unravel the N-glycan profile in cellular and tissue glycoRNA samples, we found that RNA-glycans have specific forms as compared to protein-glycans and are also tissue-specific differences, suggesting distinct functions in biological processes. Overall, GlycanDIA can provide comprehensive information for glycan identification and quantification, enabling researchers to obtain in-depth and refined details on the biological roles of glycosylation.
  5. Anal Chem. 2024 Apr 03.
      The heart contracts incessantly and requires a constant supply of energy, utilizing numerous metabolic substrates, such as fatty acids, carbohydrates, lipids, and amino acids, to supply its high energy demands. Therefore, a comprehensive analysis of various metabolites is urgently needed for understanding cardiac metabolism; however, complete metabolome analyses remain challenging due to the broad range of metabolite polarities, which makes extraction and detection difficult. Herein, we implemented parallel metabolite extractions and high-resolution mass spectrometry (MS)-based methods to obtain a comprehensive analysis of the human heart metabolome. To capture the diverse range of metabolite polarities, we first performed six parallel liquid-liquid extractions (three monophasic, two biphasic, and one triphasic) of healthy human donor heart tissue. Next, we utilized two complementary MS platforms for metabolite detection: direct-infusion ultrahigh-resolution Fourier-transform ion cyclotron resonance (DI-FTICR) and high-resolution liquid chromatography quadrupole time-of-flight tandem MS (LC-Q-TOF-MS/MS). Using DI-FTICR MS, 9644 metabolic features were detected where 7156 were assigned a molecular formula and 1107 were annotated by accurate mass assignment. Using LC-Q-TOF-MS/MS, 21,428 metabolic features were detected where 285 metabolites were identified based on fragmentation matching against publicly available libraries. Collectively, 1340 heart metabolites were identified in this study, which span a wide range of polarities including polar (benzenoids, carbohydrates, and nucleosides) as well as nonpolar (phosphatidylcholines, acylcarnitines, and fatty acids) compounds. The results from this study will provide critical knowledge regarding the selection of appropriate extraction and MS detection methods for the analysis of the diverse classes of human heart metabolites.
  6. Anal Chem. 2024 Mar 31.
      Sebum lipids are composed of nonpolar lipids, and they pose challenges for mass spectrometry-based analysis due to low ionization efficiency and the existence of numerous isomers and isobars. To address these challenges, we have developed ethyl 2-oxo-2-(pyridine-3-yacetate as a charge-tagging Paternò-Büchi reagent and Michler's ketone as a highly efficient photocatalyst, achieving ∼90% conversion for C═C derivatization under 440 nm LED irradiation. This derivatization, when coupled with electrospray ionization-tandem mass spectrometry, boosts the detection of sebum lipids and pinpoints C═C location in a chain-specific fashion. Identification and quantitation of isomers are readily achieved for wax esters, a class of underexplored sebum lipids, which have C═C bonds distributed in fatty alcohol and fatty acyl chains. A shotgun analysis workflow has been developed by pairing the offline PB derivatization with cyclic ion mobility spectrometry-mass spectrometry. Besides the dominant n-10 C═C location in unsaturated wax esters, profiling of low abundance isomers, including the rarely reported n-7 and n-13 locations, is greatly enhanced due to separations of C═C diagnostic ions by ion mobility. Over 900 distinct lipid structures from human sebum lipid extract have been profiled at the chain-specific C═C level, including wax esters (500), glycerolipids (393), and cholesterol esters (22), far more exceeding previous reports. Overall, we have developed a fast and comprehensive lipidomic profiling tool for sebum samples, a type of noninvasive biofluids holding potential for the discovery of disease markers in distal organs.
  7. Mol Cell Proteomics. 2024 Apr 03. pii: S1535-9476(24)00050-1. [Epub ahead of print] 100760
      We describe deep analysis of the human proteome in less than one hour. We achieve this expedited proteome characterization by leveraging state-of-the-art sample preparation, chromatographic separations, data analysis tools, and by using the new Orbitrap Astral mass spectrometer equipped with a quadrupole mass filter, a high-field Orbitrap mass analyzer, and an asymmetric track lossless (Astral) mass analyzer. The system offers high MS/MS acquisition speed of 200 Hz and detects hundreds of peptide sequences per second within data independent- or data-dependent acquisition modes of operation. The fast-switching capabilities of the new quadrupole complement the sensitivity and fast ion scanning of the Astral analyzer to enable narrow-bin data-independent analysis (DIA) methods. Over a 30-minute active chromatographic method consuming a total analysis time of 56 minutes, the Q-Orbitrap-Astral hybrid MS collects an average of 4,319 MS1 scans and 438,062 MS/MS scans per run, producing 235,916 peptide sequences (1% false discovery rate (FDR)). On average, each 30-minute analysis achieved detection of 10,411 protein groups (1% FDR). We conclude, with these results and alongside other recent reports, that the one-hour human proteome is within reach.
  8. Anal Chem. 2024 Apr 02.
      Untargeted metabolomics promises comprehensive characterization of small molecules in biological samples. However, the field is hampered by low annotation rates and abstract spectral data. Despite recent advances in computational metabolomics, manual annotations and manual confirmation of in-silico annotations remain important in the field. Here, exploratory data analysis methods for mass spectral data provide overviews, prioritization, and structural hypothesis starting points to researchers facing large quantities of spectral data. In this research, we propose a fluid means of dealing with mass spectral data using specXplore, an interactive Python dashboard providing interactive and complementary visualizations facilitating mass spectral similarity matrix exploration. Specifically, specXplore provides a two-dimensional t-distributed stochastic neighbor embedding embedding as a jumping board for local connectivity exploration using complementary interactive visualizations in the form of partial network drawings, similarity heatmaps, and fragmentation overview maps. SpecXplore makes use of state-of-the-art ms2deepscore pairwise spectral similarities as a quantitative backbone while allowing fast changes of threshold and connectivity limitation settings, providing flexibility in adjusting settings to suit the localized node environment being explored. We believe that specXplore can become an integral part of mass spectral data exploration efforts and assist users in the generation of structural hypotheses for compounds of interest.
  9. J Proteome Res. 2024 Apr 05.
      Biofluids contain molecules in circulation and from nearby organs that can be indicative of disease states. Characterizing the proteome of biofluids with DIA-MS is an emerging area of interest for biomarker discovery; yet, there is limited consensus on DIA-MS data analysis approaches for analyzing large numbers of biofluids. To evaluate various DIA-MS workflows, we collected urine from a clinically heterogeneous cohort of prostate cancer patients and acquired data in DDA and DIA scan modes. We then searched the DIA data against urine spectral libraries generated using common library generation approaches or a library-free method. We show that DIA-MS doubles the sample throughput compared to standard DDA-MS with minimal losses to peptide detection. We further demonstrate that using a sample-specific spectral library generated from individual urines maximizes peptide detection compared to a library-free approach, a pan-human library, or libraries generated from pooled, fractionated urines. Adding urine subproteomes, such as the urinary extracellular vesicular proteome, to the urine spectral library further improves the detection of prostate proteins in unfractionated urine. Altogether, we present an optimized DIA-MS workflow and provide several high-quality, comprehensive prostate cancer urine spectral libraries that can streamline future biomarker discovery studies of prostate cancer using DIA-MS.
    Keywords:  data-dependent acquisition; data-independent acquisition; mass spectrometry; prostate cancer; spectral library; urine
  10. J Am Soc Mass Spectrom. 2024 Apr 01.
      In untargeted metabolomics, the unambiguous identification of metabolites remains a major challenge. This requires high-quality spectral libraries for reliable metabolite identification, which is essential for translating metabolomics data into meaningful biological information. Several attempts have been made to generate reproducible product ion spectra (PIS) under a low collision energy (ELab) regime and nonresonant collisional conditions but have not fully succeeded. We examined the ERMS (energy-resolved mass spectrometry) breakdown curves of two lipo-amino acids and showed the possibility to highlight "singular points", called descriptors hereafter (linked to respective ELab depending on the instrument), for each of the monomodal product ion profiles. Using several instruments based on different technologies, the PIS recorded at these specific ELab sites shows remarkable similarities. The descriptors appeared as being independent of the fragmentation mechanisms and can be used to overcome the main instrumental effects that limit the interoperability of spectral libraries. This proof-of-concept study, performed on two particular lipo-amino acids, demonstrates the high potential of ERMS-derived information to determine the instrument-specific ELab at which PIS recorded in nonresonant conditions become highly similar and instrument-independent, thus comparable across platforms. This innovative but straightforward approach could help remove some of the obstacles to metabolite identification in nontargeted metabolomics, putting an end to a challenging chimera.
  11. J Proteome Res. 2024 Apr 02.
      Despite the recent and increasing knowledge surrounding COVID-19 infection, the underlying mechanisms of the persistence of symptoms for a long time after the acute infection are still not completely understood. Here, a multiplatform mass spectrometry-based approach was used for metabolomic and lipidomic profiling of human plasma samples from Long COVID patients (n = 40) to reveal mitochondrial dysfunction when compared with individuals fully recovered from acute mild COVID-19 (n = 40). Untargeted metabolomic analysis using CE-ESI(+/-)-TOF-MS and GC-Q-MS was performed. Additionally, a lipidomic analysis using LC-ESI(+/-)-QTOF-MS based on an in-house library revealed 447 lipid species identified with a high confidence annotation level. The integration of complementary analytical platforms has allowed a comprehensive metabolic and lipidomic characterization of plasma alterations in Long COVID disease that found 46 relevant metabolites which allowed to discriminate between Long COVID and fully recovered patients. We report specific metabolites altered in Long COVID, mainly related to a decrease in the amino acid metabolism and ceramide plasma levels and an increase in the tricarboxylic acid (TCA) cycle, reinforcing the evidence of an impaired mitochondrial function. The most relevant alterations shown in this study will help to better understand the insights of Long COVID syndrome by providing a deeper knowledge of the metabolomic basis of the pathology.
    Keywords:  CE-ESI(+/−)-TOF-MS; GC-Q-MS; RP-UHPLC-ESI(+/−)-QTOF-MS; ceramides; lipidomic; long-COVID; metabolomic; mitochondrial dysfunction; post-COVID syndrome (PCS); tricarboxylic acid (TCA) cycle
  12. Anal Chem. 2024 Apr 01.
      Microflow porous graphitized carbon liquid chromatography (PGC-LC) combined with negative mode ionization mass spectrometry (MS) provides high resolution separation and identification of reduced native N-glycan structural isomers. However, insufficient spray quality and low ionization efficiency of N-glycans present challenges for negative mode electrospray. Here, we evaluated the performance of a recently developed multinozzle electrospray source (MnESI) and accompanying M3 emitter for microflow PGC-LC-MS analysis of N-glycans in negative mode. In comparison to a standard electrospray ionization source, the MnESI with an M3 emitter improves signal intensity, identification, quantification, and resolution of structural isomers to accommodate low-input samples.
  13. bioRxiv. 2024 Mar 22. pii: 2024.03.20.586018. [Epub ahead of print]
      Clinical biomarker development has been stymied by inaccurate protein quantification from mass spectrometry (MS) discovery data and a prolonged validation process. To mitigate these issues, we created the Targeted Extraction Assessment of Quantification (TEAQ) software package. This innovative tool uses the discovery cohort analysis to select precursors, peptides, and proteins that adhere to established targeted assay criteria. TEAQ was applied to Data-Independent Acquisition MS data from plasma samples acquired on an Orbitrap™ Astral™ MS. Identified precursors were evaluated for linearity, specificity, repeatability, reproducibility, and intra-protein correlation from 11-point loading curves under three throughputs, to develop a resource for clinical-grade targeted assays. From a clinical cohort of individuals with inflammatory bowel disease (n=492), TEAQ successfully identified 1116 signature peptides for 327 quantifiable proteins from 1180 identified proteins. Embedding stringent selection criteria adaptable to targeted assay development into the analysis of discovery data will streamline the transition to validation and clinical studies.
  14. Methods Mol Biol. 2024 ;2797 299-322
      Prior analysis of intact and modified protein forms (proteoforms) of KRAS4B isolated from cell lines and tumor samples by top-down mass spectrometry revealed the presence of novel posttranslational modifications (PTMs) and potential evidence of context-specific KRAS4B modifications. However, low endogenous proteoform signal resulted in ineffective characterization, making it difficult to visualize less abundant PTMs or perform follow-up PTM validation using standard proteomic workflows. The NCI RAS Initiative has developed a model system, whereby KRAS4B bearing an N-terminal FLAG tag can be stably expressed within a panel of cancer cell lines. Herein, we present a method for combining immunoprecipitation with complementary proteomic methods to directly analyze N-terminally FLAG-tagged KRAS4B proteoforms and PTMs. We provide detailed protocols for FLAG-KRAS4B purification, proteoform analysis by targeted top-down LC-MS/MS, and validation of abundant PTMs by bottom-up LC-MS/MS with example results.
    Keywords:  FLAG tag; Farnesylation; Geranylgeranylation; Hydroxyfarnesylation; Immunoprecipitation; KRAS4B; Posttranslational modifications; Proteoform; Top-down mass spectrometry
  15. Anal Bioanal Chem. 2024 Apr 01.
      Liquid chromatography (LC) or gas chromatography (GC) coupled to high-resolution mass spectrometry (HRMS) is a versatile analytical method for the analysis of thousands of chemical pollutants that can be found in environmental and biological samples. While the tools for handling such complex datasets have improved, there are still no fully automated workflows for targeted screening analysis. Here we present an R-based workflow that is able to cope with challenging data like noisy ion chromatograms, retention time shifts, and multiple peak patterns. The workflow can be applied to batches of HRMS data recorded after GC with electron ionization (GC-EI) and LC coupled to electrospray ionization in both negative and positive mode (LC-ESIneg/LC-ESIpos) to perform peak annotation and quantitation fully unsupervised. We used Orbitrap HRMS data of surface water extracts to compare the Automated Target Screening (ATS) workflow with data evaluations performed with the vendor software TraceFinder and the established semi-automated analysis workflow in the MZmine software. The ATS approach increased the overall evaluation performance of the peak annotation compared to the established MZmine module without the need for any post-hoc corrections. The overall accuracy increased from 0.80 to 0.86 (LC-ESIpos), from 0.77 to 0.83 (LC-ESIneg), and from 0.67 to 0.76 (GC-EI). The mean average percentage errors for quantification of ATS were around 30% compared to the manual quantification with TraceFinder. The ATS workflow enables time-efficient analysis of GC- and LC-HRMS data and accelerates and improves the applicability of target screening in studies with a large number of analytes and sample sizes without the need for manual intervention.
    Keywords:  Automation; MZmine; Mass spectrometry; Target screening; TraceFinder; Workflow
  16. J Proteome Res. 2024 Mar 31.
      Protein-protein interactions (PPIs) are at the heart of the molecular landscape permeating life. Proteomics studies can explore this protein interaction landscape using mass spectrometry (MS). Thanks to their high sensitivity, mass spectrometers can easily identify thousands of proteins within a single sample, but that same sensitivity generates tangled spiderwebs of data that hide biologically relevant findings. So, what does a researcher do when she finds herself walking into spiderwebs? In a field focused on discovery, MS data require rigor in their analysis, experimental validation, or a combination of both. In this Review, we provide a brief primer on MS-based experimental methods to identify PPIs. We discuss approaches to analyze the resulting data and remove the proteomic background. We consider the advantages between comprehensive and targeted studies. We also discuss how scoring might be improved through AI-based protein structure information. Women have been essential to the development of proteomics, so we will specifically highlight work by women that has made this field thrive in recent years.
    Keywords:  mass spectrometry; protein−protein interactions; proteomic scoring
  17. J Ovarian Res. 2024 Apr 02. 17(1): 73
      Ovarian cancer is a leading cause of death among gynecologic tumors, often detected at advanced stages. Metabolic reprogramming and increased lipid biosynthesis are key factors driving cancer cell growth. Stearoyl-CoA desaturase 1 (SCD1) is a crucial enzyme involved in de novo lipid synthesis, producing mono-unsaturated fatty acids (MUFAs). Here, we aimed to investigate the expression and significance of SCD1 in epithelial ovarian cancer (EOC). Comparative analysis of normal ovarian surface epithelial (NOSE) tissues and cell lines revealed elevated SCD1 expression in EOC tissues and cells. Inhibition of SCD1 significantly reduced the proliferation of EOC cells and patient-derived organoids and induced apoptotic cell death. Interestingly, SCD1 inhibition did not affect the viability of non-cancer cells, indicating selective cytotoxicity against EOC cells. SCD1 inhibition on EOC cells induced endoplasmic reticulum (ER) stress by activating the unfolded protein response (UPR) sensors and resulted in apoptosis. The addition of exogenous oleic acid, a product of SCD1, rescued EOC cells from ER stress-mediated apoptosis induced by SCD1 inhibition, underscoring the importance of lipid desaturation for cancer cell survival. Taken together, our findings suggest that the inhibition of SCD1 is a promising biomarker as well as a novel therapeutic target for ovarian cancer by regulating ER stress and inducing cancer cell apoptosis.
    Keywords:  Apoptosis; ER stress; Lipid metabolism; Ovarian cancer; SCD1
  18. Mol Cancer. 2024 Apr 04. 23(1): 71
      It is generally recognized that tumor cells proliferate more rapidly than normal cells. Due to such an abnormally rapid proliferation rate, cancer cells constantly encounter the limits of insufficient oxygen and nutrient supplies. To satisfy their growth needs and resist adverse environmental events, tumor cells modify the metabolic pathways to produce both extra energies and substances required for rapid growth. Realizing the metabolic characters special for tumor cells will be helpful for eliminating them during therapy. Cell death is a hot topic of long-term study and targeting cell death is one of the most effective ways to repress tumor growth. Many studies have successfully demonstrated that metabolism is inextricably linked to cell death of cancer cells. Here we summarize the recently identified metabolic characters that specifically impact on different types of cell deaths and discuss their roles in tumorigenesis.
    Keywords:  Apoptosis; Autophage; Cell death; Cuproptosis; Ferroptosis; Pyroptosis; Tumor metabolism; Tumor microenvironment
  19. Heliyon. 2024 Apr 15. 10(7): e28467
      Endocannabinoids (eCBs) exert considerable influence over energy metabolism, lipid metabolism, and glucose metabolism within the human body. Among the most biologically active cannabinoids identified thus far are 2-arachidonoylglycerol (2-AG), arachidonoyl ethanolamide (AEA), 1-stearoylglycerol (1-SRG), and stearoyl ethanolamide (SEA), which are derived from arachidonic acid (AA) and stearic acid (SA). However, despite the unique in bioactivities exhibited by eCBs, their determination in plasma has been hindered by the lack of sensitive analytical methods. The aim of this study was to develop and validate a highly sensitive and rapid method using ultra-high performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) for accurate measurement of AEA, SEA, 2-AG, 1-SRG, AA, and SA levels in human plasma samples. Sample preparation involved a protein precipitation method and a methyl tert-butyl ether liquid-liquid extraction method. Chromatographic separation was accomplished by utilizing an ACQUITY UPLC BEH C8 column with a mobile phase of acetonitrile containing 0.1% formic acid and water containing 0.1% formic acid, flowing at a rate of 0.35 mL/min. AA-d8, 2-AG-d5, and AEA-d8 were selected as deuterated internal standards. The analytes were determined with MRM in both positive and negative ion mode. The lower limit of quantification ranged from 0.1 to 400 ng/mL, and the correlation coefficient (R2) was >0.99. Inter-day and intra-day precision exhibited values of 0.55-13.29% and 0.62%-13.90%, respectively. Recovery and matrix effect were within the range of 77.7%-109.7%, and 90.0%-113.5%, respectively. Stability tests confirmed the acceptability of all analytes. To demonstrate the effectiveness of the approach, it was implemented to assess and compare plasma samples from healthy volunteers (n = 49) and individuals with non-alcoholic fatty liver disease (NAFLD) (n = 62). The study revealed significant differences in AEA, SEA, AA, and SA levels between the two groups.
    Keywords:  Arachidonic acid; Endocannabinoids; LC-MS/MS; NAFLD; Stearic acid
  20. J Proteomics. 2024 Apr 02. pii: S1874-3919(24)00098-8. [Epub ahead of print] 105166
      Osteoporosis is characterized by weakened bone microstructure and loss of bone mass. Current diagnostic criteria for osteoporosis are based on the T-score, which is a measure of bone mineral density. However, osteoporotic fragility fractures can occur regardless of the T-score, underscoring the need for additional criteria for the early detection of patients at fracture risk. To identify indicators of reduced bone strength, we performed serum proteomic analysis using data-independent acquisition mass spectrometry with serum samples from two patient groups, one with osteoporosis but no fractures and the other with osteopenia and fragility fractures. Collective evaluation of the results identified six serum proteins that changed to a similar extent in both patient groups compared with controls. Of these, extracellular matrix protein 1 (ECM1), which contributes to bone formation, showed the most significant increase in serum levels in both patient groups. An ELISA-based assay suggested that ECM1 could serve as a serum indicator of the need for therapeutic intervention; however, further prospective studies with a larger sample size are necessary to confirm these results. The present findings may contribute to the provision of early and appropriate therapeutic strategies for patients at risk of osteoporotic fractures. SIGNIFICANCE: This study aimed to identify objective serum indicators of the need for therapeutic intervention in individuals at risk of osteoporotic fracture. Comprehensive proteome analyses of serum collected from patients with osteoporosis but no fractures, patients with osteopenia and fragility fractures, and controls were performed by data-independent acquisition mass spectrometry. Collective evaluation of the proteome analysis data and ELISA-based assays identified serum ECM1 as a potential objective marker of the risk of fragility fractures in patients with osteoporosis or osteopenia. The findings are an important step toward the development of appropriate bone health management methods to improve well-being and maintain quality of life.
    Keywords:  Data-independent acquisition mass spectrometry (DIA-MS); Osteoporosis; Proteomics; Serum biomarker