bims-mascan 2025-02-09 papers

bims-mascan

Biomed News

on Mass spectrometry in cancer research

Issue of 2025–02–09
twenty-two papers selected by
Giovanny Rodríguez Blanco, Uniklinikum Graz

Ion suppression correction and normalization for non-targeted metabolomics.
Formaldehyde Fixation Helps Preserve the Proteome State during Single-Cell Proteomics Sample Processing and Analysis.
TIMS2Rescore: A Data Dependent Acquisition-Parallel Accumulation and Serial Fragmentation-Optimized Data-Driven Rescoring Pipeline Based on MS2Rescore.
Dried blood spot microsampling: A semi-quantitative 4D-lipidomics approach using ultrahigh-performance liquid chromatography - high-resolution mass spectrometry (UHPLC - HRMS).
Liquid and gas-chromatography-mass spectrometry methods for exposome analysis.
Toward Machine Learning Electrospray Ionization Sensitivity Prediction for Semiquantitative Lipidomics in Stem Cells.
The effect of storage time and temperature on the proteomic analysis of FFPE tissue sections.
A Protocol for Determination of Proteinogenic Amino Acids in Biological Fluids by the High-Speed UHPLC-MS Method: Application on Transgenic Spontaneously Hypertensive Rat-24 Plasma and Cerebrospinal Fluid Samples.
Cancer cells avoid ferroptosis induced by immune cells via fatty acid binding proteins.
Integrated Metabolomics and Proteomics Analysis of the Myocardium in a Mouse Model of Acute Viral Myocarditis.
Lipid dysregulation in triple negative breast cancer: Insights from mass spectrometry-based approaches.
Pure Shift NMR with Solvent Suppression: A Robust and General Method for Determining Quantitative Metabolic Profiles in Biofluids.
Gas-phase fractionation DDA promotes in-depth DIA phosphoproteome analysis.
Multicenter Longitudinal Quality Assessment of MS-Based Proteomics in Plasma and Serum.
The emerging role of dysregulated propionate metabolism and methylmalonic acid in metabolic disease, aging, and cancer.
Protein corona formed on lipid nanoparticles compromises delivery efficiency of mRNA cargo.
Lactate homeostasis is maintained through regulation of glycolysis and lipolysis.
Metabolomics biomarkers of frailty: a longitudinal study of aging female and male mice.
Fast and comprehensive lipidomic analysis using supercritical fluid chromatography coupled with low and high resolution mass spectrometry.
ADAR1 Regulates Lipid Remodeling through MDM2 to Dictate Ferroptosis Sensitivity.
Characterization of trimethylamine metabolic pathways using pseudo-targeted metabolomics.
Arginine: at the crossroads of nitrogen metabolism.

Nat Commun. 2025 Feb 04. 16(1): 1347

Ion suppression correction and normalization for non-targeted metabolomics.

Iqbal Mahmud, Bo Wei, Lucas Veillon, Lin Tan, Sara Martinez, Bao Tran, Alexander Raskind, Felice de Jong, Yiwei Liu, Jibin Ding, Yun Xiong, Wai-Kin Chan, Rehan Akbani, John N Weinstein, Chris Beecher, Philip L Lorenzi.

Ion suppression is a major problem in mass spectrometry (MS)-based metabolomics; it can dramatically decrease measurement accuracy, precision, and sensitivity. Here we report a method, the IROA TruQuant Workflow, that uses a stable isotope-labeled internal standard (IROA-IS) library plus companion algorithms to: 1) measure and correct for ion suppression, and 2) perform Dual MSTUS normalization of MS metabolomic data. We evaluate the method across ion chromatography (IC), hydrophilic interaction liquid chromatography (HILIC), and reversed-phase liquid chromatography (RPLC)-MS systems in both positive and negative ionization modes, with clean and unclean ion sources, and across different biological matrices. Across the broad range of conditions tested, all detected metabolites exhibit ion suppression ranging from 1% to >90% and coefficients of variation ranging from 1% to 20%, but the Workflow and companion algorithms are highly effective at nulling out that suppression and error. To demonstrate a routine application of the Workflow, we employ the Workflow to study ovarian cancer cell response to the enzyme-drug L-asparaginase (ASNase). The IROA-normalized data reveal significant alterations in peptide metabolism, which have not been reported previously. Overall, the Workflow corrects ion suppression across diverse analytical conditions and produces robust normalization of non-targeted metabolomic data.

DOI: https://doi.org/10.1038/s41467-025-56646-8
J Proteome Res. 2025 Feb 03.

Formaldehyde Fixation Helps Preserve the Proteome State during Single-Cell Proteomics Sample Processing and Analysis.

Ilaria Piga, Claire Koenig, Maico Lechner, Pierre Sabatier, Jesper V Olsen.

  Mass spectrometry-based single-cell proteomics (SCP) is gaining momentum but remains limited to a few laboratories due to the high costs and specialized expertise required. The ability to send samples to specialized core facilities would benefit nonspecialist laboratories and popularize SCP for biological applications. However, no methods have been tested in SCP to "freeze" the proteome state while maintaining cell integrity for transfer between laboratories or prolonged sorting using fluorescence-activated cell sorting (FACS). This study evaluates whether short-term formaldehyde (FA) fixation can maintain the cell states. We demonstrate that short-term FA fixation does not substantially affect protein recovery, even without heating and strong detergents, and maintains analytical depth compared with classical workflows. Fixation also preserves drug-induced specific perturbations of the protein abundance during cell sorting and sample preparation for SCP analysis. Our findings suggest that FA fixation can facilitate SCP by enabling sample shipping and prolonged sorting, potentially democratizing access to SCP technology and expanding its application in biological research, thereby accelerating discoveries in cell biology and personalized medicine.

Keywords:  One-Tip; cell-sorting; formaldehyde fixation; single-cell proteomics

DOI:  https://doi.org/10.1021/acs.jproteome.4c00656
J Proteome Res. 2025 Feb 06.

TIMS2Rescore: A Data Dependent Acquisition-Parallel Accumulation and Serial Fragmentation-Optimized Data-Driven Rescoring Pipeline Based on MS2Rescore.

Arthur Declercq, Robbe Devreese, Jonas Scheid, Caroline Jachmann, Tim Van Den Bossche, Annica Preikschat, David Gomez-Zepeda, Jeewan Babu Rijal, Aurélie Hirschler, Jonathan R Krieger, Tharan Srikumar, George Rosenberger, Claudia Martelli, Dennis Trede, Christine Carapito, Stefan Tenzer, Juliane S Walz, Sven Degroeve, Robbin Bouwmeester, Lennart Martens, Ralf Gabriels.

  The high throughput analysis of proteins with mass spectrometry (MS) is highly valuable for understanding human biology, discovering disease biomarkers, identifying therapeutic targets, and exploring pathogen interactions. To achieve these goals, specialized proteomics subfields, including plasma proteomics, immunopeptidomics, and metaproteomics, must tackle specific analytical challenges, such as an increased identification ambiguity compared to routine proteomics experiments. Technical advancements in MS instrumentation can mitigate these issues by acquiring more discerning information at higher sensitivity levels. This is exemplified by the incorporation of ion mobility and parallel accumulation and serial fragmentation (PASEF) technologies in timsTOF instruments. In addition, AI-based bioinformatics solutions can help overcome ambiguity issues by integrating more data into the identification workflow. Here, we introduce TIMS2Rescore, a data-driven rescoring workflow optimized for DDA-PASEF data from timsTOF instruments. This platform includes new timsTOF MS2PIP spectrum prediction models and IM2Deep, a new deep learning-based peptide ion mobility predictor. Furthermore, to fully streamline data throughput, TIMS2Rescore directly accepts Bruker raw mass spectrometry data and search results from ProteoScape and many other search engines, including Sage and PEAKS. We showcase TIMS2Rescore performance on plasma proteomics, immunopeptidomics (HLA class I and II), and metaproteomics data sets. TIMS2Rescore is open-source and freely available at https://github.com/compomics/tims2rescore.

Keywords:  DDA-PASEF; machine learning; mass spectrometry; peptide identification; proteomics; rescoring; timsTOF

DOI:  https://doi.org/10.1021/acs.jproteome.4c00609
Talanta. 2025 Feb 01. pii: S0039-9140(25)00163-8. [Epub ahead of print]287 127677

Dried blood spot microsampling: A semi-quantitative 4D-lipidomics approach using ultrahigh-performance liquid chromatography - high-resolution mass spectrometry (UHPLC - HRMS).

Jayden Lee Roberts, Monique J Ryan, Luke Whiley, Melvin Gay, Vimalnath Nambiar, Elaine Holmes, Jeremy K Nicholson, Julien Wist, Nicola Gray, Nathan G Lawler.

  Dried blood spot (DBS) sample collections can offer a minimally invasive, cost-effective alternative to traditional venepuncture for remote sampling and high-frequency metabolic profiling. We present an optimized protocol for DBS-based extraction and comprehensive untargeted 4D lipid profiling using ultrahigh-performance liquid chromatography coupled with high-resolution mass spectrometry (trapped ion mobility - mass spectrometry), designed to support large-scale applications in population-wide lipidomics research. Inclusion of stable isotopically labelled internal standards allowed for semi-quantitative subclass-level correction for 10 μL DBS samples, enhancing the number of reproducible lipids within our curated target list (focussed on 432 unique rule-based lipid annotations out of 6845 features) across positive and negative heated electrospray ionization modes. The reproducibility of unique lipid features detected in replicate DBS (n = 6) was assessed on both peak areas (351 lipids <25 % CV) and calculated concentrations relative to internal standards (432 lipids <25 % CV), underscoring the benefit of internal standard addition. Storage conditions for DBS were also evaluated to determine short-term lipid stability at different temperatures (-20 °C, 4 °C, room temperature, and 45 °C). The majority of lipid subclasses, excluding a minority of glycerophospholipids and oxylipins, were stable up to 1 week at -20 °C and 4 °C (log2-fold change <30 % difference), which supports the short-term storage capacity for DBS in field and clinical settings. Similar stability was observed within a week at room temperature, excluding phosphatidylethanolamines and phosphatidylglycerols (log2-fold change >30 % difference). Application of the optimized workflow to a microsampling device (n = 6) identified 432 unique lipid features (CV < 25 %) with three repeated samplings over an hour showing minimal impact on lipid profiles by principal component analysis, showing promise for high-frequency, longitudinal DBS monitoring in population health. This work represents a significant advance, highlighting the potential for reliable lipid analysis from DBS samples with short-term stability under various storage conditions, an important logistical benefit for remote or resource-limited settings.

Keywords:  4D lipidomics; Dried blood spots (DBS); Lipids; Mass spectrometry; Microsampling; Patient-centric sampling; Storage stability

DOI:  https://doi.org/10.1016/j.talanta.2025.127677
J Chromatogr A. 2025 Jan 25. pii: S0021-9673(25)00077-9. [Epub ahead of print]1744 465728

Liquid and gas-chromatography-mass spectrometry methods for exposome analysis.

Victor Castro-Alves, Anh Hoang Nguyen, João Marcos G Barbosa, Matej Orešič, Tuulia Hyötyläinen.

  Mass spectrometry-based methods have become fundamental to exposome research, providing the capability to explore a broad spectrum of chemical exposures. Liquid and gas chromatography coupled with low/high-resolution mass spectrometry (MS) are among the most frequently employed platforms due to their sensitivity and accuracy. However, these approaches present challenges, such as the inherent complexity of MS data and the expertise of biologists, chemists, clinicians, and data analysts to integrate and interpret MS data with other datasets effectively. The "omics" era advances rapidly, driven by developments of AI-based algorithms and an increase in accessible data; nevertheless, further efforts are necessary to ensure that exposomics outputs are comparable and reproducible, thus enhancing research findings. This review outlines the principles of MS-based methods for the exposome analytical pipeline, from sample collection to data analysis. We summarize and review both standard and cutting-edge strategies in exposome research, covering sample preparation, focusing on MS-based platforms, data acquisition strategies, and data annotation. The ultimate goal of this review is to highlight applications that enable the simultaneous analysis of endogenous metabolites and xenobiotics, which can help enhance our understanding of the impact of human exposure on health and disease and support personalized healthcare.

Keywords:  Chromatography; Environmental pollutants; Exposome; Mass spectrometry; Metabolomics

DOI:  https://doi.org/10.1016/j.chroma.2025.465728
J Chem Inf Model. 2025 Feb 05.

Toward Machine Learning Electrospray Ionization Sensitivity Prediction for Semiquantitative Lipidomics in Stem Cells.

Alexandria Van Grouw, Markace A Rainey, Olivia K Reid, Molly M Ogle, Samuel G Moore, Johnna S Temenoff, Facundo M Fernández.

Specificity, sensitivity, and high metabolite coverage make mass spectrometry (MS) one of the most valuable tools in metabolomics and lipidomics. However, translation of metabolomics MS methods to multiyear studies conducted across multiple batches is limited by variability in electrospray ionization response, making batch-to-batch comparisons challenging. This limitation creates an artificial divide between nontargeted discovery work that is broad in scope but limited in terms of absolute quantitation ability and targeted work that is highly accurate but limited in scope due to the need for matched isotopically labeled standards. These issues are often observed in stem cell studies using metabolomic and lipidomic MS approaches, where patient recruitment can be a years-long process and samples become available in discrete batches every few months. To bridge this gap, we developed a machine learning model that predicts electrospray ionization sensitivity for lipid classes that have shown correlation with stem cell potency. Molecular descriptors derived from these lipids' chemical structures are used as model input to predict electrospray response, enabling quantitation by MS with moderate accuracy (semiquantitation). Model performance was evaluated via internal and external validation using cultured cells from various stem cell donors, achieving global percent errors of 40% and 20% for positive and negative electrospray ion modes, respectively. Although this accuracy is typically insufficient for traditional targeted lipidomics experiments, it is sufficient for semiquantitative estimation of lipid marker concentrations across batches without the need for specific chemical standards that many times are unavailable. Furthermore, the precision for model-predicted concentrations was 16.9% for the positive mode and 7.5% for the negative mode, indicating promise for data harmonization across batches. The set of molecular descriptors used by the models described here was able to yield higher accuracy than those previously published in the literature, showing high promise toward semiquantitative lipidomics.

DOI: https://doi.org/10.1021/acs.jcim.4c02040
Clin Proteomics. 2025 Feb 05. 22(1): 5

The effect of storage time and temperature on the proteomic analysis of FFPE tissue sections.

Jennifer M S Koh, Erin K Sykes, Jyoti Rukhaya, Asim Anees, Qing Zhong, Christopher Jackson, Benedict J Panizza, Roger R Reddel, Rosemary L Balleine, Peter G Hains, Phillip J Robinson.

Formalin-fixed paraffin-embedded (FFPE) tissues present an important resource for cancer proteomics. They are more readily available than fresh frozen (FF) tissues and can be stored at ambient temperature for decades. FFPE blocks are largely stable for long-term preservation of tumour histology, but the antigenicity of some proteins in FFPE sections degrades over time resulting in deteriorating performance of immunohistochemistry (IHC). It is not known whether FFPE sections that have previously been cut from blocks and used for liquid chromatography-mass spectrometry (LC-MS) analysis at a later time are affected by storage time or temperature. We determined the stability of FFPE sections stored at room temperature (RT) versus - 80 °C over 48 weeks. The stored sections were processed at different timepoints (n = 11) and compared to sections that were freshly cut from FFPE blocks at each timepoint (controls). A total of 297 sections (rat brain, kidney and liver stored at RT, - 80 °C or freshly cut) were tryptically digested and analysed on TripleTOF 6600 mass spectrometers in data-dependent acquisition (DDA) mode. Kidney and liver digests were also analysed in data-independent acquisition (DIA) mode. The number of proteins and peptides identified by DDA with ProteinPilot and some common post-translational modifications (PTMs) were unaffected by the storage time or temperature. Nine of the most common FFPE-associated modifications were quantified using DIA data and all were unaffected by storage time or temperature. Therefore, FFPE tissue sections are suitable for proteomic studies for at least 48 weeks from the time of sectioning.

DOI: https://doi.org/10.1186/s12014-025-09529-5
J Sep Sci. 2025 Feb;48(2): e70089

A Protocol for Determination of Proteinogenic Amino Acids in Biological Fluids by the High-Speed UHPLC-MS Method: Application on Transgenic Spontaneously Hypertensive Rat-24 Plasma and Cerebrospinal Fluid Samples.

Juraj Piestansky, Dominika Olesova, Petra Majerova, Petra Chalova, Andrej Kovac.

  Recently, proteinogenic amino acids have become very interesting molecules, accompanied by a large variety of metabolic processes in humans and are associated with various diseases. In the era of system biology, including a broad spectrum of associated disciplines (e.g., metabolomics, lipidomics, proteomics, etc.), the possibility of identifying trustworthy biomarkers of diseases becomes much more likely. Changes in amino acid levels in plasma, serum, or cerebrospinal fluid reflect physiological or pathological conditions and, therefore, their regular monitoring can lead to early detection of the occurrence of a disease. Therefore, the exact determination of amino acids in biological fluids is of great importance. However, it is necessary to dispose with an effective, accurate, precise, selective, and robust analytical method. This protocol describes the complex procedure of amino acid analysis based on a combination of UHPLC with single quadrupole MS. The protocol presents a highly reproducible and robust methodology that has already been established in the quality control of biopharmaceuticals and determination of proteinogenic amino acids in urine in our laboratory. Here, the application potential is extended to the most frequently investigated biological fluid, that is, plasma and to the cerebrospinal fluid, which is investigated in many neurological conditions.

Keywords:  Alzheimer's disease; biological samples; proteinogenic amino acids; single quadrupole mass spectrometer; ultraperformance liquid chromatography

DOI:  https://doi.org/10.1002/jssc.70089
Mol Cancer. 2025 Feb 03. 24(1): 40

Cancer cells avoid ferroptosis induced by immune cells via fatty acid binding proteins.

Maria Angelica Freitas-Cortez, Fatemeh Masrorpour, Hong Jiang, Iqbal Mahmud, Yue Lu, Ailing Huang, Lisa K Duong, Qi Wang, Tiffany A Voss, Claudia S Kettlun Leyton, Bo Wei, Wai-Kin Chan, Kevin Lin, Jie Zhang, Efrosini Tsouko, Shonik Ganjoo, Hampartsoum B Barsoumian, Thomas S Riad, Yun Hu, Carola Leuschner, Nahum Puebla-Osorio, Jing Wang, Jian Hu, Michael A Davies, Vinay K Puduvalli, Cyrielle Billon, Thomas P Burris, Philip L Lorenzi, Boyi Gan, James W Welsh.

   BACKGROUND: Cancer creates an immunosuppressive environment that hampers immune responses, allowing tumors to grow and resist therapy. One way the immune system fights back is by inducing ferroptosis, a type of cell death, in tumor cells through CD8 + T cells. This involves lipid peroxidation and enzymes like lysophosphatidylcholine acyltransferase 3 (Lpcat3), which makes cells more prone to ferroptosis. However, the mechanisms by which cancer cells avoid immunotherapy-mediated ferroptosis are unclear. Our study reveals how cancer cells evade ferroptosis and anti-tumor immunity through the upregulation of fatty acid-binding protein 7 (Fabp7).
METHODS: To explore how cancer cells resist immune cell-mediated ferroptosis, we used a comprehensive range of techniques. We worked with cell lines including PD1-sensitive, PD1-resistant, B16F10, and QPP7 glioblastoma cells, and conducted in vivo studies in syngeneic 129 Sv/Ev, C57BL/6, and conditional knockout mice with Rora deletion specifically in CD8+ T cells, Cd8 cre;Rorafl mice. Methods included mass spectrometry-based lipidomics, targeted lipidomics, Oil Red O staining, Seahorse analysis, quantitative PCR, immunohistochemistry, PPARγ transcription factor assays, ChIP-seq, untargeted lipidomic analysis, ROS assay, ex vivo co-culture of CD8+ T cells with cancer cells, ATAC-seq, RNA-seq, Western blotting, co-immunoprecipitation assay, flow cytometry and Imaging Mass Cytometry.
RESULTS: PD1-resistant tumors upregulate Fabp7, driving protective metabolic changes that shield cells from ferroptosis and evade anti-tumor immunity. Fabp7 decreases the transcription of ferroptosis-inducing genes like Lpcat3 and increases the transcription of ferroptosis-protective genes such as Bmal1 through epigenetic reprogramming. Lipidomic profiling revealed that Fabp7 increases triglycerides and monounsaturated fatty acids (MUFAs), which impede lipid peroxidation and ROS generation. Fabp7 also improves mitochondrial function and fatty acid oxidation (FAO), enhancing cancer cell survival. Furthermore, cancer cells increase Fabp7 expression in CD8+ T cells, disrupting circadian clock gene expression and triggering apoptosis through p53 stabilization. Clinical trial data revealed that higher FABP7 expression correlates with poorer overall survival and progression-free survival in patients undergoing immunotherapy.
CONCLUSIONS: Our study uncovers a novel mechanism by which cancer cells evade immune-mediated ferroptosis through Fabp7 upregulation. This protein reprograms lipid metabolism and disrupts circadian regulation in immune cells, promoting tumor survival and resistance to immunotherapy. Targeting Fabp7 could enhance immunotherapy effectiveness by re-sensitizing resistant tumors to ferroptosis.

Keywords:  Bmal1; Cancer; Circadian clock; FABP7; Ferroptosis; Immunotherapy; Lpcat3

DOI:  https://doi.org/10.1186/s12943-024-02198-2
Immun Inflamm Dis. 2025 Feb;13(2): e70151

Integrated Metabolomics and Proteomics Analysis of the Myocardium in a Mouse Model of Acute Viral Myocarditis.

Yimin Xue, Jiuyun Zhang, Mingguang Chen, Qiaolian Fan, Tingfeng Huang, Jun Ke, Feng Chen.

   BACKGROUND: Acute viral myocarditis (AVMC) is a common inflammatory disease affecting the myocardium and is often accompanied by severe metabolic disturbances. The molecular mechanisms underlying this disease are complex and not yet fully understood.
METHODS AND RESULTS: Coxsackievirus B3 (CVB3)-induced AVMC mouse models were established. By integrating ultra-high-performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS)-based metabolomics and data-independent acquisition (DIA)-based proteomics, we aimed to investigate the global influence of CVB3 infection on the myocardial metabolome and proteome in mice. Based on the criterion of OPLS-DA VIP > 1.0 and p value < 0.05, a total of 149 differential metabolites (DMs) were identified, including 64 upregulated and 85 downregulated metabolites. Bioinformatics analysis revealed that these DMs were mostly enriched in Global and overview maps (Metabolic pathways), Energy metabolism (Sulfur metabolism and Nitrogen metabolism), Amino acid metabolism (Taurine and hypotaurine metabolism, Lysine degradation, and Arginine and proline metabolism), and Carbohydrate metabolism (Propanoate metabolism). Differential analysis also identified 1385 differential proteins (DPs) between the two groups (|Fold Change| >1.5 and p value < 0.05), including 1092 upregulated and 293 downregulated proteins. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses of DPs indicated that metabolism-related pathways were significant components of the AVMC process. Next, we mined many DPs engaged in the above metabolic pathways through an integrated analysis of KEGG pathway-based metabolomics and proteomics data.
CONCLUSIONS: Our integrated metabolomics and proteomics analysis revealed characteristic alterations in metabolites and proteins in the myocardium of AVMC, as well as the associations between them. This not only extends the existing understanding of the molecular basis of the pathogenesis and progression of AVMC but also suggests new directions for its treatment.

Keywords:  Coxsackievirus B3; acute viral myocarditis; metabolomics; myocardium; proteomics

DOI:  https://doi.org/10.1002/iid3.70151
Prog Lipid Res. 2025 Feb 04. pii: S0163-7827(25)00012-8. [Epub ahead of print] 101330

Lipid dysregulation in triple negative breast cancer: Insights from mass spectrometry-based approaches.

Xiaoyue Huang, Ahmed Ali, Dounia E I Yachioui, Sylvia E Le Dévédec, Thomas Hankemeier.

  Triple negative breast cancer (TNBC) has the worst prognosis among breast cancers due to its aggressive nature and the absence of targeted treatments. Development of novel anti-cancer drugs for TNBC faces challenges stemming from its heterogeneity and high potential for metastasis. Metabolomics can be a useful technology in finding novel therapeutic targets and probing the heterogeneity of TNBC. Metabolomics has been enabled by advancements in mass spectrometry (MS)-based platforms that facilitated comprehensive profiling of TNBC metabolism. This review provides an overview of metabolomic changes in TNBC with emphasis on lipid alterations, and describes the key MS analytical techniques, providing the necessary background for examining the role of lipids in TNBC development.

Keywords:  Lipids; Mass spectrometry; Metastasis; Triple negative breast cancer

DOI:  https://doi.org/10.1016/j.plipres.2025.101330
Anal Chem. 2025 Feb 04.

Pure Shift NMR with Solvent Suppression: A Robust and General Method for Determining Quantitative Metabolic Profiles in Biofluids.

Xi Chen, Cédric Caradeuc, Gildas Bertho, Covadonga Lucas-Torres, Nicolas Giraud.

Ultrahigh-resolution pure shift NMR has recently been shown as a promising approach for providing quantitative metabolic profiles that can be used to study the metabolic footprint left by cancer cells in their aqueous growth medium. In this approach, a library of reference 1H pure shift spectra with water suppression was implemented to determine metabolite concentrations from the NOESY-presat-PSYCHE-SAPPHIRE spectrum recorded on the extracellular medium. This achievement clearly called for a generalization of a quantification method relying on ultrahigh-resolution data to other biological samples of interest (urine, plasma, tissue extracts, etc.), which requires evaluating the robustness of the analytical workflow. We have first addressed the influence of sample preparation on the quality of metabolite quantification. The quantification performed on a model mixture of metabolites prepared under different conditions shows good linearity, trueness, and precision, which highlights the high reproducibility of the proposed analytical protocol regardless of the physicochemical conditions in the sample. Second, we have successfully implemented this quantification protocol to determine metabolite levels in real urine and plasma samples, thereby paving the way for the use of the library of pure shift reference spectra for accurate and quantitative metabolic profiling of a broad range of aqueous samples.

DOI: https://doi.org/10.1021/acs.analchem.4c05261
Heliyon. 2025 Jan 30. 11(2): e41928

Gas-phase fractionation DDA promotes in-depth DIA phosphoproteome analysis.

Zhiwei Tu, Yabin Li, Shuhui Ji, Shanshan Wang, Rui Zhou, Gertjan Kramer, Yu Cui, Fei Xie.

  Data-independent acquisition (DIA) is a promising method for quantitative proteomics. Library-based DIA database searching against project-specific data-dependent acquisition (DDA) spectral libraries is the gold standard. These libraries are constructed using material-consuming pre-fractionation two dimensional DDA analysis. The alternative to this is library-free DIA analysis. Limited sample amounts restrict the use of fractionation to build spectral libraries for post-translational modifications (PTMs) DIA analysis. We present the use of gas-phase fractionation (GPF) DDA data to improve the depth of library-free DIA identification for the phosphoproteome, called GPF-DDA hybrid DIA. This method fully utilizes the remnants of samples post-DIA analysis and leverages both library-based and -free DIA database searching. GPF-DDA hybrid DIA analyzes phosphopeptides surplus sample after DIA analysis using a number of DDA injections with each scanning different mass-to-charge (m/z) windows, instead of preforming traditional off-line fractionation-based DDA. The GPF-DDA data is integrated into the library-free DIA database search to create a hybrid library, enhancing phosphopeptide identification. Two GPF-DDA injections proved to increase 18 % phosphopeptide and 13 % phosphosite identification in HEK293 cell lines, while five injections resulted in up to 28 % phosphopeptide and 21 % phosphosite increases compared to library-free DIA analysis alone. We used GPF-DDA hybrid DIA phosphoproteomics to characterize lung tissue upon direct (smoke induced) and indirect (sepsis induced) acute lung injury (ALI) in mice. The differentially expressed phosphosites (DEPsites) in direct ALI were found in proteins related to mRNA processing and RNA. DEPsites in indirect ALI were enriched in proteins related to microtubule polymerization, positive regulation of microtubule polymerization and fibroblast migration. This study demonstrates that GPF-DDA hybrid DIA analysis workflow can indeed promote depth of DIA analysis of phosphoproteome and could be extended to DIA analysis of other PTMs.

Keywords:  ARDS/ALI; DIA; GPF DDA; Gas phase fractionation; Phosphoproteome

DOI:  https://doi.org/10.1016/j.heliyon.2025.e41928
J Proteome Res. 2025 Feb 07.

Multicenter Longitudinal Quality Assessment of MS-Based Proteomics in Plasma and Serum.

Oliver Kardell, Thomas Gronauer, Christine von Toerne, Juliane Merl-Pham, Ann-Christine König, Teresa K Barth, Julia Mergner, Christina Ludwig, Johanna Tüshaus, Pieter Giesbertz, Stephan Breimann, Lisa Schweizer, Torsten Müller, Georg Kliewer, Ute Distler, David Gomez-Zepeda, Oliver Popp, Di Qin, Daniel Teupser, Jürgen Cox, Axel Imhof, Bernhard Küster, Stefan F Lichtenthaler, Jeroen Krijgsveld, Stefan Tenzer, Philipp Mertins, Fabian Coscia, Stefanie M Hauck.

  Advancing MS-based proteomics toward clinical applications evolves around developing standardized start-to-finish and fit-for-purpose workflows for clinical specimens. Steps along the method design involve the determination and optimization of several bioanalytical parameters such as selectivity, sensitivity, accuracy, and precision. In a joint effort, eight proteomics laboratories belonging to the MSCoreSys initiative including the CLINSPECT-M, MSTARS, DIASyM, and SMART-CARE consortia performed a longitudinal round-robin study to assess the analysis performance of plasma and serum as clinically relevant samples. A variety of LC-MS/MS setups including mass spectrometer models from ThermoFisher and Bruker as well as LC systems from ThermoFisher, Evosep, and Waters Corporation were used in this study. As key performance indicators, sensitivity, precision, and reproducibility were monitored over time. Protein identifications range between 300 and 400 IDs across different state-of-the-art MS instruments, with timsTOF Pro, Orbitrap Exploris 480, and Q Exactive HF-X being among the top performers. Overall, 71 proteins are reproducibly detectable in all setups in both serum and plasma samples, and 22 of these proteins are FDA-approved biomarkers, which are reproducibly quantified (CV < 20% with label-free quantification). In total, the round-robin study highlights a promising baseline for bringing MS-based measurements of serum and plasma samples closer to clinical utility.

Keywords:  LC-MS/MS; R package mpwR; clinical specimen; longitudinal round-robin study; plasma; serum

DOI:  https://doi.org/10.1021/acs.jproteome.4c00644
Cell Metab. 2025 Feb 04. pii: S1550-4131(25)00005-1. [Epub ahead of print]37(2): 316-329

The emerging role of dysregulated propionate metabolism and methylmalonic acid in metabolic disease, aging, and cancer.

Moniquetta Shafer, Vivien Low, Zhongchi Li, John Blenis.

  Propionate metabolism dysregulation has emerged as a source of metabolic health alterations linked to aging, cardiovascular and renal diseases, obesity and diabetes, and cancer. This is supported by several large cohort population studies and recent work revealing its role in cancer progression. Mutations in several enzymes of this metabolic pathway are associated with devastating inborn errors of metabolism, resulting in severe methylmalonic and propionic acidemias. Beyond these rare diseases, however, the broader pathological significance of propionate metabolism and its metabolites has been largely overlooked. Here, we summarize earlier studies and new evidence that the alteration of this pathway and associated metabolites are involved in the development of various metabolic diseases and link aging to cancer progression and metastasis.

Keywords:  BCAA metabolism; BCAAs; MMA; aging; branched-chain amino acids; cancer metabolism; metabolic disorders; methylmalonic acid; methylmalonyl-CoA; propionate; propionyl-CoA

DOI:  https://doi.org/10.1016/j.cmet.2025.01.005
bioRxiv. 2025 Jan 24. pii: 2025.01.20.633942. [Epub ahead of print]

Protein corona formed on lipid nanoparticles compromises delivery efficiency of mRNA cargo.

Elizabeth Voke, Mariah Arral, Henry J Squire, Teng-Jui Lin, Roxana Coreas, Alison Lui, Anthony T Iavarone, Rebecca L Pinals, Kathryn A Whitehead, Markita Landry.

Lipid nanoparticles (LNPs) are the most clinically advanced nonviral RNA-delivery vehicles, though challenges remain in fully understanding how LNPs interact with biological systems. In vivo , proteins form an associated corona on LNPs that redefines their physicochemical properties and influences delivery outcomes. Despite its importance, the LNP protein corona is challenging to study owing to the technical difficulty of selectively recovering soft nanoparticles from biological samples. Herein, we developed a quantitative, label-free mass spectrometry-based proteomics approach to characterize the protein corona on LNPs. Critically, this protein corona isolation workflow avoids artifacts introduced by the presence of endogenous nanoparticles in human biofluids. We applied continuous density gradient ultracentrifugation for protein-LNP complex isolation, with mass spectrometry for protein identification normalized to protein composition in the biofluid alone. With this approach, we quantify proteins consistently enriched in the LNP corona including vitronectin, C-reactive protein, and alpha-2-macroglobulin. We explore the impact of these corona proteins on cell uptake and mRNA expression in HepG2 human liver cells, and find that, surprisingly, increased levels of cell uptake do not correlate with increased mRNA expression in part likely due to protein corona-induced lysosomal trafficking of LNPs. Our results underscore the need to consider the protein corona in the design of LNP-based therapeutics.
Abstract Figure:

DOI: https://doi.org/10.1101/2025.01.20.633942
Cell Metab. 2025 Jan 29. pii: S1550-4131(24)00491-1. [Epub ahead of print]

Lactate homeostasis is maintained through regulation of glycolysis and lipolysis.

Won Dong Lee, Daniel R Weilandt, Lingfan Liang, Michael R MacArthur, Natasha Jaiswal, Olivia Ong, Charlotte G Mann, Qingwei Chu, Craig J Hunter, Rolf-Peter Ryseck, Wenyun Lu, Anna M Oschmann, Alexis J Cowan, Tara A TeSlaa, Caroline R Bartman, Cholsoon Jang, Joseph A Baur, Paul M Titchenell, Joshua D Rabinowitz.

  Lactate is among the highest flux circulating metabolites. It is made by glycolysis and cleared by both tricarboxylic acid (TCA) cycle oxidation and gluconeogenesis. Severe lactate elevations are life-threatening, and modest elevations predict future diabetes. How lactate homeostasis is maintained, however, remains poorly understood. Here, we identify, in mice, homeostatic circuits regulating lactate production and consumption. Insulin induces lactate production by upregulating glycolysis. We find that hyperlactatemia inhibits insulin-induced glycolysis, thereby suppressing excess lactate production. Unexpectedly, insulin also promotes lactate TCA cycle oxidation. The mechanism involves lowering circulating fatty acids, which compete with lactate for mitochondrial oxidation. Similarly, lactate can promote its own consumption by lowering circulating fatty acids via the adipocyte-expressed G-protein-coupled receptor hydroxycarboxylic acid receptor 1 (HCAR1). Quantitative modeling suggests that these mechanisms suffice to produce lactate homeostasis, with robustness to noise and perturbation of individual regulatory mechanisms. Thus, through regulation of glycolysis and lipolysis, lactate homeostasis is maintained.

Keywords:  HCAR1 signaling; TCA cycle; competitive catabolism; diabetes mellitus; insulin resistance; insulin signaling; lactate metabolism; metabolic flux; metabolic homeostasis; quantitative modeling

DOI:  https://doi.org/10.1016/j.cmet.2024.12.009
bioRxiv. 2025 Jan 22. pii: 2025.01.22.634160. [Epub ahead of print]

Metabolomics biomarkers of frailty: a longitudinal study of aging female and male mice.

Dantong Zhu, Judy Z Wu, Patrick Griffin, Brady A Samuelson, David A Sinclair, Alice E Kane.

Frailty is an age-related geriatric syndrome, for which the mechanisms remain largely unknown. We performed a longitudinal study of aging female (n = 40) and male (n = 47) C57BL/6NIA mice, measured frailty index and derived metabolomics data from plasma samples. We identify differentially abundant metabolites related to aging, determine frailty related metabolites via a machine learning approach, and generate a union set of frailty features, both in the whole cohort and in sex-stratified subgroups. Using the features, we perform an association study and build a metabolomics-based frailty clock. We find that frailty related metabolites are enriched for amino acid metabolism and metabolism of cofactors and vitamins, include ergothioneine, tryptophan, and alpha-ketoglutarate, and present sex dimorphism. We identify B vitamin metabolism related flavin adenine dinucleotide and pyridoxate as female-specific frailty biomarkers, and lipid metabolism related sphingomyelins, glycerophosphoethanolamine and glycerophosphocholine as male-specific frailty biomarkers. These associations are confirmed in a validation cohort, with ergothioneine and perfluorooctanesulfonate identified as robust frailty biomarkers. In summary, our results identify sex-specific metabolite biomarkers of frailty in aging, and shed light on potential mechanisms involved in frailty.

DOI: https://doi.org/10.1101/2025.01.22.634160
J Chromatogr A. 2025 Jan 31. pii: S0021-9673(25)00091-3. [Epub ahead of print]1745 465742

Fast and comprehensive lipidomic analysis using supercritical fluid chromatography coupled with low and high resolution mass spectrometry.

Michaela Chocholoušková, Federico Torta.

  Despite advances in the last few years, the use of supercritical fluid chromatography (SFC) in combination with mass spectrometry (MS) for lipidomic analysis has not reached the popularity of LC-MS. However, SFC presents clear advantages that can be exploited, such as fast, reproducible and class-based separations including nonpolar lipid classes, such as cholesterol esters, triacylglycerols, diacylglycerols, monoacylglycerols and cholesterol. In this study we show how SFC can be used for comprehensive lipidomic analyses after optimization of parameters such as back-pressure regulator (BPR), column temperature or overfeed volume of injection. We also compare the performances of triple quadrupole (QqQ) and quadrupole time-of-flight (QTOF) mass spectrometers coupled to SFC in terms of qualitative and quantitative analyses.

Keywords:  High Resolution Mass Spectrometry; Lipidomics; Low resolution mass spectrometry; Supercritical fluid chromatography

DOI:  https://doi.org/10.1016/j.chroma.2025.465742
bioRxiv. 2025 Jan 21. pii: 2025.01.16.633410. [Epub ahead of print]

ADAR1 Regulates Lipid Remodeling through MDM2 to Dictate Ferroptosis Sensitivity.

Che-Pei Kung, Nick D Terzich, Ma Xenia G Ilagen, Michael J Prinsen, Madhurima Kaushal, Raleigh D Kladney, Jade H Weber, Alex R Mabry, Luisangely Soto Torres, Emily R Bramel, Eric C Freeman, Thwisha Sabloak, Kyle A Cottrell, Sua Ryu, William M Weber, Leonard Maggi, Leah P Shriver, Gary J Patti, Jason D Weber.

Triple-negative breast cancer (TNBC), lacking expression of estrogen, progesterone, and HER2 receptors, is aggressive and lacks targeted treatment options. An RNA editing enzyme, adenosine deaminase acting on RNA 1 (ADAR1), has been shown to play important roles in TNBC tumorigenesis. We posit that ADAR1 functions as a homeostatic factor protecting TNBC from internal and external pressure, including metabolic stress. We tested the hypothesis that the iron- dependent cell death pathway, ferroptosis, is a ADAR1-protected metabolic vulnerability in TNBC by showing that ADAR1 knockdown sensitizes TNBC cells to GPX4 inhibitors. By performing single-reaction monitoring-based liquid chromatography coupled to mass spectrometry (LC-MS) to measure intracellular lipid contents, we showed that ADAR1 loss increased the abundance of polyunsaturated fatty acid phospholipids (PUFA-PL), of which peroxidation is the primary driver of ferroptosis. Transcriptomic analyses led to the discovery of the proto-oncogene MDM2 contributing to the lipid remodeling in TNBC upon ADAR1 loss. A phenotypic drug screen using a ferroptosis-focused library was performed to identify FDA- approved cobimetinib as a drug-repurposing candidate to synergize with ADAR1 loss to suppress TNBC tumorigenesis. By demonstrating that ADAR1 regulates the metabolic fitness of TNBC through desensitizing ferroptosis, we aim to leverage this metabolic vulnerability to inform basic, pre-clinical, and clinical studies to develop novel therapeutic strategies for TNBC.

DOI: https://doi.org/10.1101/2025.01.16.633410
J Pharm Biomed Anal. 2025 Feb 04. pii: S0731-7085(25)00078-0. [Epub ahead of print]258 116737

Characterization of trimethylamine metabolic pathways using pseudo-targeted metabolomics.

Xin-Nan Wang, Jian-Qun Liu, Wen-Liang Ji, Zong-Li Huo, Li-Fang Liu, Jia-Yi Zheng.

  Trimethylamine (TMA) metabolism comprises choline-containing compounds' metabolization, TMA production and trimethylamine N-oxide (TMAO) generation. However, the presence of numerous compounds in the carnitine and phosphatidylcholine (PC) pool compositions complicates profiling work significantly. This study is aimed at developing an efficient method for profiling TMA metabolic pathways, including quantifying known compounds and semi-quantifying the differential metabolites in the carnitine and PC pool compositions. Pseudo-targeted metabolomics is applicable for characterization. Firstly, multivariate statistics were performed to identify valuable metabolites (variable importance in the projection ＞1) from quality control biological samples. Given that TMA metabolism involved in host-gut microbiota interaction, co-metabolites were defined as the intersections of valuable metabolites from different biological samples (serum, liver, and intestinal contents) and further screened. Finally, alterations in TMA metabolism were observed in dextran sulfate sodium-induced colitis, with semi-quantitative analysis for excavated co-metabolites including 11 PCs, 6 lyso-phosphatidylcholines, and 2 acylcarnitines and quantitative analysis for 10 known metabolites. The findings revealed increased TMA production and accumulation of choline-containing compounds in the gut during ulcerative colitis exacerbation. Correspondingly, the circulating level of TMAO was elevated in the colitis group. A comprehensive understanding of TMA metabolism can contribute to disease differential diagnoses and potential mechanism studies.

Keywords:  Host-gut microbiota interaction; Pseudo-targeted metabolomics; Trimethylamine; Ultra-high-performance liquid chromatography-mass spectrometry

DOI:  https://doi.org/10.1016/j.jpba.2025.116737
EMBO J. 2025 Feb 07.

Arginine: at the crossroads of nitrogen metabolism.

Tak Shun Fung, Keun Woo Ryu, Craig B Thompson.

  L-arginine is the most nitrogen-rich amino acid, acting as a key precursor for the synthesis of nitrogen-containing metabolites and an essential intermediate in the clearance of excess nitrogen. Arginine's side chain possesses a guanidino group which has unique biochemical properties, and plays a primary role in nitrogen excretion (urea), cellular signaling (nitric oxide) and energy buffering (phosphocreatine). The post-translational modification of protein-incorporated arginine by guanidino-group methylation also contributes to epigenetic gene control. Most human cells do not synthesize sufficient arginine to meet demand and are dependent on exogenous arginine. Thus, dietary arginine plays an important role in maintaining health, particularly upon physiologic stress. How cells adapt to changes in extracellular arginine availability is unclear, mostly because nearly all tissue culture media are supplemented with supraphysiologic levels of arginine. Evidence is emerging that arginine-deficiency can influence disease progression. Here, we review new insights into the importance of arginine as a metabolite, emphasizing the central role of mitochondria in arginine synthesis/catabolism and the recent discovery that arginine can act as a signaling molecule regulating gene expression and organelle dynamics.

Keywords:  Arginine Deficiency; Arginine Metabolism; Metabolite Signaling; Mitochondria; Protein Synthesis

DOI:  https://doi.org/10.1038/s44318-025-00379-3