bims-mascan Biomed News
on Mass spectrometry in cancer research
Issue of 2025–05–11
eighteen papers selected by
Giovanny Rodríguez Blanco, Uniklinikum Graz
  1. Quality Control in the Mass Spectrometry Proteomics Core: A Practical Primer.
  2. A Streamlined Approach for Mass Spectrometry-Based Proteomics Using Selected Tissue Regions.
  3. Data Independent Acquisition to Inform the Development of Targeted Proteomics Assays Using a Triple Quadrupole Mass Spectrometer.
  4. Quantitative Label-Free Single-Cell Proteomics on the Orbitrap Astral MS.
  5. MetCohort: Precise Feature Detection and Correspondence for Untargeted Metabolomics in Large-Scale Cohort Studies.
  6. Label-free quantitative shotgun analysis of bis(monoacylglycero)phosphate lipids.
  7. LC-MS System for Collecting Time-Resolved Metabolomics Data of Cultured Cells.
  8. Revealing Acyl Chain Selectivity of Cis-to-Trans Isomerase through Profiling of C═C Geometry and Location Isomers of Bacterial Lipids.
  9. Terminomics for plant protease substrate discovery: Achievements, challenges and new opportunities.
  10. Leveraging pretrained deep protein language model to predict peptide collision cross section.
  11. Quantification of Epigenetic DNA and RNA Modifications by UHPLC-MS/MS Technologies: New Concepts and New Improvements for the Special Collections.
  12. Mapping the Edges of Mass Spectral Prediction: Evaluation of Machine Learning EIMS Prediction for Xeno Amino Acids.
  13. Enzymes Drive Glutathione Shunt to Explain Oxidative State Using an In-Parallel Multi-Omic Method.
  14. The Curated Cancer Cell Atlas provides a comprehensive characterization of tumors at single-cell resolution.
  15. Two-Step Peptide Solubilization Increases Coverage in High-Sensitivity NanoHILIC/MS/MS-Based Proteomics.
  16. Cellular metabolomics study in colorectal cancer cells and media following treatment with 5-fluorouracil by gas chromatography-tandem mass spectrometry.
  17. Activation of lysosomal iron triggers ferroptosis in cancer.
  18. Simultaneous profiling of mercapturic acids, glucuronic acids, and sulfates in human urine.
  1. J Biomol Tech. 2024 Sep 30. pii: 3fc1f5fe.42308a9a. [Epub ahead of print]35(3):
    Quality Control in the Mass Spectrometry Proteomics Core: A Practical Primer.
    Benjamin A Neely, Yasset Perez-Riverol, Magnus Palmblad.
      The past decade has seen widespread advances in quality control (QC) materials and software tools focused specifically on mass spectrometry-based proteomics, yet the rate of adoption is inconsistent. Despite the fundamental importance of QC, it typically falls behind learning new techniques, instruments, or software. Considering how important QC is in a core setting where data is generated for non-mass spectrometry experts and confidence in delivered results is paramount, we have created this quick-start guide focusing on off-the-shelf QC materials and relatively easy-to-use QC software. We hope that by providing a background on the different levels of QC, different materials and their uses, describing QC design options, and highlighting some current QC software, implementing QC in a core setting will be easier than ever. There continues to be development in each of these areas (such as new materials and software), and the current generation of QC for mass spectrometry-based proteomics is more than capable of conveying confidence in results as well as minimizing laboratory downtime by guiding experimental, technical, and analytical troubleshooting from sample to results.
    Keywords:  best practices; materials; proteomics; quality control; software; standards
    DOI:  https://doi.org/10.7171/3fc1f5fe.42308a9a
  2. J Vis Exp. 2025 Apr 18.
    A Streamlined Approach for Mass Spectrometry-Based Proteomics Using Selected Tissue Regions.
    Dongyoon Shin, Dayeon Lee, Young June Jeon, Kyoungbun Lee, Youngsoo Kim, Junho Park.
      Mass spectrometry (MS)-based proteomics enables comprehensive proteome analysis across a wide range of biological samples, including cells, tissues, and body fluids. Formalin-fixed, paraffin-embedded (FFPE) tissue sections, commonly used for long-term archiving, have emerged as valuable resources for proteomic studies. Beyond their storage benefits, researchers can isolate regions of interest (ROIs) from normal tissue regions through collaborative efforts with pathologists. Despite this potential, a streamlined approach for proteomic experiments encompassing ROI isolation, proteomic sample preparation, and MS analysis remains lacking. In this protocol, an integrated workflow that combines macrodissection of ROIs, suspension trapping-based sample preparation, and high-throughput MS analysis is presented. Through this approach, the ROIs of patients' FFPE tissues, consisting of benign serous cystic neoplasms (SCN) and precancerous intraductal papillary mucinous neoplasms (IPMN) diagnosed by pathologists, were macrodissected, collected, and analyzed, resulting in high proteome coverage. Furthermore, molecular differences between the two distinct pancreatic cystic neoplasms were successfully identified, thus demonstrating the applicability of this approach for advancing proteomic research with FFPE tissues.
    DOI:  https://doi.org/10.3791/68076
  3. J Proteome Res. 2025 May 06.
    Data Independent Acquisition to Inform the Development of Targeted Proteomics Assays Using a Triple Quadrupole Mass Spectrometer.
    Deanna L Plubell, Eric Huang, Sandra E Spencer, Kathleen L Poston, Thomas J Montine, Michael J MacCoss.
      Mass spectrometry based targeted proteomics methods provide a sensitive and high-throughput analysis of selected proteins. To develop a targeted bottom-up proteomics assay, peptides must be evaluated as proxies for the measurement of a protein or proteoform in a biological matrix. Candidate peptide selection typically relies on predetermined biochemical properties, data from semistochastic sampling, or empirical measurements. These strategies require extensive testing and method refinement due to the difficulties associated with prediction of the peptide response in the biological matrix of interest. Gas-phase fractionated (GPF) narrow window data-independent acquisition (DIA) aids in the development of reproducible selected reaction monitoring (SRM) assays by providing matrix-specific information on peptide detectability and quantification by mass spectrometry. To demonstrate the suitability of DIA data for selecting peptide targets, we reimplement a portion of an existing assay to measure 98 Alzheimer's disease proteins in cerebrospinal fluid (CSF). Peptides were selected from GPF-DIA based on signal intensity and reproducibility. The resulting SRM assay exhibits a quantitative precision similar to that of published data, despite the inclusion of different peptides between the assays. This workflow enables development of new assays without additional upfront data acquisition, demonstrated here through generation of a separate assay for an unrelated set of proteins in CSF from the same data set.
    Keywords:  Data-independent acquisition; mass spectrometry; proteomics; selected reaction monitoring; targeted assay
    DOI:  https://doi.org/10.1021/acs.jproteome.5c00016
  4. Mol Cell Proteomics. 2025 May 05. pii: S1535-9476(25)00080-5. [Epub ahead of print] 100982
    Quantitative Label-Free Single-Cell Proteomics on the Orbitrap Astral MS.
    Valdemaras Petrosius, Pedro Aragon-Fernandez, Tabiwang N Arrey, Jakob Woessman, Nil Üresin, Bauke de Boer, Jinyu Su, Benjamin Furtwängler, Hamish Stewart, Eduard Denisov, Johannes Petzoldt, Amelia C Peterson, Christian Hock, Eugen Damoc, Alexander Makarov, Vlad Zabrouskov, Bo T Porse, Erwin M Schoof.
      Single-cell proteomics by mass spectrometry (scp-MS) holds the potential to provide unprecedented insights into molecular features directly linked to the cellular phenotype, while deconvoluting complex organisms into their basic building blocks. Tailored sample preparation that maximizes the extracted amount of material that is introduced into the mass spectrometer has rapidly propelled the field forward. However, the measured signal is still at the lower edge of detection approaching the sensitivity boundary of current instrumentation. Here, we investigate the capacity of the enhanced sensitivity of the Orbitrap Astral mass spectrometer to facilitate deeper proteome profiles from low-input to single-cell samples. We carry out a comprehensive data acquisition method survey to pinpoint which parameters provide most sensitivity. Furthermore, we explore the quantitative accuracy of the obtained measurements to ensure that the obtained abundances are in line with expected ground truth values. We culminate our technical exploration by generating small datasets from two cultured cell lines and a primary bone marrow sample, to showcase obtainable proteome coverage differences from different source materials. Finally, as a proof of concept we explore protein covariation to showcase how information on known protein complexes is captured inherently in our scp-MS data.
    DOI:  https://doi.org/10.1016/j.mcpro.2025.100982
  5. Anal Chem. 2025 May 06.
    MetCohort: Precise Feature Detection and Correspondence for Untargeted Metabolomics in Large-Scale Cohort Studies.
    Jun Yang, Pengwei Guan, Di Yu, Qi Li, Xiaolin Wang, Guowang Xu, Xinyu Liu.
      Liquid chromatography-high-resolution mass spectrometry (LC-HRMS)-based untargeted metabolomics is becoming increasingly popular in large-scale cohort studies. However, its data processing is complex and challenging. We present MetCohort, a computational tool for performing metabolomics raw data alignment for large-scale sample analysis, and accurate feature detection and quantification. By combining chromatogram profile alignment and local anchor matching with an outlier removal algorithm, the retention times of the raw data were aligned. With aligned retention times across all the samples, regions of interest (ROIs) are detected and stacked among samples to form a two-dimensional (2D) ROI-matrix. This 2D ROI-matrix, resembling an image with rows representing samples and columns corresponding to the time, allows the application of image processing techniques. Since the peaks are already aligned in the alignment step, features can be accurately detected and quantified with automatic correspondence of all the samples. Based on the 2D image processing technique, holistic scale feature detection is performed, which not only significantly decreases the number of false-positives and improves the detection of low-intensity compounds, but also avoids tricky peak matching and quantification uncertainty. Overall, MetCohort has potential to enhance the accuracy and efficiency of data processing in large-scale LC-HRMS.
    DOI:  https://doi.org/10.1021/acs.analchem.4c04906
  6. Anal Bioanal Chem. 2025 May 09.
    Label-free quantitative shotgun analysis of bis(monoacylglycero)phosphate lipids.
    Lian Y Wang, Rico J E Derks, Kevin A J Brewster, Danilo Prtvar, Sabina Tahirovic, Stefan A Berghoff, Martin Giera.
      Interest in the role of bis(monoacylglycero)phosphate (BMP) lipids in lysosomal function has significantly grown in recent years. Emerging evidence highlights BMPs as critical players not only in Niemann-Pick disease type C (NPC) but also in other pathologies such as neurodegeneration, cardiovascular diseases, and cancers. However, the selective analysis of BMPs is significantly hindered by isomeric phosphatidylglycerol (PG) lipids. While this can be addressed by chromatographic separation, it poses a significant challenge for shotgun lipidomics approaches. Here, we present a shotgun lipidomics strategy to detect and separate BMPs from PGs using differential fragmentation of sodiated ions. This approach, including isotope correction, is integrated into an existing quantitative shotgun lipidomics workflow (Lipidyzer combined with Shotgun Lipidomics Assistant software) that simultaneously quantifies >1400 lipids. Validation using K-562 cell extracts demonstrated acceptable linearity, trueness, repeatability, and a limit of quantification of 0.12 µM, confirming robust analytical performance. Finally, characteristic accumulation of BMP lipids is shown in bone marrow-derived macrophages from NPC mice, demonstrating its applicability. Our method presents a quantitative, selective, rapid, and robust solution for shotgun-based BMP analysis without the need for extensive chromatographic separation or derivatization. The integration of BMP lipid detection into the Lipidyzer platform, alongside the recently launched iSODA data visualization tool, empowers chemists and biologists to gain deeper insights into BMP lipid biology.
    Keywords:  BMP; Flow injection; Label free; Mass spectrometry; Shotgun lipidomics
    DOI:  https://doi.org/10.1007/s00216-025-05890-4
  7. Anal Chem. 2025 May 08.
    LC-MS System for Collecting Time-Resolved Metabolomics Data of Cultured Cells.
    Carly C Y Chan, Ryan A Groves, Raied Aburashed, Thomas Rydzak, Ian A Lewis.
      Temporal metabolic dynamics are difficult to capture but are critical to understanding biology. We developed an automated liquid chromatography-mass spectrometry system that collects time-resolved metabolomics data from cultured cells, enabling sub-minute sequential sampling, broad metabolite coverage, robust metabolite identification, and parallel monitoring of up to 72 experimental conditions. Using this system, we identified temporal metabolic phenotypes of Escherichia coli and Proteus mirabilis that could not be captured from single time points.
    DOI:  https://doi.org/10.1021/acs.analchem.4c06697
  8. Anal Chem. 2025 May 07.
    Revealing Acyl Chain Selectivity of Cis-to-Trans Isomerase through Profiling of C═C Geometry and Location Isomers of Bacterial Lipids.
    Hengxue Shi, Huijiao Bai, Haiteng Deng, Yu Xia.
      Bacteria adapt to environmental stress by modifying their membrane lipid structures, including the C═C geometry. Profiling of bacterial lipids with accurate C═C geometry assignment is challenging due to the lack of standards and interference from C═C location isomers. By leveraging two radical reactions: thiyl radical-catalyzed C═C isomerization and the Paternò-Büchi (PB) reaction, we developed an analytical workflow to profile C═C geometric and location isomers in bacterial lipidomes. The high yield (∼80%) of cis (Z)-to-trans (E) C═C isomerization catalyzed by thiyl radicals allows for on-demand synthesis of commercially unavailable lipid C═C geometric isomers. By comparing the retention behavior of Z vs E isomers from reversed-phase liquid chromatography-mass spectrometry (RPLC-MS), we can determine C═C geometry at sub-nM levels. The location of C═C can be further obtained by conducting an online acetone PB reaction after RPLC separation. Applying this workflow to Pseudomonas putida, we profiled 60 lipid species across six subclasses, including the rarely reported glucosaminyl phosphatidylglycerol. We found that both Z and E isomers were present in bacterial lipids, however, with an increase in E isomers after toluene exposure, which correlated with an upregulation of cis-to-trans isomerase (Cti). Our workflow further revealed the chain selectivity of Cti, with a preference for C16:1(n-7Z) > C18:1(n-7Z) > C18:1(n-9Z). This finding provides valuable insights into the dynamics of lipid metabolism during bacterial stress responses.
    DOI:  https://doi.org/10.1021/acs.analchem.5c00675
  9. J Exp Bot. 2025 May 04. pii: eraf173. [Epub ahead of print]
    Terminomics for plant protease substrate discovery: Achievements, challenges and new opportunities.
    Melissa Mantz, Paula Dewes, Pitter F Huesgen.
      Plants contain hundreds of proteases that are involved in the regulation of virtually all cellular processes. Some proteases act as molecular shredders, resulting in degradation of their substrates. Others act more like scissors, cutting substrate proteins in limited manner at specific sites to alter their activity, location and function. Such tailored proteoforms share their sequence with the precursor form and sometimes only differ by the new, proteolytically modified polypeptide termini. Identification of protein termini is mandatory for unambiguous identification, but challenging in standard mass spectrometry-based proteomics. Over the last two decades, various methods for the enrichment of N- and C-terminal peptides have been developed to enable proteome-wide characterization. Here we briefly introduce major approaches to protein termini enrichment and review current applications for plant protease substrate identification and profiling of proteolytic cleavage events in vivo. We highlight both successes and limitations and discuss current improvements in sample preparation, data acquisition, mass spectrometry instrumentation and data analysis that promise to increase sensitivity, robustness and ultimately utility of termini-centric proteomics.
    Keywords:  degradomics; plant proteases; protease substrate; protein N-termini; terminomics
    DOI:  https://doi.org/10.1093/jxb/eraf173
  10. Commun Chem. 2025 May 06. 8(1): 137
    Leveraging pretrained deep protein language model to predict peptide collision cross section.
    Ayano Nakai-Kasai, Kosuke Ogata, Yasushi Ishihama, Toshiyuki Tanaka.
      Collision cross section (CCS) of peptide ions provides an important separation dimension in liquid chromatography/tandem mass spectrometry-based proteomics that incorporates ion mobility spectrometry (IMS), and its accurate prediction is the basis for advanced proteomics workflows. This paper describes experimental data and a prediction model for challenging CCS prediction tasks including longer peptides that tend to have higher charge states. The proposed model is based on a pretrained deep protein language model. While the conventional prediction model requires training from scratch, the proposed model enables training with less amount of time owing to the use of the pretrained model as a feature extractor. Results of experiments with the novel experimental data show that the proposed model succeeds in drastically reducing the training time while maintaining the same or even better prediction performance compared with the conventional method. Our approach presents the possibility of prediction on the basis of "greener" manner training of various peptide properties in proteomic liquid chromatography/tandem mass spectrometry experiments.
    DOI:  https://doi.org/10.1038/s42004-025-01540-z
  11. J Sep Sci. 2025 May;48(5): e70159
    Quantification of Epigenetic DNA and RNA Modifications by UHPLC-MS/MS Technologies: New Concepts and New Improvements for the Special Collections.
    Rui Zhang, Hailong Liu, Biao Bai, Hailin Wang.
      Dynamic and reversible DNA and RNA modifications are essential for cell differentiation and development. Aberrant epigenetic modifications are closely associated with the occurrence and progression of diseases, serving as potential markers for cancer diagnosis and prognosis. Ultra-high-performance liquid chromatography coupled with tandem mass spectrometry (UHPLC-MS/MS) offers distinct advantages in the qualitative and quantitative analysis of various modifications due to its sensitivity, specificity, and accuracy. This review provides a comprehensive overview of the current knowledge regarding the liquid chromatography-mass spectrometry (LC-MS) analysis of DNA and RNA modifications, including analytical procedures, advancements, and biological applications, with a focus on tracing the source of (N6-2'-deoxy-adenosine) 6mdA in eukaryotes. Additionally, we examine the integration of UHPLC-MS/MS with other separation techniques to achieve accurate quantification of modifications in specific regions, certain fragments, and free nucleosides.
    DOI:  https://doi.org/10.1002/jssc.70159
  12. Anal Chem. 2025 May 07.
    Mapping the Edges of Mass Spectral Prediction: Evaluation of Machine Learning EIMS Prediction for Xeno Amino Acids.
    Sean M Brown, Evan Allgair, Robin Kryštůfek.
      Mass spectrometry is one of the most effective analytical methods for unknown compound identification. By comparing observed m/z spectra with a database of experimentally determined spectra, this process identifies compound(s) in any given sample. Unknown sample identification is thus limited to whatever has been experimentally determined. To address the reliance on experimentally determined signatures, multiple state-of-the-art MS spectra prediction algorithms have been developed within the past half decade. Here we evaluate the accuracy of the NEIMS spectral prediction algorithm. We focus our analyses on monosubstituted α-amino acids given their significance as important targets for astrobiology, synthetic biology, and diverse biomedical applications. Our general intent is to inform those using generated spectra for detection of unknown biomolecules. We find predicted spectra are inaccurate for amino acids beyond the algorithms training data. Interestingly, these inaccuracies are not explained by physicochemical differences or the derivatization state of the amino acids measured. We thus highlight the need to improve both current machine learning based approaches and further optimization of ab initio spectral prediction algorithms so as to expand databases for structures beyond what is currently experimentally possible, even including theoretical molecules.
    DOI:  https://doi.org/10.1021/acs.analchem.5c00286
  13. Int J Mol Sci. 2025 Apr 11. pii: 3632. [Epub ahead of print]26(8):
    Enzymes Drive Glutathione Shunt to Explain Oxidative State Using an In-Parallel Multi-Omic Method.
    Valerie C Wasinger, Sonia Bustamante, Nashwa Najib, Ashish Diwan, Tharusha Jayasena, Nahian S Chowdhury, Julia Beretov, Siobhan Schabrun.
      The glutathione shunt is one of the most important contributors to the cellular redox state, with implications across cancer, chronic diseases, diseases of ageing, and autoimmune diseases, including inflammatory bowel disease (IBD). Traditionally, the redox state is gauged by the ratio of the surrogate metabolites GSH and GSSG. However, this presents methodological challenges and offers a constrained illustration of metabolites without a systems-level understanding of redox dynamics, failing to elucidate variations across an entire biochemical network. Targeted proteomics can fill this void. Here, we describe an in-parallel metabolomic and proteomic targeted method to encompass measurements directly related to the shunt. Samples are simultaneously prepared to extract the substrate building blocks, cysteine, cystine, methionine, glutamic acid, and kynurenine; and the proteins, SLC7A11 (xCT), Glutamate Cysteine Ligase (GSH1), Glutathione Synthetase (GSH2), Glutathione Peroxidase (GPx), and Glutathione Reductase (GSHR) for targeted mass spectrometry. We demonstrate the method by targeted analysis of proteins in plasma, serum, nasal swab, and saliva and apply the multi-omic method to assess changes in the glutathione shunt in the serum of patients diagnosed with IBD. This allows for a broader narrative to establish context at which the glutathione shunt is operating.
    Keywords:  GPx; GSH; GSSG; IBD; SLCA7A1; biomarker; glutathione shunt; liquid biopsy
    DOI:  https://doi.org/10.3390/ijms26083632
  14. Nat Cancer. 2025 May 08.
    The Curated Cancer Cell Atlas provides a comprehensive characterization of tumors at single-cell resolution.
    Michael Tyler, Avishai Gavish, Chaya Barbolin, Roi Tschernichovsky, Rouven Hoefflin, Michael Mints, Sidharth V Puram, Itay Tirosh.
      Recent years have seen a rapid proliferation of single-cell cancer studies, yet most of these studies profiled few tumors, limiting their statistical power. Combining data and results across studies holds great promise but also involves various challenges. We recently began to address these challenges by curating a large collection of cancer single-cell RNA-sequencing datasets, leveraging it for systematic analyses of tumor heterogeneity. Here we greatly extend this repository to 124 datasets for over 40 cancer types, together comprising 2,836 samples, with improved data annotations, visualizations and exploration. Using this vast cohort, we generate an updated map of recurrent expression programs in malignant cells and systematically quantify context-dependent gene expression and cell-cycle patterns across cell types and cancer types. These data, annotations and analysis results are all freely available for exploration and download through the Curated Cancer Cell Atlas, a central community resource that opens new avenues in cancer research.
    DOI:  https://doi.org/10.1038/s43018-025-00957-8
  15. Anal Chem. 2025 May 06.
    Two-Step Peptide Solubilization Increases Coverage in High-Sensitivity NanoHILIC/MS/MS-Based Proteomics.
    Koshin Akamatsu, Eisuke Kanao, Ayana Tomioka, Yasushi Ishihama.
      Nanoscale hydrophilic-interaction chromatography coupled with tandem mass spectrometry (nanoHILIC/MS/MS) is a promising alternative to reversed-phase liquid chromatography for proteomics, but its application is limited by the poor solubility of peptides in organic solvent-rich sample solutions. To overcome this issue, we have developed a two-step solubilization method, in which peptides are first solubilized in a solvent with an optimal acetonitrile (ACN) concentration of 25% and then diluted into a high ACN concentration solution of 95%. This procedure increases the peptide solubility without compromising compatibility with nanoHILIC/MS/MS. Compared to direct solubilization in 95% ACN, this approach increased the intensity of 82.8% of commonly quantified peptides in nanoHILIC/MS/MS, with an average intensity gain of 20.9%. Furthermore, nanoHILIC/MS/MS with this two-step solubilization outperformed nanoRPLC/MS/MS, identifying 8.47 times more peptides and 3.54 times more protein groups from 2.5 ng of tryptic peptides extracted from HeLa cells. The high sensitivity of nanoHILIC/MS/MS can be attributed to the enhanced loading of peptides as a result of the two-step solubilization, together with superior ESI efficiency arising from the use of the ACN-rich mobile phase. This high-sensitivity proteomics system is a promising platform for clinical and single-cell applications.
    DOI:  https://doi.org/10.1021/acs.analchem.5c00011
  16. Metabolomics. 2025 May 07. 21(3): 62
    Cellular metabolomics study in colorectal cancer cells and media following treatment with 5-fluorouracil by gas chromatography-tandem mass spectrometry.
    Songjin Oh, Hyun Bo Sim, Hyeongyeong Kim, Seul-Ki Mun, Moongi Ji, Byeongchan Choi, Doo-Young Kim, Jong-Jin Kim, Man-Jeong Paik.
       BACKGROUND: Metabolic reprogramming is a distinctive characteristic of colorectal cancer (CRC) which provides energy and nutrients for rapid proliferation. Although numerous studies have explored the rewired metabolism of CRC, the metabolic alterations occurring in CRC when the cell cycle is arrested by treatment with 5-fluorouracil (5-FU), an anticancer drug that arrests the S phase, remain unclear.
    METHODS: A systematic profiling analysis was conducted as ethoxycarbonyl/methoxime/tert-butyldimethylsilyl derivatives using gas chromatography-tandem mass spectrometry in HT29 cells and media following 5-FU treatment in a concentration- and time-dependent manner.
    RESULTS: In HT29 cells of 24 h after 5-FU treatment (3-100 μM) and 48 h after 5-FU treatment (1-10 μM), six amino acids, including valine, leucine, isoleucine, serine, glycine, and alanine and two organic acids, including pyruvic acid and lactic acid, were significantly increased compared to the DMSO-treated group. However, 48 h after 5-FU treatment (30-100 μM) in HT29 cells, the levels of these metabolites decreased along with an approximately 50% reduction in viability, an increase in the level of reactive oxygen species, induction of cycle arrest in the G1 phase, and the induction of apoptosis. On the other hand, the levels of fatty acids showed a continuous increase in HT29 cells 48 h after 5-FU treatment (1-100 μM). In the media, the decreased availabilities in the cellular uptake of nutrient metabolites, including valine, leucine, isoleucine, serine, and glutamine, were observed at 48 h after 5-FU treatment in a dose-dependent manner.
    CONCLUSION: It is assumed that there is a possible shift in energy dependence from the tricarboxylic acid cycle to fatty acid metabolism. Thus, metabolic profiling analysis revealed altered energy metabolism in CRC cells following 5-FU treatment.
    Keywords:  5-Fluorouracil; Colorectal cancer; HT29 cells; Mass spectrometry; Metabolite profiling analysis; Metabolomics
    DOI:  https://doi.org/10.1007/s11306-025-02263-x
  17. Nature. 2025 May 07.
    Activation of lysosomal iron triggers ferroptosis in cancer.
    Tatiana Cañeque, Leeroy Baron, Sebastian Müller, Alanis Carmona, Ludovic Colombeau, Antoine Versini, Stéphanie Solier, Christine Gaillet, Fabien Sindikubwabo, Julio L Sampaio, Marie Sabatier, Eikan Mishima, Armel Picard-Bernes, Laurène Syx, Nicolas Servant, Bérangère Lombard, Damarys Loew, Jiashuo Zheng, Bettina Proneth, Leishemba K Thoidingjam, Laurence Grimaud, Cameron S Fraser, Krystina J Szylo, Emma Der Kazarian, Caroline Bonnet, Emmanuelle Charafe-Jauffret, Christophe Ginestier, Patricia Santofimia-Castaño, Matias Estaras, Nelson Dusetti, Juan Lucio Iovanna, Antonio Sa Cunha, Gabriella Pittau, Pascal Hammel, Dimitri Tzanis, Sylvie Bonvalot, Sarah Watson, Vincent Gandon, Aditya Upadhyay, Derek A Pratt, Florêncio Porto Freitas, José Pedro Friedmann Angeli, Brent R Stockwell, Marcus Conrad, Jessalyn M Ubellacker, Raphaël Rodriguez.
      Iron catalyses the oxidation of lipids in biological membranes and promotes a form of cell death called ferroptosis1. Defining where this chemistry occurs in the cell can inform the design of drugs capable of inducing or inhibiting ferroptosis in various disease-relevant settings. Genetic approaches have revealed suppressors of ferroptosis2-4; by contrast, small molecules can provide spatiotemporal control of the chemistry at work5. Here we show that the ferroptosis inhibitor liproxstatin-1 exerts cytoprotective effects by inactivating iron in lysosomes. We also show that the ferroptosis inducer RSL3 initiates membrane lipid oxidation in lysosomes. We designed a small-molecule activator of lysosomal iron-fentomycin-1-to induce the oxidative degradation of phospholipids and ultimately ferroptosis. Fentomycin-1 is able to kill iron-rich CD44high primary sarcoma and pancreatic ductal adenocarcinoma cells, which can promote metastasis and fuel drug tolerance. In such cells, iron regulates cell adaptation6,7 while conferring vulnerability to ferroptosis8,9. Sarcoma cells exposed to sublethal doses of fentomycin-1 acquire a ferroptosis-resistant cell state characterized by the downregulation of mesenchymal markers and the activation of a membrane-damage response. This phospholipid degrader can eradicate drug-tolerant persister cancer cells in vitro and reduces intranodal tumour growth in a mouse model of breast cancer metastasis. Together, these results show that control of iron reactivity confers therapeutic benefits, establish lysosomal iron as a druggable target and highlight the value of targeting cell states10.
    DOI:  https://doi.org/10.1038/s41586-025-08974-4
  18. Environ Int. 2025 May 04. pii: S0160-4120(25)00267-3. [Epub ahead of print]199 109516
    Simultaneous profiling of mercapturic acids, glucuronic acids, and sulfates in human urine.
    Jin Y Chen, Saurin R Sutaria, Zhengzhi Xie, Manjiri Kulkarni, Rachel J Keith, Aruni Bhatnagar, Clara G Sears, Pawel Lorkiewicz, Sanjay Srivastava.
      Humans are constantly exposed to both naturally-occurring and anthropogenic chemicals. Targeted mass spectrometry approaches are frequently used to measure a small panel of chemicals and their metabolites in environmental or biological matrices, but methods for comprehensive individual-level exposure assessment are limited. In this study, we applied an integrated library-guided analysis (ILGA) with ultraperformance liquid chromatography-quadrupole time-of-flight mass spectrometry (UPLC-QTOF/MS) to profile phase II metabolites, specifically mercapturic acids (MAs), glucuronic acids (GAs), and sulfates (SAs) in human urine samples (n = 844). We annotated 424 metabolites (146 MAs, 171 GAs, 107 SAs) by querying chromatographic features with in-house structural libraries, filtering against fragmentation patterns (common neutral loss and ion fragment), and comparing mass spectra with in-silico fragmentations and external spectral libraries. These metabolites were derived from over 200 putative parent compounds of exogenous and endogenous sources, such as dietary compounds, benzene/monocyclic substituted aromatics, pharmaceuticals, polycyclic aromatic hydrocarbons, bile acids/bile salts, and 4-hydroxyalkenals associated with lipid peroxidation process. Further, we performed statistical analyses on 214 metabolites found in more than 75% of samples to examine the association between metabolites and demographic characteristics using integrated network analysis, principal component analysis (PCA), and multivariable linear regression models. The network analysis revealed four distinct communities of 37 positively correlated metabolites, and the PCA (using the 37 metabolites) presented 4 principal components that meaningfully explained at least 80% of the variance in the data. The multivariable linear regression models showed some positive and negative associations between metabolite profiles and certain demographic variables (e.g., age, sex, race, education, income, and tobacco use).
    Keywords:  Endobiotics; Glucuronic acids; Integrated Library-Guided Analysis; LC-HRMS; Mercapturic acids; Sulfates; Xenobiotics
    DOI:  https://doi.org/10.1016/j.envint.2025.109516
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