bims-mascan 2025-05-25 papers

bims-mascan

Biomed News

on Mass spectrometry in cancer research

Issue of 2025–05–25
27 papers selected by
Giovanny Rodríguez Blanco, Uniklinikum Graz

Polyamine quantitation by LC-MS using isobutyl chloroformate derivatives.
MCQR: Enhancing the Processing and Analysis of Quantitative Proteomics Data by Incorporating Chromatography and Mass Spectrometry Information.
Data-Independent Acquisition-Based Quantitative Proteomics for Pairwise Comparison of Serum and Plasma.
Quality control in GC-MS analysis of amino acids in human urine and plasma: Possible implications for targeted and untargeted metabolomics.
Optimization of bottom-up proteomic sample preparation by design of experiments for absolute quantification of 257 proteins in human plasma using UPLC-MRM-MS.
Dynamic single-cell metabolomics reveals cell-cell interaction between tumor cells and macrophages.
LipidIN: a comprehensive repository for flash platform-independent annotation and reverse lipidomics.
Expanding the landscape of aging via orbitrap astral mass spectrometry and tandem mass tag integration.
Metabolomics biomarkers of frailty: a longitudinal study of aging female and male mice.
A Comprehensive Proteome of Human Corneal Epithelial Cells Constructed by Cross-platform DIA-Mass Spectrometry.
Lactate dehydrogenase A-coupled NAD+ regeneration is critical for acute myeloid leukemia cell survival.
A comparison of SWATH-MS methods for measurement of residual host cell proteins in adeno-associated virus preparations.
Technical recommendations for analyzing oxylipins by liquid chromatography-mass spectrometry.
From blood drops to biomarkers: a scoping review of microsampling in mass spectrometry-based proteomics.
S-adenosylmethionine metabolism shapes CD8+ T cell functions in colorectal cancer.
Protein digestion, peptide mass and peptide fragmentation with MZCal: A user-friendly phone-compatible application.
MultiStageSearch: An Iterative Workflow for Unbiased Taxonomic Analysis of Pathogens Using Proteogenomics.
Unravelling the Mechanism of Cisplatin Resistance in Triple-Negative Breast Cancer: Insights from Metabolomic Profiling via Mass Spectrometry Analysis.
Fatty acid desaturases link cell metabolism pathways to promote proliferation of Epstein-Barr virus-infected B cells.
Quantitative GC-NICI-MS and GC-NICI-MS/MS analysis by using isotopologs as internal standards: A tutorial review.
Fully Automated Deep Learning Enabled Miniature Mass Spectrometry System for Psychoactive Therapeutic Drug Monitoring.
Secreted phospholipase A2 regulates intercellular communications by coordinating extracellular phospholipid metabolism.
Unveiling the dark matter of the metabolome: A narrative review of bioinformatics tools for LC-HRMS-based compound annotation.
Extended coverage of human serum glycosphingolipidome by 4D-RP-LC TIMS-PASEF unravels association with Parkinson's disease.
A simple surrogate approach for the quantitation of C4 (7α-hydroxy-4-cholesten-3-one) in human serum via LC-MS/MS and its application in a clinical study.
Microbiome metabolism of dietary phytochemicals controls the anticancer activity of PI3K inhibitors.
Quantification of five intracellular and extracellular methionine pathway intermediates using stable isotope dilution UHPLC-MS/MS.

Methods Enzymol. 2025 ;pii: S0076-6879(25)00086-2. [Epub ahead of print]715 437-458

Polyamine quantitation by LC-MS using isobutyl chloroformate derivatives.

Christine Isaguirre, Megan Gendjar, Kelsie M Nauta, Nicholas O Burton, Ryan D Sheldon.

  Polyamines are an important class of metabolites that are poorly covered in standard metabolomics workflows. Here, we describe a protocol for isobutyl-chloroformate derivatization that can be applied to metabolite extracts following other metabolomics applications. This simple procedure allows for quantitative measurement of thirteen polyamines and two internal standards in a short (15-minute) LC-MS method. We report at least two triple quadrupole mass spectrometer transitions for each compound. Among these are unique transitions for co-eluting isomers N1- and N8-acetylspermidine, enabling quantitation of each isomer individually. We further define the linear dynamic range for each compound, and present data in several biological sample types. This simple and robust method enables stand-alone and post-metabolomics polyamine analysis.

Keywords:  Acetylspermidine; Metabolism; Metabolomics; Reversed phase

DOI:  https://doi.org/10.1016/bs.mie.2025.01.063
J Proteome Res. 2025 May 20.

MCQR: Enhancing the Processing and Analysis of Quantitative Proteomics Data by Incorporating Chromatography and Mass Spectrometry Information.

Thierry Balliau, Anne Frambourg, Olivier Langella, Marie-Laure Martin, Michel Zivy, Mélisande Blein-Nicolas.

  In the field of proteomics, generating biologically relevant results from mass spectrometry (MS) signals remains a challenging task. This is partly due to the fact that the computational strategies for converting MS signals into biologically interpretable data depend heavily on the MS acquisition method. Additionally, the processing and the analysis of these data vary depending on whether the proteomic experiment was performed with or without labeling, and with or without fractionation. Several R packages have been developed for processing and analyzing MS data, but they only incorporate identification and quantification data; none of them takes into account other invaluable information collected during MS runs. To address this limitation, we introduce MCQR, an alternative R package for the in-depth exploration, processing, and analysis of quantitative proteomics data generated from either data-dependent or data-independent acquisition methods. MCQR leverages experimental retention time measurements for quality control, data filtering, and processing. Its modular architecture offers flexibility to accommodate various types of proteomics experiments, including label-free, label-based, fractionated, or those enriched for specific post-translational modifications. Its functions, designed as simple building blocks, are user-friendly, making it easy to test parameters and methods, and to construct customized analysis scenarios. These unique features position MCQR as a comprehensive toolbox, perfectly suited to the specific needs of MS-based proteomics experiments.

Keywords:  bioinformatics; data filtering; mass spectrometry; quality control; quantitative proteomics; statistical analysis

DOI:  https://doi.org/10.1021/acs.jproteome.4c01119
J Proteome Res. 2025 May 22.

Data-Independent Acquisition-Based Quantitative Proteomics for Pairwise Comparison of Serum and Plasma.

Yan Li, Bing Wang, Fahan Ma, Jingwen Lyu, Daojian Xun, Tao Ji, Lingli Zhu, Subei Tan, Chen Ding.

  Human blood contains proteins secreted by various organs, but there is no consensus on whether serum or plasma is preferable for proteome studies. Mass spectrometry employing data-independent acquisition has emerged as a transformative methodology in proteomics, enabling reproducible large-scale quantification of proteomes during one LC-MS/MS analytical run and facilitating identification of potential markers and elucidation of biological processes. Here, we profiled the proteome data of ten paired plasma and serum samples in the initial sample set. Functional analysis revealed similarities and differences in biological functions and the preference for different organs between serum and plasma. Furthermore, comparative proteomic analysis highlighted the different proteomic characteristics. Plasma-overrepresented pathways were related to the phagosome and immune, while serum-overrepresented pathways were associated with amino acid metabolism, which were further validated by the follow-up sample set composed of eight paired plasma and serum samples. We have detected potential markers in plasma and serum for various cancers and explored their association with prognosis using data from the TCGA pan-cancer cohort and HPA database. Further assessment is required to validate the reproducibility of the quantification for these markers. Overall, this study highlights the commonality and specificity of plasma and serum at the molecular level, underscoring their respective utility in biological exploration and clinical applications.

Keywords:  biomarkers; data-independent acquisition; mass spectrometry; proteomics; serum and plasma

DOI:  https://doi.org/10.1021/acs.jproteome.4c00783
J Chromatogr B Analyt Technol Biomed Life Sci. 2025 May 19. pii: S1570-0232(25)00215-6. [Epub ahead of print]1262 124661

Quality control in GC-MS analysis of amino acids in human urine and plasma: Possible implications for targeted and untargeted metabolomics.

Alexander Bollenbach, Bibiana Beckmann, Dimitrios Tsikas.

  In metabolomics, LC-MS(/MS) is currently used about two times more frequently than GC-MS(/MS) since about 2005, perhaps the year of appearance of metabolomics as an individual analytical approach in the life sciences. LC-MS(/MS) and GC-MS(/MS) share many common challenges in targeted and untargeted metabolomics, the Janus face of metabolomics. Especially the importance of the key issue of quality assurance (QA) and quality control (QC) has been recognized and is increasingly addressed by individual researchers and consortia. In previous work, our group has proposed a QC system for the quantitative GC-MS analysis of amino acids in human plasma samples. In the present study, we investigated the utility of such a QC approach for the quantitative (targeted) GC-MS analysis of amino acids in human urine samples by using previously validated methods. Endogenous (unlabeled) amino acids were analyzed in 10-μL aliquots of study urine samples and in QC urine samples as methyl ester pentafluoropropionyl derivatives (d0Me-PFP) using a mixture of in-situ prepared trideuteromethyl esters for use as internal standards, which were then converted into their PFP derivatives (i.e., d3Me-PFP). GC-MS analysis of 38 study urine samples and 8 QC urine samples was performed in the negative-ion chemical ionization (NICI) mode by selected-ion monitoring (SIM) of characteristic ions of d0Me-PFP and d3Me-PFP within a single run by using an oven temperature program. For direct comparison, analysis of 35 study plasma samples and 8 QC plasma samples of the same clinical study was performed. Closely comparable experimental and instrumental conditions were used in the analyses, and the same staff was involved in the entirely analytical process. Chromatographic H/D isotope effects and peak area values were determined and examined with respect to qualitative and quantitative GC and MS parameters including accuracy and precision. Study and QC plasma behaved similarly. On a molar basis, the amino acid derivatives have different peak area values. Yet, this does not affect the accuracy of the GC-MS method. Our study suggests that untargeted GC-MS metabolomics studies on amino acids in biological samples are inappropriate for quantitative GC-MS analysis. Targeted metabolomics, i.e., use of isotopologs are indispensable for reliable quantitative GC-MS analysis of amino acids in biological samples. It is reasonable to assume that our findings will also apply to other classes of analytes and types of biological samples.

Keywords:  Amino acids; Comparison; Derivatization; OMICS; Plasma; Quality control; Urine

DOI:  https://doi.org/10.1016/j.jchromb.2025.124661
Expert Rev Proteomics. 2025 May 22. 1-8

Optimization of bottom-up proteomic sample preparation by design of experiments for absolute quantification of 257 proteins in human plasma using UPLC-MRM-MS.

Kari Arnarson, Kristrun Y Holm, Valdis Gunnarsdottir Thormar, Finnur F Eiríksson, Yassene Mohammed, Christoph H Borchers, Sigridur K Bodvarsdottir, Margret Thorsteinsdottir.

   INTRODUCTION: Targeted protein absolute quantification using mass spectrometry holds promise for identifying biomarkers for diagnosis, prognosis, and personalized medicine. However, complex and time-consuming workflows, particularly during sample preparation, present significant bottlenecks. Addressing these challenges is critical for the applicability of absolute quantification of proteins in clinical research settings.
AREAS COVERED: We explore optimization strategies for protein digestion in bottom-up proteomics sample preparation. Design of experiments (DoE), a statistical approach for systematically evaluating multiple experimental factors, was used for simultaneous optimization of digestion time, temperature, enzyme-to-protein substrate ratio, and denaturing agent. Furthermore, the lower limit of quantification (LLOQ) for our platform was improved by using the Waters Xevo TQ-XS UPLC-MRM-MS. The integration of automated sample preparation into the workflow enabled reproducible absolute quantification of 257 proteins in human plasma.
EXPERT OPINION: We successfully reduced protein digestion time from 18 hours (overnight) to 4 hours while maintaining relative digestion efficiency. We improved the sensitivity of the assay via the optimized workflow and were able to quantify proteins that previously fell below the LLOQ. These advancements, combined with automation, provide a practical, efficient, and reproducible workflow suitable for clinical research.

Keywords:  Automation; UPLC-MRM-MS; biomarker discovery; chemometrics; mass spectrometry; protein digestion; targeted proteomics

DOI:  https://doi.org/10.1080/14789450.2025.2504994
Nat Commun. 2025 May 16. 16(1): 4582

Dynamic single-cell metabolomics reveals cell-cell interaction between tumor cells and macrophages.

Yi Zhang, Mingying Shi, Mingxuan Li, Shaojie Qin, Daiyu Miao, Yu Bai.

Single-cell metabolomics reveals cell heterogeneity and elucidates intracellular molecular mechanisms. However, general concentration measurement of metabolites can only provide a static delineation of metabolomics, lacking the metabolic activity information of biological pathways. Herein, we develop a universal system for dynamic metabolomics by stable isotope tracing at the single-cell level. This system comprises a high-throughput single-cell data acquisition platform and an untargeted isotope tracing data processing platform, providing an integrated workflow for dynamic metabolomics of single cells. This system enables the global activity profiling and flow analysis of interlaced metabolic networks at the single-cell level and reveals heterogeneous metabolic activities among single cells. The significance of activity profiling is underscored by a 2-deoxyglucose inhibition model, demonstrating delicate metabolic alteration within single cells which cannot reflected by concentration analysis. Significantly, the system combined with a neural network model enables the metabolomic profiling of direct co-cultured tumor cells and macrophages. This reveals intricate cell-cell interaction mechanisms within the tumor microenvironment and firstly identifies versatile polarization subtypes of tumor-associated macrophages based on their metabolic signatures, which is in line with the renewed diversity atlas of macrophages from single-cell RNA-sequencing. The developed system facilitates a comprehensive understanding single-cell metabolomics from both static and dynamic perspectives.

DOI: https://doi.org/10.1038/s41467-025-59878-w
Nat Commun. 2025 May 16. 16(1): 4566

LipidIN: a comprehensive repository for flash platform-independent annotation and reverse lipidomics.

Hao Xu, Tianhang Jiang, Yuxiang Lin, Lei Zhang, Huan Yang, Xiaoyun Huang, Ridong Mao, Zhu Yang, Changchun Zeng, Shuang Zhao, Lijun Di, Wenbin Zhang, Jun Zeng, Zongwei Cai, Shu-Hai Lin.

Improving annotation accuracy, coverage, speed and depth of lipid profiles remains a significant challenge in traditional lipid annotation. We introduce LipidIN, an advanced framework designed for flash platform-independent annotation. LipidIN features a 168.5-million lipid fragmentation hierarchical library that encompasses all potential chain compositions and carbon-carbon double bond locations. The expeditious querying module achieves speeds exceeding one hundred billion queries per second across all mass spectral libraries. The lipid categories intelligence model is developed using three relative retention time rules, reducing false positive annotations and predicting unannotated lipids with a 5.7% estimated false discovery rate, covering 8923 lipids cross various species. More importantly, LipidIN integrates a Wide-spectrum Modeling Yield network for regenerating lipid fragment fingerprints to further improve accuracy and coverage with a 20% estimated recall boosting. We further demonstrate the utility of LipidIN in multiple tasks for lipid annotation and biomarker discovery in clinical cohorts.

DOI: https://doi.org/10.1038/s41467-025-59683-5
Nat Commun. 2025 May 22. 16(1): 4753

Expanding the landscape of aging via orbitrap astral mass spectrometry and tandem mass tag integration.

Gregory R Keele, Yue Dou, Seth P Kodikara, Erin D Jeffery, Dina L Bai, Erik Hultenius, Zichen Gao, Joao A Paulo, Steven P Gygi, Xiao Tian, Tian Zhang.

Aging results in a progressive decline in physiological function due to the deterioration of essential biological processes. While proteomics offers insights into aging mechanisms, prior studies are limited in proteome coverage and lifespan range. To address this, we integrate the Orbitrap Astral Mass Spectrometer with the multiplex tandem mass tag (TMT) technology to profile the proteomes of cortex, hippocampus, striatum and kidney in the C57BL/6JN mice, quantifying 8,954 to 9,376 proteins per tissue (12,749 total). Samples spanned both sexes and three age groups (3, 12, and 20 months), representing early to late adulthood. To improve TMT quantitation accuracy, we develop a peptide-spectrum match-based filtering strategy that leverages resolution and signal-to-noise thresholds. Our analysis uncovers distinct tissue-specific patterns of protein abundance, with age and sex differences in the kidney and primarily age-related changes in brain tissues. We also identify both linear and non-linear proteomic trajectories with age, revealing complex protein dynamics over the adult lifespan. Integrating our findings with early developmental proteomic data from brain tissues highlights further divergent age-related trajectories, particularly in synaptic proteins. This study provides a robust data analysis workflow for Orbitrap Astral-based TMT analysis and expands the proteomic understanding of aging across tissues, ages, and sexes.

DOI: https://doi.org/10.1038/s41467-025-60022-x
NPJ Aging. 2025 May 23. 11(1): 40

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

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

Frailty is an age-related geriatric syndrome. 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. We identify age-related differentially abundant metabolites, determine frailty-related metabolites, and generate frailty features, both in the whole cohort and 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. Our results identify sex-specific metabolite frailty biomarkers, and shed light on potential mechanisms.

DOI: https://doi.org/10.1038/s41514-025-00237-w
Sci Data. 2025 May 23. 12(1): 848

A Comprehensive Proteome of Human Corneal Epithelial Cells Constructed by Cross-platform DIA-Mass Spectrometry.

Kenrick Kai-Yuen Chan, Jimmy Ka-Wai Cheung, Shing-Yan Roy Chung, Hang-Kin Kong, Jingfang Bian, Lei Zhou, Chi-Wai Do, Thomas Chuen Lam.

The corneal epithelium serves as the front barrier against environmental stimuli and pathogens on the ocular surface. A comprehensive protein profile of the corneal epithelium would be crucial for understanding the molecular mechanisms that are related to corneal disease. This work demonstrated a library-free data-independent acquisition (DIA) approach across different mass spectrometers and proteomic software to build a comprehensive proteomic dataset for human corneal epithelial cells (HCECs). With the combinational use of different data-independent acquisition technologies of multiple mass spectrometers, including Sciex ZenoTOF 7600 (DIA-SWATH), Bruker TimsTOF Pro2 (DIA-PASEF), and ThermoFisher Orbitrap Fusion Lumos (DIA-HRMS1), protein identification and quantification were performed with superior sensitivity and resolution. By using a library-free DIA approach, this study constructed a more diverse and unbiased proteomic profile of human corneal epithelial cells (HCECs), comprising 11,954 protein groups (1% FDR). This represents the largest corneal proteome reported to date. All raw proteomic data were deposited to ProteomeXchange Consortium via Proteomics Identifications database (PRIDE) with the dataset identifier accession number PXD059451. Our findings hold the potential to enhance future understanding of corneal pathologies and transformative therapeutics.

DOI: https://doi.org/10.1038/s41597-025-05004-w
Cancer Metab. 2025 May 19. 13(1): 22

Lactate dehydrogenase A-coupled NAD+ regeneration is critical for acute myeloid leukemia cell survival.

Ayşegül Erdem, Séléna Kaye, Francesco Caligiore, Manuel Johanns, Fleur Leguay, Jan Jacob Schuringa, Keisuke Ito, Guido Bommer, Nick van Gastel.

   BACKGROUND: Enhanced glycolysis plays a pivotal role in fueling the aberrant proliferation, survival and therapy resistance of acute myeloid leukemia (AML) cells. Here, we aimed to elucidate the extent of glycolysis dependence in AML by focusing on the role of lactate dehydrogenase A (LDHA), a key glycolytic enzyme converting pyruvate to lactate coupled with the recycling of NAD+.
METHODS: We compared the glycolytic activity of primary AML patient samples to protein levels of metabolic enzymes involved in central carbon metabolism including glycolysis, glutaminolysis and the tricarboxylic acid cycle. To evaluate the therapeutic potential of targeting glycolysis in AML, we treated AML primary patient samples and cell lines with pharmacological inhibitors of LDHA and monitored cell viability. Glycolytic activity and mitochondrial oxygen consumption were analyzed in AML patient samples and cell lines post-LDHA inhibition. Perturbations in global metabolite levels and redox balance upon LDHA inhibition in AML cells were determined by mass spectrometry, and ROS levels were measured by flow cytometry.
RESULTS: Among metabolic enzymes, we found that LDHA protein levels had the strongest positive correlation with glycolysis in AML patient cells. Blocking LDHA activity resulted in a strong growth inhibition and cell death induction in AML cell lines and primary patient samples, while healthy hematopoietic stem and progenitor cells remained unaffected. Investigation of the underlying mechanisms showed that LDHA inhibition reduces glycolytic activity, lowers levels of glycolytic intermediates, decreases the cellular NAD+ pool, boosts OXPHOS activity and increases ROS levels. This increase in ROS levels was however not linked to the observed AML cell death. Instead, we found that LDHA is essential to maintain a correct NAD+/NADH ratio in AML cells. Continuous intracellular NAD+ supplementation via overexpression of water-forming NADH oxidase from Lactobacillus brevis in AML cells effectively increased viable cell counts and prevented cell death upon LDHA inhibition.
CONCLUSIONS: Collectively, our results demonstrate that AML cells critically depend on LDHA to maintain an adequate NAD+/NADH balance in support of their abnormal glycolytic activity and biosynthetic demands, which cannot be compensated for by other cellular NAD+ recycling systems. These findings also highlight LDHA inhibition as a promising metabolic strategy to eradicate leukemic cells.

Keywords:  Acute myeloid leukemia; Cancer metabolism; Glycolysis; Lactate dehydrogenase A; NAD+ ; Redox balance

DOI:  https://doi.org/10.1186/s40170-025-00392-4
Front Bioeng Biotechnol. 2025 ;13 1579098

A comparison of SWATH-MS methods for measurement of residual host cell proteins in adeno-associated virus preparations.

Thomas M Leibiger, Lie Min, Kelvin H Lee.

   Introduction: Analysis of residual host cell proteins in adeno-associated virus (AAV) preparations is challenging due to low availability and high complexity of samples. One strategy to address these challenges is through development of improved liquid chromatography-tandem mass spectrometry (LC-MS/MS) methods with greater sensitivity and reduced sample requirement.
Methods: In this work, we compare the performance of four sequential window acquisition of all theoretical fragment ion mass spectra (SWATH-MS) methods for identification and quantitation of residual HCPs in rAAV2, -5, -8, and -9 preparations produced with human embryonic kidney 293 (HEK293) cells and purified using immunoaffinity chromatography. Key SWATH-MS parameters including spectral library construction (data dependent vs. in silico), data processing software (DIA-NN vs. Skyline), and mass spectrometer instrument (Sciex TripleTOF 6600 vs. Sciex ZenoTOF 7600) were assessed. Method attributes including sample requirement and processing time, and method outputs including protein and precursor identifications, host cell protein quantitation comparisons across methods, and quantitation coefficients of variance (CV) were considered to help establish a SWATH-MS workflow well-suited for rAAV HCP analytics.
Results: A 78% increase in HCP identifications, 80% reduction in sample requirement, and 70% reduction in instrument runtime was achieved with an in silico spectral library, data processing in DIA-NN, and data collection with the Sciex ZenoTOF 7600 instrument (DIA-NN-7600 method) compared to a previously established method using a DDA-derived spectral library, data processing in Skyline, and data collection with the Sciex TripleTOF 6600 instrument (Skyline-DDA-6600 method). Additionally, the DIA-NN-7600 method shows median HCP quantitation CV below 10% for triplicate data acquisitions, and comparable quantitation to other methods for a panel of highly abundant residual HCPs previously identified in rAAV downstream processing.
Discussion: This work highlights a SWATH-MS method with data collection and processing specifically tailored for rAAV residual HCP analysis.

Keywords:  DIA-NN; SWATH-MS; adeno-associated virus (AAV); data independent acquisition (DIA); host cell proteins (HCPs); liquid chromatography-tandem mass spectrometry (LC-MS/MS); mass spectrometry

DOI:  https://doi.org/10.3389/fbioe.2025.1579098
Sci Signal. 2025 May 20. 18(887): eadw1245

Technical recommendations for analyzing oxylipins by liquid chromatography-mass spectrometry.

Nils Helge Schebb, Nadja Kampschulte, Gerhard Hagn, Kathrin Plitzko, Sven W Meckelmann, Soumita Ghosh, Robin Joshi, Julia Kuligowski, Dajana Vuckovic, Marina T Botana, Ángel Sánchez-Illana, Fereshteh Zandkarimi, Aditi Das, Jun Yang, Louis Schmidt, Antonio Checa, Helen M Roche, Aaron M Armando, Matthew L Edin, Fred B Lih, Juan J Aristizabal-Henao, Sayuri Miyamoto, Francesca Giuffrida, Arieh Moussaieff, Rosário Domingues, Michael Rothe, Christine Hinz, Ujjalkumar Subhash Das, Katharina M Rund, Ameer Y Taha, Robert K Hofstetter, Markus Werner, Oliver Werz, Astrid S Kahnt, Justine Bertrand-Michel, Pauline Le Faouder, Robert Gurke, Dominique Thomas, Federico Torta, Ivana Milic, Irundika H K Dias, Corinne M Spickett, Denise Biagini, Tommaso Lomonaco, Helena Idborg, Jun-Yan Liu, Maria Fedorova, David A Ford, Anne Barden, Trevor A Mori, Paul D Kennedy, Kirk Maxey, Julijana Ivanisevic, Hector Gallart-Ayala, Cécile Gladine, Markus Wenk, Jean-Marie Galano, Thierry Durand, Ken D Stark, Coral Barbas, Ulrike Garscha, Stacy L Gelhaus, Uta Ceglarek, Nicolas Flamand, Julian L Griffin, Robert Ahrends, Makoto Arita, Darryl C Zeldin, Francisco J Schopfer, Oswald Quehenberger, Randall Julian, Anna Nicolaou, Ian A Blair, Michael P Murphy, Bruce D Hammock, Bruce Freeman, Gerhard Liebisch, Charles N Serhan, Harald C Köfeler, Per-Johan Jakobsson, Dieter Steinhilber, Michael H Gelb, Michal Holčapek, Ruth Andrew, Martin Giera, Garret A FitzGerald, Robert C Murphy, John W Newman, Edward A Dennis, Kim Ekroos, Ginger L Milne, Miguel A Gijón, Hubert W Vesper, Craig E Wheelock, Valerie B O'Donnell.

Several oxylipins are potent lipid mediators that regulate diverse aspects of health and disease and whose quantitative analysis by liquid chromatography-mass spectrometry (LC-MS) presents substantial technical challenges. As members of the lipidomics community, we developed technical recommendations to ensure best practices when quantifying oxylipins by LC-MS.

DOI: https://doi.org/10.1126/scisignal.adw1245
Clin Proteomics. 2025 May 18. 22(1): 20

From blood drops to biomarkers: a scoping review of microsampling in mass spectrometry-based proteomics.

Amanda J Campbell, Nicolai B Palstrøm, Lars M Rasmussen, Jes S Lindholt, Hans C Beck.

   BACKGROUND: Microsamples are simple blood sampling procedures utilizing small blood draws. Although microsamples are regularly used in some disciplines, proteomic analysis of these samples is an emerging field. Currently, it is unclear whether the quantitative precision and proteome coverage achieved in microsamples is comparable to plasma or serum. As a consequence, microsamples are not used in proteomics to the same degree as more traditional blood samples.
OBJECTIVES: The objective of this scoping review was to report the applications of microsamples within clinical mass spectrometry-based proteomics. This was accomplished by describing both proof-of-concept and clinical proteomics research within this field, with an additional evaluation of the newest advances regarding clinical proteomics.
INCLUSION CRITERIA: Original scientific literature was included where bottom-up mass spectrometry was used to analyze endogenous proteins from human microsamples.
METHODS: Relevant publications were sourced through three scientific databases (MEDLINE, EMBASE and Scopus) in addition to backward and forward citation searches through Scopus. Record screening was performed independently by two separate authors. The review was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews (PRISMA-ScR) guidelines.
RESULTS: A total of 209 records were screened for inclusion from database searches and 3157 records were screened from forward and backward citation searches, resulting in 64 eligible studies. An evaluation of proof-of-concept research within this field revealed that although microsamples are amenable to high-throughput proteomics using a variety of targeted and untargeted acquisition methods, quantification remained a relevant issue. Microsampling practices were heterogeneous, and no standard procedure existed for protein quantification. Clinical studies investigated protein expression in numerous disease or experimental groups, including hemoglobinopathies and immunodeficiency disorders.
CONCLUSION: The use of microsamples is increasing within the proteomics field and these samples are amenable to standard bottom-up workflows. Although microsamples present a clear advantage in terms of sampling procedure, both the sample collection and quantification procedures remain to be standardized. However, there is an incentive to address the remaining issues, since microsampling would greatly reduce the resources necessary to sample large cohorts within clinical proteomics, a field that currently lacks large discovery and validation cohorts.

Keywords:  Clinical proteomics; Dried blood spots; Mass spectrometry; Microsampling; Scoping review

DOI:  https://doi.org/10.1186/s12014-025-09540-w
Cancer Metab. 2025 May 19. 13(1): 23

S-adenosylmethionine metabolism shapes CD8+ T cell functions in colorectal cancer.

Xiaohua Yang, Tianzhang Kou, Hongmiao Wang, Ji Zhu, Zheng-Jiang Zhu, Yuping Cai.

  Metabolite nutrients within the tumor microenvironment shape both tumor progression and immune cell functionality. It remains elusive how the metabolic interaction between T cells and tumor cells results in different anti-cancer immunotherapeutic responses. Here, we use untargeted metabolomics to investigate the metabolic heterogeneity in patients with colorectal cancer (CRC). Our analysis reveals enhanced S-adenosylmethionine (SAM) and S-adenosylhomocysteine (SAH) metabolism in microsatellite stable (MSS) CRC, a subtype known for its resistance to immunotherapy. Functional studies reveal that SAM and SAH enhance the initial activation and effector functions of CD8+ T cells. Instead, cancer cells outcompete CD8+ T cells for SAM and SAH availability to impair T cell survival. In vivo, SAM supplementation promotes T cell proliferation and reduces exhaustion of the tumor-infiltrating CD8+ T cells, thus suppressing tumor growth in tumor-bearing mice. This study uncovers the metabolic crosstalk between T cells and tumor cells, which drives the development of tumors resistant to immunotherapy.

Keywords:  CD8+ T cell function; Metabolite nutrients; Metabolomics; Microsatellite stable colorectal cancer; S-adenosylmethionine (SAM) and S-adenosylhomocysteine (SAH) metabolism

DOI:  https://doi.org/10.1186/s40170-025-00394-2
J Proteomics. 2025 May 17. pii: S1874-3919(25)00083-1. [Epub ahead of print]318 105456

Protein digestion, peptide mass and peptide fragmentation with MZCal: A user-friendly phone-compatible application.

Brittannie Willis, Harry J Whitwell.

  MZCal is a user-friendly, mobile-compatible web application designed for assisting peptide analysis in bottom-up mass spectrometry (MS). There are many tools for basic in-silico digestion, peptide mass and peptide mz calculations, though not in a single, convenient and mobile-friendly format. Since internet availability can often be limited on mass-spectrometry linked computers, we developed MZCal for use in our laboratory, featuring tools that we commonly use in evaluating MS methods for bottom-up proteomics while working at the mass spectrometer. MZCal provides a single platform for in silico protein digestion, peptide mass and fragmentation calculations, and spectral prediction using MS2PIP. Optimised for use on both Android and iOS devices, MZCal enables convenient, real-time mass spectrum interpretation in laboratory settings and as a teaching resource. Unlike more complex web-tools, MZCal offers a streamlined interface that prioritises ease of use and accessibility. Overall, MZCal serves as a practical, portable solution for essential peptide calculations, providing an intuitive and accessible tool for both researchers and educators.

Keywords:  Bottom-up proteomics; Fragmentation prediction; In silico digest; Pepitde mass; Webtool

DOI:  https://doi.org/10.1016/j.jprot.2025.105456
J Proteome Res. 2025 May 18.

MultiStageSearch: An Iterative Workflow for Unbiased Taxonomic Analysis of Pathogens Using Proteogenomics.

Julian Pipart, Tanja Holstein, Lennart Martens, Thilo Muth.

  The global SARS-CoV-2 pandemic emphasized the need for accurate pathogen diagnostics. While genomics is the gold standard, integrating mass spectrometry-based proteomics offers additional benefits. However, current proteomic and genomic reference databases are often biased toward specific taxa, such as pathogenic strains or model organisms, and proteomic databases are less comprehensive. These biases and gaps can lead to inaccurate identifications. To address these issues, we introduce MultiStageSearch, a multistep database search method that combines proteome and genome databases for taxonomic analysis. Initially, a generalist proteome database is used to infer potential species. Then, MultiStageSearch generates a specialized proteogenomic database for precise identification. This database is preprocessed to filter duplicates and cluster identical open reading frames to reduce genomic database biases. The workflow operates independently of strain-level NCBI taxonomy, enabling the identification of strains not represented in existing taxonomies. We benchmarked the workflow on viral and bacterial samples, demonstrating its superior performance in strain-level taxonomic inference compared to existing methods. MultiStageSearch offers a flexible and accurate approach for pathogen research and diagnostics, overcoming incomplete search spaces and biases inherent in reference databases.

Keywords:  Reverse Transcription-Polymerase Chain Reaction (RT-PCR); SARS-CoV-2; open reading frame (ORF); peptide-spectrum matches (PSMs); “Norovirus GII”

DOI:  https://doi.org/10.1021/acs.jproteome.4c00901
J Am Soc Mass Spectrom. 2025 May 22.

Unravelling the Mechanism of Cisplatin Resistance in Triple-Negative Breast Cancer: Insights from Metabolomic Profiling via Mass Spectrometry Analysis.

Shashwati Parihari, Anvita Pant, Ankit Halder, Sanjeeva Srivastava.

  Triple-negative breast cancer (TNBC) poses a significant challenge due to its aggressive nature and limited treatment options, with cisplatin often used in treatment. However, the mechanism underlying the cisplatin resistance in TNBC is poorly understood. This study aimed to develop a cisplatin-resistant (cisR) TNBC cell line and understand its metabolic alterations. Characterization of cisR and cisplatin-sensitive (cisS) cell lines involved cytotoxicity, wound healing, and morphological studies. This study further employed untargeted and targeted mass spectrometry analyses for a deep metabolome comparison between cisR and cisS TNBC cell lines to elucidate the molecular mechanisms driving cisplatin resistance. Metabolomics profiling of cisR and cisS cell lines resulted in the identification of significantly altered metabolites, such as N8-acetylspermidine, d-pantothenic acid, sphingosine, sphinganine 1-phosphate (S1P), nicotinamide, choline, and certain amino acids. This global and targeted metabolomics study also revealed the downregulation of N8-acetylspermidine and d-pantothenic acid, indicating that their dysregulation is associated with cisplatin resistance in TNBC cells. Furthermore, this study unravels the dysregulation of sphingolipid metabolism, particularly the downregulation of ceramide, sphingosine, and S1P, and glycerophospholipid metabolism (choline, LysoPC) as a potential contributor to cisplatin resistance in TNBC cells. Similarly, upregulation of nicotinamide metabolism key players nicotinate and 1-methylnicotinamide emerges as a contributor to cisplatin resistance. Aminoacyl t-RNA biosynthesis and ABC transporter metabolic pathways involving proline, valine, threonine, glutamic acid, and phenylalanine amino acids are also implicated in developing TNBC-resistant cells. This comprehensive metabolomics study identifies distinct metabolic signatures and key dysregulated pathways associated with cisplatin resistance in TNBC, offering potential candidate marker and therapeutic targets.

Keywords:  Cisplatin resistance; MDA-MB-231; Mass spectrometer; Metabolomics; TNBC; Targeted metabolomics; Triple-negative breast cancer; untargeted metabolomics

DOI:  https://doi.org/10.1021/jasms.4c00445
PLoS Pathog. 2025 May 22. 21(5): e1012685

Fatty acid desaturases link cell metabolism pathways to promote proliferation of Epstein-Barr virus-infected B cells.

Emmanuela N Bonglack, Kaeden K Hill, Ashley P Barry, Alexandria Bartlett, Pol Castellano-Escuder, Matthew D Hirschey, Micah A Luftig.

Epstein-Barr virus (EBV) is a gamma herpesvirus that infects up to 95% of the human population by adulthood, typically remaining latent in the host memory B cell pool. In immunocompromised individuals, EBV can drive the transformation and rapid proliferation of infected B cells, ultimately resulting in neoplasia. The same transformation process can be induced in vitro, with EBV-infected peripheral blood B cells forming immortalized lymphoblastoid cell lines (LCLs) within weeks. In this study, we found that the fatty acid desaturases stearoyl-CoA desaturase 1 (SCD1) and fatty acid desaturase 2 (FADS2) are upregulated by EBV and crucial for EBV-induced B cell proliferation. We show that pharmacological and genetic inhibition of both SCD1 and FADS2 results in a significantly greater reduction in proliferation and cell cycle arrest, compared to perturbing either enzyme individually. Additionally, we found that inhibiting either SCD1 or FADS2 alone hypersensitizes LCLs to palmitate-induced apoptosis. Further free fatty acid profiling and metabolic analysis of dual SCD1/FADS2-inhibited LCLs revealed an increase in free unsaturated fatty acids, a reduction of oxidative phosphorylation, and a reduction of glycolysis, thereby linking the activity of SCD1 and FADS2 to overall growth-promoting metabolism. Lastly, we show that SCD1 and FADS2 are important in the growth of clinically derived EBV+ immunoblastic lymphoma cells. Collectively, these data demonstrate a previously uncharacterized role of lipid desaturation in EBV+ transformed B cell proliferation, revealing a metabolic pathway that can be targeted in future anti-lymphoma therapies.

DOI: https://doi.org/10.1371/journal.ppat.1012685
J Chromatogr B Analyt Technol Biomed Life Sci. 2025 May 15. pii: S1570-0232(25)00202-8. [Epub ahead of print]1262 124648

Quantitative GC-NICI-MS and GC-NICI-MS/MS analysis by using isotopologs as internal standards: A tutorial review.

Dimitrios Tsikas.

  The use of analytes labelled with stable-isotopes of 2H, 13C, 15N, 17O and/or 18O, i.e., the isotopologs, as internal standards is unique and considered the Golden Standard is quantitative analyses based on mass spectrometry. However, the handling with isotopologs deserves a great extent of care and attentiveness from the very begin of the analytical process. Many issues need to be considered in order to create an analytical method that generates close-to-reality concentrations of a certain analyte or of group of analytes of the same or different chemical classes in complex biological samples. They including isotopic purity, stability through the entire analytical process including sampling, derivatization, ionization and collision-induced dissociation (CID). The present work deals specifically with the use of isotopologs as internal standards for the quantitative analysis of endogenous and exogenous substances in plasma, serum and urine samples. It focuses on GC-MS and GC-MS/MS, negative-ion chemical ionization (NICI) with methane as the reagent gas, and selected-ion monitoring (SIM) or selected-reaction monitoring (SRM) using argon as the collision gas. Special attention has been paid to purity of isotopologs, cross-contribution of analyte-internal standard, and stability of isotopologs during NICI and CID, to linearity of analyte-isotope detector response upon the analyte concentration. This tutorial review re-examines and discusses exemplarily previously reported validated GC-MS and GC-MS/MS methods, and gives recommendations regarding the handling with stable-isotope labelled analogs in quantitative analyses.

Keywords:  Derivatization; Kinetic and chromatographic H/D isotope effects; Negative-ion chemical ionization

DOI:  https://doi.org/10.1016/j.jchromb.2025.124648
Adv Sci (Weinh). 2025 May 23. e02721

Fully Automated Deep Learning Enabled Miniature Mass Spectrometry System for Psychoactive Therapeutic Drug Monitoring.

Yuanhao Zhou, Jiawen Ai, Zi Ye, Kexin Chen, JingXiong Lin, Zhenhua Zhang, Mi Luo, Benjie Zhou, Shijian Xiang, Jianhua Zhou, Xinming Huo.

  Advancing precision medicine requires efficient small molecule biomarker detection in biofluids, yet existing methods encounter challenges in complexity, portability, and throughput. This study presents an integrated miniature blood processing and mass spectrometry (MS) analysis system, which incorporates automated magnetic solid-phase extraction, self-aspiration sampling miniature mass spectrometer, and deep learning algorithms for automated quantitative analysis. It achieves full automation from sample preparation to detection, demonstrating the capability to analyze serum psychoactive drugs with a 15-second/MS acquisition and 8-sample parallel processing within 30 minutes (including pretreatment). This has significantly increased detection throughput and facilitated the establishment of the standard curve. The novel dual-target ion parallel tandem MS analysis technique, combined with a U-net peak area recognition algorithm, achieved over 98% identification accuracy with less than 0.2% area prediction deviation. Quantitative analysis showed high correlation coefficients >0.99 in medically relevant ranges, supported by relative standard deviation < 10% and average back-calculated accuracy deviation < 3.5%. Clinical validation revealed strong concordance with LC-MS/MS. The system's integration of automated sample processing, miniature MS hardware, and AI-driven data analysis establishes a paradigm for high-throughput clinical detection. The advantages of accuracy, automation, intelligence, miniaturization, and high throughput suggest significant potential for this system in clinical detection and personalized medicine.

Keywords:  automated analysis; clinical mass spectrometry; intelligent diagnosis; miniature mass spectrometer; therapeutic drug monitoring

DOI:  https://doi.org/10.1002/advs.202502721
Int Immunol. 2025 May 20. pii: dxaf027. [Epub ahead of print]

Secreted phospholipase A2 regulates intercellular communications by coordinating extracellular phospholipid metabolism.

Makoto Murakami.

  Lipids play fundamental roles in life. In essence, "phospholipase A2" (PLA2) indicates a group of enzymes that release fatty acids and lysophospholipids by hydrolyzing the sn-2 position of glycerophospholipids. To date, more than 50 enzymes that possess PLA2 or related lipid-metabolizing activities have been identified in mammals and are subdivided into several families in terms of their structures, catalytic mechanisms, tissue/cellular localizations, and evolutionary relationships. Among the PLA2 superfamily, the secreted PLA2 (sPLA2) family contains 11 isoforms in mammals, each of which has unique substrate specificity and tissue/cellular distributions. Recent studies using gene-manipulated (knockout and/or transgenic) mice for a full set of sPLA2s have revealed their diverse roles in immunity, metabolism, and other biological events. Application of mass spectrometric lipidomics to these mice has allowed the identification of target substrates and products of individual sPLA2s in tissue microenvironments. In principle, sPLA2s hydrolyze extracellular phospholipids such as those in extracellular vesicles, microbes, lipoproteins, surfactants, and ingested foods, as well as phospholipids in the plasma membrane of activated or damaged cells, thereby exacerbating or ameliorating various diseases. The actions of sPLA2s are dependent on, or independent of, the generation of free fatty acids, lysophospholipids, or their metabolites (lipid mediators) according to pathophysiological contexts. In this review, I will make an overview of recent understanding of the unexplored immunoregulatory roles of sPLA2s and their underlying lipid pathways, especially focusing on their unique actions on extracellular vesicles, activated/damaged cells, and gut microbiota.

Keywords:  Extracellular vesicle; Lipid mediator; Lipidomics; Metabolism; Microbiome

DOI:  https://doi.org/10.1093/intimm/dxaf027
Talanta. 2025 May 14. pii: S0039-9140(25)00817-3. [Epub ahead of print]295 128327

Unveiling the dark matter of the metabolome: A narrative review of bioinformatics tools for LC-HRMS-based compound annotation.

Rui Xu, Jiangjiang Zhu.

  Compound annotation, including the unveiling of dark matter in the metabolomics study represents a pivotal undertaking within the metabolomics field, serving as the linchpin for unraveling the identities and attributes of chemical entities. This narrative review examines the evolution of widely adopted compound annotation tools tailored for liquid chromatography-mass spectrometry (LC-MS) data analysis over the past two decades, which has been characterized by a transition from library-based search methodologies to advanced high-throughput approaches. Furthermore, emerging tools originating from both LC and MS domains were summarized. The synergistic partnership between quantitative structure-retention relationship (QSRR) models and machine learning (ML) techniques is explored, encompassing both conventional methodologies and advanced convolutional neural networks (CNNs). This collaborative framework has played a pivotal role in the precise prediction of retention times. Additionally, the enhanced applicability and extensibility of retention order prediction are emphasized, particularly under the constraints of experimental configurations. Within the domain of mass spectra-based annotation, the foundational task of mapping compound structures to mass spectra is examined-traditionally accomplished by aligning experimental data with established standards and libraries. Recent advancements highlight emerging tools that adopt multi-tiered mapping strategies, such as molecular networks and fragmentation trees, or incorporate machine learning to capture complex mapping patterns. This comprehensive examination underscores the pivotal role of compound annotation tools in advancing our understanding of complex LC-MS data matrix to further assist the annotation of dark matter in metabolome.

Keywords:  Compound annotation; Liquid chromatography-mass spectrometry; Machine learning; Mass spectra similarity; Retention time prediction; Structure-spectra mapping

DOI:  https://doi.org/10.1016/j.talanta.2025.128327
Nat Commun. 2025 May 16. 16(1): 4567

Extended coverage of human serum glycosphingolipidome by 4D-RP-LC TIMS-PASEF unravels association with Parkinson's disease.

Huong Giang Vo, Gabriel Gonzalez-Escamilla, Daniela Mirzac, Lilia Rotaru, Damian Herz, Sergiu Groppa, Laura Bindila.

Glycosphingolipids (GSLs) are important targets in immune, infectious, lysosomal storage diseases, cancer, and neurodegenerative diseases. Circulatory GSLs profiling in clinical samples is restricted by the lack of mid- and high-throughput analytical methods and deep coverage of long-chain sialylated glycosphingolipidome. We present a 4-dimensional (4D)-glycosphingolipidomics platform for routine glycosphingolipidome profiling encompassing: extraction and fractionation of sialylated GSLs with 3 to 15 monosaccharides, neutral GSLs and sulfatides; µL-flow reversed-phase LC-TIMS-PASEF MS analysis; semi-quantification strategy adapted for fractionated glycosphingolipidome, and referential CCS, RT, and m/z values for GSLs annotation. 4D-glycosphingolipidomics of human serum reveals a high structural heterogeneity, amounting to 376 GSLs: 159 GSLs of ganglio- and neolacto-series, 145 neutral GSLs and 72 sulfatides. Here we demonstrate the platform's utility for clinical profiling of Parkinson's disease (PD) sera. 41 neolacto- and ganglio-species discriminate PD patients from controls and 14 GSLs differentiate sex subgroups, laying the foundation for further functional GSL studies with PD.

DOI: https://doi.org/10.1038/s41467-025-59755-6
J Chromatogr B Analyt Technol Biomed Life Sci. 2025 May 14. pii: S1570-0232(25)00205-3. [Epub ahead of print]1261 124651

A simple surrogate approach for the quantitation of C4 (7α-hydroxy-4-cholesten-3-one) in human serum via LC-MS/MS and its application in a clinical study.

Feng Yin, Mani Deepika Vakkalanka, Walter Wiley, M Shane Woolf, Yousef Basir, Kumar Shah, Aaron M Wheeler, Moucun Yuan, William R Mylott, Mike Baratta.

  We present a validated LC-MS/MS assay for the quantitation of 7α-hydroxy-4-cholesten-3-one (C4), a key intermediate in the bile acid synthesis pathway from cholesterol, in human serum. A surrogate matrix approach was employed to overcome the challenges posed by the endogenous C4 levels in the biological matrix. Human serum samples were spiked with stable isotope labeled internal standard (SIL-IS), processed using supported liquid extraction (SLE), and analyzed by LC-MS/MS. Parallelism was successfully demonstrated between human serum (authentic matrix) and 5 % bovine serum albumin in phosphate buffered saline containing 0.1 % tween 20 (5 % BSA in PBST) (surrogate matrix). The assay's linear analytical range was established from 0.200 to 200 ng/mL. This validated LC-MS/MS method exhibited excellent accuracy and precision. The overall accuracy was between 97.9 % and 101 % with %CV less than 4.0 % for C4 in human serum. C4 was found to be stable in human serum for up to 24.7 h at room temperature, up to 34 days when stored at -25 °C or - 80 °C, and after five freeze/thaw cycles. The assay has been successfully applied to human serum samples to support a clinical study.

Keywords:  7α-Hydroxy-4-cholesten-3-one; Biomarker; C4; Human serum; LC-MS/MS; Validated

DOI:  https://doi.org/10.1016/j.jchromb.2025.124651
Cell. 2025 May 15. pii: S0092-8674(25)00511-2. [Epub ahead of print]

Microbiome metabolism of dietary phytochemicals controls the anticancer activity of PI3K inhibitors.

Asael Roichman, Qianying Zuo, Sunghoon Hwang, Wenyun Lu, Ricardo A Cordova, Michael R MacArthur, Jacob A Boyer, Sarah J Mitchell, Jesse Powers, Sophia A Koval, Craig J Hunter, Jamie Rijmers, Rolf-Peter Ryseck, Jenna E AbuSalim, Seema Chatterjee, Won Dong Lee, Xincheng Xu, Xi Xing, Zihong Chen, Xianfeng Zeng, Siddharth Marwaha, Matthew J McBride, Jessie Y Guo, Yibin Kang, Mohamed S Donia, Joshua D Rabinowitz.

  Phosphatidylinositol 3-kinase (PI3K) signaling is both the effector pathway of insulin and among the most frequently activated pathways in human cancer. In murine cancer models, the efficacy of PI3K inhibitors is dramatically enhanced by a ketogenic diet, with a proposed mechanism involving dietary suppression of insulin. Here, we confirm profound diet-PI3K anticancer synergy but show that it is, surprisingly, unrelated to diet macronutrient composition. Instead, the diet-PI3K interaction involves microbiome metabolism of ingested phytochemicals. Specifically, murine ketogenic diet lacks the complex spectrum of phytochemicals found in standard chow, including the soy phytochemicals soyasaponins. We find that soyasaponins are converted by the microbiome into inducers of hepatic cytochrome P450 enzymes, and thereby lower PI3K inhibitor blood levels and anticancer activity. A high-carbohydrate, low-phytochemical diet synergizes with PI3K inhibition to treat cancer in mice, as do antibiotics that curtail the gut microbiome. Thus, diet impacts anticancer drug activity through phytochemical-microbiome-liver interactions.

Keywords:  PI3Ki; breast cancer; cytochrome P450; diet and cancer treatment; gut-liver axis; microbiome metabolites; pancreatic cancer; pharmacokinetics; phytochemicals; soyasaponins

DOI:  https://doi.org/10.1016/j.cell.2025.04.041
J Chromatogr A. 2025 May 10. pii: S0021-9673(25)00384-X. [Epub ahead of print]1755 466036

Quantification of five intracellular and extracellular methionine pathway intermediates using stable isotope dilution UHPLC-MS/MS.

Lyuye Zhang, Ziyu Liang, Weibing Zhang, Hailin Wang.

  Unraveling the intricate mechanisms underlying methionine metabolism reprogramming and its extracellular release during apoptosis requires robust and sensitive quantification of key intermediates in both intracellular and extracellular compartments. Here, we developed a highly sensitive and precise stable isotope-dilution UHPLC-MS/MS method for simultaneous quantification of five critical intermediates in methionine cycle and methionine salvage pathway: l-methionine (Met), S-adenosylmethionine (SAM), S-adenosylhomocysteine (SAH), l-homocysteine (Hcy), and 5'-methylthioadenosine (5'-MTA). Through optimizing mobile phase additives and implementing an effective dilution strategy, this method minimizes matrix effects. The recovery rates of the five compounds exceeds 71.6 % in cell cytosol and cell medium samples, under a wide concentration range. The validated method presents good precision and linearity, with limits of detection (LODs) ranging from 1.9 fmol/10⁵ cells (SAH) to 555.4 fmol/10⁵ cells (Hcy) in cytosolic fractions, and from 0.7 fmol/10⁵ cells (SAH) to 52.1 fmol/10⁵ cells (Met) in culture media. Application of this validated method to UV-induced apoptosis in human promyelocytic leukemia HL60 cells revealed significant dynamic alterations in both intracellular and extracellular release of methionine pathway intermediates during apoptotic progression. The quantification method provides a robust tool for investigating the regulation and functions of methionine metabolism across basic research and clinical applications.

Keywords:  5′-MTA; Apoptosis; Methionine metabolism; SAH; SAM; UHPLC-MS/MS

DOI:  https://doi.org/10.1016/j.chroma.2025.466036