bims-mascan 2025-10-19 papers

bims-mascan

Biomed News

on Mass spectrometry in cancer research

Issue of 2025–10–19
nineteen papers selected by
Giovanny Rodríguez Blanco, Uniklinikum Graz

Aged mice exhibit widespread metabolic changes but preserved major fluxes.
High-Coverage Immunopeptidomics Using timsTOF Mass Spectrometers with Thunder-DDA-PASEF Boosted by MS2Rescore.
Design and Analysis of Untargeted Metabolomics Experiments.
Mass Spectrometry-Based Proteomic Analysis of Lysosome-Enriched Fractions.
Multiplexed Nanoparticle Protein Corona Enables Accurate and Precise Deep Plasma Proteomics.
Lysosomal Immunoprecipitation (LysoIP) from Cells and Tissues for Metabolomic and Proteomic Analyses.
A Universal Spectrum Annotator for Complex Peptidoforms in Mass Spectrometry-Based Proteomics.
Characterization of Lipid Epi-Metabolites/Reactions as Diagnostic Biomarkers for Idiopathic Pulmonary Fibrosis by Lipidepifind.
High Dynamic Range Peptide Mass Spectrometry Using Segmented Precursor Ion Accumulation.
Sample preparation optimization for metabolomics and lipid profiling from a single plasma and liver tissue based on NMR and UHPLC-MS.
Analysis of Crosstalk Between Pathogens and Immune System in Human Airway Mucus via Machine Learning-Enhanced DIA Mass Spectrometry.
Targeted Analyses of MHC-I Peptides Using TOMAHAQ.
The role of fatty acid oxidation in the tumor microenvironment: Implications for cancer progression and therapeutic strategies.
RAS mutations and colorectal cancer metabolism: a metabolomic analysis of tissue samples.
Decoding adult murine pancreatic islet cell diversity through cell type-resolved proteomics and phosphoproteomics.
Glutamine: a new strategy for targeted metabolic therapy in the tumor microenvironment.
Harmonized peptide libraries enable practical biofluid selection for developing biomarker assays.
SLC25A45 is required for mitochondrial uptake of methylated amino acids and de novo carnitine biosynthesis.
Now you serine, now you don't.

Cell Metab. 2025 Oct 16. pii: S1550-4131(25)00394-8. [Epub ahead of print]

Aged mice exhibit widespread metabolic changes but preserved major fluxes.

Connor S R Jankowski, Laith Z Samarah, Michael R MacArthur, Sarah J Mitchell, Daniel R Weilandt, Craig J Hunter, Xianfeng Zeng, Melanie R McReynolds, Joshua D Rabinowitz.

  Metabolic dysregulation is a hallmark of aging. Here, we investigate in mice age-induced metabolic alterations using metabolomics and stable isotope tracing. Circulating metabolite fluxes and serum and tissue concentrations were measured in young and old (20-30 months) C57BL/6J mice, with young obese (ob/ob) mice as a comparator. For major circulating metabolites, concentrations changed more with age than fluxes, and fluxes changed more with obesity than with aging. Specifically, glucose, lactate, 3-hydroxybutryate, and many amino acids (but notably not taurine) change significantly in concentration with age. Only glutamine circulatory flux does so. The fluxes of major circulating metabolites remain stable despite underlying metabolic changes. For example, lysine catabolism shifts from the saccharopine toward the pipecolic acid pathway, and both pipecolic acid concentration and flux increase with aging. Other less-abundant metabolites also show coherent, age-induced concentration and flux changes. Thus, while aging leads to widespread metabolic changes, major metabolic fluxes are largely preserved.

Keywords:  aging; fluxomics; glutamine; metabolic flux; metabolism; metabolomics; obesity; stable isotope tracing; systemic metabolism

DOI:  https://doi.org/10.1016/j.cmet.2025.09.009
Methods Mol Biol. 2026 ;2980 115-155

High-Coverage Immunopeptidomics Using timsTOF Mass Spectrometers with Thunder-DDA-PASEF Boosted by MS2Rescore.

David Gomez-Zepeda, Julian Beyrle, Annica Preikschat, Arthur Declercq, Yannic Chen, Ralf Gabriels, Lennart Martens, Ute Distler, Stefan Tenzer.

  Major histocompatibility complex (MHC, or human leukocyte antigen, HLA) peptide ligands can be exploited to develop immunotherapies targeting immunogenic disease-specific immunopeptides, such as virus- or cancer mutation-derived peptides. Liquid chromatography coupled with mass spectrometry (LC-MS)-based immunopeptidomics is the gold standard for identifying MHC ligands. We previously optimized a workflow enabling the identification of more than 10,000 MHC class I ligands per cell line. This process comprises three major steps: (I) a high-recovery immunopeptidome enrichment, (II) an optimized MS acquisition in the timsTOF Pro called Thunder-Data-Dependent Acquisition with Parallel Accumulation-SErial Fragmentation (Thunder-DDA-PASEF), and (III) peptide identification using PEAKS XPro boosted by MS2Rescore data-driven rescoring. Here, we describe our workflow for deep-coverage immunopeptidomics step-by-step, from sample preparation to data analysis and validation.

Keywords:  Human leucocyte antigen; Immunopeptidomics; Immunoprecipitation; Major histocompatibility complex; Mass spectrometry; Re-scoring; Sample preparation

DOI:  https://doi.org/10.1007/978-1-0716-4832-2_5
Curr Protoc. 2025 Oct;5(10): e70232

Design and Analysis of Untargeted Metabolomics Experiments.

Zane G Long, Rachel W Martin.

  Untargeted metabolomics is a powerful approach for identifying small molecules from highly complex mixtures, such as biological tissues or environmental samples. This technology enables the relatively fast and inexpensive identification of metabolites in situations where many or most of the chemical species are unknown before the experiment begins. This situation often arises in biomedical and environmental research, as well as in the case described here, the discovery of metabolites from plants. The objective of this paper is to provide practical and technical knowledge about untargeted metabolomics using mass spectrometry as the detection method. Specifically, we focus on liquid chromatography tandem mass spectrometry (LC-MS/MS). We provide a consolidated protocol for new users, serving as a starting point for experimental design, data collection, and data analysis. We explain the terminology and technical details in the context of real experiments and samples. In addition to general background information, step-by-step protocols are provided for sample preparation, liquid chromatography-tandem mass spectrometry data collection, and data analysis, utilizing readily available and widely used software. The chosen example data set is based on plant metabolites with varying chemical properties; however, the approach is applicable to essentially any complex biological sample. © 2025 The Author(s). Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: Sample preparation for LC-MS/MS Support Protocol 1: Preparing a 'master mix' sample for assessment of liquid chromatography and sensitivity Basic Protocol 2: LC-MS/MS data collection Basic Protocol 3: Data analysis using the software MSConvert, MZMine, and SIRIUS Support Protocol 2: Using the MZMine batch file.

Keywords:  LC‐MS/MS; electrospray ionization; mass spectrometry; plant metabolites; untargeted metabolomics

DOI:  https://doi.org/10.1002/cpz1.70232
Methods Mol Biol. 2026 ;2976 103-118

Mass Spectrometry-Based Proteomic Analysis of Lysosome-Enriched Fractions.

Sara Bonini, Pathma Muthukottiappan, Dominic Winter.

  Lysosomes are the main degradative organelles of most mammalian cells, playing a crucial role in nutrient metabolism and acting as a signaling hub. Due to the low abundance of lysosomes, several enrichment techniques have been developed to facilitate their investigation. Combination of these approaches with mass spectrometry-based proteomics presents a powerful tool for the unbiased characterization of the lysosomal proteome under various conditions. Different enrichment strategies result in lysosome-enriched fractions with unique characteristics, varying, for example, in protein concentration and buffer composition. Therefore, in order to obtain optimal results, the subsequent strategy for proteomics sample preparation has to be adapted. Here, we describe different methods for the processing of lysosome-enriched fractions for mass spectrometry-based proteomic analyses and provide guidance for the selection of the appropriate strategy. We further elaborate on typical parameters for mass spectrometric analysis and data processing.

Keywords:  Lysosomes; Mass spectrometry; Proteomics; RapiGest; SP3; Urea

DOI:  https://doi.org/10.1007/978-1-0716-4844-5_9
J Proteome Res. 2025 Oct 17.

Multiplexed Nanoparticle Protein Corona Enables Accurate and Precise Deep Plasma Proteomics.

Ting Huang, Jian Wang, Alexey Stukalov, Simion Kreimer, Xiaoyan Zhao, Lee S Cantrell, Xiaoyuan Zhou, Adam Brewer, Giang Ho, Fredric Murolo, Kevin Quach, Mike Figa, Seth Just, Gabriel Castro, Eltaher Elgierari, Ryan W Benz, Khatereh Motamedchaboki, Serafim Batzoglou, Omid C Farokhzad, Jennifer E Van Eyk, Asim Siddiqui.

  The Proteograph Product Suite, a multiplexed nanoparticle (NP) protein corona-based workflow, substantially improves the depth of detection of proteins by mass spectrometry (MS) by compressing the dynamic range of protein abundances. Here, we evaluate its quantitative performance and suitability for large-scale studies. Using multispecies spike-in experiments, we assessed fold change accuracy, linearity, precision, and the lower limit of quantification (LLOQ) across multiple MS platforms. Combined with the Orbitrap Astral MS, the Proteograph XT assay enabled identification of more than 7,000 plasma proteins. In mixed-species dilution experiments, fold change accuracy was preserved, with Proteograph quantifying 3.5 times more proteins than the Neat plasma workflow at the same fold change error threshold. Similar accuracy was observed with the Orbitrap Exploris 480 MS, and we also demonstrate that different proteome backgrounds do not impact the accuracy. Data produced with NPs from the four distinct NP batches (each supporting >100,000 assays) showed only a 4% increase in protein intensity CV across batches. Together, these results demonstrate that the Proteograph Product Suite provides depth as well as quantitative accuracy and precision to power new biomarker discovery and biological understanding in population-scale plasma proteomics cohorts.

Keywords:  LC-MS; Proteograph Product Suite; nanoparticle; plasma proteomics; precision; protein corona; quantification accuracy

DOI:  https://doi.org/10.1021/acs.jproteome.5c00729
Methods Mol Biol. 2026 ;2976 85-102

Lysosomal Immunoprecipitation (LysoIP) from Cells and Tissues for Metabolomic and Proteomic Analyses.

Nouf N Laqtom, Monther Abu-Remaileh.

  Lysosomes, known for degrading biomolecules and damaged cellular components, are now recognized as signaling hubs for nutrient sensing and metabolic adaptation, and their dysfunction is implicated in diseases including cancer and neurodegeneration. To understand the composition of the lysosome, the dynamic behavior of its contents, and its specific roles in health and disease, we describe a lysosomal immunoprecipitation method, termed "LysoIP," that enables the isolation of intact lysosomes from cultured cells and mouse tissues. This method utilizes a lysosome-localized 3xHA epitope tag (LysoTag) and a simple, yet robust organelle immunoprecipitation workflow. Isolated lysosomes are extracted with optimized buffers to allow the efficient retrieval of lysosomal proteins, polar metabolites, and lipids, maintaining compatibility with downstream liquid chromatography and mass spectrometry (LC-MS) analyses.

Keywords:  LC-MS analyses; LysoIP; LysoTag; LysoTag mouse; Lysosomes; Metabolomics; Proteomics; TMEM192

DOI:  https://doi.org/10.1007/978-1-0716-4844-5_8
Anal Chem. 2025 Oct 14.

A Universal Spectrum Annotator for Complex Peptidoforms in Mass Spectrometry-Based Proteomics.

Douwe Schulte, Rien W Leuvenink, Shelley Jager, Albert J R Heck, Joost Snijder.

Accurate and comprehensive peptide spectrum annotation is a crucial step to interpreting mass spectrometry-based proteomics data. While peak assignment in peptide fragmentation spectra is central to a broad range of proteomics applications, current tools tend to be specialized to a specific task. Here, we present a more comprehensive interactive graphical tool (Annotator), along with the underlying codebase written in Rust (rustyms). Annotator enables unified spectrum annotation for bottom-up, middle-down, top-down, cross-linked, and glycopeptide fragmentation mass spectra from all fragmentation methods, including all ion types: a/b/c, x/y/z, d/v/w, and immonium ions. The Annotator integrates all known post-translational modifications from common databases and additionally allows for the definition of custom fragmentation models and modifications. Modifications allow for diagnostic fragment ions, site-specific neutral losses, and multiple breakage sites for cross-linkers. The underlying library used for the theoretical fragmentation and matching is based on the unified peptidoform notation ProForma 2.0 and is made available as a Rust library with Python bindings. This enables spectrum annotation in an interactive, graphical interface of diverse and complex peptidoforms across the broad range of mass spectrometry-based proteomics applications.

DOI: https://doi.org/10.1021/acs.analchem.5c02832
Anal Chem. 2025 Oct 17.

Characterization of Lipid Epi-Metabolites/Reactions as Diagnostic Biomarkers for Idiopathic Pulmonary Fibrosis by Lipidepifind.

Xinguang Liu, Yunfan Zhao, Yang Xie, Yanmin Shi, Jianya Yang, Yan Du, Jinyan Wu, Yitong Gao, Ang Zhang, Jiansheng Li.

Lipidomics enables comprehensive profiling of lipid species, providing a powerful approach for studying disease pathogenesis and identifying biomarkers. Conventional lipidomics workflows rely on the annotation of lipid species using curated biochemical databases. However, many unidentified lipids are absent from these databases, which limits the discovery of functional or pathological biomarkers. To address this limitation, we developed a method to systematically identify structurally modified lipids, referred to as epi-metabolites, in biological samples. First, 1479 parent lipids were identified across different biological matrices using liquid chromatography-high-resolution mass spectrometry. Next, the MS characteristics of all potential lipid epi-metabolites were predicted using a metabolic network expansion strategy comprising 62 reaction types and were subsequently screened in raw test sample data. To ensure reproducibility and improve analytical efficiency, we implemented this workflow in a user-friendly Shiny app (https://xinguang-liu.shinyapps.io/metabolite_mz_predictor/) and an open-source R package, Lipidepifind (https://github.com/Xinguang-Liu/Lipidepifind). Lipid epi-metabolites were then identified using four validation criteria: MS/MS analysis, retention order filtering, retention time calibration, and collision cross-section validation. Finally, differential structural modifications and putative enzyme-mediated reactions were characterized through multivariate statistics and epi-metabolic reaction enrichment analysis. We demonstrated the utility of this approach in idiopathic pulmonary fibrosis (IPF), identifying 725 lipid epi-metabolites in patient serum. Two enriched lipid oxidative cleavage reactions were observed, and two epi-metabolite biomarkers, phosphatidylcholine (16:0/9:0 (CHO)) and (16:0/5:0 (COOH)), were identified in IPF patients. This method outperformed conventional database-based strategies in matching and identifying lipid epi-metabolites and revealed differential lipid modifications and enzymatic processes in IPF.

DOI: https://doi.org/10.1021/acs.analchem.5c00277
Anal Chem. 2025 Oct 15.

High Dynamic Range Peptide Mass Spectrometry Using Segmented Precursor Ion Accumulation.

Maria C Panepinto, Francesca Minicozzi, Paolo Cifani.

Limited sensitivity and depth of proteome sampling in experiments using data-dependent acquisition (DDA) mass spectrometry are usually attributed to an insufficient rate of fragmentation spectra acquisition relative to the number of coeluting potential targets. Here, we demonstrated that limited sensitivity and dynamic range of MS1 scans reduce detection of low-intensity ions and thus their selection for fragmentation. As abundant ions occupy a large fraction of the ion accumulation capacity, we sought to improve MS1 detection of rare analytes by an easily implementable strategy based on gas-phase segmentation of the MS1 scan range, followed by coaccumulation and detection of all ions. The quadrupolar isolation windows used to segment the MS1 scan range are designed to transmit, on average, an equal number of charges, consistent with the parameter used by many recent mass spectrometers to regulate ion trap filling. This strategy, which we named high dynamic range MS1 (HDR-MS1), reduces the contribution of abundant ions to reaching the maximum ion capacity. As a result, HDR MS1 showed improved dynamic range and sensitivity compared to conventional full-range scans, resulting in a higher number of peptides and protein identifications under identical MS2 parameters, less redundant precursor ion sampling, and a higher rate of quantified precursor ions. HDR MS1 scans are compatible with any DDA precursor selection filter and MS2 parameter, and the generated files can be analyzed using any software for peptide-spectral matching and quantification.

DOI: https://doi.org/10.1021/acs.analchem.5c04349
J Pharm Biomed Anal. 2025 Sep 29. pii: S0731-7085(25)00514-X. [Epub ahead of print]268 117173

Sample preparation optimization for metabolomics and lipid profiling from a single plasma and liver tissue based on NMR and UHPLC-MS.

Chenxi Wang, Yan Gao, Ruibing Chen, Yuefen Lou.

  Currently, the majorty of metabolomics studies rely on the use of a single analytical platform, either NMR or MS, which hampers the ability to conduct an unbiased and comprehensive analysis. However, the use of multiple platforms poses an additional challenge: the limited sample material. Consequently, it is highly desirable to develop comprehensive, effective and sample-conserving procedures for metabolite extraction. In this study, we presented pretreatment strategies enabling sequential NMR and multi-LC-MS (UHPLC-Q-Orbitrap MS, and UHPLC-QqQ MS) platform analysis using a single plasma and liver tissue sample. For the plasma sample, the biphasic CHCl3/MeOH/H2O method was suitable for polar and lipid extraction after NMR-based metabolomics analysis, in terms of the number of annotated metabolites, reproducibility, and the amount of sample needed. While for the liver sample, the two-step extraction involving CHCl3/MeOH followed by MeOH/H2O was recommended. In this method, resuspension of dried lipid extracts was used for lipidomics, and polar extracts were transferred for further untargeted metabolic profiles by UHPLC-Q-Orbitrap MS following an NMR-based metabolomics study. Finally, the proposed preparation protocols were evaluated for robustness, and the identification data were used to generate a comprehensive metabolic map for plasma and liver tissue. In summary, this study provides a unique sample preparation procedure for two biological specimens, allowing for multi-platform analysis using a single sample. By adopting this approach, comprehensive metabolic profiling can be conducted to detect metabolic alterations under different physiological or pathological conditions.

Keywords:  (1)H NMR; A single sample; Lipidomics; Metabolomics; Sample preparation optimization; UHPLC-MS

DOI:  https://doi.org/10.1016/j.jpba.2025.117173
Proteomics Clin Appl. 2025 Oct 17. e70026

Analysis of Crosstalk Between Pathogens and Immune System in Human Airway Mucus via Machine Learning-Enhanced DIA Mass Spectrometry.

Rembert Pieper, Vinod Krishna, Thomas N Gaitanos, Jeroen Aerssens.

   PURPOSE: Peptide-centric machine learning enhanced (PCML) data-independent acquisition tandem mass spectrometry (LC-MS/MS-DIA) matches low-abundance MS fragmentation spectra to in silico predicted peptide spectra deduced from libraries of customized protein sequences. The study's goal was to determine proteomic depth of coverage in microbial pathogen-containing clinical samples using that method.
EXPERIMENTAL DESIGN: We employed a published machine learning method based on neural networks (Dia-NN) to the LC-MS/MS analysis of sputum protein digests derived from patients with lung infections.
RESULTS: Nearly 6800 proteins in total and 1530 proteins of microbial origin were identified from single experiments, with CVs of protein quantities among technical replicates as low as 0.12. Conventional spectral library searches of data from these experiments yielded less than 1600 and 60 protein identifications, respectively. Samples of two patients revealed colonization by pathogens difficult to clear from chronically infected lungs, Pseudomonas aeruginosa and Stenotrophomonas maltophilia. Abundant virulence factors in the datasets were the insulin-cleaving metalloproteinase IcmP (P. aeruginosa) and an inducer of human interleukin-10 expression (S. maltophilia). Each bacterium showed signs of adaptation to a hostile milieu, such as the expression of systems to generate energy anaerobically and the acquisition of host-sequestered metals.
CONCLUSIONS AND CLINICAL RELEVANCE: This work constitutes a step forward for protein-centered translational medicine on infectious diseases.
SUMMARY: We demonstrate excellent depth of proteome coverage and experimental repeatability for low-abundance pathogen proteomes in human airway secretions via data-independent acquisition liquid chromatography tandem mass spectrometry leveraging machine learning for spectral analysis. The host's sputum proteome was also profiled, allowing inferences of immune defense mechanisms against pathogens. This proof-of-principle study shows the opportunity to gain insights into respiratory disease burdens and bacterial virulence by directly analyzing clinical specimens and the potential for biomarker discovery and pharmacodynamic response monitoring in interventional studies related to respiratory tract infections.

Keywords:  Pseudomonas aeruginosa; clinical proteomics; data‐independent acquisition; machine learning; respiratory tract infection

DOI:  https://doi.org/10.1002/prca.70026
Methods Mol Biol. 2026 ;2980 97-114

Targeted Analyses of MHC-I Peptides Using TOMAHAQ.

Marlene L Heberling, Sam Pollock, Qui T Phung, Chris Rose, Jennie R Lill.

  Advances in several key technologies, including major histocompatibility (MHC) peptidomics, have significantly enhanced our understanding of basic immune-regulatory mechanisms and the identification of T-cell receptor targets for the development of immune-therapeutics. Isolating and accurately quantifying MHC-bound peptides from cells and tissues enables the characterization of dynamic changes in the MHC peptidome due to cellular perturbations. However, the current multistep analytical process is challenging, and improvements in throughput, sensitivity, and reproducibility would enable rapid characterization of multiple conditions in parallel.In this chapter, we describe a robust, sensitive, and quantitative method for enriching peptides derived from MHC-I complexes from a variety of cell lines, including challenging adherent lines such as MC38, in a semiautomated fashion using reusable, dry-storage, customized antibody cartridges. This method allows a researcher, with minimal hands-on time, to perform up to 96 simultaneous enrichments reproducibly in a single day, achieving a quality level comparable to that of a manual workflow.TOMAHAQ (Triggered by Offset, Multiplexed, Accurate-mass, High-resolution, and Absolute Quantification) is a targeted mass spectrometry technique that combines sample multiplexing and high sensitivity to characterize neoepitopes displayed on MHC-I by tumor cells and to quantitatively assess the influence of neoantigen expression and induced degradation on neoepitope presentation. This unique combination of robust, semiautomated MHC-I peptide isolation and high-throughput multiplexed-targeted quantitation allows for both the routine analysis of over 4000 unique MHC-I peptides from 250 million cells using nontargeted methods, as well as quantitative sensitivity down to the low amol/μL level using TOMAHAQ targeted MS. The protocol and tips on how to execute are outlined below.

Keywords:  Absolute quantification (TOMAHAQ); Accurate-mass; Affinity purification; Cancer immunology; High-resolution; Immunopeptidomics; Major histocompatibility complex class I (MHC-I); Mass spectrometry; Multiplexed; Neoantigen; Semi-automation; Triggered by offset

DOI:  https://doi.org/10.1007/978-1-0716-4832-2_4
Biochim Biophys Acta Rev Cancer. 2025 Oct 10. pii: S0304-419X(25)00216-1. [Epub ahead of print]1880(6): 189474

The role of fatty acid oxidation in the tumor microenvironment: Implications for cancer progression and therapeutic strategies.

Nasot Rashed, Wenbin Liu, Xiangjian Luo.

  Fatty acid oxidation (FAO), or β-oxidation, is a catabolic process that breaks down fatty acids into acetyl-CoA. FAO plays a pivotal role in the metabolic reprogramming of cancer cells and the tumor microenvironment (TME), serving as a crucial energy source that sustains cellular functions under conditions of nutrient deprivation and metabolic stress. This process significantly influences cancer cell survival, proliferation, metastasis, and therapeutic resistance. In this review, we discuss the biological functions of FAO in cancer cells, immune cells, and stromal cells, with a particular focus on its regulatory role in tumor progression and therapy resistance. Furthermore, we explore FAO inhibitors and emerging therapeutic strategies targeting FAO as a potential approach to disrupting tumor metabolism and enhancing cancer treatment efficacy.

Keywords:  Cancer progression; Fatty acid oxidation; Immune cells; Stromal cells; Therapeutic resistance; Tumor microenvironment

DOI:  https://doi.org/10.1016/j.bbcan.2025.189474
BMC Cancer. 2025 Oct 14. 25(1): 1580

RAS mutations and colorectal cancer metabolism: a metabolomic analysis of tissue samples.

Jianjiong Li, Buyuan Dong.



Keywords:  Colorectal cancer; Diagnostic biomarkers; Metabolomics; RAS mutations; Therapeutic targets

DOI:  https://doi.org/10.1186/s12885-025-14994-0
Commun Biol. 2025 Oct 17. 8(1): 1483

Decoding adult murine pancreatic islet cell diversity through cell type-resolved proteomics and phosphoproteomics.

Marvin Thielert, Adrian Villalba, Vincenth Brennsteiner, Maria Wahle, Constantin Ammar, Andreas-David Brunner, Alexis Fouque, Chloé Lourenço, Masaya Oshima, Latif Rachdi, Willem Staels, Matthias Mann, Raphaël Scharfmann.

Islets of Langerhans are micro-organs scattered throughout the pancreas. They are composed of insulin-producing beta cells, glucagon-producing alpha cells, and somatostatin-producing delta cells. While their transcriptome has been extensively analyzed, protein-level information remains limited due to cell scarcity and purification challenges. Here, we combine cell sorting with highly sensitive mass spectrometry to create the first in-depth proteomic resource of pancreatic islet cells. We achieved a depth exceeding 6000 proteins per endocrine cell population, discovering new cell type-enriched ones. Deep proteomics profiling demonstrated that all three endocrine cell types were inflamed upon interferon gamma (IFNγ) treatment, a mediator of autoimmune damage in type 1 diabetes. Resolving the phosphoproteomic landscape of alpha, beta and delta cells with more than 7000 unique phosphosites per cell type provided insights into cell-specific signaling. This omics dataset offers a valuable resource for understanding pancreatic islet biology in health and disease.

DOI: https://doi.org/10.1038/s42003-025-08918-8
Cell Death Discov. 2025 Oct 13. 11(1): 459

Glutamine: a new strategy for targeted metabolic therapy in the tumor microenvironment.

Haixu Lv, Xiao Han, Yuanshuang Yang, Jianfeng Shen, Yixuan Yin, Yu Liu.

In the tumor microenvironment, glutamine has a profound impact not only on the growth, metabolism, metastasis, and invasion of tumor cells but also on the survival and function of immune cells and the behavior of nonimmune cells. Given the limited amount of glutamine in the tumor microenvironment, there is a competitive relationship between tumor and nontumor cells. Owing to the metabolic reprogramming of tumor cells, many nutrients, including glutamine, are necessary for tumor cells to maintain their rapid growth and high metabolic demand. Therefore, tumor cells are in a superior position to compete for glutamine. These findings provide solid theoretical support for targeting glutamine metabolism for anticancer therapy. This review summarizes the importance and necessity of glutamine for tumor cells and nontumor cells in the tumor microenvironment. According to the mechanism of action of glutamine in tumor cells and the regulatory mechanism of related signaling pathways, the currently developed anticancer drugs that target glutamine metabolism are categorized on a scientific basis, and the importance of basic medicine applied in clinical medicine is emphasized. This review not only provides anticancer information for clinicians but also brings hope to cancer patients.

DOI: https://doi.org/10.1038/s41420-025-02767-4
Mol Cell Proteomics. 2025 Oct 12. pii: S1535-9476(25)00185-9. [Epub ahead of print] 101086

Harmonized peptide libraries enable practical biofluid selection for developing biomarker assays.

Katelyn B Brusach, Ariana E Shannon, Alex W Joyce, Jessica M Quimby, Brian C Searle.

Selecting the optimal biofluid for accurate biomarker assessment is vital to an informative clinical assay. However, in the initial stages of candidate biomarker discovery, the biologically appropriate biofluid might be unclear. To resolve this dilemma, we demonstrate a mass spectrometry-based workflow where paired urine, plasma, and serum samples are processed in parallel, creating biofluid-specific peptide libraries. These libraries are then harmonized to monitor consistent peptides and transitions, enabling cross-fluid normalization and quantitative comparisons. We also present a reference dataset, "CATalog," to aid in determining which biofluid to pursue based on protein relative abundance in healthy feline urine, plasma, and serum. Using this workflow and database, we explore the interchangeability of blood biofluid proteins compared to urinary proteins relating to sample processing, relative protein quantification, and clinical application. Our results suggest that when processed correctly, urine could sometimes represent blood biofluid proteins without requiring venipuncture or sample depletion of highly abundant proteins.

DOI: https://doi.org/10.1016/j.mcpro.2025.101086
Mol Cell. 2025 Oct 10. pii: S1097-2765(25)00703-8. [Epub ahead of print]

SLC25A45 is required for mitochondrial uptake of methylated amino acids and de novo carnitine biosynthesis.

Marilia M Dias, Martin S King, Engy Shokry, Sergio Lilla, Nikki Paul, Peter Thomason, Sara Zanivan, David Sumpton, Edmund R S Kunji, Thomas MacVicar.

  Methylated amino acids accumulate upon the degradation of methylated proteins and are implicated in diverse metabolic and signaling pathways. Disturbed methylated amino acid homeostasis is associated with cardiovascular disease and renal failure. Mitochondria are core processing hubs in conventional amino acid metabolism, but how they interact with methylated amino acids is unclear. Here, we reveal that the orphan mitochondrial solute carrier 25A45 (SLC25A45) is required for the mitochondrial uptake of methylated amino acids. SLC25A45 binds with dimethylarginine and trimethyllysine but has no affinity for unmethylated arginine and lysine. A non-synonymous mutation of human SLC25A45 (R285C) stabilizes the carrier by limiting its proteolytic degradation and associates with altered methylated amino acids in human plasma. Metabolic tracing of trimethyllysine in cancer cells demonstrates that SLC25A45 drives the biosynthesis of the key amino acid derivative, carnitine. SLC25A45 is therefore an essential mediator of compartmentalized methylated amino acid metabolism.

Keywords:  SLC25; carnitine; metabolism; metabolite transport; methylated amino acids; mitochondria; solute carriers

DOI:  https://doi.org/10.1016/j.molcel.2025.08.018
Trends Pharmacol Sci. 2025 Oct 11. pii: S0165-6147(25)00225-1. [Epub ahead of print]

Now you serine, now you don't.

Robert B Cameron, Nia G Hammond, Brandon Faubert.

  Cancer cells alter metabolic programs to support uncontrolled growth and proliferation. A new study from Scott and colleagues directly examined tumor metabolism in glioblastoma patients and discovered increased import of the amino acid serine. Excitingly, limiting serine uptake enhanced the effectiveness of chemoradiation in preclinical models of glioblastoma.

Keywords:  glioblastoma; metabolism; stable isotope tracing

DOI:  https://doi.org/10.1016/j.tips.2025.10.001