bims-mascan 2026-09-20 papers

bims-mascan

Biomed News

on Mass spectrometry in cancer research

Issue of 2026–09–20
eighteen papers selected by
Giovanny Rodríguez Blanco, Uniklinikum Graz

Improving Lipid Identification and Quantification: Chromatogram Deconvolution for LC-MS/MS Workflows.
Cross-Platform Comparison of Chemoproteomics Workflows: Orbitrap-TMT Versus timsTOF-diaPASEF.
BrIS: Visualizing Internal Standards at the MS1 Level via Bromine Fingerprint for Sensitive and Robust Proteomics Quality Control.
Combined Lipidomic and Metabolomic Analyses on Cardiac Organoids.
Protocol for targeted analysis of oxylipins in rat plasma and mouse macrophage samples by high-resolution UHPLC-MS/MS.
A library of experimental collision cross sections for food, beverage and plant metabolites generated by reversed-phase liquid chromatography coupled to travelling-wave ion mobility and high-resolution mass spectrometry.
Column switching liquid chromatography dual mass spectrometry system for simultaneous untargeted metabolomics and targeted exposomics.
Plasma Metabolomic and Lipidomic Profiling in Early-Stage Psychosis.
N-Alkylpyridinium sulfonates as versatile scout compounds for multi-mode highly targeted metabolomics: Application to Gammarus fossarum.
Enzyme-Metabolite Network Analysis of Endometrial Cancer-Derived Extracellular Vesicles Through Integrated Proteomics and Metabolomics.
Aspiration Patch Proteomics Enables CE-ESI-MS Proteotyping of Identified Single Neurons in Intact Brain Tissue.
Quantitative proteomics reveals coordinated changes in the proteome during replicative senescence.
An Automated, Ventana Discovery Platform-based Imaging Workflow for Simultaneous Quantification of B Cells, Plasma Cells, and Plasmablasts in FFPE Human Tissues.
Targeting lipid metabolic vulnerabilities with small-molecule inhibitors in acute myeloid leukemia: Emerging insights and therapeutic opportunities.
What's next for metabolomics?
The Crosstalk Between YAP/TAZ and Cancer Metabolism: From Mechanistic Insights to Drug Discovery.
Integrating proteomics and metabolomics to reveal MAT2A for metabolic reprogramming in non-small cell lung cancer cells.
MeTime: an R package for reproducible longitudinal metabolomics data analysis.

Bioinformatics. 2026 Sep 18. pii: btag695. [Epub ahead of print]

Improving Lipid Identification and Quantification: Chromatogram Deconvolution for LC-MS/MS Workflows.

Felix Niedermaier, Denise Wolrab-Frühauf, Robert Ahrends, Dominik Kopczynski.

   MOTIVATION: Lipidomics relies on mass spectrometry-based workflows to identify and quantify complex lipid species. Due to the modular architecture of lipids, including headgroups, backbones, and fatty acyl chains, distinct precursor ions often produce isobaric or identical fragment ions. This problem is amplified in data-independent acquisition (DIA), where wide isolation windows (e.g., 25 Da) allow co-eluting precursors with different m/z values to generate highly chimeric MS/MS spectra. Consequently, fragments originating from multiple precursors, including isobars, isomers, and lipid-class-specific ions, are merged into a single MS/MS spectrum. Current lipid identification strategies often process such chimeric spectra in an uncontrolled manner, assigning them to one or more candidate lipids, thereby increasing false-positive identifications.
RESULTS: Here, we introduce an algorithm that deconvolutes chimeric MS/MS spectra and chromatograms by exploiting their temporal correlation with associated precursor chromatographic profiles, independent of elution peak shape. Using simulated and real experimental lipidomics data, we demonstrate that this approach substantially improves lipid fragment assignment, reduces false-positive identifications, and enables more reliable fragment-level quantification, leading to more robust downstream statistical analyses and biological interpretations.
AVAILABILITY AND IMPLEMENTATION: Source code of the software library: GitLab (Apache 2.0 License): https://gitlab.com/computational-multiomics/mixture-model-deconvolution; Data: Zenodo (Apache 2.0 License): https://doi.org/10.5281/zenodo.21218594.
SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Keywords:  chemoinformatics; chromatogram deconvolution; lipidomics; mass spectrometry; spectral reconstruction

DOI:  https://doi.org/10.1093/bioinformatics/btag695
Proteomics. 2026 Sep 15. e70179

Cross-Platform Comparison of Chemoproteomics Workflows: Orbitrap-TMT Versus timsTOF-diaPASEF.

Ursula M Glocker, Michael Steidel, Henrik Hammarén, Carola Doce, Katrin Marcus, Nico Zinn, Marcus Bantscheff, H Christian Eberl.

  Chemoproteomics aims to achieve precise and comprehensive quantification of protein-small molecule interactions, yet methodological comparisons across quantitative proteomics workflows remain scarce. Here, we systematically benchmark tandem mass tag data-dependent acquisition (TMT-DDA) on Orbitrap Exploris/Eclipse instruments against label-free data-independent acquisition parallel accumulation-serial fragmentation (LFQ-diaPASEF) on a timsTOF Pro 2 mass spectrometer when applied for 2-dimensional thermal proteome profiling (2D-TPP) and Kinobeads-based chemoproteomics. Our findings demonstrate that TMT-DDA provided more confident detection of compound-induced thermal shifts despite having lower proteome coverage in high-complexity 2D-TPP datasets. In contrast, LFQ-diaPASEF excelled in low-complexity affinity enrichment experiments, achieving up to 63% broader total proteome coverage and comparable quantitative accuracy, even with ultra-short gradients. Additionally, we show that normalization strategies in DIA require careful selection to avoid artifacts when transforming IC50s into apparent dissociation constants (Kd apps). These findings emphasize that the trade-offs inherent to each platform critically impact chemoproteomics experiments and that instrument-method pairings should be selected based on experimental complexity, quantitative precision, data completeness needs, and throughput demands.

Keywords:  chemoproteomics; data‐dependent acquisition; data‐independent acquisition; mass spectrometry (MS); tandem mass tags

DOI:  https://doi.org/10.1002/pmic.70179
Angew Chem Int Ed Engl. 2026 Sep 15. e1708018

BrIS: Visualizing Internal Standards at the MS1 Level via Bromine Fingerprint for Sensitive and Robust Proteomics Quality Control.

Chenxin Li, Guoli Wang, Jiawei Fan, Bin Fu, Haoru Song, Chong Li, Jiale Li, Ying Zhang, Haojie Lu.

  Data fidelity in mass spectrometry (MS)-based proteomics demands stringent quality control, for which spiking internal standards into biological samples is a straightforward practice. Yet, conventional internal-standard tracking relies on MS/MS-dependent identification, which can be unavailable or unreliable under challenging analytical conditions. Herein, we introduce a suite of Brominated Internal Standards (BrIS) and a tailored scanning algorithm, BrScan-MS1, which exploits bromine isotopic fingerprints and conserved elution order of BrIS peptides to directly track them at the MS1 level and enable reliable retention time (RT) assignment. Across a DDA dilution series, BrScan-MS1 recognized all BrIS peptides in every BrIS-spiked replicate and provided consistent RT assignments. In long-term DIA analyses using a plasma matrix, BrIS showed greater RT stability and quantitative consistency than iRT peptides and enabled sensitive tracking of instrumental drift. Cross-platform analyses demonstrated robust BrIS-based RT calibration of endogenous peptides across LC-MS platforms. In single-cell proteomics involving three cell lines, BrIS enabled reliable tracking at low sample inputs while largely maintaining cell-line-specific proteomic patterns and showed a modest tendency to better preserve control-derived differential-expression patterns than iRT peptides. Together, BrIS and BrScan-MS1 provide a practical approach for quality control across diverse proteomics settings ranging from complex matrices to ultra-low-input samples.

Keywords:  MS1‐level recognition; bromine isotopes; internal standards; proteomics; quality control

DOI:  https://doi.org/10.1002/anie.1708018
Methods Mol Biol. 2027 ;3074 239-263

Combined Lipidomic and Metabolomic Analyses on Cardiac Organoids.

Lorenzo Fontanelli, Carolina Ferri, Adrian Florentin Suman, Elisa Ceccherini, Giovanni Signore, Fabio Anastasio Recchia, Silvia Rocchiccioli.

  Cardiac organoids are increasingly used to model human cardiac development and disease, but their small size often limits molecular characterization, especially if different approaches and protocols are necessary to extract and quantify metabolites and lipids. Here, we present a multistep workflow for combined targeted free amino-acid (FAA) based metabolomic and lipidomic profiling from a single pooled cardiac organoid sample. The protocol covers organoid harvesting, detergent-assisted lysis, and a modified Folch extraction that generates an organic phase for lipid analysis and an aqueous phase for FAA metabolite analysis. Lipids are quantified by Liquid Chromatography Electrospray Ionization Tandem Mass Spectrometry (LC-ESI-MS/MS) in Multiple Reaction Monitoring (MRM) mode using class-matched external standards and an internal standard to support calibration and reduce technical variability. Free amino acids and derivatives are analyzed from the same sample after filtration, drying, and AccQ-Tag derivatization, with norvaline as an internal standard. Together, this approach maximizes information yield from limited material and enables integrated analysis of metabolic and lipid pathways within the same biological specimen, facilitating organoid-based studies of cardiac maturation, disease modeling, and pharmacological responses.

Keywords:  Cardiac organoids; LC–MS/MS (MRM); Modified Folch extraction; Targeted lipidomics; Targeted metabolomics

DOI:  https://doi.org/10.1007/978-1-0716-5539-9_14
STAR Protoc. 2026 Sep 17. pii: S2666-1667(26)00487-9. [Epub ahead of print]7(4): 104834

Protocol for targeted analysis of oxylipins in rat plasma and mouse macrophage samples by high-resolution UHPLC-MS/MS.

Larissa R Diniz, Adriano B Chaves-Filho, Pedro H F Jordão, Rosangela S Santos, Marina T Botana, Johan Kolmert, Ana C A Zucão, Marteinn T Snaebjornsson, Eduardo M Reis, Almut Schulze, Britta Brügger, Craig E Wheelock, Sayuri Miyamoto.

  Oxylipins are bioactive oxygenated fatty acid derivatives that act as signaling mediators in diverse physiological and pathological processes. Here, we present a protocol for the simultaneous analysis of 125 oxylipins in rat plasma and mouse macrophage samples. We describe steps for preparing standards and calibration curves, extracting oxylipins, and performing ultra-high-performance liquid chromatography coupled to high-resolution tandem mass spectrometry (UHPLC-MS/MS). We also detail procedures for using staRoxy, an original R package for oxylipin abundance data analysis. For complete details on the use and execution of this protocol, please refer to Chaves-Filho et al.,1 Kolmert et al.2 and Yapici et al.3.

Keywords:  Mass Spectrometry; Metabolomics; Protocols in Metabolomics and Lipidomics

DOI:  https://doi.org/10.1016/j.xpro.2026.104834
J Chromatogr A. 2026 Sep 06. pii: S0021-9673(26)00763-6. [Epub ahead of print]1787 467437

A library of experimental collision cross sections for food, beverage and plant metabolites generated by reversed-phase liquid chromatography coupled to travelling-wave ion mobility and high-resolution mass spectrometry.

Vania Sáez, Fulvio Mattivi, Giorgio Zanoni, Pavel Solovyev, Urska Vrhovsek, Panagiotis Arapitsas.

  Collision cross section (CCS), considered an ion-specific physicochemical property derived from ion mobility spectrometry (IMS), has become a valuable orthogonal descriptor for metabolite characterisation. When coupled with liquid chromatography and high-resolution mass spectrometry, CCS enables a multidimensional analytical approach to address challenging metabolite annotation, particularly for isomeric compounds or when reference standards are unavailable. In food and plant metabolomics, where chemical diversity is vast and reference databases are limited, expanding experimental CCS libraries remains a priority. Here, using reversed-phase liquid chromatography hyphenated with travelling wave ion mobility spectrometry and high-resolution mass spectrometry (RPLC-TWIMS-HRMS), we present a comprehensive library of 597 TWCCSN2 values from 274 standard references, including commercial, non-commercial and in-house isolated compounds relevant to the wine, food and plant metabolome. High intra-and inter-day repeatability was established across 35 metabolites from diverse chemical classes, with 96.5% of the 171 paired measurements showing inter-software agreement within ±2.0% ΔCCS when processed in parallel using two commercial data processing software platforms. Evaluation of five machine learning-based CCS prediction tools against the experimental library revealed up to 68.9% of predicted values within ±3.0%ΔCCS, with chemical class-dependent performance highlighting the importance of continued expansion of experimental CCS resources for confident annotation in metabolomics workflows.

Keywords:  CCS library; Collision cross-section (CCS); Ion mobility spectrometry (IMS); Metabolite annotation; Travelling wave ion mobility (TWIMS)

DOI:  https://doi.org/10.1016/j.chroma.2026.467437
Nat Commun. 2026 Aug 14. pii: 9794. [Epub ahead of print]17(1):

Column switching liquid chromatography dual mass spectrometry system for simultaneous untargeted metabolomics and targeted exposomics.

Yuting Wang, Daidi Hou, Yuan Yuan, Pengwei Guan, Tiantian Chen, Xingyu Guo, Xin You, Xianzhe Shi, Xiaolin Wang, Qi Wang, Xinyu Liu, Guowang Xu.

Exposome-wide association studies (ExWAS) require the detection of metabolites and exposures with diverse chemical properties across wide concentration ranges, a task that typically demands multiple analytical methods. To address this challenge, we develop an integrated column-switching two-dimensional liquid chromatography-dual mass spectrometry (2DLC-dual-MS) system. This system employs a 2DLC setup to sequentially separate polar and non-polar compounds with log P ranging from -8 to 15. The separated fractions are directed via a three-way valve to a high-resolution MS (HRMS) and a triple quadrupole MS (TQMS), enabling simultaneous untargeted metabolome analysis and targeted quantification of 601 exposures. The method is particularly suited for the concurrent analysis of metabolome and exposome in human blood, where their concentrations typically differ by 2-3 orders of magnitude. In a demonstration application on lung adenocarcinoma ExWAS, the system exhibits good stability over more than 300 consecutive injections for both metabolome and exposome analysis, confirming its robustness for ExWAS applications.

DOI: https://doi.org/10.1038/s41467-026-76696-w
Neurosci Res. 2026 Sep 18. pii: S0168-0102(26)00109-4. [Epub ahead of print] 105122

Plasma Metabolomic and Lipidomic Profiling in Early-Stage Psychosis.

Shuji Kawaguchi, Kazuhiro Sonomura, Koko Ishizuka, Fumihiko Matsuda, Akira Sawa, Kun Yang.

  Metabolic alterations in early-stage psychosis may provide insights into disease pathophysiology and potential biomarkers. We performed targeted metabolomic and lipidomic profiling of plasma samples from 31 patients with early-stage psychosis (onset within 24 months) and 22 healthy controls using a liquid chromatography-mass spectrometry (LC-MS) platform. Of 523 compounds analyzed, 16 (3 metabolites, 13 lipids) were significantly altered in patients compared with controls, with a significant enrichment of glycerolipids (69%). Within patients, glycerolipids significantly correlated with symptom severity and cognitive performance. These findings highlight the involvement of glycerolipid metabolism in early psychosis and clinical outcomes.

Keywords:  Biomarkers; Glycerolipids; Lipidomics; Liquid chromatography-mass spectrometry; Metabolomics; Psychosis; Schizophrenia

DOI:  https://doi.org/10.1016/j.neures.2026.105122
J Chromatogr B Analyt Technol Biomed Life Sci. 2026 Sep 06. pii: S1570-0232(26)00380-6. [Epub ahead of print]1284 125291

N-Alkylpyridinium sulfonates as versatile scout compounds for multi-mode highly targeted metabolomics: Application to Gammarus fossarum.

Remy De Boni, Delphine Arquier, Sophie Ayciriex, Arnaud Chaumot, Davide Degli-Esposti, Olivier Geffard, Arnaud Salvador.

  Although targeted metabolomics using multiple reaction monitoring (MRM) offers high sensitivity, it struggles with multiplexing capacity and retention time drifts. Scout-triggered MRM (stMRM) overcomes these limitations by using reference molecules to dynamically frame the acquisition window. However, establishing comprehensive stMRM assays requires reliable and cost-effective scout compounds that are compatible with multi retention mode of liquid chromatography-mass spectrometry (LC-MS). This study evaluates N-alkylpyridinium sulfonates (NAPS) as versatile exogenous scouts for highly multiplexed stMRM. The chromatographic and ionization behaviours of NAPS were characterised across three stationary phases (reversed-phase C18, F5 and hydrophilic interaction liquid chromatography (HILIC)) in positive and negative electrospray ionization. Due to their zwitterionic structure, NAPS ionised efficiently in both polarities, thereby simplifying dual-polarity acquisitions. Using NAPS as retention-time-independent triggers, we developed a comprehensive multi-mode assay monitoring 559 metabolites. To validate this methodology, we investigated the physiological impact of silver (Ag) exposure on the digestive caeca of the sentinel amphipod Gammarus fossarum. Multivariate analysis revealed metabolic shifts. Mapping these alterations onto species-specific networks highlighted a pronounced disruption of the purine metabolism pathway, characterised by consistent downregulation of xanthine and related intermediate precursors. In conclusion, NAPS are highly effective dual-polarity scout compounds that simplify the multiplexing of stMRM assays. This analytical strategy is a reliable tool for capturing complex molecular responses to environmental stressors in ecotoxicology.

Keywords:  Ecotoxicology; Multi-mode chromatography; N-Alkylpyridinium sulfonate; Scout-trigerred MRM; Targeted metabolomics

DOI:  https://doi.org/10.1016/j.jchromb.2026.125291
Int J Mol Sci. 2026 Aug 28. pii: 7703. [Epub ahead of print]27(17):

Enzyme-Metabolite Network Analysis of Endometrial Cancer-Derived Extracellular Vesicles Through Integrated Proteomics and Metabolomics.

Giovanni Di Lorenzo, Feras Kharrat, Fabio Hollan, Valeria Capaci, Nour Balasan, Michelangelo Aloisio, Federica Caponnetto, Antonio Paolo Beltrami, Federico Romano, Giuseppe Ricci, Blendi Ura.

  Endometrial cancer (EC) is the most common gynecological malignancy in high-income countries. Extracellular vesicles (EVs) are key mediators of intercellular communication and metabolic reprogramming, but their molecular cargo in EC remains poorly characterized. EVs were isolated from four EC cell lines representing Type I and Type II subtypes (AN3CA, ISHIKAWA, HEC1A, and KLE). Untargeted metabolomics was performed by HILIC-LC-MS/MS, proteomics by data-independent acquisition (DIA) mass spectrometry, and multi-omics integration using MetaboAnalyst and OmicsNet. Metabolomic profiling identified 1463 annotated features and revealed significant differences among EC cell lines (PERMANOVA, p = 0.002). Twenty-eight differentially abundant metabolites, including lactic acid, succinic acid, and uric acid, were identified. Proteomic analysis quantified 8513 proteins with subtype-specific expression patterns. Integrated analysis revealed seven significantly enriched pathways, including glycolysis/gluconeogenesis, central carbon metabolism in cancer, and the pentose phosphate pathway. Increased LDHA abundance in metastatic AN3CA-derived EVs was confirmed by Western blot (p = 0.047). EC-derived EVs display subtype- and metastatic-status-specific metabolo-proteomic signatures, with glycolysis, TCA cycle remodeling, and central carbon metabolism as convergent pathway signatures of molecular reprogramming. These findings establish a multi-omics framework for characterizing EV cargo in EC and identify candidate enzyme-metabolite nodes for future biomarker validation in patient-derived specimens.

Keywords:  data independence acquisition; extracellular vesicles; metabolomics; multi-omics; proteomics

DOI:  https://doi.org/10.3390/ijms27177703
Anal Chem. 2026 Aug 07.

Aspiration Patch Proteomics Enables CE-ESI-MS Proteotyping of Identified Single Neurons in Intact Brain Tissue.

Cole C Johnson, Sam B Choi, Juan A Zegers-Delgado, Alexandre Kisner, Ricardo C Araneda, Abigail M Polter, Peter Nemes.

Direct proteome analysis of identified neurons in intact brain tissue remains limited by the difficulty of recovering intracellular material while preserving native tissue context and avoiding physical extraction of the intact soma. Here, we establish aspiration patch proteomics as a mass spectrometry (MS)-compatible microsampling strategy for proteome-level analysis of somal cytoplasmic aspirates from fluorescently identified neurons in acute mouse brain slices. The workflow combines patch-pipet aspiration, volatile internal-solution chemistry, minimal-loss bottom-up proteomics, and high-sensitivity capillary electrophoresis (CE)-electrospray ionization (ESI)-MS on a timsTOF platform. Optimization of the patch internal solution revealed a strong trade-off between electrophysiological compatibility and proteomic depth, identifying ammonium bicarbonate as an enabling volatile electrolyte for downstream CE-ESI-MS analysis. Applied to dopaminergic, parvalbumin, and serotonergic neurons, the method identified hundreds to >1000 proteins from optimized single-neuron somal cytoplasmic aspirate measurements while analyzing only ∼0.4% of the processed digest per CE-ESI-MS run. Across neuronal classes, 1894 protein entries were identified and 1703 were quantified, yielding reproducible label-free profiles sufficient to separate biological replicates by neuronal phenotype and distinguish neuronal classes from protein expression alone. These results show that aspiration-based recovery of somal cytoplasm yields sufficient proteomic information for subtype-level single-neuron proteotyping while maintaining intact-tissue targeting and avoiding cell dissociation or physical extraction of the intact soma. Aspiration patch proteomics therefore provides a chemically compatible sampling front end for MS-based analysis of identified neurons in native brain tissue.

DOI: https://doi.org/10.1021/acs.analchem.6c03049
Nat Commun. 2026 09 16. pii: 9877. [Epub ahead of print]17(1):

Quantitative proteomics reveals coordinated changes in the proteome during replicative senescence.

Nádia Da Silva Fernandes, Fridolin Kielisch, Amitkumar Fulzele, Sivarajan Karunanithi, Justus F Gräf, Jia-Xuan Chen, Christian Behl, Helle D Ulrich, Petra Beli.

Cellular senescence is a state of irreversible cell cycle arrest triggered by telomere erosion, persistent DNA damage or chronic stress. The accumulation of senescent cells disrupts tissue function and contributes to aging and disease. Here, we employ mass spectrometry-based proteomics to systematically interrogate dynamic proteome changes at multiple levels during the progression of replicative cellular senescence. We demonstrate that proteome changes during senescence occur in a coordinated manner, characterized by widespread protein depletion on chromatin. Moreover, components of the cytoplasmic translation machinery are depleted, while mitochondrial proteins display increased insolubility. Autophagic and proteasome activity is compromised in senescent cells along with remodeling of ubiquitin linkages and depletion of ubiquitin E3 ligases. Comparison of the senescent proteome with different pathophysiological cellular states reveals a distinctive senescent signature shaped by changes in the proteostasis network. Collectively, we provide a resource for the exploration of temporally resolved changes in the senescent proteome.

DOI: https://doi.org/10.1038/s41467-026-77686-8
Bio Protoc. 2026 Sep 05. 16(17): e5797

An Automated, Ventana Discovery Platform-based Imaging Workflow for Simultaneous Quantification of B Cells, Plasma Cells, and Plasmablasts in FFPE Human Tissues.

Patrick S Chang, Caleb Chan, Rajiv Jesudason, Sandra Rost, Cary D Austin.

  Accurate, sensitive quantification of B-lineage cells is critical for pharmacodynamic evaluation of B cell-targeted therapies in lupus nephritis (LN) clinical trials. While high-dimensional discovery platforms offer broad profiling, they often lack the sensitivity, quantitative rigor, and throughput needed for precise cell enumeration in renal trial needle biopsies. Traditional immunostaining is hampered by CD20-directed therapeutic masking or downregulation, inadequate sensitivity of CD19 in FFPE tissue, and confounding renal tubular CD138 expression. This protocol details an automated, fit-for-purpose, 5-plex sequential tyramide signal amplification (TSA)-based immunofluorescence assay (CD38, CD79a, CD19, Ki-67, CD138) developed on the Ventana Discovery Ultra platform for deployment on single tissue sections. The workflow anchors B-cell detection on CD79a to ensure sensitivity and utilizes CD38 as an obligate co-marker for CD138+ antibody-secreting cells (ASCs) to definitively exclude the CD138+ epithelial background. Following acquisition via fluorescence whole-slide imaging, a digital analysis pipeline utilizing InstanSeg-based automated segmentation rigorously classifies cell phenotypes to generate precise spatial densities (cells/mm2). This validated protocol maximizes data yield from scarce clinical biopsies while providing high-precision quantitative monitoring of longitudinal therapeutic depletion in the renal microenvironment. Key features • Automated trial scalability: Details an automated, TSA-based 5-plex assay optimized for the Ventana Discovery Ultra platform, ensuring high-throughput, reproducible B-lineage quantification in multicenter cohorts. • Robust lineage identification: Establishes CD79a as an anchor for sensitive B-cell detection in FFPE tissue, avoiding CD20 therapeutic masking/downregulation and CD19 epitope instability. • High-specificity ASC enumeration: Resolves confounding CD138+ renal tubular background using an obligate CD38/CD138 co-labeling strategy to definitively identify ASCs within the renal microenvironment. • Single-section phenotypic resolution: Combines multiplexing and InstanSeg segmentation on one 4-μm section to simultaneously quantify B-lineage subsets in tissue-limited renal needle biopsies.

Keywords:  Antibody-secreting cells (ASCs); B cells; FFPE tissue; Lupus nephritis; Plasma cells; Plasmablasts; Quantitative-multiplex immunofluorescence; Spatial density

DOI:  https://doi.org/10.21769/BioProtoc.5797
Tzu Chi Med J. 2026 Oct-Dec;38(4):38(4): 434-445

Targeting lipid metabolic vulnerabilities with small-molecule inhibitors in acute myeloid leukemia: Emerging insights and therapeutic opportunities.

Jui-Hung Yen, Trung Q Phan, Je-Wen Liou, Pei-Yi Chen.

  Metabolic reprogramming has recently been recognized as a hallmark of cancer. In acute myeloid leukemia (AML), clinically relevant metabolism-targeted therapies have primarily focused on inhibiting mitochondrial energy production; however, their clinical progress has been limited by substantial and nonspecific toxicity. Emerging evidence indicates that reprogramming of lipid metabolism represents a defining feature of leukemic transformation. Lipids not only serve as fundamental structural components of cellular membranes but also function as key signaling molecules and energy sources. In AML cells, lipid uptake, storage, and de novo synthesis are markedly increased, thereby supporting rapid proliferation, survival, and leukemic progression. Consequently, dysregulated lipid metabolism has attracted growing attention as a promising therapeutic vulnerability in AML. This review summarizes the conceptual framework underlying AML cell dependence on cholesterol, fatty acids (FAs), sphingolipids, and broader lipid metabolic pathways. We highlight recent advances in understanding aberrant lipid metabolic programs in AML, including alterations in cholesterol biosynthesis, FA uptake and lipogenesis, FA oxidation, and sphingolipid metabolism. Particular emphasis is placed on the regulatory mechanisms that maintain lipid metabolic homeostasis and how their disruption contributes to leukemogenesis and therapy resistance. Furthermore, we discuss emerging therapeutic strategies aimed at targeting lipid metabolic pathways, with a focus on small-molecule inhibitors that selectively interfere with lipid metabolism-associated enzymes and signaling networks. By delineating key molecular targets and their pharmacological inhibitors, this review highlights the potential of lipid metabolism-based interventions as innovative and effective treatment strategies for AML.

Keywords:  Acute myeloid leukemia; Fatty acid oxidation; Lipid metabolism; Metabolic reprogramming; Small-molecule inhibitors

DOI:  https://doi.org/10.4103/tcmj.TCMJ-D-26-00039
Curr Opin Biotechnol. 2026 Sep 17. pii: S0958-1669(26)00147-3. [Epub ahead of print]102 103582

What's next for metabolomics?

Nichole Reisdorph, Corey D Broeckling, Rafael Brüschweiler, Clary B Clish, Valérie Copié, Timothy Md Ebbels, Arthur S Edison, Facundo M Fernández, Ulrich L Günther, Ewy A Mathé, Vanessa V Phelan, Robert Powers, Daniel Raftery, Tracey B Schock, Dajana Vuckovic, David S Wishart, Min Zhang, Elizabeth Want.

Metabolomics has become a mainstream approach that examines the metabolic composition of biological systems in relation to their physiological and disease states. Using analytical techniques such as nuclear magnetic resonance spectroscopy and mass spectrometry, metabolomics enables detailed profiling of small molecules in cells, tissues, and biofluids. Recent methodological advances, along with the integration of big data analytics and expanding metabolite databases, have significantly enhanced the accuracy and scope of metabolomics research. However, despite over twenty years of development, metabolomics still encounters challenges in annotation, automation, and standardization, which are crucial for fully leveraging recent advances in machine learning and applying metabolomics in biological and clinical studies. Recently, a group of experts assembled to discuss future strategies for standardization and automation and their potential in clinical research. This review underscores critical and unresolved issues in current metabolomics research and suggests pathways toward solutions.

DOI: https://doi.org/10.1016/j.copbio.2026.103582
Int J Mol Sci. 2026 Aug 23. pii: 7537. [Epub ahead of print]27(17):

The Crosstalk Between YAP/TAZ and Cancer Metabolism: From Mechanistic Insights to Drug Discovery.

Yinhuang Gao, Minghong Chen, Songxia Lin, Min Huang, Jing Jin.

  As the core transcriptional co-activators of the Hippo signaling pathway, YAP and TAZ play essential roles in maintaining tissue homeostasis and in tumorigenesis. Their aberrant activation is frequently observed in human malignancies, and accumulating evidence has identified them as crucial drivers of tumor initiation and progression. YAP/TAZ have been recently recognized as key regulators of cellular metabolic reprogramming, a hallmark of cancer that fuels tumor cell proliferation by rewiring glucose, lipid, amino acid, and nucleotide metabolism. Conversely, the activity of YAP/TAZ is modulated by metabolites such as glucose and lipids, establishing a complex bidirectional regulatory circuit. Therefore, deciphering this intricate crosstalk is of great importance for cancer therapy and drug discovery. In this review, we systematically clarify the interplay between YAP/TAZ and metabolic reprogramming in cancer, delineate the core molecular networks through which YAP/TAZ govern each metabolic pathway, and summarize the current pharmacological inhibitors targeting YAP/TAZ-regulated metabolic networks. Collectively, these findings pave the way for therapeutic approaches targeting YAP/TAZ-driven metabolic vulnerabilities in cancer.

Keywords:  YAP/TAZ; cancer metabolism; metabolic reprogramming; therapeutic target

DOI:  https://doi.org/10.3390/ijms27177537
iScience. 2026 Sep 18. 29(9): 117336

Integrating proteomics and metabolomics to reveal MAT2A for metabolic reprogramming in non-small cell lung cancer cells.

Yimin Chen, Yuxi Liu, Zhenyun Zhu, Anqi Ding, Yuying Suo, Cheng Wang, Xiongjun Wang, Hu Zhou, Qiyu Fang, Qian Liu.

  Methionine adenosyltransferase 2A (MAT2A) links metabolic reprogramming to epigenetic regulation via S-adenosylmethionine (SAM) production, but its role in non-small cell lung cancer (NSCLC) remains unclear, and current inhibitors require combination strategies. Using proteomics and metabolomics in NSCLC cells treated with MAT2A-targeting siRNA or the inhibitor AG-270, we characterized MAT2A-driven metabolic rewiring. In fatty acid biosynthesis, MAT2A regulates FASN and SCD; exogenous palmitic acid reverses AG-270-induced growth inhibition, supporting combination with the FASN inhibitor TVB-2640. In cholesterol metabolism, MAT2A modulates biosynthesis and efflux, and an LXR agonist promoting cholesterol efflux enhances AG-270 efficacy. In energy metabolism, MAT2A governs glycolysis via HIF1A, and a GLUT1 inhibitor synergizes with AG-270. In the transsulfuration pathway, MAT2A transcriptionally regulates CBS and shows synergy with inhibitors of PHGDH (producing serine for cysteine biosynthesis) and SLC7A11 (mediating cysteine uptake). Collectively, our findings establish MAT2A as a central metabolic regulator in NSCLC and propose rational combination strategies.

Keywords:  MAT2A; metabolic reprogramming; metabolomics; non-small cell lung cancer; proteomics

DOI:  https://doi.org/10.1016/j.isci.2026.117336
Bioinform Adv. 2026 ;6(1): vbag252

MeTime: an R package for reproducible longitudinal metabolomics data analysis.

Bharadwaj Marella, Patrick Weinisch, Lara Vehovec, Vinh Tran, Josef J Bless, Yacoub A Njipouombe Nsangou, Gabi Kastenmüller, Matthias Arnold.

Summary: MeTime is an opensource R package for reproducible analysis of longitudinal metabolomics data. It builds upon a central S4 container, metime_analyser, that stores multiple datasets, associated metadata and analysis outputs, enabling unified handling of complex longitudinal studies. Analyses are constructed by piping modular functions, beginning with data transformations (mod_*), followed by calculations (calc_*), and optional meta-analysis (meta_*), so entire workflows remain transparent and easy to modify. MeTime wraps numerous existing methods within a consistent interface, including sample and metabolite distributions, correlation/distance matrices, dimensionality reduction (PCA, UMAP, t-SNE), random forest imputation and feature selection via Boruta, eigenmetabolites and WGCNA-based clustering, conservation index analysis, regression models (linear, mixed-effects, and generalized additive), and partial-correlation networks. By retaining all intermediate results and provenance within the container, MeTime facilitates iterative exploration and ensures reproducible reporting via automatically generated HTML/PDF outputs. Comprehensive user guides, case studies and reference documentation accompany the package, making MeTime a versatile platform for longitudinal omics workflows.
Availability and implementation: MeTime is available as an open-source R package and can be installed directly from GitHub (https://github.com/compneurobio/MeTime). Source code, installation instructions, documentation, tutorials, and reproducible case-study workflows are provided within the repository. MeTime has been tested on Microsoft Windows, Unix/Linux, and macOS. For users requiring a containerized environment, a Docker implementation is additionally provided through the GitHub Container Registry.

DOI: https://doi.org/10.1093/bioadv/vbag252