bims-mascan 2026-01-04 papers

bims-mascan

Biomed News

on Mass spectrometry in cancer research

Issue of 2026–01–04
fifteen papers selected by
Giovanny Rodríguez Blanco, Uniklinikum Graz

A Protocol for Robust Discovery Proteomics Using Nano Liquid Chromatography Using Pillar-Array Column Technology and High-Resolution Mass Spectrometry With Data-Independent Acquisition.
Improved preanalytical workflow for pancreatic tissue lipidomics: Insights into lipid stability and polar lipid recovery.
A simple, anesthesia-free infusion technique for in vivo metabolic tracing.
Spatial Mapping of PUFA Incorporation into Phospholipids with bisallylic deuteration.
Beyond Bulk Metabolomics: Emerging Technologies for Defining Cell-Type Specific Metabolic Pathways in Health and Disease.
Spectral Cruncher: A Visualization Tool Integrating Manual Curation, Ion-Intensity Prediction, and De Novo Tag Generation.
Editorial: Metabolic crosstalk between cancer cells and immune cells in the tumor microenvironment: cellular and molecular insights, and their therapeutic implications.
Mass spectrometry-based metabolomics in recurrent ischemic stroke: pathophysiological insights, treatment resistance, and synergistic therapies.
Robust Workflow for Multiclass Host-Gut Microbial Cometabolite Quantitation in Human Stool via 3-Nitrophenylhydrazine Derivatization and LC-MS/MS: A Validated Analytical Platform for Translational Studies.
Lipidomic changes in persister cancer cells drive enhanced ferroptosis sensitivity.
Proteomic comparison of human brain tissue preservation methods.
Protocol to assess retinal metabolic flux of mice via stable isotope-resolved metabolomics.
High-Risk Host Cell Protein Profiling with Sub-ppm Sensitivity by iRT-Assisted Targeted Mass Spectrometry.
Comprehensive Evaluation of Plasma Biomarkers in Patients with Abdominal Aortic Aneurysm Using High-Throughput Label-Free Quantitative Proteomic Profiling.
Proteomics in Practice: A Case Study Highlighting Tandem Mass Tag-Based MS for Quantitative Profiling of Extracellular Vesicles and Application to Irradiated Fibroblasts.

J Sep Sci. 2025 Dec;48(12): e70340

A Protocol for Robust Discovery Proteomics Using Nano Liquid Chromatography Using Pillar-Array Column Technology and High-Resolution Mass Spectrometry With Data-Independent Acquisition.

Daniel Papp, Hanrong Wen, David Scheich, Nico Lingg, Goran Mitulović, Sebastiaan Eeltink.

  Nano liquid chromatography-mass spectrometry has come to be a key enabling technology in shotgun proteomics due to the combination of exceptional separation power, sensitivity, and comprehensiveness. However, the know-how of setting up proteomics methods to deliver robust, reliable, and meaningful results to large-scale life science experiments has remained somewhat ambiguous. This protocol outlines guidance for establishing nano-LC-MS/MS workflows focusing on comprehensive and untargeted deep proteome profiling, using state-of-the-art column technology and mass spectrometry. Employing a second-generation micropillar-array column, a trade-off is demonstrated between analysis time and chromatographic resolving power, which in turn impacts peptide and protein identification scores from a commercial HeLa reference standard. Furthermore, a straightforward workflow to develop a data-independent acquisition (DIA)-parallel accumulation-serial fragmentation (PASEF) analytical method is proposed, with a special focus on the optimization of the ESI source settings. Besides the method development, the study discusses the use of segmented gradients, and an MS-compatible surfactant in the sample diluent is also explored. Finally, the robustness of the developed method is demonstrated through consistently identifying 7558 protein groups (CV = 0.3%) as maintaining high repeatability peptide retention times (mean CV = 0.2%) and system pressure (CV = 0.4%) over 21 consecutive analyses.

Keywords:  biomarker discovery; nano liquid chromatography coupled with mass spectrometry (LC–MS); pillar‐array column; proteomics; tims‐TOF

DOI:  https://doi.org/10.1002/jssc.70340
J Lipid Res. 2025 Dec 26. pii: S0022-2275(25)00231-7. [Epub ahead of print] 100968

Improved preanalytical workflow for pancreatic tissue lipidomics: Insights into lipid stability and polar lipid recovery.

Karol Parchem, Malena Manzi, Robert Jirásko, Ondřej Peterka, Zuzana Lásko, Ondřej Kuda, Michal Holčapek.

  Tissue lipidomics is a rapidly advancing field in clinical and biomedical research that provides crucial information on the lipid-driven molecular mechanisms underlying physiological and pathological conditions. However, accurate mass spectrometry-based analysis requires careful preanalytical handling due to the metabolic activity of tissue and analyte heterogeneity. Here, we introduce a robust tissue processing workflow with the pancreas as a model of a highly metabolically active organ. First, we evaluate lipid stability in porcine pancreatic tissue stored on ice, observing significant lysophospholipid formation after 60-120 minutes. Then, we compare sample handling using ice versus liquid nitrogen for both porcine and mouse pancreatic tissues, illustrating that processing temperature affects low-abundant lipid class levels, with liquid nitrogen providing better preservation. To enhance polar lipidome analysis, we optimize a hexane-methanol liquid-liquid extraction protocol and find that the addition of 2% (v/v) water to methanol yields the most effective recovery and reproducibility. Finally, the workflow is applied to mouse pancreatic tissue samples, enabling the identification of 209 polar lipid species across 10 classes, with 124 species quantified. Among these, hexosylceramides show clear sex-specific variation.

Keywords:  Lipid fractionation; Mass spectrometry; Pancreas; Sample preparation; Supercritical fluid chromatography; Tissue lipidomics

DOI:  https://doi.org/10.1016/j.jlr.2025.100968
bioRxiv. 2025 Dec 19. pii: 2025.12.17.694756. [Epub ahead of print]

A simple, anesthesia-free infusion technique for in vivo metabolic tracing.

Yumi Kim, Samantha Caldwell, Meredith Long, Dominique Abrahams, Margi Baldwin, Gina M DeNicola.

Accurate metabolic flux analysis requires tracer delivery that preserves physiological metabolism. Current methods may distort metabolism through anesthesia, surgical stress, or complex procedures. We demonstrate that isoflurane anesthesia profoundly alters serum and tissue metabolism across multiple pathways. Glycolytic and TCA cycle intermediates, sulfur and aromatic amino acid metabolites, acylcarnitines, and nucleotide pools decreased, while branched-chain amino acids, their ketoacids, ketone bodies, and fatty acids increased. These coordinated changes were suggestive of mitochondrial complex I inhibition and reduced oxidative catabolism, leading to shifts in metabolite pool sizes that compromise isotopologue-based flux interpretation. We established a tail vein catheterization method completed in minutes under brief anesthesia that enables multi-hour tracer infusion in awake, freely moving mice. This method achieved steady-state labeling of cystine and downstream products comparable to jugular infusion without supraphysiologic cystine accumulation. This platform provides a practical, physiologically accurate method for in vivo steady-state isotope tracing.

DOI: https://doi.org/10.64898/2025.12.17.694756
J Lipid Res. 2025 Dec 31. pii: S0022-2275(25)00234-2. [Epub ahead of print] 100971

Spatial Mapping of PUFA Incorporation into Phospholipids with bisallylic deuteration.

Junji Obi, Kuniyuki Kano, Yuta Shimanaka, Shukichi Haisa, Nozomu Kono, Junken Aoki.

  Mass spectrometry (MS) imaging using stable isotope-labeled fatty acids provides a groundbreaking approach to precisely localizing exogenous fatty acids and their metabolites in vivo. However, challenges persist, particularly with fatty acids labeled with fixed isotopic numbers, which can lead to spectral interferences and limit the number of metabolites that can be detected. In this study, we employed a bisallylic deuteration method to synthesize dihomo-γ-linolenic acid (DGLA) isotopes with m/z values ranging from +4 to +8 Da relative to endogenous DGLA, which allowed us to meticulously dissect DGLA metabolism in mice using LC-QTof-MS and MS imaging. Our strategy enabled the clear selection of m/z values for phospholipids enriched with deuterated DGLA (D-DGLA) and deuterated ARA (D-ARA) derived from D-DGLA, all while maintaining low background noise. This precision facilitated the successful visualization of D-DGLA and D-ARA-containing phospholipids in lung tissue, revealing their distinct localization compared to endogenous phospholipids. Our findings highlight bisallylic deuteration as a powerful tool for elucidating the in vivo dynamics of exogenous polyunsaturated fatty acids (PUFAs) through MS imaging techniques.

Keywords:  Bisallylic deuteration; Dihomo-γ-linolenic acid (DGLA); Mass spectrometry (MS) imaging; Phospholipids; Polyunsaturated fatty acids (PUFAs)

DOI:  https://doi.org/10.1016/j.jlr.2025.100971
Biomolecules. 2025 Dec 02. pii: 1687. [Epub ahead of print]15(12):

Beyond Bulk Metabolomics: Emerging Technologies for Defining Cell-Type Specific Metabolic Pathways in Health and Disease.

Yichen Gong, Samuel Weinberg.

  While metabolomics has emerged as a powerful tool for discovering disease biomarkers, the clinical utility of plasma or tissue metabolite profiles remains limited due to metabolic heterogeneity and flexibility across cell types. Traditional bulk metabolomics fails to capture the distinct metabolic programs operating within rare cell populations that often drive disease pathogenesis. This review examines cutting-edge approaches that overcome these limitations by characterizing metabolism at single-cell and cell-type-specific resolution, with particular emphasis on rare immune cell populations as a proof of concept. We discuss how the integration of flow cytometric metabolic profiling, molecular techniques, advanced metabolomics platforms, and computational modeling enables unprecedented insight into cell-intrinsic metabolic states within physiological contexts. We critically evaluate how these technologies reveal metabolic plasticity that confounds bulk measurements while identifying cell-type-specific metabolic vulnerabilities. Finally, we address the crucial challenge of establishing causality in metabolic pathways, a prerequisite for translating metabolomic discoveries into clinically actionable interventions. By moving beyond descriptive metabolomics toward a mechanistic understanding of cell-type-specific metabolism, these approaches promise to deliver the precision required for effective metabolic targeting in disease.

Keywords:  CRISPR screening; LC-MS HILIC; immunometabolism; rare immune cell metabolomics; single-cell metabolic profiling

DOI:  https://doi.org/10.3390/biom15121687
J Am Soc Mass Spectrom. 2025 Dec 29.

Spectral Cruncher: A Visualization Tool Integrating Manual Curation, Ion-Intensity Prediction, and De Novo Tag Generation.

Aline A M Martins, Blake L Tsu, Hulyana Brum, Lucas Sales, Marlon Dias Mariano Dos Santos, Juliana de Saldanha da Gama Fischer, Stephanie Almeida, Luisa Bulcao Vieira Coelho, Natalia Moreira, Alysson R Muotri, Paulo Costa Carvalho.

  Here, we introduce Spectral Cruncher, an interactive extension to the PatternLab for Proteomics platform, designed to bridge the gap between manual curation and state-of-the-art computational analysis of proteomic tandem mass spectra. Spectral Cruncher integrates de novo sequence tag extraction, automated spectral annotation, targeted tag search, and a customized transformer-based fragment-ion intensity predictor (SpecFormer) within a unified graphical environment, designed for interactive and instrument-specific visualization. Central to this workflow is SpecFormer, a compact transformer architecture trained on multiple data sets, providing independent ion intensity models for Q-Exactive + bulk, Astral bulk, and Astral single-cell proteomics data, enabling accurate and instrument-specific intensity prediction even under conditions of sparse fragmentation and low signal-to-noise ratios. Evaluation of SpecFormer demonstrates high predictive performance, with average cosine similarities of approximately 0.98 for bulk Q-Exactive + data sets, 0.91 for bulk Astral, and 0.87 for Astral single-cell data. These tools enable researchers to interrogate ambiguous spectra, validate peptide identifications, and develop intuition for algorithmic limitations. The tools are freely available within PatternLab 5.1, lowering technical barriers and promoting broader adoption of interactive, expert-driven workflows as well as providing a learning environment. A video of our tool in action is available at https://youtu.be/tc2sPiqJkLA.

Keywords:  Astral; PatternLab; Q-Exactive+; SpecFormer; Spectral; available; bulk; data; designed; instrument-specific; intensity; interactive; providing; sets; single-cell; tag; tools

DOI:  https://doi.org/10.1021/jasms.5c00301
Front Oncol. 2025 ;15 1751044

Editorial: Metabolic crosstalk between cancer cells and immune cells in the tumor microenvironment: cellular and molecular insights, and their therapeutic implications.

Parmanand Malvi, Shivendra Vikram Singh, Balkrishna Chaube.



Keywords:  cancer immunotherapy; cancer metabolism; immune response; immune-cell metabolism; metabolic reprogramming; therapeutic target; tumor microenvironment

DOI:  https://doi.org/10.3389/fonc.2025.1751044
Eur J Med Res. 2025 Dec 30.

Mass spectrometry-based metabolomics in recurrent ischemic stroke: pathophysiological insights, treatment resistance, and synergistic therapies.

Shiyang Liu, Siat Yee Fong, Hui Liu, Peiyang Sun.

  Recurrent ischemic stroke represents a major unmet clinical challenge, contributing significantly to the global burden of neurological disability and mortality. Despite widespread implementation of guideline-recommended secondary prevention strategies-including antiplatelet therapy, lipid management, and blood pressure control-a substantial proportion of stroke survivors experience subsequent ischemic events (GBD 2019 Stroke Collaborators. Global, regional, and national burden of stroke and its risk factors, 1990-2019: a systematic analysis for the Global Burden of Disease Study 2019. The Lancet Neurology. 2021;20(10):795-820.). This persistent residual risk suggests that current clinical paradigms fail to capture the complex, heterogeneous biological dysregulation driving the recurrent disease state (Hankey in Lancet Neurol 13:178-194, 2014). Ischemic stroke is fundamentally a catastrophic metabolic crisis, involving rapid bioenergetic failure, profound oxidative stress, and prolonged inflammatory cascades (Dirnagl et al. in Trends Neurosci 22:391-397, 1999). Mass spectrometry (MS)-based metabolomics has emerged as a premier technological platform in preclinical and exploratory clinical research, capable of simultaneously quantifying hundreds to thousands of endogenous small-molecule metabolites (Nicholson and Lindon in Nature 455:1054-1056, 2008). By providing a functional readout of cellular phenotypes, MS metabolomics offers a unique window into the dynamic biochemical alterations that precede, accompany, and follow ischemic injury. This review provides a comprehensive synthesis of recent advances in applying MS-based approaches to dissect the pathophysiology of recurrent ischemic stroke. We critically examine strong evidence implicating core metabolic disruptions, including the "sphingolipid rheostat" and blood-brain barrier integrity, the shift toward pro-inflammatory lipid mediators in the inflammation-thrombosis axis, mitochondrial tricarboxylic acid cycle dysfunction, and the complex interplay between gut microbiota-derived metabolites and host vascular health. Furthermore, we explore the emerging field of pharmacometabolomics, detailing how MS profiling is providing mechanistic insights into resistance to standard antiplatelet therapies, particularly involving clopidogrel bioactivation pathways and arachidonic acid shunting in aspirin-treated patients. The potential of metabolomics to elucidate the biological mechanisms of complementary therapies, such as acupuncture, is also reviewed with critical appraisal. Finally, we provide a realistic and sobering assessment of the current translational gap. We highlight that while MS metabolomics offers unparalleled pathophysiological insights, significant technical and validation hurdles-including standardization of protocols, absolute quantification challenges, and the need for large-scale, diverse cohort studies-must be overcome before these metabolic signatures can be translated into viable clinical tools for personalized risk stratification and prevention of recurrent stroke (Wishart in Physiol Rev 99:1819-1875, 2019).

Keywords:  Antiplatelet resistance; Biomarkers; Gut microbiota; Ischemic stroke recurrence; Mass spectrometry; Metabolomics; Pharmacometabolomics; Sphingolipids

DOI:  https://doi.org/10.1186/s40001-025-03710-0
Anal Chem. 2025 Dec 29.

Robust Workflow for Multiclass Host-Gut Microbial Cometabolite Quantitation in Human Stool via 3-Nitrophenylhydrazine Derivatization and LC-MS/MS: A Validated Analytical Platform for Translational Studies.

Daniel Zhi Wei Ng, Mingyou Koh, Adrian Low, Lin Liu, Nur Halisah Binte Jumat, Zixuan Zhang, Xiu Qi Koh, Mengtong Zhu, Mark Muthiah, Yock Young Dan, Jonathan Wei Jie Lee, Eric Chun Yong Chan.

Host-gut microbial co-metabolites, including short-chain fatty acids (SCFA), bile acids (BA), tryptophan metabolites, and branched-chain amino acids (BCAA), have key immune-metabolic functions affecting human health. Dysbiosis-induced alterations in their levels are implicated in the pathogenesis of diseases such as metabolic dysfunction-associated steatotic liver disease (MASLD). However, simultaneous quantitation of these chemically diverse analytes in stool remains analytically challenging due to their diverse physicochemical properties and wide concentration ranges. Here, we developed and rigorously validated a derivatization and targeted liquid chromatography tandem mass spectrometry workflow for the simultaneous quantitation of host-gut microbial cometabolites in human stool. A 3-nitrophenylhydrazine derivatization protocol was optimized by systematically adjusting reagent concentrations and introducing postreaction quenching to suppress in-line acetic acid derivatization. Chromatographic separation was enhanced by using a novel dual-additive mobile-phase strategy (formic acid and ammonium acetate in aqueous and organic phase, respectively) coupled to a mixed-mode C18-anion-exchange stationary phase, enabling improved resolution and sensitivity across chemically diverse metabolite classes. Our optimized analytical method achieved accurate, sensitive, and efficient quantitation of 38 metabolites (15 SCFA, 16 BA, 4 tryptophan metabolites, 3 BCAA) within 23 min, demonstrating excellent linearity (r2 > 0.99) and precision (CV < 15%), with short- (autosampler, 4 °C) and long-term (freezer, -20 °C) stability. Comparative analysis of healthy controls and MASLD stools revealed distinct metabolic signatures, including reduced SCFA and C6-oxidized BA, and elevated conjugated and secondary BA derivatives in MASLD. Our study establishes an analytically rigorous platform for multiclass host-gut cometabolite quantitation in stool, with demonstrated utility for translational research into gut-liver axis disorders.

DOI: https://doi.org/10.1021/acs.analchem.5c05360
Ferroptosis Oxid Stress. 2025 ;pii: 202501. [Epub ahead of print]1(1):

Lipidomic changes in persister cancer cells drive enhanced ferroptosis sensitivity.

Eduard Reznik, Fereshteh Zandkarimi, Joleen M Csuka, Qiulin Zhu, Jenny Jin, Taruna Vani Neelakantan, Jiewen Zheng, Vasiliki Polychronidou, Mark Fongheiser, Ashley Brown, Baiyu Qiu, Megan Rodriguez, Lela DeVine, Prem S Subramaniam, Wei Gu, Andrea Califano, Brent R Stockwell.

   Aims: Unique in the broader category of drug-resistant cells, persister cancer cells (PSs) acquire their tolerance to compounds through reversible, chromatin-mediated changes, allowing them to 'persist' in the face of cancer therapeutic agents. PSs are implicated in minimal residual disease from which cancer relapse occurs, and given their established sensitivity to ferroptosis, PSs present a critical point through which identification and targeting of drug-resistant cancers may be possible. Ferroptosis sensitivity in drug-resistant cancers may be caused by the attainment of the persister state, or it may merely be correlative with this state and due instead to extended inhibition of oncogenic signaling or the induction of chemotherapy stress. Nonetheless, ferroptosis sensitivity has emerged as a common phenotype across multiple PS and drug-resistant cancer cell types. Identifying biomarkers for and drivers of ferroptosis sensitivity in drug-resistant and PS cells is therefore a high priority.
Methods: We derived PS cells from the lung carcinoma cell line PC9 (PSPC9), performed transcriptomic analysis, and subsequently lipidomics on the PC9/PSPC9 system. Additionally, we reverted PSPC9 cells to the ferroptosis-resistant parental state (PC9PS -> PC9) and assessed the resulting lipid changes. We generated two additional PS-like cell models: PS-like prostate carcinoma (PSLNCaP) from LNCaP cells and PS-like fibrosarcoma (PSHT1080) from HT1080 cells, with lipidomics analysis. Finally, we performed a mitochondrial elimination assay and assessed its effect on ferroptosis sensitivity.
Results: We observed enrichment of lipid and sugar metabolism gene expression in PSPC9; lipidomics revealed enrichment within PSPC9 for ferroptosis-driving diPUFA phospholipids (diPUFA-PL), as well as polyunsaturated free fatty acids (PUFA FFAs). Upon PSPC9 reversion to the ferroptosis-resistant parental state (PC9PS -> PC9), this lipid signature reverted. The LNCaP and HT1080 PS-like models individually showed features consistent with PS, including an increased labile-iron pool, reversibility, and enhanced ferroptosis sensitivity, and had lipid features consistent with those in PSPC9. Finally, mitochondrial elimination partially abrogated ferroptosis sensitivity and altered the PS lipid profile.
Conclusion: In summary, lipidomic changes dependent on the presence of mitochondria are key to the ferroptosis sensitivity of drug-tolerant persister cancer cells.

Keywords:  Polyunsaturated fatty acid; cancer; diPUFA; ferroptosis; lipids; mitochondria; persisters

DOI:  https://doi.org/10.70401/fos.2025.0003
J Proteomics. 2025 Dec 30. pii: S1874-3919(25)00216-7. [Epub ahead of print] 105589

Proteomic comparison of human brain tissue preservation methods.

Laura Plantera, Anna Didio, Uta Ceglarek, Ingo Bechmann.

  This study investigated the impact of tissue preservation methods on protein profiles analyzed by reversed-phase liquid chromatography-high-resolution mass spectrometry (LC-HRMS) using data-independent acquisition (DIA). Proteomic profiles from formalin-fixed, formalin-fixed and paraffin-embedded (FFPE), and fresh-frozen human brain tissues (cortex and hippocampus, n = 6) were compared, including an FFPE-specific protein extraction kit (n = 4). Formalin-fixed samples more closely resembled fresh-frozen profiles than FFPE or FFPE-Kit samples, while still showing high correlation and overlap with FFPE tissues in principal component analyses. A core set of 1753 proteins was consistently detected across all sample preparation methods. A total of 35 proteins were identified exclusively in fresh-frozen samples, but without functional enrichment. Quantitative comparisons to the proteome of fresh-frozen tissue revealed an underrepresentation of cellular processes, energy metabolism, signaling, and transport related to protein properties such as length, location, and hydrophobicity. In contrast, neuronal development and phagosome-related pathways were overrepresented in fixed tissues. In a pilot study comparing low (Braak 0-II, n = 4) and high (Braak IV-VI, n = 4) Alzheimer's disease (AD) stages using formalin-fixed samples, we identified 12 potential protein biomarkers, primarily nucleosomal proteins and carboxypeptidase M (CPM). These findings suggest that formalin-fixed brain tissue provides reliable proteomic information, making it a valuable resource for neurodegenerative disease research. SIGNIFICANCE: Proteomics offers enormous potential for investigating the molecular regulation of the human brain. Valuable tissue samples are often preserved in formalin or additionally with paraffin for later analysis. The potential value of these preserved samples for proteomic analysis has already been recognized. However, tissue preservation poses a challenge for proteome analysis. Consequently, several studies have compared different protein extraction protocols for fixed samples. In addition, studies have been published comparing protein extraction from FFPE samples with fresh-frozen samples. To our knowledge, this is the first study to compare protein extraction across all three tissue preservation methods with subsequent functional analysis using samples obtained from the same donors, thereby eliminating inter-donor variability and enabling a direct comparison of preservation effects. This study validates a protein extraction protocol from formalin-fixed samples, laying the groundwork for future research into potential biomarkers in formalin-fixed samples.

Keywords:  Alzheimer's disease; Braak stages; DIA; FFPE; Formalin-fixed; Human brain tissue; LC-HRMS; Label-free quantification; Mass spectrometry; Proteomics

DOI:  https://doi.org/10.1016/j.jprot.2025.105589
STAR Protoc. 2025 Dec 26. pii: S2666-1667(25)00658-6. [Epub ahead of print]7(1): 104252

Protocol to assess retinal metabolic flux of mice via stable isotope-resolved metabolomics.

Georgy Komissarov, Kriti Pandey, Nicholas D Nolan, Thomas Winogrodzki, Daniel T Hass, Aykut Demirkol, Brian M Robbings, James B Hurley, Stephen H Tsang.

  Here, we present a protocol for evaluating glucose metabolism in mouse retinas and retinal pigment epithelium (RPE)-choroid tissue by tracking the incorporation of 13C6 from U-13C6-glucose with gas chromatography-mass spectrometry (GC-MS). We describe steps for incubating tissues in Krebs-Ringer bicarbonate solution and homogenizing tissues. We then detail procedures for extracting metabolites and determining isotopic labeling of intermediates in glycolysis and the tricarboxylic acid (TCA) cycle using GC-MS. The approach has been adapted to study glucose metabolism in various tissues, animal models, and genetic conditions. For complete details on the use and execution of this protocol, please refer to Nolan et al.1.

Keywords:  Mass spectrometry; Metabolism; Metabolomics

DOI:  https://doi.org/10.1016/j.xpro.2025.104252
J Proteome Res. 2026 Jan 02.

High-Risk Host Cell Protein Profiling with Sub-ppm Sensitivity by iRT-Assisted Targeted Mass Spectrometry.

Qi Wang, Ting Dong, Muchen Li, Xueliang Wang, Min Xu, Yiqing Cui, He Zhu, Tianli Zhang, Xingli Gao, Lin Zhu, Lili Wang, Le Yu, Yongsheng Xiao, Jun Tian.

  Host cell proteins (HCPs), particularly high-risk species, are critical process-related impurities that can affect the quality, safety, and efficacy of biopharmaceuticals. We developed iRT-assisted targeted mass spectrometry (iRTarget-MS), a robust platform for profiling 31 high-risk HCPs in Chinese Hamster Ovary (CHO) cells across five risk categories: drug aggregation, drug degradation, polysorbate degradation, immunogenic response, and direct biological activity. Optimized for multiplexed, reproducible, and sensitive quantification, iRTarget-MS incorporated iRT values for retention time calibration, enabling the confident identification of low-abundance HCPs. Compared to conventional shotgun proteomics, iRTarget-MS demonstrated significant sensitivity improvement at the subppm level. For example, PLBL2 quantification by iRTarget-MS demonstrated comparable yet more sensitive results compared with the protein-specific enzyme-linked immunosorbent assay (ELISA). Case studies have highlighted the broad applications of iRTarget-MS, including supporting high-throughput process optimization, verification of complete HCP removal while mapping its clearance pathways, and antibody coverage analysis for high-risk HCP subsets. In summary, iRTarget-MS serves as a transformative tool that complements ELISA and shotgun proteomics for high-risk HCP analysis, enhancing the process understanding and accelerating process development. With its ease of operation, streamlined data analysis, and accessible instrumentation, iRTarget-MS opens up opportunities for adopting liquid chromatography-mass spectrometry (LC-MS)-based HCP analysis as a routine monitoring strategy for large sample sets in the biopharmaceutical industry.

Keywords:  antibody; biotherapeutics; host cell proteins; process development; targeted mass spectrometry

DOI:  https://doi.org/10.1021/acs.jproteome.5c00680
Am J Physiol Heart Circ Physiol. 2025 Dec 30.

Comprehensive Evaluation of Plasma Biomarkers in Patients with Abdominal Aortic Aneurysm Using High-Throughput Label-Free Quantitative Proteomic Profiling.

Merry L Lindsey, Emily I Chen, Pushkar Shivam, Pius N Nde, David Horn, Santosh Renuse, Amirmansoor Hakimi, B Timothy Baxter, Michael Terrin, Jon S Matsumura, Amadou Gaye, John A Curci.

  The use of comprehensive unbiased proteomic evaluations coupled with physiological and clinical insight offers the possibility to enhance our understanding of disease mechanisms and identify potential biomarkers for diagnosis and prognosis of cardiovascular disease. In this methods and resources article, we present the methodologies employed for a workflow leveraging a high-throughput large-scale mass spectrometry-based technology for label-free quantitative proteomic profiling coupled with physiological and clinical assessment. Using this approach, we analyzed a total of 505 plasma samples at baseline and one- and two-year follow-up from patients enrolled in the Non-Invasive Treatment of Abdominal Aortic Aneurysm Clinical Trial (N-TA3CT). We successfully identified a dataset comprising over 1,000 distinct proteins. Collecting samples longitudinally provides built-in validation, allowing for direct comparisons within the same patient over time. We provide a comprehensive collection and analytical data plan tailored for such a large dataset, which encompasses data acceptance criteria, integrity checks, and database validation. We also provide methods on statistical testing, temporal cross-validation, and biological and clinical validation. This resource outlines a template for similar experiments and development of a robust statistical analysis plan that will limit false positive and false negative identifications to focus on true protein changes that may serve as diagnostic or prognostic indicators.

Keywords:  aneurysm; clinical proteomics; high-throughput proteomics; mass spectrometry; vascular biology

DOI:  https://doi.org/10.1152/ajpheart.00832.2025
Proteomics. 2025 Dec 30. e70103

Proteomics in Practice: A Case Study Highlighting Tandem Mass Tag-Based MS for Quantitative Profiling of Extracellular Vesicles and Application to Irradiated Fibroblasts.

Greg Berumen Sánchez, Purvi Patel, Kristie Lindsey Rose, Marjan Rafat.

  Extracellular vesicles (EVs) are critical mediators of intercellular communication, and valuable sources of biomarkers for diagnostic and therapeutic applications. However, the complexity and heterogeneity of EVs present significant challenges for their proteomic characterization. Major challenges of EV samples include low yield, technical variability, and the need for sensitive and high throughput quantification approaches. In this study, we implement a tandem mass tag (TMT)-based MS workflow for comprehensive, quantitative proteomic profiling of isolated EVs. Through comparison with label-free quantitation (LFQ), we highlight the potential pitfalls and limitations of methodological choices in EV proteomic analyses. Our study integrates standard EV isolation with robust TMT labeling and high-resolution MS, providing insights into practical EV analysis. Utilizing this approach, we profiled EVs isolated from human fibroblasts treated with ionizing radiation. The TMT workflow uncovered an EV proteomic signature reflective of the cellular origins and potential functional roles of irradiated fibroblasts, compared to the LFQ workflow. Our case study underscores the potential of TMT-based MS to overcome common barriers in EV proteomics, facilitating new discoveries in EV biology and advancing their application in biomarker development and translational research.

Keywords:  comparative proteomics; extracellular vesicles; ionizing radiation; label‐free quantification; tandem mass tag labelling

DOI:  https://doi.org/10.1002/pmic.70103