bims-mascan Biomed News
on Mass spectrometry in cancer research
Issue of 2026–05–17
eleven papers selected by
Giovanny Rodríguez Blanco, Uniklinikum Graz
  1. Limited Proteolysis Mass Spectrometry to Identify Protein Structural Differences in Brain Tissue.
  2. A Suspension-Trapping Protocol for Bottom-Up Proteomics Sample Preparation.
  3. Scanning central carbon metabolism: a HILIC-HR-TOF-MS metabolome method.
  4. Multi-phase hybrid metabolomics framework identifies clinically applicable plasma signatures for early detection of gastric cancer.
  5. Resolving Sialylated N-Glycans and Immune Cell Landscapes Using a Unified Same-Section IMC-MSI Workflow.
  6. Structural Diversity and Analytical Characterization of Acylhomocarnitines.
  7. A Broadly Accessible Approach to Elucidate the Carbon-Carbon Double Bond Position in Unsaturated Lipids by a Post-column In-Line Photochemical Reaction and Mass Spectrometry.
  8. Lipid Analysis in Live Caenorhabditis elegans Using Solution-State NMR Spectroscopy.
  9. Reduction-Free Thermolysin Digestion Enables Absolute Protein Quantitation in Plasma in 35 min from Sample to Result.
  10. Beyond Correlation: Constraint Architecture Explains Proteome-Metabolome Decoupling.
  11. Simultaneous quantitation of structurally analogous bile acid isomers via charge-state-engineered UPLC-MS.
  1. Bio Protoc. 2026 May 05. 16(9): e5670
    Limited Proteolysis Mass Spectrometry to Identify Protein Structural Differences in Brain Tissue.
    Haley E Tarbox, Stephen D Fried.
      Structural proteomics methods allow for the proteome-wide interrogation of protein structural differences between two different conditions. Limited proteolysis mass spectrometry (LiP-MS), as originally implemented by the Picotti lab, utilizes a promiscuous protease to cleave at solvent-exposed regions of a protein to encode structural information, which is then read out with mass spectrometry proteomics. Here, we present a protocol that details experimental steps and data analysis for a LiP-MS workflow. First, tissue is homogenized under native conditions and then subjected to limited proteolysis using proteinase K (PK). The samples are prepared for mass spectrometry, and data are acquired using either data-dependent acquisition (DDA) or data-independent acquisition (DIA). Raw data is processed using FragPipe, and raw ion abundances are processed in FragPipe Limited-Proteolysis Processor (FLiPPR). Proteins with structural changes between the two conditions are identified in a proteome-wide manner. Key features • Protocol describes how to perform limited proteolysis mass spectrometry to identify proteins in brain tissue with structural changes proteome-wide between two experimental conditions. • Includes context for how to ensure results are reliable, using permutation analyses. • Utilizes tools (FragPipe and FLiPPR) that are free and open source. • Sample preparation can be performed in two days, not including mass spec acquisition and data analysis.
    Keywords:  Brain; FLiPPR; FragPipe; Limited proteolysis mass spectrometry; Structural proteomics
    DOI:  https://doi.org/10.21769/BioProtoc.5670
  2. Bio Protoc. 2026 May 05. 16(9): e5681
    A Suspension-Trapping Protocol for Bottom-Up Proteomics Sample Preparation.
    Joseph Schrader, Dennis Province, Nicholas A DaSilva, Chang Liu.
      Bottom-up proteomics workflows encompass several key stages, including sample preparation, data acquisition, and data analysis. Of these, sample preparation is the initial and critical stage, as it significantly influences the depth, reproducibility, and reliability of subsequent mass spectrometry-based analyses. While several main digestion strategies exist, including in-gel, in-solution, and filter-aided methods, each presents distinct trade-offs in terms of throughput, contamination removal, and applicability to complex biological matrices. The Suspension Trapping (S-Trap) method offers a compelling alternative by efficiently capturing and digesting proteins while removing interferents like sodium dodecyl sulfate (SDS), which can compromise downstream LC-MS/MS performance. This protocol details a S-Trap workflow optimized for biofluid proteomics, specifically plasma, serum, and cerebrospinal fluid (CSF). We describe two complementary formats: a manual tube-based procedure for individual or small-batch samples and a 96-well-plate-based system enabling high-throughput processing. The protocol integrates optional high-abundance protein depletion to enhance coverage of low-abundance analytes and includes steps for reduction, alkylation, digestion, and peptide elution for low total protein content samples, such as plasma, serum, and cerebrospinal fluid. By providing a detailed protocol, this work aims to improve the consistency and accessibility of S-Trap-based sample preparation, facilitating robust and reproducible discoveries in bottom-up proteomics. Key features • Plasma/serum/cerebrospinal fluid sample preparation for bottom-up proteomics. • Lab Suspension Trapping (S-Trap)-based digestion for efficient detergent removal and high peptide recovery. • Optimized for challenging samples (e.g., CSF, plasma) with low protein concentration or high lipid content. • Includes both single-tube and high-throughput 96-well plate formats for flexible experimental design.
    Keywords:  LC-MS; Mass spectrometry; Proteomics; S-trap; Sample preparation
    DOI:  https://doi.org/10.21769/BioProtoc.5681
  3. Metabolomics. 2026 May 13. pii: 71. [Epub ahead of print]22(3):
    Scanning central carbon metabolism: a HILIC-HR-TOF-MS metabolome method.
    Victoria Pozo Garcia, Valentina Ferro, Jolene Rier, Sofia Moco.
       INTRODUCTION: Central carbon metabolism (CCM) is the primary metabolic hub of the cell, governing energy production and providing precursors essential for a myriad of biosynthetic pathways. Developing analytical tools that can identify and quantify intermediates of these metabolic reactions is crucial for studying cell metabolism in biomedical and biotechnological applications.
    OBJECTIVE: This study proposes a liquid chromatography (LC)-high-resolution (HR) mass spectrometry (MS) method, covering the CCM of mammalian cell systems.
    METHODS: Cells were extracted using a one-step liquid extraction, recovering the hydrophilic metabolites. A stable isotope dilution approach was employed, utilizing a U-13C-yeast internal standard (IS). A LC-HRMS metabolomics method using hydrophilic interaction liquid chromatography (HILIC) coupled to a Zeno-time-of-flight (ZenoTOF) MS was implemented for metabolite semi-quantification.
    RESULTS: A total of 82 CCM metabolites is reported, of which 77 were confirmed with authentic standards, and for 63 , linearity ranges were obtained. IS normalization enhanced overall robustness, from sample preparation to metabolite semi-quantification. To study the effects on CCM by 5 chemical inhibitors (2-deoxy-D-glucose, etomoxir, UK-5099, rotenone, and 3-nitropropionic acid), our HILIC-HR-TOF-MS method was used. The approach proved efficient in capturing altered metabolite concentrations, within implicated metabolic reactions, as a consequence of inhibitor exposure.
    CONCLUSION: Our HILIC-HR-TOF-MS metabolome method is efficient in mapping changes in metabolic intermediates of the CCM in mammalian cells. This approach holds potential for analysing a variety of biological samples across a range of applications, from drug development to biomedicine.
    Keywords:  Central carbon metabolism; HILIC; LC–MS; Metabolomics
    DOI:  https://doi.org/10.1007/s11306-026-02434-4
  4. Nat Commun. 2026 May 13.
    Multi-phase hybrid metabolomics framework identifies clinically applicable plasma signatures for early detection of gastric cancer.
    Liyi Bai, Fayong Hu, Weiqin Zhang, Huanqin Peng, Haowen Peng, Huan Li, Xu Zhu, Yibin Xie, Shutian Zhang, Li Min.
      Plasma metabolomics offers significant potential for non-invasive biomarker discovery in gastric cancer (GC), yet conventional analytical workflows face challenges in absolute quantification and biological interpretability, hindering clinical translation. Here we present an innovative multi-phase hybrid framework integrating untargeted metabolomics with relative- and absolute-quantitative targeted metabolomics, coupled with a custom interpretability-driven algorithm for de novo biomarker identification. We perform metabolic profiling on 1,706 plasma samples from multicenter cohorts, identifying 84 key metabolites significantly enriched in caffeine metabolism and primary bile acid biosynthesis during the relative quantitation phase. By applying the custom algorithm to absolute quantitation data, we establish a 12-metabolite panel covering multiple functional metabolic modules. Machine learning-based diagnostic models using this signature achieve an area under the curve of 0.951 in validation cohort. Together, our study provides a robust and interpretable framework for translational metabolomics and establishes a GC detection biomarker panel, laying the foundation for future mechanistic research and clinical application.
    DOI:  https://doi.org/10.1038/s41467-026-72983-8
  5. bioRxiv. 2026 Feb 23. pii: 2026.02.21.707206. [Epub ahead of print]
    Resolving Sialylated N-Glycans and Immune Cell Landscapes Using a Unified Same-Section IMC-MSI Workflow.
    Jake Griner, Reto Gerber, Mark D Robinson, Carsten Krieg, Silvia Guglietta.
      Integrating antibody-based imaging with mass spectrometry imaging (MSI) on the same formalin-fixed paraffin-embedded (FFPE) tissue section offers powerful opportunities for multimodal spatial analysis but remains analytically challenging due to cross-platform chemical and physical interference. In particular, chemically aggressive on-tissue derivatization strategies required for isomer-resolved glycan MSI may compromise downstream antibody detection. Here, we systematically evaluate the analytical compatibility and acquisition order of imaging mass cytometry (IMC) and sialic-acid-linkage-resolving N-glycan MALDI-MSI using an Amidation-Activation-X-Linkage (AAXL) derivatization strategy on the same FFPE tissue section. Two same-section workflows were compared: AAXL-MALDI MSI followed by IMC (MALDI-first) and IMC followed by AAXL-MALDI MSI (IMC-first). We find that AAXL-first processing results in severe and widespread loss of IMC anti-body signal across epithelial, immune, and nuclear markers, rendering subsequent antibody-based analysis unreliable. In contrast, IMC-first acquisition preserves quantitative antibody performance while maintaining spatial glycan distributions, relative abundance structure, and isomer-specific signal integrity in downstream AAXL-MALDI MSI. Using high-precision co-registration, we further demonstrate that IMC-first sequencing enables analytically robust integration of IMC and MSI data at both domain and pixel levels. These results establish IMC-first acquisition as the preferred same-section strategy for workflows combining antibody imaging with chemically intensive, isomer-resolved glycan MSI and provide generalizable guidance for the design of multimodal spatial mass spectrometry experiments.
    DOI:  https://doi.org/10.64898/2026.02.21.707206
  6. J Proteome Res. 2026 May 13.
    Structural Diversity and Analytical Characterization of Acylhomocarnitines.
    Jaclyn Weinberg, William J Crandall, Zachery Ryan Jarrell, Gahyun Lim, Ken Liu, Ho Young Lee, Shakshi Patel, Camilo Anthony Gacasan, Young-Mi Go, Dean P Jones.
      Homocarnitine is a five-carbon analog of carnitine produced in mammals through hydroxylation of the microbiome-derived metabolite δ-valerobetaine. Here, we describe liquid chromatography-mass spectrometry methods for the measurement of fatty acyl-homocarnitines, a previously uncharacterized family of mammalian metabolites. These acyl-homocarnitines are homologs of acyl-carnitines, in which the fatty acid is extended by one carbon. We show that short-chain fatty acyl-CoAs are converted to corresponding acyl-homocarnitines by carnitine acetyltransferase and that these enzyme-generated standards exhibit retention times and ion dissociation patterns identical to acyl-homocarnitines produced by mammalian cells. In vitro 13C3-homocarnitine isotope tracer studies showed that mammalian cells produce short-, medium-, and long-chain acyl-homocarnitines. Ion dissociation analyses established diagnostic product ions to distinguish acyl-homocarnitines from isomeric acyl-carnitines. Sample preparation and chromatographic methods are provided to separate and analyze isomers in extracts of mouse tissues. These findings expand knowledge of carnitine analogs and establish analytical strategies to differentiate acyl-homocarnitines from isomeric acyl-carnitines.
    Keywords:  HILIC; acylcarnitine; carnitine; chromatography; energy-resolved; fatty acid metabolism; homocarnitine; isomer; mass spectrometry; valerobetaine
    DOI:  https://doi.org/10.1021/acs.jproteome.5c01255
  7. J Am Chem Soc. 2026 May 12.
    A Broadly Accessible Approach to Elucidate the Carbon-Carbon Double Bond Position in Unsaturated Lipids by a Post-column In-Line Photochemical Reaction and Mass Spectrometry.
    Yu Feng, Athanasia Qirjollari, Raymond J Gonzalez, Kara Pearson.
      Significant advancements in mass spectrometry in the past few decades have enabled comprehensive proteomics, metabolomics, and lipidomics experiments that can describe complex biological processes. Despite faster scan rates, greater resolution, and higher throughput commonly available for new-generation mass spectrometers, some chemically unsophisticated structural characterizations remain a challenge, such as elucidating the carbon-carbon double bond position in fatty acyl chains. Although extensive strategies have been developed to differentiate double bond positional isomers in lipidomics, typically with chemical derivatizations and specialized instrumentation, a simple and broadly accessible approach is still highly desired. In this study, a postcolumn in-line photochemical reaction initiated within a commonly available photodiode array (PDA) detector was developed to cleave carbon-carbon double bonds and monitor the resulting aldehyde product ions to elucidate double bond positions. A photochemical reaction mechanism was proposed based on observations in isotope tracing studies and supplemental experiments. This approach to lipid characterization has been evaluated with multiple lipid classes to demonstrate its broad applicability for structural elucidation and ease of implementation. The effects of aldehyde product generation efficiency with mobile-phase additives commonly used in lipid profiling methods were evaluated to support the applicability in a global structural lipidomics experiment. This approach has the potential to become a powerful analytical tool, providing widespread access to structural lipidomics and further understanding of lipid biology.
    DOI:  https://doi.org/10.1021/jacs.6c01876
  8. Bio Protoc. 2026 May 05. 16(9): e5686
    Lipid Analysis in Live Caenorhabditis elegans Using Solution-State NMR Spectroscopy.
    Florencia V Guastaferri, Carla B Delprato, Bruno Hernández Cravero, Gastón Prez, Diego De Mendoza, Andres Binolfi.
      Unsaturated fatty acids (UFAs) play key roles in essential cellular functions such as membrane dynamics, metabolism, and animal development. Disruptions in UFA metabolism are linked to metabolic, cardiovascular, and neurodegenerative disorders. Cellular UFAs composition and quantification are normally determined using methods such as gas chromatography and/or mass spectrometry, which require extraction procedures and prevent analysis of live specimens. Here, we describe a protocol that employs uniform 13C isotope labeling and high-resolution 2D solution-state nuclear magnetic resonance (NMR) spectroscopy to analyze lipid composition and fatty acid unsaturation directly in the model organism Caenorhabditis elegans. The approach enables in vivo assessment of lipid storage compositions with sufficient resolution and sensitivity to distinguish wild-type animals from those with altered fatty acid desaturation. Complementary analysis of total lipid extracts provides information regarding lipid molecules that are not detected in vivo, such as phospholipid molecules organized in biological membranes. Overall, this non-destructive NMR-based method offers a powerful tool for investigating lipid metabolism in C. elegans and other small model systems that can be isotopically enriched. Key features • Solution-state NMR spectroscopy is not destructive and can be used on live cells and multicellular organisms. • 13C isotopic enrichment is required for high-resolution NMR analysis of lipids in live C. elegans. • Lipid signals from live worms arise from the mobile lipid phase in lipid droplets. • NMR provides readouts of lipid compositions in live animals at a highly sensitive rate, enabling precise interpretation of the whole cell lipid metabolism.
    Keywords:  13C isotope labeling; Caenorhabditis elegans; In vivo NMR spectroscopy; Lipids; Unsaturated fatty acids (UFAs)
    DOI:  https://doi.org/10.21769/BioProtoc.5686
  9. J Proteome Res. 2026 May 11.
    Reduction-Free Thermolysin Digestion Enables Absolute Protein Quantitation in Plasma in 35 min from Sample to Result.
    Xuehui Jiang, Ying Lao, James B Johnston, Versha Banerji, René P Zahedi.
      We previously reported that the broad-specificity protease thermolysin yields reproducible, near-complete proteome digests within 1-2 min. Here, we demonstrate rapid absolute protein quantitation in human plasma by combining reduction/alkylation-free thermolysin digestion on S-Trap cartridges with full-length stable isotope-labeled (SIL) protein standards and parallel reaction monitoring (PRM). Post-digest dilution of S-Trap eluates enabled immediate EvoTip loading, yielding LC-MS-ready samples in under 20 min. Using the anti-CD20 monoclonal antibody rituximab as a showcase, a lower limit of quantitation of 5 amol on-column per ∼250 ng plasma protein injection could be achieved on an Orbitrap Exploris 480 in 60/100 samples-per-day mode. We applied the assay to 23 total pretreatment and on-treatment plasma samples from 12 chronic lymphocytic leukemia patients, demonstrating fit-for-purpose absolute quantitation in a clinical matrix. In 100 samples-per-day mode, the full workflow enables on-demand absolute protein quantitation in 35 min from sample to fully acquired LC-MS data. The achieved sensitivity indicates the feasibility of transfer to other targets or matrices with lower concentrations. Because the required SIL proteins are used at femtomole levels (here, 40 fmol of SIL rituximab spiked into 10 μg of plasma protein), a single 10-μg SIL IgG vial is sufficient as internal standard for ∼1700 injections.
    Keywords:  PSAQ; broad-specificity protease; parallel reaction monitoring (PRM); reduction-free digestion; rituximab; stable isotope-labeled protein standard; therapeutic monoclonal antibody
    DOI:  https://doi.org/10.1021/acs.jproteome.6c00197
  10. Int J Mol Sci. 2026 Apr 29. pii: 3971. [Epub ahead of print]27(9):
    Beyond Correlation: Constraint Architecture Explains Proteome-Metabolome Decoupling.
    Kyung-Hee Kim, Byong Chul Yoo.
      Multi-omics technologies enable parallel quantification of proteomic and metabolomic layers, yet enzyme abundance often shows weak or nonlinear correspondence under diverse biological conditions. This apparent discordance has been attributed to both technical limitations-such as dynamic range compression in LC-MS/MS, metabolite derivatization artifacts, and missing values in proteomic measurements-as well as intrinsic biological properties of metabolic network architecture. While technical factors contribute to cross-omic mismatch, accumulating evidence suggests that constraint-driven network behavior plays a major role in shaping this decoupling. Enzyme abundance constrains catalytic capacity; however, realized flux is selected within this capacity under distributed flux control, as formalized by flux control coefficients in metabolic control analysis, and is further modulated by enzyme kinetics (e.g., km and Vmax), post-translational modifications, substrate availability, and thermodynamic constraints. Metabolite pools, in turn, reflect the physicochemical state of the system, while specific metabolites can also act as regulatory effectors that modulate enzymatic activity and cellular signaling. Because metabolic networks are underdetermined, multiple flux configurations can satisfy identical protein abundance and metabolite concentration data. Static cross-layer correlation is therefore insufficient for mechanistic inference. We synthesize biological mechanisms-including post-translational regulation, allostery, thermodynamic buffering, spatial compartmentalization, feedback amplification, and redox gating-that weaken linear abundance-metabolite expectations. We further outline a constraint-based interpretation framework in which proteomics imposes capacity bounds, metabolomics informs reaction directionality and metabolite pool constraints, and flux-informed approaches reduce solution degeneracy by providing additional information on pathway activity. Moving beyond correlation requires integrating perturbation, temporal resolution, and constraint-aware modeling. Proteome-metabolome discordance should therefore be interpreted not as inconsistency, but as indicative of constraint-driven state selection within high-dimensional biochemical systems.
    Keywords:  constraint-based modeling; fluxomics; metabolic flux; metabolomics; proteomics; redox metabolism; systems biology; thermodynamics
    DOI:  https://doi.org/10.3390/ijms27093971
  11. Analyst. 2026 May 08.
    Simultaneous quantitation of structurally analogous bile acid isomers via charge-state-engineered UPLC-MS.
    Desen Su, Yunyun Zheng, Xiuxian Lin, Ziqiang Chen, Minmin Huang, Qinghua Yao, Yuwu Chi.
      Ursodeoxycholic, hyodeoxycholic, chenodeoxycholic, and deoxycholic acids are endogenous, dihydroxylated bile acid isomers that share a molecular mass but fulfill specific biological roles. However, their isomeric structures complicate analytical separation, while low physiological concentrations demand high detection sensitivity. Consequently, despite the use of liquid chromatography-tandem mass spectrometry for simultaneous analysis, current methodologies are often hampered by inadequate sensitivity and lengthy analysis durations. To address this analytical bottleneck, we developed an ultra-high performance liquid chromatography-mass spectrometry (UPLC-MS) method for the quantitative analysis of four bile acid isomers. This method employs a novel charge-state homogenization strategy, guided by computational prediction of ionization behavior (pH/ionic forms), to optimize chromatographic and mass spectrometric conditions. By inducing complete deprotonation and generating uniform carboxylate anions for all analytes, this approach synergistically enhances the detection sensitivity, chromatographic resolution, and analysis speed. The rigorously validated method demonstrates exceptional performance: sub-ng mL-1 sensitivity (LODs 0.10-0.22 ng mL-1), rapid analysis (<8 min), excellent linearity (R2 > 0.998 over 4 orders of magnitude), high reproducibility (intra/inter-day RSD 1.2-9.1%), and satisfactory accuracy (86.1-107.1% recovery). Its broad applicability was confirmed across diverse matrices (poultry/porcine blood, bile, concentrates), handling trace to high bile acid levels. This rapid, sensitive and highly-resolutive analytical approach addresses key challenges in bile acid isomers quantitation, offering significant advantages for pharmacokinetic research and quality control in animal health and pharmaceutical applications. Furthermore, the underlying charge-state homogenization principle provides a rational framework for optimizing chromatographic parameters (organic modifiers, stationary phases, gradients) in complex analyses.
    DOI:  https://doi.org/10.1039/d6an00420b
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