bims-mascan 2025-11-09 papers

bims-mascan

Biomed News

on Mass spectrometry in cancer research

Issue of 2025–11–09
thirteen papers selected by
Giovanny Rodríguez Blanco, Uniklinikum Graz

Carafe enables high quality in silico spectral library generation for data-independent acquisition proteomics.
Absolute quantification of polar metabolites using matrix-free calibration curves and post-column infusion of standards in HILIC-MS based metabolomics.
Impact of Preprocessing and data analysis strategies on metabolite annotation in biological samples: A mass spectrometry-based metabolomics study using feature-based molecular networking.
OpenSpec Enables Detecting Unexpected Modifications from Proteomics Data Generated by Orbitrap Astral Mass Spectrometer.
Crosstalk between lipid droplets and autophagy in cancer: A nexus for therapeutic targeting.
Comparative evaluation of Olink Explore 3072 and mass spectrometry with peptide fractionation for plasma proteomics.
A Simple and Flexible Strategy for Single-Cell Proteomic Analysis Based on Protein Immobilization and Digestion Tube Reactor.
Data Processing and Analysis in Positional Proteomics.
Clinical glycoproteomics in cancer: toward tissue-based glycoform profiling and biomarker discovery.
Establishing 18O-Labeled Inositol Phosphates for Quantitative Capillary Electrophoresis-Mass Spectrometry: Fragmentation Pathways and Comparison with 13C-Labeled Analogs.
Comparative evaluation of comprehensive offline 2D-LC strategies coupled to MS for untargeted metabolomic studies of human urine.
Not One Method to Rule Them All: A Comparative Study of Chromatographic Platforms (RP-LC-, HILIC-, SFC-, and IC-HRMS) for Water Analysis.
Integrated native digestion and molecular weight cutoff enrichment with DIA-MS: a sensitive and selective approach for quantitative analysis of HCP.

Nat Commun. 2025 Nov 06. 16(1): 9815

Carafe enables high quality in silico spectral library generation for data-independent acquisition proteomics.

Bo Wen, Chris Hsu, David Shteynberg, Wen-Feng Zeng, Michael Riffle, Alexis Chang, Miranda C Mudge, Brook L Nunn, Brendan X MacLean, Matthew D Berg, Judit Villén, Michael J MacCoss, William S Noble.

Data-independent acquisition (DIA)-based mass spectrometry is becoming an increasingly popular mass spectrometry acquisition strategy for carrying out quantitative proteomics experiments. Most of the popular DIA search engines make use of in silico generated spectral libraries. However, the generation of high-quality spectral libraries for DIA data analysis remains a challenge, particularly because most such libraries are generated directly from data-dependent acquisition (DDA) data or are from in silico prediction using models trained on DDA data. In this study, we introduce Carafe, a tool that generates high-quality experiment-specific in silico spectral libraries by training deep learning models directly on DIA data. We demonstrate the performance of Carafe on a wide range of DIA datasets, where we observe improved fragment ion intensity prediction and peptide detection relative to existing pretrained DDA models. To make Carafe more accessible to the community, we integrate Carafe into the widely used Skyline tool.

DOI: https://doi.org/10.1038/s41467-025-64928-4
J Chromatogr A. 2025 Oct 31. pii: S0021-9673(25)00851-9. [Epub ahead of print]1764 466507

Absolute quantification of polar metabolites using matrix-free calibration curves and post-column infusion of standards in HILIC-MS based metabolomics.

Mengle Zhu, Lieke Lamont, Pascal Maas, Amy C Harms, Marian Beekman, P Eline Slagboom, Anne-Charlotte Dubbelman, Thomas Hankemeier.

  Polar metabolites play essential roles in inflammation, immune regulation, and metabolism, and have emerged as important biomarkers in clinical research. However, accurate absolute quantification of these metabolites in complex biological matrices using hydrophilic interaction liquid chromatography-mass spectrometry (HILIC-MS) remains challenging, due to matrix effects that compromise measurement accuracy. While (stable isotope-labeled-) internal standards ((SIL-)IS) are commonly used to correct these effects, their limited availability and high cost can hinder their applicability. In this study, we present a robust approach using HILIC-MS coupled with post-column infusion of standards (PCIS) to enable absolute quantification of polar metabolites in plasma, using calibration curves prepared in neat solution without using SIL standards. First, the optimal PCIS for each metabolite was identified based on absolute matrix effect (AME) values, and method performance was systematically evaluated in terms of linearity, precision, accuracy, and matrix effects. Results showed that the PCIS approach consistently achieved comparable results to (SIL-)IS correction for analytes with SIL standards, and superior performance for analytes without available SIL standards. Application to a study cohort demonstrated consistency between this HILIC-PCIS-MS method and Nuclear Magnetic Resonance (NMR) quantification. Validation using NIST SRM 1950 plasma confirmed high quantification accuracy (80 % - 120 %) for most metabolites using a matrix-free calibration curve combined with PCIS in HILIC-MS. In summary, PCIS offers a promising and cost-effective alternative to (SIL-)IS correction, particularly benefiting metabolites lacking SIL standards, and provides a strategy for accurately correcting matrix effects and advancing quantitative metabolomics in complex biological matrices.

Keywords:  Absolute quantification; HILIC-MS; Matrix effects; Polar metabolites; Post-column infusion of standards

DOI:  https://doi.org/10.1016/j.chroma.2025.466507
J Chromatogr B Analyt Technol Biomed Life Sci. 2025 Oct 28. pii: S1570-0232(25)00382-4. [Epub ahead of print]1268 124828

Impact of Preprocessing and data analysis strategies on metabolite annotation in biological samples: A mass spectrometry-based metabolomics study using feature-based molecular networking.

Qinyu Xiao, Jiamin Yang, Jianjun Xie, Qing Liu, Hongbo Huang, Yiwen Tao, Bo Ding.

  Metabolomics workflows involve multiple complex steps including sample collection, storage, preparation, metabolite extraction, analytical platforms selection, data acquisition and interpretation. Each step may introduce variability that affects the quality and reliability of metabolomic data. To systematically investigate the effects of these factors on metabolomics outcomes, plasma samples from four different anatomical sites of colon cancer patients were analyzed using Liquid chromatography- Quadrupole-Exactive Orbitrap mass spectrometry (LC-Q-Exactive Orbitrap MS) for untargeted metabolomics. Response surface methodology was employed to optimize the ultrasound-assisted extraction conditions during sample pretreatment. Data analysis strategies were systematically evaluated, including Feature-Based Molecular Networking (FBMN) construction parameters and comparative assessment of different FBMN platforms for metabolite annotation. The optimized extraction conditions were determined as 300 % methanol concentration, sample freezing at -20 °C for 40 min, followed by ultrasonication for 5 min. Sample standardization protocols requiring single-use portioning and limiting freeze-thaw cycles to ≤2-3 cycles were identified as essential for reliable biomarker discovery and therapeutic mechanism exploration. Optimal FBMN construction parameters comprised a 25-min gradient elution time, 50 mm chromatographic column length, and high sample concentration. Comparative evaluation of Global Natural Products Social Molecular Networking (GNPS) and MZmine implementations of FBMN revealed that GNPS was recommended for studies prioritizing comprehensive annotation coverage and discovery-oriented metabolomics, while MZmine was preferred for method development, or applications requiring local processing without external data upload. This study demonstrated that preprocessing and data analysis strategies were critical determinants of data quality in untargeted plasma metabolomics. The findings provided evidence-based recommendations for experimental design, storage conditions, and data handling procedures that can guide protocol standardization and minimize undesired analytical variation in metabolomics studies.

Keywords:  FBMN; GNPS; MZmine; Mass spectrometry-based metabolomics; Metabolite annotation; Sample preprocessing

DOI:  https://doi.org/10.1016/j.jchromb.2025.124828
Anal Chem. 2025 Nov 03.

OpenSpec Enables Detecting Unexpected Modifications from Proteomics Data Generated by Orbitrap Astral Mass Spectrometer.

Min Tang, Zhao Sun, Chengpin Shen, Xiaoqing Wang, Xinhang Hou, Xiang Liu, Qiushi Wei, Ao Zhang, Yuzhuo Gu, Jiayuan Zeng, Zekun Cai, Zhenchao Tang, Yang Fu, Jing-Hua Yang, Chao Liu.

The Orbitrap Astral mass spectrometer features outstanding speed, resolution, and sensitivity, making data-independent acquisition (DIA) the preferred method for deep profiling in shotgun proteomics. However, as for data generated by an Orbitrap Astral mass spectrometer, the current search engines cannot detect unexpected modifications, which are novel in biology and chemistry systems. Here we present OpenSpec, a computational workflow specifically designed for comprehensive identification of unexpected modifications from Astral-DIA data sets. The workflow incorporates a Transformer-based precursor-fragment grouping model to deconvolute DIA data to generate DDA-like pseudo-MS/MS spectra, achieving a DDA-based open search strategy on Astral-DIA data. We evaluated OpenSpec through a benchmarking study with synthetic peptides emulating diverse modification patterns and complemented by systematic comparison between DIA and DDA acquisition modes on identical samples. We investigated unexpected modifications of cysteine across various sample pretreatment conditions. OpenSpec is available for download from GitHub: https://github.com/BUAA-LiuLab/OpenSpec.git.

DOI: https://doi.org/10.1021/acs.analchem.5c03055
Pharmacol Res. 2025 Nov 04. pii: S1043-6618(25)00448-7. [Epub ahead of print]222 108023

Crosstalk between lipid droplets and autophagy in cancer: A nexus for therapeutic targeting.

Xiaofen Li, Jiwen Zhang, Shiping Luo, Xiaoqin Yu, Chuangui Song.

  Metabolic reprogramming is a cornerstone of cancer cell adaptation to the demanding tumor microenvironment, requiring fine-tuned control over energy, lipid metabolism, and stress responses. Central to this adaptation is the profound and bidirectional interplay between two key cellular processes: lipid storage in lipid droplets (LDs) and cellular recycling via autophagy. LDs are dynamic organelles that have emerged as critical metabolic and signaling hubs, extending far beyond their role as simple lipid depots. Autophagy, a fundamental degradation system, supplies essential metabolites during stress by engulfing cellular material in autophagosomes. These pathways are deeply intertwined: LDs not only provide lipids and proteins for autophagosome formation but are also selectively targeted for degradation by autophagy in a process known as lipophagy. This degradation releases free fatty acids that fuel mitochondrial β-oxidation, enabling cancer cells to withstand hypoxic and nutrient-poor conditions. Moreover, lipophagy prevents lipotoxicity by eliminating excess lipids, thus maintaining cellular homeostasis. Here, we review the molecular mechanisms governing the LD-autophagy axis in cancer, discuss its pivotal roles in tumor progression, metastasis, and therapeutic resistance, and explore the promise of targeting this nexus for future cancer therapies. Unraveling this complex network provides not only a new paradigm for understanding cancer metabolism but also offers a compelling rationale for developing novel pharmacological agents to combat tumor metabolic plasticity and therapeutic resistance.

Keywords:  Autophagy; Cancer Therapy; Lipid Droplets; Lipophagy; Metabolic Reprogramming; Tumor Microenvironment

DOI:  https://doi.org/10.1016/j.phrs.2025.108023
Commun Chem. 2025 Nov 04. 8(1): 327

Comparative evaluation of Olink Explore 3072 and mass spectrometry with peptide fractionation for plasma proteomics.

Noora Sissala, Haris Babačić, Isabelle R Leo, Xiaofang Cao, Jenny Forshed, Lars E Eriksson, Janne Lehtiö, Claudia Fredolini, Mikael Åberg, Maria Pernemalm.

Plasma proteomics technologies are advancing rapidly, offering new opportunities for biomarker discovery and precision medicine. Direct comparisons of available technologies are needed to understand how platform selection affects downstream findings. We compared the performance of a peptide fractionation-based mass spectrometry method (HiRIEF LC-MS/MS) and the Olink Explore 3072 proximity extension assays on 88 plasma samples, analyzing 1129 proteins with both methods. The platforms exhibited complementary proteome coverage, high precision, and concordance in estimating sex differences in protein levels. Quantitative agreement between platforms was moderate (median correlation 0.59, interquartile range 0.33-0.75), mainly influenced by technical factors. Finally, we present a publicly available tool for peptide-level analysis of platform agreement and demonstrate its utility in clarifying cross-platform discrepancies in protein and proteoform measurements. Our findings provide insights for platform selection and study design, and highlight the value of combining mass spectrometry and affinity-based approaches for more comprehensive and reliable plasma proteome profiling.

DOI: https://doi.org/10.1038/s42004-025-01753-2
Anal Chem. 2025 Nov 04.

A Simple and Flexible Strategy for Single-Cell Proteomic Analysis Based on Protein Immobilization and Digestion Tube Reactor.

Wenjia Zhang, Lingxiao Weng, Guoquan Yan, Wei Liu, Xuantang Wang, Mingxia Gao, Xiangmin Zhang.

Mass spectrometry-based single-cell proteomics (SCP) analysis has witnessed rapid development over the past 10 years. However, the current preprocessing methodologies face several challenges: multiple time-consuming steps, reliance on costly consumables and advanced instrumentation, and the necessity for specialized expertise and training, which hinder the widespread application of deep SCP analysis. Here, we develop a simple and flexible strategy that seamlessly integrates single-cell sampling, preprocessing, and liquid chromatography tandem mass spectrometry (LC-MS/MS) injection by constructing a microliter single-cell protein immobilization and digestion tube reactor (SPIDR), which remains free from additional transfer steps. The reactor, made through inner surface functionalization of a commercially available insert tube, achieves the end-to-end single-cell rapid preprocessing within 1 h at a low cost. The microliter reactor with a relatively large volume, instead of the popular nanoliter/picoliter volume, significantly reduces operational difficulty and facilitates process automation. Using the SPIDR workflow, an average of 4186, 3171, and 4018 protein groups are quantified from single A549 cells (n = 16), HeLa cells (n = 16), and MCF-7 cells (n = 16), respectively. Furthermore, we investigate the proteomic heterogeneity of cervical cancer cells at different apoptotic stages following paclitaxel treatment at the single-cell level, demonstrating the potential of single-cell proteomics in addressing biological problems.

DOI: https://doi.org/10.1021/acs.analchem.5c04778
Proteomics. 2025 Nov 03. e70069

Data Processing and Analysis in Positional Proteomics.

Aleksander Moldt Haack, Konstantinos Kalogeropoulos.

Proteolytic cleavage is an irreversible post-translational modification (PTM), and dysregulation of protease activity is often a hallmark in disease. Aberrant proteolysis can alter protein abundance or function, disturbing cellular state and resulting in disease-specific biomarkers or therapeutic targets. Positional proteomics facilitates global identification and precise quantification of position-specific peptides, such as those located N- or C-terminal in the protein sequence. These techniques enable the study of both natural and neo-protein termini, as well as associated PTMs. Despite its importance, proteolysis remains understudied due to experimental challenges and complex data processing. In this review, we outline key strategies for data analysis and processing in positional proteomics, emphasizing how identification, quantification, and interpretation of proteolytic cleavage sites differ from standard proteomics data analysis pipelines. We discuss differences in common approaches for terminomics-focused workflows, comparing N- versus C-terminomics, as well as different labeling strategies and acquisition methods. Additionally, we highlight considerations for proper normalization approaches, specifically the need to normalize cleavage abundances relative to protein and protease abundance. We explain the importance of integrating structural data, solvent accessibility, and tissue expression profiles during data analysis to better evaluate the biological significance of experimental results.

DOI: https://doi.org/10.1002/pmic.70069
J Biochem. 2025 Nov 03. pii: mvaf063. [Epub ahead of print]

Clinical glycoproteomics in cancer: toward tissue-based glycoform profiling and biomarker discovery.

Yoshimi Haga.

  Recent advances in mass spectrometry-based proteomics have enabled increasingly precise characterization of protein modifications in clinical specimens. Among these, glycosylation is one of the most structurally complex and biologically informative post-translational modifications, reflecting cellular differentiation and disease states. Ohashi et al. (J. Biochem. 2024; 175: 561-572) performed a site-specific N-glycosylation analysis of LAMP1 in breast cancer tissue samples, demonstrating the feasibility of targeted glycoproteomics in patient-derived specimens and revealing tumor-associated glycoform heterogeneity. Their study exemplifies how focusing on a single glycoprotein target can provide detailed insight into disease-specific glycan remodeling within the tumor microenvironment. In this commentary, I discuss the significance of such targeted approaches in the broader context of clinical glycoproteomics and highlight their potential contribution to cancer biomarker discovery and precision medicine. Continued integration of glycoproteomic data with genomic and clinical information is expected to further advance our understanding of tumor biology and therapeutic response.

Keywords:  biomarker; cancer-associated glycans; clinical proteomics; glycoproteomics; mass spectrometry

DOI:  https://doi.org/10.1093/jb/mvaf063
Anal Chem. 2025 Nov 05.

Establishing 18O-Labeled Inositol Phosphates for Quantitative Capillary Electrophoresis-Mass Spectrometry: Fragmentation Pathways and Comparison with 13C-Labeled Analogs.

Guizhen Liu, Tobias Dürr-Mayer, Mengsi Lu, Henning J Jessen.

Capillary electrophoresis mass spectrometry (CE-MS) allows for the rapid and accurate quantitative analysis of inositol phosphates (InsPs) and inositol pyrophosphates (PP-InsPs). The recent discovery of new InsPs and PP-InsPs isomers in plants and mammals necessitates new heavy isotope references for quantitative analysis of complex cellular extracts. Here, we evaluate 18O-labeled InsPs and PP-InsPs as alternatives to 13C labeled internal standards for quantitation by CE-MS. In contrast to 13C labels, the 18O labels are introduced at the end of a synthetic campaign and not at the beginning, rendering 18O much more accessible and affordable as a label. A series of 18O-labeled InsPs and PP-InsPs with different numbers and positions of 18O atoms were synthesized, enabling systematic investigation of MS2 fragmentation pathways. We propose two major dissociation pathways to elucidate the 18O redistribution of the dominant product ion (the loss of H3PO4). Based on these insights, we identified the loss of HPO3 as a suitable transition for minimizing isotope redistribution in MS2 analysis. The ratios of this alternative product ion and dominant product ion were reproducible across replicates, concentration, and measurement days, supporting the use of this alternative product ion as a reliable product ion for quantitative analysis. Application to Saccharomyces cerevisiae, HCT116 cells, and Arabidopsis thaliana extracts confirmed accurate quantitation and precision comparable to 13C-based methods.

DOI: https://doi.org/10.1021/acs.analchem.5c05114
Anal Bioanal Chem. 2025 Nov 01.

Comparative evaluation of comprehensive offline 2D-LC strategies coupled to MS for untargeted metabolomic studies of human urine.

Maria Grübner, Andreas Dunkel, Frank Steiner, Thomas Hofmann.

  Out of the broad selection of analytical methods applied in metabolomic studies, liquid chromatography coupled to mass spectrometry (LC-MS) has the highest coverage potential. In that regard, the quality of the separation process is crucial for the analytical outcome. Reversed-phase (RP) and hydrophilic interaction liquid chromatography (HILIC) are widely applied, and the potential of various setups to combine these modes for more complementary data has been deeply explored. In our previous study on the orthogonality of LC conditions in the field of metabolomics, combinations of a mixed-mode phase with parallel RP and ion-exchange (IEX) properties and several HILIC columns exhibited the widest compound distributions in a two-dimensional (2D) separation space. For further performance evaluation, an offline comprehensive 2D-LC-TOF-MS (LC×LC-TOF-MS) system was set up with the mixed RP/IEX mode in the first dimension (1D) and HILIC mode in the second dimension (2D). The transfer of fractions to the HILIC column and the effect of offline fraction preparation procedures (dilution and evaporation approaches) were comparatively investigated by using reference substances. In addition, the separation performance of the offline LC×LC-TOF-MS system with and without offline fraction preparation was assessed in comparison to other common LC-TOF-MS strategies (direct flow injection DFI, 1D-LC, serial coupling LC) by the number of detectable features in a human urine sample. In conclusion, the direct transfer of 5 µL fraction volumes without offline treatment was the most promising approach for future application in untargeted metabolomic studies for marker identification from human urine.

Keywords:  Comprehensive offline two-dimensional LC; Evaporation; Fractionation; HILIC; Metabolomics; Mixed-mode chromatography

DOI:  https://doi.org/10.1007/s00216-025-06195-2
Anal Chem. 2025 Nov 06.

Not One Method to Rule Them All: A Comparative Study of Chromatographic Platforms (RP-LC-, HILIC-, SFC-, and IC-HRMS) for Water Analysis.

Jonathan Zweigle, Michael Schlüsener, Joana Flottmann, Tobias Bader, Nanna Hjort Vidkjær, Ulla E Bollmann, Jan H Christensen, Selina Tisler.

Reversed-phase liquid chromatography coupled to high-resolution mass spectrometry (RP-LC-HRMS) is the standard for nontarget screening (NTS) of environmental samples but lacks retention of highly polar contaminants. We compared 12 chromatographic methods across four platforms, RP-LC, anion chromatography (IC), supercritical fluid chromatography (SFC), and hydrophilic interaction chromatography (HILIC), using 127 environmentally relevant compounds (logDpH7.4 -5.6 to 6.6). Compounds were analyzed in solvent and for a polar subset, in groundwater enriched by vacuum evaporation. Data were collected across four laboratories using 5 RP-LC-, 3 HILIC-, 2 SFC-, and 2 IC-HRMS setups. Feature detection with standard tools yielded more false negatives for SFC and IC. To enable a fair and method-agnostic comparison, an extracted ion chromatogram (EIC)-based workflow was used. Of the 127 compounds, 125 were detected by at least one platform. For logDpH7.4 > 0, RP-LC covered ∼90%, followed by SFC (∼70%), while IC and HILIC each covered <30%. For very polar compounds (logDpH7.4 < 0), coverage dropped across all platforms. SFC and HILIC detected up to 60% of polar analytes; IC performed better in negative ionization mode, consistent with anion-exchange separation. Detection frequency declined with polarity, reflecting analytical limitations. Combining RP-LC with either SFC or HILIC increased coverage to 94%. In spiked groundwater, coverage was lower (73%) due to matrix effects and losses during vacuum enrichment. Peak widths were narrowest for SFC (∼2.5 s) and RP-LC (∼4 s) and broadest for HILIC (∼7 s) and IC (∼17 s). Retention times showed limited cross-platform correlation while ionization efficiency was consistent, except for SFC. As no single method provided full coverage, combining RP-LC with one complementary platform (SFC, HILIC, or IC) is required to extend chemical space in environmental NTS.

DOI: https://doi.org/10.1021/acs.analchem.5c04114
Talanta. 2025 Oct 29. pii: S0039-9140(25)01543-7. [Epub ahead of print]298(Pt B): 129052

Integrated native digestion and molecular weight cutoff enrichment with DIA-MS: a sensitive and selective approach for quantitative analysis of HCP.

Yachuan Gong, Yanjia Zhao, Rui Peng, Wen Qi, Yi Zhang, Ying Peng, Jiang Zheng.

  Residual host cell proteins (HCPs) in biopharmaceutical production processes not only compromise drug efficacy but also pose risks to patient safety and product stability, particularly when high-risk HCPs are present. Continuous monitoring of HCPs content and species during downstream purification is therefore critical. Although liquid chromatography-mass spectrometry-based proteomics has emerged as a promising approach for HCP identification, its application is hindered by the substantial dynamic range disparity between high-abundance therapeutic proteins and trace-level HCPs (at parts-per-million, ppm, concentrations). Here, we developed an innovative workflow that eliminates conventional therapeutic protein pre-separation steps for increasing HCP detection. By integrating a two-stage native digestion strategy with molecular weight cutoff filtration, efficient HCP separation and enrichment were achieved. Mass spectrometry data were acquired in data-independent acquisition mode and processed using Spectronaut software for spectral library construction. This integrated approach enabled sensitive detection of HCPs down to 0.5 ppm and continuous quantitative tracking of critical impurities such as the high-risk protein PLBD2, thereby providing real-time monitoring of antibody purification processes and supporting process optimization. Comparative studies with ELISA demonstrated superior sensitivity and specificity of our approach, while systematic method validation confirmed its compliance with bioanalytical requirements, establishing the robustness of the proposed methodology.

Keywords:  DIA; HCP; MWCO; Quantitation

DOI:  https://doi.org/10.1016/j.talanta.2025.129052