bims-mascan Biomed News
on Mass spectrometry in cancer research
Issue of 2025–01–26
23 papers selected by
Giovanny Rodríguez Blanco, Uniklinikum Graz



  1. Nat Protoc. 2025 Jan 17.
      Deep and accurate proteome analysis is crucial for understanding cellular processes and disease mechanisms; however, it is challenging to implement in routine settings. In this protocol, we combine a robust chromatographic platform with a high-performance mass spectrometric setup to enable routine yet in-depth proteome coverage for a broad community. This entails tip-based sample preparation and pre-formed gradients (Evosep One) combined with a trapped ion mobility time-of-flight mass spectrometer (timsTOF, Bruker). The timsTOF enables parallel accumulation-serial fragmentation (PASEF), in which ions are accumulated and separated by their ion mobility, maximizing ion usage and simplifying spectra. Combined with data-independent acquisition (DIA), it offers high peak sampling rates and near-complete ion coverage. Here, we explain how to balance quantitative accuracy, specificity, proteome coverage and sensitivity by choosing the best PASEF and DIA method parameters. The protocol describes how to set up the liquid chromatography-mass spectrometry system and enables PASEF method generation and evaluation for varied samples by using the py_diAID tool to optimally position isolation windows in the mass-to-charge and ion mobility space. Biological projects (e.g., triplicate proteome analysis in two conditions) can be performed in 3 d with ~3 h of hands-on time and minimal marginal cost. This results in reproducible quantification of 7,000 proteins in a human cancer cell line in quadruplicate 21-min injections and 29,000 phosphosites for phospho-enriched quadruplicates. Synchro-PASEF, a highly efficient, specific and novel scan mode, can be analyzed by Spectronaut or AlphaDIA, resulting in superior quantitative reproducibility because of its high sampling efficiency.
    DOI:  https://doi.org/10.1038/s41596-024-01104-w
  2. Nat Commun. 2025 Jan 21. 16(1): 892
      Quality control (QC) in mass spectrometry (MS)-based proteomics is mainly based on data-dependent acquisition (DDA) analysis of standard samples. Here, we collect 2754 files acquired by data independent acquisition (DIA) and paired 2638 DDA files from mouse liver digests using 21 mass spectrometers across nine laboratories over 31 months. Our data demonstrate that DIA-based LC-MS/MS-related consensus QC metrics exhibit higher sensitivity compared to DDA-based QC metrics in detecting changes in LC-MS status. We then prioritize 15 metrics and invite 21 experts to manually assess the quality of 2754 DIA files based on those metrics. We develop an AI model for DIA-based QC using 2110 training files. It achieves AUCs of 0.91 (LC) and 0.97 (MS) in the first validation dataset (n = 528), and 0.78 (LC) and 0.94 (MS) in an independent validation dataset (n = 116). Finally, we develop an offline software called iDIA-QC for convenient adoption of this methodology.
    DOI:  https://doi.org/10.1038/s41467-024-54871-1
  3. Anal Bioanal Chem. 2025 Jan 24.
      Quantitative measurement of metabolites is essential to understand biological and disease processes. Absolute quantification by spiking heavy isotope-labeled internal standards and analyzing on mass spectrometry (MS) platform is a key method to determine the concentration of metabolites in biological samples. However, MS-based absolute quantification is often challenged by the commercial availability and high costs of isotope-labeled internal standards. Here, we establish an absolute quantification method for amine metabolites utilizing isotopic N,N-dimethyl leucine (iDiLeu) tagging on the LC-MS/MS platform. Absolute quantification of metabolites with excellent accuracy and precision can be achieved with five-plex iDiLeu labeling without the need of isotope-labeled internal standards. We demonstrated that iDiLeu labeling improved the separation and detection limits of polar metabolites. Particularly, detection limits for glycine, GABA, and serotonin have been improved by more than 20 folds, and valine by more than 2000 folds. With iDiLeu tagging, 87 amine-containing metabolites were identified and quantified in human cerebrospinal fluid (CSF) samples, revealing potential metabolic changes in Alzheimer's disease patients.
    Keywords:  Absolute quantification; Alzheimer’s disease; Human cerebrospinal fluid; IDiLeu; Mass spectrometry; Metabolites
    DOI:  https://doi.org/10.1007/s00216-025-05748-9
  4. J Proteome Res. 2025 Jan 24.
      Data-independent acquisition (DIA) on ion mobility mass spectrometers enables deep proteome coverage and high data completeness in large-scale proteomics studies. For advanced acquisition schemes such as parallel accumulation serial fragmentation-based DIA (diaPASEF) stability of ion mobility (1/K0) over time is crucial for consistent data quality. We found that minor changes in environmental air pressure systematically affect the vacuum pressure in the TIMS analyzer, causing ion mobility shifts. By comparing experimental ion mobilities with historical weather data, we attributed observed drifts to fluctuations in the ground air pressure. Moderate air pressure changes of e.g. fifteen mbar induce ion mobility shifts of 0.025 Vs/cm2. These drifts negatively impact peptide quantification across consecutively acquired samples due to drift-dependent abundance changes and increased missing values for ions located at the boundaries of diaPASEF isolation windows, which cannot be corrected by postprocessing. To address this, we applied an in-batch mobility autocalibration feature on a run-wise basis, leading to full elimination of ion mobility drifts.
    Keywords:  Data-independent acquisition (DIA); TIMS TOF; diaPASEF; ion mobility shifts; peptide; quantification
    DOI:  https://doi.org/10.1021/acs.jproteome.4c00932
  5. J Proteome Res. 2025 Jan 22.
      We introduce here a novel approach, termed time-segmented acquisition (Seg), to enhance the identification of peptides and proteins in trapped ion mobility spectrometry (TIMS)-time-of-flight (TOF) mass spectrometry. Our method exploits the positive correlation between ion mobility values and reversed-phase liquid chromatography (LC) retention time to improve ion separation and resolution. By dividing the LC retention time into multiple segments and applying a segment-specific narrower ion mobility range within the TIMS tunnel, we achieved better separation and higher resolution of ion mobility. In comparison to conventional TIMS methods, which typically scan a static ion mobility range (either from 0.6 to 1.6 [Wide] or from 0.85 to 1.3 [Narrow], V × s/cm2), the Seg method demonstrates marked improvements in identification rates. Compared to Wide scanning, the Seg method increases peptide identifications by 17-27% and protein identifications by 6-16% depending on the gradient length and the sample load. The enhancement in peptide identification is even more pronounced when compared to Narrow scanning, with an increase of 34-86%. These findings highlight the potential of the Seg dda-PASEF method in expanding the capabilities of TIMS-TOF mass spectrometry, especially for peptide-focused analyses, such as post-translational modifications and peptidomics.
    Keywords:  TIMS-TOF; dda-PASEF; ion mobility; label-free quantitation; phosphoproteomics
    DOI:  https://doi.org/10.1021/acs.jproteome.4c00690
  6. J Proteome Res. 2025 Jan 23.
      Mass spectrometry is a cornerstone of quantitative proteomics, enabling relative protein quantification and differential expression analysis (DEA) of proteins. As experiments grow in complexity, involving more samples, groups, and identified proteins, interactive differential expression analysis tools become impractical. The prolfquapp addresses this challenge by providing a command-line interface that simplifies DEA, making it accessible to nonprogrammers and seamlessly integrating it into workflow management systems. Prolfquapp streamlines data processing and result visualization by generating dynamic HTML reports that facilitate the exploration of differential expression results. These reports allow for investigating complex experiments, such as those involving repeated measurements or multiple explanatory variables. Additionally, prolfquapp supports various output formats, including XLSX files, SummarizedExperiment objects and rank files, for further interactive analysis using spreadsheet software, the exploreDE Shiny application, or gene set enrichment analysis software, respectively. By leveraging advanced statistical models from the prolfqua R package, prolfquapp offers a user-friendly, integrated solution for large-scale quantitative proteomics studies, combining efficient data processing with insightful, publication-ready outputs.
    Keywords:  differential expression analysis; proteomics; statistical software; workflows
    DOI:  https://doi.org/10.1021/acs.jproteome.4c00911
  7. Transl Lung Cancer Res. 2024 Dec 31. 13(12): 3692-3717
      For over a century, we have appreciated that the biochemical processes through which micro- and macronutrients are anabolized and catabolized-collectively referred to as "cellular metabolism"-are reprogrammed in malignancies. Cancer cells in lung tumors rewire pathways of nutrient acquisition and metabolism to meet the bioenergetic demands for unchecked proliferation. Advances in precision medicine have ushered in routine genotyping of patient lung tumors, enabling a deeper understanding of the contribution of altered metabolism to tumor biology and patient outcomes. This paradigm shift in thoracic oncology has spawned a new enthusiasm for dissecting oncogenotype-specific metabolic phenotypes and creates opportunity for selective targeting of essential tumor metabolic pathways. In this review, we discuss metabolic states across histologic and molecular subtypes of lung cancers and the additional changes in tumor metabolic pathways that occur during acquired therapeutic resistance. We summarize the clinical investigation of metabolism-specific therapies, addressing successes and limitations to guide the evaluation of these novel strategies in the clinic. Beyond changes in tumor metabolism, we also highlight how non-cellular autonomous processes merit particular consideration when manipulating metabolic processes systemically, such as efforts to disentangle how lung tumor cells influence immunometabolism. As the future of metabolic therapeutics hinges on use of models that faithfully recapitulate metabolic rewiring in lung cancer, we also discuss best practices for harmonizing workflows to capture patient specimens for translational metabolic analyses.
    Keywords:  Lung cancer; immunometabolism; metabolism; resistance
    DOI:  https://doi.org/10.21037/tlcr-24-662
  8. Antibodies (Basel). 2025 Jan 07. pii: 3. [Epub ahead of print]14(1):
      This review describes mass spectrometry (MS)-based approaches for the absolute quantification of therapeutic monoclonal antibodies (mAbs), focusing on technical challenges in sample treatment and calibration. Therapeutic mAbs are crucial for treating cancer and inflammatory, infectious, and autoimmune diseases. We trace their development from hybridoma technology and the first murine mAbs in 1975 to today's chimeric and fully human mAbs. With increasing commercial relevance, the absolute quantification of mAbs, traceable to an international standard system of units (SI units), has attracted attention from science, industry, and national metrology institutes (NMIs). Quantification of proteotypic peptides after enzymatic digestion using high-performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS) has emerged as the most viable strategy, though methods targeting intact mAbs are still being explored. We review peptide-based quantification, focusing on critical experimental steps like denaturation, reduction, alkylation, choice of digestion enzyme, and selection of signature peptides. Challenges in amino acid analysis (AAA) for quantifying pure mAbs and peptide calibrators, along with software tools for targeted MS data analysis, are also discussed. Short explanations within each chapter provide newcomers with an overview of the field's challenges. We conclude that, despite recent progress, further efforts are needed to overcome the many technical hurdles along the quantification workflow and discuss the prospects of developing standardized protocols and certified reference materials (CRMs) for this goal. We also suggest future applications of newer technologies for absolute mAb quantification.
    Keywords:  absolute quantification; certified reference material; isotope labeling; liquid chromatography; mass spectrometry; metrology; monoclonal antibody; therapeutic antibodies; traceability
    DOI:  https://doi.org/10.3390/antib14010003
  9. Front Pharmacol. 2024 ;15 1531524
       Background: Lipids are vital biomolecules involved in the formation of various biofilms. Seizures can cause changes in lipid metabolism in the brain. In-depth studies at multiple levels are urgently needed to elucidate lipid composition, distribution, and metabolic pathways in the brain after seizure.
    Methods: In this research, a cutting-edge targeted quantitative lipidomics study was conducted on the hippocampal tissues of six rats with temporal lobe epilepsy and six normal rats. Accurate lipid quantification based on linear equations was calculated using an internal standard. The lipids were quantitatively and qualitatively analyzed by ultra-high performance liquid chromatography (UPLC) and mass spectrometry (MS).
    Results: A total of 21 lipid classes were identified. Among them, the most abundant were triacylglycerol (TG), phosphatidyl ethanolamine (PE-P), and fatty acids (FA). Cholesteryl ester (ChE) exhibits the most considerable difference between the normal and epileptic samples. ChE was found to be the most significantly upregulated lipid, while FA was observed to be the most significantly downregulated lipid.
    Conclusion: Based on the absolute quantitative analysis of lipids in rat hippocampal specimens, the contents and change trends of different lipids were observed. Upregulation of ChE and dihydroceramide (DHCer) was observed, and an analysis of the distribution changes elucidated the causes and possible molecular mechanisms of lipid accumulation in temporal lobe epilepsy. The results and methods described provide a comprehensive analysis of lipid metabolism in temporal lobe epilepsy and a new therapeutic target for the treatment of epilepsy.
    Keywords:  epilepsy; molecular mechanism; targeted lipidomics analysis; temporal lobe epilepsy; therapeutic target
    DOI:  https://doi.org/10.3389/fphar.2024.1531524
  10. Anal Chim Acta. 2025 Feb 08. pii: S0003-2670(24)01352-7. [Epub ahead of print]1338 343551
      Chemical proteomics has advanced small molecule ligand discovery by providing insights into protein-ligand binding mechanism and enabling medicinal chemistry optimization of protein selectivity on a global scale. Mass spectrometry is the predominant analytical method for chemoproteomics, and various approaches have been deployed to investigate and target a rapidly growing number of protein classes and biological systems. Two methods, intact mass analysis (IMA) and top-down proteomics (TDMS), have gained interest in recent years due to advancements in high resolution mass spectrometry instrumentation. Both methods apply mass spectrometry analysis at the proteoform level, as opposed to the peptide level of bottom-up proteomics (BUMS), thus addressing some of the challenges of protein inference and incomplete information on modification stoichiometry. This Review covers recent research progress utilizing MS-based proteomics methods, discussing in detail the capabilities and opportunities for improvement of each method. Further, heightened attention is given to IMA and TDMS, highlighting these methods' strengths and considerations when utilized in chemoproteomic studies. Finally, we discuss the capabilities of native mass spectrometry (nMS) and ion mobility mass spectrometry (IM-MS) and how these methods can be used in chemoproteomics research to complement existing approaches to further advance the field of functional proteomics.
    DOI:  https://doi.org/10.1016/j.aca.2024.343551
  11. Mini Rev Med Chem. 2025 Jan 17.
      Metabolic reprogramming is a hallmark of cancer. Distinct and unusual metabolic aberrations occur during tumor development that lead to the growth and development of tumors. Oncogenic signaling pathways eventually converge to regulate three major metabolic pathways in tumor cells i.e., glucose, lipid, and amino acid metabolism. Therefore, identifying and targeting the metabolic nodes of cancer cells can be a promising intervention and therapeutic strategy for patients with malignancies. The long road of new drug discovery for cancer therapy has necessitated relooking alternative strategies such as drug repurposing. Advanced genomic and proteomic technologies for the assessment of cancer-specific biological pathways have led to the discovery of new drug targets, which provide excellent opportunities for drug repurposing. The development of effective, safe, cheaper, and readily available anticancer agents is the need of the hour, and drug repurposing has the potential to break the current drug shortage bottleneck. This review will accordingly cover various metabolic pathways that are aberrant in cancer, and strategies for targeting metabolic reprogramming by using repurposed drugs.
    Keywords:  Drug repurposing; cancer; cancer metabolism; cancer treatment; cell deathh; metabolic reprogramming
    DOI:  https://doi.org/10.2174/0113895575339660250106093738
  12. Annu Rev Anal Chem (Palo Alto Calif). 2025 Jan 23.
      Mass spectrometry (MS)-based top-down proteomics (TDP) characterizes proteoforms in cells, tissues, and biological fluids (e.g., human plasma) to better our understanding of protein function and to discover new protein biomarkers for disease diagnosis and therapeutic development. Separations of proteoforms with high peak capacity are needed due to the high complexity of biological samples. Capillary electrophoresis (CE)-MS has been recognized as a powerful analytical tool for protein analysis since the 1980s owing to its high separation efficiency and sensitivity of CE-MS for proteoforms. Here, we review benefits of CE-MS for advancing TDP, challenges and solutions of the method, and the main research areas in which CE-MS-based TDP can make significant contributions. We provide a brief perspective of CE-MS-based TDP moving forward.
    DOI:  https://doi.org/10.1146/annurev-anchem-071124-092242
  13. Nat Metab. 2025 Jan 20.
      Increased glycolytic flux is a hallmark of cancer; however, an increasing body of evidence indicates that glycolytic ATP production may be dispensable in cancer, as metabolic plasticity allows cancer cells to readily adapt to disruption of glycolysis by increasing ATP production via oxidative phosphorylation. Using functional genomic screening, we show here that liver cancer cells show a unique sensitivity toward aldolase A (ALDOA) depletion. Targeting glycolysis by disrupting the catalytic activity of ALDOA led to severe energy stress and cell cycle arrest in murine and human hepatocellular carcinoma cell lines. With a combination of metabolic flux analysis, metabolomics, stable-isotope tracing and mathematical modelling, we demonstrate that inhibiting ALDOA induced a state of imbalanced glycolysis in which the investment phase outpaced the payoff phase. Targeting ALDOA effectively converted glycolysis from an energy producing into an energy-consuming process. Moreover, we found that depletion of ALDOA extended survival and reduced cancer cell proliferation in an animal model of hepatocellular carcinoma. Thus, our findings indicate that induction of imbalanced glycolysis by targeting ALDOA presents a unique opportunity to overcome the inherent metabolic plasticity of cancer cells.
    DOI:  https://doi.org/10.1038/s42255-024-01201-w
  14. Metabolites. 2025 Jan 14. pii: 48. [Epub ahead of print]15(1):
      Introduction: NMR spectroscopy is a powerful technique for studying metabolism, either in metabolomics settings or through tracing with stable isotope-enriched metabolic precursors. MetaboLabPy (version 0.9.66) is a free and open-source software package used to process 1D- and 2D-NMR spectra. The software implements a complete workflow for NMR data pre-processing to prepare a series of 1D-NMR spectra for multi-variate statistical data analysis. This includes a choice of algorithms for automated phase correction, segmental alignment, spectral scaling, variance stabilisation, export to various software platforms, and analysis of metabolic tracing data. The software has an integrated help system with tutorials that demonstrate standard workflows and explain the capabilities of MetaboLabPy. Materials and Methods: The software is implemented in Python and uses numerous Python toolboxes, such as numpy, scipy, pandas, etc. The software is implemented in three different packages: metabolabpy, qtmetabolabpy, and metabolabpytools. The metabolabpy package contains classes to handle NMR data and all the numerical routines necessary to process and pre-process 1D NMR data and perform multiplet analysis on 2D-1H, 13C HSQC NMR data. The qtmetabolabpy package contains routines related to the graphical user interface. Results: PySide6 is used to produce a modern and user-friendly graphical user interface. The metabolabpytools package contains routines which are not specific to just handling NMR data, for example, routines to derive isotopomer distributions from the combination of NMR multiplet and GC-MS data. A deep-learning approach for the latter is currently under development. MetaboLabPy is available via the Python Package Index or via GitHub.
    Keywords:  NMR; Python; deep learning; metabolomics; stable isotope; tracing
    DOI:  https://doi.org/10.3390/metabo15010048
  15. Anal Chem. 2025 Jan 23.
      Metabolite levels and turnover rates are necessary to understand metabolomic dynamics in a living organism fully. Amino acids can play distinct roles in various cellular processes, and their abnormal levels are associated with pathological conditions, including cancer. Therefore, their levels, especially turnover rates, may provide enormous information about a phenotype. 13C- or 13C,15N-labeled amino acids have also been commonly used to trace amino acid metabolism. This study presented a new methodology based on 18O labeling for amino acids that relied on monitoring mass isotopologues to calculate the turnover rates of amino acids. The method optimization studies were carried over for selective amino acid monitoring. This methodology provides a rapid, robust, and simple GC-MS method for analyzing the fluxes of amino acid metabolism. The developed method was applied to fetal human colon (FHC) and human colon carcinoma (Caco-2) cell lines to determine cancer-induced shifts in the turnover rates of amino acids. These results defined metabolic reprogramming in Caco-2 cells through increased glutamate and serine turnovers and sharply decreased turnovers of aspartate, threonine, and methionine, therefore pointing to some metabolic vulnerabilities in the metabolism of cancerous cells. The simple mechanism of the developed methodology, the availability of affordable 18O-enriched water, and the ease of application can open a new arena in fluxomics analysis.
    DOI:  https://doi.org/10.1021/acs.analchem.4c05015
  16. Rapid Commun Mass Spectrom. 2025 Jan 23. e9985
       RATIONALE: Teaching mass spectrometry essentials is usually connected with one of the basic courses for undergrads. Thus, specific previous knowledge is required from students. However, the necessity of teaching mass spectrometry essentials to students of different academic specializations and multidisciplinary groups can arise in every academic group. A specific workshop is needed to address such a demand.
    METHODS: The presented workshop consisted of several thematic parts: assembling an ambient ionization ion source using improvised materials, preparing biological samples for analysis, data acquisition, and interpretation of data to solve a simple problem from the real world.
    RESULTS: The first part of the work consisted of assembling an ambient ionization setup and obtaining mass spectra of substances from standard solutions, natural mixtures, and biological fluids such as saliva. The second half of the workshop consists of analyzing the composition of fatty acids of natural and artificial fats using the same ion source. The identification of oils is a simple model problem that makes the workshop attractive for attendees with different backgrounds.
    CONCLUSIONS: The workshop provides students with practical skills that are highly valuable in fundamental and applied mass spectrometry. Students familiarize themselves with the basic concepts, instrument use, and mass spectra interpretation. They achieve basic hands-on experience in experimentation procedures and the practice of using mass spectrometry to solve problems related to real life.
    Keywords:  education; fatty acids methyl esters; paper spray; touch spray
    DOI:  https://doi.org/10.1002/rcm.9985
  17. Cancer Metab. 2025 Jan 21. 13(1): 2
       BACKGROUND: Leptomeningeal metastasis (LM) is a devastating complication of cancer that is difficult to treat. Thus, early diagnosis is essential for LM patients. However, cerebrospinal fluid (CSF) cytology has low sensitivity, and imaging approaches are ineffective. We explored targeted CSF metabolic profiling to discriminate among LM and other conditions affecting the central nervous system (CNS).
    METHODS: We quantitatively measured amino acids, biogenic amines, hexoses, acylcarnitines (AC), cholesteryl esters (CE), glycerides, phosphatidylcholines (PC), lysophosphatidylcholines (LPC), sphingomyelins (SM), and ceramides (Cer) in 117 CSF samples from various groups of healthy controls (HC, n = 10), patients with LM (LM, n = 47), parenchymal brain tumor (PBT, n = 45), and inflammatory disease (ID, n = 13) with internal standards using the Absolute IDQ- p400® targeted mass spectrometry kit. Metabolites detected in > 90% of samples or showing a difference in proportional level between groups ≥ 75% were used in logistic regression models when there was no single metabolite with AUC = 1 for the groups of comparison.
    RESULTS: PC and SM had higher levels in LM than in PBT or HC, whereas LPC had lower level in PBT than the other groups. Glycerides and Cer levels were higher in PBT and LM than in HC. Long-chain AC level in PBT was lower than in LM or HC. A regression model including Ala, PC (42:7), PC (30:3), PC (37:0), and Tyr achieved complete discrimination (AUC = 1.0) between LM and HC. In comparison of PBT and HC, twenty-six individual metabolites allowed complete discrimination between two groups, and between ID and HC fourty-six individual lipid metabolites allowed complete discrimination. Twenty-one individual metabolites (18 ACs and 3 PCs) allowed complete discrimination between LM and PBT.
    CONCLUSIONS: Using a commercial targeted liquid chromatography-mass spectrometry (LC-MS) metabolomics kit, we were able to differentiate LM from HC and PBT. Most of the discriminative metabolites among different diseases were lipid metabolites, for which their CNS distribution and quantification in different cell types are largely unknown, whereas amino acids, biogenic amines, and hexoses failed to show significant differences. Future validation studies with larger, controlled cohorts should be performed, and hopefully, the kit may expand its metabolite coverage for unique cancer cell glucose metabolism.
    Keywords:  Cerebrospinal fluid; Diagnosis; Leptomeningeal metastasis; Metabolome; Profile
    DOI:  https://doi.org/10.1186/s40170-024-00367-x
  18. Metabolites. 2025 Jan 16. pii: 62. [Epub ahead of print]15(1):
      Blood microsampling (BμS) has recently emerged as an interesting approach in the analysis of endogenous metabolites but also in metabolomics applications. Their non-invasive way of use and the simplified logistics that they offer renders these technologies highly attractive in large-scale studies, especially the novel quantitative microsampling approaches such as VAMs or qDBS. Objectives: Herein, we investigate the potential of BµS devices compared to the conventional plasma samples used in global untargeted mass spectrometry-based metabolomics of blood. Methods: Two novel quantitative devices, namely, Mitra, Capitainer, and the widely used Whatman cards, were selected for comparison with plasma. Venous blood was collected from 10 healthy, overnight-fasted individuals and loaded on the devices; plasma was also collected from the same venous blood. An extraction solvent optimization study was first performed on the three devices before the main study, which compared the global metabolic profiles of the four extracts (three BµS devices and plasma). Analysis was conducted using reverse phase LC-TOF MS in positive mode. Results: BµS devices, especially Mitra and Capitainer, provided equal or even superior information on the metabolic profiling of human blood based on the number and intensity of features and the precision and stability of some annotated metabolites compared to plasma. Despite their rich metabolic profiles, BµS did not capture metabolites associated with biological differentiation of sexes. Conclusions: Overall, our results suggest that a more in-depth investigation of the acquired information is needed for each specific application, as a metabolite-dependent trend was obvious.
    Keywords:  blood metabolic phenotype; blood metabolites; blood microsampling (BµS); dried blood spot (DBS); global metabolic profile; liquid chromatography–mass spectrometry (LC-MS); metabolome; quantitative dried blood spots (qDBS); untargeted metabolomics; volumetric absorptive microsampling (VAM)
    DOI:  https://doi.org/10.3390/metabo15010062
  19. Anal Chem. 2025 Jan 20.
      The identification of polar and neutral lipid species as biomarkers in complex biological samples is a key task in clinical and life sciences. Electrospray and plasma-based ionization techniques are necessary to cover the full range of lipidomes, owing to their limited molecular polarity ranges. However, combining both to generate hybrid spectra is difficult without averaging spectra, as electrospray and plasma sources operate under vastly different conditions. Their electric fields also interfere, resulting in a mutual destabilization of the ionization processes. Herein, a heated nanoelectrospray is combined with a flexible microtube plasma using a rapid (kHz range) switching process (heated nESI-sFμTP) to generate quasi-simultaneous ionization. This approach loads the ion trap with polar and less-polar ions during each injection cycle, generating hybrid spectra without averaging it. The performance of the quasi-simultaneous approach is investigated in positive ion mode, comparing it with conventional ion sources through the analysis of complex lipid liver and heart samples. While no improvements are observed in negative ion mode, the novel quasi-simultaneous approach shows great potential for analyzing complex samples in positive ion mode. The combined heated nESI-sFμTP exceeds the molecular polarity range of individual sources, offering excellent ionization efficiency and MS2 capabilities.
    DOI:  https://doi.org/10.1021/acs.analchem.4c03621
  20. Curr Cancer Drug Targets. 2025 Jan 22.
      Pancreatic Cancer (PC) is a devastating malignancy with a poor prognosis and in-creasing morbidity. Current treatment strategies have limited efficacy in improving patient survival. Metabolic reprogramming is a hallmark of cancer and plays a key role in the pro-gression and maintenance of PC. PC cells exhibit a unique glutamine metabolism that is dis-tinct from other cancer types. The non-classical pathway of glutamine metabolic reprogram-ming plays a "permissive role" in the survival and proliferation of PC cells, mainly by affect-ing the redox homeostasis of the cells. In this review, we compare and contrast the canonical and non-canonical glutamine metabolic pathways and highlight recent advances in targeting non-canonical glutamine metabolism for therapeutic intervention. This may provide novel in-sights and opportunities for exploiting glutamine metabolic reprogramming in PC treatment.
    Keywords:  Pancreatic cancer; glutamine metabolism; glutamine metabolism inhibitors; metabolic reprogramming; targeted treat-ment.
    DOI:  https://doi.org/10.2174/0115680096357993241206072609
  21. J Pharm Biomed Anal. 2025 Jan 20. pii: S0731-7085(25)00025-1. [Epub ahead of print]256 116684
      Alkaptonuria (AKU) is a rare autosomal-recessive disease which is characterized through black urine and ochronosis. It is caused by deficiency of the enzyme Homogentisate 1,2-dioxygenase in the Phenylalanine/Tyrosine degradation pathway which leads to the accumulation of Homogentisic acid (HGA). Urine was provided by AKU patients and healthy controls. Several different methods were developed in this study each with a specific goal. Firstly, a simple and inexpensive RP-UHPLC-UV method for routine monitoring of HGA as a key metabolite employing a Phenylhexyl stationary phase chemistry. Validation was performed in accordance to FDA guidelines and method selectivity was further evaluated via on-line high-resolution sampling 2D-LC-QToF-MS, coupling the Phenylhexyl phase in the first dimension with a C18 phase in the second dimension. Secondly, a targeted and accurate RP-UHPLC-MRM-QTRAP assay, providing quantitative analysis of the relevant pathway metabolites based on a Phenylhexyl stationary phase, and lastly an untargeted HILIC-UHPLC-QToF-MS/MS method with SWATH (sequential window acquisition of all theoretical mass spectra) acquisition employing a sulfobetaine-type HILIC-Z superficially porous particle column, with the aim of uncovering more details about the metabolic profile of this genetic disorder. By untargeted analysis 204 metabolites could be detected and annotated in positive and negative ESI mode in total. Two separate LC methods were employed, differing in their conditions depending on the ionization mode (20 mM ammonium formate as buffer additive adjusted to a pH = 3.5 with formic acid in ESI+ mode and 20 mM ammonium acetate adjusted to a pH = 7.5 with acetic acid in ESI- mode). By effectively combining the aforementioned methods, a comprehensive workflow was developed, allowing the effective analysis of both patient and control urine samples.
    Keywords:  Data-independent acquisition; HILIC; Inherited metabolic disease; Mass spectrometry; Phenylhexyl-column; Sulfobetaine-column
    DOI:  https://doi.org/10.1016/j.jpba.2025.116684
  22. Aging Clin Exp Res. 2025 Jan 21. 37(1): 28
       BACKGROUND: Osteopenia (ON) and osteoporosis (OP) are highly prevalent among postmenopausal women and poses a challenge for early diagnosis. Therefore, identifying reliable biomarkers for early prediction using metabolomics is critically important.
    METHODS: Initially, non-targeted metabolomics was employed to identify differential metabolites in plasma samples from cohort 1, which included healthy controls (HC, n = 23), osteonecrosis (ON, n = 36), and osteoporosis (OP, n = 37). Subsequently, we performed targeted metabolomic validation of 37 amino acids and their derivatives in plasma samples from cohort 2, consisting of healthy controls (HC, n = 10), osteonecrosis (ON, n = 10), and osteoporosis (OP, n = 10).
    RESULTS: The non-targeted metabolomic analysis revealed an increase in differential metabolites with the progression of the disease, showing abnormalities in lipid and organic acid metabolism in ON and OP patients. Several substances were found to correlate positively or negatively with bone mineral density (BMD), for example, N-undecanoylglycine, sphingomyelins, and phosphatidylinositols exhibited positive correlations with BMD, while acetic acid, phenylalanine, taurine, inosine, and pyruvic acid showed negative correlations with BMD. Subsequently, targeted validation of 37 amino acids and their metabolites revealed six amino acids related to ON and OP.
    CONCLUSION: Significant metabolomic features were identified between HC and patients with ON/OP, with multiple metabolites correlating positively or negatively with BMD. Integrating both targeted and non-targeted metabolomic results suggests that lipid, organic acid, and amino acid metabolism may represent important metabolomic characteristics of patients with OP, offering new insights into the development of metabolomic applications in OP.
    Keywords:  Biomarker; Metabolomics; Osteopenia; Osteoporosis; Postmenopausal women
    DOI:  https://doi.org/10.1007/s40520-024-02923-3
  23. Mol Cell Proteomics. 2025 Jan 20. pii: S1535-9476(25)00005-2. [Epub ahead of print] 100907
      Extracellular vesicles (EVs), membrane-delimited nanovesicles that are secreted by cells into the extracellular environment, are gaining substantial interest due to their involvement in cellular homeostasis and their contribution to disease pathology. The latter in particular has led to an exponential increase in interest in EVs as they are considered to be circulating packages containing potential biomarkers and are also a possible biological means to deliver drugs in a cell-specific manner. However, several challenges hamper straightforward proteome analysis of EVs as they are generally low abundant and reside in complex biological matrices. These matrices typically contain abundant proteins at concentrations that vastly exceed the concentrations of proteins found in the EV proteome. Therefore, extensive EV isolation and purification protocols are imperative and many have been developed, including (density) ultracentrifugation, size-exclusion and precipitation methods. Here, we describe filter-aided extracellular vesicle enrichment (FAEVEr) as an approach based on 300 kDa MWCO filtration that allows the processing of multiple samples in parallel within a reasonable timeframe and at moderate cost. We demonstrate that FAEVEr is capable of quantitatively retaining EV particles on filters, whilst allowing extensive washing with the mild detergent TWEEN-20 to remove interfering non-EV proteins. The retained particles are directly lysed on the filter for a complete recovery of the EV protein cargo towards proteome analysis. Here, we validate and optimize FAEVEr on recombinant EV material and apply it on conditioned medium as well as on complex bovine serum, human plasma and urine. Our results indicate that EVs isolated from MCF7 cells cultured with or without serum have a drastic different proteome because of nutrient deprivation.
    Keywords:  300 kDa MWCO ultrafiltration; EV-depleted serum; Extracellular vesicles; LC-MS/MS; TWEEN-20; conditioned medium; proteomics; starvation
    DOI:  https://doi.org/10.1016/j.mcpro.2025.100907