bims-mascan Biomed News
on Mass spectrometry in cancer research
Issue of 2025–01–19
twenty papers selected by
Giovanny Rodríguez Blanco, Uniklinikum Graz
  1. Untargeted Metabolic Phenotyping by LC-MS.
  2. Ion Pair Chromatography for Endogenous Metabolite LC-MS Analysis in Tissue Samples Following HGH Resolution Untargeted Acquisition.
  3. Quantitative Lipidomics of Biological Samples Using Supercritical Fluid Chromatography Mass Spectrometry.
  4. Establishment of a novel large-scale targeted metabolomics method based on NFSWI-DDA mode utilizing HRMS and TQ-MS.
  5. Quality Control and Validation Issues in LC-MS-Based Metabolomics.
  6. Quality Assurance in Metabolomics and Metabolic Profiling.
  7. OzNOxESI: A Novel Mass Spectrometry Ion Chemistry for Elucidating Lipid Double-Bond Regioisomerism in Complex Mixtures.
  8. Simultaneous Profiling of Multiple Phosphorylated Metabolites in Typical Biological Matrices via Ion-Pair Reversed-Phase Ultrahigh-Performance Liquid Chromatography and Mass Spectrometry.
  9. UHPLC-TIMS-PASEF®-MS for Lipidomics: From Theory to Practice.
  10. A Streamlined High-Throughput LC-MS Assay for Quantifying Peptide Degradation in Cell Culture.
  11. Data Treatment for LC-MS Untargeted Analysis.
  12. Advanced LC-IMS-MS Protocol for Holistic Metabolite Analysis in Wine and Grape Samples.
  13. Enhanced Discovery of Alternative Proteins (AltProts) in Mouse Cardiac Development Using Data-Independent Acquisition (DIA) Proteomics.
  14. Characterization of 53 Multiplexed Targeted Proteomics Assays for Verification Studies in Cancer Cell Lines.
  15. Ion mobility spectrometry and ion mobility-mass spectrometry in clinical chemistry.
  16. A sensitive post-column derivatization approach for enhancing hydroxyl metabolites detection.
  17. Bio- and Chemoinformatic Approaches for Metabolomics Data Analysis.
  18. Metabolic Signaling in the Tumor Microenvironment.
  19. Spatial metabolomics platform combining mass spectrometry imaging and in-depth chemical characterization with capillary electrophoresis.
  20. Analysis of Urinary Metanephrines Using Liquid Chromatography Tandem Mass Spectrometry.
  1. Methods Mol Biol. 2025 ;2891 109-129
    Untargeted Metabolic Phenotyping by LC-MS.
    Ian D Wilson, Elizabeth Want.
      Untargeted analysis by LC-MS is a valuable tool for metabolic profiling (metabonomics/metabolomics), and applications of this technology have grown rapidly over the past decade. LC-MS offers advantages of speed, sensitivity, relative ease of sample preparation, and large dynamic range compared to other platforms in this role. However, like any analytical approach, there are still drawbacks and challenges that have to be overcome, some of which are being addressed by advances in both column chemistries and instrumentation. In particular, the combination of LC-MS with ion mobility offers many new possibilities for improved analyte separation, detection, and structural identification. There are many untargeted LC-MS approaches which can be applied to metabolic phenotyping, and these usually need to be optimized for the type of sample, the nature of the study, or the biological question. Some of the main LC-MS approaches for untargeted metabolic phenotyping are described in detail in the following protocol.
    Keywords:  Ion mobility; LC-MS; Liquid chromatography; Mass spectrometry; Untargeted metabolic profiling
    DOI:  https://doi.org/10.1007/978-1-0716-4334-1_6
  2. Methods Mol Biol. 2025 ;2891 165-180
    Ion Pair Chromatography for Endogenous Metabolite LC-MS Analysis in Tissue Samples Following HGH Resolution Untargeted Acquisition.
    Filippos Michopoulos.
      A protocol for the preparation of tissue extracts for the targeted analysis ca. 150 polar metabolites, including those involved in central carbon metabolism, is described, using a reversed phase ion pair U(H)PLC-MS method. Data collection enabled in high-resolution mass spectrometry detection provides highly specific and sensitive acquisition of metabolic intermediates with wide range physicochemical properties and pathway coverage. Technical aspects are discussed for method transfer along with the basic principles of sample sequence setup, data analysis, and validation. At last general comments are given to help the assessment of data quality and system performance.
    Keywords:  Ion pair chromatography; Mass spectrometry; Metabolite profiling; Polar metabolites
    DOI:  https://doi.org/10.1007/978-1-0716-4334-1_9
  3. Methods Mol Biol. 2025 ;2891 131-152
    Quantitative Lipidomics of Biological Samples Using Supercritical Fluid Chromatography Mass Spectrometry.
    Hiroaki Takeda, Yoshihiro Izumi, Takeshi Bamba.
      Lipidomics has attracted attention in the discovery of unknown biomolecules and for capturing the changes in metabolism caused by genetic and environmental factors in an unbiased manner. However, obtaining reliable lipidomics data, including structural diversity and quantification data, is still challenging. Supercritical fluid chromatography (SFC) is a suitable technique for separating lipid molecules with high throughput and separation efficiency. Here, we describe a quantitative lipidomics method using SFC coupled with mass spectrometry. This technique is suitable for characterizing the structural diversity of lipids (e.g., phospholipids, sphingolipids, glycolipids, and glycerolipids) with high quantitative accuracy to understand their biological functions.
    Keywords:  Cells; Extracellular vesicles; Glycerolipids; Glycolipids; Lipidomics; Lipoproteins; Liquid-liquid extraction; Mass spectrometry; Organs; Phospholipids; Plasma; Quantitative analysis; Sphingolipids; Supercritical fluid chromatography; Tissues
    DOI:  https://doi.org/10.1007/978-1-0716-4334-1_7
  4. Talanta. 2025 Jan 10. pii: S0039-9140(25)00052-9. [Epub ahead of print]286 127566
    Establishment of a novel large-scale targeted metabolomics method based on NFSWI-DDA mode utilizing HRMS and TQ-MS.
    Rongrong Li, Xinyi Jiao, Xiaolin Wu, Lei Xu, Lin Zhang, Lifeng Han, Guixiang Pai, Wei Mi, Jiang Wu, Liming Wang.
      Metabolites identification is the major bottleneck in untargeted LC-MS metabolomics, primarily due to the limited availability of MS2 information for most detected metabolites in data dependent acquisition (DDA) mode. To solve this problem, we have integrated the iterative, interval, and segmented window acquisition concepts to develop an innovative non-fixed segmented window interval data dependency acquisition (NFSWI-DDA) mode, which achieves comparable MS2 coverage to data independent acquisition (DIA) mode. This acquisition strategy harnesses the strengths of both DDA and DIA, which could provide extensive coverage and excellent reproducibility of MS2 spectra. Furthermore, utilizing the NFSWI-DDA data, we successfully acquired and identified a large-scale of multiple reaction monitoring (MRM) ion pairs, and transitioned them from high-resolution mass spectrometry (HRMS) to triple quadrupole mass spectrometry (TQ-MS). At last, a large-scale targeted metabolomics method was established practically. This method enables targeted analysis of 475 endogenous metabolites encompassing amino acids, nucleotides, bile acids, fatty acids, and carnitines, which could cover 9 major metabolic pathways as well as 65 secondary metabolic pathways. The established targeted method allows for semi-quantitative assessment of 475 metabolites while enabling quantitative analysis of 327 specific metabolites in biological samples. The method demonstrates immense potential in the detection of various biological samples, offering robust technical support and generating extensive data to advance applications in precision medicine and life sciences.
    Keywords:  LC-MS; Large-scale; MRM; NFSWI-DDA; Targeted metabolomics
    DOI:  https://doi.org/10.1016/j.talanta.2025.127566
  5. Methods Mol Biol. 2025 ;2891 53-66
    Quality Control and Validation Issues in LC-MS-Based Metabolomics.
    Olga Begou, Helen G Gika, Georgios Theodoridis, Ian D Wilson.
      Metabolic profiling performed using untargeted metabolomics of different, complex biological samples aims to apply agnostic/holistic, hypothesis-free, analysis of the small molecules that are present in the analyzed sample. This approach has been the center of major investments and dedicated efforts from the research community for many years. However, limitations and challenges remain, particularly with regard to the validation and the quality of the obtained results. This has led to increasing community engagement, with the formation of think tanks, the establishment of working groups, and the many seminars on quality control (QC) in metabolomics. Here we describe a quality control (QC) protocol used to monitor LC-MS-based metabolomics analysis. A key target is the monitoring of analytical precision. This methodology is described for the analysis of urine but can be applied to different biological matrices, such as various biofluids, cell, and tissue extracts.
    Keywords:  Biological samples; LC-MS; Quality control; Untargeted metabolomics; Validation
    DOI:  https://doi.org/10.1007/978-1-0716-4334-1_3
  6. Methods Mol Biol. 2025 ;2891 15-51
    Quality Assurance in Metabolomics and Metabolic Profiling.
    Jennifer A Kirwan, Ulrike Bruning, Jonathan D Mosley.
      Metabolic profiling (untargeted metabolomics) aims for a global unbiased analysis of metabolites in a cell or biological system. It remains a highly useful research tool used across various analytical platforms. Incremental improvements across multiple steps in the analytical process may have large consequences for the end quality of the data. Thus, this chapter concentrates on which aspects of quality assurance can be implemented by a lab in the (pre-)analytical stages of the analysis to improve the overall end quality of their data. The scope of this chapter is limited to liquid-chromatography-mass spectrometry (LC-MS)-based profiling, which is one of the most widely utilized platforms, although the general principles are applicable to all metabolomics experiments.
    Keywords:  Data quality; Mass spectrometry; Metabolomics; NMR; Quality assurance; Quality control; Quality management; Robust method; Untargeted; Validation
    DOI:  https://doi.org/10.1007/978-1-0716-4334-1_2
  7. Anal Chem. 2025 Jan 16.
    OzNOxESI: A Novel Mass Spectrometry Ion Chemistry for Elucidating Lipid Double-Bond Regioisomerism in Complex Mixtures.
    Ryan A Smith, Ashraf M Omar, Fayaj A Mulani, Qibin Zhang.
      Double bond (C═C) position isomerism in unsaturated lipids can indicate abnormal lipid metabolism and pathological conditions. Novel chemical derivatization and mass spectrometry-based techniques are under continuing development to provide more accurate elucidation of lipid structure in finer structural detail. Here, we introduce a new ion chemistry for annotating lipid C═C positions, which is highly efficient for liquid chromatography-mass spectrometry-based lipidomics. This ion chemistry relies on the online derivatization of lipid C═C with ozone and nitrogen oxides upon fragmentation by tandem mass spectrometry, yielding characteristic product ions capable of unambiguously annotating C═C regioisomers. The new workflow was thoroughly evaluated with various glycerophospholipids and fatty acids and applied to human plasma lipid extract, successfully identified and quantified 270 glycerophospholipid and 36 fatty acid C═C isomers with an in-house developed software, OzNOx Companion, for automated data analysis.
    DOI:  https://doi.org/10.1021/acs.analchem.4c05940
  8. Anal Chem. 2025 Jan 13.
    Simultaneous Profiling of Multiple Phosphorylated Metabolites in Typical Biological Matrices via Ion-Pair Reversed-Phase Ultrahigh-Performance Liquid Chromatography and Mass Spectrometry.
    Huan Wang, Qinsheng Chen, Yuanpeng Wu, Li Xu, Qi Wang, Qingyu Hu, Huiru Tang.
      Simultaneous analysis of multiple phosphorylated metabolites (phosphorylated metabolome) in biological samples is vital to reveal their physiological and pathophysiological functions, which is extremely challenging due to their low abundance in some biological matrices, high hydrophilicity, and poor chromatographic behavior. Here, we developed a new method with ion-pair reversed-phase ultrahigh-performance liquid chromatography and mass spectrometry using BEH C18 columns modified with hybrid surface technology. This method demonstrated good performances for various phosphorylated metabolites, including phosphorylated sugars and amino acids, nucleotides, NAD-based cofactors, and acyl-CoAs in a single run using standard LC systems. Specifically, the method showed good retention (capacity factor > 2) and reproducibility (ΔtR < 0.09 min, n = 6), peak symmetry (tailing factor < 2), and sensitivity (limit-of-detection < 238 fmol-on-column with QTOFMS) for all tested analytes especially for the medium- and/or long-chain acyl-CoAs. The method demonstrated reproducible applicability across numerous biological matrices, including tissue (liver), human biofluids (urine, plasma), cells, and feces, and revealed significant molecular phenotypic differences in phosphorylated metabolite composition.
    DOI:  https://doi.org/10.1021/acs.analchem.4c04692
  9. Methods Mol Biol. 2025 ;2891 221-237
    UHPLC-TIMS-PASEF®-MS for Lipidomics: From Theory to Practice.
    Vanna Denti, Simone Serrao, Eleonora Bossi, Giuseppe Paglia.
      Trapped ion mobility spectrometry (TIMS) using parallel accumulation serial fragmentation (PASEF®) is an advanced analytical technique that offers several advantages in mass spectrometry (MS)-based lipidomics. TIMS provides an additional dimension of separation to mass spectrometry and accurate collision cross-section (CCS) measurements for ions, aiding in the structural characterization of molecules. This is especially valuable in lipidomics for identifying and distinguishing isomeric or structurally similar compounds. On the other hand, PASEF technology allows for fast and efficient data acquisition by accumulating ions in parallel and then serially fragmenting them. This accelerates the analysis process and improves throughput, making it suitable for high-throughput applications. Moreover, the combination of TIMS and PASEF reduces co-elution and ion coalescence issues, leading to cleaner and more interpretable mass spectra. This results in higher data quality and more confident identifications. In this chapter, a data-dependent TIMS-PASEF® workflow for lipidomics analysis is presented.
    Keywords:  Ion mobility; Lipidomics; Mass spectrometry; PASEF; TIMS
    DOI:  https://doi.org/10.1007/978-1-0716-4334-1_12
  10. J Biomed Mater Res A. 2025 Jan;113(1): e37864
    A Streamlined High-Throughput LC-MS Assay for Quantifying Peptide Degradation in Cell Culture.
    Samuel J Rozans, Yingjie Wu, Abolfazl S Moghaddam, E Thomas Pashuck.
      Peptides are widely used in biomaterials due to their ease of synthesis, ability to signal cells, and modify the properties of biomaterials. A key benefit of using peptides is that they are natural substrates for cell-secreted enzymes, which creates the possibility of utilizing cell-secreted enzymes for tuning cell-material interactions. However, these enzymes can also induce unwanted degradation of bioactive peptides in biomaterials, or in peptide therapies. Liquid chromatography-mass spectrometry (LC-MS) is a widely used, powerful methodology that can separate complex mixtures of molecules and quantify numerous analytes within a single run. There are several challenges in using LC-MS for the multiplexed quantification of cell-induced peptide degradation, including the need for nondegradable internal standards and the identification of optimal sample storage conditions. Another problem is that cell culture media and biological samples typically contain both proteins and lipids that can accumulate on chromatography columns and degrade their performance. Removing these constituents can be expensive, time-consuming, and increases sample variability. However, loading unpurified samples onto the column without removing lipids and proteins will foul the column. Here, we show that directly injecting complex, unpurified samples onto the LC-MS without any purification enables rapid and accurate quantification of peptide concentration and that hundreds of LC-MS runs can be done on a single column without significantly diminishing the ability to quantify the degradation of peptide libraries. To understand how repeated injections degrade column performance, a model library was injected into the LC-MS hundreds of times. It was then determined that column failure is evident when hydrophilic peptides are no longer retained on the column and that failure can be easily identified by using standard peptide mixtures for column benchmarking. In total, this work introduces a simple and effective method for simultaneously quantifying the degradation of dozens of peptides in cell culture. By providing a streamlined and cost-effective method for the direct quantification of peptide degradation in complex biological samples, this work enables more efficient assessment of peptide stability and functionality, facilitating the development of advanced biomaterials and peptide-based therapies.
    DOI:  https://doi.org/10.1002/jbm.a.37864
  11. Methods Mol Biol. 2025 ;2891 91-108
    Data Treatment for LC-MS Untargeted Analysis.
    Mar Garcia-Aloy, Johannes Rainer, Pietro Franceschi.
      Liquid Chromatography-Mass Spectrometry (LC-MS) untargeted experiments require complex bioinformatic strategies to extract information from the experimental data. Here we discuss the "data preprocessing," the set of procedures performed on the raw data to produce a data matrix which will be the starting point for the subsequent statistical analysis. Data preprocessing is a crucial step on the path to knowledge extraction, which should be carefully controlled and optimized in order to maximize the output of any untargeted metabolomics investigation.
    Keywords:  Metadata; Missing values; Peak picking; Preprocessing; Quality check; Retention time correction
    DOI:  https://doi.org/10.1007/978-1-0716-4334-1_5
  12. Methods Mol Biol. 2025 ;2891 239-256
    Advanced LC-IMS-MS Protocol for Holistic Metabolite Analysis in Wine and Grape Samples.
    Vania Sáez, Sara Ferrero-Del-Teso, Fulvio Mattivi, Urska Vrhovsek, Panagiotis Arapitsas.
      The final aim of metabolomics is the comprehensive and holistic study of the metabolome in biological samples. Therefore, the use of instruments that enable the analysis of metabolites belonging to various chemical classes in a wide range of concentrations is essential, without compromising on robustness, resolution, sensitivity, specificity, and metabolite annotation. These characteristics are crucial for the analysis of very complex samples, such as wine, whose metabolome is the result of the sum of metabolites derived from grapes, yeast(s), bacteria(s), and chemical or physical modification during winemaking. In recent years, a big advantage, in this direction, was the hardware developments on hyphenated instruments that enable the integration of liquid chromatography (LC), ion mobility spectrometry (IMS), and mass spectrometry (MS). This chapter describes an LC-IMS-MS protocol for the analysis of wine and grape samples as well as the use of IMS data in metabolite annotation.
    Keywords:  CCS; HDMSE; Mass spectrometry; Metabolite annotation; Metabolomics; Traveling wave ion mobility; Vitis
    DOI:  https://doi.org/10.1007/978-1-0716-4334-1_13
  13. Anal Chem. 2025 Jan 15.
    Enhanced Discovery of Alternative Proteins (AltProts) in Mouse Cardiac Development Using Data-Independent Acquisition (DIA) Proteomics.
    Yuanliang Zhang, Ying Yang, Kecheng Li, Lei Chen, Yang Yang, Chenxi Yang, Zhi Xie, Hongwei Wang, Qian Zhao.
      Alternative proteins (AltProts) are a class of proteins encoded by DNA sequences previously classified as noncoding. Despite their historically being overlooked, recent studies have highlighted their widespread presence and distinctive biological roles. So far, direct detection of AltProt has been relying on data-dependent acquisition (DDA) mass spectrometry (MS). However, data-independent acquisition (DIA) MS, a method that is rapidly gaining popularity for the analysis of canonical proteins, has seen limited application in AltProt research, largely due to the complexities involved in constructing DIA libraries. In this study, we present a novel DIA workflow that leverages a fragmentation spectra predictor for the efficient construction of DIA libraries, significantly enhancing the detection of AltProts. Our method achieved a 2-fold increase in the identification of AltProts and a 50% reduction in missing values compared to DDA. We conducted a comprehensive comparison of four AltProt databases, four DIA-library construction strategies, and three analytical software tools to establish an optimal workflow for AltProt analysis. Utilizing this workflow, we investigated the mouse heart development process and identified over 50 AltProts with differential expression between embryonic and adult heart tissues. Over 30 unannotated mouse AltProts were validated, including ASDURF, which played a crucial role in cardiac development. Our findings not only provide a practical workflow for MS-based AltProt analysis but also reveal novel AltProts with potential significance in biological functions.
    DOI:  https://doi.org/10.1021/acs.analchem.4c02924
  14. J Proteome Res. 2025 Jan 13.
    Characterization of 53 Multiplexed Targeted Proteomics Assays for Verification Studies in Cancer Cell Lines.
    Constance A Sobsey, Gerald Batist, Christoph H Borchers.
      The National Cancer Institute's Clinical Proteomics Tumor Analysis Consortium (CPTAC) was established to address the need for improved design, standardization, and validation of proteomics assays to enable better translation of biomarkers from the analytical lab to the clinic. Here, we applied CPTAC guidelines to characterize quantitative mass spectrometry (MS) assays in a new multiple reaction monitoring (MRM) proteomics panel. The panel of 50 proteins was developed in response to a previous study that identified a proteomic profile of altered translational control associated with response to a new cancer drug. MRM-MS assays for 53 peptides of interest were developed, optimized, and characterized on a UPLC system coupled to a triple-quadrupole mass spectrometer (QQQ-MS) using synthetic proteotypic peptides and corresponding stable-isotope labeled internal standard (SIS) peptides. Most of the assays were found to be fit-for-purpose for biomarker verification in that they precisely and reproducibly quantify the peptides at levels corresponding to the endogenous concentration in the desired cancer cell lines. Of these, 28 peptide assays represent to proteins that previously had no associated assays published in the CPTAC database. The targeted proteins in this publicly deposited validated multiplexed panel may be of use for research applications in cancer, cellular stress, neurology, cardiology, and metabolism.
    Keywords:  Clinical Proteomic Tumor Analysis Consortium (CPTAC); biomarker verification; fit-for-purpose assay validation; internal standards; mass spectrometry; multiple reaction monitoring (MRM); multiplexed quantitation; targeted proteomics; translational control
    DOI:  https://doi.org/10.1021/acs.jproteome.4c00576
  15. Adv Clin Chem. 2025 ;pii: S0065-2423(24)00130-6. [Epub ahead of print]124 123-160
    Ion mobility spectrometry and ion mobility-mass spectrometry in clinical chemistry.
    Kyle E Lira, Jody C May, John A McLean.
      Advancements in clinical chemistry have major implications in terms of public health, prompting many clinicians to seek out chemical information to aid in diagnoses and treatments. While mass spectrometry (MS) and hyphenated-MS techniques such as LC-MS or tandem MS/MS have long been the analytical methods of choice for many clinical applications, these methods routinely demonstrate difficulty in differentiating between isomeric forms in complex matrices. Consequently, ion mobility spectrometry (IM), which differentiates molecules on the basis of size, shape, and charge, has demonstrated unique advantages in the broad application of stand-alone IM and hyphenated IM instruments towards clinical challenges. Here, we highlight representative IM applications and approaches and describe contemporary commercial offerings of IM technology and how these can be, or are currently being, applied to the field of clinical chemistry.
    Keywords:  Breath analysis; High-resolution ion mobility (HRIM); Ion mobility spectrometry (IMS); Ion mobility-mass spectrometry (IM-MS); Lipidomics; Metabolomics; Multidimensional separations; Volatile organic compounds
    DOI:  https://doi.org/10.1016/bs.acc.2024.10.003
  16. Anal Chim Acta. 2025 Feb 01. pii: S0003-2670(24)01360-6. [Epub ahead of print]1337 343559
    A sensitive post-column derivatization approach for enhancing hydroxyl metabolites detection.
    Yen-Chu Lin, Shiu-Wen Huang, San-Yuan Wang, Jing-Rong Su, Jimmy Junxiang Wang, Ming-Jen Hsu, Hsiao-Wei Liao.
       BACKGROUND: Chemical derivatization is a common technique in liquid chromatography-mass spectrometry (LC-MS) metabolomics used to improve the ionizability and chromatographic properties of metabolites in complex biological samples. This process facilitates better detection and separation of a wide array of compounds. The reagent 2-(4-boronobenzyl) isoquinolin-2-ium bromide (BBII), developed as a glucose labeling reagent for matrix-assisted laser desorption/ionization MS, enhances ionization for glucose and other hydroxyl metabolites. Its quaternary ammonium group increases ionization efficiency, and its rapid reaction time simplifies pretreatment procedures.
    RESULTS: We developed a novel post-column derivatization (PCD) method using BBII to boost the detection sensitivity of hydroxyl metabolites in LC-MS. By optimizing this BBII PCD approach with 14 hydroxyl-containing compounds, we were able to detect previously undetectable metabolites such as glucose, ribose, and long-chain alcohols. Sensitivity enhancements for these metabolites ranged from 1.1 to 42.9-fold. Applying this method to metabolic profiling of hydroxyl metabolites in the DBTRG-05MG glioblastoma cell line, with and without treatment with the new drug MFB [1-(4-chlorobenzyl)-2-(5-methyl-2-furfurylideneamino)benzimidazole], revealed several hydroxyl metabolites with significantly reduced levels post-treatment.
    SIGNIFICANCE AND NOVELTY: This study presents a new BBII PCD method that substantially improves the detection sensitivity of hydroxyl metabolites in LC-MS. This innovative approach is highly valuable for untargeted metabolomics studies in biological and clinical research, offering a robust tool for identifying metabolite changes and advancing our understanding of metabolic processes in disease and therapeutic contexts.
    Keywords:  2-(4-boronobenzyl) isoquinolin-2-ium bromide; Hydroxyl metabolites; LC-MS; Post-column derivatization; Untargeted metabolomics
    DOI:  https://doi.org/10.1016/j.aca.2024.343559
  17. Methods Mol Biol. 2025 ;2891 67-89
    Bio- and Chemoinformatic Approaches for Metabolomics Data Analysis.
    Michael Witting, Johannes Rainer.
      Metabolomics data analysis includes, next to the preprocessing, several additional repetitive tasks that can however be heavily dataset dependent or experiment setup specific due to the vast heterogeneity in instrumentation, protocols, or also compounds/samples that are being measured. To address this, various toolboxes and software packages in Python or R have been and are being developed providing researchers and analysts with bioinformatic/chemoinformatic tools to create their own workflows tailored toward their specific needs. This chapter presents tools and example workflows for common tasks focusing on the functionality provided by R packages developed as part of the RforMassSpectrometry initiative. These tasks include, among others, examples to work with chemical formulae, handle and process mass spectrometry data, or calculate similarities between fragment spectra.
    Keywords:  Formula handling; Mass spectra handling; R; RforMassSpectrometry; Spectra similarity calculation
    DOI:  https://doi.org/10.1007/978-1-0716-4334-1_4
  18. Cancers (Basel). 2025 Jan 06. pii: 155. [Epub ahead of print]17(1):
    Metabolic Signaling in the Tumor Microenvironment.
    Ryan Clay, Kunyang Li, Lingtao Jin.
      Cancer cells must reprogram their metabolism to sustain rapid growth. This is accomplished in part by switching to aerobic glycolysis, uncoupling glucose from mitochondrial metabolism, and performing anaplerosis via alternative carbon sources to replenish intermediates of the tricarboxylic acid (TCA) cycle and sustain oxidative phosphorylation (OXPHOS). While this metabolic program produces adequate biosynthetic intermediates, reducing agents, ATP, and epigenetic remodeling cofactors necessary to sustain growth, it also produces large amounts of byproducts that can generate a hostile tumor microenvironment (TME) characterized by low pH, redox stress, and poor oxygenation. In recent years, the focus of cancer metabolic research has shifted from the regulation and utilization of cancer cell-intrinsic pathways to studying how the metabolic landscape of the tumor affects the anti-tumor immune response. Recent discoveries point to the role that secreted metabolites within the TME play in crosstalk between tumor cell types to promote tumorigenesis and hinder the anti-tumor immune response. In this review, we will explore how crosstalk between metabolites of cancer cells, immune cells, and stromal cells drives tumorigenesis and what effects the competition for resources and metabolic crosstalk has on immune cell function.
    Keywords:  cancer metabolism; immune response; oncometabolite; tumor microenvironment
    DOI:  https://doi.org/10.3390/cancers17010155
  19. Talanta. 2025 Jan 10. pii: S0039-9140(24)01842-3. [Epub ahead of print]286 127460
    Spatial metabolomics platform combining mass spectrometry imaging and in-depth chemical characterization with capillary electrophoresis.
    Leonidas Mavroudakis, Anastasia Golubova, Ingela Lanekoff.
      Spatial metabolomics offers the combination of molecular identification and localization. As a tool for spatial metabolomics, mass spectrometry imaging (MSI) can provide detailed information on localization. However, molecular annotation with MSI is challenging due to the lack of separation prior to mass spectrometric analysis. Contrarily, surface sampling capillary electrophoresis mass spectrometry (SS-CE-MS) provides detailed molecular information, although the size of the sampling sites is modest. Here, we describe a platform for spatial metabolomics where MSI using pneumatically assisted nanospray desorption electrospray ionization (PA-nano-DESI) is combined with SS-CE-MS to gain both in-depth chemical information and spatial localization from thin tissue sections. We present the workflow, including the user-friendly setup and switching between the techniques, compare the obtained data, and demonstrate a quantitative approach when using the platform for spatial metabolomics of ischemic stroke.
    Keywords:  Capillary electrophoresis; Ischemic stroke; MSI; Spatial metabolomics; Surface sampling
    DOI:  https://doi.org/10.1016/j.talanta.2024.127460
  20. Methods Mol Biol. 2025 ;2891 257-268
    Analysis of Urinary Metanephrines Using Liquid Chromatography Tandem Mass Spectrometry.
    Marlene N Thaitumu, Elizabeth L Frank.
      Metanephrines (metanephrine [MN] and normetanephrine [NMN]) are O-methylated metabolites derived from the catecholamines, epinephrine, and norepinephrine, respectively. High concentrations of metanephrines have been observed in individuals with pheochromocytoma, a neuroendocrine tumor. Measurement of metanephrines in urine is used to screen for the tumor. Analysis using liquid chromatography-tandem mass spectrometry (LC-MS/MS) is recommended due to the high sensitivity, specificity, and throughput of the technique. Herein, we describe an optimized LC-MS/MS assay for the analysis of urinary metanephrines.
    Keywords:  Liquid chromatography-tandem mass spectrometry; Metanephrines; Pheochromocytoma
    DOI:  https://doi.org/10.1007/978-1-0716-4334-1_14
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