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Stillger MN, Li MJ, Hönscheid P, von Neubeck C, Föll MC. Advancing rare cancer research by MALDI mass spectrometry imaging: Applications, challenges, and future perspectives in sarcoma. Proteomics 2024; 24:e2300001. [PMID: 38402423 DOI: 10.1002/pmic.202300001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2023] [Revised: 02/10/2024] [Accepted: 02/12/2024] [Indexed: 02/26/2024]
Abstract
MALDI mass spectrometry imaging (MALDI imaging) uniquely advances cancer research, by measuring spatial distribution of endogenous and exogenous molecules directly from tissue sections. These molecular maps provide valuable insights into basic and translational cancer research, including tumor biology, tumor microenvironment, biomarker identification, drug treatment, and patient stratification. Despite its advantages, MALDI imaging is underutilized in studying rare cancers. Sarcomas, a group of malignant mesenchymal tumors, pose unique challenges in medical research due to their complex heterogeneity and low incidence, resulting in understudied subtypes with suboptimal management and outcomes. In this review, we explore the applicability of MALDI imaging in sarcoma research, showcasing its value in understanding this highly heterogeneous and challenging rare cancer. We summarize all MALDI imaging studies in sarcoma to date, highlight their impact on key research fields, including molecular signatures, cancer heterogeneity, and drug studies. We address specific challenges encountered when employing MALDI imaging for sarcomas, and propose solutions, such as using formalin-fixed paraffin-embedded tissues, and multiplexed experiments, and considerations for multi-site studies and digital data sharing practices. Through this review, we aim to spark collaboration between MALDI imaging researchers and clinical colleagues, to deploy the unique capabilities of MALDI imaging in the context of sarcoma.
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Affiliation(s)
- Maren Nicole Stillger
- Institute for Surgical Pathology, Faculty of Medicine, University Medical Center, Freiburg, Germany
- Bioinformatics Group, Department of Computer Science, Albert-Ludwigs-University Freiburg, Freiburg, Germany
| | - Mujia Jenny Li
- Institute for Surgical Pathology, Faculty of Medicine, University Medical Center, Freiburg, Germany
- Institute for Pharmaceutical Sciences, University of Freiburg, Freiburg, Germany
| | - Pia Hönscheid
- Institute of Pathology, Faculty of Medicine, University Hospital Carl Gustav Carus at the Technische Universität Dresden, Dresden, Germany
- National Center for Tumor Diseases, Partner Site Dresden, German Cancer Research Center Heidelberg, Dresden, Germany
- German Cancer Consortium (DKTK) and German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Cläre von Neubeck
- Department of Particle Therapy, University Hospital Essen, University of Duisburg-Essen, Essen, Germany
| | - Melanie Christine Föll
- Institute for Surgical Pathology, Faculty of Medicine, University Medical Center, Freiburg, Germany
- German Cancer Consortium (DKTK) and German Cancer Research Center (DKFZ), Heidelberg, Germany
- Khoury College of Computer Sciences, Northeastern University, Boston, USA
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2
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Dannhorn A, Kazanc E, Flint L, Guo F, Carter A, Hall AR, Jones SA, Poulogiannis G, Barry ST, Sansom OJ, Bunch J, Takats Z, Goodwin RJA. Morphological and molecular preservation through universal preparation of fresh-frozen tissue samples for multimodal imaging workflows. Nat Protoc 2024:10.1038/s41596-024-00987-z. [PMID: 38806741 DOI: 10.1038/s41596-024-00987-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2023] [Accepted: 02/14/2024] [Indexed: 05/30/2024]
Abstract
The landscape of tissue-based imaging modalities is constantly and rapidly evolving. While formalin-fixed, paraffin-embedded material is still useful for histological imaging, the fixation process irreversibly changes the molecular composition of the sample. Therefore, many imaging approaches require fresh-frozen material to get meaningful results. This is particularly true for molecular imaging techniques such as mass spectrometry imaging, which are widely used to probe the spatial arrangement of the tissue metabolome. As high-quality fresh-frozen tissues are limited in their availability, any sample preparation workflow they are subjected to needs to ensure morphological and molecular preservation of the tissues and be compatible with as many of the established and emerging imaging techniques as possible to obtain the maximum possible insights from the tissues. Here we describe a universal sample preparation workflow, from the initial step of freezing the tissues to the cold embedding in a new hydroxypropyl methylcellulose/polyvinylpyrrolidone-enriched hydrogel and the generation of thin tissue sections for analysis. Moreover, we highlight the optimized storage conditions that limit molecular and morphological degradation of the sections. The protocol is compatible with human and plant tissues and can be easily adapted for the preparation of alternative sample formats (e.g., three-dimensional cell cultures). The integrated workflow is universally compatible with histological tissue analysis, mass spectrometry imaging and imaging mass cytometry, as well as spatial proteomic, genomic and transcriptomic tissue analysis. The protocol can be completed within 4 h and requires minimal prior experience in the preparation of tissue samples for multimodal imaging experiments.
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Affiliation(s)
- Andreas Dannhorn
- Imaging and Data analytics, Clinical Pharmacology and Safety Sciences, R&D, AstraZeneca, Cambridge, UK
- Department of Digestion, Metabolism and Reproduction, Sir Alexander Fleming Building, Imperial College London, London, UK
| | - Emine Kazanc
- Department of Digestion, Metabolism and Reproduction, Sir Alexander Fleming Building, Imperial College London, London, UK
| | - Lucy Flint
- Imaging and Data analytics, Clinical Pharmacology and Safety Sciences, R&D, AstraZeneca, Cambridge, UK
| | - Fei Guo
- Imaging and Data analytics, Clinical Pharmacology and Safety Sciences, R&D, AstraZeneca, Cambridge, UK
- Safety Innovations, Clinical Pharmacology and Safety Sciences, R&D, AstraZeneca, Cambridge, UK
| | - Alfie Carter
- Imaging and Data analytics, Clinical Pharmacology and Safety Sciences, R&D, AstraZeneca, Cambridge, UK
- Safety Innovations, Clinical Pharmacology and Safety Sciences, R&D, AstraZeneca, Cambridge, UK
| | - Andrew R Hall
- Safety Innovations, Clinical Pharmacology and Safety Sciences, R&D, AstraZeneca, Cambridge, UK
| | - Stewart A Jones
- Imaging and Data analytics, Clinical Pharmacology and Safety Sciences, R&D, AstraZeneca, Cambridge, UK
| | | | - Simon T Barry
- Bioscience, Discovery, Oncology R&D, AstraZeneca, Cambridge, UK
| | | | - Josephine Bunch
- National Centre of Excellence in Mass Spectrometry Imaging (NiCE-MSI), National Physical Laboratory, Teddington, UK
| | - Zoltan Takats
- Department of Digestion, Metabolism and Reproduction, Sir Alexander Fleming Building, Imperial College London, London, UK
| | - Richard J A Goodwin
- Imaging and Data analytics, Clinical Pharmacology and Safety Sciences, R&D, AstraZeneca, Cambridge, UK.
- Institute of Infection, Immunity and Inflammation, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow, UK.
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3
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Ma X, Fernández FM. Advances in mass spectrometry imaging for spatial cancer metabolomics. MASS SPECTROMETRY REVIEWS 2024; 43:235-268. [PMID: 36065601 PMCID: PMC9986357 DOI: 10.1002/mas.21804] [Citation(s) in RCA: 29] [Impact Index Per Article: 29.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/12/2022] [Revised: 08/02/2022] [Accepted: 08/02/2022] [Indexed: 05/09/2023]
Abstract
Mass spectrometry (MS) has become a central technique in cancer research. The ability to analyze various types of biomolecules in complex biological matrices makes it well suited for understanding biochemical alterations associated with disease progression. Different biological samples, including serum, urine, saliva, and tissues have been successfully analyzed using mass spectrometry. In particular, spatial metabolomics using MS imaging (MSI) allows the direct visualization of metabolite distributions in tissues, thus enabling in-depth understanding of cancer-associated biochemical changes within specific structures. In recent years, MSI studies have been increasingly used to uncover metabolic reprogramming associated with cancer development, enabling the discovery of key biomarkers with potential for cancer diagnostics. In this review, we aim to cover the basic principles of MSI experiments for the nonspecialists, including fundamentals, the sample preparation process, the evolution of the mass spectrometry techniques used, and data analysis strategies. We also review MSI advances associated with cancer research in the last 5 years, including spatial lipidomics and glycomics, the adoption of three-dimensional and multimodal imaging MSI approaches, and the implementation of artificial intelligence/machine learning in MSI-based cancer studies. The adoption of MSI in clinical research and for single-cell metabolomics is also discussed. Spatially resolved studies on other small molecule metabolites such as amino acids, polyamines, and nucleotides/nucleosides will not be discussed in the context.
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Affiliation(s)
- Xin Ma
- School of Chemistry and Biochemistry and Petit Institute for Bioengineering and Bioscience, Georgia Institute of Technology, Atlanta, Georgia, USA
| | - Facundo M Fernández
- School of Chemistry and Biochemistry and Petit Institute for Bioengineering and Bioscience, Georgia Institute of Technology, Atlanta, Georgia, USA
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4
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Huang HX, Inglese P, Tang J, Yagoubi R, Correia GDS, Horneffer-van der Sluis VM, Camuzeaux S, Wu V, Kopanitsa MV, Willumsen N, Jackson JS, Barron AM, Saito T, Saido TC, Gentlemen S, Takats Z, Matthews PM. Mass spectrometry imaging highlights dynamic patterns of lipid co-expression with Aβ plaques in mouse and human brains. J Neurochem 2024. [PMID: 38372586 DOI: 10.1111/jnc.16042] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2023] [Revised: 11/13/2023] [Accepted: 12/06/2023] [Indexed: 02/20/2024]
Abstract
Lipids play crucial roles in the susceptibility and brain cellular responses to Alzheimer's disease (AD) and are increasingly considered potential soluble biomarkers in cerebrospinal fluid (CSF) and plasma. To delineate the pathological correlations of distinct lipid species, we conducted a comprehensive characterization of both spatially localized and global differences in brain lipid composition in AppNL-G-F mice with spatial and bulk mass spectrometry lipidomic profiling, using human amyloid-expressing (h-Aβ) and WT mouse brains controls. We observed age-dependent increases in lysophospholipids, bis(monoacylglycerol) phosphates, and phosphatidylglycerols around Aβ plaques in AppNL-G-F mice. Immunohistology-based co-localization identified associations between focal pro-inflammatory lipids, glial activation, and autophagic flux disruption. Likewise, in human donors with varying Braak stages, similar studies of cortical sections revealed co-expression of lysophospholipids and ceramides around Aβ plaques in AD (Braak stage V/VI) but not in earlier Braak stage controls. Our findings in mice provide evidence of temporally and spatially heterogeneous differences in lipid composition as local and global Aβ-related pathologies evolve. Observing similar lipidomic changes associated with pathological Aβ plaques in human AD tissue provides a foundation for understanding differences in CSF lipids with reported clinical stage or disease severity.
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Affiliation(s)
- Helen Xuexia Huang
- Section of Bioanalytical Chemistry, Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK
- UK Dementia Research Institute at Imperial College London, Imperial College London, London, UK
| | - Paolo Inglese
- Section of Bioanalytical Chemistry, Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK
- National Phenome Centre, Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK
| | - Jiabin Tang
- Department of Brain Sciences, Imperial College London, London, UK
| | - Riad Yagoubi
- Section of Bioanalytical Chemistry, Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK
- UK Dementia Research Institute at Imperial College London, Imperial College London, London, UK
| | - Gonçalo D S Correia
- Section of Bioanalytical Chemistry, Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK
- National Phenome Centre, Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK
| | | | - Stephane Camuzeaux
- National Phenome Centre, Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK
| | - Vincen Wu
- Section of Bioanalytical Chemistry, Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK
| | - Maksym V Kopanitsa
- UK Dementia Research Institute at Imperial College London, Imperial College London, London, UK
| | - Nanet Willumsen
- UK Dementia Research Institute at Imperial College London, Imperial College London, London, UK
- Department of Brain Sciences, Imperial College London, London, UK
| | - Johanna S Jackson
- UK Dementia Research Institute at Imperial College London, Imperial College London, London, UK
- Department of Brain Sciences, Imperial College London, London, UK
| | - Anna M Barron
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore
| | - Takashi Saito
- Laboratory for Proteolytic Neuroscience, RIKEN Center for Brain Science, Saitama, Japan
- Department of Neurocognitive Science, Institute of Brain Science, Nagoya City University, Graduate School of Medical Sciences, Nagoya, Aichi, Japan
| | - Takaomi C Saido
- Laboratory for Proteolytic Neuroscience, RIKEN Center for Brain Science, Saitama, Japan
- Department of Neurocognitive Science, Institute of Brain Science, Nagoya City University, Graduate School of Medical Sciences, Nagoya, Aichi, Japan
| | - Steve Gentlemen
- Department of Brain Sciences, Imperial College London, London, UK
| | - Zoltan Takats
- Section of Bioanalytical Chemistry, Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK
| | - Paul M Matthews
- UK Dementia Research Institute at Imperial College London, Imperial College London, London, UK
- Department of Brain Sciences, Imperial College London, London, UK
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5
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Bi S, Wang M, Pu Q, Yang J, Jiang N, Zhao X, Qiu S, Liu R, Xu R, Li X, Hu C, Yang L, Gu J, Du D. Multi-MSIProcessor: Data Visualizing and Analysis Software for Spatial Metabolomics Research. Anal Chem 2024; 96:339-346. [PMID: 38102989 DOI: 10.1021/acs.analchem.3c04192] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2023]
Abstract
Mass spectrometry imaging (MSI) has emerged as a revolutionary analytical strategy in biomedical research for molecular visualization. By linking the characterization of functional metabolites with tissue architecture, it is now possible to reveal unknown biological functions of tissues. However, due to the complexity and high dimensionality of MSI data, mining bioinformatics-related peaks from batch MSI data sets and achieving complete spatially resolved metabolomics analysis remain a great challenge. Here, we propose novel MSI data processing software, Multi-MSIProcessor (MMP), which integrates the data read-in, MSI visualization, processed data preservation, and biomarker discovery functions. The MMP focuses on the AFADESI-MSI data platform but also supports mzXML and imzmL data input formats for compatibility with data generated by other MSI platforms such as MALDI/SIMS-MSI. MMP enables deep mining of batch MSI data and has flexible adaptability with the source code opened that welcomes new functions and personalized analysis strategies. Using multiple clinical biosamples with complex heterogeneity, we demonstrated that MMP can rapidly establish complete MSI analysis workflows, assess batch sample data quality, screen and annotate differential MS peaks, and obtain abnormal metabolic pathways. MMP provides a novel platform for spatial metabolomics analysis of multiple samples that could meet the diverse analysis requirements of scholars.
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Affiliation(s)
- Siwei Bi
- Department of Plastic and Burn Surgery, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, China
| | - Manjiangcuo Wang
- Advanced Mass Spectrometry Center, Research Core Facility, Frontiers Science Center for Disease-related Molecular Network, West China Hospital, Sichuan University, Chengdu 610213, China
| | - Qianlun Pu
- Advanced Mass Spectrometry Center, Research Core Facility, Frontiers Science Center for Disease-related Molecular Network, West China Hospital, Sichuan University, Chengdu 610213, China
| | - Jinxi Yang
- West China Centre of Excellence for Pancreatitis, Institute of Integrated Traditional Chinese and Western Medicine, West China Hospital/West China Medical School, Sichuan University, Chengdu 610041, China
| | - Na Jiang
- Advanced Mass Spectrometry Center, Research Core Facility, Frontiers Science Center for Disease-related Molecular Network, West China Hospital, Sichuan University, Chengdu 610213, China
| | - Xueshan Zhao
- Department of Cardiovascular Surgery, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, China
| | - Siyuan Qiu
- Division of Gastrointestinal Surgery, Department of General Surgery, West China Hospital, Sichuan University, Chengdu,Sichuan 610041, China
| | - Ruiqi Liu
- Department of Plastic and Burn Surgery, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, China
| | - Renjie Xu
- Department of Respiratory Health West China Hospital, Sichuan University, Chengdu, Sichuan 610041, China
| | - Xia Li
- West China School of Nursing, Sichuan University, Chengdu, Sichuan 610041, China
- Department of Critical Care Medicine, West China Hospital, Sichuan University, Chengdu 610041, China
| | - Chenggong Hu
- Department of Critical Care Medicine, West China Hospital, Sichuan University, Chengdu 610041, China
| | - Lie Yang
- Division of Gastrointestinal Surgery, Department of General Surgery, West China Hospital, Sichuan University, Chengdu,Sichuan 610041, China
| | - Jun Gu
- Department of Cardiovascular Surgery, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, China
| | - Dan Du
- Advanced Mass Spectrometry Center, Research Core Facility, Frontiers Science Center for Disease-related Molecular Network, West China Hospital, Sichuan University, Chengdu 610213, China
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6
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Vandenbosch M, Mutuku SM, Mantas MJQ, Patterson NH, Hallmark T, Claesen M, Heeren RMA, Hatcher NG, Verbeeck N, Ekroos K, Ellis SR. Toward Omics-Scale Quantitative Mass Spectrometry Imaging of Lipids in Brain Tissue Using a Multiclass Internal Standard Mixture. Anal Chem 2023; 95:18719-18730. [PMID: 38079536 DOI: 10.1021/acs.analchem.3c02724] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2023]
Abstract
Mass spectrometry imaging (MSI) has accelerated our understanding of lipid metabolism and spatial distribution in tissues and cells. However, few MSI studies have approached lipid imaging quantitatively and those that have focused on a single lipid class. We overcome this limitation by using a multiclass internal standard (IS) mixture sprayed homogeneously over the tissue surface with concentrations that reflect those of endogenous lipids. This enabled quantitative MSI (Q-MSI) of 13 lipid classes and subclasses representing almost 200 sum-composition lipid species using both MALDI (negative ion mode) and MALDI-2 (positive ion mode) and pixel-wise normalization of each lipid species in a manner analogous to that widely used in shotgun lipidomics. The Q-MSI approach covered 3 orders of magnitude in dynamic range (lipid concentrations reported in pmol/mm2) and revealed subtle changes in distribution compared to data without normalization. The robustness of the method was evaluated by repeating experiments in two laboratories using both timsTOF and Orbitrap mass spectrometers with an ∼4-fold difference in mass resolution power. There was a strong overall correlation in the Q-MSI results obtained by using the two approaches. Outliers were mostly rationalized by isobaric interferences or the higher sensitivity of one instrument for a particular lipid species. These data provide insight into how the mass resolving power can affect Q-MSI data. This approach opens up the possibility of performing large-scale Q-MSI studies across numerous lipid classes and subclasses and revealing how absolute lipid concentrations vary throughout and between biological tissues.
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Affiliation(s)
- Michiel Vandenbosch
- Maastricht MultiModal Molecular Imaging (M4I) Institute, Division of Imaging Mass Spectrometry, Maastricht University, Maastricht 6229ER, Netherlands
| | - Shadrack M Mutuku
- Molecular Horizons and School of Chemistry and Molecular Bioscience, University of Wollongong, Wollongong, NSW 2522, Australia
| | | | | | | | | | - Ron M A Heeren
- Maastricht MultiModal Molecular Imaging (M4I) Institute, Division of Imaging Mass Spectrometry, Maastricht University, Maastricht 6229ER, Netherlands
| | - Nathan G Hatcher
- Merck & Co., Inc., 770 Sumneytown Pk, West Point, Pennsylvania 19486, United States
| | | | - Kim Ekroos
- Lipidomics Consulting Ltd., Esbo 02230, Finland
| | - Shane R Ellis
- Molecular Horizons and School of Chemistry and Molecular Bioscience, University of Wollongong, Wollongong, NSW 2522, Australia
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7
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Huang S, Wang H, Liu X, Liu L, Liu D, Zhang X, Zhang L, Xie P, Zhang Y. Pyrylium-based derivatization for rapid labeling and enhanced detection of thiol in mass spectrometry imaging. Anal Chim Acta 2023; 1284:341968. [PMID: 37996155 DOI: 10.1016/j.aca.2023.341968] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2023] [Revised: 10/05/2023] [Accepted: 10/26/2023] [Indexed: 11/25/2023]
Abstract
Many endogenous antioxidants, including glutathione (GSH), cysteine (Cys), cysteinyl-glycine (Cys-Gly) and homocysteine (Hcy) possess free thiol functional groups. In most cases, matrix-assisted laser desorption ionization (MALDI) analyses of trace amounts of thiol compounds are challenging because of their instability and poor ionization properties. We present a mass spectrometry imaging (MSI) approach for mapping of thiol compounds on brain tissue sections. Our derivatization reagents 1-(2-(2,5-dioxo-2,5-dihydro-1H-pyrrol-1-yl)ethyl)-2,4,6-trimethylpyridinium (MTMP) and 1-(2-(2,5-dioxo-2,5-dihydro-1H-pyrrol-1-yl)ethyl)-2,4,5-triphenylpyridinium (MTPP) facilitate the covalent charge-tagging of molecules containing free thiol group for the selective and rapid detection of GSH synthesis and metabolic pathway related metabolites by MALDI-MSI. The developed thiol-specific mass spectrometry imaging method realizes the quantitative detection of exogenous N-acetylcysteine tissue sections, and the detection limit in mass spectrometry imaging could reach 0.05 ng. We illustrate the capabilities of the developed method to mapping of thiol compounds on brain tissue from the chronic social defeat stress (CSDS) depression model mice.
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Affiliation(s)
- Shuai Huang
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, 116023, PR China; University of Chinese Academy of Science, Beijing, 100039, PR China
| | - Haiyang Wang
- Chongqing Medical University, Chongqing, 400016, PR China
| | - Xinxin Liu
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, 116023, PR China
| | - Lanxiang Liu
- Chongqing Medical University, Chongqing, 400016, PR China
| | - Dan Liu
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, 116023, PR China.
| | - Xiaozhe Zhang
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, 116023, PR China.
| | - Lihua Zhang
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, 116023, PR China
| | - Peng Xie
- Chongqing Medical University, Chongqing, 400016, PR China
| | - Yukui Zhang
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, 116023, PR China
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8
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Krestensen KK, Heeren RMA, Balluff B. State-of-the-art mass spectrometry imaging applications in biomedical research. Analyst 2023; 148:6161-6187. [PMID: 37947390 DOI: 10.1039/d3an01495a] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2023]
Abstract
Mass spectrometry imaging has advanced from a niche technique to a widely applied spatial biology tool operating at the forefront of numerous fields, most notably making a significant impact in biomedical pharmacological research. The growth of the field has gone hand in hand with an increase in publications and usage of the technique by new laboratories, and consequently this has led to a shift from general MSI reviews to topic-specific reviews. Given this development, we see the need to recapitulate the strengths of MSI by providing a more holistic overview of state-of-the-art MSI studies to provide the new generation of researchers with an up-to-date reference framework. Here we review scientific advances for the six largest biomedical fields of MSI application (oncology, pharmacology, neurology, cardiovascular diseases, endocrinology, and rheumatology). These publications thereby give examples for at least one of the following categories: they provide novel mechanistic insights, use an exceptionally large cohort size, establish a workflow that has the potential to become a high-impact methodology, or are highly cited in their field. We finally have a look into new emerging fields and trends in MSI (immunology, microbiology, infectious diseases, and aging), as applied MSI is continuously broadening as a result of technological breakthroughs.
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Affiliation(s)
- Kasper K Krestensen
- The Maastricht MultiModal Molecular Imaging (M4I) Institute, Maastricht University, 6229 ER Maastricht, The Netherlands.
| | - Ron M A Heeren
- The Maastricht MultiModal Molecular Imaging (M4I) Institute, Maastricht University, 6229 ER Maastricht, The Netherlands.
| | - Benjamin Balluff
- The Maastricht MultiModal Molecular Imaging (M4I) Institute, Maastricht University, 6229 ER Maastricht, The Netherlands.
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9
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Akbari B, Huber BR, Sherman JH. Unlocking the Hidden Depths: Multi-Modal Integration of Imaging Mass Spectrometry-Based and Molecular Imaging Techniques. Crit Rev Anal Chem 2023:1-30. [PMID: 37847593 DOI: 10.1080/10408347.2023.2266838] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2023]
Abstract
Multimodal imaging (MMI) has emerged as a powerful tool in clinical research, combining different imaging modes to acquire comprehensive information and enabling scientists and surgeons to study tissue identification, localization, metabolic activity, and molecular discovery, thus aiding in disease progression analysis. While multimodal instruments are gaining popularity, challenges such as non-standardized characteristics, custom software, inadequate commercial support, and integration issues with other instruments need to be addressed. The field of multimodal imaging or multiplexed imaging allows for simultaneous signal reproduction from multiple imaging strategies. Intraoperatively, MMI can be integrated into frameless stereotactic surgery. Recent developments in medical imaging modalities such as magnetic resonance imaging (MRI), and Positron Emission Topography (PET) have brought new perspectives to multimodal imaging, enabling early cancer detection, molecular tracking, and real-time progression monitoring. Despite the evidence supporting the role of MMI in surgical decision-making, there is a need for comprehensive studies to validate and perform integration at the intersection of multiple imaging technologies. They were integrating mass spectrometry-based technologies (e.g., imaging mass spectrometry (IMS), imaging mass cytometry (IMC), and Ion mobility mass spectrometry ((IM-IM) with medical imaging modalities, offering promising avenues for molecular discovery and clinical applications. This review emphasizes the potential of multi-omics approaches in tissue mapping using MMI integrated into desorption electrospray ionization (DESI) and matrix-assisted laser desorption ionization (MALDI), allowing for sequential analyses of the same section. By addressing existing knowledge gaps, this review encourages future research endeavors toward multi-omics approaches, providing a roadmap for future research and enhancing the value of MMI in molecular pathology for diagnosis.
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Affiliation(s)
- Behnaz Akbari
- Department of Chemistry, Purdue University, West Lafayette, Indiana, USA
| | - Bertrand Russell Huber
- Chobanian and Avedisian School of Medicine, Boston University, Boston, Massachusetts, USA
- Boston University Alzheimer's Disease and CTE Center, Boston University School of Medicine, Boston, Massachusetts, USA
- Department of Neurology, Boston University School of Medicine, Boston, Massachusetts, USA
- US Department of Veteran Affairs, VA Boston Healthcare System, Boston, Massachusetts USA
- US Department of Veterans Affairs, National Center for PTSD, Boston, Massachusetts USA
| | - Janet Hope Sherman
- Chobanian and Avedisian School of Medicine, Boston University, Boston, Massachusetts, USA
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10
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Li Y, Wang B, Ahmad Khan Z, He J, Cheung E, Su W, Wang A, Jiang H, Jiang L, Ding X. Platinum-Chimeric Carrier Cells for Ultratrace Cell Analysis in Mass Cytometry. Anal Chem 2023; 95:14998-15007. [PMID: 37767956 DOI: 10.1021/acs.analchem.3c02706] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/29/2023]
Abstract
Mass cytometry by time-of-flight (CyTOF), a high-dimensional single-cell analysis platform, detects up to 50 biomarkers at single-cell resolution. However, CyTOF analysis of biological samples with a minimal number of available cells or rare cell subsets remains a major technical challenge due to the extensive loss of cells during cell recovery, staining, and acquisition. Here, we introduce a platinum-chimeric carrier cell strategy for mass cytometry profiling of ultratrace cell samples. Cisplatin can rapidly enter broken plasma membranes of dead cells and form a chimeric interaction with cellular proteins, peptides, and amino acids. Thus, 198Pt-cisplatin is adopted to tag carrier cells in the pretreatment stage. We investigated 8 cell lines that are commonly accessible in laboratories for their potential as carrier cells to preserve rare target cells for CyTOF analysis. We designed a panel of 35 protein biomarkers to evaluate the comprehensive single-cell subtype classification capability with or without the carrier cell strategy. We further demonstrated the detection and analysis of as few as 1 × 104 immune cells using our method. The proposed method thus allows CyTOF analysis on precious clinical samples with less abundant cells.
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Affiliation(s)
- Yiyang Li
- Department of Anesthesiology and Surgical Intensive Care Unit, Xinhua Hospital, School of Medicine and School of Biomedical Engineering, Shanghai Jiao Tong University, 1954 Huashan Road, Shanghai 200030, China
- State Key Laboratory of Oncogenes and Related Genes, Institute for Personalized Medicine, Shanghai Jiao Tong University, 1954 Huashan Road, Shanghai 200030, China
| | - Boqian Wang
- Department of Anesthesiology and Surgical Intensive Care Unit, Xinhua Hospital, School of Medicine and School of Biomedical Engineering, Shanghai Jiao Tong University, 1954 Huashan Road, Shanghai 200030, China
- State Key Laboratory of Oncogenes and Related Genes, Institute for Personalized Medicine, Shanghai Jiao Tong University, 1954 Huashan Road, Shanghai 200030, China
| | - Zara Ahmad Khan
- Department of Anesthesiology and Surgical Intensive Care Unit, Xinhua Hospital, School of Medicine and School of Biomedical Engineering, Shanghai Jiao Tong University, 1954 Huashan Road, Shanghai 200030, China
- State Key Laboratory of Oncogenes and Related Genes, Institute for Personalized Medicine, Shanghai Jiao Tong University, 1954 Huashan Road, Shanghai 200030, China
| | - Jie He
- Department of Anesthesiology and Surgical Intensive Care Unit, Xinhua Hospital, School of Medicine and School of Biomedical Engineering, Shanghai Jiao Tong University, 1954 Huashan Road, Shanghai 200030, China
- State Key Laboratory of Oncogenes and Related Genes, Institute for Personalized Medicine, Shanghai Jiao Tong University, 1954 Huashan Road, Shanghai 200030, China
| | - Edwin Cheung
- Cancer Centre, University of Macau, Taipa 999078, Macau SAR
- Centre for Precision Medicine Research and Training, University of Macau, Taipa 999078, Macau SAR
- MoE Frontiers Science Center for Precision Oncology, University of Macau, Taipa 999078, Macau SAR
- Faculty of Health Sciences, University of Macau, Taipa 999078, Macau SAR
| | - Wenqiong Su
- Department of Anesthesiology and Surgical Intensive Care Unit, Xinhua Hospital, School of Medicine and School of Biomedical Engineering, Shanghai Jiao Tong University, 1954 Huashan Road, Shanghai 200030, China
- State Key Laboratory of Oncogenes and Related Genes, Institute for Personalized Medicine, Shanghai Jiao Tong University, 1954 Huashan Road, Shanghai 200030, China
| | - Aiting Wang
- Department of Anesthesiology and Surgical Intensive Care Unit, Xinhua Hospital, School of Medicine and School of Biomedical Engineering, Shanghai Jiao Tong University, 1954 Huashan Road, Shanghai 200030, China
- State Key Laboratory of Oncogenes and Related Genes, Institute for Personalized Medicine, Shanghai Jiao Tong University, 1954 Huashan Road, Shanghai 200030, China
| | - Hui Jiang
- Department of Anesthesiology and Surgical Intensive Care Unit, Xinhua Hospital, School of Medicine and School of Biomedical Engineering, Shanghai Jiao Tong University, 1954 Huashan Road, Shanghai 200030, China
- State Key Laboratory of Oncogenes and Related Genes, Institute for Personalized Medicine, Shanghai Jiao Tong University, 1954 Huashan Road, Shanghai 200030, China
| | - Lai Jiang
- Department of Anesthesiology and Surgical Intensive Care Unit, Xinhua Hospital, School of Medicine and School of Biomedical Engineering, Shanghai Jiao Tong University, 1954 Huashan Road, Shanghai 200030, China
- State Key Laboratory of Oncogenes and Related Genes, Institute for Personalized Medicine, Shanghai Jiao Tong University, 1954 Huashan Road, Shanghai 200030, China
| | - Xianting Ding
- Department of Anesthesiology and Surgical Intensive Care Unit, Xinhua Hospital, School of Medicine and School of Biomedical Engineering, Shanghai Jiao Tong University, 1954 Huashan Road, Shanghai 200030, China
- State Key Laboratory of Oncogenes and Related Genes, Institute for Personalized Medicine, Shanghai Jiao Tong University, 1954 Huashan Road, Shanghai 200030, China
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11
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Planque M, Igelmann S, Ferreira Campos AM, Fendt SM. Spatial metabolomics principles and application to cancer research. Curr Opin Chem Biol 2023; 76:102362. [PMID: 37413787 DOI: 10.1016/j.cbpa.2023.102362] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2022] [Revised: 05/07/2023] [Accepted: 06/06/2023] [Indexed: 07/08/2023]
Abstract
Mass spectrometry imaging (MSI) is an emerging technology in cancer metabolomics. Desorption electrospray ionization (DESI) and matrix-assisted laser desorption ionization (MALDI) MSI are complementary techniques to identify hundreds of metabolites in space with close to single-cell resolution. This technology leap enables research focusing on tumor heterogeneity, cancer cell plasticity, and the communication signals between cancer and stromal cells in the tumor microenvironment (TME). Currently, unprecedented knowledge is generated using spatial metabolomics in fundamental cancer research. Yet, also translational applications are emerging, including the assessment of spatial drug distribution in organs and tumors. Moreover, clinical research investigates the use of spatial metabolomics as a rapid pathology tool during cancer surgeries. Here, we summarize MSI applications, the knowledge gained by this technology in space, future directions, and developments needed.
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Affiliation(s)
- Mélanie Planque
- Laboratory of Cellular Metabolism and Metabolic Regulation, VIB-KU Leuven Center for Cancer Biology, VIB, Leuven, Belgium; Laboratory of Cellular Metabolism and Metabolic Regulation, Department of Oncology, KU Leuven and Leuven Cancer Institute (LKI), Leuven, Belgium
| | - Sebastian Igelmann
- Laboratory of Cellular Metabolism and Metabolic Regulation, VIB-KU Leuven Center for Cancer Biology, VIB, Leuven, Belgium; Laboratory of Cellular Metabolism and Metabolic Regulation, Department of Oncology, KU Leuven and Leuven Cancer Institute (LKI), Leuven, Belgium
| | - Ana Margarida Ferreira Campos
- Laboratory of Cellular Metabolism and Metabolic Regulation, VIB-KU Leuven Center for Cancer Biology, VIB, Leuven, Belgium; Laboratory of Cellular Metabolism and Metabolic Regulation, Department of Oncology, KU Leuven and Leuven Cancer Institute (LKI), Leuven, Belgium
| | - Sarah-Maria Fendt
- Laboratory of Cellular Metabolism and Metabolic Regulation, VIB-KU Leuven Center for Cancer Biology, VIB, Leuven, Belgium; Laboratory of Cellular Metabolism and Metabolic Regulation, Department of Oncology, KU Leuven and Leuven Cancer Institute (LKI), Leuven, Belgium.
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12
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Kumar BS. Recent Advances and Applications of Ambient Mass Spectrometry Imaging in Cancer Research: An Overview. Mass Spectrom (Tokyo) 2023; 12:A0129. [PMID: 37789912 PMCID: PMC10542858 DOI: 10.5702/massspectrometry.a0129] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2023] [Accepted: 08/25/2023] [Indexed: 10/05/2023] Open
Abstract
Cancer metabolic variability has a significant impact on both diagnosis and treatment outcomes. The discovery of novel biological indicators and metabolic dysregulation, can significantly rely on comprehension of the modified metabolism in cancer, is a research focus. Tissue histology is a critical feature in the diagnostic testing of many ailments, such as cancer. To assess the surgical margin of the tumour on patients, frozen section histology is a tedious, laborious, and typically arbitrary method. Concurrent monitoring of ion images in tissues facilitated by the latest advancements in mass spectrometry imaging (MSI) is far more efficient than optical tissue image analysis utilized in conventional histopathology examination. This article focuses on the "desorption electrospray ionization (DESI)-MSI" technique's most recent advancements and uses in cancer research. DESI-MSI can provide wealthy information based on the variances in metabolites and lipids in normal and cancerous tissues by acquiring ion images of the lipid and metabolite variances on biopsy samples. As opposed to a systematic review, this article offers a synopsis of the most widely employed cutting-edge DESI-MSI techniques in cancer research.
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Affiliation(s)
- Bharath S. Kumar
- Correspondence to: Bharath S. Kumar, 21, B2, 27th Street, Nanganallur, Chennai, India, e-mail:
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13
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Isin EM. Unusual Biotransformation Reactions of Drugs and Drug Candidates. Drug Metab Dispos 2023; 51:413-426. [PMID: 36653118 DOI: 10.1124/dmd.121.000744] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2021] [Revised: 12/09/2022] [Accepted: 01/03/2023] [Indexed: 01/19/2023] Open
Abstract
Detailed assessment of the fate of drugs in nonclinical test species and humans is essential to ensure the safety and efficacy of medicines in patients. In this context, biotransformation of drugs and drug candidates has been an area of keen interest over many decades in the pharmaceutical industry as well as academia. Although many of the enzymes and biotransformation pathways involved in the metabolism of xenobiotics and more specifically drugs have been well characterized, each drug molecule is unique and constitutes specific challenges for the biotransformation scientist. In this mini-review written for the special issue on the occasion of the 50th Anniversary celebration of Drug Metabolism and Disposition and to celebrate contributions of F. Peter Guengerich, one of the pioneers of the drug metabolism field, recently reported "unusual" biotransformation reactions are presented. Scientific and technological advances in the "toolbox" of the biotransformation scientists are summarized. As the pharmaceutical industry continues to explore therapeutic modalities different from the traditional small molecule drugs, the new challenges confronting the biotransformation scientist as well as future opportunities are discussed. SIGNIFICANCE STATEMENT: For the biotransformation scientists, it is essential to share and be aware of unexpected biotransformation reactions so that they can increase their confidence in predicting metabolites of drugs in humans to ensure the safety and efficacy of these metabolites before the medicines reach large numbers of patients. The purpose of this review is to highlight recent observations of "unusual" metabolites so that the scientists working in the area of drug metabolism can strengthen their readiness in expecting the unexpected.
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Affiliation(s)
- Emre M Isin
- Translational Medicine, Servier, 25/27 Rue Eugène Vignat, 45000, Orléans, France
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14
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Glasson Y, Chépeaux LA, Dumé AS, Jay P, Pirot N, Bonnefoy N, Michaud HA. A 31-plex panel for high-dimensional single-cell analysis of murine preclinical models of solid tumors by imaging mass cytometry. Front Immunol 2023; 13:1011617. [PMID: 36741363 PMCID: PMC9893499 DOI: 10.3389/fimmu.2022.1011617] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2022] [Accepted: 12/28/2022] [Indexed: 01/20/2023] Open
Abstract
Currently, the study of resistance mechanisms and disease progression in cancer relies on the capacity to analyze tumors as a complex ecosystem of healthy and malignant cells. Therefore, one of the current challenges is to decipher the intra-tumor heterogeneity and especially the spatial distribution and interactions of the different cellular actors within the tumor. Preclinical mouse models are widely used to extend our understanding of the tumor microenvironment (TME). Such models are becoming more sophisticated and allow investigating questions that cannot be addressed in clinical studies. Indeed, besides studying the tumor cell interactions within their environment, mouse models allow evaluating the efficacy of new drugs and delivery approaches, treatment posology, and toxicity. Spatially resolved analyses of the intra-tumor heterogeneity require global approaches to identify and localize a large number of different cell types. For this purpose, imaging mass cytometry (IMC) is a major asset in the field of human immuno-oncology. However, the paucity of validated IMC panels to study TME in pre-clinical mouse models remains a critical obstacle to translational or basic research in oncology. Here, we validated a panel of 31 markers for studying at the single-cell level the TME and the immune landscape for discovering/characterizing cells with complex phenotypes and the interactions shaping the tumor ecosystem in mouse models.
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Affiliation(s)
- Yaël Glasson
- Institut de Recherche en Cancérologie de Montpellier (IRCM), Univ Montpellier, Inserm, Institut régional du Cancer de Montpellier (ICM), Plateforme de Cytométrie et d’Imagerie de Masse, Montpellier, France,Institut de Recherche en Cancérologie de Montpellier (IRCM), Univ Montpellier, Inserm, Institut régional du Cancer de Montpellier (ICM), Montpellier, France
| | - Laure-Agnès Chépeaux
- Institut de Recherche en Cancérologie de Montpellier (IRCM), Univ Montpellier, Inserm, Institut régional du Cancer de Montpellier (ICM), Plateforme de Cytométrie et d’Imagerie de Masse, Montpellier, France
| | - Anne-Sophie Dumé
- Institut de Recherche en Cancérologie de Montpellier (IRCM), Univ Montpellier, Inserm, Institut régional du Cancer de Montpellier (ICM), Plateforme de Cytométrie et d’Imagerie de Masse, Montpellier, France
| | - Philippe Jay
- Institut de Génomique Fonctionnelle (IGF), University of Montpellier, Centre national de la recherche scientifique (CNRS), Inserm, Montpellier, France
| | - Nelly Pirot
- Institut de Recherche en Cancérologie de Montpellier (IRCM), Univ Montpellier, Inserm, Institut régional du Cancer de Montpellier (ICM), Montpellier, France,BioCampus Montpellier, Univ Montpellier, Centre national de la recherche scientifique (CNRS), Inserm, Réseau d’Histologie Expérimentale de Montpellier, Montpellier, France
| | - Nathalie Bonnefoy
- Institut de Recherche en Cancérologie de Montpellier (IRCM), Univ Montpellier, Inserm, Institut régional du Cancer de Montpellier (ICM), Plateforme de Cytométrie et d’Imagerie de Masse, Montpellier, France,Institut de Recherche en Cancérologie de Montpellier (IRCM), Univ Montpellier, Inserm, Institut régional du Cancer de Montpellier (ICM), Montpellier, France
| | - Henri-Alexandre Michaud
- Institut de Recherche en Cancérologie de Montpellier (IRCM), Univ Montpellier, Inserm, Institut régional du Cancer de Montpellier (ICM), Plateforme de Cytométrie et d’Imagerie de Masse, Montpellier, France,Institut de Recherche en Cancérologie de Montpellier (IRCM), Univ Montpellier, Inserm, Institut régional du Cancer de Montpellier (ICM), Montpellier, France,*Correspondence: Henri-Alexandre Michaud,
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15
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Glasson Y, Chépeaux LA, Dumé AS, Lafont V, Faget J, Bonnefoy N, Michaud HA. Single-cell high-dimensional imaging mass cytometry: one step beyond in oncology. Semin Immunopathol 2023; 45:17-28. [PMID: 36598557 PMCID: PMC9812013 DOI: 10.1007/s00281-022-00978-w] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2022] [Accepted: 12/11/2022] [Indexed: 01/05/2023]
Abstract
Solid tumors have a dynamic ecosystem in which malignant and non-malignant (endothelial, stromal, and immune) cell types constantly interact. Importantly, the abundance, localization, and functional orientation of each cell component within the tumor microenvironment vary significantly over time and in response to treatment. Such intratumoral heterogeneity influences the tumor course and its sensitivity to treatments. Recently, high-dimensional imaging mass cytometry (IMC) has been developed to explore the tumor ecosystem at the single-cell level. In the last years, several studies demonstrated that IMC is a powerful tool to decipher the tumor complexity. In this review, we summarize the potential of this technology and how it may be useful for cancer research (from preclinical to clinical studies).
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Affiliation(s)
- Yaël Glasson
- IRCM, Univ Montpellier, ICM, Plateforme de Cytométrie Et d’Imagerie de Masse, Inserm Montpellier, France
| | - Laure-Agnès Chépeaux
- IRCM, Univ Montpellier, ICM, Plateforme de Cytométrie Et d’Imagerie de Masse, Inserm Montpellier, France
| | - Anne-Sophie Dumé
- IRCM, Univ Montpellier, ICM, Plateforme de Cytométrie Et d’Imagerie de Masse, Inserm Montpellier, France
| | | | - Julien Faget
- IRCM, Univ Montpellier, ICM, Inserm Montpellier, France
| | - Nathalie Bonnefoy
- IRCM, Univ Montpellier, ICM, Plateforme de Cytométrie Et d’Imagerie de Masse, Inserm Montpellier, France
| | - Henri-Alexandre Michaud
- IRCM, Univ Montpellier, ICM, Plateforme de Cytométrie Et d'Imagerie de Masse, Inserm Montpellier, France.
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16
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Hou JJ, Zhang ZJ, Wu WY, He QQ, Zhang TQ, Liu YW, Wang ZJ, Gao L, Long HL, Lei M, Wu WY, Guo DA. Mass spectrometry imaging: new eyes on natural products for drug research and development. Acta Pharmacol Sin 2022; 43:3096-3111. [PMID: 36229602 PMCID: PMC9712638 DOI: 10.1038/s41401-022-00990-8] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2022] [Accepted: 08/25/2022] [Indexed: 11/09/2022] Open
Abstract
Natural products (NPs) and their structural analogs represent a major source of novel drug development for disease prevention and treatment. The development of new drugs from NPs includes two crucial aspects. One is the discovery of NPs from medicinal plants/microorganisms, and the other is the evaluation of the NPs in vivo at various physiological and pathological states. The heterogeneous spatial distribution of NPs in medicinal plants/microorganisms or in vivo can provide valuable information for drug development. However, few molecular imaging technologies can detect thousands of compounds simultaneously on a label-free basis. Over the last two decades, mass spectrometry imaging (MSI) methods have progressively improved and diversified, thereby allowing for the development of various applications of NPs in plants/microorganisms and in vivo NP research. Because MSI allows for the spatial mapping of the production and distribution of numerous molecules in situ without labeling, it provides a visualization tool for NP research. Therefore, we have focused this mini-review on summarizing the applications of MSI technology in discovering NPs from medicinal plants and evaluating NPs in preclinical studies from the perspective of new drug research and development (R&D). Additionally, we briefly reviewed the factors that should be carefully considered to obtain the desired MSI results. Finally, the future development of MSI in new drug R&D is proposed.
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Affiliation(s)
- Jin-Jun Hou
- National Engineering Research Center of TCM Standardization Technology, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai, 201203, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Zi-Jia Zhang
- National Engineering Research Center of TCM Standardization Technology, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai, 201203, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Wen-Yong Wu
- National Engineering Research Center of TCM Standardization Technology, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai, 201203, China
- School of Chinese Materia Medica, Nanjing University of Chinese Medicine, Nanjing, 210029, China
| | - Qing-Qing He
- National Engineering Research Center of TCM Standardization Technology, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai, 201203, China
| | - Teng-Qian Zhang
- National Engineering Research Center of TCM Standardization Technology, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai, 201203, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Ya-Wen Liu
- National Engineering Research Center of TCM Standardization Technology, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai, 201203, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Zhao-Jun Wang
- National Engineering Research Center of TCM Standardization Technology, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai, 201203, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Lei Gao
- National Engineering Research Center of TCM Standardization Technology, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai, 201203, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Hua-Li Long
- National Engineering Research Center of TCM Standardization Technology, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai, 201203, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Min Lei
- National Engineering Research Center of TCM Standardization Technology, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai, 201203, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Wan-Ying Wu
- National Engineering Research Center of TCM Standardization Technology, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai, 201203, China.
- University of Chinese Academy of Sciences, Beijing, 100049, China.
| | - De-An Guo
- National Engineering Research Center of TCM Standardization Technology, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai, 201203, China.
- University of Chinese Academy of Sciences, Beijing, 100049, China.
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17
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Liu Z, Xun J, Liu S, Wang B, Zhang A, Zhang L, Wang X, Zhang Q. Imaging mass cytometry: High-dimensional and single-cell perspectives on the microenvironment of solid tumours. PROGRESS IN BIOPHYSICS AND MOLECULAR BIOLOGY 2022; 175:140-146. [DOI: 10.1016/j.pbiomolbio.2022.10.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/07/2022] [Revised: 10/07/2022] [Accepted: 10/11/2022] [Indexed: 01/04/2023]
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18
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Multiplex Tissue Imaging: Spatial Revelations in the Tumor Microenvironment. Cancers (Basel) 2022; 14:cancers14133170. [PMID: 35804939 PMCID: PMC9264815 DOI: 10.3390/cancers14133170] [Citation(s) in RCA: 20] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2022] [Revised: 06/22/2022] [Accepted: 06/23/2022] [Indexed: 11/17/2022] Open
Abstract
Simple Summary Cancer is the leading cause of death worldwide, and the overall aging of the population results in an increased risk of a cancer diagnosis during a person’s lifetime. Diagnosis and treatment at an early stage will typically increase the chances of survival. Tumors can develop therapy resistance, and it is difficult to predict how individual patients will respond to therapy. Most studies that aim to resolve this problem have focused on studying the composition and characteristics of dissociated tumors, while ignoring the role of cell localization and interactions within the tumor microenvironment. In the past decade, technological innovations have enabled multiplex imaging analyses of intact tumors to study localization and interaction parameters, which can be used as biomarkers, or can be correlated with treatment responses and clinical outcomes. Abstract The tumor microenvironment is a complex ecosystem containing various cell types, such as immune cells, fibroblasts, and endothelial cells, which interact with the tumor cells. In recent decades, the cancer research field has gained insight into the cellular subtypes that are involved in tumor microenvironment heterogeneity. Moreover, it has become evident that cellular interactions in the tumor microenvironment can either promote or inhibit tumor development, progression, and drug resistance, depending on the context. Multiplex spatial analysis methods have recently been developed; these have offered insight into how cellular crosstalk dynamics and heterogeneity affect cancer prognoses and responses to treatment. Multiplex (imaging) technologies and computational analysis methods allow for the spatial visualization and quantification of cell–cell interactions and properties. These technological advances allow for the discovery of cellular interactions within the tumor microenvironment and provide detailed single-cell information on properties that define cellular behavior. Such analyses give insights into the prognosis and mechanisms of therapy resistance, which is still an urgent problem in the treatment of multiple types of cancer. Here, we provide an overview of multiplex imaging technologies and concepts of downstream analysis methods to investigate cell–cell interactions, how these studies have advanced cancer research, and their potential clinical implications.
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19
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Tuck M, Grélard F, Blanc L, Desbenoit N. MALDI-MSI Towards Multimodal Imaging: Challenges and Perspectives. Front Chem 2022; 10:904688. [PMID: 35615316 PMCID: PMC9124797 DOI: 10.3389/fchem.2022.904688] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2022] [Accepted: 04/14/2022] [Indexed: 01/22/2023] Open
Abstract
Multimodal imaging is a powerful strategy for combining information from multiple images. It involves several fields in the acquisition, processing and interpretation of images. As multimodal imaging is a vast subject area with various combinations of imaging techniques, it has been extensively reviewed. Here we focus on Matrix-assisted Laser Desorption Ionization Mass Spectrometry Imaging (MALDI-MSI) coupling other imaging modalities in multimodal approaches. While MALDI-MS images convey a substantial amount of chemical information, they are not readily informative about the morphological nature of the tissue. By providing a supplementary modality, MALDI-MS images can be more informative and better reflect the nature of the tissue. In this mini review, we emphasize the analytical and computational strategies to address multimodal MALDI-MSI.
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