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Zirem Y, Ledoux L, Roussel L, Maurage CA, Tirilly P, Le Rhun É, Meresse B, Yagnik G, Lim MJ, Rothschild KJ, Duhamel M, Salzet M, Fournier I. Real-time glioblastoma tumor microenvironment assessment by SpiderMass for improved patient management. Cell Rep Med 2024; 5:101482. [PMID: 38552622 PMCID: PMC11031375 DOI: 10.1016/j.xcrm.2024.101482] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2023] [Revised: 01/15/2024] [Accepted: 03/01/2024] [Indexed: 04/19/2024]
Abstract
Glioblastoma is a highly heterogeneous and infiltrative form of brain cancer associated with a poor outcome and limited therapeutic effectiveness. The extent of the surgery is related to survival. Reaching an accurate diagnosis and prognosis assessment by the time of the initial surgery is therefore paramount in the management of glioblastoma. To this end, we are studying the performance of SpiderMass, an ambient ionization mass spectrometry technology that can be used in vivo without invasiveness, coupled to our recently established artificial intelligence pipeline. We demonstrate that we can both stratify isocitrate dehydrogenase (IDH)-wild-type glioblastoma patients into molecular sub-groups and achieve an accurate diagnosis with over 90% accuracy after cross-validation. Interestingly, the developed method offers the same accuracy for prognosis. In addition, we are testing the potential of an immunoscoring strategy based on SpiderMass fingerprints, showing the association between prognosis and immune cell infiltration, to predict patient outcome.
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Affiliation(s)
- Yanis Zirem
- Université de Lille, Inserm, CHU Lille, U1192 - Protéomique Réponse Inflammatoire Spectrométrie de Masse - PRISM, 59000 Lille, France
| | - Léa Ledoux
- Université de Lille, Inserm, CHU Lille, U1192 - Protéomique Réponse Inflammatoire Spectrométrie de Masse - PRISM, 59000 Lille, France
| | - Lucas Roussel
- Université de Lille, Inserm, CHU Lille, U1192 - Protéomique Réponse Inflammatoire Spectrométrie de Masse - PRISM, 59000 Lille, France
| | | | - Pierre Tirilly
- Université de Lille, CNRS, Centrale Lille, UMR 9189 CRIStAL, 59000 Lille, France
| | - Émilie Le Rhun
- Université de Lille, Inserm, CHU Lille, U1192 - Protéomique Réponse Inflammatoire Spectrométrie de Masse - PRISM, 59000 Lille, France; Departments of Neurosurgery and Neurology, Clinical Neuroscience Center, University Hospital of Zurich, University of Zurich, Zurich, Switzerland
| | - Bertrand Meresse
- Université de Lille, Inserm, CHU Lille, U1286 - INFINITE - Institute for Translational Research in Inflammation, 59000 Lille, France
| | | | | | - Kenneth J Rothschild
- AmberGen, Inc., Billerica, MA, USA; Department of Physics and Photonics Center, Boston University, Boston, MA, USA
| | - Marie Duhamel
- Université de Lille, Inserm, CHU Lille, U1192 - Protéomique Réponse Inflammatoire Spectrométrie de Masse - PRISM, 59000 Lille, France
| | - Michel Salzet
- Université de Lille, Inserm, CHU Lille, U1192 - Protéomique Réponse Inflammatoire Spectrométrie de Masse - PRISM, 59000 Lille, France; Institut Universitaire de France (IUF), Paris, France.
| | - Isabelle Fournier
- Université de Lille, Inserm, CHU Lille, U1192 - Protéomique Réponse Inflammatoire Spectrométrie de Masse - PRISM, 59000 Lille, France; Institut Universitaire de France (IUF), Paris, France.
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2
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Vlocskó M, Piffkó J, Janovszky Á. Intraoperative Assessment of Resection Margin in Oral Cancer: The Potential Role of Spectroscopy. Cancers (Basel) 2023; 16:121. [PMID: 38201548 PMCID: PMC10777979 DOI: 10.3390/cancers16010121] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2023] [Revised: 12/21/2023] [Accepted: 12/22/2023] [Indexed: 01/12/2024] Open
Abstract
In parallel with the increasing number of oncological cases, the need for faster and more efficient diagnostic tools has also appeared. Different diagnostic approaches are available, such as radiological imaging or histological staining methods, but these do not provide adequate information regarding the resection margin, intraoperatively, or are time consuming. The purpose of this review is to summarize the current knowledge on spectrometric diagnostic modalities suitable for intraoperative use, with an emphasis on their relevance in the management of oral cancer. The literature agrees on the sensitivity, specificity, and accuracy of spectrometric diagnostic modalities, but further long-term prospective, multicentric clinical studies are needed, which may standardize the intraoperative assessment of the resection margin and the use of real-time spectroscopic approaches.
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Affiliation(s)
| | | | - Ágnes Janovszky
- Department of Oral and Maxillofacial Surgery, Albert Szent-Györgyi Medical School, University of Szeged, Kálvária 57, H-6725 Szeged, Hungary; (M.V.); (J.P.)
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3
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Stadlhofer R, Moritz M, Fuh MM, Heeren J, Zech H, Clauditz TS, Schlüter H, Betz CS, Eggert D, Böttcher A, Hahn J. Lipidome Analysis of Oropharyngeal Tumor Tissues Using Nanosecond Infrared Laser (NIRL) Tissue Sampling and Subsequent Mass Spectrometry. Int J Mol Sci 2023; 24:ijms24097820. [PMID: 37175533 PMCID: PMC10178251 DOI: 10.3390/ijms24097820] [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: 03/23/2023] [Revised: 04/16/2023] [Accepted: 04/21/2023] [Indexed: 05/15/2023] Open
Abstract
Ultrashort pulse infrared lasers can simultaneously sample and homogenize biological tissue using desorption by impulsive vibrational excitation (DIVE). With growing attention on alterations in lipid metabolism in malignant disease, mass spectrometry (MS)-based lipidomic analysis has become an emerging topic in cancer research. In this pilot study, we investigated the feasibility of tissue sampling with a nanosecond infrared laser (NIRL) for the subsequent lipidomic analysis of oropharyngeal tissues, and its potential to discriminate oropharyngeal squamous cell carcinoma (OPSCC) from non-tumorous oropharyngeal tissue. Eleven fresh frozen oropharyngeal tissue samples were ablated. The produced aerosols were collected by a glass fiber filter, and the lipidomes were analyzed with mass spectrometry. Data was evaluated by principal component analysis and Welch's t-tests. Lipid profiles comprised 13 lipid classes and up to 755 lipid species. We found significant inter- and intrapatient alterations in lipid profiles for tumor and non-tumor samples (p-value < 0.05, two-fold difference). Thus, NIRL tissue sampling with consecutive MS lipidomic analysis is a feasible and promising approach for the differentiation of OPSCC and non-tumorous oropharyngeal tissue and may provide new insights into lipid composition alterations in OPSCC.
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Affiliation(s)
- Rupert Stadlhofer
- Department of Otorhinolaryngology, University Medical Center Hamburg-Eppendorf, Martinistraße 52, 20246 Hamburg, Germany
| | - Manuela Moritz
- Section/Core Facility Mass Spectrometric Proteomics, Diagnostic Center, University Medical Center Hamburg-Eppendorf, Martinistraße 52, 20246 Hamburg, Germany
| | - Marceline M Fuh
- Department of Biochemistry and Molecular Cell Biology, Center for Experimental Medicine, University Medical Center Hamburg-Eppendorf, Martinistraße 52, 20246 Hamburg, Germany
| | - Jörg Heeren
- Department of Biochemistry and Molecular Cell Biology, Center for Experimental Medicine, University Medical Center Hamburg-Eppendorf, Martinistraße 52, 20246 Hamburg, Germany
| | - Henrike Zech
- Department of Otorhinolaryngology, University Medical Center Hamburg-Eppendorf, Martinistraße 52, 20246 Hamburg, Germany
- Mildred Scheel Cancer Career Center HaTriCS4, University Medical Center Hamburg-Eppendorf, Martinistraße 52, 20246 Hamburg, Germany
| | - Till S Clauditz
- Department of Pathology, Diagnostic Center, University Medical Center Hamburg-Eppendorf, Martinistraße 52, 20246 Hamburg, Germany
| | - Hartmut Schlüter
- Section/Core Facility Mass Spectrometric Proteomics, Diagnostic Center, University Medical Center Hamburg-Eppendorf, Martinistraße 52, 20246 Hamburg, Germany
| | - Christian S Betz
- Department of Otorhinolaryngology, University Medical Center Hamburg-Eppendorf, Martinistraße 52, 20246 Hamburg, Germany
| | - Dennis Eggert
- Department of Otorhinolaryngology, University Medical Center Hamburg-Eppendorf, Martinistraße 52, 20246 Hamburg, Germany
| | - Arne Böttcher
- Department of Otorhinolaryngology, University Medical Center Hamburg-Eppendorf, Martinistraße 52, 20246 Hamburg, Germany
| | - Jan Hahn
- Section/Core Facility Mass Spectrometric Proteomics, Diagnostic Center, University Medical Center Hamburg-Eppendorf, Martinistraße 52, 20246 Hamburg, Germany
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4
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Morato NM, Brown HM, Garcia D, Middlebrooks EH, Jentoft M, Chaichana K, Quiñones-Hinojosa A, Cooks RG. High-throughput analysis of tissue microarrays using automated desorption electrospray ionization mass spectrometry. Sci Rep 2022; 12:18851. [PMID: 36344609 PMCID: PMC9640715 DOI: 10.1038/s41598-022-22924-4] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2022] [Accepted: 10/20/2022] [Indexed: 11/09/2022] Open
Abstract
Tissue microarrays (TMAs) are commonly used for the rapid analysis of large numbers of tissue samples, often in morphological assessments but increasingly in spectroscopic analysis, where specific molecular markers are targeted via immunostaining. Here we report the use of an automated high-throughput system based on desorption electrospray ionization (DESI) mass spectrometry (MS) for the rapid generation and online analysis of high-density (6144 samples/array) TMAs, at rates better than 1 sample/second. Direct open-air analysis of tissue samples (hundreds of nanograms) not subjected to prior preparation, plus the ability to provide molecular characterization by tandem mass spectrometry (MS/MS), make this experiment versatile and applicable to both targeted and untargeted analysis in a label-free manner. These capabilities are demonstrated in a proof-of-concept study of frozen brain tissue biopsies where we showcase (i) a targeted MS/MS application aimed at identification of isocitrate dehydrogenase mutation in glioma samples and (ii) an untargeted MS tissue type classification using lipid profiles and correlation with tumor cell percentage estimates from histopathology. The small sample sizes and large sample numbers accessible with this methodology make for a powerful analytical system that facilitates the identification of molecular markers for later use in intraoperative applications to guide precision surgeries and ultimately improve patient outcomes.
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Affiliation(s)
- Nicolás M. Morato
- grid.169077.e0000 0004 1937 2197Department of Chemistry, Purdue Center for Cancer Research, and Bindley Bioscience Center, Purdue University, 560 Oval Drive, West Lafayette, IN 47907 USA
| | - Hannah Marie Brown
- grid.169077.e0000 0004 1937 2197Department of Chemistry, Purdue Center for Cancer Research, and Bindley Bioscience Center, Purdue University, 560 Oval Drive, West Lafayette, IN 47907 USA ,grid.4367.60000 0001 2355 7002Present Address: Department of Pathology and Immunology, Washington University School of Medicine, St. Louis, MO USA
| | - Diogo Garcia
- grid.417467.70000 0004 0443 9942Department of Neurosurgery, Mayo Clinic, Jacksonville, FL USA
| | - Erik H. Middlebrooks
- grid.417467.70000 0004 0443 9942Department of Neurosurgery, Mayo Clinic, Jacksonville, FL USA ,grid.417467.70000 0004 0443 9942Department of Radiology, Mayo Clinic, Jacksonville, FL USA
| | - Mark Jentoft
- grid.417467.70000 0004 0443 9942Department of Laboratory Medicine and Pathology, Mayo Clinic, Jacksonville, FL USA
| | - Kaisorn Chaichana
- grid.417467.70000 0004 0443 9942Department of Neurosurgery, Mayo Clinic, Jacksonville, FL USA
| | | | - R. Graham Cooks
- grid.169077.e0000 0004 1937 2197Department of Chemistry, Purdue Center for Cancer Research, and Bindley Bioscience Center, Purdue University, 560 Oval Drive, West Lafayette, IN 47907 USA
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5
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Zhou X, Wang H, Feng C, Xu R, He Y, Li L, Tu C. Emerging Applications of Deep Learning in Bone Tumors: Current Advances and Challenges. Front Oncol 2022; 12:908873. [PMID: 35928860 PMCID: PMC9345628 DOI: 10.3389/fonc.2022.908873] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2022] [Accepted: 06/15/2022] [Indexed: 12/12/2022] Open
Abstract
Deep learning is a subfield of state-of-the-art artificial intelligence (AI) technology, and multiple deep learning-based AI models have been applied to musculoskeletal diseases. Deep learning has shown the capability to assist clinical diagnosis and prognosis prediction in a spectrum of musculoskeletal disorders, including fracture detection, cartilage and spinal lesions identification, and osteoarthritis severity assessment. Meanwhile, deep learning has also been extensively explored in diverse tumors such as prostate, breast, and lung cancers. Recently, the application of deep learning emerges in bone tumors. A growing number of deep learning models have demonstrated good performance in detection, segmentation, classification, volume calculation, grading, and assessment of tumor necrosis rate in primary and metastatic bone tumors based on both radiological (such as X-ray, CT, MRI, SPECT) and pathological images, implicating a potential for diagnosis assistance and prognosis prediction of deep learning in bone tumors. In this review, we first summarized the workflows of deep learning methods in medical images and the current applications of deep learning-based AI for diagnosis and prognosis prediction in bone tumors. Moreover, the current challenges in the implementation of the deep learning method and future perspectives in this field were extensively discussed.
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Affiliation(s)
- Xiaowen Zhou
- Department of Orthopaedics, The Second Xiangya Hospital, Central South University, Changsha, China
- Xiangya School of Medicine, Central South University, Changsha, China
| | - Hua Wang
- Xiangya School of Medicine, Central South University, Changsha, China
| | - Chengyao Feng
- Department of Orthopaedics, The Second Xiangya Hospital, Central South University, Changsha, China
- Hunan Key Laboratory of Tumor Models and Individualized Medicine, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Ruilin Xu
- Department of Orthopaedics, The Second Xiangya Hospital, Central South University, Changsha, China
- Hunan Key Laboratory of Tumor Models and Individualized Medicine, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Yu He
- Department of Radiology, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Lan Li
- Department of Pathology, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Chao Tu
- Department of Orthopaedics, The Second Xiangya Hospital, Central South University, Changsha, China
- Hunan Key Laboratory of Tumor Models and Individualized Medicine, The Second Xiangya Hospital, Central South University, Changsha, China
- *Correspondence: Chao Tu,
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Isberg OG, Giunchiglia V, McKenzie JS, Takats Z, Jonasson JG, Bodvarsdottir SK, Thorsteinsdottir M, Xiang Y. Automated Cancer Diagnostics via Analysis of Optical and Chemical Images by Deep and Shallow Learning. Metabolites 2022; 12:455. [PMID: 35629959 PMCID: PMC9143055 DOI: 10.3390/metabo12050455] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2022] [Revised: 05/10/2022] [Accepted: 05/13/2022] [Indexed: 02/04/2023] Open
Abstract
Optical microscopy has long been the gold standard to analyse tissue samples for the diagnostics of various diseases, such as cancer. The current diagnostic workflow is time-consuming and labour-intensive, and manual annotation by a qualified pathologist is needed. With the ever-increasing number of tissue blocks and the complexity of molecular diagnostics, new approaches have been developed as complimentary or alternative solutions for the current workflow, such as digital pathology and mass spectrometry imaging (MSI). This study compares the performance of a digital pathology workflow using deep learning for tissue recognition and an MSI approach utilising shallow learning to annotate formalin-fixed and paraffin-embedded (FFPE) breast cancer tissue microarrays (TMAs). Results show that both deep learning algorithms based on conventional optical images and MSI-based shallow learning can provide automated diagnostics with F1-scores higher than 90%, with the latter intrinsically built on biochemical information that can be used for further analysis.
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Affiliation(s)
- Olof Gerdur Isberg
- Department of Metabolism, Digestion and Reproduction, Faculty of Medicine, Imperial College London, London SW7 2AZ, UK; (O.G.I.); (V.G.); (J.S.M.); (Z.T.)
- Faculty of Pharmaceutical Sciences, University of Iceland, Hofsvallagata 53, 107 Reykjavik, Iceland
- Biomedical Center, School of Health Sciences, University of Iceland, 101 Reykjavik, Iceland;
| | - Valentina Giunchiglia
- Department of Metabolism, Digestion and Reproduction, Faculty of Medicine, Imperial College London, London SW7 2AZ, UK; (O.G.I.); (V.G.); (J.S.M.); (Z.T.)
| | - James S. McKenzie
- Department of Metabolism, Digestion and Reproduction, Faculty of Medicine, Imperial College London, London SW7 2AZ, UK; (O.G.I.); (V.G.); (J.S.M.); (Z.T.)
| | - Zoltan Takats
- Department of Metabolism, Digestion and Reproduction, Faculty of Medicine, Imperial College London, London SW7 2AZ, UK; (O.G.I.); (V.G.); (J.S.M.); (Z.T.)
| | - Jon Gunnlaugur Jonasson
- Department of Pathology, Landspitali the National University Hospital, Hringbraut, 101 Reykjavik, Iceland;
- Faculty of Medicine, University of Iceland, Vatnsmyrarvegur 16, 101 Reykjavik, Iceland
| | | | - Margret Thorsteinsdottir
- Faculty of Pharmaceutical Sciences, University of Iceland, Hofsvallagata 53, 107 Reykjavik, Iceland
- Biomedical Center, School of Health Sciences, University of Iceland, 101 Reykjavik, Iceland;
| | - Yuchen Xiang
- Department of Metabolism, Digestion and Reproduction, Faculty of Medicine, Imperial College London, London SW7 2AZ, UK; (O.G.I.); (V.G.); (J.S.M.); (Z.T.)
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7
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Ogrinc N, Attencourt C, Colin E, Boudahi A, Tebbakha R, Salzet M, Testelin S, Dakpé S, Fournier I. Mass Spectrometry-Based Differentiation of Oral Tongue Squamous Cell Carcinoma and Nontumor Regions With the SpiderMass Technology. FRONTIERS IN ORAL HEALTH 2022; 3:827360. [PMID: 35309279 PMCID: PMC8929397 DOI: 10.3389/froh.2022.827360] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2021] [Accepted: 01/26/2022] [Indexed: 12/14/2022] Open
Abstract
Oral cavity cancers are the 15th most common cancer with more than 350,000 new cases and ~178,000 deaths each year. Among them, squamous cell carcinoma (SCC) accounts for more than 90% of tumors located in the oral cavity and on oropharynx. For the oral cavity SCC, the surgical resection remains the primary course of treatment. Generally, surgical margins are defined intraoperatively using visual and tactile elements. However, in 15-30% of cases, positive margins are found after histopathological examination several days postsurgery. Technologies based on mass spectrometry (MS) were recently developed to help guide surgical resection. The SpiderMass technology is designed for in-vivo real-time analysis under minimally invasive conditions. This instrument achieves tissue microsampling and real-time molecular analysis with the combination of a laser microprobe and a mass spectrometer. It ultimately acts as a tool to support histopathological decision-making and diagnosis. This pilot study included 14 patients treated for tongue SCC (T1 to T4) with the surgical resection as the first line of treatment. Samples were first analyzed by a pathologist to macroscopically delineate the tumor, dysplasia, and peritumoral areas. The retrospective and prospective samples were sectioned into three consecutive sections and thaw-mounted on slides for H&E staining (7 μm), SpiderMass analysis (20 μm), and matrix-assisted laser desorption ionization (MALDI) MS imaging (12 μm). The SpiderMass microprobe collected lipidometabolic profiles of the dysplasia, tumor, and peritumoral regions annotated by the pathologist. The MS spectra were then subjected to the multivariate statistical analysis. The preliminary data demonstrate that the lipidometabolic molecular profiles collected with the SpiderMass are significantly different between the tumor and peritumoral regions enabling molecular classification to be established by linear discriminant analysis (LDA). MALDI images of the different samples were submitted to segmentation for cross instrument validation and revealed additional molecular discrimination within the tumor and nontumor regions. These very promising preliminary results show the applicability of the SpiderMass to SCC of the tongue and demonstrate its interest in the surgical treatment of head and neck cancers.
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Affiliation(s)
- Nina Ogrinc
- University of Lille, Inserm, CHU Lille, U1192 - Protéomique Réponse Inflammatoire Spectrométrie de Masse – PRISM, Lille, France
| | - Christophe Attencourt
- Department of Pathology, CHU Amiens-Picardie, Amiens, France
- UR7516 CHIMERE, Université de Picardie Jules Verne, Amiens, France
| | - Emilien Colin
- UR7516 CHIMERE, Université de Picardie Jules Verne, Amiens, France
- Department of Maxillofacial Surgery, CHU Amiens-Picardie, Amiens, France
- Institut Faire Faces, Amiens, France
| | - Ahmed Boudahi
- Department of Pathology, CHU Amiens-Picardie, Amiens, France
| | - Riad Tebbakha
- Tumorothèque de Picardie, CHU Amiens-Picardie, Amiens, France
| | - Michel Salzet
- University of Lille, Inserm, CHU Lille, U1192 - Protéomique Réponse Inflammatoire Spectrométrie de Masse – PRISM, Lille, France
- Institut Universitaire de France (IUF), Paris, France
| | - Sylvie Testelin
- UR7516 CHIMERE, Université de Picardie Jules Verne, Amiens, France
- Department of Maxillofacial Surgery, CHU Amiens-Picardie, Amiens, France
- Institut Faire Faces, Amiens, France
| | - Stéphanie Dakpé
- UR7516 CHIMERE, Université de Picardie Jules Verne, Amiens, France
- Department of Maxillofacial Surgery, CHU Amiens-Picardie, Amiens, France
- Institut Faire Faces, Amiens, France
| | - Isabelle Fournier
- University of Lille, Inserm, CHU Lille, U1192 - Protéomique Réponse Inflammatoire Spectrométrie de Masse – PRISM, Lille, France
- Institut Universitaire de France (IUF), Paris, France
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8
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Buszewska-Forajta M, Rafińska K, Buszewski B. Tissue sample preparations for preclinical research determined by molecular imaging mass spectrometry using MALDI. J Sep Sci 2022; 45:1345-1361. [PMID: 35122386 DOI: 10.1002/jssc.202100578] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2021] [Revised: 01/25/2022] [Accepted: 01/26/2022] [Indexed: 11/09/2022]
Abstract
Matrix-assisted laser desorption/ionization - imaging mass spectrometry is an alternative tool, which can be implemented in order to obtain and visualize the "omic" signature of tissue samples. Its application to clinical study enables simultaneous imaging-based morphological observations and mass spectrometry analysis. Application of fully informative material like tissue, allows to obtain the complex and unique profile of analyzed samples. This knowledge leads to diagnose disease, study the mechanism of cancer development, select the potential biomarkers as well as correlating obtained image with prognosis. Nevertheless, it is worth to notice that this method is found to be objective but the result of analysis is mainly influenced by the sample preparation protocol, included collection of biological material, its preservation and processing. However, application of this approach requires a special sample preparation procedure. The main goal of the study is to present the current knowledge on the clinical application of matrix-assisted laser desorption/ionization - imaging mass spectrometry in cancer research, with particular emphasis on the sample preparation step. For this purpose, several protocols based on cryosections and formalin-fixed paraffin embedded tissue were compiled and compared, taking into account the measured metabolites of potential diagnostic importance for a given type of cancer. This article is protected by copyright. All rights reserved.
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Affiliation(s)
- Magdalena Buszewska-Forajta
- Institute of Veterinary Medicine, Faculty of Biological and Veterinary Sciences, Nicolaus Copernicus University, Lwowska 1, Toruń, 87-100, Poland
| | - Katarzyna Rafińska
- Department of Environmental Chemistry and Bioanalytics, Faculty of Chemistry, Nicolaus Copernicus University, 7 Gagarina Str., Torun, 87-100, Poland
| | - Boguslaw Buszewski
- Department of Environmental Chemistry and Bioanalytics, Faculty of Chemistry, Nicolaus Copernicus University, 7 Gagarina Str., Torun, 87-100, Poland.,Centre for Modern Interdisciplinary Technologies, Nicolaus Copernicus University in Torun, 4 Wileńska Str., Torun, 87-100, Poland
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