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Fan X, Sun AR, Young RSE, Afara IO, Hamilton BR, Ong LJY, Crawford R, Prasadam I. Spatial analysis of the osteoarthritis microenvironment: techniques, insights, and applications. Bone Res 2024; 12:7. [PMID: 38311627 PMCID: PMC10838951 DOI: 10.1038/s41413-023-00304-6] [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: 09/05/2023] [Revised: 11/21/2023] [Accepted: 11/27/2023] [Indexed: 02/06/2024] Open
Abstract
Osteoarthritis (OA) is a debilitating degenerative disease affecting multiple joint tissues, including cartilage, bone, synovium, and adipose tissues. OA presents diverse clinical phenotypes and distinct molecular endotypes, including inflammatory, metabolic, mechanical, genetic, and synovial variants. Consequently, innovative technologies are needed to support the development of effective diagnostic and precision therapeutic approaches. Traditional analysis of bulk OA tissue extracts has limitations due to technical constraints, causing challenges in the differentiation between various physiological and pathological phenotypes in joint tissues. This issue has led to standardization difficulties and hindered the success of clinical trials. Gaining insights into the spatial variations of the cellular and molecular structures in OA tissues, encompassing DNA, RNA, metabolites, and proteins, as well as their chemical properties, elemental composition, and mechanical attributes, can contribute to a more comprehensive understanding of the disease subtypes. Spatially resolved biology enables biologists to investigate cells within the context of their tissue microenvironment, providing a more holistic view of cellular function. Recent advances in innovative spatial biology techniques now allow intact tissue sections to be examined using various -omics lenses, such as genomics, transcriptomics, proteomics, and metabolomics, with spatial data. This fusion of approaches provides researchers with critical insights into the molecular composition and functions of the cells and tissues at precise spatial coordinates. Furthermore, advanced imaging techniques, including high-resolution microscopy, hyperspectral imaging, and mass spectrometry imaging, enable the visualization and analysis of the spatial distribution of biomolecules, cells, and tissues. Linking these molecular imaging outputs to conventional tissue histology can facilitate a more comprehensive characterization of disease phenotypes. This review summarizes the recent advancements in the molecular imaging modalities and methodologies for in-depth spatial analysis. It explores their applications, challenges, and potential opportunities in the field of OA. Additionally, this review provides a perspective on the potential research directions for these contemporary approaches that can meet the requirements of clinical diagnoses and the establishment of therapeutic targets for OA.
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Affiliation(s)
- Xiwei Fan
- Centre for Biomedical Technologies, Queensland University of Technology, Brisbane, QLD, Australia
- School of Mechanical, Medical & Process Engineering, Queensland University of Technology, Brisbane, QLD, Australia
| | - Antonia Rujia Sun
- Centre for Biomedical Technologies, Queensland University of Technology, Brisbane, QLD, Australia
- School of Mechanical, Medical & Process Engineering, Queensland University of Technology, Brisbane, QLD, Australia
| | - Reuben S E Young
- Central Analytical Research Facility, Queensland University of Technology, Brisbane, QLD, Australia
- Molecular Horizons, University of Wollongong, Wollongong, NSW, Australia
| | - Isaac O Afara
- Department of Technical Physics, University of Eastern Finland, Kuopio, Finland
- School of Electrical Engineering and Computer Science, Faculty of Engineering, Architecture and Information Technology, University of Queensland, Brisbane, QLD, Australia
| | - Brett R Hamilton
- Centre for Microscopy and Microanalysis, University of Queensland, Brisbane, QLD, Australia
| | - Louis Jun Ye Ong
- Centre for Biomedical Technologies, Queensland University of Technology, Brisbane, QLD, Australia
- School of Mechanical, Medical & Process Engineering, Queensland University of Technology, Brisbane, QLD, Australia
| | - Ross Crawford
- Centre for Biomedical Technologies, Queensland University of Technology, Brisbane, QLD, Australia
- The Prince Charles Hospital, Brisbane, QLD, Australia
| | - Indira Prasadam
- Centre for Biomedical Technologies, Queensland University of Technology, Brisbane, QLD, Australia.
- School of Mechanical, Medical & Process Engineering, Queensland University of Technology, Brisbane, QLD, Australia.
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2
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Föll MC, Volkmann V, Enderle-Ammour K, Timme S, Wilhelm K, Guo D, Vitek O, Bronsert P, Schilling O. Moving translational mass spectrometry imaging towards transparent and reproducible data analyses: a case study of an urothelial cancer cohort analyzed in the Galaxy framework. Clin Proteomics 2022; 19:8. [PMID: 35439943 PMCID: PMC9016955 DOI: 10.1186/s12014-022-09347-z] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2021] [Accepted: 04/04/2022] [Indexed: 11/24/2022] Open
Abstract
Background Mass spectrometry imaging (MSI) derives spatial molecular distribution maps directly from clinical tissue specimens and thus bears great potential for assisting pathologists with diagnostic decisions or personalized treatments. Unfortunately, progress in translational MSI is often hindered by insufficient quality control and lack of reproducible data analysis. Raw data and analysis scripts are rarely publicly shared. Here, we demonstrate the application of the Galaxy MSI tool set for the reproducible analysis of a urothelial carcinoma dataset. Methods Tryptic peptides were imaged in a cohort of 39 formalin-fixed, paraffin-embedded human urothelial cancer tissue cores with a MALDI-TOF/TOF device. The complete data analysis was performed in a fully transparent and reproducible manner on the European Galaxy Server. Annotations of tumor and stroma were performed by a pathologist and transferred to the MSI data to allow for supervised classifications of tumor vs. stroma tissue areas as well as for muscle-infiltrating and non-muscle infiltrating urothelial carcinomas. For putative peptide identifications, m/z features were matched to the MSiMass list. Results Rigorous quality control in combination with careful pre-processing enabled reduction of m/z shifts and intensity batch effects. High classification accuracy was found for both, tumor vs. stroma and muscle-infiltrating vs. non-muscle infiltrating urothelial tumors. Some of the most discriminative m/z features for each condition could be assigned a putative identity: stromal tissue was characterized by collagen peptides and tumor tissue by histone peptides. Immunohistochemistry confirmed an increased histone H2A abundance in the tumor compared to the stroma tissues. The muscle-infiltration status was distinguished via MSI by peptides from intermediate filaments such as cytokeratin 7 in non-muscle infiltrating carcinomas and vimentin in muscle-infiltrating urothelial carcinomas, which was confirmed by immunohistochemistry. To make the study fully reproducible and to advocate the criteria of FAIR (findability, accessibility, interoperability, and reusability) research data, we share the raw data, spectra annotations as well as all Galaxy histories and workflows. Data are available via ProteomeXchange with identifier PXD026459 and Galaxy results via https://github.com/foellmelanie/Bladder_MSI_Manuscript_Galaxy_links. Conclusion Here, we show that translational MSI data analysis in a fully transparent and reproducible manner is possible and we would like to encourage the community to join our efforts.
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Affiliation(s)
- Melanie Christine Föll
- Faculty of Medicine, Institute for Surgical Pathology, Medical Center - University of Freiburg, Breisacher Straße 115a, 79106, FreiburgFreiburg, Germany. .,Khoury College of Computer Sciences, Northeastern University, Boston, USA.
| | - Veronika Volkmann
- Faculty of Medicine, Institute for Surgical Pathology, Medical Center - University of Freiburg, Breisacher Straße 115a, 79106, FreiburgFreiburg, Germany
| | - Kathrin Enderle-Ammour
- Faculty of Medicine, Institute for Surgical Pathology, Medical Center - University of Freiburg, Breisacher Straße 115a, 79106, FreiburgFreiburg, Germany
| | - Sylvia Timme
- Faculty of Medicine, Institute for Surgical Pathology, Medical Center - University of Freiburg, Breisacher Straße 115a, 79106, FreiburgFreiburg, Germany.,Core Facility for Histopathology and Digital Pathology, Faculty of Medicine, Medical Center - University of Freiburg, 79106, Freiburg, Germany
| | - Konrad Wilhelm
- Department of Urology, Center for Surgery, Medical Center, Faculty of Medicine, University of Freiburg, Hugstetter Str. 55, 79106, Freiburg, Germany
| | - Dan Guo
- Khoury College of Computer Sciences, Northeastern University, Boston, USA
| | - Olga Vitek
- Khoury College of Computer Sciences, Northeastern University, Boston, USA
| | - Peter Bronsert
- Faculty of Medicine, Institute for Surgical Pathology, Medical Center - University of Freiburg, Breisacher Straße 115a, 79106, FreiburgFreiburg, Germany.,German Cancer Consortium (DKTK) and Cancer Research Center (DKFZ), Freiburg, Germany.,Tumorbank Comprehensive Cancer Center Freiburg, Freiburg, Germany
| | - Oliver Schilling
- Faculty of Medicine, Institute for Surgical Pathology, Medical Center - University of Freiburg, Breisacher Straße 115a, 79106, FreiburgFreiburg, Germany.,German Cancer Consortium (DKTK) and Cancer Research Center (DKFZ), Freiburg, Germany
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3
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Implementation of MALDI Mass Spectrometry Imaging in Cancer Proteomics Research: Applications and Challenges. J Pers Med 2020; 10:jpm10020054. [PMID: 32580362 PMCID: PMC7354689 DOI: 10.3390/jpm10020054] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2020] [Revised: 06/12/2020] [Accepted: 06/19/2020] [Indexed: 02/07/2023] Open
Abstract
Studying the proteome–the entire set of proteins in cells, tissues, organs and body fluids—is of great relevance in cancer research, as differential forms of proteins are expressed in response to specific intrinsic and extrinsic signals. Discovering protein signatures/pathways responsible for cancer transformation may lead to a better understanding of tumor biology and to a more effective diagnosis, prognosis, recurrence and response to therapy. Moreover, proteins can act as a biomarker or potential drug targets. Hence, it is of major importance to implement proteomic, particularly mass spectrometric, approaches in cancer research, to provide new crucial insights into tumor biology. Recently, mass spectrometry imaging (MSI) approaches were implemented in cancer research, to provide individual molecular characteristics of each individual tumor while retaining molecular spatial distribution, essential in the context of personalized disease management and medicine.
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4
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Matrix-assisted laser desorption/ionization mass spectrometry imaging to uncover protein alterations associated with the progression of IgA nephropathy. Virchows Arch 2019; 476:903-914. [PMID: 31838587 DOI: 10.1007/s00428-019-02705-7] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2019] [Revised: 09/27/2019] [Accepted: 10/22/2019] [Indexed: 02/07/2023]
Abstract
IgA nephropathy (IgAN) is one of the most diffuse glomerulonephrites worldwide, and many issues still remain regarding our understanding of its pathogenesis. The disease is diagnosed by renal biopsy examination, but potential pitfalls still persist with regard to discriminating its primary origin and, as a result, determining patient outcome remains challenging. In this pilot study, matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI) was performed on renal biopsies obtained from patients with IgAN (n = 11) and other mesangioproliferative glomerulonephrites (MesPGN, n = 6) in order to enlighten proteomic alterations that may be associated with the progression of IgAN. Differences in the proteomic profiles of IgAN and MesPGN tissue could clearly be detected using this approach and, furthermore, 14 signals (AUC ≥ 0.8) were observed to have an altered intensity among the different CKD stages within the IgAN group. In particular, large increases in the intensity of these signals could be observed at CKD stages II and above. These signals primarily corresponded to proteins involved in either inflammatory and healing pathways and their increased intensity was localized within regions of tissue with large amounts of inflammatory cells or sclerosis. Despite much work in recent years, our molecular understanding of IgAN progression remains incomplete. This pilot study represents a promising starting point in the search for novel protein markers that can assist clinicians in better understanding the pathogenesis of IgAN and highlighting those patients who may progress to end-stage renal disease.
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5
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Han J, Permentier H, Bischoff R, Groothuis G, Casini A, Horvatovich P. Imaging of protein distribution in tissues using mass spectrometry: An interdisciplinary challenge. Trends Analyt Chem 2019. [DOI: 10.1016/j.trac.2018.12.016] [Citation(s) in RCA: 22] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
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6
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Vaysse PM, Heeren RMA, Porta T, Balluff B. Mass spectrometry imaging for clinical research - latest developments, applications, and current limitations. Analyst 2018. [PMID: 28642940 DOI: 10.1039/c7an00565b] [Citation(s) in RCA: 136] [Impact Index Per Article: 22.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
Mass spectrometry is being used in many clinical research areas ranging from toxicology to personalized medicine. Of all the mass spectrometry techniques, mass spectrometry imaging (MSI), in particular, has continuously grown towards clinical acceptance. Significant technological and methodological improvements have contributed to enhance the performance of MSI recently, pushing the limits of throughput, spatial resolution, and sensitivity. This has stimulated the spread of MSI usage across various biomedical research areas such as oncology, neurological disorders, cardiology, and rheumatology, just to name a few. After highlighting the latest major developments and applications touching all aspects of translational research (i.e. from early pre-clinical to clinical research), we will discuss the present challenges in translational research performed with MSI: data management and analysis, molecular coverage and identification capabilities, and finally, reproducibility across multiple research centers, which is the largest remaining obstacle in moving MSI towards clinical routine.
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Affiliation(s)
- Pierre-Maxence Vaysse
- Maastricht MultiModal Molecular Imaging (M4I) institute, Division of Imaging Mass Spectrometry, Maastricht University, Universiteitssingel 50, 6229 ER, Maastricht, The Netherlands.
| | - Ron M A Heeren
- Maastricht MultiModal Molecular Imaging (M4I) institute, Division of Imaging Mass Spectrometry, Maastricht University, Universiteitssingel 50, 6229 ER, Maastricht, The Netherlands.
| | - Tiffany Porta
- Maastricht MultiModal Molecular Imaging (M4I) institute, Division of Imaging Mass Spectrometry, Maastricht University, Universiteitssingel 50, 6229 ER, Maastricht, The Netherlands.
| | - Benjamin Balluff
- Maastricht MultiModal Molecular Imaging (M4I) institute, Division of Imaging Mass Spectrometry, Maastricht University, Universiteitssingel 50, 6229 ER, Maastricht, The Netherlands.
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7
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Klein O, Strohschein K, Nebrich G, Fuchs M, Thiele H, Giavalisco P, Duda GN, Winkler T, Kobarg JH, Trede D, Geissler S. Unraveling local tissue changes within severely injured skeletal muscles in response to MSC-based intervention using MALDI Imaging mass spectrometry. Sci Rep 2018; 8:12677. [PMID: 30140012 PMCID: PMC6107672 DOI: 10.1038/s41598-018-30990-w] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2017] [Accepted: 08/09/2018] [Indexed: 12/11/2022] Open
Abstract
Pre-clinical and clinical studies are now beginning to demonstrate the high potential of cell therapies in enhancing muscle regeneration. We previously demonstrated functional benefit after the transplantation of autologous bone marrow mesenchymal stromal cells (MSC-TX) into a severe muscle crush trauma model. Despite our increasing understanding of the molecular and cellular mechanisms underlying MSC's regenerative function, little is known about the local molecular alterations and their spatial distribution within the tissue after MSC-TX. Here, we used MALDI imaging mass spectrometry (MALDI-IMS) in combination with multivariate statistical strategies to uncover previously unknown peptide alterations within severely injured skeletal muscles. Our analysis revealed that very early molecular alterations in response to MSC-TX occur largely in the region adjacent to the trauma and only to a small extent in the actual trauma region. Using "bottom up" mass spectrometry, we subsequently identified the proteins corresponding to the differentially expressed peptide intensity distributions in the specific muscle regions and used immunohistochemistry to validate our results. These findings extend our current understanding about the early molecular processes of muscle healing and highlights the critical role of trauma adjacent tissue during the early therapeutic response upon treatment with MSC.
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Affiliation(s)
- Oliver Klein
- Berlin-Brandenburg Center for Regenerative Therapies, Charité - Universitätsmedizin Berlin, Augustenburger Platz 1, 13353, Berlin, Germany.
| | - Kristin Strohschein
- Berlin-Brandenburg Center for Regenerative Therapies, Charité - Universitätsmedizin Berlin, Augustenburger Platz 1, 13353, Berlin, Germany
- Julius Wolff Institute & Center for Musculoskeletal Surgery, Charité - Universitätsmedizin Berlin, Augustenburger Platz 1, 13353, Berlin, Germany
| | - Grit Nebrich
- Julius Wolff Institute & Center for Musculoskeletal Surgery, Charité - Universitätsmedizin Berlin, Augustenburger Platz 1, 13353, Berlin, Germany
| | - Michael Fuchs
- Julius Wolff Institute & Center for Musculoskeletal Surgery, Charité - Universitätsmedizin Berlin, Augustenburger Platz 1, 13353, Berlin, Germany
| | - Herbert Thiele
- Fraunhofer - Inst. Medical Image Computing MEVIS, Maria-Goeppert-Straße 3, 23562, Lübeck, Germany
| | - Patrick Giavalisco
- Experimental Systems Biology Max-Planck-Institute of Molecular Plant Physiology, Am Mühlenberg, 14476, Golm, Germany
| | - Georg N Duda
- Berlin-Brandenburg Center for Regenerative Therapies, Charité - Universitätsmedizin Berlin, Augustenburger Platz 1, 13353, Berlin, Germany
- Julius Wolff Institute & Center for Musculoskeletal Surgery, Charité - Universitätsmedizin Berlin, Augustenburger Platz 1, 13353, Berlin, Germany
| | - Tobias Winkler
- Berlin-Brandenburg Center for Regenerative Therapies, Charité - Universitätsmedizin Berlin, Augustenburger Platz 1, 13353, Berlin, Germany
- Julius Wolff Institute & Center for Musculoskeletal Surgery, Charité - Universitätsmedizin Berlin, Augustenburger Platz 1, 13353, Berlin, Germany
| | - Jan Hendrik Kobarg
- SCiLS, Zweigniederlassung Bremen der Bruker Daltonik, Fahrenheitstr. 1, 28359, Bremen, Germany
| | - Dennis Trede
- SCiLS, Zweigniederlassung Bremen der Bruker Daltonik, Fahrenheitstr. 1, 28359, Bremen, Germany
| | - Sven Geissler
- Berlin-Brandenburg Center for Regenerative Therapies, Charité - Universitätsmedizin Berlin, Augustenburger Platz 1, 13353, Berlin, Germany
- Julius Wolff Institute & Center for Musculoskeletal Surgery, Charité - Universitätsmedizin Berlin, Augustenburger Platz 1, 13353, Berlin, Germany
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8
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Jaegger CF, Negrão F, Assis DM, Belaz KRA, Angolini CFF, Fernandes AMAP, Santos VG, Pimentel A, Abánades DR, Giorgio S, Eberlin MN, Rocha DFO. MALDI MS imaging investigation of the host response to visceral leishmaniasis. MOLECULAR BIOSYSTEMS 2018; 13:1946-1953. [PMID: 28758666 DOI: 10.1039/c7mb00306d] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/12/2023]
Abstract
Mass spectrometry imaging (MSI) of animal tissues has become an important tool for in situ molecular analyses and biomarker studies in several clinical areas, but there are few applications in parasitological studies. Leishmaniasis is a neglected tropical disease, and experimental mouse models have been essential to evaluate pathological and immunological processes and to develop diagnostic methods. Herein we have employed MALDI MSI to examine peptides and low molecular weight proteins (2 to 20 kDa) differentially expressed in the liver during visceral leishmaniasis in mice models. We analyzed liver sections of Balb/c mice infected with Leishmania infantum using the SCiLS Lab software for statistical analysis, which facilitated data interpretation and thus highlighted several key proteins and/or peptides. We proposed a decision tree classification for visceral leishmaniasis with distinct phases of the disease, which are named here as healthy, acute infection and chronic infection. Among others, the ion of m/z 4963 was the most important to identify acute infection and was tentatively identified as Thymosin β4. This peptide was previously established as a recovery factor in the human liver and might participate in the response of mice to Leishmania infection. This preliminary investigation shows the potential of MALDI MSI to complement classical compound selective imaging techniques and to explore new features not yet recognized by these approaches.
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Affiliation(s)
- C F Jaegger
- ThoMSon Mass Spectrometry Laboratory, University of Campinas - UNICAMP, Campinas, SP, Brazil.
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9
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Blomme A, Van Simaeys G, Doumont G, Costanza B, Bellier J, Otaka Y, Sherer F, Lovinfosse P, Boutry S, Palacios AP, De Pauw E, Hirano T, Yokobori T, Hustinx R, Bellahcène A, Delvenne P, Detry O, Goldman S, Nishiyama M, Castronovo V, Turtoi A. Murine stroma adopts a human-like metabolic phenotype in the PDX model of colorectal cancer and liver metastases. Oncogene 2017; 37:1237-1250. [PMID: 29242606 DOI: 10.1038/s41388-017-0018-x] [Citation(s) in RCA: 47] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2017] [Revised: 08/22/2017] [Accepted: 10/19/2017] [Indexed: 12/26/2022]
Abstract
Cancer research is increasingly dependent of patient-derived xenograft model (PDX). However, a major point of concern regarding the PDX model remains the replacement of the human stroma with murine counterpart. In the present work we aimed at clarifying the significance of the human-to-murine stromal replacement for the fidelity of colorectal cancer (CRC) and liver metastasis (CRC-LM) PDX model. We have conducted a comparative metabolic analysis between 6 patient tumors and corresponding PDX across 4 generations. Metabolic signatures of cancer cells and stroma were measured separately by MALDI-imaging, while metabolite changes in entire tumors were quantified using mass spectrometry approach. Measurement of glucose metabolism was also conducted in vivo using [18F]-fluorodeoxyglucose (FDG) and positron emission tomography (PET). In CRC/CRC-LM PDX model, human stroma was entirely replaced at the second generation. Despite this change, MALDI-imaging demonstrated that the metabolic profiles of both stromal and cancer cells remained stable for at least four generations in comparison to the original patient material. On the tumor level, profiles of 86 water-soluble metabolites as well as 93 lipid mediators underlined the functional stability of the PDX model. In vivo PET measurement of glucose uptake (reflecting tumor glucose metabolism) supported the ex vivo observations. Our data show for the first time that CRC/CRC-LM PDX model maintains the functional stability at the metabolic level despite the early replacement of the human stroma by murine cells. The findings demonstrate that human cancer cells actively educate murine stromal cells during PDX development to adopt the human-like phenotype.
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Affiliation(s)
- Arnaud Blomme
- Metastasis Research Laboratory, GIGA Cancer, University of Liège, Liège, Belgium
| | - Gaetan Van Simaeys
- Hôpital Erasme, Université Libre de Bruxelles, Brussels, Belgium.,Center for Microscopy and Molecular Imaging, Université Libre de Bruxelles, Charleroi (Gosselies), Brussels, Belgium
| | - Gilles Doumont
- Center for Microscopy and Molecular Imaging, Université Libre de Bruxelles, Charleroi (Gosselies), Brussels, Belgium
| | - Brunella Costanza
- Metastasis Research Laboratory, GIGA Cancer, University of Liège, Liège, Belgium
| | - Justine Bellier
- Metastasis Research Laboratory, GIGA Cancer, University of Liège, Liège, Belgium
| | - Yukihiro Otaka
- Department of Molecular Pharmacology and Oncology, Gunma University Graduate School of Medicine, Gunma, Japan
| | - Félicie Sherer
- Hôpital Erasme, Université Libre de Bruxelles, Brussels, Belgium.,Center for Microscopy and Molecular Imaging, Université Libre de Bruxelles, Charleroi (Gosselies), Brussels, Belgium
| | - Pierre Lovinfosse
- Nuclear Medicine and Oncological Imaging Division, Medical Physics Department, Liège University Hospital, Liège, Belgium
| | - Sébastien Boutry
- NMR and Molecular Imaging Laboratory, Department of General, Organic and Biomedical Chemistry, University of Mons, Mons, Belgium.,Center for Microscopy and Molecular Imaging, Université de Mons (UMONS), Charleroi (Gosselies), Belgium
| | - Ana Perez Palacios
- Metastasis Research Laboratory, GIGA Cancer, University of Liège, Liège, Belgium
| | - Edwin De Pauw
- Mass Spectrometry Laboratory, University of Liège, Liège, Belgium
| | - Touko Hirano
- Laboratory for Analytical Instruments, Gunma University Graduate School of Medicine, Gunma, Japan
| | - Takehiko Yokobori
- Department of Molecular Pharmacology and Oncology, Gunma University Graduate School of Medicine, Gunma, Japan
| | - Roland Hustinx
- Nuclear Medicine and Oncological Imaging Division, Medical Physics Department, Liège University Hospital, Liège, Belgium
| | - Akeila Bellahcène
- Metastasis Research Laboratory, GIGA Cancer, University of Liège, Liège, Belgium
| | - Philippe Delvenne
- Department of Pathology, University Hospital, University of Liège, Liège, Belgium
| | - Olivier Detry
- Department of Abdominal Surgery, University Hospital, University of Liège, Liège, Belgium
| | - Serge Goldman
- Hôpital Erasme, Université Libre de Bruxelles, Brussels, Belgium.,Center for Microscopy and Molecular Imaging, Université Libre de Bruxelles, Charleroi (Gosselies), Brussels, Belgium
| | - Masahiko Nishiyama
- Department of Molecular Pharmacology and Oncology, Gunma University Graduate School of Medicine, Gunma, Japan
| | - Vincent Castronovo
- Metastasis Research Laboratory, GIGA Cancer, University of Liège, Liège, Belgium
| | - Andrei Turtoi
- Metastasis Research Laboratory, GIGA Cancer, University of Liège, Liège, Belgium. .,Tumor Microenvironment and Resistance to Treatment Lab, Institut de Recherche en Cancérologie de Montpellier, Montpellier, France. .,Institut du Cancer, Montpellier, Montpellier, France. .,INSERM, U1194, Montpellier, France. .,Université, Montpellier, Montpellier, France.
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10
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Lou S, Balluff B, de Graaff MA, Cleven AHG, Briaire-de Bruijn I, Bovée JVMG, McDonnell LA. High-grade sarcoma diagnosis and prognosis: Biomarker discovery by mass spectrometry imaging. Proteomics 2017; 16:1802-13. [PMID: 27174013 DOI: 10.1002/pmic.201500514] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2015] [Revised: 05/04/2016] [Accepted: 05/09/2016] [Indexed: 12/24/2022]
Abstract
The combination of high heterogeneity, both intratumoral and intertumoral, with their rarity has made diagnosis, prognosis of high-grade sarcomas difficult. There is an urgent need for more objective molecular biomarkers, to differentiate between the many different subtypes, and to also provide new treatment targets. Mass spectrometry imaging (MSI) has amply demonstrated its ability to identify potential new markers for patient diagnosis, survival, metastasis and response to therapy in cancer research. In this study, we investigated the ability of MALDI-MSI of proteins to distinguish between high-grade osteosarcoma (OS), leiomyosarcoma (LMS), myxofibrosarcoma (MFS) and undifferentiated pleomorphic sarcoma (UPS) (Ntotal = 53). We also investigated if there are individual proteins or protein signatures that are statistically associated with patient survival. Twenty diagnostic protein signals were found characteristic for specific tumors (p ≤ 0.05), amongst them acyl-CoA-binding protein (m/z 11 162), macrophage migration inhibitory factor (m/z 12 350), thioredoxin (m/z 11 608) and galectin-1 (m/z 14 633) were assigned. Another nine protein signals were found to be associated with overall survival (p ≤ 0.05), including proteasome activator complex subunit 1 (m/z 9753), indicative for non-OS patients with poor survival; and two histone H4 variants (m/z 11 314 and 11 355), indicative of poor survival for LMS patients.
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Affiliation(s)
- Sha Lou
- Center for Proteomics and Metabolomics, Leiden University Medical Center, Leiden, The Netherlands
| | - Benjamin Balluff
- Center for Proteomics and Metabolomics, Leiden University Medical Center, Leiden, The Netherlands.,Maastricht MultiModal Molecular Imaging Institute, Maastricht University, Maastricht, The Netherlands
| | - Marieke A de Graaff
- Department of Pathology, Leiden University, Medical Center, Leiden, The Netherlands
| | - Arjen H G Cleven
- Department of Pathology, Leiden University, Medical Center, Leiden, The Netherlands
| | | | - Judith V M G Bovée
- Department of Pathology, Leiden University, Medical Center, Leiden, The Netherlands
| | - Liam A McDonnell
- Center for Proteomics and Metabolomics, Leiden University Medical Center, Leiden, The Netherlands.,Department of Pathology, Leiden University, Medical Center, Leiden, The Netherlands.,Fondazione Pisana per la Scienza ONLUS, Pisa, Italy
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11
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Dilillo M, Ait-Belkacem R, Esteve C, Pellegrini D, Nicolardi S, Costa M, Vannini E, Graaf ELD, Caleo M, McDonnell LA. Ultra-High Mass Resolution MALDI Imaging Mass Spectrometry of Proteins and Metabolites in a Mouse Model of Glioblastoma. Sci Rep 2017; 7:603. [PMID: 28377615 PMCID: PMC5429601 DOI: 10.1038/s41598-017-00703-w] [Citation(s) in RCA: 114] [Impact Index Per Article: 16.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2016] [Accepted: 03/08/2017] [Indexed: 01/27/2023] Open
Abstract
MALDI mass spectrometry imaging is able to simultaneously determine the spatial distribution of hundreds of molecules directly from tissue sections, without labeling and without prior knowledge. Ultra-high mass resolution measurements based on Fourier-transform mass spectrometry have been utilized to resolve isobaric lipids, metabolites and tryptic peptides. Here we demonstrate the potential of 15T MALDI-FTICR MSI for molecular pathology in a mouse model of high-grade glioma. The high mass accuracy and resolving power of high field FTICR MSI enabled tumor specific proteoforms, and tumor-specific proteins with overlapping and isobaric isotopic distributions to be clearly resolved. The protein ions detected by MALDI MSI were assigned to proteins identified by region-specific microproteomics (0.8 mm2 regions isolated using laser capture microdissection) on the basis of exact mass and isotopic distribution. These label free quantitative experiments also confirmed the protein expression changes observed by MALDI MSI and revealed changes in key metabolic proteins, which were supported by in-situ metabolite MALDI MSI.
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Affiliation(s)
- M Dilillo
- Fondazione Pisana per la Scienza ONLUS - Via Panfilo Castaldi 2, 56121, Pisa, Italy
- Department of Chemistry and Industrial Chemistry - Università di Pisa - Via Giuseppe Moruzzi 13, 56124, Pisa, Italy
| | - R Ait-Belkacem
- Fondazione Pisana per la Scienza ONLUS - Via Panfilo Castaldi 2, 56121, Pisa, Italy
| | - C Esteve
- Center for Proteomics and Metabolomics, Leiden University Medical Center, Leiden, The Netherlands
| | - D Pellegrini
- Fondazione Pisana per la Scienza ONLUS - Via Panfilo Castaldi 2, 56121, Pisa, Italy
- NEST, Istituto Nanoscienze-National Research Council, 56127, Pisa, Italy
| | - S Nicolardi
- Center for Proteomics and Metabolomics, Leiden University Medical Center, Leiden, The Netherlands
| | - M Costa
- CNR Neuroscience Institute, Via Moruzzi 1, 56124, Pisa, Italy
| | - E Vannini
- CNR Neuroscience Institute, Via Moruzzi 1, 56124, Pisa, Italy
| | - E L de Graaf
- Fondazione Pisana per la Scienza ONLUS - Via Panfilo Castaldi 2, 56121, Pisa, Italy
| | - M Caleo
- CNR Neuroscience Institute, Via Moruzzi 1, 56124, Pisa, Italy
| | - L A McDonnell
- Fondazione Pisana per la Scienza ONLUS - Via Panfilo Castaldi 2, 56121, Pisa, Italy.
- Center for Proteomics and Metabolomics, Leiden University Medical Center, Leiden, The Netherlands.
- Department of Pathology, Leiden University Medical Center, Leiden, The Netherlands.
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12
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Angel PM, Baldwin HS, Gottlieb Sen D, Su YR, Mayer JE, Bichell D, Drake RR. Advances in MALDI imaging mass spectrometry of proteins in cardiac tissue, including the heart valve. BIOCHIMICA ET BIOPHYSICA ACTA-PROTEINS AND PROTEOMICS 2017; 1865:927-935. [PMID: 28341601 DOI: 10.1016/j.bbapap.2017.03.009] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/14/2016] [Revised: 02/15/2017] [Accepted: 03/20/2017] [Indexed: 01/01/2023]
Abstract
Significant progress has been made for tissue imaging of proteins using matrix-assisted laser desorption ionization imaging mass spectrometry (MALDI IMS). These advancements now facilitate mapping of a wide range of proteins, peptides, and post-translational modifications in a wide variety of tissues; however, the use of MALDI IMS to detect proteins from cardiac tissue is limited. This review discusses the most recent advances in protein imaging and demonstrates application to cardiac tissue, including the heart valve. Protein imaging by MALDI IMS allows multiplexed histological mapping of proteins and protein components that are inaccessible by antibodies and should be considered an important tool for basic and clinical cardiovascular research. This article is part of a Special Issue entitled: MALDI Imaging, edited by Dr. Corinna Henkel and Prof. Peter Hoffmann.
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Affiliation(s)
- Peggi M Angel
- Department of Cell and Molecular Pharmacology & Experimental Therapeutics, Medical University of South Carolina, Charleston, USA; Medical University of South Carolina Proteomics Center, Medical University of South Carolina, Charleston, USA.
| | - H Scott Baldwin
- Department of Pediatrics and Cell Development and Biology, Vanderbilt University Medical Center, Nashville, TN, USA
| | | | - Yan Ru Su
- Department of Cardiovascular Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - John E Mayer
- Department of Cardiac Surgery, Boston Children's Hospital & Harvard Medical School, Boston, MA, USA
| | - David Bichell
- Division of Pediatric Cardiac Surgery, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Richard R Drake
- Department of Cell and Molecular Pharmacology & Experimental Therapeutics, Medical University of South Carolina, Charleston, USA; Medical University of South Carolina Proteomics Center, Medical University of South Carolina, Charleston, USA
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13
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Quanico J, Franck J, Wisztorski M, Salzet M, Fournier I. Integrated mass spectrometry imaging and omics workflows on the same tissue section using grid-aided, parafilm-assisted microdissection. Biochim Biophys Acta Gen Subj 2017; 1861:1702-1714. [PMID: 28300637 DOI: 10.1016/j.bbagen.2017.03.006] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/26/2016] [Revised: 03/08/2017] [Accepted: 03/10/2017] [Indexed: 01/03/2023]
Abstract
BACKGROUND In spite of the number of applications describing the use of MALDI MSI, one of its major drawbacks is the limited capability of identifying multiple compound classes directly on the same tissue section. METHODS We demonstrate the use of grid-aided, parafilm-assisted microdissection to perform MALDI MS imaging and shotgun proteomics and metabolomics in a combined workflow and using only a single tissue section. The grid is generated by microspotting acid dye 25 using a piezoelectric microspotter, and this grid was used as a guide to locate regions of interest and as an aid during manual microdissection. Subjecting the dissected pieces to the modified Folch method allows to separate the metabolites from proteins. The proteins can then be subjected to digestion under controlled conditions to improve protein identification yields. RESULTS The proof of concept experiment on rat brain generated 162 and 140 metabolite assignments from three ROIs (cerebellum, hippocampus and midbrain/hypothalamus) in positive and negative modes, respectively, and 890, 1303 and 1059 unique proteins. Integrated metabolite and protein overrepresentation analysis identified pathways associated with the biological functions of each ROI, most of which were not identified when looking at the protein and metabolite lists individually. CONCLUSIONS This combined MALDI MS imaging and multi-omics approach further extends the amount of information that can be generated from single tissue sections. GENERAL SIGNIFICANCE To the best of our knowledge, this is the first report combining both imaging and multi-omics analyses in the same workflow and on the same tissue section.
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Affiliation(s)
- Jusal Quanico
- Université de Lille 1, INSERM, U1192-Laboratoire Protéomique, Réponse Inflammatoire et Spectrométrie de Masse (PRISM), F-59000 Lille, France
| | - Julien Franck
- Université de Lille 1, INSERM, U1192-Laboratoire Protéomique, Réponse Inflammatoire et Spectrométrie de Masse (PRISM), F-59000 Lille, France
| | - Maxence Wisztorski
- Université de Lille 1, INSERM, U1192-Laboratoire Protéomique, Réponse Inflammatoire et Spectrométrie de Masse (PRISM), F-59000 Lille, France
| | - Michel Salzet
- Université de Lille 1, INSERM, U1192-Laboratoire Protéomique, Réponse Inflammatoire et Spectrométrie de Masse (PRISM), F-59000 Lille, France
| | - Isabelle Fournier
- Université de Lille 1, INSERM, U1192-Laboratoire Protéomique, Réponse Inflammatoire et Spectrométrie de Masse (PRISM), F-59000 Lille, France.
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14
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Casadonte R, Longuespée R, Kriegsmann J, Kriegsmann M. MALDI IMS and Cancer Tissue Microarrays. Adv Cancer Res 2017; 134:173-200. [PMID: 28110650 DOI: 10.1016/bs.acr.2016.11.007] [Citation(s) in RCA: 33] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
Matrix-assisted laser desorption/ionization imaging mass spectrometry (MALDI IMS) technology creates a link between the molecular assessment of numerous molecules and the morphological information about their special distribution. The application of MALDI IMS on formalin-fixed paraffin-embedded (FFPE) tissue microarrays (TMAs) is suitable for large-scale discovery analyses. Data acquired from FFPE TMA cancer samples in current research are very promising, and applications for routine diagnostics are under development. With the current rapid advances in both technology and applications, MALDI IMS technology is expected to enter into routine diagnostics soon. This chapter is intended to be comprehensive with respect to all aspects and considerations for the application of MALDI IMS on FFPE cancer TMAs with in-depth notes on technical aspects.
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Affiliation(s)
| | | | - J Kriegsmann
- Proteopath GmbH, Trier, Germany; Institute of Molecular Pathology, Trier, Germany; Center for Histology, Cytology and Molecular Diagnostics, Trier, Germany
| | - M Kriegsmann
- Institute of Pathology, University of Heidelberg, Heidelberg, Germany.
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15
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Quanico J, Franck J, Wisztorski M, Salzet M, Fournier I. Progress and Potential of Imaging Mass Spectrometry Applied to Biomarker Discovery. Methods Mol Biol 2017; 1598:21-43. [PMID: 28508356 DOI: 10.1007/978-1-4939-6952-4_2] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/07/2023]
Abstract
Mapping provides a direct means to assess the impact of protein biomarkers and puts into context their relevance in the type of cancer being examined. To this end, mass spectrometry imaging (MSI) was developed to provide the needed spatial information which is missing in traditional liquid-based mass spectrometric proteomics approaches. Aptly described as a "molecular histology" technique, MSI gives an additional dimension in characterizing tumor biopsies, allowing for mapping of hundreds of molecules in a single analysis. A decade of developments focused on improving and standardizing MSI so that the technique can be translated into the clinical setting. This review describes the progress made in addressing the technological development that allows to bridge local protein detection by MSI to its identification and to illustrate its potential in studying various aspects of cancer biomarker discovery.
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Affiliation(s)
- Jusal Quanico
- Université de Lille 1, INSERM, U1192-Laboratoire Protéomique, Réponse Inflammatoire et Spectrométrie de Masse (PRISM), 59000, Lille, France
| | - Julien Franck
- Université de Lille 1, INSERM, U1192-Laboratoire Protéomique, Réponse Inflammatoire et Spectrométrie de Masse (PRISM), 59000, Lille, France
| | - Maxence Wisztorski
- Université de Lille 1, INSERM, U1192-Laboratoire Protéomique, Réponse Inflammatoire et Spectrométrie de Masse (PRISM), 59000, Lille, France
| | - Michel Salzet
- Université de Lille 1, INSERM, U1192-Laboratoire Protéomique, Réponse Inflammatoire et Spectrométrie de Masse (PRISM), 59000, Lille, France
| | - Isabelle Fournier
- Université de Lille 1, INSERM, U1192-Laboratoire Protéomique, Réponse Inflammatoire et Spectrométrie de Masse (PRISM), 59000, Lille, France.
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16
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Rocha B, Ruiz-Romero C, Blanco FJ. Mass spectrometry imaging: a novel technology in rheumatology. Nat Rev Rheumatol 2016; 13:52-63. [DOI: 10.1038/nrrheum.2016.184] [Citation(s) in RCA: 38] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/15/2023]
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17
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Apparicio M, Santos VG, Rocha D, Ferreira CR, Macente BI, Magalhães GM, Alves AE, Motheo TF, Padilha-Nakaghi LC, Pires-Buttler EA, Luvoni GC, Eberlin MN, Vicente W. Matrix-assisted laser desorption/ionization imaging mass spectrometry for the spatial location of feline oviductal proteins. Reprod Domest Anim 2016; 52 Suppl 2:88-92. [PMID: 27807892 DOI: 10.1111/rda.12842] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/04/2023]
Abstract
With the purpose of identifying factors involved in early stages of embryo development in the domestic cat, matrix-assisted laser desorption/ionization imaging mass spectrometry (MALDI-IMS) was used for the first time to describe the spatial localization of proteins in the oviducts of queens. Oviducts were obtained from two 2 and 4 years old cross-bred queens, divided into three segments, snap-frozen in liquid nitrogen and then stored at -80°C until use. Next, they were sectioned in a cryostat, fixed on ITO (indium tin oxide) conductive glass slides for MALDI-IMS and serial sections were collected on microscope slides for histology. As confirmed by histology, MALDI-IMS was able to show contrasting protein distributions in the oviductal infundibulum, ampulla and isthmus. Mass spectra were characterized by abundant ions of m/z 1,259, 4,939, 4,960 and 10,626, which have been tentatively attributed to keratin, thymosin β10, thymosin β4 and S100, respectively. Keratin and thymosins are involved in the biological response to tissue damage. S100 proteins are calcium-modulated proteins implicated in a variety of cellular activities, including cell differentiation and regulation of cell motility. These results suggest that protein composition differs between segments of the cat oviduct, which corresponds to morphological changes within these sections. Further functional studies could elucidate the effects of these proteins on feline reproductive physiology.
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Affiliation(s)
- M Apparicio
- Programa de Mestrado em Ciência Animal, Universidade de Franca, UNIFRAN, Franca/SP, Brazil
| | - V G Santos
- Thomson Mass Spectrometry Laboratory, Institute of Chemistry, University of Campinas, UNICAMP, Campinas/SP, Brazil
| | - Dfo Rocha
- Thomson Mass Spectrometry Laboratory, Institute of Chemistry, University of Campinas, UNICAMP, Campinas/SP, Brazil
| | - C R Ferreira
- Thomson Mass Spectrometry Laboratory, Institute of Chemistry, University of Campinas, UNICAMP, Campinas/SP, Brazil
| | - B I Macente
- Departamento de Medicina Veterinária Preventiva e Reprodução Animal, UNESP, Jaboticabal/SP, Brazil
| | - G M Magalhães
- Programa de Mestrado em Ciência Animal, Universidade de Franca, UNIFRAN, Franca/SP, Brazil
| | - A E Alves
- Departamento de Medicina Veterinária Preventiva e Reprodução Animal, UNESP, Jaboticabal/SP, Brazil
| | - T F Motheo
- Departamento de Medicina Veterinária Preventiva e Reprodução Animal, UNESP, Jaboticabal/SP, Brazil
| | - L C Padilha-Nakaghi
- Departamento de Medicina Veterinária Preventiva e Reprodução Animal, UNESP, Jaboticabal/SP, Brazil
| | - E A Pires-Buttler
- Departamento de Medicina Veterinária Preventiva e Reprodução Animal, UNESP, Jaboticabal/SP, Brazil
| | - G C Luvoni
- Dipartimento di Scienze Veterinarie per la Salute, la Produzione Animale e la Sicurezza Alimentare, Università degli Studi di Milano, Milan, Italy
| | - M N Eberlin
- Thomson Mass Spectrometry Laboratory, Institute of Chemistry, University of Campinas, UNICAMP, Campinas/SP, Brazil
| | - Wrr Vicente
- Departamento de Medicina Veterinária Preventiva e Reprodução Animal, UNESP, Jaboticabal/SP, Brazil
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18
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Schwamborn K, Kriegsmann M, Weichert W. MALDI imaging mass spectrometry - From bench to bedside. BIOCHIMICA ET BIOPHYSICA ACTA-PROTEINS AND PROTEOMICS 2016; 1865:776-783. [PMID: 27810414 DOI: 10.1016/j.bbapap.2016.10.014] [Citation(s) in RCA: 47] [Impact Index Per Article: 5.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/07/2016] [Revised: 10/24/2016] [Accepted: 10/28/2016] [Indexed: 10/20/2022]
Abstract
Today, pathologists face many challenges in defining the precise morphomolecular diagnosis and in guiding clinicians to the optimal patients' treatment. To achieve this goal, increasingly, classical histomorphological methods have to be supplemented by high throughput molecular assays. Since MALDI imaging mass spectrometry (IMS) enables the assessment of spatial molecular arrangements in tissue sections, it goes far beyond microscopy in providing hundreds of different molecular images from a single scan without the need of target-specific reagents. Thus, this technology has the potential to uncover new markers for diagnostic purposes or markers that correlate with disease severity as well as prognosis and therapeutic response. Additionally, in the future MALDI IMS based classifiers measured with this technology in real time in the diagnostic setting might be applicable in the routine diagnostic setting. In this review, recently published studies that show the usefulness, advantages, and applicability of MALDI IMS in different fields of pathology (diagnosis, prognosis and treatment response) are highlighted. This article is part of a Special Issue entitled: MALDI Imaging, edited by Dr. Corinna Henkel and Prof. Peter Hoffmann.
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Affiliation(s)
- Kristina Schwamborn
- Institute of Pathology, Technische Universität München (TUM), Munich, Germany.
| | - Mark Kriegsmann
- University of Heidelberg, Department of Pathology, Heidelberg, Germany
| | - Wilko Weichert
- Institute of Pathology, Technische Universität München (TUM), Munich, Germany
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19
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A Proof of Concept to Bridge the Gap between Mass Spectrometry Imaging, Protein Identification and Relative Quantitation: MSI~LC-MS/MS-LF. Proteomes 2016; 4:proteomes4040032. [PMID: 28248242 PMCID: PMC5260965 DOI: 10.3390/proteomes4040032] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2016] [Revised: 10/04/2016] [Accepted: 10/17/2016] [Indexed: 01/08/2023] Open
Abstract
Mass spectrometry imaging (MSI) is a powerful tool to visualize the spatial distribution of molecules on a tissue section. The main limitation of MALDI-MSI of proteins is the lack of direct identification. Therefore, this study focuses on a MSI~LC-MS/MS-LF workflow to link the results from MALDI-MSI with potential peak identification and label-free quantitation, using only one tissue section. At first, we studied the impact of matrix deposition and laser ablation on protein extraction from the tissue section. Then, we did a back-correlation of the m/z of the proteins detected by MALDI-MSI to those identified by label-free quantitation. This allowed us to compare the label-free quantitation of proteins obtained in LC-MS/MS with the peak intensities observed in MALDI-MSI. We managed to link identification to nine peaks observed by MALDI-MSI. The results showed that the MSI~LC-MS/MS-LF workflow (i) allowed us to study a representative muscle proteome compared to a classical bottom-up workflow; and (ii) was sparsely impacted by matrix deposition and laser ablation. This workflow, performed as a proof-of-concept, suggests that a single tissue section can be used to perform MALDI-MSI and protein extraction, identification, and relative quantitation.
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20
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Rocha B, Cillero-Pastor B, Blanco FJ, Ruiz-Romero C. MALDI mass spectrometry imaging in rheumatic diseases. BIOCHIMICA ET BIOPHYSICA ACTA-PROTEINS AND PROTEOMICS 2016; 1865:784-794. [PMID: 27742553 DOI: 10.1016/j.bbapap.2016.10.004] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/02/2016] [Revised: 09/29/2016] [Accepted: 10/04/2016] [Indexed: 01/15/2023]
Abstract
Mass spectrometry imaging (MSI) is a technique used to visualize the spatial distribution of biomolecules such as peptides, proteins, lipids or other organic compounds by their molecular masses. Among the different MSI strategies, MALDI-MSI provides a sensitive and label-free approach for imaging of a wide variety of protein or peptide biomarkers from the surface of tissue sections, being currently used in an increasing number of biomedical applications such as biomarker discovery and tissue classification. In the field of rheumatology, MALDI-MSI has been applied to date for the analysis of joint tissues such as synovial membrane or cartilage. This review summarizes the studies and key achievements obtained using MALDI-MSI to increase understanding on rheumatic pathologies and to describe potential diagnostic or prognostic biomarkers of these diseases. This article is part of a Special Issue entitled: MALDI Imaging, edited by Dr. Corinna Henkel and Prof. Peter Hoffmann.
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Affiliation(s)
- Beatriz Rocha
- Proteomics Unit-ProteoRed/ISCIII, Rheumatology Group, INIBIC - Hospital Universitario de A Coruña, SERGAS, A Coruña, Spain
| | | | - Francisco J Blanco
- Proteomics Unit-ProteoRed/ISCIII, Rheumatology Group, INIBIC - Hospital Universitario de A Coruña, SERGAS, A Coruña, Spain; RIER-RED de Inflamación y Enfermedades Reumáticas, INIBIC-CHUAC, A Coruña, Spain.
| | - Cristina Ruiz-Romero
- Proteomics Unit-ProteoRed/ISCIII, Rheumatology Group, INIBIC - Hospital Universitario de A Coruña, SERGAS, A Coruña, Spain; CIBER-BBN Instituto de Salud Carlos III, INIBIC-CHUAC, A Coruña, Spain.
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21
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An experimental guideline for the analysis of histologically heterogeneous tumors by MALDI-TOF mass spectrometry imaging. BIOCHIMICA ET BIOPHYSICA ACTA-PROTEINS AND PROTEOMICS 2016; 1865:957-966. [PMID: 27725306 DOI: 10.1016/j.bbapap.2016.09.020] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/08/2016] [Revised: 08/26/2016] [Accepted: 09/30/2016] [Indexed: 12/11/2022]
Abstract
Mass spectrometry imaging (MSI) has been widely used for the direct molecular assessment of tissue samples and has demonstrated great potential to complement current histopathological methods in cancer research. It is now well established that tissue preparation is key to a successful MSI experiment; for histologically heterogeneous tumor tissues, other parts of the workflow are equally important to the experiment's success. To demonstrate these facets here we describe a matrix-assisted laser desorption/ionization MSI biomarker discovery investigation of high-grade, complex karyotype sarcomas, which often have histological overlap and moderate response to chemo-/radio-therapy. Multiple aspects of the workflow had to be optimized, ranging from the tissue preparation and data acquisition protocols, to the post-MSI histological staining method, data quality control, histology-defined data selection, data processing and statistical analysis. Only as a result of developing every step of the biomarker discovery workflow was it possible to identify a panel of protein signatures that could distinguish between different subtypes of sarcomas or could predict patient survival outcome. This article is part of a Special Issue entitled: MALDI Imaging, edited by Dr. Corinna Henkel and Prof. Peter Hoffmann.
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22
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Spraggins JM, Rizzo DG, Moore JL, Noto MJ, Skaar EP, Caprioli RM. Next-generation technologies for spatial proteomics: Integrating ultra-high speed MALDI-TOF and high mass resolution MALDI FTICR imaging mass spectrometry for protein analysis. Proteomics 2016; 16:1678-89. [PMID: 27060368 DOI: 10.1002/pmic.201600003] [Citation(s) in RCA: 105] [Impact Index Per Article: 13.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2016] [Revised: 03/02/2016] [Accepted: 03/31/2016] [Indexed: 12/23/2022]
Abstract
MALDI imaging mass spectrometry is a powerful analytical tool enabling the visualization of biomolecules in tissue. However, there are unique challenges associated with protein imaging experiments including the need for higher spatial resolution capabilities, improved image acquisition rates, and better molecular specificity. Here we demonstrate the capabilities of ultra-high speed MALDI-TOF and high mass resolution MALDI FTICR IMS platforms as they relate to these challenges. High spatial resolution MALDI-TOF protein images of rat brain tissue and cystic fibrosis lung tissue were acquired at image acquisition rates >25 pixels/s. Structures as small as 50 μm were spatially resolved and proteins associated with host immune response were observed in cystic fibrosis lung tissue. Ultra-high speed MALDI-TOF enables unique applications including megapixel molecular imaging as demonstrated for lipid analysis of cystic fibrosis lung tissue. Additionally, imaging experiments using MALDI FTICR IMS were shown to produce data with high mass accuracy (<5 ppm) and resolving power (∼75 000 at m/z 5000) for proteins up to ∼20 kDa. Analysis of clear cell renal cell carcinoma using MALDI FTICR IMS identified specific proteins localized to healthy tissue regions, within the tumor, and also in areas of increased vascularization around the tumor.
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Affiliation(s)
- Jeffrey M Spraggins
- Department of Biochemistry, Vanderbilt University School of Medicine, Nashville, TN, USA.,Mass Spectrometry Research Center, Vanderbilt University School of Medicine, Nashville, TN, USA.,Department of Chemistry, Vanderbilt University, Nashville, TN, USA
| | - David G Rizzo
- Mass Spectrometry Research Center, Vanderbilt University School of Medicine, Nashville, TN, USA.,Department of Chemistry, Vanderbilt University, Nashville, TN, USA
| | - Jessica L Moore
- Mass Spectrometry Research Center, Vanderbilt University School of Medicine, Nashville, TN, USA.,Department of Chemistry, Vanderbilt University, Nashville, TN, USA
| | - Michael J Noto
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Eric P Skaar
- Department of Pathology, Microbiology and Immunology, Vanderbilt University School of Medicine, Nashville, TN, USA.,United States (U.S.) Department of Veterans Affairs, Tennessee Valley Healthcare System, Nashville, TN, USA
| | - Richard M Caprioli
- Department of Biochemistry, Vanderbilt University School of Medicine, Nashville, TN, USA.,Mass Spectrometry Research Center, Vanderbilt University School of Medicine, Nashville, TN, USA.,Department of Chemistry, Vanderbilt University, Nashville, TN, USA.,Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA.,Departments of Pharmacology and Medicine, Vanderbilt University School of Medicine, Nashville, TN, USA
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23
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Donnarumma F, Cao F, Murray KK. Laser Ablation with Vacuum Capture for MALDI Mass Spectrometry of Tissue. JOURNAL OF THE AMERICAN SOCIETY FOR MASS SPECTROMETRY 2016; 27:108-116. [PMID: 26374229 DOI: 10.1007/s13361-015-1249-0] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/22/2015] [Revised: 08/04/2015] [Accepted: 08/08/2015] [Indexed: 06/05/2023]
Abstract
We have developed a laser ablation sampling technique for matrix-assisted laser desorption ionization (MALDI) mass spectrometry and tandem mass spectrometry (MS/MS) analyses of in-situ digested tissue proteins. Infrared laser ablation was used to remove biomolecules from tissue sections for collection by vacuum capture and analysis by MALDI. Ablation and transfer of compounds from tissue removes biomolecules from the tissue and allows further analysis of the collected material to facilitate their identification. Laser ablated material was captured in a vacuum aspirated pipette-tip packed with C18 stationary phase and the captured material was dissolved, eluted, and analyzed by MALDI. Rat brain and lung tissue sections 10 μm thick were processed by in-situ trypsin digestion after lipid and salt removal. The tryptic peptides were ablated with a focused mid-infrared laser, vacuum captured, and eluted with an acetonitrile/water mixture. Eluted components were deposited on a MALDI target and mixed with matrix for mass spectrometry analysis. Initial experiments were conducted with peptide and protein standards for evaluation of transfer efficiency: a transfer efficiency of 16% was obtained using seven different standards. Laser ablation vacuum capture was applied to freshly digested tissue sections and compared with sections processed with conventional MALDI imaging. A greater signal intensity and lower background was observed in comparison with the conventional MALDI analysis. Tandem time-of-flight MALDI mass spectrometry was used for compound identification in the tissue.
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Affiliation(s)
- Fabrizio Donnarumma
- Department of Chemistry, Louisiana State University, Baton Rouge, LA, 70803, USA
| | - Fan Cao
- Department of Chemistry, Louisiana State University, Baton Rouge, LA, 70803, USA
| | - Kermit K Murray
- Department of Chemistry, Louisiana State University, Baton Rouge, LA, 70803, USA.
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24
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Tikka S, Monogioudi E, Gotsopoulos A, Soliymani R, Pezzini F, Scifo E, Uusi-Rauva K, Tyynelä J, Baumann M, Jalanko A, Simonati A, Lalowski M. Proteomic Profiling in the Brain of CLN1 Disease Model Reveals Affected Functional Modules. Neuromolecular Med 2015; 18:109-33. [PMID: 26707855 DOI: 10.1007/s12017-015-8382-6] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2015] [Accepted: 12/15/2015] [Indexed: 02/06/2023]
Abstract
Neuronal ceroid lipofuscinoses (NCL) are the most commonly inherited progressive encephalopathies of childhood. Pathologically, they are characterized by endolysosomal storage with different ultrastructural features and biochemical compositions. The molecular mechanisms causing progressive neurodegeneration and common molecular pathways linking expression of different NCL genes are largely unknown. We analyzed proteome alterations in the brains of a mouse model of human infantile CLN1 disease-palmitoyl-protein thioesterase 1 (Ppt1) gene knockout and its wild-type age-matched counterpart at different stages: pre-symptomatic, symptomatic and advanced. For this purpose, we utilized a combination of laser capture microdissection-based quantitative liquid chromatography tandem mass spectrometry (MS) and matrix-assisted laser desorption/ionization time-of-flight MS imaging to quantify/visualize the changes in protein expression in disease-affected brain thalamus and cerebral cortex tissue slices, respectively. Proteomic profiling of the pre-symptomatic stage thalamus revealed alterations mostly in metabolic processes and inhibition of various neuronal functions, i.e., neuritogenesis. Down-regulation in dynamics associated with growth of plasma projections and cellular protrusions was further corroborated by findings from RNA sequencing of CLN1 patients' fibroblasts. Changes detected at the symptomatic stage included: mitochondrial functions, synaptic vesicle transport, myelin proteome and signaling cascades, such as RhoA signaling. Considerable dysregulation of processes related to mitochondrial cell death, RhoA/Huntington's disease signaling and myelin sheath breakdown were observed at the advanced stage of the disease. The identified changes in protein levels were further substantiated by bioinformatics and network approaches, immunohistochemistry on brain tissues and literature knowledge, thus identifying various functional modules affected in the CLN1 childhood encephalopathy.
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Affiliation(s)
- Saara Tikka
- Medicum, Biochemistry/Developmental Biology, Meilahti Clinical Proteomics Core Facility, University of Helsinki, P.O. Box 63 (Haartmaninkatu 8), Room C214a, 00014, Helsinki, Finland.,Folkhälsan Institute of Genetics, 00014, Helsinki, Finland
| | - Evanthia Monogioudi
- Folkhälsan Institute of Genetics, 00014, Helsinki, Finland.,Joint Research Centre, Directorate D-Institute for Reference Materials and Measurements, Standards for Innovation and Sustainable Development, Geel, Belgium
| | - Athanasios Gotsopoulos
- Brain and Mind Laboratory, Department of Biomedical Engineering and Computational Science (BECS), Aalto University School of Science, 02150, Espoo, Finland
| | - Rabah Soliymani
- Medicum, Biochemistry/Developmental Biology, Meilahti Clinical Proteomics Core Facility, University of Helsinki, P.O. Box 63 (Haartmaninkatu 8), Room C214a, 00014, Helsinki, Finland
| | - Francesco Pezzini
- Department of Neurological and Movement Sciences, University of Verona, 37134, Verona, Italy
| | - Enzo Scifo
- Medicum, Biochemistry/Developmental Biology, Meilahti Clinical Proteomics Core Facility, University of Helsinki, P.O. Box 63 (Haartmaninkatu 8), Room C214a, 00014, Helsinki, Finland.,Doctoral Program Brain & Mind, University of Helsinki, Helsinki, Finland.,Campbell Family Mental Health Research Institute, CAMH, University of Toronto, Toronto, Canada
| | - Kristiina Uusi-Rauva
- Folkhälsan Institute of Genetics, 00014, Helsinki, Finland.,Genomics and Biomarkers, National Institute for Health and Welfare (THL), P.O. Box 30, 00271, Helsinki, Finland
| | - Jaana Tyynelä
- Medicum, Biochemistry/Developmental Biology, Meilahti Clinical Proteomics Core Facility, University of Helsinki, P.O. Box 63 (Haartmaninkatu 8), Room C214a, 00014, Helsinki, Finland
| | - Marc Baumann
- Medicum, Biochemistry/Developmental Biology, Meilahti Clinical Proteomics Core Facility, University of Helsinki, P.O. Box 63 (Haartmaninkatu 8), Room C214a, 00014, Helsinki, Finland
| | - Anu Jalanko
- Institute for Molecular Medicine (FIMM), University of Helsinki, 00014, Helsinki, Finland.,Genomics and Biomarkers, National Institute for Health and Welfare (THL), P.O. Box 30, 00271, Helsinki, Finland
| | - Alessandro Simonati
- Department of Neurological and Movement Sciences, University of Verona, 37134, Verona, Italy
| | - Maciej Lalowski
- Medicum, Biochemistry/Developmental Biology, Meilahti Clinical Proteomics Core Facility, University of Helsinki, P.O. Box 63 (Haartmaninkatu 8), Room C214a, 00014, Helsinki, Finland. .,Folkhälsan Institute of Genetics, 00014, Helsinki, Finland.
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25
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Palmer A, Ovchinnikova E, Thuné M, Lavigne R, Guével B, Dyatlov A, Vitek O, Pineau C, Borén M, Alexandrov T. Using collective expert judgements to evaluate quality measures of mass spectrometry images. Bioinformatics 2015; 31:i375-84. [PMID: 26072506 PMCID: PMC4765867 DOI: 10.1093/bioinformatics/btv266] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023] Open
Abstract
Motivation: Imaging mass spectrometry (IMS) is a maturating technique of molecular imaging. Confidence in the reproducible quality of IMS data is essential for its integration into routine use. However, the predominant method for assessing quality is visual examination, a time consuming, unstandardized and non-scalable approach. So far, the problem of assessing the quality has only been marginally addressed and existing measures do not account for the spatial information of IMS data. Importantly, no approach exists for unbiased evaluation of potential quality measures. Results: We propose a novel approach for evaluating potential measures by creating a gold-standard set using collective expert judgements upon which we evaluated image-based measures. To produce a gold standard, we engaged 80 IMS experts, each to rate the relative quality between 52 pairs of ion images from MALDI-TOF IMS datasets of rat brain coronal sections. Experts’ optional feedback on their expertise, the task and the survey showed that (i) they had diverse backgrounds and sufficient expertise, (ii) the task was properly understood, and (iii) the survey was comprehensible. A moderate inter-rater agreement was achieved with Krippendorff’s alpha of 0.5. A gold-standard set of 634 pairs of images with accompanying ratings was constructed and showed a high agreement of 0.85. Eight families of potential measures with a range of parameters and statistical descriptors, giving 143 in total, were evaluated. Both signal-to-noise and spatial chaos-based measures performed highly with a correlation of 0.7 to 0.9 with the gold standard ratings. Moreover, we showed that a composite measure with the linear coefficients (trained on the gold standard with regularized least squares optimization and lasso) showed a strong linear correlation of 0.94 and an accuracy of 0.98 in predicting which image in a pair was of higher quality. Availability and implementation: The anonymized data collected from the survey and the Matlab source code for data processing can be found at: https://github.com/alexandrovteam/IMS_quality. Contact:theodore.alexandrov@embl.de
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Affiliation(s)
- Andrew Palmer
- European Molecular Biology Laboratory, Heidelberg, Germany, Center for Industrial Mathematics, University of Bremen, Bremen, Germany, High Performance Humanoid Technologies Lab, Institute for Anthropomatics, Karlsruhe Institute of Technology, Karlsruhe, Germany, Denator, Uppsala, Sweden, Protim, Inserm U1085 - Irset, University of Rennes 1, Rennes, France, SCiLS GmbH, Bremen, Germany, College of Computer and Information Science, Northeastern University, Boston, MA, USA and Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, CA, USA European Molecular Biology Laboratory, Heidelberg, Germany, Center for Industrial Mathematics, University of Bremen, Bremen, Germany, High Performance Humanoid Technologies Lab, Institute for Anthropomatics, Karlsruhe Institute of Technology, Karlsruhe, Germany, Denator, Uppsala, Sweden, Protim, Inserm U1085 - Irset, University of Rennes 1, Rennes, France, SCiLS GmbH, Bremen, Germany, College of Computer and Information Science, Northeastern University, Boston, MA, USA and Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, CA, USA
| | - Ekaterina Ovchinnikova
- European Molecular Biology Laboratory, Heidelberg, Germany, Center for Industrial Mathematics, University of Bremen, Bremen, Germany, High Performance Humanoid Technologies Lab, Institute for Anthropomatics, Karlsruhe Institute of Technology, Karlsruhe, Germany, Denator, Uppsala, Sweden, Protim, Inserm U1085 - Irset, University of Rennes 1, Rennes, France, SCiLS GmbH, Bremen, Germany, College of Computer and Information Science, Northeastern University, Boston, MA, USA and Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, CA, USA European Molecular Biology Laboratory, Heidelberg, Germany, Center for Industrial Mathematics, University of Bremen, Bremen, Germany, High Performance Humanoid Technologies Lab, Institute for Anthropomatics, Karlsruhe Institute of Technology, Karlsruhe, Germany, Denator, Uppsala, Sweden, Protim, Inserm U1085 - Irset, University of Rennes 1, Rennes, France, SCiLS GmbH, Bremen, Germany, College of Computer and Information Science, Northeastern University, Boston, MA, USA and Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, CA, USA
| | - Mikael Thuné
- European Molecular Biology Laboratory, Heidelberg, Germany, Center for Industrial Mathematics, University of Bremen, Bremen, Germany, High Performance Humanoid Technologies Lab, Institute for Anthropomatics, Karlsruhe Institute of Technology, Karlsruhe, Germany, Denator, Uppsala, Sweden, Protim, Inserm U1085 - Irset, University of Rennes 1, Rennes, France, SCiLS GmbH, Bremen, Germany, College of Computer and Information Science, Northeastern University, Boston, MA, USA and Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, CA, USA
| | - Régis Lavigne
- European Molecular Biology Laboratory, Heidelberg, Germany, Center for Industrial Mathematics, University of Bremen, Bremen, Germany, High Performance Humanoid Technologies Lab, Institute for Anthropomatics, Karlsruhe Institute of Technology, Karlsruhe, Germany, Denator, Uppsala, Sweden, Protim, Inserm U1085 - Irset, University of Rennes 1, Rennes, France, SCiLS GmbH, Bremen, Germany, College of Computer and Information Science, Northeastern University, Boston, MA, USA and Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, CA, USA
| | - Blandine Guével
- European Molecular Biology Laboratory, Heidelberg, Germany, Center for Industrial Mathematics, University of Bremen, Bremen, Germany, High Performance Humanoid Technologies Lab, Institute for Anthropomatics, Karlsruhe Institute of Technology, Karlsruhe, Germany, Denator, Uppsala, Sweden, Protim, Inserm U1085 - Irset, University of Rennes 1, Rennes, France, SCiLS GmbH, Bremen, Germany, College of Computer and Information Science, Northeastern University, Boston, MA, USA and Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, CA, USA
| | - Andrey Dyatlov
- European Molecular Biology Laboratory, Heidelberg, Germany, Center for Industrial Mathematics, University of Bremen, Bremen, Germany, High Performance Humanoid Technologies Lab, Institute for Anthropomatics, Karlsruhe Institute of Technology, Karlsruhe, Germany, Denator, Uppsala, Sweden, Protim, Inserm U1085 - Irset, University of Rennes 1, Rennes, France, SCiLS GmbH, Bremen, Germany, College of Computer and Information Science, Northeastern University, Boston, MA, USA and Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, CA, USA European Molecular Biology Laboratory, Heidelberg, Germany, Center for Industrial Mathematics, University of Bremen, Bremen, Germany, High Performance Humanoid Technologies Lab, Institute for Anthropomatics, Karlsruhe Institute of Technology, Karlsruhe, Germany, Denator, Uppsala, Sweden, Protim, Inserm U1085 - Irset, University of Rennes 1, Rennes, France, SCiLS GmbH, Bremen, Germany, College of Computer and Information Science, Northeastern University, Boston, MA, USA and Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, CA, USA
| | - Olga Vitek
- European Molecular Biology Laboratory, Heidelberg, Germany, Center for Industrial Mathematics, University of Bremen, Bremen, Germany, High Performance Humanoid Technologies Lab, Institute for Anthropomatics, Karlsruhe Institute of Technology, Karlsruhe, Germany, Denator, Uppsala, Sweden, Protim, Inserm U1085 - Irset, University of Rennes 1, Rennes, France, SCiLS GmbH, Bremen, Germany, College of Computer and Information Science, Northeastern University, Boston, MA, USA and Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, CA, USA
| | - Charles Pineau
- European Molecular Biology Laboratory, Heidelberg, Germany, Center for Industrial Mathematics, University of Bremen, Bremen, Germany, High Performance Humanoid Technologies Lab, Institute for Anthropomatics, Karlsruhe Institute of Technology, Karlsruhe, Germany, Denator, Uppsala, Sweden, Protim, Inserm U1085 - Irset, University of Rennes 1, Rennes, France, SCiLS GmbH, Bremen, Germany, College of Computer and Information Science, Northeastern University, Boston, MA, USA and Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, CA, USA
| | - Mats Borén
- European Molecular Biology Laboratory, Heidelberg, Germany, Center for Industrial Mathematics, University of Bremen, Bremen, Germany, High Performance Humanoid Technologies Lab, Institute for Anthropomatics, Karlsruhe Institute of Technology, Karlsruhe, Germany, Denator, Uppsala, Sweden, Protim, Inserm U1085 - Irset, University of Rennes 1, Rennes, France, SCiLS GmbH, Bremen, Germany, College of Computer and Information Science, Northeastern University, Boston, MA, USA and Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, CA, USA
| | - Theodore Alexandrov
- European Molecular Biology Laboratory, Heidelberg, Germany, Center for Industrial Mathematics, University of Bremen, Bremen, Germany, High Performance Humanoid Technologies Lab, Institute for Anthropomatics, Karlsruhe Institute of Technology, Karlsruhe, Germany, Denator, Uppsala, Sweden, Protim, Inserm U1085 - Irset, University of Rennes 1, Rennes, France, SCiLS GmbH, Bremen, Germany, College of Computer and Information Science, Northeastern University, Boston, MA, USA and Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, CA, USA European Molecular Biology Laboratory, Heidelberg, Germany, Center for Industrial Mathematics, University of Bremen, Bremen, Germany, High Performance Humanoid Technologies Lab, Institute for Anthropomatics, Karlsruhe Institute of Technology, Karlsruhe, Germany, Denator, Uppsala, Sweden, Protim, Inserm U1085 - Irset, University of Rennes 1, Rennes, France, SCiLS GmbH, Bremen, Germany, College of Computer and Information Science, Northeastern University, Boston, MA, USA and Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, CA, USA European Molecular Biology Laboratory, Heidelberg, Germany, Center for Industrial Mathematics, University of Bremen, Bremen, Germany, High Performance Humanoid Technologies Lab, Institute for Anthropomatics, Karlsruhe Institute of Technology, Karlsruhe, Germany, Denator, Uppsala, Sweden, Protim, Inserm U1085 - Irset, University of Rennes 1, Rennes, France, SCiLS GmbH, Bremen, Germany, College of Computer and Information Science, Northeastern University, Boston, MA, USA and Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, CA, USA European Molecular Biology Laboratory, Heidelberg, Germany, Center for Industrial Mathematics, University of Bremen, Bremen, Germany, High Performance Humanoid Technologies Lab, Institute for Anthropomatics, Karlsruhe Institute of Technolo
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26
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Martin-Lorenzo M, Balluff B, Maroto AS, Carreira RJ, van Zeijl RJ, Gonzalez-Calero L, de la Cuesta F, Barderas MG, Lopez-Almodovar LF, Padial LR, McDonnell LA, Vivanco F, Alvarez-Llamas G. Lipid and protein maps defining arterial layers in atherosclerotic aorta. Data Brief 2015; 4:328-31. [PMID: 26217810 PMCID: PMC4510571 DOI: 10.1016/j.dib.2015.06.005] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2015] [Revised: 06/16/2015] [Accepted: 06/16/2015] [Indexed: 11/24/2022] Open
Abstract
Subclinical atherosclerosis cannot be predicted and novel therapeutic targets are needed. The molecular anatomy of healthy and atherosclerotic tissue is pursued to identify ongoing molecular changes in atherosclerosis development. Mass Spectrometry Imaging (MSI) accounts with the unique advantage of analyzing proteins and metabolites (lipids) while preserving their original localization; thus two dimensional maps can be obtained. Main molecular alterations were investigated in a rabbit model in response to early development of atherosclerosis. Aortic arterial layers (intima and media) and calcified regions were investigated in detail by MALDI-MSI and proteins and lipids specifically defining those areas of interest were identified. These data further complement main findings previously published in J Proteomics (M. Martin-Lorenzo et al., J. Proteomics. (In press); M. Martin-Lorenzo et al., J. Proteomics 108 (2014) 465-468.) [1,2].
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Affiliation(s)
- Marta Martin-Lorenzo
- Department of Immunology, IIS-Fundacion Jimenez Diaz, UAM, REDinREN, Madrid, Spain
| | - Benjamin Balluff
- Center for Proteomics and Metabolomics, Leiden University Medical Center, Leiden, The Netherlands
| | - Aroa S. Maroto
- Department of Immunology, IIS-Fundacion Jimenez Diaz, UAM, REDinREN, Madrid, Spain
| | - Ricardo J. Carreira
- Center for Proteomics and Metabolomics, Leiden University Medical Center, Leiden, The Netherlands
| | - Rene J.M. van Zeijl
- Center for Proteomics and Metabolomics, Leiden University Medical Center, Leiden, The Netherlands
| | | | - Fernando de la Cuesta
- Department of Vascular Physiopathology, Hospital Nacional de Paraplejicos, SESCAM, Toledo, Spain
| | - Maria G Barderas
- Department of Vascular Physiopathology, Hospital Nacional de Paraplejicos, SESCAM, Toledo, Spain
| | | | - Luis R Padial
- Department of Cardiology, Hospital Virgen de la Salud, SESCAM, Toledo, Spain
| | - Liam A. McDonnell
- Center for Proteomics and Metabolomics, Leiden University Medical Center, Leiden, The Netherlands
| | - Fernando Vivanco
- Department of Immunology, IIS-Fundacion Jimenez Diaz, UAM, REDinREN, Madrid, Spain
- Department of Biochemistry and Molecular Biology I, Universidad Complutense, Madrid, Spain
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27
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Martin-Lorenzo M, Balluff B, Maroto AS, Carreira RJ, van Zeijl RJM, Gonzalez-Calero L, de la Cuesta F, Barderas MG, Lopez-Almodovar LF, Padial LR, McDonnell LA, Vivanco F, Alvarez-Llamas G. Molecular anatomy of ascending aorta in atherosclerosis by MS Imaging: Specific lipid and protein patterns reflect pathology. J Proteomics 2015; 126:245-51. [PMID: 26079611 DOI: 10.1016/j.jprot.2015.06.005] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2015] [Revised: 06/03/2015] [Accepted: 06/07/2015] [Indexed: 12/22/2022]
Abstract
The molecular anatomy of healthy and atherosclerotic tissue is pursued here to identify ongoing molecular changes in atherosclerosis development. Subclinical atherosclerosis cannot be predicted and novel therapeutic targets are needed. Mass spectrometry imaging (MSI) is a novel unexplored ex vivo imaging approach in CVD able to provide in-tissue molecular maps. A rabbit model of early atherosclerosis was developed and high-spatial-resolution MALDI-MSI was applied to comparatively analyze histologically-based arterial regions of interest from control and early atherosclerotic aortas. Specific protocols were applied to identify lipids and proteins significantly altered in response to atherosclerosis. Observed protein alterations were confirmed by immunohistochemistry in rabbit tissue, and additionally in human aortas. Molecular features specifically defining different arterial regions were identified. Localized in the intima, increased expression of SFA and lysolipids and intimal spatial organization showing accumulation of PI, PG and SM point to endothelial dysfunction and triggered inflammatory response. TG, PA, SM and PE-Cer were identified specifically located in calcified regions. Thymosin β4 (TMSB4X) protein was upregulated in intima versus media layer and also in response to atherosclerosis. This overexpression and localization was confirmed in human aortas. In conclusion, molecular histology by MS Imaging identifies spatial organization of arterial tissue in response to atherosclerosis.
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Affiliation(s)
- Marta Martin-Lorenzo
- Department of Immunology, IIS-Fundación Jiménez Díaz, UAM, REDinREN, Madrid, Spain
| | - Benjamin Balluff
- Center for Proteomics and Metabolomics, Leiden University Medical Center, Leiden, The Netherlands
| | - Aroa S Maroto
- Department of Immunology, IIS-Fundación Jiménez Díaz, UAM, REDinREN, Madrid, Spain
| | - Ricardo J Carreira
- Center for Proteomics and Metabolomics, Leiden University Medical Center, Leiden, The Netherlands
| | - Rene J M van Zeijl
- Center for Proteomics and Metabolomics, Leiden University Medical Center, Leiden, The Netherlands
| | | | - Fernando de la Cuesta
- Department of Vascular Physiopathology, Hospital Nacional de Paraplejicos, SESCAM, Toledo, Spain
| | - Maria G Barderas
- Department of Vascular Physiopathology, Hospital Nacional de Paraplejicos, SESCAM, Toledo, Spain
| | | | - Luis R Padial
- Department of Cardiology, Hospital Virgen de la Salud, SESCAM, Toledo, Spain
| | - Liam A McDonnell
- Center for Proteomics and Metabolomics, Leiden University Medical Center, Leiden, The Netherlands.
| | - Fernando Vivanco
- Department of Immunology, IIS-Fundación Jiménez Díaz, UAM, REDinREN, Madrid, Spain; Department of Biochemistry and Molecular Biology I, Universidad Complutense, Madrid, Spain
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28
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Supremacy of modern morphometry in typing renal oncocytoma and malignant look-alikes. Histochem Cell Biol 2015; 144:147-56. [PMID: 25929744 DOI: 10.1007/s00418-015-1324-4] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 04/18/2015] [Indexed: 12/31/2022]
Abstract
In the era of tumour type-specific therapies, the correct typing of renal tumours is of prime importance. As immunotyping and genotyping approaches are laborious and fall short of standardization, we used whole-scale computer-assisted morphometry instead. Three different types of renal tumours with different prognoses and therapies, notoriously prone to mistyping, were analysed . The sample of 335 tumours included clear cell renal cell carcinoma, chromophobe renal cell carcinoma and renal oncocytoma. The sample was analysed using H&E stains of tissue microarrrays in combination with an image-scanning software. Nuclear and cytoplasmic features were registered with the aid of computer-assisted morphometry. Features included shape, texture, colour and colour intensity for different cell compartments, e.g. nuclei and cytoplasm. The software passed several training steps for final validation. Using morphometry, we were able to classify the three renal tumour types correctly, with a 100 % specificity compared to the WHO typing. Nuclear features dominated the typing of chromophobe renal cell carcinoma, whereas cytoplasmic features were the leading classificators for renal oncocytoma. The grading of clear cell renal cell carcinoma attained a specificity of 80 %. In conclusion, modern morphometry may serve as a tool for typing renal epithelial tumours and additionally draws the attention to future nuclear research in chromophobe renal cell carcinoma.
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29
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MALDI Imaging mass spectrometry: current frontiers and perspectives in pathology research and practice. J Transl Med 2015; 95:422-31. [PMID: 25621874 DOI: 10.1038/labinvest.2014.156] [Citation(s) in RCA: 295] [Impact Index Per Article: 32.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2014] [Revised: 11/07/2014] [Accepted: 11/07/2014] [Indexed: 01/14/2023] Open
Abstract
MALDI Imaging mass spectrometry has entered the field of tissue-based research by providing unique advantages for analyzing tissue specimen in an unprecedented detail. A broad spectrum of analytes ranging from proteins, peptides, protein modification over small molecules, drugs and their metabolites as well as pharmaceutical components, endogenous cell metabolites, lipids, and other analytes are made accessible by this in situ technique in tissue. Some of them were even not accessible in tissues within the histological context before. Thereby, the great advantage of MALDI Imaging is the correlation of molecular information with traditional histology by keeping the spatial localization information of the analytes after mass spectrometric measurement. This method is label-free and allows multiplex analysis of hundreds to thousands of molecules in the very same tissue section simultaneously. Imaging mass spectrometry brings a new quality of molecular data and links the expert discipline of pathology and deep molecular mass spectrometric analysis to tissue-based research. This review will focus on state-of-the-art of MALDI Imaging mass spectrometry, its recent applications by analyzing tissue specimen and the contributions in understanding the biology of disease as well as its perspectives for pathology research and practice.
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30
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Heijs B, Carreira RJ, Tolner EA, de Ru AH, van den Maagdenberg AMJM, van Veelen PA, McDonnell LA. Comprehensive Analysis of the Mouse Brain Proteome Sampled in Mass Spectrometry Imaging. Anal Chem 2015; 87:1867-75. [DOI: 10.1021/ac503952q] [Citation(s) in RCA: 40] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Affiliation(s)
- Bram Heijs
- Center
for Proteomics and Metabolomics, Leiden University Medical Center, Leiden, 2333ZA The Netherlands
| | - Ricardo J. Carreira
- Center
for Proteomics and Metabolomics, Leiden University Medical Center, Leiden, 2333ZA The Netherlands
| | - Else A. Tolner
- Department
of Neurology, Leiden University Medical Center, Leiden, 2333ZA The Netherlands
| | - Arnoud H. de Ru
- Department
of Immunohematology and Blood Transfusion, Leiden University Medical Center, Leiden, 2333ZA The Netherlands
| | - Arn M. J. M. van den Maagdenberg
- Department
of Neurology, Leiden University Medical Center, Leiden, 2333ZA The Netherlands
- Department
of Human Genetics, Leiden University Medical Center, Leiden, 2333ZA The Netherlands
| | - Peter A. van Veelen
- Department
of Immunohematology and Blood Transfusion, Leiden University Medical Center, Leiden, 2333ZA The Netherlands
| | - Liam A. McDonnell
- Center
for Proteomics and Metabolomics, Leiden University Medical Center, Leiden, 2333ZA The Netherlands
- Fondazione Pisana
per la Scienza ONLUS, Pisa, 56121 Italy
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31
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Rawlins CM, Salisbury JP, Feldman DR, Isim S, Agar NYR, Luther E, Agar JN. Imaging and Mapping of Tissue Constituents at the Single-Cell Level Using MALDI MSI and Quantitative Laser Scanning Cytometry. Methods Mol Biol 2015; 1346:133-49. [PMID: 26542720 DOI: 10.1007/978-1-4939-2987-0_10] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/01/2023]
Abstract
For nearly a century, histopathology involved the laborious morphological analyses of tissues stained with broad-spectrum dyes (i.e., eosin to label proteins). With the advent of antibody-labeling, immunostaining (fluorescein and rhodamine for fluorescent labeling) and immunohistochemistry (DAB and hematoxylin), it became possible to identify specific immunological targets in cells and tissue preparations. Technical advances, including the development of monoclonal antibody technology, led to an ever-increasing palate of dyes, both fluorescent and chromatic. This provides an incredibly rich menu of molecular entities that can be visualized and quantified in cells-giving rise to the new discipline of Molecular Pathology. We describe the evolution of two analytical techniques, cytometry and mass spectrometry, which complement histopathological visual analysis by providing automated, cellular-resolution constituent maps. For the first time, laser scanning cytometry (LSC) and matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) are combined for the analysis of tissue sections. The utility of the marriage of these techniques is demonstrated by analyzing mouse brains with neuron-specific, genetically encoded, fluorescent proteins. We present a workflow that: (1) can be used with or without expensive matrix deposition methods, (2) uses LSC images to reveal the diverse landscape of neural tissue as well as the matrix, and (3) uses a tissue fixation method compatible with a DNA stain. The proposed workflow can be adapted for a variety of sample preparation and matrix deposition methods.
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Affiliation(s)
- Catherine M Rawlins
- Barnett Institute of Chemical and Biological Analysis, Northeastern University, Boston, MA, USA.
| | - Joseph P Salisbury
- Barnett Institute of Chemical and Biological Analysis, Northeastern University, Boston, MA, USA.
| | - Daniel R Feldman
- Department of Neurosurgery, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
| | - Sinan Isim
- Life Sciences Department, Brandeis University, Waltham, MA, USA.
| | - Nathalie Y R Agar
- Department of Neurosurgery, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
| | - Ed Luther
- Department of Pharmaceutical Sciences, Northeastern University, 360 Huntington Avenue, Boston, MA, 02115, USA.
| | - Jeffery N Agar
- Barnett Institute of Chemical and Biological Analysis, Northeastern University, Boston, MA, USA. .,Department of Neurosurgery, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
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32
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Crecelius AC, Schubert US, von Eggeling F. MALDI mass spectrometric imaging meets “omics”: recent advances in the fruitful marriage. Analyst 2015; 140:5806-20. [DOI: 10.1039/c5an00990a] [Citation(s) in RCA: 32] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Matrix-assisted laser desorption/ionization mass spectrometric imaging (MALDI MSI) is a method that allows the investigation of the molecular content of surfaces, in particular, tissues, within its morphological context.
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Affiliation(s)
- A. C. Crecelius
- Laboratory of Organic and Macromolecular Chemistry (IOMC)
- Friedrich Schiller University Jena
- 07743 Jena
- Germany
- Jena Center for Soft Matter (JCSM)
| | - U. S. Schubert
- Laboratory of Organic and Macromolecular Chemistry (IOMC)
- Friedrich Schiller University Jena
- 07743 Jena
- Germany
- Jena Center for Soft Matter (JCSM)
| | - F. von Eggeling
- Jena Center for Soft Matter (JCSM)
- Friedrich Schiller University Jena
- 07743 Jena
- Germany
- Institute of Physical Chemistry
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33
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Kriegsmann J, Kriegsmann M, Casadonte R. MALDI TOF imaging mass spectrometry in clinical pathology: a valuable tool for cancer diagnostics (review). Int J Oncol 2014; 46:893-906. [PMID: 25482502 DOI: 10.3892/ijo.2014.2788] [Citation(s) in RCA: 117] [Impact Index Per Article: 11.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2014] [Accepted: 11/04/2014] [Indexed: 11/06/2022] Open
Abstract
Matrix-assisted laser desorption/ionization (MALDI) time-of-flight (TOF) imaging mass spectrometry (IMS) is an evolving technique in cancer diagnostics and combines the advantages of mass spectrometry (proteomics), detection of numerous molecules, and spatial resolution in histological tissue sections and cytological preparations. This method allows the detection of proteins, peptides, lipids, carbohydrates or glycoconjugates and small molecules.Formalin-fixed paraffin-embedded tissue can also be investigated by IMS, thus, this method seems to be an ideal tool for cancer diagnostics and biomarker discovery. It may add information to the identification of tumor margins and tumor heterogeneity. The technique allows tumor typing, especially identification of the tumor of origin in metastatic tissue, as well as grading and may provide prognostic information. IMS is a valuable method for the identification of biomarkers and can complement histology, immunohistology and molecular pathology in various fields of histopathological diagnostics, especially with regard to identification and grading of tumors.
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Affiliation(s)
- Jörg Kriegsmann
- MVZ for Histology, Cytology and Molecular Diagnostics, Trier, Germany
| | - Mark Kriegsmann
- Institute for Pathology, University of Heidelberg, Heidelberg, Germany
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34
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Balluff B, Frese CK, Maier SK, Schöne C, Kuster B, Schmitt M, Aubele M, Höfler H, Deelder AM, Heck A, Hogendoorn PCW, Morreau J, Maarten Altelaar AF, Walch A, McDonnell LA. De novo discovery of phenotypic intratumour heterogeneity using imaging mass spectrometry. J Pathol 2014; 235:3-13. [PMID: 25201776 DOI: 10.1002/path.4436] [Citation(s) in RCA: 103] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2014] [Revised: 08/04/2014] [Accepted: 09/03/2014] [Indexed: 12/31/2022]
Abstract
An essential and so far unresolved factor influencing the evolution of cancer and the clinical management of patients is intratumour clonal and phenotypic heterogeneity. However, the de novo identification of tumour subpopulations is so far both a challenging and an unresolved task. Here we present the first systematic approach for the de novo discovery of clinically detrimental molecular tumour subpopulations. In this proof-of-principle study, spatially resolved, tumour-specific mass spectra were acquired, using matrix-assisted laser desorption/ionization (MALDI) imaging mass spectrometry, from tissues of 63 gastric carcinoma and 32 breast carcinoma patients. The mass spectra, representing the proteomic heterogeneity within tumour areas, were grouped by a corroborated statistical clustering algorithm in order to obtain segmentation maps of molecularly distinct regions. These regions were presumed to represent different phenotypic tumour subpopulations. This was confirmed by linking the presence of these tumour subpopulations to the patients' clinical data. This revealed several of the detected tumour subpopulations to be associated with a different overall survival of the gastric cancer patients (p = 0.025) and the presence of locoregional metastases in patients with breast cancer (p = 0.036). The procedure presented is generic and opens novel options in cancer research, as it reveals microscopically indistinct tumour subpopulations that have an adverse impact on clinical outcome. This enables their further molecular characterization for deeper insights into the biological processes of cancer, which may finally lead to new targeted therapies.
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Affiliation(s)
- Benjamin Balluff
- Centre for Proteomics and Metabolomics, Leiden University Medical Centre, The Netherlands
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35
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Klein O, Strohschein K, Nebrich G, Oetjen J, Trede D, Thiele H, Alexandrov T, Giavalisco P, Duda GN, von Roth P, Geissler S, Klose J, Winkler T. MALDI imaging mass spectrometry: discrimination of pathophysiological regions in traumatized skeletal muscle by characteristic peptide signatures. Proteomics 2014; 14:2249-60. [PMID: 25056804 DOI: 10.1002/pmic.201400088] [Citation(s) in RCA: 43] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2014] [Revised: 06/24/2014] [Accepted: 07/21/2014] [Indexed: 01/06/2023]
Abstract
Due to formation of fibrosis and the loss of contractile muscle tissue, severe muscle injuries often result in insufficient healing marked by a significant reduction of muscle force and motor activity. Our previous studies demonstrated that the local transplantation of mesenchymal stromal cells into an injured skeletal muscle of the rat improves the functional outcome of the healing process. Since, due to the lack of sufficient markers, the accurate discrimination of pathophysiological regions in injured skeletal muscle is inadequate, underlying mechanisms of the beneficial effects of mesenchymal stromal cell transplantation on primary trauma and trauma adjacent muscle area remain elusive. For discrimination of these pathophysiological regions, formalin-fixed injured skeletal muscle tissue was analyzed by MALDI imaging MS. By using two computational evaluation strategies, a supervised approach (ClinProTools) and unsupervised segmentation (SCiLS Lab), characteristic m/z species could be assigned to primary trauma and trauma adjacent muscle regions. Using "bottom-up" MS for protein identification and validation of results by immunohistochemistry, we could identify two proteins, skeletal muscle alpha actin and carbonic anhydrase III, which discriminate between the secondary damage on adjacent tissue and the primary traumatized muscle area. Our results underscore the high potential of MALDI imaging MS to describe the spatial characteristics of pathophysiological changes in muscle.
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Affiliation(s)
- Oliver Klein
- Berlin-Brandenburg Center for Regenerative Therapies, Charité-Universitätsmedizin Berlin, Berlin, Germany; Core Unit Proteomics, Berlin-Brandenburg Center for Regenerative Therapies, Charité-Universitätsmedizin Berlin, Berlin, Germany
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36
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Dekker TJA, Balluff BD, Jones EA, Schöne CD, Schmitt M, Aubele M, Kroep JR, Smit VTHBM, Tollenaar RAEM, Mesker WE, Walch A, McDonnell LA. Multicenter Matrix-Assisted Laser Desorption/Ionization Mass Spectrometry Imaging (MALDI MSI) Identifies Proteomic Differences in Breast-Cancer-Associated Stroma. J Proteome Res 2014; 13:4730-8. [DOI: 10.1021/pr500253j] [Citation(s) in RCA: 68] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Affiliation(s)
- Tim J. A. Dekker
- Department
of Clinical Oncology, Leiden University Medical Center, Leiden, The Netherlands
- Department
of Surgery, Leiden University Medical Center, Leiden, The Netherlands
| | - Benjamin D. Balluff
- Center
for Proteomics and Metabolomics, Leiden University Medical Center, Einthovenweg 20, 2333 ZC Leiden, The Netherlands
| | - Emrys A. Jones
- Center
for Proteomics and Metabolomics, Leiden University Medical Center, Einthovenweg 20, 2333 ZC Leiden, The Netherlands
| | - Cédrik D. Schöne
- Research
Unit Analytical Pathology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany
| | - Manfred Schmitt
- Department
of Obstetrics and Gynecology, Klinikum rechts der Isar, Technische Universität München, Munich, Germany
| | - Michaela Aubele
- Institute
of Pathology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany
| | - Judith R. Kroep
- Department
of Surgery, Leiden University Medical Center, Leiden, The Netherlands
| | | | | | - Wilma E. Mesker
- Department
of Surgery, Leiden University Medical Center, Leiden, The Netherlands
| | - Axel Walch
- Research
Unit Analytical Pathology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany
| | - Liam A. McDonnell
- Center
for Proteomics and Metabolomics, Leiden University Medical Center, Einthovenweg 20, 2333 ZC Leiden, The Netherlands
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