1
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Frendi S, Martineau C, Cazier H, Nicolle R, Chassac A, Albuquerque M, Raffenne J, Le Faouder J, Paradis V, Cros J, Couvelard A, Rebours V. Role of the fatty pancreatic infiltration in pancreatic oncogenesis. Sci Rep 2024; 14:6582. [PMID: 38503902 PMCID: PMC10951200 DOI: 10.1038/s41598-024-57294-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2023] [Accepted: 03/16/2024] [Indexed: 03/21/2024] Open
Abstract
Although pancreatic precancerous lesions are known to be related to obesity and fatty pancreatic infiltration, the mechanisms remain unclear. We assessed the role of fatty infiltration in the process of pancreatic oncogenesis and obesity. A combined transcriptomic, lipidomic and pathological approach was used to explore neoplastic transformations. Intralobular (ILF) and extralobular (ELF) lipidomic profiles were analyzed to search for lipids associated with pancreatic intraepithelial neoplasia (PanINs) and obesity; the effect of ILF and ELF on acinar tissue and the histopathological aspects of pancreatic parenchyma changes in obese (OB) and non-obese patients. This study showed that the lipid composition of ILF was different from that of ELF. ILF was related to obesity and ELF-specific lipids were correlated to PanINs. Acinar cells were shown to have different phenotypes depending on the presence and proximity to ILF in OB patients. Several lipid metabolic pathways, oxidative stress and inflammatory pathways were upregulated in acinar tissue during ILF infiltration in OB patients. Early acinar transformations, called acinar nodules (AN) were linked to obesity but not ELF or ILF suggesting that they are the first reversible precancerous pancreatic lesions to occur in OB patients. On the other hand, the number of PanINs was higher in OB patients and was positively correlated to ILF and ELF scores as well as to fibrosis. Our study suggests that two types of fat infiltration must be distinguished, ELF and ILF. ILF plays a major role in acinar modifications and the development of precancerous lesions associated with obesity, while ELF may play a role in the progression of PDAC.
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Affiliation(s)
- Sonia Frendi
- Inflammation Research Center (CRI), INSERM, U1149, Paris-Cité University, 75018, Paris, France
| | - Chloé Martineau
- Pancreatology and digestive oncology Department - DMU Digest, Beaujon Hospital, AP-HP, Paris-Cité University, 100 Boulevard du Général Leclerc, 92110, Clichy, France
| | - Hélène Cazier
- Inflammation Research Center (CRI), INSERM, U1149, Paris-Cité University, 75018, Paris, France
| | - Rémy Nicolle
- INSERM U1149, CNRS ERL 8252, Inflammation Research Center (CRI), Paris-Cité University, 75018, Paris, France
| | - Anaïs Chassac
- Pathology Department, Bichat Hospital, AP-HP, Paris-Cité University, Paris, France
| | - Miguel Albuquerque
- Inflammation Research Center (CRI), INSERM, U1149, Paris-Cité University, 75018, Paris, France
- Pathology Department, FHU MOSAIC, AP-HP, Beaujon Hospital, Clichy, France
| | | | - Julie Le Faouder
- Inflammation Research Center (CRI), INSERM, U1149, Paris-Cité University, 75018, Paris, France
| | - Valérie Paradis
- Inflammation Research Center (CRI), INSERM, U1149, Paris-Cité University, 75018, Paris, France
- Pathology Department, FHU MOSAIC, AP-HP, Beaujon Hospital, Clichy, France
| | - Jérôme Cros
- Inflammation Research Center (CRI), INSERM, U1149, Paris-Cité University, 75018, Paris, France
- Pathology Department, FHU MOSAIC, AP-HP, Beaujon Hospital, Clichy, France
| | - Anne Couvelard
- Inflammation Research Center (CRI), INSERM, U1149, Paris-Cité University, 75018, Paris, France
- Pathology Department, Bichat Hospital, AP-HP, Paris-Cité University, Paris, France
| | - Vinciane Rebours
- Inflammation Research Center (CRI), INSERM, U1149, Paris-Cité University, 75018, Paris, France.
- Pancreatology and digestive oncology Department - DMU Digest, Beaujon Hospital, AP-HP, Paris-Cité University, 100 Boulevard du Général Leclerc, 92110, Clichy, France.
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2
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Shen EYL, U MRA, Cox IJ, Taylor-Robinson SD. The Role of Mass Spectrometry in Hepatocellular Carcinoma Biomarker Discovery. Metabolites 2023; 13:1059. [PMID: 37887384 PMCID: PMC10609223 DOI: 10.3390/metabo13101059] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2023] [Revised: 10/03/2023] [Accepted: 10/05/2023] [Indexed: 10/28/2023] Open
Abstract
Hepatocellular carcinoma (HCC) is the main liver malignancy and has a high mortality rate. The discovery of novel biomarkers for early diagnosis, prognosis, and stratification purposes has the potential to alleviate its disease burden. Mass spectrometry (MS) is one of the principal technologies used in metabolomics, with different experimental methods and machine types for different phases of the biomarker discovery process. Here, we review why MS applications are useful for liver cancer, explain the MS technique, and briefly summarise recent findings from metabolomic MS studies on HCC. We also discuss the current challenges and the direction for future research.
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Affiliation(s)
- Eric Yi-Liang Shen
- Department of Radiation Oncology and Proton Therapy Center, Linkou Chang Gung Memorial Hospital and Chang Gung University, Taoyuan City 333, Taiwan
- Clinical Metabolomics Core Laboratory, Linkou Chang Gung Memorial Hospital and Chang Gung University, Taoyuan City 333, Taiwan
- Department of Surgery and Cancer, Faculty of Medicine, Imperial College London, London W2 1NY, UK
| | - Mei Ran Abellona U
- Department of Surgery and Cancer, Faculty of Medicine, Imperial College London, London W2 1NY, UK
- School of Clinical Medicine, University of Cambridge, Cambridge CB2 0SP, UK
| | - I. Jane Cox
- The Roger Williams Institute of Hepatology, Foundation for Liver Research, London SE5 9NT, UK
- Faculty of Life Sciences & Medicine, King’s College London, London SE5 8AF, UK
| | - Simon D. Taylor-Robinson
- Department of Surgery and Cancer, Faculty of Medicine, Imperial College London, London W2 1NY, UK
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3
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Applications of mass spectroscopy in understanding cancer proteomics. Proteomics 2023. [DOI: 10.1016/b978-0-323-95072-5.00007-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/01/2023]
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4
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Marsh-Wakefield F, Ferguson AL, Liu K, Santhakumar C, McCaughan G, Palendira U. Approaches to spatially resolving the tumour immune microenvironment of hepatocellular carcinoma. Ther Adv Med Oncol 2022; 14:17588359221113270. [PMID: 35898965 PMCID: PMC9310213 DOI: 10.1177/17588359221113270] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2022] [Accepted: 06/27/2022] [Indexed: 12/15/2022] Open
Abstract
Hepatocellular carcinoma (HCC) is a common and deadly cancer worldwide. Many factors contribute to mortality and place an individual at high risk of developing HCC, including viral infection, alcohol intake, metabolic-associated disease, autoimmunity and genetic liver disorders. Although there are many therapeutics available, much about this disease remains to be understood. This is most evident when investigating the tumour microenvironment (TME). Both innate and adaptive immune cells have been associated with carcinogenesis within the TME of HCC patients. The ability to interrogate the TME more thoroughly with spatial technologies continues to improve, both at the experimental and analytical stages. This review provides insight into technologies available to investigate the TME, and how such technologies are beneficial for improving our understanding of HCC carcinogenesis.
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Affiliation(s)
- Felix Marsh-Wakefield
- Liver Injury & Cancer Program, Centenary Institute, Royal Prince Alfred Hospital, Missenden Road, Sydney, NSW, 2050, Australia
- Human Immunology Laboratory, The University of Sydney, Sydney, NSW, Australia
| | - Angela L Ferguson
- Liver Injury & Cancer Program, Centenary Institute, Sydney, NSW, Australia
- Human Immunology Laboratory, The University of Sydney, Sydney, NSW, Australia
| | - Ken Liu
- Liver Injury & Cancer Program, Centenary Institute, Sydney, NSW, Australia
- A.W. Morrow Gastroenterology and Liver Centre, Royal Prince Alfred Hospital, The University of Sydney, Sydney, NSW, Australia
| | - Cositha Santhakumar
- Liver Injury & Cancer Program, Centenary Institute, Sydney, NSW, Australia
- A.W. Morrow Gastroenterology and Liver Centre, Royal Prince Alfred Hospital, The University of Sydney, Sydney, NSW, Australia
| | - Geoffrey McCaughan
- Liver Injury & Cancer Program, Centenary Institute, Sydney, NSW, Australia
- A.W. Morrow Gastroenterology and Liver Centre, Royal Prince Alfred Hospital, The University of Sydney, Sydney, NSW, Australia
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5
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Basu SS, Agar NYR. Bringing Matrix-Assisted Laser Desorption/Ionization Mass Spectrometry Imaging to the Clinics. Clin Lab Med 2021; 41:309-324. [PMID: 34020766 DOI: 10.1016/j.cll.2021.03.009] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI) is an emerging analytical technique that promises to change tissue-based diagnostics. This article provides a brief introduction to MALDI MSI as well as clinical diagnostic workflows and opportunities to apply this powerful approach. It describes various MALDI MSI applications, from more clinically mature applications such as cancer to emerging applications such as infectious diseases and drug distribution. In addition, it discusses the analytical considerations that need to be considered when bringing these approaches to different diagnostic problems and settings.
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Affiliation(s)
- Sankha S Basu
- Department of Pathology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Nathalie Y R Agar
- Department of Neurosurgery, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA; Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA; Department of Cancer Biology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA 02115, USA.
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6
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Jain D, Torres R, Celli R, Koelmel J, Charkoftaki G, Vasiliou V. Evolution of the liver biopsy and its future. Transl Gastroenterol Hepatol 2021; 6:20. [PMID: 33824924 PMCID: PMC7829074 DOI: 10.21037/tgh.2020.04.01] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/12/2020] [Accepted: 03/19/2020] [Indexed: 12/12/2022] Open
Abstract
Liver biopsies are commonly used to evaluate a wide variety of medical disorders, including neoplasms and post-transplant complications. However, its use is being impacted by improved clinical diagnosis of disorders, and non-invasive methods for evaluating liver tissue and as a result the indications of a liver biopsy have undergone major changes in the last decade. The evolution of highly effective treatments for some of the common indications for liver biopsy in the last decade (e.g., viral hepatitis B and C) has led to a decline in the number of liver biopsies in recent years. At the same time, the emergence of better technologies for histologic evaluation, tissue content analysis and genomics are among the many new and exciting developments in the field that hold great promise for the future and are going to shape the indications for a liver biopsy in the future. Recent advances in slide scanners now allow creation of "digital/virtual" slides that have image of the entire tissue section present in a slide [whole slide imaging (WSI)]. WSI can now be done very rapidly and at very high resolution, allowing its use in routine clinical practice. In addition, a variety of technologies have been developed in recent years that use different light sources and/or microscopes allowing visualization of tissues in a completely different way. One such technique that is applicable to liver specimens combines multiphoton microscopy (MPM) with advanced clearing and fluorescent stains known as Clearing Histology with MultiPhoton Microscopy (CHiMP). Although it has not yet been extensively validated, the technique has the potential to decrease inefficiency, reduce artifacts, and increase data while being readily integrable into clinical workflows. Another technology that can provide rapid and in-depth characterization of thousands of molecules in a tissue sample, including liver tissues, is matrix assisted laser desorption/ionization (MALDI) mass spectrometry. MALDI has already been applied in a clinical research setting with promising diagnostic and prognostic capabilities, as well as being able to elucidate mechanisms of liver diseases that may be targeted for the development of new therapies. The logical next step in huge data sets obtained from such advanced analysis of liver tissues is the application of machine learning (ML) algorithms and application of artificial intelligence (AI), for automated generation of diagnoses and prognoses. This review discusses the evolving role of liver biopsies in clinical practice over the decades, and describes newer technologies that are likely to have a significant impact on how they will be used in the future.
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Affiliation(s)
- Dhanpat Jain
- Department of Anatomic Pathology, Yale University School of Medicine, New Haven, CT, USA
| | - Richard Torres
- Department of Laboratory Medicine, Yale University School of Medicine, New Haven, CT, USA
| | - Romulo Celli
- Department of Anatomic Pathology, Yale University School of Medicine, New Haven, CT, USA
| | - Jeremy Koelmel
- Department of Environmental Health Sciences, Yale School of Public Health, New Haven, CT, USA
| | - Georgia Charkoftaki
- Department of Environmental Health Sciences, Yale School of Public Health, New Haven, CT, USA
| | - Vasilis Vasiliou
- Department of Environmental Health Sciences, Yale School of Public Health, New Haven, CT, USA
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7
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Kirchberger-Tolstik T, Ryabchykov O, Bocklitz T, Dirsch O, Settmacher U, Popp J, Stallmach A. Nondestructive molecular imaging by Raman spectroscopy vs. marker detection by MALDI IMS for an early diagnosis of HCC. Analyst 2021; 146:1239-1252. [PMID: 33313629 DOI: 10.1039/d0an01555e] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/21/2023]
Abstract
Hepatocellular carcinoma (HCC) is a leading cause of cancer-related deaths worldwide with a steadily increasing mortality rate. Fast diagnosis at early stages of HCC is of key importance for the improvement of patient survival rates. In this regard, we combined two imaging techniques with high potential for HCC diagnosis in order to improve the prediction of liver cancer. In detail, Raman spectroscopic imaging and matrix-assisted laser desorption ionization imaging mass spectrometry (MALDI IMS) were applied for the diagnosis of 36 HCC tissue samples. The data were analyzed using multivariate methods, and the results revealed that Raman spectroscopy alone showed a good capability for HCC tumor identification (sensitivity of 88% and specificity of 80%), which could not be improved by combining the Raman data with MALDI IMS. In addition, it could be shown that the two methods in combination can differentiate between well-, moderately- and poorly-differentiated HCC using a linear classification model. MALDI IMS not only classified the HCC grades with a sensitivity of 100% and a specificity of 80%, but also showed significant differences in the expression of glycerophospholipids and fatty acyls during HCC differentiation. Furthermore, important differences in the protein, lipid and collagen compositions of differentiated HCC were detected using the model coefficients of a Raman based classification model. Both Raman and MALDI IMS, as well as their combination showed high potential for resolving concrete questions in liver cancer diagnosis.
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Affiliation(s)
- Tatiana Kirchberger-Tolstik
- Jena University Hospital, Department of Internal Medicine IV, Gastroenterology, Hepatology, Infectious Disease, Am Klinikum, 1, 07747 Jena, Germany
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8
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Abstract
Mass spectrometry imaging (MSI) is a label-free molecular imaging technique allowing an untargeted detection of a broad range of biomolecules and xenobiotics. MSI enables imaging of the spatial distribution of proteins, peptides, lipids and metabolites from a wide range of samples. To date, this technique is commonly applied to tissue sections in cancer diagnostics and biomarker development, but also molecular histology in general. Advances in the methodology and bioinformatics improved the resolution of MS images below the single cell level and increased the flexibility of the workflow. However, MSI-based research in virology is just starting to gain momentum and its full potential has not been exploited yet. In this review, we discuss the main applications of MSI in virology. We review important aspects of matrix-assisted laser desorption/ionization (MALDI) MSI, the most widely used MSI technique in virology. In addition, we summarize relevant literature on MSI studies that aim to unravel virus-host interactions and virus pathogenesis, to elucidate antiviral drug kinetics and to improve current viral disease diagnostics. Collectively, these studies strongly improve our general understanding of virus-induced changes in the proteome, metabolome and metabolite distribution in host tissues of humans, animals and plants upon infection. Furthermore, latest MSI research provided important insights into the drug distribution and distribution kinetics, especially in antiretroviral research. Finally, MSI-based investigations of oncogenic viruses greatly increased our knowledge on tumor mass signatures and facilitated the identification of cancer biomarkers.
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Affiliation(s)
- Luca D Bertzbach
- Institute of Virology, Freie Universität Berlin, Berlin, Germany
| | | | - Axel Karger
- Institute of Molecular Virology and Cell Biology, Friedrich-Loeffler-Institut, Greifswald-Insel Riems, Germany.
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9
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Verbeeck N, Caprioli RM, Van de Plas R. Unsupervised machine learning for exploratory data analysis in imaging mass spectrometry. MASS SPECTROMETRY REVIEWS 2020; 39:245-291. [PMID: 31602691 PMCID: PMC7187435 DOI: 10.1002/mas.21602] [Citation(s) in RCA: 118] [Impact Index Per Article: 29.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/01/2017] [Accepted: 08/27/2018] [Indexed: 05/20/2023]
Abstract
Imaging mass spectrometry (IMS) is a rapidly advancing molecular imaging modality that can map the spatial distribution of molecules with high chemical specificity. IMS does not require prior tagging of molecular targets and is able to measure a large number of ions concurrently in a single experiment. While this makes it particularly suited for exploratory analysis, the large amount and high-dimensional nature of data generated by IMS techniques make automated computational analysis indispensable. Research into computational methods for IMS data has touched upon different aspects, including spectral preprocessing, data formats, dimensionality reduction, spatial registration, sample classification, differential analysis between IMS experiments, and data-driven fusion methods to extract patterns corroborated by both IMS and other imaging modalities. In this work, we review unsupervised machine learning methods for exploratory analysis of IMS data, with particular focus on (a) factorization, (b) clustering, and (c) manifold learning. To provide a view across the various IMS modalities, we have attempted to include examples from a range of approaches including matrix assisted laser desorption/ionization, desorption electrospray ionization, and secondary ion mass spectrometry-based IMS. This review aims to be an entry point for both (i) analytical chemists and mass spectrometry experts who want to explore computational techniques; and (ii) computer scientists and data mining specialists who want to enter the IMS field. © 2019 The Authors. Mass Spectrometry Reviews published by Wiley Periodicals, Inc. Mass SpecRev 00:1-47, 2019.
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Affiliation(s)
- Nico Verbeeck
- Delft Center for Systems and ControlDelft University of Technology ‐ TU DelftDelftThe Netherlands
- Aspect Analytics NVGenkBelgium
- STADIUS Center for Dynamical Systems, Signal Processing, and Data Analytics, Department of Electrical Engineering (ESAT)KU LeuvenLeuvenBelgium
| | - Richard M. Caprioli
- Mass Spectrometry Research CenterVanderbilt UniversityNashvilleTN
- Department of BiochemistryVanderbilt UniversityNashvilleTN
- Department of ChemistryVanderbilt UniversityNashvilleTN
- Department of PharmacologyVanderbilt UniversityNashvilleTN
- Department of MedicineVanderbilt UniversityNashvilleTN
| | - Raf Van de Plas
- Delft Center for Systems and ControlDelft University of Technology ‐ TU DelftDelftThe Netherlands
- Mass Spectrometry Research CenterVanderbilt UniversityNashvilleTN
- Department of BiochemistryVanderbilt UniversityNashvilleTN
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10
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Bockmayr T, Erdmann G, Treue D, Jurmeister P, Schneider J, Arndt A, Heim D, Bockmayr M, Sachse C, Klauschen F. Multiclass cancer classification in fresh frozen and formalin-fixed paraffin-embedded tissue by DigiWest multiplex protein analysis. J Transl Med 2020; 100:1288-1299. [PMID: 32601356 PMCID: PMC7498367 DOI: 10.1038/s41374-020-0455-y] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2020] [Revised: 06/02/2020] [Accepted: 06/07/2020] [Indexed: 11/28/2022] Open
Abstract
Histomorphology and immunohistochemistry are the most common ways of cancer classification in routine cancer diagnostics, but often reach their limits in determining the organ origin in metastasis. These cancers of unknown primary, which are mostly adenocarcinomas or squamous cell carcinomas, therefore require more sophisticated methodologies of classification. Here, we report a multiplex protein profiling-based approach for the classification of fresh frozen and formalin-fixed paraffin-embedded (FFPE) cancer tissue samples using the digital western blot technique DigiWest. A DigiWest-compatible FFPE extraction protocol was developed, and a total of 634 antibodies were tested in an initial set of 16 FFPE samples covering tumors from different origins. Of the 303 detected antibodies, 102 yielded significant correlation of signals in 25 pairs of fresh frozen and FFPE primary tumor samples, including head and neck squamous cell carcinomas (HNSC), lung squamous cell carcinomas (LUSC), lung adenocarcinomas (LUAD), colorectal adenocarcinomas (COAD), and pancreatic adenocarcinomas (PAAD). For this signature of 102 analytes (covering 88 total proteins and 14 phosphoproteins), a support vector machine (SVM) algorithm was developed. This allowed for the classification of the tissue of origin for all five tumor types studied here with high overall accuracies in both fresh frozen (90.4%) and FFPE (77.6%) samples. In addition, the SVM classifier reached an overall accuracy of 88% in an independent validation cohort of 25 FFPE tumor samples. Our results indicate that DigiWest-based protein profiling represents a valuable method for cancer classification, yielding conclusive and decisive data not only from fresh frozen specimens but also FFPE samples, thus making this approach attractive for routine clinical applications.
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Affiliation(s)
- Teresa Bockmayr
- grid.7468.d0000 0001 2248 7639Institute of Pathology, Charité – Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany
| | | | - Denise Treue
- grid.7468.d0000 0001 2248 7639Institute of Pathology, Charité – Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany ,Central Biobank Charité (ZeBanC), Berlin, Germany
| | - Philipp Jurmeister
- grid.7468.d0000 0001 2248 7639Institute of Pathology, Charité – Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany ,grid.7497.d0000 0004 0492 0584German Cancer Consortium (DKTK), Partner Site Berlin, and German Cancer Research Center (DKFZ), Heidelberg, Germany
| | | | | | - Daniel Heim
- grid.7468.d0000 0001 2248 7639Institute of Pathology, Charité – Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany
| | - Michael Bockmayr
- grid.7468.d0000 0001 2248 7639Institute of Pathology, Charité – Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany ,grid.13648.380000 0001 2180 3484Department of Pediatric Hematology and Oncology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany ,grid.470174.1Research Institute Children’s Cancer Center Hamburg, Hamburg, Germany
| | | | - Frederick Klauschen
- Institute of Pathology, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany. .,German Cancer Consortium (DKTK), Partner Site Berlin, and German Cancer Research Center (DKFZ), Heidelberg, Germany.
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11
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Zhu Y, Zhu J, Lu C, Zhang Q, Xie W, Sun P, Dong X, Yue L, Sun Y, Yi X, Zhu T, Ruan G, Aebersold R, Huang S, Guo T. Identification of Protein Abundance Changes in Hepatocellular Carcinoma Tissues Using PCT-SWATH. Proteomics Clin Appl 2018; 13:e1700179. [PMID: 30365225 DOI: 10.1002/prca.201700179] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2018] [Revised: 10/16/2018] [Indexed: 12/16/2022]
Abstract
PURPOSE To rapidly identify protein abundance changes in biopsy-level fresh-frozen hepatocellular carcinoma (HCC). EXPERIMENTAL DESIGN The pressure-cycling technology (PCT) is applied and sequential window acquisition of all theoretical mass spectra (SWATH-MS) workflow is optimized to analyze 38 biopsy-level tissue samples from 19 HCC patients. Each proteome is analyzed with 45 min LC gradient. MCM7 is validated using immunohistochemistry (IHC). RESULTS A total of 11 787 proteotypic peptides from 2579 SwissProt proteins are quantified with high confidence. The coefficient of variation (CV) of peptide yield using PCT is 32.9%, and the R2 of peptide quantification is 0.9729. Five hundred forty-one proteins showed significant abundance change between the tumor area and its adjacent benign area. From 24 upregulated pathways and 13 suppressed ones, enhanced biomolecule synthesis and suppressed small molecular metabolism in liver tumor tissues are observed. Protein changes based on α-fetoprotein expression and hepatitis B virus infection are further analyzed. The data altogether highlight 16 promising tumor marker candidates. The upregulation of minichromosome maintenance complex component 7 (MCM7) is further observed in multiple HCC tumor tissues by IHC. CONCLUSIONS AND CLINICAL RELEVANCE The practicality of rapid proteomic analysis of biopsy-level fresh-frozen HCC tissue samples with PCT-SWATH has been demonstrated and promising tumor marker candidates including MCM7 are identified.
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Affiliation(s)
- Yi Zhu
- Westlake Institute for Advanced Study, Westlake University, Hangzhou, Zhejiang, P. R. China.,Department of Biology, Institute of Molecular Systems Biology, Eidgenössische Technische Hochschule (ETH) Zurich, Zurich, Switzerland
| | - Jiang Zhu
- Center for Stem Cell Research and Application, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, P. R. China
| | - Cong Lu
- Center for Stem Cell Research and Application, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, P. R. China
| | - Qiushi Zhang
- Westlake Institute for Advanced Study, Westlake University, Hangzhou, Zhejiang, P. R. China
| | - Wei Xie
- Center for Stem Cell Research and Application, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, P. R. China
| | - Ping Sun
- Department of Hepatobiliary Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, P. R. China
| | - Xiaochuan Dong
- Department of Pathology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, P. R. China
| | - Liang Yue
- Westlake Institute for Advanced Study, Westlake University, Hangzhou, Zhejiang, P. R. China
| | - Yaoting Sun
- Westlake Institute for Advanced Study, Westlake University, Hangzhou, Zhejiang, P. R. China
| | - Xiao Yi
- Westlake Institute for Advanced Study, Westlake University, Hangzhou, Zhejiang, P. R. China
| | - Tiansheng Zhu
- Westlake Institute for Advanced Study, Westlake University, Hangzhou, Zhejiang, P. R. China
| | - Guan Ruan
- Westlake Institute for Advanced Study, Westlake University, Hangzhou, Zhejiang, P. R. China
| | - Ruedi Aebersold
- Department of Biology, Institute of Molecular Systems Biology, Eidgenössische Technische Hochschule (ETH) Zurich, Zurich, Switzerland.,Faculty of Science, University of Zürich, Zürich, Switzerland
| | - Shi'ang Huang
- Center for Stem Cell Research and Application, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, P. R. China
| | - Tiannan Guo
- Westlake Institute for Advanced Study, Westlake University, Hangzhou, Zhejiang, P. R. China.,Department of Biology, Institute of Molecular Systems Biology, Eidgenössische Technische Hochschule (ETH) Zurich, Zurich, Switzerland
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12
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Mato JM, Elortza F, Lu SC, Brun V, Paradela A, Corrales FJ. Liver cancer-associated changes to the proteome: what deserves clinical focus? Expert Rev Proteomics 2018; 15:749-756. [PMID: 30204005 DOI: 10.1080/14789450.2018.1521277] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Abstract
INTRODUCTION Hepatocellular carcinoma (HCC) is recognized as the fifth most common neoplasm and currently represents the second leading form of cancer-related death worldwide. Despite great progress has been done in the understanding of its pathogenesis, HCC represents a heavy societal and economic burden as most patients are still diagnosed at advanced stages and the 5-year survival rate remain below 20%. Early detection and revolutionary therapies that rely on the discovery of new molecular biomarkers and therapeutic targets are therefore urgently needed to develop precision medicine strategies for a more efficient management of patients. Areas covered: This review intends to comprehensively analyse the proteomics-based research conducted in the last few years to address some of the principal still open riddles in HCC biology, based on the identification of molecular drivers of tumor progression and metastasis. Expert commentary: The technical advances in mass spectrometry experienced in the last decade have significantly improved the analytical capacity of proteome wide studies. Large-scale protein and protein variant (post-translational modifications) identification and quantification have allowed detailed dissections of molecular mechanisms underlying HCC progression and are already paving the way for the identification of clinically relevant proteins and the development of their use on patient care.
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Affiliation(s)
- José M Mato
- a CIC bioGUNE, CIBERehd, ProteoRed-ISCIII, Bizkaia Science and Technology Park , Derio , Spain.,b National Institute for the Study of Liver and Gastrointestinal Diseases (CIBERehd), Carlos III National Institute of Health , Madrid , Spain
| | - Félix Elortza
- a CIC bioGUNE, CIBERehd, ProteoRed-ISCIII, Bizkaia Science and Technology Park , Derio , Spain.,b National Institute for the Study of Liver and Gastrointestinal Diseases (CIBERehd), Carlos III National Institute of Health , Madrid , Spain
| | - Shelly C Lu
- c Division of Digestive and Liver Diseases , Cedars-Sinai Medical Center , LA , CA , USA
| | - Virginie Brun
- d Université Grenoble-Alpes, CEA, BIG, Biologie à Grande Echelle, Inserm , Grenoble , France
| | - Alberto Paradela
- e Functional Proteomics Laboratory , Centro Nacional de Biotecnología-CSIC, Proteored-ISCIII, CIBERehd , Madrid , Spain
| | - Fernando J Corrales
- b National Institute for the Study of Liver and Gastrointestinal Diseases (CIBERehd), Carlos III National Institute of Health , Madrid , Spain.,e Functional Proteomics Laboratory , Centro Nacional de Biotecnología-CSIC, Proteored-ISCIII, CIBERehd , Madrid , Spain
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13
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MALDI imaging: beyond classic diagnosis. BOLETIN MEDICO DEL HOSPITAL INFANTIL DE MEXICO 2017; 74:212-218. [PMID: 29382489 DOI: 10.1016/j.bmhimx.2017.03.004] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2017] [Revised: 03/21/2017] [Accepted: 03/28/2017] [Indexed: 02/04/2023] Open
Abstract
Mass spectrometry has been the focus of technology development and application for imaging for several decades. Imaging mass spectrometry using matrix-assisted laser desorption ionization is a new and effective tool for molecular studies of complex biological samples such as tissue sections. As histological features remain intact throughout the analysis of a section, distribution maps of multiple analytes can be correlated with histological and clinical features. Spatial molecular arrangements can be assessed without the need for target-specific reagents, allowing the discovery of diagnostic and prognostic markers of different cancer types and enabling the determination of effective therapies.
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Hinsch A, Buchholz M, Odinga S, Borkowski C, Koop C, Izbicki JR, Wurlitzer M, Krech T, Wilczak W, Steurer S, Jacobsen F, Burandt EC, Stahl P, Simon R, Sauter G, Schlüter H. MALDI imaging mass spectrometry reveals multiple clinically relevant masses in colorectal cancer using large-scale tissue microarrays. JOURNAL OF MASS SPECTROMETRY : JMS 2017; 52:165-173. [PMID: 28117928 DOI: 10.1002/jms.3916] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/12/2016] [Revised: 01/13/2017] [Accepted: 01/19/2017] [Indexed: 06/06/2023]
Abstract
For identification of clinically relevant masses to predict status, grade, relapse and prognosis of colorectal cancer, we applied Matrix-assisted laser desorption ionization (MALDI) imaging mass spectrometry (IMS) to a tissue micro array containing formalin-fixed and paraffin-embedded tissue samples from 349 patients. Analysis of our MALDI-IMS data revealed 27 different m/z signals associated with epithelial structures. Comparison of these signals showed significant association with status, grade and Ki-67 labeling index. Fifteen out of 27 IMS signals revealed a significant association with survival. For seven signals (m/z 654, 776, 788, 904, 944, 975 and 1013) the absence and for eight signals (m/z 643, 678, 836, 886, 898, 1095, 1459 and 1477) the presence were associated with decreased life expectancy, including five masses (m/z 788, 836, 904, 944 and 1013) that provided prognostic information independently from the established prognosticators pT and pN. Combination of these five masses resulted in a three-step classifier that provided prognostic information superior to univariate analysis. In addition, a total of 19 masses were associated with tumor stage, grade, metastasis and cell proliferation. Our data demonstrate the suitability of combining IMS and large-scale tissue micro arrays to simultaneously identify and validate clinically useful molecular marker. Copyright © 2017 John Wiley & Sons, Ltd.
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Affiliation(s)
- A Hinsch
- Department of Pathology, University Medical Center Hamburg-Eppendorf, Martinistr. 52, 20246, Hamburg, Germany
| | - M Buchholz
- Department of Pathology, University Medical Center Hamburg-Eppendorf, Martinistr. 52, 20246, Hamburg, Germany
| | - S Odinga
- Department of Pathology, University Medical Center Hamburg-Eppendorf, Martinistr. 52, 20246, Hamburg, Germany
| | - C Borkowski
- Department of Pathology, University Medical Center Hamburg-Eppendorf, Martinistr. 52, 20246, Hamburg, Germany
| | - C Koop
- Department of Pathology, University Medical Center Hamburg-Eppendorf, Martinistr. 52, 20246, Hamburg, Germany
| | - J R Izbicki
- Department of General, Visceral and Thoracic Surgery, University Medical Center Hamburg-Eppendorf, Martinistr. 52, 20246, Hamburg, Germany
| | - M Wurlitzer
- Dept. of Clinical Chemistry, University Medical Center Hamburg-Eppendorf, Martinistr. 52, 20246, Hamburg, Germany
| | - T Krech
- Department of Pathology, University Medical Center Hamburg-Eppendorf, Martinistr. 52, 20246, Hamburg, Germany
| | - W Wilczak
- Department of Pathology, University Medical Center Hamburg-Eppendorf, Martinistr. 52, 20246, Hamburg, Germany
| | - S Steurer
- Department of Pathology, University Medical Center Hamburg-Eppendorf, Martinistr. 52, 20246, Hamburg, Germany
| | - F Jacobsen
- Department of Pathology, University Medical Center Hamburg-Eppendorf, Martinistr. 52, 20246, Hamburg, Germany
| | - E-C Burandt
- Department of Pathology, University Medical Center Hamburg-Eppendorf, Martinistr. 52, 20246, Hamburg, Germany
| | - P Stahl
- Department of Pathology, University Medical Center Hamburg-Eppendorf, Martinistr. 52, 20246, Hamburg, Germany
| | - R Simon
- Department of Pathology, University Medical Center Hamburg-Eppendorf, Martinistr. 52, 20246, Hamburg, Germany
| | - G Sauter
- Department of Pathology, University Medical Center Hamburg-Eppendorf, Martinistr. 52, 20246, Hamburg, Germany
| | - H Schlüter
- Dept. of Clinical Chemistry, University Medical Center Hamburg-Eppendorf, Martinistr. 52, 20246, Hamburg, Germany
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15
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Ucal Y, Durer ZA, Atak H, Kadioglu E, Sahin B, Coskun A, Baykal AT, Ozpinar A. Clinical applications of MALDI imaging technologies in cancer and neurodegenerative diseases. BIOCHIMICA ET BIOPHYSICA ACTA-PROTEINS AND PROTEOMICS 2017; 1865:795-816. [PMID: 28087424 DOI: 10.1016/j.bbapap.2017.01.005] [Citation(s) in RCA: 41] [Impact Index Per Article: 5.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/01/2016] [Revised: 12/08/2016] [Accepted: 01/06/2017] [Indexed: 12/25/2022]
Abstract
Matrix-assisted laser desorption/ionization (MALDI) time-of-flight (TOF) imaging mass spectrometry (IMS) enables localization of analytes of interest along with histology. More specifically, MALDI-IMS identifies the distributions of proteins, peptides, small molecules, lipids, and drugs and their metabolites in tissues, with high spatial resolution. This unique capacity to directly analyze tissue samples without the need for lengthy sample preparation reduces technical variability and renders MALDI-IMS ideal for the identification of potential diagnostic and prognostic biomarkers and disease gradation. MALDI-IMS has evolved rapidly over the last decade and has been successfully used in both medical and basic research by scientists worldwide. In this review, we explore the clinical applications of MALDI-IMS, focusing on the major cancer types and neurodegenerative diseases. In particular, we re-emphasize the diagnostic potential of IMS and the challenges that must be confronted when conducting MALDI-IMS in clinical settings. 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)
- Yasemin Ucal
- Acibadem University, Department of Medical Biochemistry, School of Medicine, Istanbul, Turkey
| | - Zeynep Aslıhan Durer
- Acibadem University, Department of Medical Biochemistry, School of Medicine, Istanbul, Turkey
| | - Hakan Atak
- Acibadem University, Department of Medical Biochemistry, School of Medicine, Istanbul, Turkey
| | - Elif Kadioglu
- Acibadem University, Department of Medical Biochemistry, School of Medicine, Istanbul, Turkey
| | - Betul Sahin
- Acibadem University, Department of Medical Biochemistry, School of Medicine, Istanbul, Turkey
| | - Abdurrahman Coskun
- Acibadem University, Department of Medical Biochemistry, School of Medicine, Istanbul, Turkey
| | - Ahmet Tarık Baykal
- Acibadem University, Department of Medical Biochemistry, School of Medicine, Istanbul, Turkey
| | - Aysel Ozpinar
- Acibadem University, Department of Medical Biochemistry, School of Medicine, Istanbul, Turkey.
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16
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Arentz G, Mittal P, Zhang C, Ho YY, Briggs M, Winderbaum L, Hoffmann MK, Hoffmann P. Applications of Mass Spectrometry Imaging to Cancer. Adv Cancer Res 2017; 134:27-66. [PMID: 28110654 DOI: 10.1016/bs.acr.2016.11.002] [Citation(s) in RCA: 42] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
Pathologists play an essential role in the diagnosis and prognosis of benign and cancerous tumors. Clinicians provide tissue samples, for example, from a biopsy, which are then processed and thin sections are placed onto glass slides, followed by staining of the tissue with visible dyes. Upon processing and microscopic examination, a pathology report is provided, which relies on the pathologist's interpretation of the phenotypical presentation of the tissue. Targeted analysis of single proteins provide further insight and together with clinical data these results influence clinical decision making. Recent developments in mass spectrometry facilitate the collection of molecular information about such tissue specimens. These relatively new techniques generate label-free mass spectra across tissue sections providing nonbiased, nontargeted molecular information. At each pixel with spatial coordinates (x/y) a mass spectrum is acquired. The acquired mass spectrums can be visualized as intensity maps displaying the distribution of single m/z values of interest. Based on the sample preparation, proteins, peptides, lipids, small molecules, or glycans can be analyzed. The generated intensity maps/images allow new insights into tumor tissues. The technique has the ability to detect and characterize tumor cells and their environment in a spatial context and combined with histological staining, can be used to aid pathologists and clinicians in the diagnosis and management of cancer. Moreover, such data may help classify patients to aid therapy decisions and predict outcomes. The novel complementary mass spectrometry-based methods described in this chapter will contribute to the transformation of pathology services around the world.
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Affiliation(s)
- G Arentz
- Adelaide Proteomics Centre, School of Biological Sciences, University of Adelaide, Adelaide, SA, Australia; Institute for Photonics and Advanced Sensing (IPAS), University of Adelaide, Adelaide, SA, Australia
| | - P Mittal
- Adelaide Proteomics Centre, School of Biological Sciences, University of Adelaide, Adelaide, SA, Australia; Institute for Photonics and Advanced Sensing (IPAS), University of Adelaide, Adelaide, SA, Australia
| | - C Zhang
- Adelaide Proteomics Centre, School of Biological Sciences, University of Adelaide, Adelaide, SA, Australia; Institute for Photonics and Advanced Sensing (IPAS), University of Adelaide, Adelaide, SA, Australia
| | - Y-Y Ho
- Adelaide Proteomics Centre, School of Biological Sciences, University of Adelaide, Adelaide, SA, Australia
| | - M Briggs
- Adelaide Proteomics Centre, School of Biological Sciences, University of Adelaide, Adelaide, SA, Australia; Institute for Photonics and Advanced Sensing (IPAS), University of Adelaide, Adelaide, SA, Australia; ARC Centre for Nanoscale BioPhotonics (CNBP), University of Adelaide, Adelaide, SA, Australia
| | - L Winderbaum
- Adelaide Proteomics Centre, School of Biological Sciences, University of Adelaide, Adelaide, SA, Australia
| | - M K Hoffmann
- Adelaide Proteomics Centre, School of Biological Sciences, University of Adelaide, Adelaide, SA, Australia; Institute for Photonics and Advanced Sensing (IPAS), University of Adelaide, Adelaide, SA, Australia
| | - P Hoffmann
- Adelaide Proteomics Centre, School of Biological Sciences, University of Adelaide, Adelaide, SA, Australia; Institute for Photonics and Advanced Sensing (IPAS), University of Adelaide, Adelaide, SA, Australia.
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17
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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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18
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Longuespée R, Casadonte R, Kriegsmann M, Pottier C, Picard de Muller G, Delvenne P, Kriegsmann J, De Pauw E. MALDI mass spectrometry imaging: A cutting-edge tool for fundamental and clinical histopathology. Proteomics Clin Appl 2016; 10:701-19. [PMID: 27188927 DOI: 10.1002/prca.201500140] [Citation(s) in RCA: 54] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2015] [Revised: 04/07/2016] [Accepted: 05/13/2016] [Indexed: 01/16/2023]
Abstract
Histopathological diagnoses have been done in the last century based on hematoxylin and eosin staining. These methods were complemented by histochemistry, electron microscopy, immunohistochemistry (IHC), and molecular techniques. Mass spectrometry (MS) methods allow the thorough examination of various biocompounds in extracts and tissue sections. Today, mass spectrometry imaging (MSI), and especially matrix-assisted laser desorption ionization (MALDI) imaging links classical histology and molecular analyses. Direct mapping is a major advantage of the combination of molecular profiling and imaging. MSI can be considered as a cutting edge approach for molecular detection of proteins, peptides, carbohydrates, lipids, and small molecules in tissues. This review covers the detection of various biomolecules in histopathological sections by MSI. Proteomic methods will be introduced into clinical histopathology within the next few years.
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Affiliation(s)
- Rémi Longuespée
- Proteopath GmbH, Trier, Germany.,Mass Spectrometry Laboratory, GIGA-Research, Department of Chemistry, University of Liège, Liège, Belgium
| | | | - Mark Kriegsmann
- Institute of Pathology, University of Heidelberg, Heidelberg, Germany
| | - Charles Pottier
- Laboratory of Experimental Pathology, GIGA-Cancer, Department of Pathology, University of Liège, Liège, Belgium
| | | | - Philippe Delvenne
- Laboratory of Experimental Pathology, GIGA-Cancer, Department of Pathology, University of Liège, Liège, Belgium
| | - Jörg Kriegsmann
- Proteopath GmbH, Trier, Germany.,MVZ for Histology, Cytology and Molecular Diagnostics Trier, Trier, Germany
| | - Edwin De Pauw
- Mass Spectrometry Laboratory, GIGA-Research, Department of Chemistry, University of Liège, Liège, Belgium
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19
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Lahiri S, Sun N, Buck A, Imhof A, Walch A. MALDI imaging mass spectrometry as a novel tool for detecting histone modifications in clinical tissue samples. Expert Rev Proteomics 2016; 13:275-84. [DOI: 10.1586/14789450.2016.1146598] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023]
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20
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Josić D, Andjelković U. The Role of Proteomics in Personalized Medicine. Per Med 2016. [DOI: 10.1007/978-3-319-39349-0_9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
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21
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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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22
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Label-free alpha fetoprotein immunosensor established by the facile synthesis of a palladium–graphene nanocomposite. Biosens Bioelectron 2014; 61:245-50. [DOI: 10.1016/j.bios.2014.05.021] [Citation(s) in RCA: 55] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2014] [Revised: 05/08/2014] [Accepted: 05/08/2014] [Indexed: 01/28/2023]
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23
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Laouirem S, Le Faouder J, Alexandrov T, Mestivier D, Léger T, Baudin X, Mebarki M, Paradis V, Camadro JM, Bedossa P. Progression from cirrhosis to cancer is associated with early ubiquitin post-translational modifications: identification of new biomarkers of cirrhosis at risk of malignancy. J Pathol 2014; 234:452-63. [DOI: 10.1002/path.4398] [Citation(s) in RCA: 24] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2014] [Revised: 06/03/2014] [Accepted: 06/25/2014] [Indexed: 12/14/2022]
Affiliation(s)
- Samira Laouirem
- INSERM U773; Université Paris-Diderot, Sorbonne Paris Cité; Paris France
| | - Julie Le Faouder
- INSERM U773; Université Paris-Diderot, Sorbonne Paris Cité; Paris France
| | - Theodore Alexandrov
- Center for Industrial Mathematics; University of Bremen; Bremen 28359 Germany
- Steinbeis Innovation Center SCiLS Research; Richard-Dehmel-Strasse 69 28211 Bremen Germany
- SCiLS GmbH; Fahrenheitstrasse 1 28359 Bremen Germany
- Skaggs School of Pharmacy and Pharmaceutical Sciences; University of California San Diego; 9500 Gilman Drive La Jolla CA 92093 USA
| | - Denis Mestivier
- ‘Modeling in Integrative Biology’ Group, Jacques Monod Institute; UMR7592 CNRS - Université Paris Diderot, Sorbonne Paris Cité; 15 Rue Hélène Brion 75013 Paris France
| | - Thibaut Léger
- Structural and Functional Mass Spectrometry Facility; Jacques Monod Institute, UMR7592 CNRS - Université Paris Diderot; Sorbonne Paris Cité, 15 Rue Hélène Brion 75013 Paris France
| | - Xavier Baudin
- ImagoSeine Facility, Jacques Monod Institute; UMR7592 CNRS - Université Paris Diderot, Sorbonne Paris Cité; 15 Rue Hélène Brion 75013 Paris France
| | - Mouniya Mebarki
- INSERM U773; Université Paris-Diderot, Sorbonne Paris Cité; Paris France
| | - Valérie Paradis
- INSERM U773; Université Paris-Diderot, Sorbonne Paris Cité; Paris France
- Pathology Department, Beaujon Hospital; Assistance Publique-Hôpitaux de Paris; Clichy France
| | - Jean-Michel Camadro
- Structural and Functional Mass Spectrometry Facility; Jacques Monod Institute, UMR7592 CNRS - Université Paris Diderot; Sorbonne Paris Cité, 15 Rue Hélène Brion 75013 Paris France
- ‘Mitochondria, Metals and Oxidative Stress’ Group, Jacques Monod Institute; UMR7592 CNRS - Université Paris Diderot; Sorbonne Paris Cité, 15 Rue Hélène Brion 75013 Paris France
| | - Pierre Bedossa
- INSERM U773; Université Paris-Diderot, Sorbonne Paris Cité; Paris France
- Pathology Department, Beaujon Hospital; Assistance Publique-Hôpitaux de Paris; Clichy France
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MALDI-ToF mass spectrometry for the rapid diagnosis of cancerous lung nodules. PLoS One 2014; 9:e97511. [PMID: 24830707 PMCID: PMC4022527 DOI: 10.1371/journal.pone.0097511] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2013] [Accepted: 04/16/2014] [Indexed: 01/03/2023] Open
Abstract
Recently, tissue-based methods for proteomic analysis have been used in clinical research and appear reliable for digestive, brain, lymphomatous, and lung cancers classification. However simple, tissue-based methods that couple signal analysis to tissue imaging are time consuming. To assess the reliability of a method involving rapid tissue preparation and analysis to discriminate cancerous from non-cancerous tissues, we tested 141 lung cancer/non-tumor pairs and 8 unique lung cancer samples among the stored frozen samples of 138 patients operated on during 2012. Samples were crushed in water, and 1.5 µl was spotted onto a steel target for analysis with the Microflex LT analyzer (Bruker Daltonics). Spectra were analyzed using ClinProTools software. A set of samples was used to generate a random classification model on the basis of a list of discriminant peaks sorted with the k-nearest neighbor genetic algorithm. The rest of the samples (n = 43 cancerous and n = 41 non-tumoral) was used to verify the classification capability and calculate the diagnostic performance indices relative to the histological diagnosis. The analysis found 53 m/z valid peaks, 40 of which were significantly different between cancerous and non-tumoral samples. The selected genetic algorithm model identified 20 potential peaks from the training set and had 98.81% recognition capability and 89.17% positive predictive value. In the blinded set, this method accurately discriminated the two classes with a sensitivity of 86.7% and a specificity of 95.1% for the cancer tissues and a sensitivity of 87.8% and a specificity of 95.3% for the non-tumor tissues. The second model generated to discriminate primary lung cancer from metastases was of lower quality. The reliability of MALDI-ToF analysis coupled with a very simple lung preparation procedure appears promising and should be tested in the operating room on fresh samples coupled with the pathological examination.
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Le Faouder J, Laouirem S, Alexandrov T, Ben-Harzallah S, Léger T, Albuquerque M, Bedossa P, Paradis V. Tumoral heterogeneity of hepatic cholangiocarcinomas revealed by MALDI imaging mass spectrometry. Proteomics 2014; 14:965-72. [DOI: 10.1002/pmic.201300463] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2013] [Revised: 01/24/2014] [Accepted: 01/27/2014] [Indexed: 01/29/2023]
Affiliation(s)
- Julie Le Faouder
- Claude Bernard Institute; Paris-Diderot University; Paris France
- INSERM U773; Biomedical Research Center; Paris-Diderot University; Paris France
| | - Samira Laouirem
- INSERM U773; Biomedical Research Center; Paris-Diderot University; Paris France
| | - Theodore Alexandrov
- Center for Industrial Mathematics; University of Bremen; Bremen Germany
- Steinbeis Innovation Center SCiLS Research; Bremen Germany
- SCiLS GmbH; Bremen Germany
- Skaggs School of Pharmacy and Pharmaceutical Sciences; University of California San Diego; La Jolla CA USA
| | | | - Thibaut Léger
- Mass Spectrometry Facility; Jacques Monod Institute; UMR7592-CNRS; University Paris-Diderot; Paris France
| | - Miguel Albuquerque
- Pathology Department; Beaujon Hospital; Assistance Publique-Hôpitaux de Paris; Clichy France
| | - Pierre Bedossa
- INSERM U773; Biomedical Research Center; Paris-Diderot University; Paris France
- Pathology Department; Beaujon Hospital; Assistance Publique-Hôpitaux de Paris; Clichy France
| | - Valérie Paradis
- INSERM U773; Biomedical Research Center; Paris-Diderot University; Paris France
- Pathology Department; Beaujon Hospital; Assistance Publique-Hôpitaux de Paris; Clichy France
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26
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Beyoğlu D, Idle JR. Painting the liver with lasers: the future of liver histology? Hepatology 2014; 59:757-60. [PMID: 24009190 DOI: 10.1002/hep.26734] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/09/2013] [Revised: 08/27/2013] [Accepted: 08/29/2013] [Indexed: 12/16/2022]
Affiliation(s)
- Diren Beyoğlu
- Hepatology Research Group, Department of Clinical Research, University of Bern, Bern, Switzerland
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Morita Y, Sakaguchi T, Ikegami K, Goto-Inoue N, Hayasaka T, Hang VT, Tanaka H, Harada T, Shibasaki Y, Suzuki A, Fukumoto K, Inaba K, Murakami M, Setou M, Konno H. Lysophosphatidylcholine acyltransferase 1 altered phospholipid composition and regulated hepatoma progression. J Hepatol 2013; 59:292-9. [PMID: 23567080 DOI: 10.1016/j.jhep.2013.02.030] [Citation(s) in RCA: 111] [Impact Index Per Article: 10.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/04/2012] [Revised: 02/08/2013] [Accepted: 02/18/2013] [Indexed: 01/12/2023]
Abstract
BACKGROUND & AIMS Several lipid synthesis pathways play important roles in the development and progression of hepatocellular carcinoma (HCC), although the precise molecular mechanisms remain to be elucidated. Here, we show the relationship between HCC progression and alteration of phospholipid composition regulated by lysophosphatidylcholine acyltransferase (LPCAT). METHODS Molecular lipidomic screening was performed by imaging mass spectrometry (IMS) in 37 resected HCC specimens. RT-PCR and Western blotting were carried out to examine the mRNA and protein levels of LPCATs, which catalyze the conversion of lysophosphatidylcholine (LPC) into phosphatidylcholine (PC) and have substrate specificity for some kinds of fatty acids. We examined the effect of LPCAT1 overexpression or knockdown on cell proliferation, migration, and invasion in HCC cell lines. RESULTS IMS revealed the increase of PC species with palmitoleic acid or oleic acid at the sn-2-position and the reduction of LPC with palmitic acid at the sn-1-position in HCC tissues. mRNA and protein of LPCAT1, responsible for LPC to PC conversion, were more abundant in HCCs than in the surrounding parenchyma. In cell line experiments, LPCAT1 overexpression enriched PCs observed in IMS and promoted cell proliferation, migration, and invasion. LPCAT1 knockdown did viceversa. CONCLUSIONS Enrichment or depletion of some specific PCs, was found in HCC by IMS. Alteration of phospholipid composition in HCC would affect tumor character. LPCAT1 modulates phospholipid composition to create favorable conditions to HCC cells. LPCAT1 is a potent target molecule to inhibit HCC progression.
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Affiliation(s)
- Yoshifumi Morita
- Second Department of Surgery, Hamamatsu University School of Medicine, Japan
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28
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Quaas A, Bahar AS, von Loga K, Seddiqi AS, Singer JM, Omidi M, Kraus O, Kwiatkowski M, Trusch M, Minner S, Burandt E, Stahl P, Wilczak W, Wurlitzer M, Simon R, Sauter G, Marx A, Schlüter H. MALDI imaging on large-scale tissue microarrays identifies molecular features associated with tumour phenotype in oesophageal cancer. Histopathology 2013; 63:455-62. [PMID: 23855813 DOI: 10.1111/his.12193] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2013] [Accepted: 05/15/2013] [Indexed: 01/06/2023]
Abstract
AIMS Matrix-assisted laser desorption/ionisation mass spectrometry imaging (MALDI-MSI) and tissue microarray (TMA) technologies were jointly utilized to search for molecular features associated with clinicopathological parameters in oesophageal cancer. METHODS AND RESULTS Two TMAs from formalin-fixed tissue samples, including 300 adenocarcinomas and 177 squamous cell carcinomas with clinical follow-up data, were analysed. MALDI-MSI analysis revealed 72 distinct mass per charge (m/z) signals associated with tumour cells, 48 of which were found in squamous cell carcinomas only, and 12 of which were specific for adenocarcinomas. In adenocarcinomas, six signals were linked to early-stage (pT1-T2) tumours (two signals) and the presence (one signal) or absence (three signals) of lymph node metastasis. In squamous cell carcinomas, 24 signals were strongly linked to different phenotypic features, including tumour stage (four signals), histological grade (four signals), and lymph node metastasis (three signals). CONCLUSIONS The high number of m/z signals that were found to be significantly linked to one or more phenotypic features of oesophageal cancer highlights the power of MALDI-MSI in the analysis of high-density TMAs. The data also emphasise substantial biological differences between adenocarcinomas and squamous cell carcinomas.
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Affiliation(s)
- Alexander Quaas
- Institute of Pathology, University of Hamburg, Hamburg, Germany
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Angel PM, Caprioli RM. Matrix-assisted laser desorption ionization imaging mass spectrometry: in situ molecular mapping. Biochemistry 2013; 52:3818-28. [PMID: 23259809 PMCID: PMC3864574 DOI: 10.1021/bi301519p] [Citation(s) in RCA: 103] [Impact Index Per Article: 9.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/08/2023]
Abstract
Matrix-assisted laser desorption ionization imaging mass spectrometry (IMS) is a relatively new imaging modality that allows mapping of a wide range of biomolecules within a thin tissue section. The technology uses a laser beam to directly desorb and ionize molecules from discrete locations on the tissue that are subsequently recorded in a mass spectrometer. IMS is distinguished by the ability to directly measure molecules in situ ranging from small metabolites to proteins, reporting hundreds to thousands of expression patterns from a single imaging experiment. This article reviews recent advances in IMS technology, applications, and experimental strategies that allow it to significantly aid in the discovery and understanding of molecular processes in biological and clinical samples.
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Affiliation(s)
- Peggi M. Angel
- Mass Spectrometry Research Center and Department of Biochemistry, Vanderbilt University Medical Center, 465 21st Avenue South, MRB III Suite 9160, Nashville, Tennessee 37232, United States
| | - Richard M. Caprioli
- Mass Spectrometry Research Center and Department of Biochemistry, Medicine, Pharmacology, and Chemistry, Vanderbilt University Medical Center, 465 21st Avenue South, MRB III Suite 9160, Nashville, Tennessee 37232, United States
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30
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Megger DA, Bracht T, Kohl M, Ahrens M, Naboulsi W, Weber F, Hoffmann AC, Stephan C, Kuhlmann K, Eisenacher M, Schlaak JF, Baba HA, Meyer HE, Sitek B. Proteomic differences between hepatocellular carcinoma and nontumorous liver tissue investigated by a combined gel-based and label-free quantitative proteomics study. Mol Cell Proteomics 2013; 12:2006-20. [PMID: 23462207 DOI: 10.1074/mcp.m113.028027] [Citation(s) in RCA: 93] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022] Open
Abstract
Proteomics-based clinical studies have been shown to be promising strategies for the discovery of novel biomarkers of a particular disease. Here, we present a study of hepatocellular carcinoma (HCC) that combines complementary two-dimensional difference in gel electrophoresis (2D-DIGE) and liquid chromatography (LC-MS)-based approaches of quantitative proteomics. In our proteomic experiments, we analyzed a set of 14 samples (7 × HCC versus 7 × nontumorous liver tissue) with both techniques. Thereby we identified 573 proteins that were differentially expressed between the experimental groups. Among these, only 51 differentially expressed proteins were identified irrespective of the applied approach. Using Western blotting and immunohistochemical analysis the regulation patterns of six selected proteins from the study overlap (inorganic pyrophosphatase 1 (PPA1), tumor necrosis factor type 1 receptor-associated protein 1 (TRAP1), betaine-homocysteine S-methyltransferase 1 (BHMT)) were successfully verified within the same sample set. In addition, the up-regulations of selected proteins from the complements of both approaches (major vault protein (MVP), gelsolin (GSN), chloride intracellular channel protein 1 (CLIC1)) were also reproducible. Within a second independent verification set (n = 33) the altered protein expression levels of major vault protein and betaine-homocysteine S-methyltransferase were further confirmed by Western blots quantitatively analyzed via densitometry. For the other candidates slight but nonsignificant trends were detectable in this independent cohort. Based on these results we assume that major vault protein and betaine-homocysteine S-methyltransferase have the potential to act as diagnostic HCC biomarker candidates that are worth to be followed in further validation studies.
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Affiliation(s)
- Dominik A Megger
- Medizinisches Proteom-Center, Ruhr-Universität Bochum, Bochum, Germany
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31
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Steurer S, Borkowski C, Odinga S, Buchholz M, Koop C, Huland H, Becker M, Witt M, Trede D, Omidi M, Kraus O, Bahar AS, Seddiqi AS, Singer JM, Kwiatkowski M, Trusch M, Simon R, Wurlitzer M, Minner S, Schlomm T, Sauter G, Schlüter H. MALDI mass spectrometric imaging based identification of clinically relevant signals in prostate cancer using large-scale tissue microarrays. Int J Cancer 2013; 133:920-8. [DOI: 10.1002/ijc.28080] [Citation(s) in RCA: 51] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2012] [Accepted: 01/21/2013] [Indexed: 12/27/2022]
Affiliation(s)
- Stefan Steurer
- Institute of Pathology; University Medical Center Hamburg-Eppendorf; Germany
| | - Carina Borkowski
- Institute of Pathology; University Medical Center Hamburg-Eppendorf; Germany
| | - Sinje Odinga
- Institute of Pathology; University Medical Center Hamburg-Eppendorf; Germany
| | - Malte Buchholz
- Institute of Pathology; University Medical Center Hamburg-Eppendorf; Germany
| | - Christina Koop
- Institute of Pathology; University Medical Center Hamburg-Eppendorf; Germany
| | - Hartwig Huland
- Martini-Clinic at University Medical Center Hamburg-Eppendorf; Germany
| | | | | | - Dennis Trede
- Steinbeis Innovation Center SCiLS (Scientific Computing in Life Sciences); Bremen; Germany
| | - Maryam Omidi
- Institute of Clinical Chemistry; Mass Spectrometric Proteomics; University Medical Center Hamburg-Eppendorf; Germany
| | - Olga Kraus
- Institute of Clinical Chemistry; Mass Spectrometric Proteomics; University Medical Center Hamburg-Eppendorf; Germany
| | - Ahmad S. Bahar
- Institute of Pathology; University Medical Center Hamburg-Eppendorf; Germany
| | - A. Shoaib Seddiqi
- Institute of Pathology; University Medical Center Hamburg-Eppendorf; Germany
| | - Julius M. Singer
- Institute of Pathology; University Medical Center Hamburg-Eppendorf; Germany
| | - Marcel Kwiatkowski
- Institute of Clinical Chemistry; Mass Spectrometric Proteomics; University Medical Center Hamburg-Eppendorf; Germany
| | - Maria Trusch
- Institute of Organic Chemistry; Mass Spectrometry; University of Hamburg; Germany
| | - Ronald Simon
- Institute of Pathology; University Medical Center Hamburg-Eppendorf; Germany
| | - Marcus Wurlitzer
- Institute of Clinical Chemistry; Mass Spectrometric Proteomics; University Medical Center Hamburg-Eppendorf; Germany
| | - Sarah Minner
- Institute of Pathology; University Medical Center Hamburg-Eppendorf; Germany
| | - Thorsten Schlomm
- Martini-Clinic at University Medical Center Hamburg-Eppendorf; Germany
| | - Guido Sauter
- Institute of Pathology; University Medical Center Hamburg-Eppendorf; Germany
| | - Hartmut Schlüter
- Institute of Clinical Chemistry; Mass Spectrometric Proteomics; University Medical Center Hamburg-Eppendorf; Germany
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Quanico J, Franck J, Dauly C, Strupat K, Dupuy J, Day R, Salzet M, Fournier I, Wisztorski M. Development of liquid microjunction extraction strategy for improving protein identification from tissue sections. J Proteomics 2013; 79:200-18. [DOI: 10.1016/j.jprot.2012.11.025] [Citation(s) in RCA: 78] [Impact Index Per Article: 7.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2012] [Revised: 11/20/2012] [Accepted: 11/30/2012] [Indexed: 12/22/2022]
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Lagarrigue M, Alexandrov T, Dieuset G, Perrin A, Lavigne R, Baulac S, Thiele H, Martin B, Pineau C. New Analysis Workflow for MALDI Imaging Mass Spectrometry: Application to the Discovery and Identification of Potential Markers of Childhood Absence Epilepsy. J Proteome Res 2012; 11:5453-63. [DOI: 10.1021/pr3006974] [Citation(s) in RCA: 29] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Affiliation(s)
- Mélanie Lagarrigue
- Inserm U1085, IRSET, Proteomics Core Facility Biogenouest, Campus de Beaulieu,
F-35042 Rennes, France
| | - Theodore Alexandrov
- Center for Industrial Mathematics, University of Bremen, 28359 Bremen, Germany
- Steinbeis Innovation Center SCiLS, Richard-Dehmel-Str. 69 D, 28211
Bremen, Germany
| | - Gabriel Dieuset
- INSERM U1099, F-35000 Rennes, France
- Université de Rennes 1, LTSI, F-35000 Rennes, France
| | - Aline Perrin
- Inserm UMR S975/CNRS UMR 7225, Centre
de Recherche de l’Institut du Cerveau et de la Moelle Épinière,
Université Pierre et Marie Curie, Hôpital de la Pitié-Salpêtrière, F-75013
Paris, France
| | - Régis Lavigne
- Inserm U1085, IRSET, Proteomics Core Facility Biogenouest, Campus de Beaulieu,
F-35042 Rennes, France
| | - Stéphanie Baulac
- Inserm UMR S975/CNRS UMR 7225, Centre
de Recherche de l’Institut du Cerveau et de la Moelle Épinière,
Université Pierre et Marie Curie, Hôpital de la Pitié-Salpêtrière, F-75013
Paris, France
| | - Herbert Thiele
- Steinbeis Innovation Center SCiLS, Richard-Dehmel-Str. 69 D, 28211
Bremen, Germany
| | - Benoit Martin
- INSERM U1099, F-35000 Rennes, France
- Université de Rennes 1, LTSI, F-35000 Rennes, France
| | - Charles Pineau
- Inserm U1085, IRSET, Proteomics Core Facility Biogenouest, Campus de Beaulieu,
F-35042 Rennes, France
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Morgan TM, Seeley EH, Fadare O, Caprioli RM, Clark PE. Imaging the clear cell renal cell carcinoma proteome. J Urol 2012; 189:1097-103. [PMID: 23009866 DOI: 10.1016/j.juro.2012.09.074] [Citation(s) in RCA: 39] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 09/11/2012] [Indexed: 11/19/2022]
Abstract
PURPOSE A key barrier to identifying tissue biomarkers of clear cell renal cell carcinoma is the heterogeneity of protein expression in tissue. However, by providing spectra for every 0.05 mm(2) area of tissue, imaging mass spectrometry reveals the spatial distribution of peptides. We determined whether this approach could be used to identify and map protein signatures of clear cell renal cell carcinoma. MATERIALS AND METHODS We constructed 2 tissue microarrays with 2 cores each of matched tumor and normal tissue from the nephrectomy specimens of 70 patients with clear cell renal cell carcinoma. Samples were analyzed by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry. In each tissue microarray peptide signatures were identified that differentiated cancer from normal tissue. The signatures were then cross validated. Mass spectrometry/mass spectrometry sequencing was performed to determine the identity of select, differentially expressed peptides. Immunohistochemistry was used for validation. RESULTS In each tissue microarray peptide signatures were identified that had 94.7% to 98.5% classification accuracy for each 0.05 mm(2) spot (spectrum) and 96.9% to 100% accuracy for each tissue core. Cross validation across tissue microarrays revealed a classification accuracy of 82.6% to 84.7% for each spot and 88.9% to 92.4% for each core. We identified vimentin, histone 2A.X and α-enolase as proteins with greater expression in cancer tissue. This was validated by immunohistochemistry. CONCLUSIONS Imaging mass spectrometry identified and mapped specific peptides that accurately distinguished malignant from normal renal tissue. This demonstrates its potential as a novel, high throughput approach to clear cell renal cell carcinoma biomarker discovery. Given the multiple pathways and known heterogeneity involved in tumors such as clear cell renal cell carcinoma, multiple peptide signatures that maintain their spatial relationships may outperform traditional protein biomarkers.
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Affiliation(s)
- Todd M Morgan
- Department of Urologic Surgery, Vanderbilt University Medical Center, Nashville, Tennessee.
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35
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Balluff B, Rauser S, Ebert MP, Siveke JT, Höfler H, Walch A. Direct molecular tissue analysis by MALDI imaging mass spectrometry in the field of gastrointestinal disease. Gastroenterology 2012; 143:544-549.e2. [PMID: 22820311 DOI: 10.1053/j.gastro.2012.07.022] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Affiliation(s)
- Benjamin Balluff
- Institute of Pathology, Research Unit Analytical Pathology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany; Department of Medicine II, Klinikum rechts der Isar, Technische Universität München, Munich, Germany
| | - Sandra Rauser
- Institute of Pathology, Research Unit Analytical Pathology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Matthias P Ebert
- Department of Medicine II, Universitätsklinikum Mannheim, University of Heidelberg, Mannheim, Germany
| | - Jens T Siveke
- Department of Medicine II, Klinikum rechts der Isar, Technische Universität München, Munich, Germany
| | - Heinz Höfler
- Institute of Pathology, Research Unit Analytical Pathology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany; Institute of Pathology, Technische Universität München, Munich, Germany
| | - Axel Walch
- Institute of Pathology, Research Unit Analytical Pathology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany.
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36
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Meding S, Nitsche U, Balluff B, Elsner M, Rauser S, Schöne C, Nipp M, Maak M, Feith M, Ebert MP, Friess H, Langer R, Höfler H, Zitzelsberger H, Rosenberg R, Walch A. Tumor classification of six common cancer types based on proteomic profiling by MALDI imaging. J Proteome Res 2012; 11:1996-2003. [PMID: 22224404 DOI: 10.1021/pr200784p] [Citation(s) in RCA: 112] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
In clinical diagnostics, it is of outmost importance to correctly identify the source of a metastatic tumor, especially if no apparent primary tumor is present. Tissue-based proteomics might allow correct tumor classification. As a result, we performed MALDI imaging to generate proteomic signatures for different tumors. These signatures were used to classify common cancer types. At first, a cohort comprised of tissue samples from six adenocarcinoma entities located at different organ sites (esophagus, breast, colon, liver, stomach, thyroid gland, n = 171) was classified using two algorithms for a training and test set. For the test set, Support Vector Machine and Random Forest yielded overall accuracies of 82.74 and 81.18%, respectively. Then, colon cancer liver metastasis samples (n = 19) were introduced into the classification. The liver metastasis samples could be discriminated with high accuracy from primary tumors of colon cancer and hepatocellular carcinoma. Additionally, colon cancer liver metastasis samples could be successfully classified by using colon cancer primary tumor samples for the training of the classifier. These findings demonstrate that MALDI imaging-derived proteomic classifiers can discriminate between different tumor types at different organ sites and in the same site.
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Affiliation(s)
- Stephan Meding
- Institute of Pathology, Helmholtz Zentrum München , Neuherberg, Germany
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Abstract
Imaging MS (IMS) is generating tremendous interest in scientific communities because of its unparalleled capabilities to provide chemical analysis of intact tissue. Advances in analytical chemistry and MS are providing new insights into chemical and biological processes. This review will discuss various IMS platforms and their applications in biomedical and pharmaceutical research.
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