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Bech JM, Terkelsen T, Bartels AS, Coscia F, Doll S, Zhao S, Zhang Z, Brünner N, Lindebjerg J, Madsen GI, Fang X, Mann M, Afonso Moreira JM. Proteomic Profiling of Colorectal Adenomas Identifies a Predictive Risk Signature for Development of Metachronous Advanced Colorectal Neoplasia. Gastroenterology 2023:S0016-5085(23)00507-3. [PMID: 36966943 DOI: 10.1053/j.gastro.2023.03.208] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/23/2023] [Revised: 03/09/2023] [Accepted: 03/14/2023] [Indexed: 04/17/2023]
Abstract
BACKGROUND AND AIMS Colonic adenomatous polyps, or adenomas, are frequent precancerous lesions and the origin of most cases of colorectal adenocarcinoma. However, we know from epidemiologic studies that although most colorectal cancers (CRCs) originate from adenomas, only a small fraction of adenomas (3%-5%) ever progress to cancer. At present, there are no molecular markers to guide follow-up surveillance programs. METHODS We profiled, by mass spectrometry-based proteomics combined with machine learning analysis, a selected cohort of formalin-fixed, paraffin-embedded high-grade (HG) adenomas with long clinical follow-up, collected as part of the Danish national screening program. We grouped subjects in the cohort according to their subsequent history of findings: a nonmetachronous advanced neoplasia group (G0), with no new HG adenomas or CRCs up to 10 years after polypectomy, and a metachronous advanced neoplasia group (G1) where individuals developed a new HG adenoma or CRC within 5 years of diagnosis. RESULTS We generated a proteome dataset from 98 selected HG adenoma samples, including 20 technical replicates, of which 45 samples belonged to the nonmetachronous advanced neoplasia group and 53 to the metachronous advanced neoplasia group. The clear distinction of these 2 groups seen in a Uniform Manifold Approximation and Projection plot indicated that the information contained within the abundance of the ∼5000 proteins was sufficient to predict the future occurrence of HG adenomas or development of CRC. CONCLUSIONS We performed an in-depth analysis of quantitative proteomic data from 98 resected adenoma samples using various novel algorithms and statistical packages and found that their proteome can predict development of metachronous advanced lesions and progression several years in advance.
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Affiliation(s)
- Jacob Mathias Bech
- Department of Drug Design and Pharmacology, University of Copenhagen, Copenhagen, Denmark; Sino-Danish Center for Education and Research, Aarhus University, Denmark
| | - Thilde Terkelsen
- Center for Health Data Science, University of Copenhagen, Copenhagen, Denmark
| | | | - Fabian Coscia
- Spatial Proteomics Group, Max-Delbrück-Centrum for Molecular Medicine in the Helmholtz Association, Berlin, Germany; Proteomics Program, Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | | | - Siqi Zhao
- Beijing Institute of Genomics, China National Center for Bioinformation, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Beijing, China
| | - Zhaojun Zhang
- Beijing Institute of Genomics, China National Center for Bioinformation, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Beijing, China
| | - Nils Brünner
- Department of Drug Design and Pharmacology, University of Copenhagen, Copenhagen, Denmark
| | - Jan Lindebjerg
- Department of Pathology, Lillebaelt Hospital, Vejle Hospital, Vejle, Denmark
| | | | - Xiangdong Fang
- Beijing Institute of Genomics, China National Center for Bioinformation, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Beijing, China
| | - Matthias Mann
- Proteomics Program, Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
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Coscia F, Doll S, Bech JM, Schweizer L, Mund A, Lengyel E, Lindebjerg J, Madsen GI, Moreira JM, Mann M. A streamlined mass spectrometry-based proteomics workflow for large-scale FFPE tissue analysis. J Pathol 2020; 251:100-112. [PMID: 32154592 DOI: 10.1002/path.5420] [Citation(s) in RCA: 86] [Impact Index Per Article: 21.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2019] [Revised: 03/02/2020] [Accepted: 03/04/2020] [Indexed: 12/15/2022]
Abstract
Formalin fixation and paraffin-embedding (FFPE) is the most common method to preserve human tissue for clinical diagnosis, and FFPE archives represent an invaluable resource for biomedical research. Proteins in FFPE material are stable over decades but their efficient extraction and streamlined analysis by mass spectrometry (MS)-based proteomics has so far proven challenging. Herein we describe a MS-based proteomic workflow for quantitative profiling of large FFPE tissue cohorts directly from histopathology glass slides. We demonstrate broad applicability of the workflow to clinical pathology specimens and variable sample amounts, including low-input cancer tissue isolated by laser microdissection. Using state-of-the-art data dependent acquisition (DDA) and data independent acquisition (DIA) MS workflows, we consistently quantify a large part of the proteome in 100 min single-run analyses. In an adenoma cohort comprising more than 100 samples, total workup took less than a day. We observed a moderate trend towards lower protein identification in long-term stored samples (>15 years), but clustering into distinct proteomic subtypes was independent of archival time. Our results underscore the great promise of FFPE tissues for patient phenotyping using unbiased proteomics and they prove the feasibility of analyzing large tissue cohorts in a robust, timely, and streamlined manner. © 2020 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of Pathological Society of Great Britain and Ireland.
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Affiliation(s)
- Fabian Coscia
- Clinical Proteomics Group, The Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark.,Department of Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, Martinsried, Germany
| | - Sophia Doll
- Department of Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, Martinsried, Germany
| | - Jacob Mathias Bech
- Section for Molecular Disease Biology, Department of Drug Design and Pharmacology, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Lisa Schweizer
- Department of Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, Martinsried, Germany
| | - Andreas Mund
- Department of Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, Martinsried, Germany
| | - Ernst Lengyel
- Department of Obstetrics and Gynecology, Section of Gynecologic Oncology, University of Chicago, Chicago, IL, USA
| | - Jan Lindebjerg
- Lillebaelt Hospital, Vejle Hospital, Department of Pathology, Vejle, Denmark
| | | | - José Ma Moreira
- Section for Molecular Disease Biology, Department of Drug Design and Pharmacology, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Matthias Mann
- Clinical Proteomics Group, The Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark.,Department of Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, Martinsried, Germany
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