Novel Autoantibody Signatures in Sera of Patients with Pancreatic Cancer, Chronic Pancreatitis and Autoimmune Pancreatitis: A Protein Microarray Profiling Approach

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Version: author
License: CC BY 4.0
Serval ID
serval:BIB_47438984F688
Type
Article: article from journal or magazin.
Collection
Publications
Institution
Title
Novel Autoantibody Signatures in Sera of Patients with Pancreatic Cancer, Chronic Pancreatitis and Autoimmune Pancreatitis: A Protein Microarray Profiling Approach
Journal
International Journal of Molecular Sciences
Author(s)
Ghassem-Zadeh Sahar, Hufnagel Katrin, Bauer Andrea, Frossard Jean-Louis, Yoshida Masaru, Kutsumi Hiromu, Acha-Orbea Hans, Neulinger-Muñoz Matthias, Vey Johannes, Eckert Christoph, Strobel Oliver, Hoheisel Jörg D., Felix Klaus
ISSN
1422-0067
ISSN-L
1422-0067
Publication state
Published
Issued date
31/03/2020
Peer-reviewed
Oui
Volume
21
Number
7
Pages
2403
Language
english
Notes
Publication types: Journal Article
Publication Status: epublish
Abstract
Identification of disease-associated autoantibodies is of high importance. Their assessment could complement current diagnostic modalities and assist the clinical management of patients. We aimed at developing and validating high-throughput protein microarrays able to screen patients' sera to determine disease-specific autoantibody-signatures for pancreatic cancer (PDAC), chronic pancreatitis (CP), autoimmune pancreatitis and their subtypes (AIP-1 and AIP-2). In-house manufactured microarrays were used for autoantibody-profiling of IgG-enriched preoperative sera from PDAC-, CP-, AIP-1-, AIP-2-, other gastrointestinal disease (GID) patients and healthy controls. As a top-down strategy, three different fluorescence detection-based protein-microarrays were used: large with 6400, intermediate with 345, and small with 36 full-length human recombinant proteins. Large-scale analysis revealed 89 PDAC, 98 CP and 104 AIP immunogenic antigens. Narrowing the selection to 29 autoantigens using pooled sera first and individual sera afterwards allowed a discrimination of CP and AIP from PDAC. For validation, predictive models based on the identified antigens were generated which enabled discrimination between PDAC and AIP-1 or AIP-2 yielded high AUC values of 0.940 and 0.925, respectively. A new repertoire of autoantigens was identified and their assembly as a multiplex test will provide a fast and cost-effective tool for differential diagnosis of pancreatic diseases with high clinical relevance.
Keywords
Physical and Theoretical Chemistry, Inorganic Chemistry, Organic Chemistry, Spectroscopy, Molecular Biology, Catalysis, General Medicine, Computer Science Applications
Pubmed
Web of science
Open Access
Yes
Create date
25/04/2020 21:50
Last modification date
08/07/2021 5:37
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