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dc.contributor.authorBader, Luciusen_US
dc.date.accessioned2020-09-08T07:33:01Z
dc.date.available2020-09-08T07:33:01Z
dc.date.issued2020-09-16
dc.date.submitted2020-09-01T07:33:30.261Z
dc.identifiercontainer/63/f3/b6/60/63f3b660-f196-4f61-8db7-2c98971f5054
dc.identifier.isbn9788230852309en_US
dc.identifier.isbn9788230856031en_US
dc.identifier.urihttps://hdl.handle.net/1956/24065
dc.description.abstractIntroduction: Rheumatoid arthritis (RA) is a chronic inflammatory disease, characterized by synovial inflammation that, if not treated early and efficiently, causes joint damage. The proinflammatory cytokine tumor necrosis factor (TNF) plays a central role in the pathogenesis of RA and is the target of treatment with TNF inhibitors. TNF inhibitors are generally effective and well-tolerated. However, up to one-third of patients are primary non-responders, and responses in up to one-third of initial responders abate over time. Currently, there are no predictive biomarkers for treatment with TNF inhibitors. TNF inhibitor drug levels and anti-drug antibodies (ADAb) are indicative of secondary treatment responses, but these markers are not standardized for clinical application. Previous studies have indicated the potential of single-cell profiling by flow or mass cytometry for patient stratification in RA and in other autoimmune conditions. Distinct signaling patterns have been found in leukocytes of RA patients before and during treatment with TNF inhibitors in exploratory and proof-of-principle studies. The aim of this thesis was to explore and compare existing markers for TNF inhibitor drug responses, to set up a methodological background for mass cytometry experiments and finally to explore signaling signatures in immune cell subsets from RA patients compared to healthy individuals, with an emphasis on TNF signaling. Material, methods and results: First, we explored existing assays for TNF inhibitor drug levels and for ADAb in sera from 107 patients with inflammatory diseases treated with the TNF inhibitor infliximab. We found that the assays measured on different scales and that the agreement between quantitative results was limited. However, inter-assay differences could partially be overcome by assay-individualized translations of quantities into categories, which is also necessary for meaningful clinical application (paper 1). Second, we established a basis for mass cytometry experiments, including the extensive collection of biobank material and patient data. Methodological work in the design and titration of antibody panels for mass cytometry was carried out to provide a hierarchical titration method for complex mass cytometry panels, which takes in account abundancies, sources of signal spillover and non-specific antibody binding (paper 2). Last, we explored signaling patterns in heterogeneous immune cells from 20 newly diagnosed RA patients and from 20 healthy donors, with a focus on TNF signaling. In an automated data analysis pipeline, 18 of 20 RA patients and 17 of 20 healthy donors were correctly classified based on their signaling patterns (paper 3). Conclusion: RA is a heterogeneous disease with a plethora of treatment options, and patients might profit from more exact classification and stratification. This thesis highlights the lack of classification and stratification markers, and shows, how single cell profiling by mass cytometry may contribute to the search for such markers. Methodological aspects such as antibody panel design and approaches for the analysis of high-dimensional data are emphasized. The core results of the thesis show that newly diagnosed RA patients can be classified correctly with relatively high precision based on signaling patterns in single cells, when compared to healthy donors. The mass cytometry platform adds many dimensions to “cytomics” of heterogenous cell suspensions and tissues. While studies on malignancies as well as physiology and development of the immune system dominate the field, rheumatic diseases are currently relatively underrepresented. The door for further and deeper study of rheumatic diseases and signaling far beyond the TNF pathway is wide open.en_US
dc.language.isoengeng
dc.publisherThe University of Bergeneng
dc.relation.haspartPaper I: Bader LI, Solberg SM, Kaada SH, Bolstad N, Warren DJ, Gavasso S, Gjesdal CG, Vedeler C. Assays for infliximab drug levels and antibodies: a matter of scales and categories. Scand J Immunol. 2017. The article is available in the main thesis. The article is also available at: <a href="https://doi.org/10.1111/sji.12572" target="blank">https://doi.org/10.1111/sji.12572</a>en_US
dc.relation.haspartPaper II: Gullaksen SE, Bader L, Hellesøy M, Sulen A, Fagerholt OEE, Engen CB, Skavland J, Gjertsen BT, Gavasso S. Titrating complex mass cytometry panels. Cytometry Part A. 2019. The article is available at: <a href="http://hdl.handle.net/1956/21656" target="blank">http://hdl.handle.net/1956/21656</a>en_US
dc.relation.haspartPaper III: Bader L, Gullaksen SE, Blaser N, Brun M, Sulen A, Vedeler C, Gram Gjesdal C, Gavasso S. Candidate markers for stratification and classification in rheumatoid arthritis. Frontiers in Immunology. 2019. The article is available at: <a href="http://hdl.handle.net/1956/22434" target="blank">http://hdl.handle.net/1956/22434</a>en_US
dc.rightsAttribution-NonCommercial-NoDerivs (CC BY-NC-ND). This item's Creative Commons-license does not apply to the included articles in the thesis.eng
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/eng
dc.titleExploration of Cellular Signaling Patterns for the Stratification of Patients with Rheumatoid Arthritisen_US
dc.typeDoctoral thesis
dc.date.updated2020-09-01T07:33:30.261Z
dc.rights.holderCopyright the Author.
dc.contributor.orcidhttps://orcid.org/0000-0002-1745-7600
fs.unitcode13-25-0


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Attribution-NonCommercial-NoDerivs (CC BY-NC-ND). This item's Creative Commons-license does not apply to the included articles in the thesis.
Except where otherwise noted, this item's license is described as Attribution-NonCommercial-NoDerivs (CC BY-NC-ND). This item's Creative Commons-license does not apply to the included articles in the thesis.