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A multi-biomarker panel for predicting Tocilizumab response in Rheumatoid arthritis patients.

Authors :
Cho, Ara
Ahn, Jinsung
Kim, Andrew
Lee, Yun Jong
Song, Yeong Wook
Tanaka, Yoshiya
Yi, Eugene C.
Source :
Translational Research: The Journal of Laboratory & Clinical Medicine; Nov2024, Vol. 273, p23-31, 9p
Publication Year :
2024

Abstract

• Identification of protein biomarkers for predicting Tocilizumab response in Rheumatoid arthritis. • High-precision proteomics approach using Data-independent acquisition mass spectrometry in RA patient serum. • Developed a robust multi-biomarker panel with 86 % discriminative power and 0.84 AUC. • Potential diagnostic tool for TCZ non-responder prediction in RA patients. Rheumatoid arthritis (RA) is a chronic systemic autoimmune disease characterized by inflammation in the synovial lining of the joints. Key inflammatory cytokines such as interleukin-6 (IL-6), TNF-α, and others play a critical role in the activation of local synovial leukocytes and the induction of chronic inflammation. Tocilizumab (TCZ), a humanized anti-IL-6 receptor monoclonal antibody, has demonstrated significant clinical efficacy in treating RA patients. However, similar to other inflammatory cytokine blockers, such as TNF-alpha inhibitors, Interleukin-1 inhibitors, or CD20 inhibitors, some patients do not respond to treatment. To address this challenge, our study employed a high-precision proteomics approach to identify protein biomarkers capable of predicting clinical responses to Tocilizumab in RA patients. Through the use of data-independent acquisition (DIA) mass spectrometry, we analyzed serum samples from both TCZ responders and non-responders to discover potential biomarker candidates. These candidates were subsequently validated using individual serum samples from two independent cohorts: a training set (N = 70) and a test set (N = 18), allowing for the development of a robust multi-biomarker panel. The constructed multi-biomarker panel demonstrated an average discriminative power of 86 % between response and non-response groups, with a high area under the curve (AUC) value of 0.84. Additionally, the panel exhibited 100 % sensitivity and 60 % specificity. Collectively, our multi-biomarker panel holds promise as a diagnostic tool to predict non-responders to TCZ treatment in RA patients. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
19315244
Volume :
273
Database :
Supplemental Index
Journal :
Translational Research: The Journal of Laboratory & Clinical Medicine
Publication Type :
Academic Journal
Accession number :
179526794
Full Text :
https://doi.org/10.1016/j.trsl.2024.07.001