Rivellese, Felice 
ORCID: 0000-0002-6759-7521, Surace, Anna EA ORCID: 0000-0001-9589-3005, Goldmann, Katriona ORCID: 0000-0002-9073-6323, Sciacca, Elisabetta ORCID: 0000-0001-7525-1558, Çubuk, Cankut ORCID: 0000-0003-4646-0849, Giorli, Giovanni, John, Christopher R, Nerviani, Alessandra ORCID: 0000-0003-4064-4014, Fossati-Jimack, Liliane ORCID: 0000-0003-3757-3999, Thorborn, Georgina et al (show 12 more authors)
(2022)
Rituximab versus tocilizumab in rheumatoid arthritis: synovial biopsy-based biomarker analysis of the phase 4 R4RA randomized trial.
Nature medicine, 28 (6).
pp. 1256-1268.
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Rituximab versus tocilizumab in rheumatoid arthritis synovial biopsy-based biomarker analysis of the phase 4 R4RA randomized.pdf - Open Access published version Download (15MB) | Preview |
Abstract
Patients with rheumatoid arthritis (RA) receive highly targeted biologic therapies without previous knowledge of target expression levels in the diseased tissue. Approximately 40% of patients do not respond to individual biologic therapies and 5-20% are refractory to all. In a biopsy-based, precision-medicine, randomized clinical trial in RA (R4RA; n = 164), patients with low/absent synovial B cell molecular signature had a lower response to rituximab (anti-CD20 monoclonal antibody) compared with that to tocilizumab (anti-IL6R monoclonal antibody) although the exact mechanisms of response/nonresponse remain to be established. Here, in-depth histological/molecular analyses of R4RA synovial biopsies identify humoral immune response gene signatures associated with response to rituximab and tocilizumab, and a stromal/fibroblast signature in patients refractory to all medications. Post-treatment changes in synovial gene expression and cell infiltration highlighted divergent effects of rituximab and tocilizumab relating to differing response/nonresponse mechanisms. Using ten-by-tenfold nested cross-validation, we developed machine learning algorithms predictive of response to rituximab (area under the curve (AUC) = 0.74), tocilizumab (AUC = 0.68) and, notably, multidrug resistance (AUC = 0.69). This study supports the notion that disease endotypes, driven by diverse molecular pathology pathways in the diseased tissue, determine diverse clinical and treatment-response phenotypes. It also highlights the importance of integration of molecular pathology signatures into clinical algorithms to optimize the future use of existing medications and inform the development of new drugs for refractory patients.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | R4RA collaborative group, Humans, Arthritis, Rheumatoid, Antirheumatic Agents, Antibodies, Monoclonal, Biopsy, Antibodies, Monoclonal, Humanized, Biomarkers, Rituximab |
| Divisions: | Faculty of Health and Life Sciences Faculty of Health and Life Sciences > Institute of Life Courses and Medical Sciences |
| Depositing User: | Symplectic Admin |
| Date Deposited: | 17 May 2023 15:05 |
| Last Modified: | 17 May 2023 15:05 |
| DOI: | 10.1038/s41591-022-01789-0 |
| Open Access URL: | https://doi.org/10.1038/s41591-022-01789-0 |
| Related URLs: | |
| URI: | https://livrepository.liverpool.ac.uk/id/eprint/3170455 |
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