A recent study published in Nature Medicine lends credence to the idea that different clinical and treatment-response phenotypes are determined by different disease endotypes, which are influenced by various molecular pathology pathways in the diseased tissue.1
A collaborative group led by Felice Rivellese evaluated 164 patients who received rituximab (anti-CD20 monoclonal antibody) or tocilizumab (anti-IL6R monoclonal antibody). They were randomly assigned to TNF-inhibitor-inadequate responders in a biopsy-driven, randomized clinical study in RA (R4RA), followed by stratification based on synovial B cell signatures. Patients’ responses to rituximab were less favorable than those to tocilizumab in those with a low missing synovial B cell molecular profile.
In-depth histological and molecular investigations of R4RA synovial biopsies revealed stromal/fibroblast signatures in patients resistant to rituximab and tocilizumab, as well as humoral immune response gene signatures linked to responsiveness to these drugs. Post-treatment changes in synovial gene expression and cell infiltration revealed distinct effects of rituximab and tocilizumab. Rivellese and co-authors created machine learning algorithms that are predictive of response to rituximab (area under the curve (AUC) = 0.74), tocilizumab (AUC = 0.68), and, most significantly, multidrug resistance (AUC = 0.69) using ten-by-tenfold nested cross-validation.
A previous study by Bresnihan et al. reported the significance of synovial macrophages as a predictor of TNF response by determining the correlation between mean change in disease activity and the mean change in synovial sublining CD68 expression.2 A another study has linked baseline synovial gene score (GS) with both early and late clinical responses to rituximab. According to GS biology, remodelling and interferon-gene expression are correlated with poor response, but T cells and macrophages are crucial for the body’s reaction to B cell depletion therapy.3
The current study emphasizes the need to incorporate predicted molecular pathology characteristics into clinical algorithms in order to maximize the effectiveness of currently available medications.
References
- Rivellese F, Surace AEA, Goldmann K, et al. Rituximab versus tocilizumab in rheumatoid arthritis: synovial biopsy-based biomarker analysis of the phase 4 R4RA randomized trial. Nat Med. 2022 Jun;28(6):1256-1268.
- Bresnihan B, Pontifex E, Thurlings RM, et al. Synovial tissue sublining CD68 expression is a biomarker of therapeutic response in rheumatoid arthritis clinical trials: consistency across centers. J Rheumatol. 2009 Aug;36(8):1800-2.
- Hogan VE, Holweg CT, Choy DF, et al. Pretreatment synovial transcriptional profile is associated with early and late clinical response in rheumatoid arthritis patients treated with rituximab. Ann Rheum Dis. 2012 Nov;71(11):1888-94.