medwireNews: An in-depth molecular analysis of synovial biopsies from people with rheumatoid arthritis (RA) who participated in the R4RA trial has identified gene signatures associated with treatment response.
This phase 4 trial previously demonstrated that treatment with the interleukin (IL)-6 receptor inhibitor tocilizumab results in higher response rates than the anti-CD20 monoclonal antibody rituximab among patients with a low synovial B cell molecular signature, but “the exact mechanisms of response/nonresponse remain to be established,” write the researchers in Nature Medicine.
In the current study, Myles Lewis (Queen Mary University of London, UK) and team found that 6625 genes were differentially expressed in pretreatment synovial biopsies from rituximab responders (n=28) relative to nonresponders (n=54), while 85 genes differed in tocilizumab responders (n=37) versus nonresponders (n=42). Treatment response was defined as a 50% or greater improvement in CDAI score from baseline to week 16.
Upregulated genes in rituximab responders included leukocyte-related genes and members of the immunoglobulin superfamily, while tocilizumab response was associated with IL-6 pathway genes, as well as lymphocyte and immunoglobulin genes.
The researchers also identified 1277 unique genes that were upregulated in patients who did not respond to either rituximab or tocilizumab, including fibroblast and extracellular matrix-encoding genes.
“Together, these results show that baseline histological and molecular signatures are associated with response to individual drugs, while nonresponse to multiple biologics is linked to a specific pretreatment signature associated with fibroblasts,” write Lewis and team.
They then compared pre-and post-treatment histopathologic and molecular data, which revealed changes in cell infiltration and gene expression that “highlighted divergent effects of rituximab and tocilizumab relating to differing response/nonresponse mechanisms.”
Specifically, only participants responding to rituximab experienced a significant reduction in CD138- and CD79a-positive plasmoblasts/plasma cells, whereas only those responding to tocilizumab had a significant reduction in CD68SL-positive macrophages. In the molecular analysis, changes in the expression levels of 349 genes differed significantly between rituximab responders and nonresponders, as did changes in the expression of 136 genes between tocilizumab responders and nonresponders.
Lewis et al used genetic data from their study to generate machine-learning models to predict drug response. The models for rituximab and tocilizumab included 40 and 39 genes, respectively, and predicted drug response with a corresponding accuracy of 74% and 68%.
The researchers say that their findings highlight “the importance of integrating predictive molecular pathology signatures into clinical algorithms to optimize the usage of existing drugs.”
Looking to the future, they “envisage that routine use of synovial biopsies could facilitate a patient-centered approach to the management of RA, thus moving away from the current trial-and-error drug prescribing towards an emergent era in which selection of the optimal drug is based on synovial biopsy gene signatures.”
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