Anti-TNF drugs have dramatically improved the lives of many patients living with rheumatoid arthritis. Not all patients respond to therapy however, with almost 40% showing a poor response to treatment.
An alternative treatment to anti-TNF is the targeting of B-cells which are known to contribute to the development of RA by driving synovial inflammation. The B-cell depleting drug rituximab is used after an inadequate response to initial anti-TNF, but in this more therapy-resistant patient cohort, rituximab also shows limited improvement. The research team hypothesised that the number or markers of synovial tissue B-cells before treatment could be used to predict a response.
Peter Taylor, the Norman Collisson chair of musculoskeletal sciences at NDORMS said: “We wanted to test the levels of B-cells in synovial tissue from patients with rheumatoid arthritis to see whether low or absent levels of the cells were preventing rituximab from working effectively. Against this we wanted to test whether tocilizumab, which works by inhibiting the action of IL-6, a protein that can cause inflammation and damage, improved clinical outcomes. Our study was the first biopsy-driven randomised clinical trial in rheumatoid arthritis.”
The study was a 48-week, biopsy-driven trial done in 19 centres across five European countries. Following a baseline synovial biopsy, patients were classified as B-cell poor or rich, then randomly assigned to receive either rituximab or tocilizumab infusions.
To enhance the accuracy of the classification of B-cell poor and B-cell rich patients, baseline synovial biopsies from all participants were subjected to RNA sequencing and reclassified by B-cell molecular signature. At 16 weeks, any improvement in Clinical Disease Activity Index was measured in all patients.
In the synovial biopsies classified as B-cell poor with RNA sequencing the tocilizumab group had a significantly higher response rate compared with the rituximab group.
“Our trial represents a milestone towards precision rheumatology,” said Peter. “In future, by investigating disease at the tissue level we can start to tailor our treatment and make the best drug selection for each individual patient’s needs. This may improve clinical response and have a major effect on related health and societal costs while reducing patient exposure to potentially toxic drugs.”