Background and Aims

In rheumatoid arthritis (RA) a portion of patients fail to respond to first biological therapy. Predicting the patient’s responsiveness to the first biological therapy is still an unmet medical need. For non-responder patients, this leads to unnecessary exposure, delay of adequate therapy, disease progression and waste of money for the payer as well.

The aim of our study was to identify the selected gene set as genomic biomarkers to predict month 6 therapeutic response to infliximab (IFX), differentiate between good responders and non-responders.

Methods

In the study we enrolled 217 bio-naive RA patients with moderate-high disease activity RA (DAS28-CRP >3.2), who have responded inadequately to DMARDs and assigned to IFX treatment. Developing our in vitro diagnostic test method for the prediction of IFX treatment responsiveness 250 genes were identified by differential gene expression analyses from NGS RNA-Seq data using various machine learning modelling methods, 44 genes were selected which showed significant differences between non-responders and good responders as biomarkers in patient stratification. The expression of this gene set was analyzed using reverse-transcription and quantitative real-time PCR.

Results

Validation clinical studies confirmed that this selected gene set as genomic biomarkers and a proprietary algorithm may predict month 6 therapeutic response to IFX, discriminating between good responders (reached DAS target value DAS28≤3.2 at 6 month) and non-responders.

Conclusions

Our kit received the CE IVD Medical Device Certificate in December 2020, providing a precision medicine tool to personalize IFX therapy.