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Combination of peripheral blood gene expression profiles and clinical parameters predicts response to tocilizumab treatment in rheumatoid arthritis
  1. Bertalan Meskó1,
  2. Szilárd Poliska1,
  3. Szilvia Szamosi2,
  4. Zoltán Szekanecz2,
  5. János Podani3,
  6. László Nagy1
  1. 1Department of Biochemistry and Molecular Biology, University of Debrecen, Medical and Health Sciences Center, Debrecen, Hungary
  2. 2Department of Rheumatology, Institute of Medicine, University of Debrecen, Medical and Health Science Center, Debrecen, Hungary
  3. 3Department of Plant Taxonomy and Ecology, Eötvös University, Budapest, Hungary

Abstract

Background and objectives Tocilizumab, a humanised anti-interleukin 6 receptor monoclonal antibody, has recently been approved as a biologic therapy for rheumatoid arthritis and other diseases. It is not known if there are characteristic gene expression changes following therapy and if such alterations alone or in combination with clinical parameters can be used to predict responses.

Materials and methods Global gene expression profiles from peripheral blood mononuclear cells of 13 rheumatoid arthritis patients with active disease at week 0 and 4 following treatment were obtained as well as clinical parameters and serum cytokine levels using ELISA. Gene sets separating responders and non-responders were created by using Canonical Variates Analysis. This approach also revealed important gene groups and pathways that differentiate responders from non-responders.

Results Altogether 59 genes showed significant differences between week 0 and 4; and four genes (CCDC32, DHFR, EPHA4, TRAV8-3) separated responders from non-responders after multiple-testing correction. Genes correlating with disease activity and the responder status based on a novel scoring system were also found. 10 of the 12 genes with the most significant changes were validated using RT-QPCR.

Conclusions This is the first instance that the gene expression changes as the result of tocilizumab therapy were examined and gene sets discriminating between responders and non-responders found and validated. This data also show that the use of the combination of a clinical score system along with Canonical Variates Analysis are likely to help predict responder status from peripheral blood in rheumatoid arthritis.

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