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OP0111 Anti-TNF Therapy in Axial Spondyloarthritis: Prediction of Therapeutic Responses Using Immunological Signatures
  1. L. Rogge1,
  2. S. Menegatti1,
  3. E. Latis1,
  4. H. Yahia1,
  5. C. Leloup1,
  6. N. Ménagé2,
  7. A. Moltό2,
  8. C. Miceli-Richard2,
  9. M. Dougados2,
  10. E. Bianchi1
  1. 1Immunology, Institut Pasteur
  2. 2Rheumatology B, AP-HP Cochin Hospital, Paris, France


Background The introduction of anti-TNF therapy has proven effective to reduce inflammation and clinical symptoms in several chronic inflammatory diseases. However, TNF-blockers are effective only in a subpopulation of patients and can be associated with serious side effects. Despite intense efforts, it is currently not possible to predict responsiveness of patients to anti-TNF treatment. To address this issue, we have asked whether the analysis of the immune functions of patients will allow us to define biomarkers that can predict therapeutic responses to TNF blockers.

Objectives The goals of this project were to define (i) the impact of anti-TNF therapy on immune responses to microbial challenges and stimuli targeting specific immune pathways in axial spondyloarthritis (axSpA) patients and (ii) to identify immunological correlates associated with therapeutic responses to TNF blockers before the initiation of therapy.

Methods We have recently developed a set of whole-blood, syringe-based assays to assess innate or adaptive immune responses to stimuli targeting different signaling pathways (e.g. cytokines and TLR/NLR agonists), or mimicking infections in patients (1). This “TruCulture” system is designed to capture immune cell activity in response to specific stimuli without introducing sample collection and manipulation variables. Using this assay system, we have investigated immune responses to 20 different stimuli in a pilot study involving 12 axSpA patients before and 3 months after initiation of anti-TNF therapy. We are currently validating our findings in a replication cohort.

Results We noted a highly significant reduction of the secretion of IL-1ra, IL-1β, and MIP-1β in response to selected stimuli after treatment with TNF-blockers. In contrast, TNF blockers had only minor effects on cytokine/chemokine production in unstimulated cultures, indicating that the effects of anti-TNF therapy can be measured when immune cells are challenged, but not at steady state. We also tested whether there is a correlation between the responses of immune cells to specific stimuli and the clinical response to TNF-blockers. For this, we calculated the “Ankylosing Spondylitis Disease Activity Score” (ASDAS) before treatment and 3 months after initiation of anti-TNF therapy and determined the “Improvement Score” (ASDASbefore treatment – ASDASafter treatment). We found that axSpA patients who secreted the highest levels of inflammatory cytokines and chemokines in response to specific immune stimuli before initiation of anti-TNF therapy had the best therapeutic responses (highest improvement score).

Conclusions Our results show that TruCulture assays are an efficient and robust tool to monitor immune functions in patients and that anti-TNF therapy induces specific changes in immune responses to selected stimuli. Our data also indicate that analyzing immune responses in patients before therapy is a promising strategy to develop biomarkers predicting therapeutic efficacy of TNF-blockers.

  1. Duffy et al., Immunity. 2014 Mar 20;40(3):436–50

Disclosure of Interest None declared

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