Article Text

THU0121 The interferon type I signature towards prediction of non-response to rituximab in rheumatoid arthritis patients
  1. H. Raterman1,
  2. S. Vosslamber2,
  3. S. de Ridder2,
  4. M. Nurmohamed3,
  5. W. Lems1,
  6. M. Boers1,4,
  7. M. van der Wiel4,
  8. B. Dijkmans1,
  9. C. Verweij1,2,
  10. A. Voskuyl1
  1. 1Rheumatology
  2. 2Pathology, VU University medical center
  3. 3Rheumatology, Jan van Breemen Institute/Reade
  4. 4Department of Epidemiology and Biostatistics, VU University medical center, Amsterdam, Netherlands


Background B cell depletion therapy is efficacious in rheumatoid arthritis (RA) patients failing on tumor necrosis factor (TNF) blocking agents. However, approximately 40-50% of rituximab (RTX) treated RA patients have a poor response

Objectives We investigated whether baseline gene expression levels can discriminate between clinical nonresponders and responders to RTX.

Methods In 14 consecutive RA patients starting with RTX (test cohort), gene expression profiling on whole peripheral blood RNA was performed by Illumina® HumanHT beadchip microarrays. Supervised cluster analysis (patients ranked on difference in 28 joints disease activity score (DAS28) after 6 months RTX) identified genes expressed differently at baseline in case of nonresponse (both ΔDAS28 <1.2 and EULAR nonresponse). Genes of interest were measured by quantitative real-time PCR and tested for their predictive value using Receiver Operating Characteristics (ROC) curves in an independent validation cohort (n=26).

Results Genome-wide microarray analysis revealed a marked variation in the peripheral blood cells between RA patients before the start of RTX treatment. Here, we demonstrated that only a cluster consisting of interferon (IFN) type I network genes, represented by a set of IFN type I response genes (IRGs), i.e. LY6E, HERC5, IFI44L, ISG15, MxA, MxB, EPSTI1 and RSAD2, was associated with ΔDAS28 and EULAR response outcome (p=0.0074 and p=0.0599, respectively). Based on the 8 IRGs an IFN-score was calculated that reached an AUC of 0.82 to separate non-responders from responders in an independent validation cohort of 26 patients using ROC curves analysis according to ΔDAS28<1.2 criteria. Advanced classifier analysis yielded a 3 IRG-set that reached an AUC of 87%. Comparable findings applied to EULAR nonresponse criteria.

Conclusions This study demonstrates clinical utility for the use of baseline IRG expression levels as predictive biomarker for nonresponse to RTX in RA.

Disclosure of Interest H. Raterman: None Declared, S. Vosslamber: None Declared, S. de Ridder: None Declared, M. Nurmohamed Consultant for: Dr. M. Nurmohamed has been a speaker and consultant for BMS, MSD, Roche, Abbott, Pfizer and UCB, W. Lems: None Declared, M. Boers: None Declared, M. van der Wiel: None Declared, B. Dijkmans: None Declared, C. Verweij: None Declared, A. Voskuyl: None Declared

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