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SAT0246 Proteomic analysis of synovial tissue: A unique tool to predict response to anti-TNF-α therapy in patients with inflammatory arthritis
  1. O.S. Ademowo1,
  2. E. Collins1,2,
  3. C. Rooney1,
  4. A. van Kuijk3,
  5. D. Gerlag3,
  6. P.-P. Tak3,
  7. O. Fitzgerald1,2,
  8. S. Pennington1
  1. 1UCD Conway Institute of Biomolecular and Biomedical Research, University College Dublin
  2. 2Department of Rheumatology, St. Vincent’s University Hospital, Dublin, Ireland
  3. 3Department of Clinical Immunology/Rheumatology, Academic Medical Centre/University of Amsterdam, Amsterdam, Netherlands

Abstract

Background Inflammatory arthritis, which includes rheumatoid arthritis (RA) and psoriatic arthritis (PsA), is a leading cause of joint deformity, disability and reduced quality of life with a high economic cost [1]. A common target for therapeutic intervention is TNF-α, a key cytokine that drives the inflammatory and destructive processes of these diseases. However, due to common drug failure, diverse degree of response to therapy, cost of treatment as well as adverse drug events [2, 3] there is an urgent need for personalised medicine [4].

Objectives We hypothesized that there are distinct proteins or peptides within the synovial tissue that may predict the degree of response to anti TNF-α therapy in patients with inflammatory arthritis. Hence we aim to discover, develop and validate potential predictive biomarkers of treatment outcomes and map the protein changes to potential pathways.

Methods Baseline protein expressions were investigated and compared in the synovium of 20 PsA patients with diverse responses to adalimumab (a monoclonal antibody against TNF-α) [5]. The EULAR response criteria were used to classify patients’ treatment response categories at 3 months follow-up. Synovial proteins were extracted, subjected to digestion with trypsin and the resulting peptides were analysed by label free liquid chromatography-mass spectrometry (LC-MS) on an Agilent 6520 QTOF with HPLC chip cube source attached. Progenesis LC-MS software (version 2.6) was used for the differential proteomic expression analysis.

Results The protein profile of the different response categories varied. 313 proteins were differentially expressed between responders and non-responders. The majority of these proteins have been found to be associated with inflammation. The identified proteins were quantified. 68 proteins were over expressed and 64 proteins under expressed in responders. Looking at the data, a cut off p-value<0.05 and fold change>2 were used to select the biomarker panel. This resulted into 19 proteins significantly over expressed in responders and 22 proteins over expressed in non responders.

Conclusions Label-free LC-MS of synovial tissue is a robust approach to the discovery of differentially expressed proteins that might predict response in PsA patients. These proteins are potential candidate synovial biomarkers of response to anti-TNF-α therapy and will be validated on a larger cohort of patients. The possibility of detecting and measuring these candidate markers in the serum will be explored.

  1. Heuber and Robinson Proteomics Clin. Appl.6, 4100-4105(2006)

  2. Fitzgerald and Winchester. Arthritis Res. Ther., 11(1), 214(2009)

  3. Bennett et al; Rheumatology, 44(8), 1026(2005)

  4. Liao et al. Arthr& Rheum.,50(12),3792-3803(2004)

  5. van Kuijk et al. Ann Rheum Dis. 68(8), 1303-1309 (2009)

Disclosure of Interest None Declared

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