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SAT0447 Identification of Predictive Biomarkers of Therapeutic Response in Knee OA: The Moves Study
  1. V. Calamia1,
  2. J. Mateo1,
  3. P. Fernández-Puente1,
  4. L. Lourido1,
  5. M. Camacho1,
  6. N. Oreiro2,
  7. A. Raga2,
  8. M. Acasuso2,
  9. M. Herrero3,
  10. H. Martinez3,
  11. J. Verges3,
  12. C. Ruiz-Romero1,
  13. F.J. Blanco1,2
  1. 1Grupo de Proteomica-PBR2-ProteoRed/ISCIII-Servicio de Reumatología
  2. 2Unidad de Investigacion Clinica-Servicio de Reumatología, Instituto de Investigaciόn Biomédica de A Coruña (INIBIC), Complexo Hospitalario Universitario de A Coruña (CHUAC), Sergas. Universidade da Coruña, A Coruña
  3. 3Clinical R&D Area, Bioiberica S.A., Barcelona, Spain

Abstract

Background The high costs incurred when drugs fail during clinical trials has prompted interest in biomarkers as biological indicators for progress of disease, effect of therapeutic interventions, and/or drug-induced toxicity1.

Objectives The aim of this study is to identify predictive protein biomarkers useful to stratify osteoarthritis (OA) patients into responders and non-responders, either to Droglican® (Bioiberica S.A.,Barcelona,Spain) or Celecoxib, in order to optimize therapeutic outcomes in OA.

Methods A shotgun proteomic analysis was performed on sera from patients enrolled in the Multicentre Osteoarthritis interVEntion trial with Sysadoa (MOVES)2. Sixteen serum pools from a representative group of the whole cohort (n=80) were analyzed to find a panel of proteins quantitatively different between responders and non-responders at baseline. The samples were classified between responders and non-responders, either to Droglican (glucosamine hydrochloride+chondroitin sulfate) or Celecoxib, according to the WOMAC pain score (<20 and <70) and the OMERACT-OARSI criteria recorded at the end of the trial (after 6 months of treatment). Two independent set of experiments were carried out. The pools from each condition to be compared were subjected to immunodepletion, protein digestion and labeled with the different 8-plex iTRAQ reagents as previously described3. The labeled peptide mixtures were mixed and resolved by reversed phase chromatography. The eluted fractions were collected onto a MALDI plate for the subsequent mass spectrometric analysis. The identification of proteins was performed with ProteinPilot v4.0 software (ABSciex). Furthermore, the results obtained were verified by ELISA assay.

Results The proteomic screening led to the identification of 176 different proteins in the serum samples at baseline. The Protein Pilot software also provided data relative to the quantification between each of the samples (iTRAQ ratios). All ratios were obtained comparing the abundance of each protein identified in the responders to the abundance in the non-responders. Several proteins showed at baseline a statistically significant increase in the responder groups, such as beta-2-glycoprotein 1 (APOH) in the droglican responders and thrombospondin 1 (TSP1) in the celecoxib responders, among others. The putative biomarker usefulness of TSP1 was validated by ELISA assay on individual sera from the same cohort. The results for TSP1 (n=80) confirmed that the levels of this protein at baseline are lower in the group of non-responders to celecoxib in comparison to the responders one according to WOMAC criteria.

Conclusions Protein biomarkers, such as APOH or TSP1, can predict patient response to a specific compound (droglican or celecoxib) by identifying certain OA patient populations that are more likely to respond to a specific drug therapy. This shift toward personalized medicine can help the clinicians to choose the best treatment option for each OA patient, thus enhancing the probability of success of the pharmacotherapy while reducing specific adverse events.

  1. Abdel-Baset, 2011.

  2. Hochberg et al., 2015.

  3. Fernández-Puente et al., 2011

Disclosure of Interest None declared

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