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SAT0020 BLOOD RNA SEQUENCING REVEALS IMMUNOLOGICAL PROCESSES ASSOCIATED WITH THE RESPONSE TO ABATACEPT IN RHEUMATOID ARTHRITIS
  1. Antonio Julià1,
  2. Maria Lopez Lasanta1,
  3. Antonio Gómez1,
  4. Raimon Sanmarti2,
  5. Carlos Marras Fernandez Cid3,
  6. José Manuel Pina Salvador4,
  7. Susana Romero-Yuste5,
  8. Raul Maria Veiga Cabello6,
  9. Pilar Navarro7,
  10. Carme Moragues Pastor8,
  11. Silvia Martinez Pardo9,
  12. Javier de Toro-Santos10,
  13. Amalia Sánchez11,
  14. Dacia Cerda12,
  15. Alejandro Prada13,
  16. Alba Erra1,
  17. Jordi Monfort14,
  18. Ana Urruticoechea-Arana15,
  19. Núria Palau1,
  20. Raquel M. Lastra1,
  21. Raül Tortosa1,
  22. Andrea Pluma Sanjurjo1,
  23. Sara Marsal1
  1. 1Vall Hebron H, Barcelona, Spain
  2. 2H Clinic, Barcelona, Spain
  3. 3H Virgen Arrixaca, Murcia, Spain
  4. 4H Barbastro, Huesca, Spain
  5. 5CHU Pontevedra, Pontevedra, Spain
  6. 6HUC de la Defensa Gómez Ulla, Madrid, Spain
  7. 7HU Fuenlabrada, Madrid, Spain
  8. 8H Platò, Barcelona, Spain
  9. 9HU Mutua Terrrassa, Terrassa, Barcelona, Spain
  10. 10U A Coruña, La Coruña, Spain
  11. 11HU Lucus Augusti, Lugo, Spain
  12. 12H Moises Broggi, Sant Joan Despí, Barcelona, Spain
  13. 13HU Torrejón de Ardoz, Madrid, Spain
  14. 14H Del Mar, Barcelona, Spain
  15. 15H Can Misses, Ibiza, Spain

Abstract

Background: Abatacept (CTLA4-Ig) is an approved biological therapy for the treatment of rheumatoid arthritis (RA). Similar to other biological agents, most patients (60%) respond significantly to this therapy. To date, however, the biological mechanisms underlying the lack of efficacy for this drug are unknown.

Objectives: The objectives of the present study were to characterize the biological processes underlying the lack of efficacy of abatacept and to evaluate the blood transcriptome as a valid source for drug response prediction.

Methods: A total of n=57 patients diagnosed with RA were recruited for this study from 16 rheumatology departments in Spain. All patients were >18 years old and, had >6 months of disease evolution. The primary clinical response to abatacept was defined at week 12 using the EULAR criteria. Good and moderate responders were aggregated into a single response group, and compared to the no response group of patients. Blood RNA was collected from all patients at baseline. From a subgroup of patients (n=31), blood RNA was also obtained at weeks 12, 24 and 48 of treatment with abatacept. Gene expression levels were determined using paired-end RNA-seq (Illumina). Differential gene expression, association to biological processes, longitudinal association analysis and building of the multigenic predictor were performed using the R software and the specialized Bioconductor libraries. The the prediction accuracy was evaluated using the ROC AUC.

Results: From the 57 patients treated with abatacept, n=10 (17.5%) were good EULAR responders, n=24 (42%) moderate EULAR responders and n=23 (40.5%) non-responders at week 12 of therapy. Biological process analysis identified two significantly distinct biological profiles between responders and non-responders. In responders, we found an association to pathways associated with the effector phase of T cells (e.g. interleukin-15 and 2 signalling, P < 0.05). Non-responder patients showed instead a strong association to biological processes associated with antigen presentation and activation of T cells (P < 0.005). Using the baseline gene expression profiles, we built a multigenic predictor of response to abatacept with an AUC = 75%. In the longitudinal cohort, patients were stratified based on reaching an inactive state (i.e. DAS28 < 3.2). Using this endpoint measure, the longitudinal analysis of the 4 time points corroborated the association of response with antigen presentation (P < 0.01).

Conclusion: The analysis of blood RNA profiles of RA patients has enabled the identification of specific biological processes associated with the lack of response to abatacept. Also, we demonstrate that blood expression profiles can be predictive of the response to the drug at week 12 of therapy.

Disclosure of Interests: Antonio Julià: None declared, Maria Lopez Lasanta: None declared, Antonio Gómez: None declared, Raimon Sanmarti Grant/research support from: Research support: Bristol-Myers Squibb, Speakers bureau: Speakers bureau: Bristol-Myers Squibb, Carlos Marras Fernandez Cid: None declared, José Manuel Pina Salvador: None declared, Susana Romero-Yuste: None declared, Raul Maria Veiga Cabello: None declared, Pilar Navarro: None declared, Carme Moragues Pastor : None declared, Silvia Martinez Pardo: None declared, Javier de Toro-Santos: None declared, Amalia Sánchez: None declared, Dacia Cerda: None declared, Alejandro Prada: None declared, Alba Erra: None declared, Jordi Monfort Speakers bureau: Bioibérica

Procare Health, ANA URRUTICOECHEA-ARANA: None declared, Núria Palau: None declared, Raquel M Lastra: None declared, Raül Tortosa: None declared, Andrea Pluma Sanjurjo: None declared, Sara Marsal: None declared

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