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RNA sequencing to predict response to TNF-α inhibitors reveals possible mechanism for nonresponse in smokers

Bart V J Cuppen1, Marzia Rossato2,3, Ruth D E Fritsch-Stork1,4,5

  • 1a Rheumatology & Clinical Immunology , University Medical Center Utrecht , Utrecht , The Netherlands.

Expert Review of Clinical Immunology
|May 30, 2018
PubMed
Abstract

Insights

Predicting rheumatoid arthritis (RA) treatment response using gene expression failed. GPR15 and SEMA6B showed promise but were linked to smoking, not predicting tumor necrosis factor-alpha inhibitor (TNFi) efficacy.

Area of Science:

  • Rheumatology
  • Immunology
  • Genetics

Background:

  • Previous attempts to predict rheumatoid arthritis (RA) treatment response to tumor necrosis factor-alpha inhibitors (TNFi) using gene expression have been unsuccessful in clinical settings.
  • Microarray-based profiling has shown limited success in identifying reliable predictive biomarkers for TNFi therapy in RA patients.

Purpose of the Study:

  • To identify novel gene expression profiles that can predict treatment response to TNFi in rheumatoid arthritis (RA).
  • To validate potential predictive biomarkers in a separate cohort of RA patients undergoing TNFi therapy.

Main Methods:

  • RNA sequencing was performed on peripheral blood mononuclear cells (PBMCs) from extreme responders and non-responders to TNFi therapy in the BiOCURA cohort.
  • Pathway and individual gene transcript expression were analyzed, with promising targets validated using qPCR in a new cohort of 40 RA patients.

Main Results:

  • Non-responders to TNFi therapy exhibited lower expression of interferon and cytokine signaling pathways before treatment initiation.
  • Elevated levels of GPR15 and SEMA6B were observed in non-responders, but further analysis indicated these were dose-dependent markers of smoking, not independent predictors of TNFi response.
  • The identified genes GPR15 and SEMA6B did not independently predict treatment response in RA patients.

Conclusions:

  • This study did not identify new gene transcripts suitable for clinical prediction of TNFi response in RA.
  • GPR15 and SEMA6B were identified as potential explanatory markers for reduced treatment success in RA patients who smoke.
  • Smoking status is a significant confounding factor in identifying predictive biomarkers for TNFi therapy in rheumatoid arthritis.
Keywords:
RNA sequencingTNF-alphamRNApredictionqPCRresponserheumatoid arthritis

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