Gene expression profile predicting the response to anti-TNF treatment in patients with rheumatoid arthritis; analysis of GEO datasets

Abstract

Objectives: Anti-tumor necrosis factor (TNF) therapy is the treatment of choice for rheumatoid arthritis (RA) patients in whom standard disease-modifying anti-rheumatic drugs are ineffective. However, a substantial proportion of RA patients treated with anti-TNF agents do not show a significant clinical response. Therefore, biomarkers predicting response to anti-TNF agents are needed. Recently, gene expression profiling has been applied in research for developing such biomarkers. Methods: We compared gene expression profiles reported by previous studies dealing with the responsiveness of anti-TNF therapy in RA patients and attempted to identify differentially expressed genes (DEGs) that discriminated between responders and non-responders to anti-TNF therapy. We used microarray datasets available at the National Center for Biotechnology Information (NCBI) Gene Expression Omnibus (GEO). Results: This analysis included 6 studies and 5 sets of microarray data that used peripheral blood samples for identification of DEGs predicting response to anti-TNF therapy. We found little overlap in the DEGs that were highly ranked in each study. Three DEGs including IL2RB, SH2D2A and G0S2 appeared in more than 1 study. In addition, a meta-analysis designed to increase statistical power found one DEG, G0S2 by the Fisher's method. Conclusion: Our finding suggests the possibility that G0S2 plays as a biomarker to predict response to anti-TNF therapy in patients with rheumatoid arthritis. Further investigations based on larger studies are therefore needed to confirm the significance of G0S2 in predicting response to anti-TNF therapy.