Gene expression profile predicting the response to anti-TNF treatment in patients with rheumatoid arthritis; analysis of GEO datasets
- Authors
- Kim, Tae-Hwan; Choi, Sung Jae; Lee, Young Ho; Song, Gwan Gyu; Ji, Jong Bae
- Issue Date
- Jul-2014
- Publisher
- ELSEVIER FRANCE-EDITIONS SCIENTIFIQUES MEDICALES ELSEVIER
- Keywords
- Rheumatoid arthritis; Anti-TNF; Response; Microarray
- Citation
- JOINT BONE SPINE, v.81, no.4, pp.325 - 330
- Indexed
- SCIE
SCOPUS
- Journal Title
- JOINT BONE SPINE
- Volume
- 81
- Number
- 4
- Start Page
- 325
- End Page
- 330
- URI
- https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/159581
- DOI
- 10.1016/j.jbspin.2014.01.013
- ISSN
- 1297-319X
- 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.
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