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.
| Original language | English |
|---|---|
| Pages (from-to) | 325-330 |
| Number of pages | 6 |
| Journal | Joint Bone Spine |
| Volume | 81 |
| Issue number | 4 |
| DOIs | |
| Publication status | Published - 2014 Jan 1 |
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Keywords
- Anti-TNF
- Microarray
- Response
- Rheumatoid arthritis
ASJC Scopus subject areas
- Rheumatology
Cite this
Gene expression profile predicting the response to anti-TNF treatment in patients with rheumatoid arthritis; analysis of GEO datasets. / Kim, Tae Hwan; Choi, Sungjae; Lee, Young Ho; Song, Gwan Gyu; Ji, Jong Dae.
In: Joint Bone Spine, Vol. 81, No. 4, 01.01.2014, p. 325-330.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Gene expression profile predicting the response to anti-TNF treatment in patients with rheumatoid arthritis; analysis of GEO datasets
AU - Kim, Tae Hwan
AU - Choi, Sungjae
AU - Lee, Young Ho
AU - Song, Gwan Gyu
AU - Ji, Jong Dae
PY - 2014/1/1
Y1 - 2014/1/1
N2 - 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.
AB - 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.
KW - Anti-TNF
KW - Microarray
KW - Response
KW - Rheumatoid arthritis
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U2 - 10.1016/j.jbspin.2014.01.013
DO - 10.1016/j.jbspin.2014.01.013
M3 - Article
VL - 81
SP - 325
EP - 330
JO - Revue du Rhumatisme (English Edition)
JF - Revue du Rhumatisme (English Edition)
SN - 1169-8446
IS - 4
ER -