The Gene Expression Profile in the Synovium as a Predictor of the Clinical Response to Infliximab Treatment in Rheumatoid Arthritis

被引:68
作者
Lindberg, Johan [1 ]
Wijbrandts, Carla A. [2 ]
van Baarsen, Lisa G. [2 ]
Nader, Gustavo [3 ]
Klareskog, Lars [3 ]
Catrina, Anca [3 ]
Thurlings, Rogier [2 ]
Vervoordeldonk, Margriet [2 ]
Lundeberg, Joakim [1 ]
Tak, Paul P. [2 ]
机构
[1] Royal Inst Technol, AlbaNova Univ Ctr, Sch Biotechnol, Dept Gene Technol, Stockholm, Sweden
[2] Univ Amsterdam, Acad Med Ctr, Div Clin Immunol & Rheumatol, NL-1105 AZ Amsterdam, Netherlands
[3] Karolinska Univ Hosp, Karolinska Inst, Dept Med, Rheumatol Unit, Solna, Sweden
关键词
FACTOR-ALPHA THERAPY; COLLEGE-OF-RHEUMATOLOGY; LYMPHOID NEOGENESIS; SET ENRICHMENT; BLOOD-CELLS; MICROARRAY; CANCER; TISSUE; RESPONSIVENESS; INFLAMMATION;
D O I
10.1371/journal.pone.0011310
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Background: Although the use of TNF inhibitors has fundamentally changed the way rheumatoid arthritis (RA) is treated, not all patients respond well. It is desirable to facilitate the identification of responding and non-responding patients prior to treatment, not only to avoid unnecessary treatment but also for financial reasons. In this work we have investigated the transcriptional profile of synovial tissue sampled from RA patients before anti-TNF treatment with the aim to identify biomarkers predictive of response. Methodology/Principal Findings: Synovial tissue samples were obtained by arthroscopy from 62 RA patients before the initiation of infliximab treatment. RNA was extracted and gene expression profiling was performed using an in-house spotted long oligonucleotide array covering 17972 unique genes. Tissue sections were also analyzed by immunohistochemistry to evaluate cell infiltrates. Response to infliximab treatment was assessed according to the EULAR response criteria. The presence of lymphocyte aggregates dominated the expression profiles and a significant overrepresentation of lymphocyte aggregates in good responding patients confounded the analyses. A statistical model was set up to control for the effect of aggregates, but no differences could be identified between responders and non-responders. Subsequently, the patients were split into lymphocyte aggregate positive-and negative patients. No statistically significant differences could be identified except for 38 transcripts associated with differences between good- and non-responders in aggregate positive patients. A profile was identified in these genes that indicated a higher level of metabolism in good responding patients, which indirectly can be connected to increased inflammation. Conclusions/Significance: It is pivotal to account for the presence of lymphoid aggregates when studying gene expression patterns in rheumatoid synovial tissue. In spite of our original hypothesis, the data do not support the notion that microarray analysis of whole synovial biopsy specimens can be used in the context of personalized medicine to identify non-responders to anti-TNF therapy before the initiation of treatment.
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