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Use of Whole‐Blood Transcriptomic Profiling to Highlight Several Pathophysiologic Pathways Associated With Response to Rituximab in Patients With Rheumatoid Arthritis: Data From a Randomized, Controlled, Open‐Label Trial
Author(s) -
Sellam Jérémie,
MarionThore Sandrine,
Dumont Florent,
Jacques Sébastien,
Garchon HenriJean,
Rouanet Stéphanie,
Taoufik Yassine,
HendelChavez Houria,
Sibilia Jean,
Tebib Jacques,
Le Loët Xavier,
Combe Bernard,
Dougados Maxime,
Mariette Xavier,
Chiocchia Gilles
Publication year - 2014
Publication title -
arthritis and rheumatology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 4.106
H-Index - 314
eISSN - 2326-5205
pISSN - 2326-5191
DOI - 10.1002/art.38671
Subject(s) - transcriptome , rheumatoid arthritis , medicine , rituximab , microarray , gene expression profiling , whole blood , immunology , microarray analysis techniques , gene , bioinformatics , gene expression , antibody , biology , genetics
Objective To identify a molecular signature that could be predictive of the clinical response to rituximab (RTX) and elucidate the transcriptomic changes after RTX therapy in patients with rheumatoid arthritis (RA), with the use of whole‐blood transcriptomic profiling. Methods A microarray assay of the whole human genome was performed using RNA from peripheral blood samples obtained before the first cycle of RTX from 68 patients with RA in the SMART study. The transcriptomic profile was also assessed 24 weeks after the first administration of RTX (among 24 nonresponders and 44 responders, according to the European League Against Rheumatism response criteria at week 24). Ingenuity Interactive Pathways Analysis was used to identify molecular pathways that were modified by RTX therapy according to the clinical response. Quantitative polymerase chain reaction was performed to confirm the microarray results. Results In total, 198 genes showed significant baseline differential expression between patient groups according to their subsequent response to RTX (good or moderate responder versus nonresponder). This molecular signature could be reduced to 143 genes, which allowed for correctly classifying 89% of the patients by their EULAR response status at week 24, with 93% identification of responders and 100% identification of nonresponders. The signature for response featured up‐regulation of inflammatory genes centered on NF‐κB, including IL33 and STAT5A , and down‐regulation of the interferon pathway. As expected, at week 24 post–RTX therapy, genes involved in the development and functions of B cells were the genes most strongly down‐regulated, without any difference between the 2 groups. Conclusion Whole‐blood transcriptomic analyses may accurately identify patients with RA who will not respond to RTX therapy. These findings could open new perspectives on the clinical management of RA.