Validation Study of Existing Gene Expression Signatures for Anti-TNF Treatment in Patients with Rheumatoid Arthritis

Overview

Journal PLoS One

Specialties General Medicine
Science

Date 2012 Mar 30

PMID 22457743

Citations 33

Authors

Erik J M Toonen

Christian Gilissen

Barbara Franke

Wietske Kievit

Agnes M Eijsbouts

Alfons A den Broeder

Simon V van Reijmersdal

Joris A Veltman

Hans Scheffer

Timothy R D J Radstake

Piet L C M van Riel

Pilar Barrera

Marieke J H Coenen

Affiliations

Soon will be listed here.

Abstract

So far, there are no means of identifying rheumatoid arthritis (RA) patients who will fail to respond to tumour necrosis factor blocking agents (anti-TNF), prior to treatment. We set out to validate eight previously reported gene expression signatures predicting therapy outcome. Genome-wide expression profiling using Affymetrix GeneChip Exon 1.0 ST arrays was performed on RNA isolated from whole blood of 42 RA patients starting treatment with infliximab or adalimumab. Clinical response according to EULAR criteria was determined at week 14 of therapy. Genes that have been reported to be associated with anti-TNF treatment were extracted from our dataset. K-means partition clustering was performed to assess the predictive value of the gene-sets. We performed a hypothesis-driven analysis of the dataset using eight existing gene sets predictive of anti-TNF treatment outcome. The set that performed best reached a sensitivity of 71% and a specificity of 61%, for classifying the patients in the current study. We successfully validated one of eight previously reported predictive expression profile. This replicated expression signature is a good starting point for developing a prediction model for anti-TNF treatment outcome that can be used in a daily clinical setting. Our results confirm that gene expression profiling prior to treatment is a useful tool to predict anti-TNF (non) response.

Citing Articles

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