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Peripheral blood derived gene panels predict response to infliximab in rheumatoid arthritis and Crohn's disease

Biological therapies have been introduced for the treatment of chronic inflammatory diseases including rheumatoid arthritis (RA) and Crohn's disease (CD). The efficacy of biologics differs from patient to patient. Moreover these therapies are rather expensive, therefore treatment of primary non...

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Published in:Genome medicine 2013-06, Vol.5 (6), p.59-59, Article 59
Main Authors: Mesko, Bertalan, Poliska, Szilard, Váncsa, Andrea, Szekanecz, Zoltan, Palatka, Karoly, Hollo, Zsolt, Horvath, Attila, Steiner, Laszlo, Zahuczky, Gabor, Podani, Janos, Nagy, And Laszlo
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Language:English
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Summary:Biological therapies have been introduced for the treatment of chronic inflammatory diseases including rheumatoid arthritis (RA) and Crohn's disease (CD). The efficacy of biologics differs from patient to patient. Moreover these therapies are rather expensive, therefore treatment of primary non-responders should be avoided. We addressed this issue by combining gene expression profiling and biostatistical approaches. We performed peripheral blood global gene expression profiling in order to filter the genome for target genes in cohorts of 20 CD and 19 RA patients. Then RT-quantitative PCR validation was performed, followed by multivariate analyses of genes in independent cohorts of 20 CD and 15 RA patients, in order to identify sets ofinterrelated genes that can separate responders from non-responders to the humanized chimeric anti-TNFalpha antibody infliximab at baseline. Gene panels separating responders from non-responders were identified using leave-one-out cross-validation test, and a pool of genes that should be tested on larger cohorts was created in both conditions. Our data show that peripheral blood gene expression profiles are suitable for determining gene panels with high discriminatory power to differentiate responders from non-responders in infliximab therapy at baseline in CD and RA, which could be cross-validated successfully. Biostatistical analysis of peripheral blood gene expression data leads to the identification of gene panels that can help predict responsiveness of therapy and support the clinical decision-making process.
ISSN:1756-994X
1756-994X
DOI:10.1186/gm463