[en] BACKGROUND AND AIMS: Infliximab is an effective treatment for ulcerative colitis with over 60% of patients responding to treatment and up to 30% reaching remission. The mechanism of resistance to anti-tumour necrosis factor alpha (anti-TNFalpha) is unknown. This study used colonic mucosal gene expression to provide a predictive response signature for infliximab treatment in ulcerative colitis. METHODS: Two cohorts of patients who received their first treatment with infliximab for refractory ulcerative colitis were studied. Response to infliximab was defined as endoscopic and histological healing. Total RNA from pre-treatment colonic mucosal biopsies was analysed with Affymetrix Human Genome U133 Plus 2.0 Arrays. Quantitative RT-PCR was used to confirm microarray data. RESULTS: For predicting response to infliximab treatment, pre-treatment colonic mucosal expression profiles were compared for responders and non-responders. Comparative analysis identified 179 differentially expressed probe sets in cohort A and 361 in cohort B with an overlap of 74 probe sets, representing 53 known genes, between both analyses. Comparative analysis of both cohorts combined, yielded 212 differentially expressed probe sets. The top five differentially expressed genes in a combined analysis of both cohorts were osteoprotegerin, stanniocalcin-1, prostaglandin-endoperoxide synthase 2, interleukin 13 receptor alpha 2 and interleukin 11. All proteins encoded by these genes are involved in the adaptive immune response. These markers separated responders from non-responders with 95% sensitivity and 85% specificity. CONCLUSION: Gene array studies of ulcerative colitis mucosal biopsies identified predictive panels of genes for (non-)response to infliximab. Further study of the pathways involved should allow a better understanding of the mechanisms of resistance to infliximab therapy in ulcerative colitis. ClinicalTrials.gov number, NCT00639821.
Disciplines :
Gastroenterology & hepatology
Author, co-author :
Arijs, I.
Li, K.
Toedter, G.
Quintens, R.
Van Lommel, L.
Van Steen, Kristel ; Université de Liège - ULiège > Dép. d'électric., électron. et informat. (Inst.Montefiore) > Bioinformatique
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