Mucosal gene signatures to predict response to infliximab in patients with ulcerative colitis

Ingrid Arijs ¹, Katherine Li ², Gary Toedter ², Roel Quintens ³, Leentje Van Lommel ³, Kristel Van Steen ⁴, Peter Leemans ¹, Gert De Hertogh ¹, Katleen Lemaire ³, Marc Ferrante ¹, Fabian Schnitzler ¹, Lieven Thorrez ³, Keying Ma ², Xiao-Yu R Song ⁵, Colleen Marano ², Gert Van Assche ¹, Séverine Vermeire ¹, Karel Geboes ¹, Frans Schuit ³, Frédéric Baribaud ² and Paul Rutgeerts ^1*

¹ University Hospital Gasthuisberg, Leuven, Belgium
² Centocor Research and Development, Inc., Radnor, Pennsylvania, United States
³ Katholieke Universiteit Leuven, Leuven, Belgium
⁴ University of Liege, Liege, Belgium
⁵ Ethicon, Inc., Somerville, NJ, United States

^* To whom correspondence should be addressed. E-mail: paul.rutgeerts{at}uz.kuleuven.ac.be.

Accepted 23 June 2009

Abstract

Background & Aims: Infliximab is an effective treatment for ulcerative colitis (UC) with over 60% of patients responding to treatment and up to 30% reaching remission. The mechanism of resistance to anti-TNF-alpha is unknown. This study used colonic mucosal gene expression to provide a predictive response signature for infliximab treatment in UC.

Methods: Two cohorts of patients who received their first treatment with infliximab for refractory UC were studied. Response to infliximab was defined as endoscopic and histologic healing. Total RNA from pre-treatment colonic mucosal biopsies was analyzed 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 5 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 UC 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 UC.