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.
RCT Entities:
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.
Authors: Jeffrey S Hyams; Sonia Davis Thomas; Nathan Gotman; Yael Haberman; Rebekah Karns; Melanie Schirmer; Angela Mo; David R Mack; Brendan Boyle; Anne M Griffiths; Neal S LeLeiko; Cary G Sauer; David J Keljo; James Markowitz; Susan S Baker; Joel Rosh; Robert N Baldassano; Ashish Patel; Marian Pfefferkorn; Anthony Otley; Melvin Heyman; Joshua Noe; Maria Oliva-Hemker; Paul A Rufo; Jennifer Strople; David Ziring; Stephen L Guthery; Boris Sudel; Keith Benkov; Prateek Wali; Dedrick Moulton; Jonathan Evans; Michael D Kappelman; M Alison Marquis; Francisco A Sylvester; Margaret H Collins; Suresh Venkateswaran; Marla Dubinsky; Vin Tangpricha; Krista L Spada; Bradley Saul; Jessie Wang; Jose Serrano; Kevin Hommel; Urko M Marigorta; Greg Gibson; Ramnik J Xavier; Subra Kugathasan; Thomas Walters; Lee A Denson Journal: Lancet Date: 2019-03-29 Impact factor: 79.321
Authors: Ingrid Arijs; Gert De Hertogh; Katleen Lemaire; Roel Quintens; Leentje Van Lommel; Kristel Van Steen; Peter Leemans; Isabelle Cleynen; Gert Van Assche; Séverine Vermeire; Karel Geboes; Frans Schuit; Paul Rutgeerts Journal: PLoS One Date: 2009-11-24 Impact factor: 3.240