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  • Immune markers and differential signaling networks in ulcerative colitis and Crohn's disease.

Immune markers and differential signaling networks in ulcerative colitis and Crohn's disease.

Inflammatory bowel diseases (2012-04-03)
George P Christophi, Rong Rong, Philip G Holtzapple, Paul T Massa, Steve K Landas
要旨

Cytokine signaling pathways play a central role in the pathogenesis of inflammatory bowel disease (IBD). Ulcerative colitis (UC) and Crohn's disease (CD) have unique as well as overlapping phenotypes, susceptibility genes, and gene expression profiles. This study aimed to delineate patterns within cytokine signaling pathways in colonic mucosa of UC and CD patients, explore molecular diagnostic markers, and identify novel immune mediators in IBD pathogenesis. We quantified 70 selected immune genes that are important in IBD signaling from formalin-fixed, paraffin-embedded (FFPE) colon biopsy samples from normal control subjects and UC and CD patients having either severe colitis or quiescent disease (n = 98 subjects). We utilized and validated a new modified real-time reverse-transcription polymerase chain reaction (RT-PCR) technique for gene quantification. Expression levels of signaling molecules including IL-6/10/12/13/17/23/33, STAT1/3/6, T-bet, GATA3, Foxp3, SOCS1/3, and downstream inflammatory mediators such as chemokines CCL-2/11/17/20, oxidative stress inducers, proteases, and mucosal genes were differentially regulated between UC and CD and between active and quiescent disease. We also document the possible role of novel genes in IBD, including SHP-1, IRF-1,TARC, Eotaxin, NOX2, arginase I, and ADAM 8. This comprehensive approach to quantifying gene expression provides insights into the pathogenesis of IBD by elucidating distinct immune signaling networks in CD and UC. Furthermore, this is the first study demonstrating that gene expression profiling in FFPE colon biopsies might be a practical and effective tool in the diagnosis and prognosis of IBD and may help identify molecular markers that can predict and monitor response to individualized therapeutic treatments.