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Elsevier, Gastroenterology, 3(140), p. 1021-1031.e10, 2011

DOI: 10.1053/j.gastro.2010.11.039

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Interferon-Induced Gene Expression Is a Stronger Predictor of Treatment Response than IL28B Genotype in Patients with Hepatitis C

This paper was not found in any repository, but could be made available legally by the author.
This paper was not found in any repository, but could be made available legally by the author.

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Abstract

BACKGROUND and AIMS: The host immune response during the chronic phase of hepatitis C virus infection varies among individuals-some patients have a no interferon (IFN) response in the liver whereas others have full activation IFN-stimulated genes (ISGs). Pre-activation of this endogenous IFN system is associated with non-response to pegylated IFN? (pegIFN?) and ribavirin. Genome-wide association studies have associated allelic variants near the IL28B (IFN?3) gene with treatment response. We investigated whether IL28B genotype determines the constitutive expression of ISGs in the liver and compared the abilities of ISG levels and IL28B genotype to predict treatment outcome. METHODS: We genotyped 109 patients with chronic hepatitis C for IL28B allelic variants and quantified the hepatic expression of ISGs and of IL28B. Decision tree ensembles, in the form of a random forest classifier, were used to calculate the relative predictive power of these different variables in a multivariate analysis. RESULTS: The minor IL28B allele was significantly associated with increased expression of ISG. However, stratification of the patients according to treatment response revealed increased ISG expression in non-responders, irrespective of IL28B genotype. Multivariate analysis of ISG expression, IL28B genotype, and several other factors associated with response to therapy identified ISG expression as the best predictor of treatment response. CONCLUSIONS: IL28B genotype and hepatic expression of ISGs are independent predictors of response to treatment with pegIFN? and ribavirin in patients with chronic hepatitis C. The most accurate prediction of response was obtained with a 4-gene classifier comprising IFI27, ISG15, RSAD2, and HTATIP2.