Abstract

BackgroundTreating hepatitis C with interferon/ribavirin results in a varied response in terms of decrease in viral titer and ultimate outcome. Marked responders have a sharp decline in viral titer within a few days of treatment initiation, whereas in other patients there is no effect on the virus (poor responders). Previous studies have shown that combination therapy modifies expression of hundreds of genes in vitro and in vivo. However, identifying which, if any, of these genes have a role in viral clearance remains challenging.AimsThe goal of this paper is to link viral levels with gene expression and thereby identify genes that may be responsible for early decrease in viral titer.MethodsMicroarrays were performed on RNA isolated from PBMC of patients undergoing interferon/ribavirin therapy. Samples were collected at pre-treatment (day 0), and 1, 2, 7, 14 and 28 days after initiating treatment. A novel method was applied to identify genes that are linked to a decrease in viral titer during interferon/ribavirin treatment. The method uses the relationship between inter-patient gene expression based proximities and inter-patient viral titer based proximities to define the association between microarray gene expression measurements of each gene and viral-titer measurements.ResultsWe detected 36 unique genes whose expressions provide a clustering of patients that resembles viral titer based clustering of patients. These genes include IRF7, MX1, OASL and OAS2, viperin and many ISG's of unknown function.ConclusionThe genes identified by this method appear to play a major role in the reduction of hepatitis C virus during the early phase of treatment. The method has broad utility and can be used to analyze response to any group of factors influencing biological outcome such as antiviral drugs or anti-cancer agents where microarray data are available.

Highlights

  • Treating with peginterferon/ribavirin combination therapy patients who have chronic hepatitis C virus (HCV) infection results in a varied response in terms of outcome and decrease in viral titer [1,2,3,4]

  • The branches of the clustering tree were labeled by type of response according to the initial categorization of the early response [11] (Fig 1). This hypothesis-free clustering based on inter-patient Euclidean distances according to viral titer demonstrated that patients could be placed into three groups corresponding to the response classification of patients

  • We developed a mathematical model that can be applied to any situation using gene expression and viral titer or any other attributes

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Summary

Introduction

Treating with peginterferon/ribavirin combination therapy patients who have chronic hepatitis C virus (HCV) infection results in a varied response in terms of outcome and decrease in viral titer [1,2,3,4]. In this paper we report a novel mathematical method to explore the association between decrease in viral titer and changes in gene expression in hepatitis C patients following combination treatment with pegylated interferon and ribavirin. Treating hepatitis C with interferon/ribavirin results in a varied response in terms of decrease in viral titer and ultimate outcome. The goal of this paper is to link viral levels with gene expression and thereby identify genes that may be responsible for early decrease in viral titer. A novel method was applied to identify genes that are linked to a decrease in viral titer during interferon/ribavirin treatment. The method has broad utility and can be used to analyze response to any group of factors influencing biological outcome such as antiviral drugs or anti-cancer agents where microarray data are available

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