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An Interferon Response Gene Signature Is Associated with the Therapeutic Response of Hepatitis C Patients
An Interferon Response Gene Signature Is Associated with the Therapeutic Response of Hepatitis C Patients
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An Interferon Response Gene Signature Is Associated with the Therapeutic Response of Hepatitis C Patients
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An Interferon Response Gene Signature Is Associated with the Therapeutic Response of Hepatitis C Patients
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An Interferon Response Gene Signature Is Associated with the Therapeutic Response of Hepatitis C Patients
An Interferon Response Gene Signature Is Associated with the Therapeutic Response of Hepatitis C Patients
Journal Article

An Interferon Response Gene Signature Is Associated with the Therapeutic Response of Hepatitis C Patients

2014
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Overview
Infection with the hepatitis C virus (HCV) is a major cause of chronic liver diseases and hepatocellular carcinoma worldwide, and thus represents a significant public health problem. The type I interferon (IFN), IFNα, has been successful in treating HCV-infected patients, but current IFN-based treatment regimens for HCV have suboptimal efficacy, and relatively little is known about why IFN therapy eliminates the virus in some patients but not in others. Therefore, it is critical to understand the basic mechanisms that underlie the therapeutic resistance to IFN action in HCV-infected individuals, and there is an urgent need to identify those patients most likely to respond to IFN therapy for HCV. To characterize the response of HCV-infected patients to treatment with IFNα, the expression of an IFN-response gene signature comprised of IFN-stimulated genes and genes that play an important role in the innate immune response was examined in liver biopsies from HCV-infected patients enrolled in a clinical trial. In the present study we found that the expression of a subset of IFN-response genes was dysregulated in liver biopsy samples from nonresponsive hepatitis C patients as compared with virologic responders. Based on these findings, a statistical model was developed to help predict the response of patients to IFN therapy, and compared to results obtained to the IL28 mutation model, which is highly predictive of the response to IFN-based therapy in HCV-infected patients. We found that a model incorporating gene expression data can improve predictions of IFN responsiveness compared to IL28 mutation status alone.