Gene expression profiling to predict and assess the consequences of therapy-induced virus eradication in chronic

Jun Hou1, Gertine van Oord1, Zwier M A Groothuismink1

  • 1Department of Gastroenterology and Hepatology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands.

Journal of Virology
|August 8, 2014
PubMed
Abstract

Insights

A set of 18 genes can predict Hepatitis C Virus (HCV) treatment outcomes with 94% accuracy. Even after successful treatment, blood gene expression profiles in HCV patients remain altered, suggesting long-term immune changes.

Area of Science:

  • Systems biology and transcriptomics in infectious disease research.
  • Hepatitis C Virus (HCV) infection and treatment response.
  • Immunology and host-pathogen interactions.

Background:

  • Predicting treatment response in chronic Hepatitis C Virus (HCV) infection is crucial for optimizing therapy.
  • Previous studies have not fully explored baseline gene expression patterns differentiating sustained responders from relapsers.
  • Understanding the long-term impact of successful antiviral therapy on host gene expression is important.

Purpose of the Study:

  • To identify a gene expression signature in blood that predicts treatment outcome in chronic HCV patients.
  • To determine if successful HCV therapy leads to normalization of blood transcriptome.
  • To investigate potential biomarkers for predicting viral relapse after interferon-based therapy.

Main Methods:

  • Systems biology approach analyzing gene expression profiles in blood of chronic HCV patients.
  • Utilized interferon (IFN)-based therapy and assessed treatment response (sustained response vs. relapse).
  • Compared gene expression pre- and post-treatment, and against healthy individuals.

Main Results:

  • A baseline set of 18 genes accurately predicted treatment outcome (sustained response vs. relapse) with 94% accuracy.
  • Successful HCV therapy reduced expression of Interferon-Stimulated Genes (ISGs) but did not normalize the overall transcriptome.
  • 1,424 genes showed altered expression in successfully treated patients compared to healthy controls, indicating persistent transcriptional changes.

Conclusions:

  • A specific 18-gene signature is a potential biomarker for predicting HCV treatment efficacy.
  • Successful antiviral therapy for HCV does not fully restore normal blood gene expression patterns.
  • Altered transcriptional signatures post-treatment may reflect long-term immune modulation or HCV-induced damage.