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

unlabelledSystems biology has proven to be a powerful tool to identify reliable predictors of treatment response in chronic hepatitis C virus (HCV) infection. In the present study, we studied patients with chronic HCV infection who responded to interferon (IFN)-based therapy, as evidenced by an absence of HCV RNA at the end of treatment, and focused on two issues that have not received much attention. First, we evaluated whether specific genes or gene expression patterns in blood were able to distinguish responder patients with a viral relapse from responder patients who remained virus negative after cessation of treatment. We found that patients with chronic HCV infection who were sustained responders and relapsers after IFN-based therapy showed comparable baseline clinical parameters and immune compositions in blood. However, at baseline, the gene expression profiles of a set of 18 genes predicted treatment outcome with an accuracy of 94%. Second, we examined whether patients with successful therapy-induced clearance of HCV still exhibited gene expression patterns characteristic of HCV or whether normalization of their transcriptome was observed. We observed that the relatively high expression levels of IFN-stimulated genes (ISGs) in patients with chronic HCV infection prior to therapy were reduced after successful IFN-based antiviral therapy (at 24 weeks of follow-up). These ISGs included the CXCL10, OAS1, IFI6, DDX60, TRIM5, and STAT1 genes. In addition, 1,428 differentially expressed non-ISGs were identified in paired pre- and posttreatment samples from sustained responders, which included genes involved in transforming growth factor beta (TGF-β) signaling, apoptosis, autophagy, and nucleic acid and protein metabolism. Interestingly, 1,424 genes with altered expression levels in responder patients after viral eradication were identified, in comparison to normal expression levels in healthy individuals. Additionally, aberrant expression levels of a subset of these genes, including the interleukin-32 (IL-32), IL-16, CCND3, and RASSF1 genes, were also observed at baseline. Our findings indicate that successful antiviral therapy for patients with chronic HCV infection does not lead to normalization of their blood transcriptional signature. The altered transcriptional activity may reflect HCV-induced liver damage in previously infected individuals. IMPORTANCE: Tools to predict the efficacy of antiviral therapy for patients with HCV infection are important to select the optimal therapeutic strategy. Using a systems biology approach, we identify a set of 18 genes expressed in blood that predicts the recurrence of HCV RNA after cessation of therapy consisting of peginterferon and ribavirin. This set of genes may be applicable as a useful biomarker in clinical decision-making, since the number of genes included in the predictor is small and the correct prediction rate is high (94%). In addition, we observed that the blood transcriptional profile in patients with chronic HCV infection who were successfully treated is not normalized to the status observed in healthy individuals. Even 6 months after therapy-induced elimination of HCV RNA, gene expression profiles in blood are still altered in these patients with chronic HCV infection, strongly suggesting long-term modulation of immune parameters in previously infected patients.