BACKGROUND AND AIMS: The gold standard treatment of chronic hepatitis C (CHC) is combined pegylated interferon and ribavirin. Considering side effects and treatment cost, prediction of treatment response before therapy is important. The aim of this study was to identify a liver gene signature to predict sustained virological response in patients with CHC. METHODS: Group A (training set) comprised 40 patients with CHC including 14 non-responders (NRs) and 26 sustained virological responders (SVRs). Group B (validation set) comprised 29 patients including 9 NRs and 20 SVRs. Eleven responder-relapsers were also included. A total of 58 genes associated with liver gene expression dysregulation during CHC were selected from the literature. Real-time quantitative RT-PCR assays were used to analyse the mRNA expression of these 58 selected genes in liver biopsy specimens taken from the patients before treatment. RESULTS: From the Group A data, three genes whose expression was significantly increased in NRs compared with SVRs were identified: IFI-6-16/G1P3, IFI27 and ISG15/G1P2. These three genes also showed significant differences in their expression profiles between NRs and SVRs in the independent sample (Group B). Supervised class prediction analysis identified a two-gene (IFI27 and CXCL9) signature, which accurately predicted treatment response in 79.3% (23/29) of patients from the validation set (Group B), with a predictive accuracy of 100% (9/9) and of 70% (14/20) in NRs and SVRs, respectively. The expression profiles of responder-relapsers did not differ significantly from those of NRs and SVRs, and 73% (8/11) of them were predicted as SVRs with the two-gene classifier. CONCLUSION: NRs and SVRs have different liver gene expression profiles before treatment. The most notable changes occurred mainly in interferon-stimulated genes. Treatment response could be predicted with a two-gene signature (IFI27 and CXCL9).
BACKGROUND AND AIMS: The gold standard treatment of chronic hepatitis C (CHC) is combined pegylated interferon and ribavirin. Considering side effects and treatment cost, prediction of treatment response before therapy is important. The aim of this study was to identify a liver gene signature to predict sustained virological response in patients with CHC. METHODS: Group A (training set) comprised 40 patients with CHC including 14 non-responders (NRs) and 26 sustained virological responders (SVRs). Group B (validation set) comprised 29 patients including 9 NRs and 20 SVRs. Eleven responder-relapsers were also included. A total of 58 genes associated with liver gene expression dysregulation during CHC were selected from the literature. Real-time quantitative RT-PCR assays were used to analyse the mRNA expression of these 58 selected genes in liver biopsy specimens taken from the patients before treatment. RESULTS: From the Group A data, three genes whose expression was significantly increased in NRs compared with SVRs were identified: IFI-6-16/G1P3, IFI27 and ISG15/G1P2. These three genes also showed significant differences in their expression profiles between NRs and SVRs in the independent sample (Group B). Supervised class prediction analysis identified a two-gene (IFI27 and CXCL9) signature, which accurately predicted treatment response in 79.3% (23/29) of patients from the validation set (Group B), with a predictive accuracy of 100% (9/9) and of 70% (14/20) in NRs and SVRs, respectively. The expression profiles of responder-relapsers did not differ significantly from those of NRs and SVRs, and 73% (8/11) of them were predicted as SVRs with the two-gene classifier. CONCLUSION: NRs and SVRs have different liver gene expression profiles before treatment. The most notable changes occurred mainly in interferon-stimulated genes. Treatment response could be predicted with a two-gene signature (IFI27 and CXCL9).
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