Personal Hepatic Gene Expression Predicts and Underlies the Need for Dual or Triple Therapy in Patients with Hepatitis C Genotype 1
Yoav Smith1, Shlomo Pundak1, Michal Safran 2, Maya Sultan 2, Hasid Avishag 3, Ella Veitsman 3, Ziv Ben-Ari 1,2,3,4
2 Liver Research Laboratory, Sheba Medical Center, Ramat Gan, Israel
3 Liver Disease Center, Sheba Medical Center, Ramat Gan, Israel
4 Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel
Maya Sultanemail: Maya.Sultan@sheba.health.gov.il
Michal Safran: Michal.Safran@sheba.health.gov.il
Avishag Hassid: Avishag.Hassid@sheba.health.gov.il
Ella Veitsman: Ella.Veitsman@sheba.health.gov.il
Ziv Ben Ari email: firstname.lastname@example.org
Ziv Ben Ari is the only AASLD member
Background and Aim: A specific intracellular gene expression pattern during the early stages of viral replication determines the ability of the cell to clear Hepatitis C virus (HCV).Spontaneous HCV clearance occurs in up to 15% of infected patients. Moreover, less than 50% of chronic HCV patients respond to dual antiviral therapy (pegylated-Interferon- alpha2a [Peg-IFN] and ribavirin).
The aim of this study was to define hepatic gene expression signature which can predict either response to the dual treatment or the need for combining Peg-IFN with the new direct acting antiviral agents (DAAs).
Methods: A novel computational algorithm for scanning publicly available microarray datasets of patients with HCV genotype 1 comparing PEG-IFN responders with non-responders was used by Genefron to construct a genomic signature of optimal statistical power .
A simulation mathematical model was also derived to predict personal viral load and the targeted hepatic gene expression response during anti viral treatment. The signature and the model were verified on RT-PCR data published by Dill MT et al,(Gastroenterology 2011;140:1021–1031). In addition we have analyzed the intermediate results of the hepatic gene signature in 15 HCV genotype 1 patients undergoing anti viral therapy from the ongoing Genefron clinical trial (GF-2012-1) in Sheba Medical Center in Israel.
Results: The hepatic gene expression signature was consistent in both the Genefron analysis, the Dill MT et al (2011) study and the combined results of each study. This gene signature predicted treatment responders with a 95% accuracy (Figure1).
Non-responders in comparison with responders, had marked pretreatment up-regulation of a subset of interferon stimulated genes, matching the simulation model (Figure1) .
Conclusions: The hepatic gene expression signature in HCV genotype 1 patients reflects the inherent efficiency of their innate immune system and defines Peg-IFN responders from non-responders.
Hepatic gene expression signature provide a new molecular marker for pre-treatment prediction, helping in patients selection for the dual or DAAs combined antiviral therapy and thus optimize treatment outcomes.
Results of RT-PCR of hepatic genes expression signature in pre-treated 43 HCV genotype 1 patients. Red-responders. Blue-non responders. Above threshold line- one false negative. No false positives.