Harel Dahari

Rapid Emergence of Protease Inhibitor Resistance in Hepatitis C Virus

Computational modeling suggests that the rapid emergence of resistance to drugs against hepatitis C virus is a result of preexisting resistant virus and potent suppression of wild-type virus. Fighting the Resistance in Hepatitis C Following a few decades behind the infection-fighting miracles wrought by antibiotics was the cloud to the silver lining—drug resistance. Microbes evolved under the selection pressure exerted by antibiotics, and drug-resistant strains began to emerge. The microbes that cause respiratory infections, HIV/AIDS, diarrhea, tuberculosis, and malaria have all developed some resistance to their primary treatment, forcing physicians to turn to secondary, often inferior agents. Hepatitis C virus (HCV), which can cause serious liver damage, is genetically diverse and so may be particularly prone to develop resistance, sometimes within days of treatment onset. One way to combat this would be to administer multiple drugs, each with a different way of inhibiting the pathogen. Rong and colleagues have used a modeling approach to predict how resistance emerges in this disease and suggest that a combination of drugs that can fight three or more mutated viral strains may be needed to cure this disease. By using experimentally measured mutation rates and knowing the rate of viral production and other parameters, the authors were able to calculate that all possible HCV variants with single and double mutations already exist in infected patients before treatment and that one additional mutation is expected to arise during therapy. Thus, they concluded that a combination of direct antiviral drugs would need to be effective against variants with three or more mutations. The authors also constructed a model to study the development of drug-resistant virus during treatment. They showed that the model predictions match well with the actual data from a clinical trial in which the drug telaprevir was given to patients with HCV. Because hepatitis C is potentially curable, this modeling tool for designing more effective treatments is especially welcome. It may, however, also prove useful for application to other situations in which the emergence of viral or bacterial resistance renders the primary therapeutic treatment ineffective. About 170 million people worldwide are infected with hepatitis C virus (HCV). The current standard therapy leads to sustained viral elimination in only ~50% of the treated patients. Telaprevir, an HCV protease inhibitor, has substantial antiviral activity in patients with chronic HCV infection. However, in clinical trials, drug-resistant variants emerge at frequencies of 5 to 20% of the total virus population as early as the second day after the beginning of treatment. Here, using probabilistic and viral dynamic models, we show that such rapid emergence of drug resistance is expected. We calculate that all possible single- and double-mutant viruses preexist before treatment and that one additional mutation is expected to arise during therapy. Examining data from a clinical trial of telaprevir therapy for HCV infection in detail, we show that our model fits the observed dynamics of both drug-sensitive and drug-resistant viruses and argue that therapy with only direct antivirals will require drug combinations that have a genetic barrier of four or more mutations.

Modeling shows that the NS5A inhibitor daclatasvir has two modes of action and yields a shorter estimate of the hepatitis C virus half-life

The nonstructural 5A (NS5A) protein is a target for drug development against hepatitis C virus (HCV). Interestingly, the NS5A inhibitor daclatasvir (BMS-790052) caused a decrease in serum HCV RNA levels by about two orders of magnitude within 6 h of administration. However, NS5A has no known enzymatic functions, making it difficult to understand daclatasvir’s mode of action (MOA) and to estimate its antiviral effectiveness. Modeling viral kinetics during therapy has provided important insights into the MOA and effectiveness of a variety of anti-HCV agents. Here, we show that understanding the effects of daclatasvir in vivo requires a multiscale model that incorporates drug effects on the HCV intracellular lifecycle, and we validated this approach with in vitro HCV infection experiments. The model predicts that daclatasvir efficiently blocks two distinct stages of the viral lifecycle, namely viral RNA synthesis and virion assembly/secretion with mean effectiveness of 99% and 99.8%, respectively, and yields a more precise estimate of the serum HCV half-life, 45 min, i.e., around four times shorter than previous estimates. Intracellular HCV RNA in HCV-infected cells treated with daclatasvir and the HCV polymerase inhibitor NM107 showed a similar pattern of decline. However, daclatasvir treatment led to an immediate and rapid decline of extracellular HCV titers compared to a delayed (6–9 h) and slower decline with NM107, confirming an effect of daclatasvir on both viral replication and assembly/secretion. The multiscale modeling approach, validated with in vitro kinetic experiments, brings a unique conceptual framework for understanding the mechanism of action of a variety of agents in development for the treatment of HCV.

Triphasic decline of hepatitis C virus RNA during antiviral therapy.

When patients chronically infected with hepatitis C virus (HCV) are placed on antiviral therapy with pegylated interferon (IFN)‐α or IFN‐α plus ribavirin (RBV), HCV RNA generally declines in a biphasic manner. However, a triphasic decline has been reported in a subset of patients. A triphasic decline consists of a first phase (1‐2 days) with rapid virus load decline, followed by a “shoulder phase” (4‐28 days) in which virus load decays slowly or remains constant, and a third phase of renewed viral decay. We show that by including the proliferation of both uninfected and infected cells, a viral kinetic model can account for a triphasic HCV RNA decay. The model predicts that a triphasic decline occurs only in patients in which a majority of hepatocytes are infected before therapy. The shoulder phase does not represent the intrinsic death rate of infected cells, but rather the third phase slope is close to the intrinsic death rate of infected cells when overall drug efficacy is close to 1. Conclusion: Triphasic responses can be predicted from a generalization of existent viral kinetic models through the inclusion of homeostatic proliferation of hepatocytes. This generalized model can also explain the viral kinetics seen in flat partial responders. Finally, the enhanced third phase in patients treated with IFN‐α in combination with RBV versus patients treated with IFN‐α alone can be explained by a mutagenic effect of RBV against HCV. (HEPATOLOGY 2007;46:16–21.)

Mathematical Modeling of Subgenomic Hepatitis C Virus Replication in Huh-7 Cells

ABSTRACT Cell-based hepatitis C virus (HCV) replicon systems have provided a means for understanding HCV replication mechanisms and for testing new antiviral agents. We describe here a mathematical model of HCV replication that assumes that the translation of the HCV polyprotein occurs in the cytoplasm, that HCV RNA synthesis occurs in vesicular-membrane structures, and that the strategy of replication involves a double-stranded RNA intermediate. Our results shed light on the intracellular dynamics of subgenomic HCV RNA replication from transfection to steady state within Huh-7 cells. We predict the following: (i) about 6 × 103 ribosomes are involved in generating millions of HCV NS5B-polymerase molecules in a Huh-7 cell, (ii) the observed 10:1 asymmetry of plus- to minus-strand RNA levels can be explained by a higher-affinity (200-fold) interaction of HCV NS5B polymerase-containing replication complexes with HCV minus-strand RNA over HCV plus-strand RNA in order to initiate synthesis, (iii) the latter higher affinity can also account for the observed ∼6:1 plus-strand/minus-strand ratio in vesicular-membrane structures, and (iv) the introduction of higher numbers of HCV plus-strand RNA by transfection leads to faster attainment of steady-state but does not change the steady-state HCV RNA level. Fully permissive HCV replication systems have been developed, and the model presented here is a first step toward building a comprehensive model for complete HCV replication. Moreover, the model can serve as an important tool in understanding HCV replication mechanisms and should prove useful in designing and evaluating new antivirals against HCV.

Meta-Analysis of Hepatitis C Virus Vaccine Efficacy in Chimpanzees Indicates an Importance for Structural Proteins

BACKGROUND & AIMS Studies in patients and chimpanzees that spontaneously cleared hepatitis C virus (HCV) infections demonstrated that natural immunity to the virus is induced during primary infections and that this immunity can be cross protective. These discoveries led to optimism about prophylactic HCV vaccines, and several studies were performed in chimpanzees, although most included fewer than 6 animals. To draw meaningful conclusions about the efficacy of HCV vaccines in chimpanzees, we performed statistical analyses of data from previously published studies from different groups. METHODS We performed a meta-analysis that compared parameters among naïve (n = 63), vaccinated (n = 53), and rechallenged (n = 36) animals, including peak RNA titer postchallenge, time points of peak RNA titer, duration of viremia, and proportion of persistent infections. RESULTS Each vaccination study induced immune responses that were effective in rapidly controlling HCV replication. Levels of induced T-cell responses did not indicate vaccine success. There was no reduction in the rate of HCV persistence in vaccinated animals, compared with naïve animals, when nonstructural proteins were included in the vaccine. Vaccines that contained only structural proteins had clearance rates that were significantly higher than vaccines that contained nonstructural components (P = .015). CONCLUSIONS The inclusion of nonstructural proteins in HCV vaccines might be detrimental to protective immune responses, and/or structural proteins might activate T-cell responses that mediate viral clearance.

A perspective on modelling hepatitis C virus infection

Summary.  By mathematically describing early hepatitis C virus (HCV) RNA decay after initiation of interferon (IFN)‐based antiviral therapy, crucial parameters of the in vivo viral kinetics have been estimated, such as the rate of production and clearance of free virus, and the rate of loss of infected cells. Furthermore, by suggesting mechanisms of action for IFN and ribavirin mathematical modelling has provided a means for evaluating and optimizing treatment strategies. Here, we review recent modelling developments for understanding complex viral kinetics patterns, such as triphasic HCV RNA declines and viral rebounds observed in patients treated with pegylated interferon and ribavirin. Moreover, we discuss new modelling approaches developed to interpret the viral kinetics observed in clinical trials with direct‐acting antiviral agents, which induce a rapid decline of wild‐type virus but also engender a higher risk for emergence of drug‐resistant variants. Lastly, as in vitro systems have allowed a better characterization of the virus lifecycle, we discuss new modelling approaches that combine the intracellular and the extracellular viral dynamics.

Modeling Complex Decay Profiles of Hepatitis B Virus during Antiviral Therapy

Typically, hepatitis B virus (HBV) decays in patients under therapy in a biphasic manner. However, more complex decay profiles of HBV DNA (e.g., flat partial response, triphasic, and stepwise), for which we have no clear understanding, have also been observed in some treated patients. We recently introduced the notion of a critical drug efficacy, ϵc, such that if overall drug efficacy, ϵtot, is higher than the critical drug efficacy (i.e., ϵtot > ϵc) then viral levels will continually decline on therapy, while if ϵtot < ϵc, then viral loads will initially decline but will ultimately stabilize at a new set point, as seen in flat partial responders. Using the idea of critical efficacy and including hepatocyte proliferation in a viral kinetic model, we can account for these complex HBV DNA decay profiles. The model predicts that complex profiles such as those exhibiting a plateau or shoulder phase, as well as a class of stepwise declines, occur only in patients in whom the majority of hepatocytes are infected before therapy. Conclusion: We show via kinetic modeling how a variety of HBV DNA decay profiles can arise in treated patients. (HEPATOLOGY 2009;49:32‐38.)

Analysis of Hepatitis C Virus Decline during Treatment with the Protease Inhibitor Danoprevir Using a Multiscale Model

The current paradigm for studying hepatitis C virus (HCV) dynamics in patients utilizes a standard viral dynamic model that keeps track of uninfected (target) cells, infected cells, and virus. The model does not account for the dynamics of intracellular viral replication, which is the major target of direct-acting antiviral agents (DAAs). Here we describe and study a recently developed multiscale age-structured model that explicitly considers the potential effects of DAAs on intracellular viral RNA production, degradation, and secretion as virus into the circulation. We show that when therapy significantly blocks both intracellular viral RNA production and virus secretion, the serum viral load decline has three phases, with slopes reflecting the rate of serum viral clearance, the rate of loss of intracellular viral RNA, and the rate of loss of intracellular replication templates and infected cells, respectively. We also derive analytical approximations of the multiscale model and use one of them to analyze data from patients treated for 14 days with the HCV protease inhibitor danoprevir. Analysis suggests that danoprevir significantly blocks intracellular viral production (with mean effectiveness 99.2%), enhances intracellular viral RNA degradation about 5-fold, and moderately inhibits viral secretion (with mean effectiveness 56%). The multiscale model can be used to study viral dynamics in patients treated with other DAAs and explore their mechanisms of action in treatment of hepatitis C.

Modeling Subgenomic Hepatitis C Virus RNA Kinetics during Treatment with Alpha Interferon

ABSTRACT Although replicons have been used to demonstrate hepatitis C virus (HCV) inhibition by alpha interferon (IFN-α), the detailed inhibition kinetics required to mathematically model HCV RNA decline have been lacking. Therefore, we measured genotype 1b subgenomic replicon (sg1b) RNA levels under various IFN-α concentrations to assess the inhibition kinetics of intracellular HCV RNA. During nine days of IFN-α treatment, sg1b RNA decreased in a biphasic, dose-dependent manner. Using frequent measurements to dissect these phases during IFN-α treatments of 100 and 250 U/ml revealed that the first-phase sg1b RNA decline began ∼12 h posttreatment, continued for 2 to 4 days, and then exhibited a distinct flat or slower second phase. Based on these data, we developed a mathematical model of IFN-α-induced intracellular sg1b RNA decline, and we show that the mechanism(s) mediating IFN-α inhibition of HCV acts primarily by reducing sg1b RNA amplification, with an additional effect on HCV RNA stability/degradation detectable at a dose of 250 U/ml IFN-α. While the extremely slow or flat second phase of viral RNA inhibition observed in vitro, in which there is little or no cell death, supports the in vivo modeling prediction that the more profound second-phase decline observed in IFN-α-treated patients reflects immune-mediated death/loss of productively infected cells, the second-phase decline in viral RNA with a dose of 250 U/ml IFN-α suggests that a further inhibition of intracellular HCV RNA levels may contribute as well. As such, dissection of HCV IFN-α inhibition kinetics in vitro has brought us closer to understanding the mechanism(s) by which IFN-α may be inhibiting HCV in vivo.

Effect of ribavirin on viral kinetics and liver gene expression in chronic hepatitis C

Objective Ribavirin improves treatment response to pegylated-interferon (PEG-IFN) in chronic hepatitis C but the mechanism remains controversial. We studied correlates of response and mechanism of action of ribavirin in treatment of hepatitis C. Design 70 treatment-naive patients were randomised to 4 weeks of ribavirin (1000–1200 mg/d) or none, followed by PEG-IFNα-2a and ribavirin at standard doses and durations. Patients were also randomised to a liver biopsy 24 h before or 6 h after starting PEG-IFN. Hepatic gene expression was assessed by microarray and interferon-stimulated gene (ISG) expression quantified by nCounter platform. Temporal changes in ISG expression were assessed by qPCR in peripheral-blood mononuclear cells (PBMC) and by serum levels of IP-10. Results After 4 weeks of ribavirin monotherapy, hepatitis C virus (HCV) levels decreased by 0.5±0.5 log10 (p=0.009 vs controls) and ALT by 33% (p<0.001). Ribavirin pretreatment, while modestly augmenting ISG induction by PEG-IFN, did not modify the virological response to subsequent PEG-IFN and ribavirin treatment. However, biochemical, but not virological, response to ribavirin monotherapy predicted response to subsequent combination treatment (rapid virological response, 71% in biochemical responders vs 22% non-responders, p=0.01; early virological response, 100% vs 68%, p=0.03; sustained virological response 83% vs 41%, p=0.053). Ribavirin monotherapy lowered serum IP-10 levels but had no effect on ISG expression in PBMC. Conclusions Ribavirin is a weak antiviral but its clinical effect seems to be mediated by a separate, indirect mechanism, which may act to reset IFN-responsiveness in HCV-infected liver.