Sustained virological response with intravenous silibinin: individualized <scp>IFN</scp>‐free therapy via real‐time modelling of <scp>HCV</scp> kinetics

Dahari, Harel; Shteingart, Shimon; Gafanovich, Inna; Cotler, Scott J.; D’Amato, Massimo; Pohl, Ralf T.; Weiss, Gali; Ashkenazi, Yaakov Jack; Tichler, Thomas; Goldin, Eran; Lurie, Yoav

doi:10.1111/liv.12692

Cited by 34 publications

(28 citation statements)

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“…Mathematical modeling has been widely used to understand viral infection dynamics and treatment response; however, these models typically assume only cell-free virus infection mechanisms (18)(19)(20)(21)(22)(23). In vitro mathematical models were developed to understand intracellular HCV RNA kinetics during infection and treatment (24)(25)(26) and cell-free HCV entry (27).…”

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confidence: 99%

Quantification of Hepatitis C Virus Cell-to-Cell Spread Using a Stochastic Modeling Approach

Graw

Martin

Perelson

et al. 2015

J Virol

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It has been proposed that viral cell-to-cell transmission plays a role in establishing and maintaining chronic infections. Thus, understanding the mechanisms and kinetics of cell-to-cell spread is fundamental to elucidating the dynamics of infection and may provide insight into factors that determine chronicity. Because hepatitis C virus (HCV) spreads from cell to cell and has a chronicity rate of up to 80% in exposed individuals, we examined the dynamics of HCV cell-to-cell spread in vitro and quantified the effect of inhibiting individual host factors. Using a multidisciplinary approach, we performed HCV spread assays and assessed the appropriateness of different stochastic models for describing HCV focus expansion. To evaluate the effect of blocking specific host cell factors on HCV cell-to-cell transmission, assays were performed in the presence of blocking antibodies and/or small-molecule inhibitors targeting different cellular HCV entry factors. In all experiments, HCV-positive cells were identified by immunohistochemical staining and the number of HCV-positive cells per focus was assessed to determine focus size. We found that HCV focus expansion can best be explained by mathematical models assuming focus size-dependent growth. Consistent with previous reports suggesting that some factors impact HCV cell-to-cell spread to different extents, modeling results estimate a hierarchy of efficacies for blocking HCV cell-to-cell spread when targeting different host factors (e.g., CLDN1 > NPC1L1 > TfR1). This approach can be adapted to describe focus expansion dynamics under a variety of experimental conditions as a means to quantify cell-to-cell transmission and assess the impact of cellular factors, viral factors, and antivirals. IMPORTANCEThe ability of viruses to efficiently spread by direct cell-to-cell transmission is thought to play an important role in the establishment and maintenance of viral persistence. As such, elucidating the dynamics of cell-to-cell spread and quantifying the effect of blocking the factors involved has important implications for the design of potent antiviral strategies and controlling viral escape. Mathematical modeling has been widely used to understand HCV infection dynamics and treatment response; however, these models typically assume only cell-free virus infection mechanisms. Here, we used stochastic models describing focus expansion as a means to understand and quantify the dynamics of HCV cell-to-cell spread in vitro and determined the degree to which cellto-cell spread is reduced when individual HCV entry factors are blocked. The results demonstrate the ability of this approach to recapitulate and quantify cell-to-cell transmission, as well as the impact of specific factors and potential antivirals. V iral entry into permissive cells is the first step in establishing infection and is thus a common and often effective target for antiviral therapy. However, after replication and assembly of viral particles in an infected cell, many viruses, including hepatitis C virus...

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confidence: 99%

Quantification of Hepatitis C Virus Cell-to-Cell Spread Using a Stochastic Modeling Approach

Graw

Martin

Perelson

et al. 2015

J Virol

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“…First, our prediction about time to viral extinction should be treated cautiously. We predict the time of extinction (as in other models [54][55][56]) by assuming that infected cells decline at a rate set by their death rate, and infection is cleared when the number of infected cells is below one. However, factors such as pressures from the immune system and infections in different tissue compartments may influence the extinction threshold.…”

Section: Discussionmentioning

confidence: 99%

Rational design and adaptive management of combination therapies for Hepatitis C virus infection

Loverdo

Qi³

et al. 2014

Preprint

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Recent discoveries of direct acting antivirals against Hepatitis C virus (HCV) have raised hopes of effective treatment via combination therapies. Yet rapid evolution and high diversity of HCV populations, combined with the reality of suboptimal treatment adherence, make drug resistance a clinical and public health concern. We develop a general model incorporating viral dynamics and pharmacokinetics/ pharmacodynamics to assess how suboptimal adherence affects resistance development and clinical outcomes. We derive design principles and adaptive treatment strategies, identifying a high-risk period when missing doses is particularly risky for de novo resistance, and quantifying the number of additional doses needed to compensate when doses are missed. Using data from large-scale resistance assays, we demonstrate that the risk of resistance can be reduced substantially by applying these principles to a combination therapy of daclatasvir and asunaprevir. By providing a mechanistic framework to link patient characteristics to the risk of resistance, these findings show the potential of rational treatment design. Author SummaryHepatitis C virus (HCV) affects approximately 170 million people world-wide and chronic infections can lead to cirrhosis and liver cancer. New combination therapies of direct acting antivirals have achieved remarkably high cure rates in clinical trials. However, high mutation rates and high diversity of HCV populations, combined with the reality of suboptimal treatment adherence, make drug resistance a clinical and public health concern. By constructing a mechanistic framework to assess the risk of drug resistance, we provide PLOS Computational Biology |

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“…The time to reach cure, or SVR, was previously defined as the time to reach less than one hepatitis C virion in the extracellular fluid volume (approximately 13.5-15 L) [9][10][11][12] . Thus a value of approximately 3 × 10 -5 IU/mL is the threshold for viral clearance (termed here cure boundary).…”

Section: Case Reportmentioning

confidence: 99%

“…The fact that the patient achieved SVR despite a very short course of therapy (24 d) was striking since her viral load level 10 d before DAA therapy stopped (3/15/15) was 97 IU/mL, which is several log IU/mL higher than the cure boundary. To estimate, retrospectively, when the patient reached cure we used the standard biphasic HCV treatment model [11,12] and the multiscale HCV treatment model [13,14] . Both these models predicted that cure occurred 3 to 6 wk after therapy was stopped (not shown).…”

Section: Case Reportmentioning

confidence: 99%

Hepatitis C virus cures after direct acting antiviral-related drug-induced liver injury: Case report

Hasin

Shteingart

Dahari

et al. 2016

WJH

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The United States Food and Drug Administration recently warned that the direct acting antiviral (DAA) combination hepatitis C virus (HCV) treatment of Paritaprevir, Ombitasvir, Dasabuvir, Ritonavir, and Ribavirin (PODr + R) can cause severe liver injury in patients with advanced liver disease. Drug induced liver injury was observed in a small number of patients with decompensated cirrhosis treated with other DAAs, but has not been reported in patients with compensated cirrhosis. We report a case of a 74-year-old woman with chronic HCV and Child-Pugh class A cirrhosis (compensated cirrhosis) treated with PODr + R. The patient presented on day 14 of PODr + R therapy with jaundice and new-onset ascites. Her total bilirubin level increased to 23 mg/dL and international normalized ratio rose to 1.65, while aminotransferase levels remained relatively stable. Hepatitis C treatment was discontinued on day 24 and she gradually recovered. Follow-up testing showed that she achieved a sustained virologic response. In conclusion, hepatic decompensation developed within two weeks of starting treatment with Hasin Y et al . HCV cures after DAA-related drug-induced liver injury PODr + R in a patient with Child-Pugh class A cirrhosis and was characterized by jaundice and ascites with stable aminotransferase levels. Careful monitoring is warranted in patients with HCV-related cirrhosis treated with PODr + R.

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Sustained virological response with intravenous silibinin: individualized IFN‐free therapy via real‐time modelling of HCV kinetics

Cited by 34 publications

References 34 publications

Quantification of Hepatitis C Virus Cell-to-Cell Spread Using a Stochastic Modeling Approach

Quantification of Hepatitis C Virus Cell-to-Cell Spread Using a Stochastic Modeling Approach

Rational design and adaptive management of combination therapies for Hepatitis C virus infection

Hepatitis C virus cures after direct acting antiviral-related drug-induced liver injury: Case report

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