Systems-level modelling of hepatitis C virus Infection and treatment response

Abstract

Hepatitis C Virus (HCV) infection affects approximately 130-170 million people worldwide. Interferon-based treatment, the current standard of care, fails to cure a significant fraction of patients. The cause of this treatment failure remains poorly understood.

Interferon triggers a signaling cascade leading to the expression of hundreds of genes that together induce an antiviral state in cells. HCV interferes at multiple points in this network, thwarting its antiviral activity. Understanding how HCV overcomes interferon and causes treatment failure is of clinical importance.

Part I - Interferon Signaling and Treatment Response Treatment response is predicted to be an emergent property of the interferon-signaling network.

A reaction kinetics-based model revealed bistability:

One stable state where HCV establishes persistent infection.

Another stable state where HCV is cleared by interferon.

Cells that admit only the persistent state are refractory to interferon.

Viral kinetics modeling showed that when the fraction of interferon-refractory cells exceeds a critical threshold, interferon treatment fails.

Direct-acting antivirals (DAAs):

Monotherapy with DAAs fails in most patients.

In combination with interferon, DAAs significantly improve response rates, suggesting synergy.

Incorporating DAA activity into the interferon model showed that beyond a critical efficacy, the network exhibits a single steady state where HCV is cleared.

DAAs alter the emergent properties of the network, reducing the fraction of refractory cells and improving treatment response.

Conclusion: This provides a new conceptual basis for understanding patient responses to interferon-based therapies, explains the origin of synergy between DAAs and interferon, and offers a framework for rational treatment optimization.

Part II - Viral Kinetics in Cell Culture Recent development of cell culture systems supporting persistent HCV infection has yielded extensive data on replication, evolution, and drug impact.

A mathematical model of HCV viral kinetics in vitro was constructed.

Predictions of viral kinetics were in quantitative agreement with experimental observations.

By accounting for dependence of HCV entry on the target cell surface receptor CD81, the threshold number of E2-CD81 complexes required for viral entry was quantified.

These estimates may inform treatment strategies targeting the E2-CD81 interaction.

The model provides a framework for quantitative analysis of cell culture studies now widely used to investigate HCV infection.

Overall Conclusion This thesis demonstrates:

Treatment failure with interferon arises from bistability in the interferon-signaling network.

DAAs synergize with interferon by altering network properties.

Mathematical modeling of HCV kinetics in vitro provides mechanistic insights into viral entry and replication.

Together, these findings advance understanding of HCV pathogenesis and therapeutic optimization.