Formal Modeling of the Key Determinants of Hepatitis C Virus (HCV) Induced Adaptive Immune Response Network: An Integrative Approach to Map the Cellular and Cytokine-Mediated Host Immune Regulations

HCV is a major causative agent of liver infection and is the leading cause of Hepatocellular carcinoma (HCC). To understand the complexity in interactions within the HCV induced immune signaling networks, a logic-based diagram is generated based on multiple reported interactions. A simple conceptual framework is presented to explore the key determinants of the immune system and their functions during HCV infection. Furthermore, an abstracted sub-network is modeled qualitatively which consists of both the key cellular and cytokine components of the HCV induced immune system. In the presence of NS5A protein of HCV, the behaviors and the interplay amongst the natural killer (NK) and T regulatory (Tregs) cells along with cytokines such as IFN-γ, IL-10, IL-12 are predicted. The overall modelling approach followed in this study comprises of prior knowledge-based logical interaction network, network abstraction, parameter estimation, regulatory network construction and analysis through state graph, enabling the prediction of paths leading to both, disease state and a homeostatic path/cycle predicted based on maximum betweenness centrality. To study the continuous dynamics of the network, Petri net (PN) model was generated. The analysis implicates the critical role of IFN-γ producing NK cells in recovery while, the role of IL-10 and IL-12 in pathogenesis. The predictive ability of the model implicates that IL-12 has a dual role under varying circumstances and leads to varying disease outcomes. This model attempts to reduce the noisy biological data and captures a holistic view of the key determinants of the HCV induced immune response.