Systems Biology Analyses to Define Host Responses to HCV Infection and Therapy

Abstract

While 170 million people worldwide are chronically infected with HCV, the response rate to the current treatment regimens of pegylated IFN-α (IFN) in combination with ribavirin is only approximately 55 % of all HCV patients undergoing therapy. This IFN-based therapy is now slated to serve as the backbone for future combination therapeutics involving direct-acting antiviral compounds, including HCV protease inhibitors, viral polymerase inhibitors, and other small molecules. It is essential that the application of IFN be improved for overall enhancement of therapy outcome to effectively cure HCV infection. Systems approaches, including genomics and network modeling, are particularly powerful tools that are now being used to dissect the underlying mechanisms of successful or failed treatment response in an effort to design improved IFN-based therapeutic regimens. Furthermore, systems applications can be used to define virus-host interactions and map their variation within viral and host genomes, leading to identification of targets for novel therapy strategies. Using these approaches, we have defined distinct hepatic expression and tissue distribution of innate immune signaling molecules and gene networks that associate with IFN-based treatment outcome for HCV infection. This chapter will focus on using systems approaches to understand the host response to both HCV infection and therapy to drive the development of improved HCV therapeutics.