Hepatitis B virus (HBV) and hepatitis C virus (HCV) infection are the
major causes of chronic liver disease, cirrhosis and hepatocellular
carcinoma (HCC). The resolution or chronicity of acute infection is
dependent on a complex interplay between virus and innate/adaptive
immunity. The mechanisms that lead a significant proportion of patients
to more severe liver disease are not clearly defined and involve virus
induced host gene/protein alterations. The utilization of protein
interaction networks (PINs) is expected to identify novel aspects of the
disease concerning the patients’ immune response to virus as well as the
main pathways that are involved in the development of fibrosis and HCC.
In this study, we designed several PINs for HBV and HCV and employed
topological, modular, and functional analysis techniques in order to
determine significant network nodes that correspond to prominent
candidate biomarkers. The networks were built using data from various
interaction databases. When the overall PINs of HBV and HCV were
compared, 48 nodes were found in common. The implementation of a
statistical ranking procedure indicated that three of them are of higher
importance