Understanding the transcriptional regulatory elements that influence the progression of liver disease in the presence of hepatitis C virus (HCV) infection is critical for the development of diagnostic and therapeutic approaches. Systems biology provides a roadmap by which these elements may be integrated. In this study, a previously published dataset of 124 microarray samples was analyzed in order to determine differentially expressed genes across four tissue types/conditions (normal, cirrhosis, cirrhosis HCC, and HCC). Differentially expressed genes were assessed for their functional clustering and those genes were annotated with their potential transcription factors and miRNAs. Transcriptional regulatory networks were constructed for each pairwise comparison between the 4 tissue types/conditions. Based on our analysis, it is predicted that the disruption in the regulation of transcription factors such as AP-1, PPARγ, and NF-κB could contribute to the liver progression from cirrhosis to steatosis and eventually to HCC. Whereas the condition of the liver digresses, the downregulation of miRNAs' (such as miR-27, Let-7, and miR-106a) expression makes the transition of the liver through each pathological stage more apparent. This preliminary data can be used to guide future experimental work. An understanding of the transcriptional regulatory attributes acts as a road map to help design interference strategies in order to target the key regulators of progression of HCV induced HCC.