Transcriptional Regulatory Networks in Hepatitis C Virus-induced Hepatocellular Carcinoma

Abstract

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.

Figure 1

Schematic display of study design. As an overview of how this study was performed this diagram shows the process that the study proceeded in to create transcriptional regulatory networks for HCV-induced HCC.

Figure 2

Network visualization of transcription factors that were found to be the most common in regulation of differentially expressed genes in the comparison between Normal vs. Cirrhosis. The blue circles represent differentially expressed genes and their respective size is representative of their fold change value. The green circles represent the transcription factors that are regulating their respective differentially expressed genes.

Figure 3

Network visualization of transcription factors that were found to be the most common in regulation of differentially expressed genes between Normal and HCC. The blue circles represent differentially expressed genes and their respective size is representative of their fold change value. The green circles represent the transcription factors that are regulating their respective differentially expressed genes.

Figure 4

Network visualization of transcription factors that were found to be the most common in regulation of differentially expressed genes between cirrhosis and HCC. The blue circles represent differentially expressed genes and their respective size is representative of their fold change value. The green circles represent the transcription factors that are regulating their respective differentially expressed genes.

Figure 5

Network visualization of transcription factors that were found to be the most common in regulation of differentially expressed genes between cirrhosis HCC and HCC. The blue circles represent differentially expressed genes and their respective size is representative of their fold change value. The green circles represent the transcription factors that are regulating their respective differentially expressed genes.

Figure 6

Network visualization of most common miRNAs regulating differentially expressed genes between Normal and Cirrhosis. The blue circles represent differentially expressed genes and their respective size is representative of their fold change value. The red circles represent the miRNAs that are regulating their respective differentially expressed genes.

Figure 7

Network visualization of most common miRNAs regulating differentially expressed genes in the comparison between Normal and HCC. The blue circles represent differentially expressed genes and their respective size is representative of their fold change value. The red circles represent the miRNAs that are regulating their respective differentially expressed genes.

Figure 8

Network visualization of most common miRNAs regulating differentially expressed genes in the comparison between cirrhosis and HCC. The blue circles represent differentially expressed genes and their respective size is representative of their fold change value. The red circles represent the miRNAs that are regulating their respective differentially expressed genes.

Figure 9

Network visualization of most common miRNAs regulating differentially expressed genes in the comparison between Cirrhosis HCC and HCC. The blue circles represent differentially expressed genes and their respective size is representative of their fold change value. The red circles represent the miRNAs that are regulating their respective differentially expressed genes.

Figure 10

Overview of the transcription factors that regulate HCV induced HCC in each stage as the liver digresses to eventually becoming carcinomic; and the digression of miRNA expression in liver tissue as they digress to carcinoma.

Figure 11

Transcription Regulation HCV-induced HCC. This is an illustration of the master regulators in HCV-induced HCC and their differentially expressed genes. The key genes and transcription factors associated with each condition of the liver is illustrated as they were found in each of the 6 pairwise comparisons, also with the general expression of miRNAs as the liver transitions from one condition to the next.