Identifying hepatocellular carcinoma-related genes and pathways by system biology analysis

Abstract

Background: Previous researches have been focused on revealing the functions of each individual gene and/or pathway in the initiation, progression and maintenance of hepatocellular carcinoma (HCC). However, the mechanistic relationships among different genes and/or pathways are largely unknown.

Aims: In this study, we tended to uncover the potential molecular networks and critical genes which play important roles in HCC progression.

Methods: The transcriptional profiles from normal and HCC patient samples were analyzed and compared using bioinformatic methods, including differentially expressed gene (DEG) analysis, hierarchical clustering, construction of protein-protein interaction (PPI) network and GO-Elite analysis.

Results: Initially, the normal and HCC sample data were processed and 679 most dramatic DEGs were identified. The PPI network analysis indicates the significance of multiple biological processes as well as signaling pathways in affecting liver function and HCC progression. In addition, hierarchical clustering analysis showed the most significant modules and identified the relationship between different genes, and some important genes such as FOS, IGF1, ADH4, ITGA2 and LEF1 were found to be hubs which master each individual module.

Conclusion: Our study greatly improves the understanding of the HCC development in a systematic manner and provides the potential clue for exploiting drugs which might target the most significant genes and/or signaling pathways.