A systematic investigation and network interaction analysis on preventive treatments against HepG2 cancer cells from a genomic-level perspective

Abstract

Worldwide, the fourth most common malignancy leading to death via cancer transformation is hepatocellular carcinoma (HCC). Notwithstanding various preventive approaches, the incidence and mortality of patients with HCC continue to increase. However, a successful early diagnosis of HCC is beneficial given a potentially curative treatment. We systematically searched the publicly available NCBI microarray database to extract the required information on different preventive treatments and their affected genes and signaling pathways on HCC. Furthermore, the significant genes were analyzed through the Kaplan-Meier tool for overall survival, relapse-free survival, progression-free survival, and disease-specific survival rates. Subsequently, we assessed the protein-protein network interaction analysis and their corresponding drugs and diseases. The thorough screening of the literature microarray gene datasets revealed that various compounds could be implicated in HCC prevention. The results showed that nine genes (i.e., FGA, FGG, TP53, HELLS, CCNA2, MCM10, MCM2, PCTP, and CYP24A1) modulated the four above-mentioned survival rates. Furthermore, the associations between genes, drugs, and related diseases discovered 39 out of 61 medications covered potential anticancer agents. Finally, we demonstrated that numerous signaling pathways were simultaneously modulated in HCC. In conclusion, this work underlines the importance of the genomic-level perspective in studying HCC treatment and development.