Hepatocellular carcinoma (HCC) is a global health problem with complex etiology and pathogenesis. Microarray data are increasingly being used as a novel and effective method for cancer pathogenesis analysis. An integrative analysis of genes and miRNA for HCC was conducted to unravel the potential prognosis of HCC. Two gene microarray datasets (GSE89377 and GSE101685) and two miRNA expression profiles (GSE112264 and GSE113740) were obtained from Gene Expression Omnibus database. A total of 177 differently expressed genes (DEGs) and 80 differently expressed miRNAs (DEMs) were screened out. Functional enrichment of DEGs was proceeded by Clue GO and these genes were significantly enriched in the chemical carcinogenesis pathway. A protein-protein interaction network was then established on the STRING platform, and ten hub genes (CDC20, TOP2A, ASPM, NCAPG, AURKA, CYP2E1, HMMR, PRC1, TYMS, and CYP4A11) were visualized via Cytoscape software. Then, a miRNA-target network was established to identify the hub dysregulated miRNA. A key miRNA (hsa-miR-124-3p) was filtered. Finally, the miRNA-target-transcription factor network was constructed for hsa-miR-124-3p. The network for hsa-miR-124-3p included two transcription factors (TFs) and five targets. These identified DEGs and DEMs, TFs, targets, and regulatory networks may help advance our understanding of the underlying pathogenesis of HCC.
Keywords: Bioinformatic; Hepatocellular carcinoma; Hub genes; Key miRNA; Regulatory network.
© 2021. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.