Abstract

BACKGROUND: It is widely known that hepatocellular carcinoma (HCC) has high rates of morbidity and mortality. A large number of studies have indicated that pseudogenes have an important effect on the carcinogenesis of HCC. Pseudogenes can play a role through the ceRNA network. There have been numerous studies on lncRNA-miRNA-mRNA and circRNA-miRNA-mRNA networks. However, the pseudogene-miRNA-mRNA network in HCC has rarely been researched or reported on.

MATERIAL AND METHODS: The Cancer Genome Atlas (TCGA) database was researched and differences between selected genes were studied. A pseudogene-miRNA-mRNA network was then constructed and clustering of pseudogenes was studied. The diagnostic value of the selected pseudogenes, their functions, and pathways were investigated using available databases to understand their possible pathogenic mechanism in HCC. The protein-protein interaction network of target genes was found and the top 10 hub genes were identified. Expression of hub genes in HCC tissues was then detected by RT-qPCR.

RESULTS: By analyzing the gene difference and clinical data of HCC, we constructed a ceRNA network composed of 4 pseudogenes, 8 miRNAs, and 30 mRNAs. The pseudogenes AP000769.1, KRT16P1, KRT16P3, and RPLP0P2 were all correlated with the diagnosis and prognosis of HCC. Functional analyses through the Kyoto Encyclopedia of Genes and Genomes and the Gene Ontology databases indicated that pseudogenes can affect the physiological process of HCC through the p53 pathway. The top 10 hub genes identified were all highly expressed in HCC tissues and affected the patient survival rate.

CONCLUSIONS: In this study, 4 pseudogenes related to the diagnosis and prognosis of liver cancer were found through the construction of a ceRNA network. These 4 pseudogenes might constitute new therapeutic targets for liver cancer patients.

Keywords: Carcinoma, Hepatocellular, Molecular Targeted Therapy, Pseudogenes, Computational Biology, Databases, Genetic, Gene Expression Profiling, Gene Expression Regulation, Neoplastic, gene ontology, Gene Regulatory Networks, Liver Neoplasms, MicroRNAs, Prognosis, Protein Interaction Maps, RNA, Circular, RNA, Long Noncoding, RNA, Messenger