Abstract
Hepatocellular carcinoma (HCC) is common worldwide, and novel therapeutic targets and biomarkers are needed to improve outcomes. In this study, bioinformatics analyses combined with in vitro and in vivo assays were used to identify the potential therapeutic targets. Differentially expressed genes (DEG) in HCC were identified by the intersection between The Cancer Genome Atlas and International Cancer Genome Consortium data. The DEGs were evaluated by a gene set enrichment analysis as well as Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses. A protein interaction network, univariate Cox regression, and Lasso regression were used to screen out hub genes correlated with survival. Increased expression of the long noncoding RNA GBAP1 in HCC was confirmed in additional datasets and its biological function was evaluated in HCC cell lines and nude mice. Among 121 DEGs, GBAP1 and PRC1 were identified as hub genes with significant prognostic value. Overexpression of GBAP1 in HCC was confirmed in 21 paired clinical tissues and liver cancer or normal cell lines. The inhibition of GBAP1 expression reduced HCC cell proliferation and promoted apoptosis by inactivating the PI3K/AKT pathway in vitro and in vivo. Therefore, GBAP1 has a pro-oncogenic function in HCC and is a candidate prognostic biomarker and therapeutic target.
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