Abstract
Hepatocellular carcinoma (HCC) is a common yet deadly form of malignant cancer. However, the specific mechanisms involved in HCC diagnosis have not yet fully elucidated. Herein, we screened four publically available Gene Expression Omnibus (GEO) expression profiles (GSE14520, GSE29721, GSE45267 and GSE60502), and used them to identify 409 differentially expressed genes (DEGs), including 142 and 267 up- and down-regulated genes, respectively. The DAVID database was used to look for functionally enriched pathways among DEGs, and the STRING database and Cytoscape platform were used to generate a protein-protein interaction (PPI) network for these DEGs. The cytoHubba plug-in was utilized to detect 185 hub genes, and three key clustering modules were constructed with the MCODE plug-in. Gene functional enrichment analyses of these three key clustering modules were further performed, and nine core genes including BIRC5, DLGAP5, DTL, FEN1, KIAA0101, KIF4A, MCM2, MKI67, and RFC4, were identified in the most critical cluster. Subsequently, the hierarchical clustering and expression of core genes in TCGA liver cancer tissues were analyzed using the UCSC Cancer Genomics Browser, and whether elevated core gene expression was linked to a poor prognosis in HCC patients was assessed using the GEPIA database. The PPI of the nine core genes revealed an interaction between FEN1, MCM2, RFC4, and BIRC5. Furthermore, the expression of FEN1 was positively correlated with that of three other core genes in TCGA liver cancer tissues. FEN1 expression in HCC and other tumor types was assessed with the FIREBROWSE and ONCOMINE databases, and results were verified in HCC samples and hepatoma cells. FEN1 levels were also positively correlated with tumor size, distant metastasis and vascular invasion. In conclusion, we identified nine core genes associated with HCC development, offering novel insight into HCC progression. In particular, the aberrantly elevated FEN1 may represent a potential biomarker for HCC diagnosis and treatment.
Highlights
Hepatocellular carcinoma remains among the most common and deadly forms of cancer globally, posing a significant threat to human life (Forner, Reig & Bruix, 2018)
With respect to biological processes (BP), up-regulated differentially expressed genes (DEGs) were primarily enriched in processes such as mitotic nuclear division, cell division, cell cycle, DNA replication, and mitotic sister chromatid segregation (Fig. S1A), while down-regulated DEGs were primarily enriched in processes such as redox process, the cytochrome 450 pathway, drug metabolism, and negative regulation of growth (Fig. S2A)
With respect to cellular components (CC), up-regulated DEGs were primarily enriched in the nucleoplasm, nucleus, cytoplasm, spindle, and cellular intermediates (Fig. S1B), while down-regulated DEGs were mostly enriched in extracellular exosomes, organelle membranes, blood microparticles, extracellular regions, and the mitochondrial matrix (Fig. S2B)
Summary
Hepatocellular carcinoma remains among the most common and deadly forms of cancer globally, posing a significant threat to human life (Forner, Reig & Bruix, 2018). A large number of biomarkers for the diagnosis of HCC have been identified (Turnbull, Sud & Houlston, 2018), the specific molecular mechanisms related to the onset, recurrence and treatment of HCC remain obscure. It is essential to identify and exploit novel biomarkers involved in HCC onset and progression to better understand the pathogenesis of HCC. Precision medicine relies upon initially exploring potential therapeutic targets via high-throughput sequencing technologies (Robinson, 2012), as these technologies allow for the large-scale investigation of altered gene expression in the context of disease (Chen et al, 2010). This study sought to analyze genes involved in liver cancer development using a range of available liver cancer-related gene chip datasets, with the goal of identifying potential novel molecular targets for liver cancer treatment and diagnosis
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