Identification of differentially expressed genes in hepatocellular carcinoma by integrated bioinformatic analysis

Hepatocellular carcinoma is one of the most common tumors in the world and has a high mortality rate. This study elucidates the mechanism of hepatocellular carcinoma- (HCC) related development. The HCC gene expression profile (GSE54238, GSE84004) was downloaded from Gene Expression Omnibus for comprehensive analysis. A total of 359 genes were identified, of which 195 were upregulated and 164 were downregulated. Analysis of the condensed results showed that “extracellular allotrope” is a substantially enriched term. “Cell cycle”, “metabolic pathway” and “DNA replication” are three significantly enriched Kyoto Encyclopedia of Genes and Genomespathways. Subsequently, a protein-protein interaction network was constructed. The most important module in the protein-protein interaction network was selected for path enrichment analysis. The results showed that CCNA2, PLK1, CDC20, UBE2C and AURKA were identified as central genes, and the expression of these five hub genes in liver cancer was significantly increased in The Cancer Genome Atlas. Univariate regression analysis was also performed to show that the overall survival and disease-free survival of patients in the high expression group were longer than in the expression group. In addition, genes in important modules are mainly involved in “cell cycle”, “DNA replication” and “oocyte meiosis” signaling pathways. Finally, through upstream miRNA analysis, mir-300 and mir-381-3p were found to coregulate CCNA2, AURKA and UBE2C. These results provide a set of targets that can help researchers to further elucidate the underlying mechanism of liver cancer.


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Liver cancer is one of the most common cancers in the world, and mainly 57 includes three different pathological types comprising hepatocellular carcinoma 58 (HCC), intrahepatic bile duct (ICC) and HCC-ICC hybrid types, among which HCC 59 accounts for 85% to 90% of all HCCs.The incidence and mortality of HCC increase 60 with age, and the incidence of HCC is about three times higher in men than in 61 women [1]. Although HCC treatment has made great progress in recent years, the 62 5-year survival rate of HCC patients is still <25% [2]. Therefore, more research are 63 needed to understand the molecular mechanisms of HCC development and 64 progression, which is important to develop more effective diagnostics and treatments. of prognostic signatures for HCC OS prediction [5]. Microarray technology has since 77 been applied to the study of genetic changes in HCC, has defined several different 78 genetic variants of the disease, and has identified genetic features that predict poor 79 outcomes and metastasis [6][7][8]. Although the cellular and molecular genetic 80 alterations of HCC have been more well-understood through these technologies, the 81 molecular mechanisms have not yet been fully elucidated. Based on the information obtained on the miRNA-mRNA pairs in starBase 145 (version 2.0), the upstream mRNAs were respectively predicted. The shared upstream 146 miRNAs of the mRNAs were then identified according to their expression levels.  (Table 1).  the DEGs were mainly enriched in 'arachidonic acid epoxygenase activity', 'retinol 186 dehydrogenase activity' and 'alcohol dehydrogenase activity, zinc-dependent' (Fig.   187 3).KEGG pathway analysis demonstrated that DEGs were significantly enriched in 188 'Cell cycle', 'Metabolic pathways', and 'DNA replication' (Fig. 4). analysis of genes in selected modules (Table 2).  'CCNA2', 'PLK1', 'CDC20', 'UBE2C' and 'AURKA' were significantly increased in 222 HCC samples as compared to normal liver samples (Fig. 7). We performed univariate Cox regression analysis. The results showed that 228 the five hub genes were significantly correlated with the overall survival(log-rank P 229 <.05) and disease free survival (logarithmic rank P <.05) of HCC patients (Fig. 8).

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These findings suggest that these hub genes may be a useful candidate for survival 231 prediction in HCC patients. According to the information in starBase v2.0, the miRanda prediction 238 program was selected to search for miRNAs upstream of the five hub genes. By 239 comparing DEM targets, CCNA2 was found to be a potential target of 48 miRNAs,

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AURKA was found to be a potential target of 31 miRNAs, UBE2C was found to be a 241 potential target of nine miRNAs, and PLK1 was found to be a potential target of three 242 miRNAs. CDC20 was not found to be a potential target of miRNA. Notably, upstream  In summary, this study identified candidate genes and pathways that may be 347 involved in HCC progression using a comprehensive analysis of two cohort data sets.

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These results may facilitate a deeper understanding of the molecular mechanisms 349 underlying HCC and provide a range of potential biomarkers for future research.

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These findings add important insights into the diagnosis and treatment of HCC.