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

Abstract

31Hepatocellular carcinoma is one of the most common tumors in the world 32 and has a high mortality rate. This study elucidates the mechanism of hepatocellular 33 carcinoma-(HCC) related development. The HCC gene expression profile 34 (GSE54238, GSE84004) was downloaded from Gene Expression Omnibus for 35 comprehensive analysis. A total of 359 genes were identified, of which 195 were 36 upregulated and 164 were downregulated. Analysis of the condensed results showed 37 that "extracellular allotrope" is a substantially enriched term. "Cell cycle", "metabolic 38 pathway" and "DNA replication" are three significantly enriched Kyoto Encyclopedia 39 of Genes and Genomespathways. Subsequently, a protein-protein interaction network 40 was constructed. The most important module in the protein-protein interaction 41 network was selected for path enrichment analysis. The results showed that CCNA2, 42 PLK1, CDC20, UBE2C and AURKA were identified as central genes, and the 43 expression of these five hub genes in liver cancer was significantly increased in The 44 Cancer Genome Atlas. Univariate regression analysis was also performed to show that 45 the overall survival and disease-free survival of patients in the high expression group 46 were longer than in the expression group. In addition, genes in important modules are 47 mainly involved in "cell cycle", "DNA replication" and "oocyte meiosis" signaling 48 pathways. Finally, through upstream miRNA analysis, mir-300 and mir-381-3p were 49 found to coregulate CCNA2,AURKA and UBE2C. These results provide a set of 50 targets that can help researchers to further elucidate the underlying mechanism of 51 liver cancer. 3 52 53 Key Words HCC;GEO;TCGA;DEGs;bioinformatic analysis; 54 55 1. Introduction 56 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 59accounts 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. 65 66 At present, gene microarray technology has been widely used to collect 67 gene chip expression profiling data and to study gene expression profiles in many 68 human cancers. A large amount of data has been published in public database 69 platforms, and researchers have integrated these databases to find valuable 70 information about cancer pathogenesis. Lau et al. identified approximately 4,000 71 genes in 10 pairs of HCC and non-tumor tissues by microarray technology[3].Zhou et 72 al. analyzed the mRNA expression profiles of a large number of human HCC 73 spe...

Differentially expressed discriminative genes and significant meta-hub genes based key genes identification for hepatocellular carcinoma using statistical machine learning

“…Our findings also showed that CDC20 was a potential key biomarker that played an crucial or essential role for the development and progression of HCC. Different existing studies also supported our findings 10,13,14,17,18,20,24,30,32,37,40,41,44,48,50,[55][56][57] .…”

“…Similarly, we proposed UBE2C as a key or core predictor for development of HCC, which was supported by various existing studies 10,18,33,36,41,44,58 . Xiong et al 94 suggested UBE2C as a potential biomarker or gene for HCC.…”

A systematic analysis of molecular mechanisms in non-metastatic renal cancer delineates affected regulatory pathways and genes in tumor growth

“…Another hub gene, AURKA, can increase the expression of anti-apoptotic molecules in tumorigenic tissues. This gene encodes auroa kinase A, which affects the spindle, centrosome, and chromosome segregation therefore it controls G2 and mitosis phases in the cell cycle (62). In addition, it was indicated that overexpression of AURKA can cause genomic instability and produce cells with multinuclear, overexpressed in neuroblastoma, liver cancer, and kidney carcinoma (63).…”

Identification of Differentially Expressed Genes Associated with the Prognosis and Diagnosis of Hepatocellular Carcinoma by Integrated Bioinformatics Analysis

“…Meng et al identified 11 hub genes as closely connected to pathogenesis and HCC prognosis (CCNB2, CDK1, CCNB1, CDC20, CCNA2, TOP2A, MELK, TPX2, PBK, KIF20A, and AURKA) [ 37 ]. Yan and Liu identified five hub genes CCNA2, PLK1, CDC20, UBE2C, and AURKA of hepatic cancer, which were dramatically elevated in the Cancer Genome Atlas [ 19 ]. Zhang et al screened 293 frequent DEGs, comprising 103 upregulated and 190 downregulated genes.…”

“…The diverse factors implicated in liver cancer are cellular tumor antigen p53 (TP53), axin-1 (AXIN1), catenin β-1 (CTNNB1), and telomerase reverse transcriptase (TERT) promoters as well as other primary genes for mutation generation, p53 cell cycle system, WNT/β-catenin, oxidative stress, RAS/RAF/MAPK, and PI3K/AKT/MTOR pathways along with other main primary signaling pathways. Liu et al used highly efficient microarray technology to screen molecular indicators across all human cancerous tumors, especially for liver cancer, by using Gene Expression Omnibus (GEO) datasets and The Cancer Genome Atlas (TCGA) RNA-sequence, and analysed with the help of bioinformatics methods [18][19][20][21][22]. Gene chip technology can also reliably represent the molecular expression profile and detect genetic variants correlated with HCC in liver cancer studies [23,24].…”