S Y Yang1, H Ren1, C F Li2, H Tang1. 1. Department of Infectious Diseases, Institute for Viral Hepatitis, The Key Laboratory of Molecular Biology for Infectious Diseases, Chinese Ministry of Education, The Second Affiliated Hospital of Chongqing Medical University, Chongqing 400010, China. 2. Department of Gastroenterology, The Second Affiliated Hospital of Chongqing Medical University, Chongqing 400010, China.
Abstract
Objective: To screen out and explore the core gene (Hub gene) involvement and the potential role of cyclin B2 (CCNB2) in the development and prognosis of hepatocellular carcinoma (HCC) through bioinformatics methods. Methods: Four HCC-related datasets were screened, and downloaded from the GEO database. GEO2R tool was used to analyze data and identify the differentially expressed genes (DEGs). Gene Ontology (GO) and KEGG signal pathway enrichment analysis were completed using DAVID database and Cytoscape (ClueGO) plug-in, respectively. Protein-protein interaction network (PPI) of DEGs was established using the STRING database. Cytoscape software was used to visualize PPI network, key modules (cluster) construction and core genes identification. UCSC and UALCAN database were used to analyze the differential expression and survival of TCGA hepatocellular carcinoma core genes. Firebrowse, Oncomine and UALCAN databases were used to analyze the expression of core genes in multiple tumors including HCC. Real-time quantitative reverse transcription PCR (RT-qPCR) was used to detect the expression levels of candidate genes in HCC tissues and liver cancer cell lines. Results: A total of 73 DEGs were identified from the four datasets, including 15 up-regulated genes and 58 down-regulated genes. KEGG pathway enrichment analysis signal showed that DEGs were mainly enriched in tumor-related pathways. PPI network based on DEGs had screened the key modules and 10 core genes. CCNB2 and NCAPG were highly expressed in liver cancer tissues in multiple databases. CCNB2 was positively correlated with NCAPG and was considered as a key gene related to prognosis (P < 0.01). RT-qPCR results showed that CCNB2 was highly expressed in human HCC tissues and cell lines (P < 0.01). Conclusion: Successfully screened DEGs and core genes related to HCC. Among them, CCNB2 is highly expressed in HCC and is related to the survival and prognosis of patients, so it is expected to become a biomarker for the diagnosis and prognosis of HCC.
Objective: To screen out and explore the core gene (Hub gene) involvement and the potential role of cyclin B2 (CCNB2) in the development and prognosis of hepatocellular carcinoma (HCC) through bioinformatics methods. Methods: Four HCC-related datasets were screened, and downloaded from the GEO database. GEO2R tool was used to analyze data and identify the differentially expressed genes (DEGs). Gene Ontology (GO) and KEGG signal pathway enrichment analysis were completed using DAVID database and Cytoscape (ClueGO) plug-in, respectively. Protein-protein interaction network (PPI) of DEGs was established using the STRING database. Cytoscape software was used to visualize PPI network, key modules (cluster) construction and core genes identification. UCSC and UALCAN database were used to analyze the differential expression and survival of TCGA hepatocellular carcinoma core genes. Firebrowse, Oncomine and UALCAN databases were used to analyze the expression of core genes in multiple tumors including HCC. Real-time quantitative reverse transcription PCR (RT-qPCR) was used to detect the expression levels of candidate genes in HCC tissues and liver cancer cell lines. Results: A total of 73 DEGs were identified from the four datasets, including 15 up-regulated genes and 58 down-regulated genes. KEGG pathway enrichment analysis signal showed that DEGs were mainly enriched in tumor-related pathways. PPI network based on DEGs had screened the key modules and 10 core genes. CCNB2 and NCAPG were highly expressed in liver cancer tissues in multiple databases. CCNB2 was positively correlated with NCAPG and was considered as a key gene related to prognosis (P < 0.01). RT-qPCR results showed that CCNB2 was highly expressed in human HCC tissues and cell lines (P < 0.01). Conclusion: Successfully screened DEGs and core genes related to HCC. Among them, CCNB2 is highly expressed in HCC and is related to the survival and prognosis of patients, so it is expected to become a biomarker for the diagnosis and prognosis of HCC.