Screening and Functional Prediction of Key Candidate Genes in Hepatitis B Virus-Associated Hepatocellular Carcinoma

Abstract

Background. The molecular mechanism by which hepatitis B virus (HBV) induces hepatocellular carcinoma (HCC) is still unknown. The genomic expression profile and bioinformatics methods were used to investigate the potential pathogenesis and therapeutic targets for HBV-associated HCC (HBV-HCC). Methods. The microarray dataset GSE55092 was downloaded from the Gene Expression Omnibus (GEO) database. The data was analyzed by the bioinformatics software to find differentially expressed genes (DEGs). Gene Ontology (GO) enrichment analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, ingenuity pathway analysis (IPA), and protein-protein interaction (PPI) network analysis were then performed on DEGs. The hub genes were identified using Centiscape2.2 and Molecular Complex Detection (MCODE) in the Cytoscape software (Cytoscape_v3.7.2). The survival data of these hub genes was downloaded from the Gene Expression Profiling Interactive Analysis (GEPIA). Results. A total of 2264 mRNA transcripts were differentially expressed, including 764 upregulated and 1500 downregulated in tumor tissues. GO analysis revealed that these DEGs were related to the small-molecule metabolic process, xenobiotic metabolic process, and cellular nitrogen compound metabolic process. KEGG pathway analysis revealed that metabolic pathways, complement and coagulation cascades, and chemical carcinogenesis were involved. Diseases and biofunctions showed that DEGs were mainly associated with the following diseases or biological function abnormalities: cancer, organismal injury and abnormalities, gastrointestinal disease, and hepatic system disease. The top 10 upstream regulators were predicted to be activated or inhibited by Z-score and identified 25 networks. The 10 genes with the highest degree of connectivity were defined as the hub genes. Cox regression revealed that all the 10 genes (CDC20, BUB1B, KIF11, TTK, EZH2, ZWINT, NDC80, TPX2, MELK, and KIF20A) were related to the overall survival. Conclusion. Our study provided a registry of genes that play important roles in regulating the development of HBV-HCC, assisting us in understanding the molecular mechanisms that underlie the carcinogenesis and progression of HCC.

Identification of the miRNA signature and key genes in colorectal cancer lymph node metastasis

“…Functional annotation indicated that these five DE-miRNAs were mostly related to the cellular nitrogen compound metabolic process, protein complex and RNA binding. This is consistent with the recognition that the cellular nitrogen compound metabolic process and protein complex play important roles in tumor development [ 27 , 28 ]. KEGG pathway analysis indicated that the target genes of five DE-miRNAs were mainly enriched in ten pathways, including fatty acid metabolism, fatty acid biosynthesis, hippo signaling pathway, proteoglycans in cancer, lysine degradation and so on.…”

Construction and validation of prognostic signature for hepatocellular carcinoma basing on hepatitis B virus related specific genes

“…TPX2 has been associated with the carcinogenesis and proliferation of HBV-related HCC [ 39 , 40 ], while more details are not clear. KIF20A was reported to be related to the OS of HCC patients [ 41 ], besides, a prognostic marker based on 12 genes included KIF20A showed good predictive effect [ 42 ], both of which supported our results. High expression of CCL20 has been documented to be correlated with the poor prognosis of HCC patients [ 43 ].…”

Construction and validation of a joint diagnosis model based on random forest and artificial intelligence network for hepatitis B-related hepatocellular carcinoma

“…An ANN model for the diagnosis and screening of HBV-related HCC was constructed based on nine important genes from random forests. Of these nine genes, TOP2A and BUB1B have been extensively studied in HCC [23][24][25][26][27] . KMO [28,29] , CDHR2 [30] , CLEC1B [31] , CXCL14 [32] and FCN2 [33] were signi cantly decreased in HCC tissues (or) and cell lines overexpression of these genes exhibits tumour-inhibitory effects towards HCC [28,29] , including inhibits tumor formation and the growth of subcutaneous tumours, suppresses proliferation, migration and invasion of HCC cells, EMT and induced apoptosis.…”