Bioinformatics analysis reveals meaningful markers and outcome predictors in HBV-associated hepatocellular carcinoma

Experimental and Therapeutic Medicine
Lijie ZhangBin Liang

Abstract

Hepatocellular carcinoma (HCC) is the most common type of malignant neoplasm of the liver with high morbidity and mortality. Extensive research into the pathology of HCC has been performed; however, the molecular mechanisms underlying the development of hepatitis B virus-associated HCC have remained elusive. Thus, the present study aimed to identify critical genes and pathways associated with the development and progression of HCC. The expression profiles of the GSE121248 dataset were downloaded from the Gene Expression Omnibus database and the differentially expressed genes (DEGs) were identified. Gene Ontology (GO) and Kyoto Encyclopedia of Gene and Genome (KEGG) analyses were performed by using the Database for Annotation, Visualization and Integrated Discovery. Subsequently, protein-protein interaction (PPI) networks were constructed for detecting hub genes. In the present study, 1,153 DEGs (777 upregulated and 376 downregulated genes) were identified and the PPI network yielded 15 hub genes. GO analysis revealed that the DEGs were primarily enriched in 'protein binding', 'cytoplasm' and 'extracellular exosome'. KEGG analysis indicated that DEGs were accumulated in 'metabolic pathways', 'chemical carcinogenesis' and 'fatty ...Continue Reading

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Datasets Mentioned

BETA
GSE54236
GSE76427
GSE121248
GPL570

Methods Mentioned

BETA
chips
chip

Software Mentioned

GEO2R
GEPIA
Bingo
Cytoscape
DAVID
GraphPad prism
Search Tool for the Retrieval

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