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Key signaling pathways, genes and transcription factors associated with hepatocellular carcinoma.


ABSTRACT: The purpose of the present study was to investigate the underlying molecular mechanism of hepatocellular carcinoma (HCC) using bioinformatics approaches. The microarray dataset GSE64041 was downloaded from the Gene Expression Omnibus database, which included 60 tumor liver samples and 60 matched control samples. Differentially expressed genes (DEGs) between HCC and control groups were identified. Then functional enrichment analyses, protein?protein interaction (PPI) network, sub?network and integrated transcription factor (TF)?microRNA (miRNA)?target network analyses were performed for these DEGs. A total of 378 DEGs were obtained, including 101 upregulated and 277 downregulated DEGs. In addition, functional enrichment analysis for DEGs in the sub?network revealed 'cell division' and 'cell cycle' as key Gene Ontology (GO) terms and pathways. Topoisomerase (DNA) II? (TOP2A) and integrin subunit ?2 (ITGA2) were hub nodes in the PPI network. TOP2A, cyclin dependent kinase 1 (CDK1) and polo like kinase 1 (PLK1) were revealed to be hub nodes in the sub?network. Finally, 4 TFs including forkhead box M1 (FOXM1), E2F transcription factor 4 (E2F4), SIN3 transcription regulator family member A (SIN3A) and transcription factor 7 like 1 (TCF7L1) were obtained through integrated network analysis. TOP2A, ITGA2, PLK1 and CDK1 may be key genes involved in HCC development. 'Cell division' and 'cell cycle' were indicated to act as key GO terms and Kyoto Encyclopedia of Genes and Genomes pathways in HCC. In addition, FOXM1, TCF7L1, E2F4 and SIN3A were revealed to be key TFs associated with HCC.

SUBMITTER: Wang J 

PROVIDER: S-EPMC5983994 | biostudies-literature | 2018 Jun

REPOSITORIES: biostudies-literature

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Key signaling pathways, genes and transcription factors associated with hepatocellular carcinoma.

Wang Jingcheng J   Tian Yang Y   Chen Hui H   Li Hui H   Zheng Shusen S  

Molecular medicine reports 20180412 6


The purpose of the present study was to investigate the underlying molecular mechanism of hepatocellular carcinoma (HCC) using bioinformatics approaches. The microarray dataset GSE64041 was downloaded from the Gene Expression Omnibus database, which included 60 tumor liver samples and 60 matched control samples. Differentially expressed genes (DEGs) between HCC and control groups were identified. Then functional enrichment analyses, protein‑protein interaction (PPI) network, sub‑network and inte  ...[more]

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