Identification of sulforaphane regulatory network in hepatocytes by microarray data analysis based on GEO database

基于GEO数据库的微阵列数据分析鉴定肝细胞中萝卜硫素调控网络

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Abstract

For the past several years, more and more attention has been paid to the exploration of traditional medicinal plants. Further studies have shown that more dietary consumption of cruciferous vegetables can prevent the occurrence of tumor, indicating the potential applications in the chemoprevention of cancer. Sulforaphane (SFN) has been identified by the National Cancer Institute as a candidate for chemopreventive research; it is one of several compounds selected by the National Cancer Institute's Rapid Access to Preventive Intervention Development Program and is currently in use. In the present study, based on the data of Gene Expression Omnibus database (GEO), the gene expression profile of hepatocytes that were treated with SFN was analyzed. The ANOVA and Limma packets in R were used to analyze the differentially expressed genes (DEGs). On this basis, gene ontology (GO) function and Kyoto Encyclopedia of Genes and Genomes (KEGG) signaling pathway enrichment were further analyzed. The core gene HSP90-α (cytosolic), class A member 1 (HSP90AA1) was screened by protein-protein interaction (PPI) network established by STRING and Cytoscape software for further study. Finally, miRNAs targeted HSP90AA1 were predicted by miRanda. All in all, based on the data of GSE20479 chip, the molecular mechanism of SFN on hepatocytes was studied by a series of bioinformatics analysis methods, and it indicated that SFN might effect on the hepatocyte by regulating HSP90AA1.

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