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Multiple omics analysis of the protective effects of SFN on estrogen-dependent breast cancer cells.
Huang, Hui; Cao, Shuyuan; Zhang, Zhan; Li, Lei; Chen, Feng; Wu, Qian.
Affiliation
  • Huang H; Department of Biostatistics and China International Cooperation Center for Environment and Human Health, School of Public Health, Nanjing Medical University, Nanjing, 211166, China.
  • Cao S; Department of Hygienic Analysis and the Key Laboratory of Modern Toxicology of Ministry of Education, School of Public Health, Nanjing Medical University, Nanjing, 211166, China.
  • Zhang Z; Department of Hygienic Analysis and the Key Laboratory of Modern Toxicology of Ministry of Education, School of Public Health, Nanjing Medical University, Nanjing, 211166, China.
  • Li L; Department of Hygienic Analysis and the Key Laboratory of Modern Toxicology of Ministry of Education, School of Public Health, Nanjing Medical University, Nanjing, 211166, China.
  • Chen F; Department of Biostatistics and China International Cooperation Center for Environment and Human Health, School of Public Health, Nanjing Medical University, Nanjing, 211166, China. fengchen@njmu.edu.cn.
  • Wu Q; Department of Hygienic Analysis and the Key Laboratory of Modern Toxicology of Ministry of Education, School of Public Health, Nanjing Medical University, Nanjing, 211166, China. wuqian@njmu.edu.cn.
Mol Biol Rep ; 47(5): 3331-3346, 2020 May.
Article in En | MEDLINE | ID: mdl-32342433
In recent years, sulforaphane (SFN) has been shown to have antitumor effects. To better understand the molecular basis of SFN intervention in estrogen-dependent breast cancer, integrated multi-omics data analysis was used to provide evidence and insights into molecular biology. MCF-7 breast cancer cells were treated with estradiol (E2) or/and SFN. Genome-wide DNA methylation analysis was performed by using microarray platforms. The protein profile was analyzed by TMT labeled HPLC-MS/MS. The metabolic profile was obtained by GC-MS and UPLC-MS methods. Multivariate statistics analyses, such as PCA and hierarchical clustering, were performed. The Gene Ontology (GO) and KEGG analysis were used to perform enrichment analysis of biological processes and pathways. A set of differentially methylated genes and differentially expressed proteins and metabolites were found, which indicated that SFN may reverse the adverse effects induced by E2. Integrated analysis revealed cancer genes that responded to estrogen and other pathways frequently associated with cancer. Co-pathway analysis revealed that the reversal effects of SFN were associated with purine metabolism and glutathione metabolism. The integrated omics analysis outlined a promising blueprint of the relationship of biological molecules in different dimensions, which will be beneficial for understanding the mechanism of anti-breast cancer effects and for new targets of medicines.
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Isothiocyanates Limits: Female / Humans Language: En Journal: Mol Biol Rep Year: 2020 Document type: Article Affiliation country: Country of publication:

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Isothiocyanates Limits: Female / Humans Language: En Journal: Mol Biol Rep Year: 2020 Document type: Article Affiliation country: Country of publication: