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http://dx.doi.org/10.7314/APJCP.2012.13.8.3681

Transcription Regulation Network Analysis of MCF7 Breast Cancer Cells Exposed to Estradiol  

Wu, Jun-Zhao (Breast Cancer Diagnosis and Treatment Center, Henan Cancer Hospital)
Lu, Peng (Department of Oncological Surgery, People's Hospital of Zhengzhou)
Liu, Rong (Academician Experts Workstation of Henan Province, People's Hospital of Zhengzhou)
Yang, Tie-Jian (Department of Oncological Surgery, People's Hospital of Zhengzhou)
Publication Information
Asian Pacific Journal of Cancer Prevention / v.13, no.8, 2012 , pp. 3681-3685 More about this Journal
Abstract
Background: In breast cancer, estrogen receptors have been demonstrated to interact with transcription factors to regulate target gene expression. However, high-throughput identification of the transcription regulation relationship between transcription factors and their target genes in response to estradiol is still in its infancy. Purpose: Thus, the objective of our study was to interpret the transcription regulation network of MCF7 breast cancer cells exposed to estradiol. Methods: In this work, GSE11352 microarray data were used to identify differentially expressed genes (DEGs). Results: Our results showed that the MYB (v-myb myeloblastosis viral oncogene homolog [avian]), PGR (progesterone receptor), and MYC (v-myc myelocytomatosis viral oncogene homolog [avian]) were hub nodes in our transcriptome network, which may interact with ER and, in turn, regulate target gene expression. MYB can up-regulate MCM3 (minichromosome maintenance 3) and MCM7 expression; PGR can suppress BCL2 (B-cell lymphoma 2) expression; MYC can inhibit TGFB2 (transforming growth factor, beta 2) expression. These genes are associated with breast cancer progression via cell cycling and the $TGF{\beta}$ signaling pathway. Conclusion: Analysis of transcriptional regulation may provide a better understanding of molecular mechanisms and clues to potential therapeutic targets in the treatment of breast cancer.
Keywords
Regulation network; network motif analysis; breast cancer; estradiol; microarray; transcriptome network;
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