Metabolomics,Unknown,Transcriptomics,Genomics,Proteomics

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Transcription profiling by array of human breast cancer cell line BT-474 with annexin A1 over-expression or silenced with siRNA to demonstrate design of multi-condition experiments

ABSTRACT: Multiple-condition experiment was desinged to be any number of conditions in an experiment without replicate observations for microarray and used to identify genes differentially expressed between different pairs of conditions (treatments).
In this study we used breast cancer stable cell lines for overexpressing and silencing annexin A1 (ANXA1), which belongs to a family of -dependent phospholipid binding proteins and are preferentially located on the cytosolic face of the plasma membrane. Cell lines overexpressing ANXA1 (MDA_MB-453/cDNA) were generated by introducing retroviral vectors containing ANXA1 cDNA (pBabe/ANXA1 cDNA) into breast cancer cell line MDA-MB-453 (a low expressor of ANXA1). Breast cancer cell line BT-474, a high expressor of ANXA1, was infected with ANXA1 siRNA-plasmid viruses to knockdown ANAXAI expressor (BT-474/siRNA) where nucleotides corresponding to siRNA were synthesized and ligated into the pLNCX retroviral vector [35,36]. We also used a pLNCX/U6 empty vector to infect BT-474 and obtained an empty vector expressor. Therefore, 5 breast cancer cell lines (MDA_MB-453, MDA_MB-453/cDNA, BT-474, BT-474/siRNA, and BT-474/U6) are attributed to two genotypes: MDA_MB-453 and BT-474. MCE was performed for microarray analysis with these 5 breast cancer cell lines, that is, only one sample was drawn from each breast cancer cell line.

ORGANISM(S): Homo sapiens

SUBMITTER: Yuande Tan

PROVIDER: E-MEXP-2775 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Project description:The complexity of gene regulation has created obstacles to defining mechanisms that establish the patterns of gene expression characteristic of the different clinical phenotypes of breast cancer. Transcription factor TFAP2C plays a critical role in the regulation of both estrogen receptor-alpha (ERM-NM-1) and c-ErbB2/HER2 (Her2). Herein, we performed chromatin immunoprecipitation and direct sequencing (ChIP-seq) for TFAP2C in four breast cancer cell lines representing different clinical phenotypes. Comparing the genomic binding sites for TFAP2C in the various cell lines, we identified that glutathione peroxidase (GPX1) is regulated by TFAP2C through an AP-2 regulatory region in the promoter of the GPX1 gene. Knock-down of TFAP2C, but not the related factor TFAP2A, resulted in an abrogation of GPX1 expression. Selenium-dependent GPX activity correlated with endogenous GPX1 expression, and overexpression of exogenous GPX1 induced GPX activity and significantly increased resistance to tert-butyl hydroperoxide. Methylation of the CpG island encompassing the AP-2 regulatory region was identified in cell lines where TFAP2C failed to bind the GPX1 promoter and GPX1 expression was unresponsive to TFAP2C. Furthermore, in cell lines where GPX1 promoter methylation was associated with gene silencing, treatment with 5-aza-dC (an inhibitor of DNA methylation) resulted in activation of GPX1 RNA and protein expression. Methylation of the GPX1 promoter was identified in approximately 20% of primary breast cancers and a highly significant correlation between TFAP2C and GPX1 expression was confirmed when considering only those tumors with an unmethylated promoter, whereas the related factor, TFAP2A, failed to demonstrate a correlation. The results demonstrate that TFAP2C regulates the expression of GPX1, which influences the redox state and sensitivity to oxidative stress induced by peroxides. Given the established role of GPX1 in breast cancer, the results provide an important mechanism for TFAP2C to further influence oncogenesis and progression of breast carcinoma cells. 4 ChIP-Seq data for TFAP2C in human breast carcinoma cell lines MCF-7, BT-474, MDA-MB-453 and SKBR-3.

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Transcription profiling by array of human breast cancer cell line BT-474 with annexin A1 over-expression or silenced with siRNA to demonstrate design of multi-condition experiments

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