E-GEOD-2225
Ontology highlight
ABSTRACT:
OTHER RELATED OMICS DATASETS IN: PRJNA91481
PROVIDER: E-GEOD-2225 | ExpressionAtlas | 2014-07-03
REPOSITORIES: ExpressionAtlas
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| E-GEOD-2225-analysis-methods.tsv | Tabular | |||
| E-GEOD-2225-atlasExperimentSummary.Rdata | Rdata | |||
| E-GEOD-2225-configuration.xml | Xml | |||
| E-GEOD-2225-percentile-ranks.tsv | Tabular | |||
| E-GEOD-2225.condensed-sdrf.tsv | Tabular |
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2011-02-18 | E-GEOD-27375 | biostudies-arrayexpress
Project description:We have previously demonstrated that endoxifen is the most important tamoxifen metabolite responsible for eliciting the anti-estrogenic effects of this drug in breast cancer cells expressing estrogen receptor-alpha. However, the relevance of estrogen receptor-beta in mediating endoxifen action has yet to be explored. Therefore, the goals of this study were to determine the differences in the global gene expression profiles elicited by estradiol treatment and endoxifen between parental MCF7 breast cancer cells (expressing estrogen receptor alpha only) and MCF7 cells stably expressing estrogen receptor beta.
2011-02-18 | GSE27375 | GEO
Project description:Anti-estrogens and aromatase inhibitors are important drugs in the treatment of estrogen-dependent breast cancer. In order to investigate the effects of these drugs on gene expression in breast cancer cells, we treated estrogen receptor-positive MCF-7 cells, stably transfected with the aromatase gene (known as MCF-7aro cells), with testosterone, 17β-estradiol, two aromatase inhibitors (letrozole and anastrozole), and an anti-estrogen (tamoxifen). Microarray analyses using Affymetrix Human Genome U133A GeneChips were carried out using total RNA isolated from the control and treated cells. When comparing the effect of each inhibitor on gene expression we observe that letrozole and anastrozole are more similar in terms of the genes they affect, compared to treatment with tamoxifen. The results of this study provide us with a better understanding of the actions of both aromatase inhibitors and anti-estrogens at the molecular level. We believe that the results of this study serve as the first step in identifying unique expression patterns following drug treatment, and that this will ultimately be useful in customizing patient treatment strategies for estrogen-dependent breast cancer. The data presented here have been processed using the R-Project Bioconductor statistical tools package using the affy library. The following were applied: RMA background correction, pmonly probe-level correction, quantile normalization, avgdiff summary method. Raw data is provided in the form of .CEL files.
2007-10-27 | E-GEOD-2225 | biostudies-arrayexpress
Project description:Anti-estrogens and aromatase inhibitors are important drugs in the treatment of estrogen-dependent breast cancer. In order to investigate the effects of these drugs on gene expression in breast cancer cells, we treated estrogen receptor-positive MCF-7 cells, stably transfected with the aromatase gene (known as MCF-7aro cells), with testosterone, 17β-estradiol, two aromatase inhibitors (letrozole and anastrozole), and an anti-estrogen (tamoxifen). Microarray analyses using Affymetrix Human Genome U133A GeneChips were carried out using total RNA isolated from the control and treated cells. When comparing the effect of each inhibitor on gene expression we observe that letrozole and anastrozole are more similar in terms of the genes they affect, compared to treatment with tamoxifen. The results of this study provide us with a better understanding of the actions of both aromatase inhibitors and anti-estrogens at the molecular level. We believe that the results of this study serve as the first step in identifying unique expression patterns following drug treatment, and that this will ultimately be useful in customizing patient treatment strategies for estrogen-dependent breast cancer. The data presented here have been processed using the R-Project Bioconductor statistical tools package using the affy library. The following were applied: RMA background correction, pmonly probe-level correction, quantile normalization, avgdiff summary method. Raw data is provided in the form of .CEL files. Keywords = estrogen-dependent breast cancer Keywords = aromatase Keywords: other
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