Dataset Information

Xenoestrogen Dose-dependent Transcriptomal Changes in MCF-7 Human Breast Cancer Cells

ABSTRACT: Transcriptome analysis of MCF-7 cells exposed for 48 hours to various concentrations of xenoestrogen chemicals. Although biological effects of endocrine disrupting chemicals (EDCs) are often observed at unexpectedly low doses with occasional non-monotonic dose-response characteristics, transcriptome-wide profiles of sensitivities or dose-dependent behaviors of the EDC responsive genes have remained unexplored. Here, we describe expressome analysis for the comprehensive examination of dose-dependent gene responses and its applications to characterize estrogen responsive genes in MCF-7 cells. Transcriptomes of MCF-7 cells exposed to varying concentrations of representative natural and xenobiotic estrogens for 48 hours were determined by microarray and used for computational calculation of interpolated approximations of estimated transcriptomes for 300 doses uniformly distributed in log space for each chemical. The entire collection of these estimated transcriptomes, designated as the expressome, has provided unique opportunities to profile chemical-specific distributions of ligand sensitivities for large numbers of estrogen responsive genes, revealing that at low concentrations estrogens generally tended to suppress rather than to activate transcription. Gene ontology analysis demonstrated distinct functional enrichment between high- and low-sensitivity estrogen responsive genes, supporting the notion that a single EDC chemical can cause qualitatively distinct biological responses at different doses. Expressomal heatmap visualization of dose-dependent induction of Bisphenol A-inducible genes showed a weak gene activation peak at a very low concentration range (ca. 0.1 nM) in addition to the main, strong gene activation peak at and above 100 nM. Thus, expressome analysis is a powerful approach to understanding the EDC dose-dependent dynamic changes in gene expression at the transcriptomal level, providing important information on the overall profiles of ligand sensitivities and non-monotonic responses.

ORGANISM(S): Homo sapiens

PROVIDER: GSE50705 | GEO | 2013/09/10

SECONDARY ACCESSION(S): PRJNA218527

REPOSITORIES: GEO

ACCESS DATA

Similar Datasets

Project description:Transcriptome analysis of MCF-7 cells exposed for 48 hours to various concentrations of xenoestrogen chemicals. Although biological effects of endocrine disrupting chemicals (EDCs) are often observed at unexpectedly low doses with occasional non-monotonic dose-response characteristics, transcriptome-wide profiles of sensitivities or dose-dependent behaviors of the EDC responsive genes have remained unexplored. Here, we describe expressome analysis for the comprehensive examination of dose-dependent gene responses and its applications to characterize estrogen responsive genes in MCF-7 cells. Transcriptomes of MCF-7 cells exposed to varying concentrations of representative natural and xenobiotic estrogens for 48 hours were determined by microarray and used for computational calculation of interpolated approximations of estimated transcriptomes for 300 doses uniformly distributed in log space for each chemical. The entire collection of these estimated transcriptomes, designated as the expressome, has provided unique opportunities to profile chemical-specific distributions of ligand sensitivities for large numbers of estrogen responsive genes, revealing that at low concentrations estrogens generally tended to suppress rather than to activate transcription. Gene ontology analysis demonstrated distinct functional enrichment between high- and low-sensitivity estrogen responsive genes, supporting the notion that a single EDC chemical can cause qualitatively distinct biological responses at different doses. Expressomal heatmap visualization of dose-dependent induction of Bisphenol A-inducible genes showed a weak gene activation peak at a very low concentration range (ca. 0.1 nM) in addition to the main, strong gene activation peak at and above 100 nM. Thus, expressome analysis is a powerful approach to understanding the EDC dose-dependent dynamic changes in gene expression at the transcriptomal level, providing important information on the overall profiles of ligand sensitivities and non-monotonic responses. Subconfluent density of MCF-7 cells were exposed to various concentrations of xenoestrogen chemicals for 48 hours and then subjected to transcriptomal analysis using Affymetrix U133 version 2 plus microarray.

Project description:Despite the success of the aromatase inhibitors (AIs) in treating estrogen receptor positive breast cancer, 15-20% of patients receiving adjuvant AIs will relapse within 5-10 years of treatment initiation. Long term estrogen deprivation (LTED) of breast cancer cells in culture has been successfully used to mimic AI-induced estrogen depletion to dissect mechanisms of AI resistance. However, we hypothesized that a subset of patients receiving AI therapy may maintain low circulating concentrations of estrogens that influence the development of endocrine resistance. We sought to expand established LTED models to account for these observations. MCF-7 cells were grown in medium with charcoal stripped serum supplemented with defined concentrations of E2 or the estrogenic androgen metabolite 3βAdiol. Cells were selected in the EC10 and EC90 of E2 or 3βAdiol, or estrogen deprived. Estrogen-independence was evaluated during selection by assessing cell growth in the absence or presence of E2 or 3βAdiol. Following >7 months of selection, estrogen-independence developed in estrogen-deprived cells and cells maintained in low concentrations of steroid hormone. Functional analyses demonstrated that estrogen-deprived and low-steroid selected cells developed estrogen-independence via unique mechanisms, independent and dependent of ERα, respectively. Estrogen-independent growth in low-steroid selected cells could be blocked by kinase inhibitors. However, these cells were completely resistant to kinase inhibition in the presence of low steroid hormone concentrations. These data offer a novel perspective on the development of resistance to AI therapy, and may yield novel approaches to treat AI-resistant tumors. MCF-7 cells were selected for >7months in IMEM+10% Charcoal Stripped FBS, supplmented with defined steroid hormone conditions. Following outgrowth of estrogen-independent cells, cell lines were grown in estrogen-free conditions and gene expression analysis was performed to identify drivers of estrogen-independent growth. Cells were assessed in biological triplicates.

Dataset Information

Xenoestrogen Dose-dependent Transcriptomal Changes in MCF-7 Human Breast Cancer Cells

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure