Emergence of antiestrogen-resistant cells in MCF-7 cells during suppression of estrogen signaling is a widely accepted model of acquired breast cancer resistance to endocrine therapy. To obtain insight into the genomic basis of endocrine therapy resistance, we characterized MCF-7 monoclonal sublines that survived 21-day exposure to tamoxifen (T-series sublines) or fulvestrant (F-series sublines) and sublines unselected by drugs (U-series). All T/Fsublines were resistant to the cytocidal effects of both tamoxifen and fulvestrant. However, their responses to the cytostatic effects of fulvestrant varied greatly, and their remarkably diversified morphology showed no correlation with drug resistance. mRNA expression profiles of the U-sublines differed significantly from those of the T/F-sublines, whose transcriptomal responsiveness to fulvestrant was largely lost. A set of genes strongly expressed in the U-sublines successfully predicted metastasis-free survival of breast cancer patients. Most T/F-sublines shared highly homogeneous genomic DNA aberration patterns that were distinct from those of the U-sublines. Genomic DNA of the U-sublines harbored many aberrations that were not found in the T/F-sublines. These results suggest that the T/F-sublines are derived from a common monoclonal progenitor that lost transcriptomal responsiveness to antiestrogens as a consequence of genetic abnormalities many population doublings ago, not from the antiestrogen-sensitive cells in the same culture during the exposure to antiestrogens. Thus, the apparent acquisition of antiestrogen resistance by MCF-7 cells reflects selection of preexisting drug-resistant subpopulations without involving changes in individual cells. Our results suggest the importance of clonal selection in endocrine therapy resistance of breast cancer. acquired resistance ͉ clonal selection ͉ DNA copy number ͉ fulvestrant ͉ tumor heterogeneity A pproximately 50% to 70% of breast cancers are estrogen receptor (ER␣) positive without amplification of the ERBB2/HER2 gene (1). Such ER ϩ /HER2Ϫ breast cancers typically respond well to endocrine therapy (ET), which suppresses estrogen signaling in cancer cells and halts their proliferation (cytostatic effect) and/or induces apoptosis (cytocidal effect). Although ET is proven effective, its clinical benefit is seriously limited by drug resistance. Approximately 50% of ER ϩ metastatic breast cancers do not respond to ET at all (de novo resistance); even when they initially respond to ET, most eventually become resistant during the course of therapy (acquired resistance). Nearly 40% of early-stage breast cancers treated with ET relapse with ET-resistant disease. Thus, ET resistance is an important clinical challenge in breast cancer treatment.The MCF-7 cell line is an extensively studied cell culture model of ER ϩ /HER2 Ϫ breast cancer (2). Because proliferation and survival of MCF-7 cells in culture or as xenograft are strictly dependent on estrogen (3-5), this cell line has been widely used to study mechanisms of ET resis...

Although biological effects of endocrine disrupting chemicals (EDCs) are often observed at unexpectedly low doses with occasional nonmonotonic dose-response characteristics, transcriptomewide 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 dosedependent 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 h 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 nonmonotonic responses.