Estrogen receptor alpha positive breast tumors and breast cancer cell lines share similarities in their transcriptome data structures

Abstract

Abstract.Established human breast cancer cell lines are widely used as experimental models in breast cancer research. While these cell lines and their variants share many phenotypic characteristics with human breast tumors, the extent to which they reflect the underlying molecular biology of breast cancer remains controversial. We explored this issue using a probabilistic rather than heuristic approach. Data from gene expression microarrays were used to compare the global structures of the transcriptomes of three estrogen receptor alpha positive (ER + ) human breast cancer cell lines (MCF-7, T47D, ZR-75-1) and 13 human breast tumors (11 ER + ; 2 ER -). Linear representations of the respective data structures were obtained by deriving those top principal components (PCs) required to capture ≥80% of the cumulative variance for each data set (M PCs). We then identified those genes most highly correlated with the M PCs (Pearson's correlation coefficient r≥0.800) and identified a group of 36 genes commonly correlated with both the cell line (M = 5 PCs) and tumor (M = 6 PCs) data structures. All 36 common genes were correlated with PC1 from the breast tumor data: 21/36 genes were correlated with PC1, 14/36 genes correlated with PC2, and 1/36 genes correlated with PC3 from the cell line data. Genes important in defining the data structures include NFκB p65, IGFBP-6, ornithine decarboxylase-1, and paxillin. When data from MDA-MB-435 xenografts (ER -) were included in the analysis, we were unable to find any common genes between these xenografts and the breast tumors. These data clearly imply that MCF-7, T47D, and ZR-75-1 cells and ER + breast tumors share substantial global similarities in the structures of their respective transcriptomes, and that these cell lines are good models in which to identify molecular events that are likely to be important in some ER + human breast cancers.

Estrogen Receptor α Controls a Gene Network in Luminal-Like Breast Cancer Cells Comprising Multiple Transcription Factors and MicroRNAs

“…This is an important asset in clinical oncology because effective endocrine treatments of BC with ER␣ antagonists or aromatase inhibitors would be greatly improved by reliable predictors of tumor sensitivity to these drugs in the adjuvant or metastatic settings, as well as by the availability of markers of pharmacological resistance and new therapeutic targets to overcome it. 7 Estrogen responsive BC cell models have proven to be very useful in this case because ER␣-expressing breast tumors and cell lines share significant similarities in their transcriptomes 8 and the expression profiles of estrogen-responsive gene sets identified in vitro in luminal-like BC cell models have been found to be an intrinsic genetic signature of ER␣-expressing breast tumors. 9 These gene signatures have been useful to define BC prognosis and response to endocrine therapy.…”

“…11 A detailed definition of the estrogen-responsive gene network in BC cell models is thus a prerequisite not only to be able to identify defined breast tumor subtypes according to their estrogen-dependent intrinsic molecular signatures, but also to understand ER␣ contribution to the establishment and maintenance of specific BC clinical phenotypes, characterized by diverse disease prognosis and responsiveness to therapy. 12 For these reasons, a number of studies have focused on identification of gene sets regulated by estrogen in ER␣-expressing luminal-like BC cell models, including MCF-7, [13][14][15] T47D, 8 and ZR-75.1 16 -18 cells. Although these studies led to the identification of a significant number of hormone-regulated genes, an integrated view of the estrogen-responsive genetic pathway of luminallike BC cells is still missing, due in part to biological and technical variables among experiments.…”

“…8,50 We performed a high resolution time-course analysis of the estrogen-regulated transcriptome in both of these cell lines with a whole-genome microarray platform with the aim of identifying all known genes showing identical kinetics and type of response to the hormone in this luminal-like BC cell models. For this, total RNA was extracted from hormone-starved, growth-arrested cells at time t ϭ 0 and at 11 time-points, for up to 32 hours, into stimulation with 10 Ϫ8 M E2, a timing that corresponds to completion of a cell cycle under these conditions.…”

“…17,28 For mRNA expression profiling, RNA was extracted from MCF-7 and ZR-75.1 cells before (0) or after 1, 2, 4,6,8,12,16,20,24,28, and 32 hours of stimulation with 17␤-estradiol 10 Ϫ8 M (ϩE2) or ethanol vehicle. For miRNAs expression profiling, RNA was extracted from MCF-7 cells before (0) or after 2, 12, 24, and 72 hours of stimulation with 17␤-estradiol 10 Ϫ8 M (ϩE2) or ethanol vehicle.…”

Protein Tyrosine Phosphatase 4A2 Expression Predicts Overall and Disease-Free Survival of Human Breast Cancer and Is Associated with Estrogen and Progestin Receptor Status

“…However, these studies did not investigate the relationship of PTP4A2 gene expression and the levels of breast cancer biomarkers ER and PR nor the association of the enzyme and biomarkers with breast cancer behavior. Several studies in breast cancer cell lines described genes associated with either ER or PR [58][59][60][61][62][63][64], but none of these studies reported results suggesting that PTP4A2 was an ERor PR-regulated gene.…”