A Rapid, Extensive, and Transient Transcriptional Response to Estrogen Signaling in Breast Cancer Cells

Abstract

Summary We report the immediate effects of estrogen signaling on the transcriptome of breast cancer cells using Global Run-On and sequencing (GRO-seq). The data were analyzed using a new bioinformatic approach that allowed us to identify transcripts directly from the GRO-seq data. We found that estrogen signaling directly regulates a strikingly large fraction of the transcriptome in a rapid, robust, and unexpectedly transient manner. In addition to protein coding genes, estrogen regulates the distribution and activity of all three RNA polymerases, and virtually every class of non-coding RNA that has been described to date. We also identified a large number of previously undetected estrogen-regulated intergenic transcripts, many of which are found proximal to estrogen receptor binding sites. Collectively, our results provide the most comprehensive measurement of the primary and immediate estrogen effects to date and a resource for understanding rapid signal-dependent transcription in other systems.

Oncogenic Pathway Signatures and Survival Outcome

“…Other immunohistochemical studies have shown that the PR protein expression has predictive of prognostic value, more than the expression of ER. (Hah et al, 2011;Høgdall et al, 2007;Tangjitgamol, Manusirivithaya, Khunnarong, Jesadapatarakul, & Tanwanich, 2009;X.-Y. Yang, Xi, K.-X.…”

Interplay between steroid signalling and microRNAs: implications for hormone-dependent cancers

“…119 miR-containing transcripts that were regulated by E 2 at one or more time points were identified. Interestingly, MCF7 cells were enriched for 2700 predicted targets of these E 2 -regulated miRs compared with other cells, indicating the presence of a complex regulatory network of miRs and their mRNA targets (Hah et al 2011). Other studies have combined microarray expression profiling of miRs with global ERa-binding site mapping through ChIP-seq to provide mechanistic insights: Bhat-Nakshatri et al examined functional ERa-binding sites within 20 kb regions 5 0 of miR genes following estrogen stimulation that resulted in increased pri-miR transcription.…”

“…miRNAome-wide profiling arrays, such as microarrays and qPCR arrays, have helped to define a signature of estrogen-regulated miRs. The first examples of such arrays are limited in their applicability to ERa signalling in humans, being performed in zebrafish, rat breast tissue and mouse spleen (Kovalchuk et al 2007, Dai et al 2008, and to date only around 15 studies have examined estrogen regulation of miRs in human cells (Iorio et al 2005, Bhat-Nakshatri et al 2009, Castellano et al 2009, Klinge 2009, Maillot et al 2009, Wickramasinghe et al 2009, Cicatiello et al 2010, Cochrane et al 2010, Di Leva et al 2010, Hah et al 2011, Ferraro et al 2012, Masuda et al 2012, Zhao et al 2013. Despite the majority of these being performed in MCF7 breast cancer cells, inconsistencies are evident, presumably attributable to differences in ligand, treatment duration, array platform, statistical processing and threshold setting as well as lab-specific cell line differences.…”

“…As a more direct, and arguably more physiologically relevant method for identification of transcriptionally estrogen-regulated miRs, Hah et al (2011) used global nuclear run-on and sequencing (GRO-seq) to map the position and orientation of all RNA polymerases across the MCF7 genome following treatment with 100 nM E 2 for 10, 60 or 160 min. 119 miR-containing transcripts that were regulated by E 2 at one or more time points were identified.…”

Noncoding RNAs and the control of hormonal signaling via nuclear receptor regulation

“…Upon ligand binding, these receptors interact with specific DNA sequences in the promoter and enhancer regions of their target genes. The transcription of regulated genes is modulated by co-binding of an array of co-factors as well as RNA polymerases and several components of the transcription initiation machinery (Acevedo & Kraus 2004, Cheung & Kraus 2010, Hah et al 2011. Based on ligand properties, the NR superfamily can be broadly divided into three classes: hormone, metabolic, and orphan NRs (Gadaleta & Magnani 2014).…”