Information-dependent Enrichment Analysis Reveals Time-dependent Transcriptional Regulation of the Estrogen Pathway of Toxicity

Abstract

The twenty-first century vision for toxicology involves a transition away from high-dose animal studies and into in vitro and computational models. This movement requires mapping pathways of toxicity through an understanding of how in vitro systems respond to chemical perturbation. Uncovering transcription factors responsible for gene expression patterns is essential for defining pathways of toxicity, and ultimately, for determining chemical mode of action, through which a toxicant acts. Traditionally this is achieved via chromatin immunoprecipitation studies and summarized by calculating, which transcription factors are statistically associated with the upand down-regulated genes. These lists are commonly determined via statistical or fold-change cutoffs, a procedure that is sensitive to statistical power and may not be relevant to determining transcription factor associations. To move away from an arbitrary statistical or fold-change based cutoffs, we have developed in the context of the Mapping the Human Toxome project, a novel enrichment paradigm called Information Dependent Enrichment Analysis (IDEA) to guide identification of the transcription factor network. We used the test case of endocrine disruption of MCF-7 cells activated by 17β estradiol (E2). Using this new approach, we were able to establish a time course for transcriptional and functional responses to E2. ERα and ERβ are associated with short-term transcriptional changes in response to E2. Sustained exposure leads to the recruitment of an additional ensemble of transcription factors and alteration of cell-cycle machinery. TFAP2C and SOX2 were the transcription factors most highly correlated with dose.

Gene Coregulation and Coexpression in the Aryl Hydrocarbon Receptor-mediated Transcriptional Regulatory Network in the Mouse Liver

“…Finally, we found that co-regulated gene clusters activated distinct groups of downstream biological processes, with the AHR-bound genomic cluster enriched for metabolic processes and the AHR-unbound non-genomic cluster primarily activating immune processes. This work, together with other recent studies of the PPARα and estrogen receptor pathways (McMullen et al 2014;Pendse et al 2016), illustrates the application of bioinformatic and statistical tools for reconstruction and analysis of the transcriptional regulatory cascades underlying cellular stress response.…”

Multiple receptors shape the estrogen response pathway and are critical considerations for the future of in vitro-based risk assessment efforts

“…ERa interacts with coactivators such as AP1 (cFos/ cJun), Sp1, and SNCG or, conversely, with co-repressors such as Sin3A to modify transcriptional responses to estrogen (Kushner et al 2000;Jiang et al 2003;Schultz et al 2003;Ellison-Zelski et al 2009;. Global gene expression profiling of breast tumor cell lines following E2 stimulation has identified as many as 1500 genes that are differentially regulated in response to estrogen (Katzenellenbogen et al 2000;Klinge 2000;Harrington et al 2003;Kininis & Kraus 2008;Pendse et al 2017). Only a small fraction of the differentially expressed genes are directly modulated by the ERa and ERb transcription factors (Madak-Erdogan et al 2008).…”

“…Only a small fraction of the differentially expressed genes are directly modulated by the ERa and ERb transcription factors (Madak-Erdogan et al 2008). In addition to the ERs, other transcription factors including Foxm1, E2F1, E2F7, and ZNF217 are responsible for initiating expression of genes associated with cell cycle, cell growth, and differentiation (Shen et al 2011;Pendse et al 2017). This low degree of overlap between estrogen receptor binding and gene expression regulation is in sharp contrast to other nuclear receptors that have been shown to account for approximately half of the affected genes' expression (van der Meer et al 2010;McMullen et al 2014) and highlights the contribution of the so-called "nongenomic" signaling (i.e.…”

The need for strategic development of safety sciences

“…CAAT, with one of the authors (TH) as principal investigator, promotes the use of advanced-omics and high-throughput technologies and supports the implementation of knowledge-based frameworks such as Pathways of Toxicity and Adverse Outcome Pathways (Hartung and McBride, 2011) and thus plays a key role in implementing the NAS Tox21 vision. A key goal of the Human Toxome Project is the development of tools for identification of pathways of toxicity (Kleensang et al, 2014) from multi-omics technologies (Maertens et al 2015Pendse et al, 2016) to feed into a systems toxicology approach (Hartung et al, 2012). The combination of orthogonal omics technologies has the advantage that the tremendous signal/noise problem of any omics technology is overcome.…”