title: 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 to in vitro and computational models (NRC in Toxicity testing in the 21st century: a vision and a strategy, The National Academies Press, Washington, DC, 2007). This transition requires mapping pathways of toxicity by understanding how in vitro systems respond to chemical perturbation. Uncovering transcription factors/signaling networks responsible for gene expression patterns is essential for defining pathways of toxicity, and ultimately, for determining the chemical modes of action through which a toxicant acts. Traditionally, transcription factor identification is achieved via chromatin immunoprecipitation studies and summarized by calculating which transcription factors are statistically associated with up- and downregulated genes. These lists are commonly determined via statistical or fold-change cutoffs, a procedure that is sensitive to statistical power and may not be as useful for determining transcription factor associations. To move away from an arbitrary statistical or fold-change-based cutoff, we developed, in the context of the Mapping the Human Toxome project, an enrichment paradigm called information-dependent enrichment analysis (IDEA) to guide identification of the transcription factor network. We used a test case of activation in MCF-7 cells by 17β estradiol (E2). Using this new approach, we established a time course for transcriptional and functional responses to E2. ERα and ERβ were associated with short-term transcriptional changes in response to E2. Sustained exposure led to recruitment of additional transcription factors and alteration of cell cycle machinery. TFAP2C and SOX2 were the transcription factors most highly correlated with dose. E2F7, E2F1, and Foxm1, which are involved in cell proliferation, were enriched only at 24 h. IDEA should be useful for identifying candidate pathways of toxicity. IDEA outperforms gene set enrichment analysis (GSEA) and provides similar results to weighted gene correlation network analysis, a platform that helps to identify genes not annotated to pathways.
authors: The Hamner Institutes for Health Sciences, Research Triangle Park, NC, USA.|ScitoVation, LLC, 6 Davis Drive, PO Box 110566, Research Triangle Park, NC, 27709, USA.
authors: Salil N
authors: SN
authors: Pendse
authors: Center for Alternatives to Animal Testing (CAAT), Department of Environmental Health Sciences, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA.
authors: Alexandra
authors: A
authors: Maertens
authors: Agilent Technologies, Inc., Santa Clara, CA, USA.
authors: Michael
authors: M
authors: Rosenberg
authors: Agilent Technologies, Inc., Santa Clara, CA, USA.
authors: Dipanwita
authors: D
authors: Roy
authors: Agilent Technologies, Inc., Santa Clara, CA, USA.
authors: Rick A
authors: RA
authors: Fasani
authors: Department of Pathology and Laboratory Medicine, Brown University, Providence, RI, USA.
authors: Marguerite M
authors: MM
authors: Vantangoli
authors: Department of Pathology and Laboratory Medicine, Brown University, Providence, RI, USA.
authors: Samantha J
authors: SJ
authors: Madnick
authors: Department of Pathology and Laboratory Medicine, Brown University, Providence, RI, USA.
authors: Kim
authors: K
authors: Boekelheide
authors: Department of Biochemistry and Molecular and Cellular Biology, and Lombardi Comprehensive Cancer Center, Georgetown University, Washington, DC, USA.
authors: Albert J
authors: AJ
authors: Fornace
authors: Department of Environmental Health Sciences, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA.
authors: Shelly-Ann
authors: SA
authors: Odwin
authors: Department of Environmental Health Sciences, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA.
authors: James D
authors: JD
authors: Yager
authors: Center for Alternatives to Animal Testing (CAAT), Department of Environmental Health Sciences, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA.|Center for Alternatives to Animal Testing-Europe, University of Konstanz, Constance, Germany.
authors: Thomas
authors: T
authors: Hartung
authors: The Hamner Institutes for Health Sciences, Research Triangle Park, NC, USA.|ScitoVation, LLC, 6 Davis Drive, PO Box 110566, Research Triangle Park, NC, 27709, USA.
authors: Melvin E
authors: ME
authors: Andersen
authors: The Hamner Institutes for Health Sciences, Research Triangle Park, NC, USA. pmcmullen@scitovation.com.|ScitoVation, LLC, 6 Davis Drive, PO Box 110566, Research Triangle Park, NC, 27709, USA. pmcmullen@scitovation.com.
authors: Patrick D
authors: PD
authors: McMullen
mesh_terms: D000818:Animals; D049109:Cell Proliferation / Q000187:drug effects; D004958:Estradiol / Q000008:administration & dosage / Q000633:toxicity*; D047628:Estrogen Receptor alpha / Q000187:drug effects* / Q000378:metabolism; D047629:Estrogen Receptor beta / Q000187:drug effects* / Q000378:metabolism; D005786:Gene Expression Regulation / Q000187:drug effects; D006801:Humans; D061986:MCF-7 Cells; D055748:SOXB1 Transcription Factors / Q000235:genetics; D015398:Signal Transduction / Q000187:drug effects; D013997:Time Factors; D018675:Toxicity Tests / Q000379:methods*; D050656:Transcription Factor AP-2 / Q000235:genetics; D014157:Transcription Factors / Q000235:genetics
chemical_list: C506487:ESR1 protein, human; D047628:Estrogen Receptor alpha; D047629:Estrogen Receptor beta; C527782:SOX2 protein, human; D055748:SOXB1 Transcription Factors; C493679:TFAP2C protein, human; D050656:Transcription Factor AP-2; D014157:Transcription Factors; D004958:Estradiol
keywords: Bioinformatics; Endocrine Disruption; Enrichment Analysis; Gene Expression; Pathways of Toxicity