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Series GSE84981 Query DataSets for GSE84981
Status Public on Jun 05, 2017
Title Information-dependent Enrichment Analysis Reveals Time-dependent Transcriptional Regulation of the Estrogen Pathway of Toxicity
Organism Homo sapiens
Experiment type Expression profiling by array
Summary The twenty-first century vision for toxicology involves a transition away from high-dose animal studies to in vitro and computational models (NRC 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 are 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 cutoffs 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 24h. 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.
Overall design Gene Expression in MCF7 Cells treated with 0.01nM,0.1nM,1nM E2 for 2h,4h,8h,24h measured against time-matched controls
Contributor(s) Pendse SN
Citation(s) 27592001
Submission date Jul 29, 2016
Last update date Nov 27, 2018
Contact name Salil N Pendse
Organization name Scitovation
Street address 6 Davis Drive
City RTP
State/province NC
ZIP/Postal code 27709
Country USA
Platforms (1)
GPL13607 Agilent-028004 SurePrint G3 Human GE 8x60K Microarray (Feature Number version)
Samples (60)
GSM2255300 0nM_E2_24h_Rep1 [US12302349_252800421118_S02_GE1_1105_Oct12_2_1]
GSM2255301 0nM_E2_24h_Rep2 [US12302349_252800421118_S02_GE1_1105_Oct12_2_2]
GSM2255302 0nM_E2_24h_Rep3 [US12302349_252800421118_S02_GE1_1105_Oct12_2_3]
BioProject PRJNA335817

Download family Format
SOFT formatted family file(s) SOFTHelp
MINiML formatted family file(s) MINiMLHelp
Series Matrix File(s) TXTHelp

Supplementary file Size Download File type/resource
GSE84981_RAW.tar 187.9 Mb (http)(custom) TAR (of TXT)
Processed data included within Sample table

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