Paper Chase is a research database designed to offer abstracts of research articles published in journals that have a highly rated impact factor as determined by ISI Impact Factor and PageRank. Abstracts are organized by date, with the most recently published papers listed first. 

Paper Chase

Expressomal approach for comprehensive analysis and visualization of ligand sensitivities of xenoestrogen responsive genes.

Proc. Natl. Acad. Sci. U.S.A.. Oct 8, 2013;110(41):16508-13.
Shioda T, Rosenthal NF, Coser KR, Suto M, Phatak M, Medvedovic M, Carey VJ, Isselbacher KJ.

Molecular Profiling Laboratory, Massachusetts General Hospital Center for Cancer Research, Charlestown, MA 02129.

Abstract:

Although biological effects of endocrine disrupting chemicals (EDCs) are often observed at unexpectedly low doses with occasional nonmonotonic dose-response characteristics, transcriptome-wide profiles of sensitivities or dose-dependent behaviors of the EDC responsive genes have remained unexplored. Here, we describe expressome analysis for the comprehensive examination of dose-dependent gene responses and its applications to characterize estrogen responsive genes in MCF-7 cells. Transcriptomes of MCF-7 cells exposed to varying concentrations of representative natural and xenobiotic estrogens for 48 h were determined by microarray and used for computational calculation of interpolated approximations of estimated transcriptomes for 300 doses uniformly distributed in log space for each chemical. The entire collection of these estimated transcriptomes, designated as the expressome, has provided unique opportunities to profile chemical-specific distributions of ligand sensitivities for large numbers of estrogen responsive genes, revealing that at low concentrations estrogens generally tended to suppress rather than to activate transcription. Gene ontology analysis demonstrated distinct functional enrichment between high- and low-sensitivity estrogen responsive genes, supporting the notion that a single EDC chemical can cause qualitatively distinct biological responses at different doses. Expressomal heatmap visualization of dose-dependent induction of Bisphenol A inducible genes showed a weak gene activation peak at a very low concentration range (ca. 0.1 nM) in addition to the main, strong gene activation peak at and above 100 nM. Thus, expressome analysis is a powerful approach to understanding the EDC dose-dependent dynamic changes in gene expression at the transcriptomal level, providing important information on the overall profiles of ligand sensitivities and nonmonotonic responses.