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Cancer Res. 2011 Nov 15;71(22):6940-7. doi: 10.1158/0008-5472.CAN-11-2091. Epub 2011 Sep 22.

A comprehensive view of nuclear receptor cancer cistromes.

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Department of Bioinformatics, School of Life Science and Technology, Tongji University, Shanghai, China.


Nuclear receptors comprise a superfamily of ligand-activated transcription factors that play important roles in both physiology and diseases including cancer. The technologies of chromatin immunoprecipitation followed by array hybridization (ChIP-chip) or massively parallel sequencing (ChIP-seq) has been used to map, at an unprecedented rate, the in vivo genome-wide binding (cistrome) of nuclear receptors in both normal and cancer cells. We developed a curated database of 88 nuclear receptor cistrome data sets and other associated high-throughput data sets including 121 collaborating factor cistromes, 94 epigenomes, and 319 transcriptomes. Through integrative analysis of the curated nuclear receptor ChIP-chip/seq data sets, we discovered novel factor-specific noncanonical motifs that may have important regulatory roles. We also revealed a common feature of nuclear receptor pioneering factors to recognize relatively short and AT-rich motifs. Most nuclear receptors bind predominantly to introns and distal intergenetic regions, and binding sites closer to transcription start sites were found to be neither stronger nor more evolutionarily conserved. Interestingly, while most nuclear receptors appear to be predominantly transcriptional activators, our analysis suggests that the binding of ESR1, RARA, and RARG has both activating and repressive effects. Through meta-analysis of different omic data of the same cancer cell line model from multiple studies, we generated consensus cistrome and expression profiles. We further made probabilistic predictions of the nuclear receptor target genes by integrating cistrome and transcriptome data and validated the predictions using expression data from tumor samples. The final database, with comprehensive cistrome, epigenome, and transcriptome data sets and downstream analysis results, constitutes a valuable resource for the nuclear receptor and cancer community.

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