Literature DB >> 27200367

Pan-cancer analyses of the nuclear receptor superfamily.

Mark D Long1, Moray J Campbell1.   

Abstract

Nuclear receptors (NR) act as an integrated conduit for environmental and hormonal signals to govern genomic responses, which relate to cell fate decisions. We review how their integrated actions with each other, shared co-factors and other transcription factors are disrupted in cancer. Steroid hormone nuclear receptors are oncogenic drivers in breast and prostate cancer and blockade of signaling is a major therapeutic goal. By contrast to blockade of receptors, in other cancers enhanced receptor function is attractive, as illustrated initially with targeting of retinoic acid receptors in leukemia. In the post-genomic era large consortia, such as The Cancer Genome Atlas, have developed a remarkable volume of genomic data with which to examine multiple aspects of nuclear receptor status in a pan-cancer manner. Therefore to extend the review of NR function we have also undertaken bioinformatics analyses of NR expression in over 3000 tumors, spread across six different tumor types (bladder, breast, colon, head and neck, liver and prostate). Specifically, to ask how the NR expression was distorted (altered expression, mutation and CNV) we have applied bootstrapping approaches to simulate data for comparison, and also compared these NR findings to 12 other transcription factor families. Nuclear receptors were uniquely and uniformly downregulated across all six tumor types, more than predicted by chance. These approaches also revealed that each tumor type had a specific NR expression profile but these were most similar between breast and prostate cancer. Some NRs were down-regulated in at least five tumor types (e.g. NR3C2/MR and NR5A2/LRH-1)) whereas others were uniquely down-regulated in one tumor (e.g. NR1B3/RARG). The downregulation was not driven by copy number variation or mutation and epigenetic mechanisms maybe responsible for the altered nuclear receptor expression.

Entities:  

Keywords:  Bootstrap analyses; TCGA; cancer NR3C1/GR NR5A2/LRH-1 NR1B3/RARG; copy number variation; gene expression; mutation

Year:  2015        PMID: 27200367      PMCID: PMC4869537          DOI: 10.11131/2015/101182

Source DB:  PubMed          Journal:  Nucl Receptor Res        ISSN: 2314-5706


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