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. 2015 Dec;2:101182.
doi: 10.11131/2015/101182. Epub 2015 Dec 15.

Pan-cancer Analyses of the Nuclear Receptor Superfamily

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Free PMC article

Pan-cancer Analyses of the Nuclear Receptor Superfamily

Mark D Long et al. Nucl Receptor Res. .
Free PMC article

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.

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

Figures

Figure 1
Figure 1. Workflow diagram summarizing TCGA analyses
Data were downloaded directly from the UCSC Cancer Genomics Browser (https://genome-cancer.ucsc.edu/), filtered, and global transcriptomic and genomic alterations determined. Observed alterations of NRs and other TF families were directly compared to their genomic background equivalents using a bootstrapping approach.
Figure 2
Figure 2. Nuclear Receptors are downregulated in cancer
(A) Heatmap depicting the relative expression of all 42 NRs (rows) detectable in 1095 BRCA samples (columns) relative to the expression of NRs observed in a pool of 113 matched normal samples. Tumors with relative expression (Z-score) ≥ +/− 2 are considered significantly upregulated (red) or downregulated (green), respectively. (B) Bootstrapping results comparing the observed mean % of tumors with significantly disrupted expression for NRs relative to the background transcriptome in BRCA. Note that NRs are significantly upregulated less than is predicted by chance (p = 0.00065) and significantly downregulated more than is predicted by chance (p = 0.00179). (C) Pan-Cancer summary of NR expression patterns. Relative expression scores were determined by summing the Z-scores for a given gene in a given cancer and dividing by the square root of the number of tumors available for that tumor type. Shown are the 37 NRs detectable across all cancer types.
Figure 2
Figure 2. Nuclear Receptors are downregulated in cancer
(A) Heatmap depicting the relative expression of all 42 NRs (rows) detectable in 1095 BRCA samples (columns) relative to the expression of NRs observed in a pool of 113 matched normal samples. Tumors with relative expression (Z-score) ≥ +/− 2 are considered significantly upregulated (red) or downregulated (green), respectively. (B) Bootstrapping results comparing the observed mean % of tumors with significantly disrupted expression for NRs relative to the background transcriptome in BRCA. Note that NRs are significantly upregulated less than is predicted by chance (p = 0.00065) and significantly downregulated more than is predicted by chance (p = 0.00179). (C) Pan-Cancer summary of NR expression patterns. Relative expression scores were determined by summing the Z-scores for a given gene in a given cancer and dividing by the square root of the number of tumors available for that tumor type. Shown are the 37 NRs detectable across all cancer types.
Figure 3
Figure 3. Comparing Nuclear Receptor CNV alterations to expression changes in BRCA
Relative scores were determined for CNV alterations (Sum of GISTIC 2 threshold alteration values / square root(number of tumors)) and expression changes (Sum of Z-scores / square root(number of tumors)) for each member of the nuclear receptor superfamily. NRs which were not detectable in >80% of samples are considered not detectable (ND).
Figure 4
Figure 4. Nuclear Receptors are not common targets of somatic mutation in cancer
(A) Heatmap depicting non-synonymous mutations found in protein coding regions for all 48 NRs (rows) in 977 primary BRCA samples (columns). Observed mutations are depicted in blue. (B) Bootstrapping results comparing the observed mutation frequency (mutations / protein coding base pair) for NRs relative to the background protein coding genome in BRCA. Note that NRs are not significantly mutated more or less than is predicted by chance.

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