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. 2011 Feb 1;108(5):2076-81.
doi: 10.1073/pnas.1011936108. Epub 2011 Jan 18.

Differential regulation of the p73 cistrome by mammalian target of rapamycin reveals transcriptional programs of mesenchymal differentiation and tumorigenesis

Jennifer M Rosenbluth  1 , Deborah J Mays, Aixiang Jiang, Yu Shyr, Jennifer A Pietenpol
Affiliations

Differential regulation of the p73 cistrome by mammalian target of rapamycin reveals transcriptional programs of mesenchymal differentiation and tumorigenesis

V体育官网入口 - Jennifer M Rosenbluth et al. Proc Natl Acad Sci U S A. .

VSports - Abstract

The transcription factor p73 plays critical roles during development and tumorigenesis. It exhibits sequence identity and structural homology with p53, and can engage p53-like tumor-suppressive programs VSports手机版. However, different pathways regulate p53 and p73, and p73 is not mutated in human tumors. Therefore, p73 represents a therapeutic target, and there is a critical need to understand genes and noncoding RNAs regulated by p73 and how they change during treatment regimens. Here, we define the p73 genomic binding profile and demonstrate its modulation by rapamycin, an inhibitor of mammalian target of rapamycin (mTOR) and inducer of p73. Rapamycin selectively increased p73 occupancy at a subset of its binding sites. In addition, multiple determinants of p73 binding, activity, and function were evident, and were modulated by mTOR. We generated an mTOR-p73 signature that is enriched for p73 target genes and miRNAs that are involved in mesenchymal differentiation and tumorigenesis, can classify rhabdomyosarcomas by clinical subtype, and can predict patient outcome. .

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Fig. 1.
Fig. 1.
Rapamycin increases p73 binding to specific regions of the genome. (A) Protein levels of p73 increase in Rh30 cells treated with 40 nM rapamycin for 24 h, as analyzed by Western blot. “C” is vehicle control; pS6 is a marker of mTOR activity. (B) ChIP-qPCR was performed to assess p73 occupancy at MDM2 and RPS27L promoters using two antibodies that preferentially recognize either p73α or p73β. Error bars indicate SD from triplicate analyses. (C) Histogram analysis was performed to assess the distribution of p73 binding sites relative to transcriptional start sites. The control sample (Left) and rapamycin-treated sample (Right) were compared using the two-sample Kolmogorov-Smirnov test. The P value was 0.6, indicating no significant difference. (D) Histogram analysis was performed to assess the impact of rapamycin on overall p73 binding level. The ratio of binding levels in rapamycin-treated vs. control samples was calculated and log-transformed. A skew to the right is evident in this plot, indicating higher binding in rapamycin-treated samples. The degree of skew is 0.34, with P < 0.0001. (E) Binding levels of p73 were plotted for 18 loci that exhibited the greatest increase in binding after rapamycin treatment. Chromosomal locations within 10 kb of known genes are indicated by an asterisk. From left to right, these genes are: FLJ32810, ARHGEF12, ETV6, RAPGEF3/FLJ20489, RBMS3, C3orf16, SCHIP1, HNRPDL/ENOPH1, and FBXO32.
Fig. 2.
Fig. 2.
Tissue-specific factors associate with p73-bound loci. (A) DNA-binding factors with motifs overrepresented in the p73 cistrome are organized by tissue-specific function (binomial test, P < 0.0001). Marked factors have ≥ 20% increased enrichment in rapamycin-treated or control samples. (B) Small interfering RNA-mediated depletion of c-Jun does not alter p73 protein levels in Rh30 cells, as assessed by Western blot. (C) ChIP-qPCR is shown assessing p73 binding to select genomic loci (indicated by interval number or by nearest target gene, where possible) in Rh30 cells treated with siRNA targeting c-Jun or control siRNA. Error bars indicate SD from triplicate analyses. (D) ChIP of c-Jun binding to sites within 500 bp of p73 binding sites is shown. Primers flank c-Jun motifs as assessed by sequence analysis for the same genomic loci as in C. PCR product was resolved by acrylamide gel electrophoresis for reactions using the following DNA samples: genomic input (“I”), DNA purified after ChIP with a c-Jun-specific antibody (“J”), and DNA purified after ChIP with a control, nonspecific, isotype-matched antibody (“C”). ADCY8 in C and D is a negative control locus that does not have a c-Jun consensus binding site within 500 bp of the p73 interval.
Fig. 3.
Fig. 3.
Genes and miRNAs regulated by mTOR and p73 display distinct patterns of regulation. (A) Microarray analysis was performed in duplicate using Rh30 cells transduced with shRNA targeting p73 (KD) or GFP (C) for 3 d, cells were treated with vehicle (con) or 40 nM rapamycin (rap) for 24 h. Depicted by heat map are genes that changed >50% with rapamycin treatment or p73 depletion. Hierarchical clustering (average linkage) reveals distinct groups of transcripts: A, increased by p73; B, increased by p73 in an mTOR-dependent manner; C, decreased by p73 in an mTOR-dependent manner; D, decreased by p73; E, regulated by mTOR alone. Major gene ontologies (hypergeometric test, P < 0.05), total transcript numbers, and the percentage of genes present in the ChIP-on-Chip dataset are indicated for each cluster. (B) Hierarchical clustering was used to segregate 142 miRNAs whose expression levels were regulated by mTOR or p73 into discrete groups. Rh30 cells were treated with p73 RNAi (shp73) or 40 nM rapamycin (rapa), and the ΔΔCT method was used to calculate expression relative to control samples. (C) A total of 14 miRNAs whose expression levels increase after rapamycin treatment in a p73-dependent manner are shown. Those miRNAs that are located within 10 kb of a p73 binding site are highlighted in orange text.
Fig. 4.
Fig. 4.
The p73-regulated genes are differentially expressed in rhabdomyosarcoma subtypes. The mTOR-p73 gene signature was assessed using a publicly available dataset in which 29 rhabdomyosarcoma tumors were profiled by microarray (14). (A) All genes that changed >20% with rapamycin or p73 RNAi were included in this initial analysis to increase overlap across microarray platforms. Hierarchical clustering demonstrates that the mTOR-p73 gene signature segregates tumors to two classes, corresponding to the clinical alveolar and embryonal subtypes. (B) Genes regulated > 50% by p73 were analyzed in ARMS and ERMS. Box plots demonstrate opposing gene expression trends in these two tumor subtypes. (C) The expression levels of 17 direct p73 target genes were used to segregate an independent cohort of 64 ARMS patients to two groups, using Cox proportional hazards modeling and Kaplan-Meier analysis. This 17-gene p73 signature segregates patients with ARMS but not ERMS by clinical survival time.
Fig. 5.
Fig. 5.
Genes and miRNAs regulated by p73 and mTOR are associated with MSC differentiation. (A) Analysis of p73 binding level to select target genes by ChIP-qPCR, performed in human MSCs. Error bars indicate SD from triplicate analysis. (B) p73/mTOR-regulated genes, p73-bound genes (ChIP-on-Chip), and genes significantly altered during 5AZA-induced myogenic differentiation of MSCs (multiple testing, corrected P value < 0.05) were compared. MSC microarray data were publicly available (17). The Venn diagram shows the number of Affymetrix probes in each category. (C) Treatment of MSCs with 5AZA results in decreased mTOR activity as shown by Western blot analysis of pS6, total S6, and actin levels. (D) This core set of nine direct p73 target genes from those regulated by 5AZA was sufficient to segregate ARMS and ERMS. Fold-changes are indicated in two bar charts for: 5AZA-treated MSCs relative to control (Left), and ARMS relative to ERMS (Right). (E) Quantitative RT-PCR was performed in MSCs treated with 5AZA, after knock-down of p73 (shp73) or control (shGFP) for the indicated genes, normalized to GAPDH levels and control. (F) Quantitative RT-PCR analysis of mature miR-133b levels was performed in Rh30 cells treated with control RNAi (shGFP), or three different RNAi constructs that target p73 (shp73-1, -2, and -3), normalized to RNU19 levels. Error bars represent SDs from three independent experiments.
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VSports最新版本 - References

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