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accession-icon GSE30183
Expression profiling of MCF7 cells upon nutlin3a treatment
  • organism-icon Homo sapiens
  • sample-icon 18 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U219 Array (hgu219)

Description

The tumor suppressor p53 can induce various biological responses. Yet it is not clear whether it is p53 in vivo promoter selectivity that triggers different transcription programs leading to different outcomes. Our analysis of genome-wide chromatin occupancy by p53 using ChIP-seq (deposited in Sequence Read Archive database as SRP007261) revealed p53 default program, i.e. the pattern of major p53-bound sites that is similar upon p53 activation by nutlin3a, RITA or 5-FU in breast cancer cells, despite different biological outcomes triggered by these compounds. Parallel analysis of gene expression allowed identification of 280 previously unknown p53 target genes, including p53-repressed AURKA. The consensus p53 binding motif was present more frequently in p53-induced, than in repressed targets, indicating different mechanisms of gene activation versus repression. We identified several possible cofactors of p53, and found that STAT3 antagonised p53-mediated repression of a subset of genes, including AURKA. Finally, we showed that the expression of the novel p53 targets correlates with p53 status and survival in breast cancer patients.

Publication Title

Insights into p53 transcriptional function via genome-wide chromatin occupancy and gene expression analysis.

Sample Metadata Fields

Cell line, Treatment

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refine.bio is a repository of uniformly processed and normalized, ready-to-use transcriptome data from publicly available sources. refine.bio is a project of the Childhood Cancer Data Lab (CCDL)

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Cite refine.bio

Casey S. Greene, Dongbo Hu, Richard W. W. Jones, Stephanie Liu, David S. Mejia, Rob Patro, Stephen R. Piccolo, Ariel Rodriguez Romero, Hirak Sarkar, Candace L. Savonen, Jaclyn N. Taroni, William E. Vauclain, Deepashree Venkatesh Prasad, Kurt G. Wheeler. refine.bio: a resource of uniformly processed publicly available gene expression datasets.
URL: https://www.refine.bio

Note that the contributor list is in alphabetical order as we prepare a manuscript for submission.

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