Metabolomics,Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

Expression profiling of MCF7 cells upon nutlin3a treatment

ABSTRACT: 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. We used microarrays to detail the global programme of gene expression changed upon nutlin3a treatment and knocking-down of STAT3 transcription program MCF7 cell with or without knock-down of STAT3 were treated with nutlin3a and collected for RNA extraction and hybridization on Affymetrix microarrays.

ORGANISM(S): Homo sapiens

SUBMITTER: Fedor Nikulenkov

PROVIDER: E-GEOD-30183 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Publications

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

Nikulenkov F F Spinnler C C Li H H Tonelli C C Shi Y Y Turunen M M Kivioja T T Ignatiev I I Kel A A Taipale J J Selivanova G G

Cell death and differentiation 20120713 12

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 chromatin immunoprecipitation (ChIP)-seq revealed 'p53 default program', that is, the pattern of major p53-bound sites that is similar upon p53 activation by nutlin3a, reactivation of p53 and induction of tumor cell apoptosis ( ...[more]

PMID: 22790872

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Project description:Background: With the incidence of papillary thyroid carcinoma rising worldwide, the decision about lobectomy versus total thyroidectomy will become relevant for an increasing number of patients. There exists no reliable biomarker for metastatic potential or tendency of recurrence that could assist in the risk stratification of patients. Objective: To develop a gene expression classifier for metastatic potential by measuring RNA expression in the primary tumor at the time of cancer surgery. Further, to investigate the ability of the gene expression classifier to identify metastatic and recurrent cases. Method: Genome-wide expression analyses. The development cohort consisted of freshly frozen tissues from 38 patients collected between the years 1986 and 2009. Validation was performed on a consecutive cohort of formalin fixated paraffin embedded surgical tissue specimens from 183 patients treated at Odense and Aarhus University Hospitals. Results: A 17 gene classifier (ADAMTS1, ANTXR1, C7, CXCL12, EBF1, FBLN2, FOSL2, GGT5, GPR124, JAM3, LRIG1, NDRG1, PRRX1, ROBO1, SORL1, TCF4, and ZEB1) was identified based on the expression values of these genes in the groups with and without metastasis in the development cohort. The 17 gene classifier for regional and/or distant metastasis identified was tested against the clinical status in the validation cohort. Sensitivity was 51.6% (95% CI 41.2%-61.8) and specificity 61.6 % (95% CI 50.5%-71.9%). Further, the Kaplan-Meyer method was used to estimate whether the classifier was useful as a prognostic marker for recurrences. Log-rank testing failed to identify any significance (p=0.32). Conclusion: A 17 gene classifier for metastatic potential was developed, and the results showed a clear biological difference between groups. However, through validation, the prognostic significance of this classifier could not be shown in identifying metastatic cases or in the ability of dichotomizing patients according to risk of recurrence after primary treatment. 38 patients with papillary thyroid carcinoma from a consecutive cohort of patients, no replicates

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Dataset Information

Expression profiling of MCF7 cells upon nutlin3a treatment

Publications

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

Similar Datasets

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