Oncogene-induced senescence (OIS) is a p53-dependent defence mechanism against uncontrolled proliferation. Consequently, many human tumours harbour p53 mutations while others show a dysfunctional p53 pathway, frequently by unknown mechanisms. We identified BRD7, a bromodomain-containing protein whose inhibition allows full neoplastic transformation in the presence of wild-type p53. Intriguingly, in human breast tumours harbouring wild-type, but not mutant p53, the BRD7 gene locus was frequently deleted and low BRD7 expression was found in a subgroup of tumours. Functionally, BRD7 is required for efficient p53-mediated transcription of a subset of target genes. BRD7 interacts with p53 and p300, and is recruited to target gene promoters, affecting histone acetylation, p53 acetylation, and promoter activity. Thus, BRD7 suppresses tumourigenicity by serving as a p53 cofactor required for efficient induction of p53-dependent OIS.
BRD7 is a candidate tumour suppressor gene required for p53 function.
Specimen part, Disease, Cell line
View SamplesWe have identified ZNF423 (also known as Ebfaz, OAZ or Zfp423) as a component critically required for retinoic acid (RA)-induced differentiation. ZNF423 associates with the RAR/RXR nuclear receptor complex and is essential for transactivation in response to retinoids. Down-regulation of ZNF423 expression by RNA interference in neuroblastoma cells results in a growth advantage and resistance to RA-induced differentiation, whereas overexpression of ZNF423 leads to growth inhibition and enhanced differentiation. Futhermore, we show that low ZNF423 expression is associated with poor disease outcome of neuroblastoma patients. To identify the other key pathways regulated by ZNF423 in human neuroblastoma, we expressed elevated levels of ZNF423 in SH-SY5Y cells and performed full genome gene expression analysis in these cells.
ZNF423 is critically required for retinoic acid-induced differentiation and is a marker of neuroblastoma outcome.
Specimen part
View SamplesThis SuperSeries is composed of the SubSeries listed below.
Pretreatment microRNA Expression Impacting on Epithelial-to-Mesenchymal Transition Predicts Intrinsic Radiosensitivity in Head and Neck Cancer Cell Lines and Patients.
Sex, Specimen part, Cell line
View SamplesPurpose: Predominant causes of head and neck cancer recurrence after radiotherapy are rapid repopulation, hypoxia, fraction of cancer stem cells and intrinsic radioresistance. Currently, intrinsic radioresistance can only be assessed by ex-vivo colony assays. Besides being time-consuming, colony assays do not identify causes of intrinsic resistance. We aimed to identify a biomarker for intrinsic radioresistance to be used before start of treatment and to reveal biological processes that could be targeted to overcome intrinsic resistance.
Pretreatment microRNA Expression Impacting on Epithelial-to-Mesenchymal Transition Predicts Intrinsic Radiosensitivity in Head and Neck Cancer Cell Lines and Patients.
Specimen part, Cell line
View SamplesPurpose: Predominant causes of head and neck cancer recurrence after radiotherapy are rapid repopulation, hypoxia, fraction of cancer stem cells and intrinsic radioresistance. Currently, intrinsic radioresistance can only be assessed by ex-vivo colony assays. Besides being time-consuming, colony assays do not identify causes of intrinsic resistance. We aimed to identify a biomarker for intrinsic radioresistance to be used before start of treatment and to reveal biological processes that could be targeted to overcome intrinsic resistance.
Pretreatment microRNA Expression Impacting on Epithelial-to-Mesenchymal Transition Predicts Intrinsic Radiosensitivity in Head and Neck Cancer Cell Lines and Patients.
Specimen part
View SamplesPseudomonas fluorescens strain SS101 (Pf.SS101) promotes growth of Arabidopsis thaliana, enhances greening and lateral root formation, and induces systemic resistance (ISR) against the bacterial pathogen Pseudomonas syringae pv. tomato (Pst). Here, targeted and untargeted approaches were adopted to identify bacterial determinants and underlying mechanisms involved in plant growth promotion and ISR by Pf.SS101. Based on targeted analyses, no evidence was found for volatiles, lipopeptides and siderophores in plant growth promotion by Pf.SS101. Untargeted, genome-wide analyses of 7,488 random transposon mutants of Pf.SS101 led to the identification of 21 mutants defective in both plant growth promotion and ISR. Many of these mutants, however, were auxotrophic and impaired in root colonization. Genetic analysis of three mutants followed by site-directed mutagenesis, genetic complementation and plant bioassays revealed the involvement of the phosphogluconate dehydratase gene edd, the response regulator gene colR and the adenylsulfate reductase gene cysH in both plant growth promotion and ISR. Subsequent comparative plant transcriptomics analyses strongly suggest that modulation of sulfur assimilation, auxin biosynthesis and transport, steroid biosynthesis and carbohydrate metabolism in Arabidopsis are key mechanisms linked to growth promotion and ISR by Pf.SS101.
Genome-wide analysis of bacterial determinants of plant growth promotion and induced systemic resistance by Pseudomonas fluorescens.
Specimen part, Treatment
View SamplesThis SuperSeries is composed of the SubSeries listed below.
No associated publication
Sex, Age, Specimen part, Time
View SamplesCombinations of anticancer agents may have synergistic anti-tumor effects, but enhanced toxicity often limit their clinical use. The risk that combinations of two or more drugs will cause adverse effects that are more severe than drugs used as monotherpies can be hypothesized from comprehensive analysis of each compounds activity. We generated microarray gene expression data following a single dose of agents administered individually with that of the agents administered in a combination. The key objective of this initiative is to generate and make publicly available key high-content gene expression data sets for mechanistic hypothesis generation for several anticancer drug combinations. The expectation is that availability of tissue-based genomic information that are derived from target tissues will facilitate the generation and testing of mechanistic hypotheses. The view is that availability of these data sets for bioinformaticians and other scientists will contribute to analysis of these data and evaluation of the approach.
No associated publication
Sex, Specimen part, Time
View SamplesCombinations of anticancer agents may have synergistic anti-tumor effects, but enhanced toxicity often limit their clinical use. The risk that combinations of two or more drugs will cause adverse effects that are more severe than drugs used as monotherpies can be hypothesized from comprehensive analysis of each compounds activity. We generated microarray gene expression data following a single dose of agents administered individually with that of the agents administered in a combination. The key objective of this initiative is to generate and make publicly available key high-content gene expression data sets for mechanistic hypothesis generation for several anticancer drug combinations. The expectation is that availability of tissue-based genomic information that are derived from target tissues will facilitate the generation and testing of mechanistic hypotheses. The view is that availability of these data sets for bioinformaticians and other scientists will contribute to analysis of these data and evaluation of the approach.
No associated publication
Sex, Specimen part, Time
View SamplesCombinations of anticancer agents may have synergistic anti-tumor effects, but enhanced toxicity often limit their clinical use. The risk that combinations of two or more drugs will cause adverse effects that are more severe than drugs used as monotherpies can be hypothesized from comprehensive analysis of each compounds activity. We generated microarray gene expression data following a single dose of agents administered individually with that of the agents administered in a combination. The key objective of this initiative is to generate and make publicly available key high-content gene expression data sets for mechanistic hypothesis generation for several anticancer drug combinations. The expectation is that availability of tissue-based genomic information that are derived from target tissues will facilitate the generation and testing of mechanistic hypotheses. The view is that availability of these data sets for bioinformaticians and other scientists will contribute to analysis of these data and evaluation of the approach.
No associated publication
Sex, Age, Specimen part, Time
View Samples