TP53-Status-Dependent Oncogenic EZH2 Activity in Pancreatic Cancer
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PROVIDER: PRJNA808385 | ENA |
REPOSITORIES: ENA
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Project description:Transcriptomic analysis of p53-wildtype and -mutant murine PDAC cells in the presence and absence of EZH2 revealed p53-status determined EZH2-dependent target gene regulation. We found that among others p53-pathway and apoptosis-related gene sets are enriched in p53wt PDAC cells upon EZH2 depletion but not in cells bearing a mutation in the Trp53 gene.
2022-08-02 | GSE197006 | GEO
Project description:Pancreatic Ductal Adenocarcinoma (PDAC) represents a lethal malignancy with a consistently poor outcome. Besides mutations in PDAC driver genes, the aggressive tumor biology of the disease and its remarkable therapy resistance are predominantly installed by potentially reversible epigenetic dysregulation. However, epigenetic regulators act in a context-dependent manner with opposing implication on tumor progression, thus critically determining the therapeutic efficacy of epigenetic targeting. Herein, we aimed at exploring the molecular prerequisites and underlying mechanisms of oncogenic Enhancer of Zeste Homolog 2 (EZH2) activity in PDAC progression. Preclinical studies in EZH2 proficient and deficient transgenic and orthotopic in vivo PDAC models and transcriptome analysis identified the TP53 status as a pivotal context-defining molecular cue determining oncogenic EZH2 activity in PDAC. Importantly, the induction of pro-apoptotic gene signatures and processes as well as a favorable PDAC prognosis upon EZH2 depletion were restricted to p53 wildtype (wt) PDAC subtypes. Mechanistically, we illustrate that EZH2 blockade de-represses CDKN2A transcription for the subsequent posttranslational stabilization of p53wt expression and function. Together, our findings suggest an intact CDKN2A-p53wt axis as a prerequisite for the anti-tumorigenic consequences of EZH2 depletion and emphasize the significance of molecular stratification for the successful implementation of epigenetic targeting in PDAC.
| S-EPMC9320674 | biostudies-literature
Project description:TP53 mutations are a poor prognostic factor in breast cancers. This study sets out to identify the gene set that determine expression signature of the TP53 status (TP53 signature) and to correlate it with clinical outcome. Using comprehensive expression analysis and DNA sequencing of the TP53 gene in 38 Japanese breast cancer patients, we have isolated a gene set of 33 genes from differentially expressed genes in the learning set (n=26), depending on the TP53 status. Predictive accuracy of TP53 status by gene expression profile was 83.3% in the test set (n=12). As independent external datasets, two published datasets were introduced for validation of TP53 status prediction (251 Swedish samples) and survival analysis (both the Swedish and 295 Dutch samples). TP53 signature has the ability to predict recurrence-free survival (RFS) of 29 stage I and II Japanese breast cancers (log rank, P = 0.032), and RFS, overall survival of two independently published datasets (log rank, both P < 0.0001). Multivariate analysis has shown an independent and significant prognostic factor with a hazard ratio (HR) for recurrence and survival in two external datasets (P < 0.0001). The TP53 signature is also a strong prognostic factor in the subgroups: estrogen-receptor positive, lymph node (LN) positive and negative, intermediate/high risk in St. Gallen criteria, and high risk in National Cancer Institute (NCI) criteria (log rank, P < 0.0001). TP53 signature is a reliable and independent predictor of the outcome of disease in operated breast cancer. Keywords: Tumor sample comparison
2006-08-23 | GSE5546 | GEO
Project description:The goal of this study was to delineate the important EZH2 direct target genes that mediate the oncogenic properties of EZH2 in HCC. The EZH2 direct target genes in two HCC cell lines were identified by chromatin immunoprecipitation microarray (ChIP-chip) analysis and later confirmed by independent ChIP-PCR. The functions of the target genes were further examined. Two human HCC cell lines, Huh7 and PLC/PRF/5 (PLC5), were grown in DMEM supplemented with 10% fetal bovine serum. ChIP assays were performed using anti-EZH2 antibody. The immunoprecipitated and input DNA were used to probe the Agilent human ChIP-chip arrays.
2011-05-31 | E-GEOD-17733 | biostudies-arrayexpress
Project description:Background: Gene expression profiling of breast carcinomas has increased our understanding of the heterogeneous biology of this disease and promises to impact clinical care. The aim of this study was to evaluate the prognostic value of gene expression-based classification along with established prognostic markers and mutation status of the TP53 gene, in a group of breast cancer patients with long-term (12-16 years) follow-up. Methods: The clinical and histopathological parameters of 200 breast cancer patients were studied for their effects on clinical outcome using univariate/multivariate Cox regression. The prognostic impact of mutations in the TP53 gene, identified using TTGE and sequencing, was also evaluated. Eighty of the samples were analyzed for gene expression using 42K cDNA microarrays and the patients were assigned to five previously defined molecular expression groups. The strength of the gene expression based classification versus standard markers was evaluated by adding this variable to the Cox regression model used to analyze all samples. Results: Both univariate and multivariate analysis showed that TP53 mutation status, tumor size and lymph node status were the strongest predictors of breast cancer survival for the whole group of patients. Analyses of the patients with gene expression data showed that TP53 mutation status, gene expression based classification, tumor size and lymph node status were significant predictors of survival. The TP53 mutation status showed strong association with the ?basal-like? and ?ERBB2+? gene expression subgroups, and tumors with mutation had a characteristic gene expression pattern. Conclusions: TP53 mutation status and gene-expression based groups are important survival markers of breast cancer, and these molecular markers may provide prognostic information that complements clinical variables. The study adds experience and knowledge to an ongoing characterization and classification of the disease. Experiment set consisting of 80 primary breast carcinomas collected at Ulleval University Hospital (ULL-samples), Oslo, Norway from 1990-94, and one normal sample from breast reduction surgery.
2012-09-18 | E-GEOD-40954 | biostudies-arrayexpress
Project description:Background: Gene expression profiling of breast carcinomas has increased our understanding of the heterogeneous biology of this disease and promises to impact clinical care. The aim of this study was to evaluate the prognostic value of gene expression-based classification along with established prognostic markers and mutation status of the TP53 gene, in a group of breast cancer patients with long-term (12-16 years) follow-up. Methods: The clinical and histopathological parameters of 200 breast cancer patients were studied for their effects on clinical outcome using univariate/multivariate Cox regression. The prognostic impact of mutations in the TP53 gene, identified using TTGE and sequencing, was also evaluated. Eighty of the samples were analyzed for gene expression using 42K cDNA microarrays and the patients were assigned to five previously defined molecular expression groups. The strength of the gene expression based classification versus standard markers was evaluated by adding this variable to the Cox regression model used to analyze all samples. Results: Both univariate and multivariate analysis showed that TP53 mutation status, tumor size and lymph node status were the strongest predictors of breast cancer survival for the whole group of patients. Analyses of the patients with gene expression data showed that TP53 mutation status, gene expression based classification, tumor size and lymph node status were significant predictors of survival. The TP53 mutation status showed strong association with the ?basal-like? and ?ERBB2+? gene expression subgroups, and tumors with mutation had a characteristic gene expression pattern. Conclusions: TP53 mutation status and gene-expression based groups are important survival markers of breast cancer, and these molecular markers may provide prognostic information that complements clinical variables. The study adds experience and knowledge to an ongoing characterization and classification of the disease.
2012-09-18 | GSE40954 | GEO
Project description:The goal of this study was to delineate the important EZH2 direct target genes that mediate the oncogenic properties of EZH2 in HCC. The EZH2 direct target genes in two HCC cell lines were identified by chromatin immunoprecipitation microarray (ChIP-chip) analysis and later confirmed by independent ChIP-PCR. The functions of the target genes were further examined.
2011-05-31 | GSE17733 | GEO
Project description:TP53 mutations are a poor prognostic factor in breast cancers. This study sets out to identify the gene set that determine expression signature of the TP53 status (TP53 signature) and to correlate it with clinical outcome. Using comprehensive expression analysis and DNA sequencing of the TP53 gene in 38 Japanese breast cancer patients, we have isolated a gene set of 33 genes from differentially expressed genes in the learning set (n=26), depending on the TP53 status. Predictive accuracy of TP53 status by gene expression profile was 83.3% in the test set (n=12). As independent external datasets, two published datasets were introduced for validation of TP53 status prediction (251 Swedish samples) and survival analysis (both the Swedish and 295 Dutch samples). TP53 signature has the ability to predict recurrence-free survival (RFS) of 29 stage I and II Japanese breast cancers (log rank, P = 0.032), and RFS, overall survival of two independently published datasets (log rank, both P < 0.0001). Multivariate analysis has shown an independent and significant prognostic factor with a hazard ratio (HR) for recurrence and survival in two external datasets (P < 0.0001). The TP53 signature is also a strong prognostic factor in the subgroups: estrogen-receptor positive, lymph node (LN) positive and negative, intermediate/high risk in St. Gallen criteria, and high risk in National Cancer Institute (NCI) criteria (log rank, P < 0.0001). TP53 signature is a reliable and independent predictor of the outcome of disease in operated breast cancer. Experiment Overall Design: Microarray hybridizations (Agilent: Whole Human Genome Oligo Microarray; 41k unique probe) were carried out with 1μg Cy3 labeled cRNA and 1 μg Cy5 labeled cRNA, both prepared from each sample and reference pool, respectively. Experiment Overall Design: Fluorescent intensities of scanned images were quantified by ArrayVision Ver.8 rev.4 (Imaging research). Experiment Overall Design: The gene expression data was quantified and analyzed by GeneSpring 6.2 (Silicon Genetics). To identify the TP53 status predictor gene set, a Wilcoxon rank sum test along with Benjamini and Hochberg false discovery rate (FDR) was used.
2008-06-13 | E-GEOD-5546 | biostudies-arrayexpress
Project description:Uveal melanoma cells are resistant to EZH2 inhibition regardless of BAP1 status
2016-06-06 | GSE79905 | GEO
Project description:Epigenetic alterations have been increasingly implicated in oncogenesis. Analysis of Drosophila mutants suggests that Polycomb and SWI/SNF complexes can serve antagonistic developmental roles. However, the relevance of this relationship to human disease is unclear. Here we have investigated functional relationships between these epigenetic regulators in oncogenic transformation. Mechanistically, we show that loss of the SNF5 tumor suppressor leads to elevated expression of the Polycomb gene EZH2 and that Polycomb targets are broadly H3K27-trimethylated and repressed in SNF5-deficient fibroblasts and cancers. Further, we show antagonism between SNF5 and EZH2 in the regulation of stem cell-associated programs and that Snf5 loss activates those programs. Finally, using conditional mouse models, we show that inactivation of Ezh2 blocks tumor formation driven by Snf5 loss. Mouse Embryonic Fibroblasts (MEFs) conditionally inactivated for Ezh2, Snf5 and Ezh2, or from control WT MEFs were used to evaluated epigenetic antagonism between Snf5 and Ezh2 in the control of gene expression programs. Snf5-deficient lymphoma samples and control CD8+ WT T-cells were used to evaluate genetic programs misregulated by Snf5 inactivation during tumorigenesis. RNA was isolated from each of these samples and used for gene expression profiling on Affymetrix arrays.
2010-10-19 | E-GEOD-23656 | biostudies-arrayexpress