Browse
Submit Data
Databases
API
Help

Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Phenotype specific analyses of p53 reveal distinct regulatory mechanism for chronically activated p53

ABSTRACT: microarray analysis with and without sh-p53 in IMR90 (normal human diploid fiborblasts) Phenotypes were created by overexpression of RasG12V, E1A/RasG12V in IMR90 cells, in growing IMR90, inr quiescent IMR90 cells (3 days confluence) and 24 or 48 hours Etoposide treated IMR90 cells were subjected to lentiviral knockdown of p53 or vector

ORGANISM(S): Homo sapiens

SUBMITTER: Suraj Menon

PROVIDER: E-GEOD-53379 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

ACCESS DATA

Json Xml

Similar Datasets

Phenotype specific analyses of p53 reveal distinct regulatory mechanism for chronically activated p53

Project description:p53 ChIP seq and Histone mark ChIP Seq data in IMR90 (normal human diploid fibroblasts) Phenotypes were created by overexpression of RasG12V, E1A/RasG12V in IMR90 cells, growing IMR90 and 24 hour Etoposide treated IMR90 cells were subjected to p53 and histone mark ChIP Seq

2015-03-02 | E-GEOD-53491 | biostudies-arrayexpress

Gene expression profiling of normal lung cells and K-RasG12V driven hyperplasias

Project description:We aimed to analyze the transcriptional profile of lung epithelial cells early after the expression of a resident K-RasG12V oncogene. This approach was based on the rationale that valuable therapeutic targets should be easier to detect in the first stages of tumor development due to tumor heterogeneity which occurr at late stages. We used a GEM model of lung adenocarcinoma driven by a resident K-RasG12V oncogene. In this GEM, the K-RasG12V allele also expresses a color marker that allows identification of K-RasG12V expressing cells at the single cell level in tissue sections. Thanks to this strategy we isolated early K-RasG12V-driven hyperplastic lesions (about 500 cells) and analyzed their gene expression profiling by Affymetrix GeneChip hybridization. Normal cells were isolated accordingly by LCM in the same lung sections.

2015-12-14 | E-GEOD-65256 | biostudies-arrayexpress

Gene expression profiling of advanced murine K-RasG12V lung adenocarcinomas

Project description:We aimed to analyze the transcriptional profile of full-blown murine lung adenocarcinomas driven by K-RasG12V oncogene. We used a GEM model of lung adenocarcinoma driven by a resident K-RasG12V oncogene. On average, tumors were collected 10 months after Adeno-CRE infection.

2015-12-14 | E-GEOD-65257 | biostudies-arrayexpress

Phenotype specific analyses of p53 reveal distinct regulatory mechanism for chronically activated p53

Project description:microarray analysis with and without sh-p53 in IMR90 (normal human diploid fiborblasts)

2015-02-27 | GSE53379 | GEO

Phenotype specific analyses of p53 reveal distinct regulatory mechanism for chronically activated p53

Project description:p53 ChIP seq and Histone mark ChIP Seq data in IMR90 (normal human diploid fibroblasts)

2015-03-02 | GSE53491 | GEO

Distinct p53 Genomic Binding Patterns in Normal and Cancer-derived Human Cells

Project description:We report here genome-wide analysis of the tumor suppressor p53 binding sites in normal human cells. 743 high-confidence ChIP-seq peaks representing putative genomic binding sites were identified in normal IMR90 fibroblasts using a reference chromatin sample. More than 40 % were located within 2 kb of a transcription start site (TSS), a distribution similar to that documented for individually studied functional p53 binding sites and to date not observed by previous genome-wide studies. Nearly half of the high-confidence binding sites in the IMR90 cells reside in CpG islands, in marked contrast to sites reported in cancer-derived cells. The distinct genomic features of the IMR90 binding sites do not reflect a distinct preference for specific sequences, since the de novo developed p53 motif based on our study is similar to those reported by genome-wide studies of cancer cells. More likely the different chromatin landscape in normal compared to cancer-derived cells influences p53 binding via modulating availability of the sites. We compared the IMR90 ChIP-seq peaks to the recently published IMR90 methylome1, and demonstrated that they are enriched at hypomethylated DNA. Our study represents the first genome-wide, de novo mapping of p53 binding sites in normal human cells and reveals that p53 binding sites reside in distinct genomic landscapes in normal and cancer-derived human cells.

2011-12-08 | GSE31558 | GEO

Chromatin dynamics of p53 binding sites in IMR90

Project description:We report the chromatin modification dynamics at p53 binding sites upon treatment with DMSO or nutlin3-a (5uM) in IMR90 human lung fibroblasts using ChIP-seq and RNA-seq analyses. We assessed the genomewide changes in H3, H3K4me3, H3K4me2, H3K4me1, H3K27ac, H4K16ac, RNA polymerase II, and p53 in response to p53 activation.

2014-11-12 | GSE58740 | GEO

Distinct p53 Genomic Binding Patterns in Normal and Cancer-derived Human Cells

2011-12-08 | E-GEOD-31558 | biostudies-arrayexpress

RNA-seq timecourse of p53 activation with Nutlin-3a in IMR90 cells

Project description:To investigate the dynamics of the p53 response, we treated IMR90 cells with Nutlin-3a, a small molecule that inhibits the interaction between p53 and its inhibitor Mdm2, for 6, 9, or 12 hours.

2020-10-31 | GSE139003 | GEO

p53 binding and chromatin dynamics after etoposide treatment of primary lung fibroblast

Project description:We report the chromatin modification dynamics at p53 binding sites afte 6 hours of treatment of etoposide (100 micromolar final) in IMR90 human lung fibroblasts using ChIP-seq , ATAC-seq, and polyA+ RNA-seq analyses. We assessed the genomewide occupancy of histone H3, H3K4me3, H3K4me2, H3K4me1, H3K27ac, H4K16ac, RNA polymerase II, p53, and transposase-accessible chromatin (ATAC-seq) in response to etoposide treatment.

2018-06-19 | GSE115940 | GEO

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data