Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Transcriptome analysis after knockdown of target genes (either HSP27 or TGF-β1, both HSP27 and TGF-β1) via shRNAs in MDA-MB-231 cells

ABSTRACT: Comparing expression profiles : among comparable samples in which target genes are knocked down Global gene expression profiling has shown that more than 1500 (3.2%) genes over 2-fold gene fluctuations are differentially expressed in shTGF-β1-treated cells compared to control shRNA-treated cells.

ORGANISM(S): Homo sapiens

PROVIDER: GSE196289 | GEO | 2022/02/08

REPOSITORIES: GEO

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

Transcriptome analysis after knockdown of target genes (either HSP27 or TGF-β1, both HSP27 and TGF-β1) via shRNAs in A549 cells

Project description:Comparing expression profiles : among comparable samples in which target genes are knocked down Global gene expression profiling has shown that more than 1500 (3.2%) genes over 2-fold gene fluctuations are differentially expressed in shTGF-β1-treated cells compared to control shRNA-treated cells.

2022-02-08 | GSE196286 | GEO

Transcriptome analysis after knockdown of target genes (either HSP27 or TGF-β1, both HSP27 and TGF-β1) via shRNAs in MIA PaCa-2 cells

2022-02-08 | GSE196288 | GEO

Transcriptome analysis after knockdown of target genes (either HSP27 or TGF-β1, both HSP27 and TGF-β1) via shRNAs in SNU-398 cells

Project description:Comparing expression profiles : among comparable samples in which target genes are knocked down Global gene expression profiling has shown that only 134 (0.3%) genes over 2-fold gene fluctuations are differentially expressed in shTGF-β1-treated cells compared to control shRNA-treated cells.

2022-02-08 | GSE196287 | GEO

Transcriptome analysis after knockdown of target genes (either HSP27 or TGF-β1, both HSP27 and TGF-β1) via shRNAs in MDA-MB-231 cells

Project description:Transcriptome analysis after knockdown of target genes (either HSP27 or TGF-β1, both HSP27 and TGF-β1) via shRNAs in MDA-MB-231 cells

| PRJNA804178 | ENA

Transcriptome analysis after knockdown of target genes (either HSP27 or TGF-β1, both HSP27 and TGF-β1) via shRNAs in A549 cells

Project description:Transcriptome analysis after knockdown of target genes (either HSP27 or TGF-β1, both HSP27 and TGF-β1) via shRNAs in A549 cells

| PRJNA804181 | ENA

Transcriptome analysis after knockdown of target genes (either HSP27 or TGF-β1, both HSP27 and TGF-β1) via shRNAs in SNU-398 cells

Project description:Transcriptome analysis after knockdown of target genes (either HSP27 or TGF-β1, both HSP27 and TGF-β1) via shRNAs in SNU-398 cells

| PRJNA804180 | ENA

Transcriptome analysis after knockdown of target genes (either HSP27 or TGF-β1, both HSP27 and TGF-β1) via shRNAs in MIA PaCa-2 cells

Project description:Transcriptome analysis after knockdown of target genes (either HSP27 or TGF-β1, both HSP27 and TGF-β1) via shRNAs in MIA PaCa-2 cells

| PRJNA804179 | ENA

Transcriptomic Changes in TGF-β1 Differentiated and PGE2 Dedifferentiated Myofibroblasts

Project description:These data show that the genes that distinguish myofibroblasts from fibroblasts are myriad, and that some genes not traditionally associated with myofibroblast differentiation may serve as novel therapeutic targets for fibrosing disorders. Gene expression levels were assessed from total RNA on the Affymetrix U219 microarray. Here, we use transforming growth factor-β1 (TGF-β1) and prostaglandin E2 (PGE2), which has recently been shown to reverse myofibroblast differentiation, to investigate the transcriptomic changes that occur during TGF-β1-induced differentiation and PGE2-induced de-differentiation of myofibroblasts.

2015-06-30 | E-GEOD-63659 | biostudies-arrayexpress

Effect of TGF-β1 treatment on gene expression of HK2 cells

Project description:To elucidate the expression file under TGF-β1 treatment , we performed RNA-seq on HK2 cells treated with TGF-β or not We then performed gene expression profiling analysis using data obtained from RNA-seq of HK2 cells untreated or treated with TGF-β1 (5ng/ml) for 24 h

2024-08-11 | GSE240748 | GEO

Genome-wide transcript profiling for native porcine valvular interstitial cells and those cultured on TCPS and treated with TGF-β1

Project description:Fibrotic diseases have significant health impact and have been associated with differentiation of the resident fibroblasts into myofibroblasts. In particular, stiffened extracellular matrix and TGF-β1 in fibrotic lesions have been shown to promote pathogenic myofibroblast activation and progression of fibrosis in various tissues. To better understand the roles of mechanical and chemical cues on myofibroblast differentiation and how they may crosstalk, we cultured primary valvular interstitial cells (VICs) isolated from porcine aortic valves and studied how traditional TCPS culture, which presents a non-physiologically stiff environment, and TGF-β1 affect native VIC phenotypes. We carried out gene expression profiling using porcine genome microarrays from Affymetrix and found that traditional TCPS culture induces major changes in gene expression of native VICs, rendering these cells more activated and similar to cells treated with TGF-β1. We also monitored time-dependent effects induced by TGF-β1 by examining gene expression changes induced by TGF-β1 at 8 hours and 24 hours. Porcine aortic VICs were isolated and cultured with or without TGF-β1 treatment for RNA extraction and hybridization on Affymetrix microarrays. We included 3 biological replicates for each condition. P0 VICs were freshly isolated cells which had not been cultured. P2 VICs were cells that had been passaged 2 times and cultured on plastic plates in low serum media. Some of the P2 VICs were treated with TGF-β1 at 5ng/ml for 8 hours or 24 hours. All the control and TGF-β1-treated conditions were collected at the same time on day 3 of culture.

2013-09-02 | E-GEOD-48839 | biostudies-arrayexpress

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