Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Next Generation Sequencing Facilitates Quantitative Analysis of HGF treated (HGF+) and matched control (HGF-) HepG2 cells

ABSTRACT: Next Generation Sequencing Facilitates Quantitative Analysis of HGF treated (HGF+) and matched control (HGF-) HepG2 cells

PROVIDER: PRJNA551437 | ENA |

REPOSITORIES: ENA

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
	SRR9608240_1.fastq.gz	Fastqsanger.gz
	SRR9608240_2.fastq.gz	Fastqsanger.gz
	SRR9608237_1.fastq.gz	Fastqsanger.gz
	SRR9608237_2.fastq.gz	Fastqsanger.gz
	SRR9608238_1.fastq.gz	Fastqsanger.gz

Items per page:

1 - 5 of 8

Similar Datasets

Next Generation Sequencing Facilitates Quantitative Analysis of HGF treated (HGF+) and matched control (HGF-) HepG2 cells

Project description:We report the high-throughput profiling of HGF treated liver cancer cell (HepG2) for differentiated genes analysis. We generated HGF stimulated and paired control HepG2 cells for 4 days. We find that tumor suppressor genes that are overexpressed and some tumor associated genes were downregulated, therefore reflect cell state and HGF induced anti-tumor potential. This study provides a potential framework for the research of HGF induced critical genes in the application of liver cancer therapy.

2021-12-30 | GSE133424 | GEO

HepG2 Cell: Control vs. HGF treated

Project description:Transcription profile of HepG2 cells treated with hepatocyte growth factor and control cells Two condition experiment, Hep G2 vs. Hep G2-HGF. Biological replicates: 1 control and 1 HGF-treated (no replication)

2012-02-23 | E-GEOD-35994 | biostudies-arrayexpress

Next-generation sequencing facilitates quantitative analysis of CON and PMB treatment HepG2 cells transcriptomes

Project description:Next-generation sequencing facilitates quantitative analysis of CON and PMB treatment HepG2 cells transcriptomes

| PRJNA856662 | ENA

Next Generation Sequencing Facilitates Quantitative Analysis of CON and PMB treatment HepG2 cells Transcriptomes

Project description:Next Generation Sequencing Facilitates Quantitative Analysis of CON and PMB treatment HepG2 cells Transcriptomes

| PRJNA770983 | ENA

Next Generation Sequencing Facilitates Quantitative Analysis of HepG2 cells exploring to the Fluid shear stress

Project description:Next Generation Sequencing Facilitates Quantitative Analysis of HepG2 cells exploring to the Fluid shear stress

| PRJNA609656 | ENA

Next Generation Sequencing Facilitates Quantitative Analysis of HepG2 cells exploring to the Fluid shear stress

Project description:To investigate the mechanisms underlying Fluid shear stress affecting HepG2 cells motility, we conducted global gene expression profiling of FSS-HepG2 cells compared with static cultured HepG2 cells.

2020-03-03 | GSE146169 | GEO

The effect of human gingival fibroblast-conditioned medium (HGF-CM) on pulp regeneration

Project description:HGF-CM increases the proliferation and migration ability of DPSC (Dental pulp stem cells) in a dosage dependent manner, and facilitates the mineralization of DPSC by upregulating odotogenic genes. Although lack of in vitro evidence, DPSC and hGF-CM could be a promising combination for pulp regeneration in the future.

2022-10-29 | GSE201524 | GEO

Transcriptomic and Proteomic Response of HC-04 to hepatocyte growth factor (HGF)

Project description:The routine study of human malaria liver-stage biology in vitro is hampered by low infection efficiency of human hepatocellular carcinoma (HCC) lines (<0.1%), poor understanding of steady-state HCC biology, and lack of appropriate tools for trace sample analysis. HC-04 is the only HCC that supports complete development of human malaria parasites. We hypothesized that HCCs are in various intermediate stages of the epithelial-mesenchymal transition (EMT) and HC-04s retain epithelial characteristics that permit infection. We developed an novel analytical approach to test this hypothesis viz. the HC-04 response to hepatocyte growth factor (HGF). We used online two-dimensional liquid chromatography tandem mass spectrometry (2D-LC-MS/MS) to quantify protein expression profiles in HC-04 pre-/post-HGF treatment and validated these results by RT-qPCR and microscopy. We successfully increased protein identification efficiency over offline-2D methods by 12-fold using less sample material, allowing robust protein quantification. We observed expected up-regulation and down-regulation of EMT protein markers in response to HGF, but also unexpected cellular responses. HC-04 is thus susceptible to HGF-mediated signaling but to a lesser degree than what we observed for HepG2, a widely used, but poor malaria HCC model. Our analytical approach to understanding the basic biology of HC-04 helps us understand the factors that may influence its utility as a model for malaria liver-stage development. We observed that HC-04 treatment with HGF prior to the addition of Plasmodium falciparum sporozoites did not facilitate cell invasion, arguing for unlinking the effect of HGF on malaria liver stage development from hepatocyte invasion. Finally, our 2D-LC-MS/MS approach and broadly applicable experimental strategy should prove useful in the analysis of various hepatocyte-pathogen interactions, tumor progression and early disease events.

2014-02-17 | PXD000682 | Pride

Next Generation Sequencing Facilitates Quantitative Analysis of IFNα Stimulated Transcriptomes in HepG2, SETD2-KO, STAT1-KO and STAT1-K525ARe HepG2 cells

Project description:Purpose: Using RNA-seq to analyze the different expressions induced by IFNα among the SETD2-KO HepG2 cells, STAT1-KO HepG2 cells and STAT1-K525A-Re HepG2 cells and HepG2 control cells Methods: mRNA profiles of HepG2 control cells and SETD2-KO cells, STAT1-KO cells, STAT1-K525A-Re cells were generated by deep sequencing, using BGISEQ-500RS. The sequence reads that passed quality filters were analyzed at the transcriptional level with RSEM (RNA-seq by Expectation Maximization).

2019-03-12 | GSE98372 | GEO

Differential expression of miRNAs in HGF treated SWAN-71 versus untreated control by next generation sequencing

Project description:The goal of this study is to compare miRNAs expressed by HGF treated SWAN-71 cells to miRNAs expressed in untreated control SWAN-71 cells to identify micro RNAs which play a role during HGF-mediated SWAN-71 cell invasion

2019-01-29 | GSE125790 | 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