Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

MeRIP-sequencing in lung adenocarcinoma cells

ABSTRACT: MeRIP-sequencing in lung adenocarcinoma cells

PROVIDER: PRJNA719778 | ENA |

REPOSITORIES: ENA

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
	SRR14142649_1.fastq.gz	Fastqsanger.gz
	SRR14142649_2.fastq.gz	Fastqsanger.gz
	SRR14142650_1.fastq.gz	Fastqsanger.gz
	SRR14142650_2.fastq.gz	Fastqsanger.gz
	SRR14142651_1.fastq.gz	Fastqsanger.gz

Items per page:

1 - 5 of 8

Similar Datasets

Comprehensive Analysis of the Transcriptome-Wide m6A Methylome in Lung Adenocarcinoma by MeRIP Sequencing

Project description:To investigate the role of m6A modification,MeRIP-seq was used to identify differential m6A modifications in lung adenocarcinoma .

2022-06-27 | GSE198288 | GEO

Comprehensive Analysis of the Transcriptome-Wide m6A Methylome in Lung Adenocarcinoma by MeRIP Sequencing

Project description:Comprehensive Analysis of the Transcriptome-Wide m6A Methylome in Lung Adenocarcinoma by MeRIP Sequencing

| PRJNA814496 | ENA

Ito2019 - gefitnib resistance of lung adenocarcinoma caused by MET amplification

Project description:The model is based on publication: Mathematical analysis of gefitinib resistance of lung adenocarcinoma caused by MET amplification Abstract: Gefitinib, one of the tyrosine kinase inhibitors of epidermal growth factor receptor (EGFR), is effective for treating lung adenocarcinoma harboring EGFR mutation; but later, most cases acquire a resistance to gefitinib. One of the mechanisms conferring gefitinib resistance to lung adenocarcinoma is the amplification of the MET gene, which is observed in 5–22% of gefitinib-resistant tumors. A previous study suggested that MET amplification could cause gefitinib resistance by driving ErbB3-dependent activation of the PI3K pathway. In this study, we built a mathematical model of gefitinib resistance caused by MET amplification using lung adenocarcinoma HCC827-GR (gefitinib resistant) cells. The molecular reactions involved in gefitinib resistance consisted of dimerization and phosphorylation of three molecules, EGFR, ErbB3, and MET were described by a series of ordinary differential equations. To perform a computer simulation, we quantified each molecule on the cell surface using flow cytometry and estimated unknown parameters by dimensional analysis. Our simulation showed that the number of active ErbB3 molecules is around a hundred-fold smaller than that of active MET molecules. Limited contribution of ErbB3 in gefitinib resistance by MET amplification is also demonstrated using HCC827-GR cells in culture experiments. Our mathematical model provides a quantitative understanding of the molecular reactions underlying drug resistance.

2024-09-02 | BIOMD0000000827 | BioModels

The molecular mechanism and clinical significance of IGF2BP3 in adenocarcinoma of the esophagogastric junction [meRIP-seq]

Project description:To reveal the potential m6A modification gene in Adenocarcinoma of the esophagogastric junction, we performed methylated RNA immunoprecipitation and sequencing (meRIP-seq) in OE-19 cells.

2024-10-09 | GSE261201 | GEO

Genomic Sequencing of Lung Adenocarcinoma

Project description:Genomic Sequencing of Lung Adenocarcinoma

| PRJNA157937 | ENA

MeRIP-sequencing in ESCC cells

Project description:MeRIP-sequencing in ESCC cells

| PRJNA646697 | ENA

Transcriptomic analyses of lung adenocarcinoma cells

Project description:Transcriptomic analyses of lung adenocarcinoma cells

| PRJNA843347 | ENA

MeRIP sequencing

Project description:MeRIP sequencing

| PRJNA655242 | ENA

MeRIP sequencing

Project description:MeRIP sequencing

| PRJNA725397 | ENA

Single cell RNA sequencing of lung adenocarcinoma

Project description:We performed single cell RNA sequencing (scRNA-seq) for 208,506 cells derived from 58 lung adenocarcinomas from 44 patients, which covers primary tumour, lymph node and brain metastases, and pleural effusion in addition to normal lung tissues and lymph nodes. The extensive single cell profiles depicted a complex cellular atlas of lung adenocarcinoma progression which includes cancer, stromal, and immune cells in the surrounding tumor microenvironments.

2020-03-27 | GSE131907 | 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