Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Single-cell ATAC and RNA sequencing reveal pre-existing and persistent cells associated with prostate cancer relapse [scATAC-seq]

ABSTRACT: Single-cell ATAC and RNA sequencing reveal pre-existing and persistent cells associated with prostate cancer relapse [scATAC-seq]

PROVIDER: PRJNA713355 | ENA |

REPOSITORIES: ENA

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
	SRR13927735_1.fastq.gz	Fastqsanger.gz
	SRR13927735_2.fastq.gz	Fastqsanger.gz
	SRR13927736_1.fastq.gz	Fastqsanger.gz
	SRR13927736_2.fastq.gz	Fastqsanger.gz
	SRR13927737_1.fastq.gz	Fastqsanger.gz

Items per page:

1 - 5 of 8

Similar Datasets

Single-cell ATAC and RNA sequencing reveal pre-existing and persistent cells associated with prostate cancer relapse [scATAC-seq]

Project description:Prostate cancer is heterogeneous and patients would benefit from methods that stratify those who are likely to respond to systemic therapy. Here, we employ single-cell assays for transposase-accessible chromatin (ATAC) and RNA sequencing in models of early treatment response and resistance to enzalutamide. In doing so, we identify pre-existing and treatment-persistent cell subpopulations that possess regenerative potential when subjected to treatment. We find distinct chromatin landscapes associated with enzalutamide treatment and resistance that are linked to alternative transcriptional programs. Transcriptional profiles characteristic of persistent cells are able to stratify the treatment response of patients. Ultimately, we show that defining changes in chromatin and gene expression in single-cell populations from pre-clinical models can reveal as yet unrecognized molecular predictors of treatment response. This suggests that the application of single-cell methods with high analytical resolution in pre-clinical models may powerfully inform clinical decision-making.

2021-08-17 | GSE168667 | GEO

Single-cell ATAC and RNA sequencing reveal pre-existing and persistent cells associated with prostate cancer relapse

Project description:Single-cell ATAC and RNA sequencing reveal pre-existing and persistent cells associated with prostate cancer relapse

| PRJNA713352 | ENA

Single-cell ATAC and RNA sequencing reveal pre-existing and persistent cells associated with prostate cancer relapse [RNA-seq]

2021-08-17 | GSE169305 | GEO

Single-cell ATAC and RNA sequencing reveal pre-existing and persistent cells associated with prostate cancer relapse [scRNA-seq]

2021-08-17 | GSE168668 | GEO

Single-cell ATAC and RNA sequencing reveal pre-existing and persistent cells associated with prostate cancer relapse [FAIRE-seq]

2021-08-17 | GSE168666 | GEO

Single-cell ATAC and RNA sequencing reveal pre-existing and persistent cells associated with prostate cancer relapse [scRNA-seq]

Project description:Single-cell ATAC and RNA sequencing reveal pre-existing and persistent cells associated with prostate cancer relapse [scRNA-seq]

| PRJNA713356 | ENA

Single-cell ATAC and RNA sequencing reveal pre-existing and persistent cells associated with prostate cancer relapse [RNA-seq]

Project description:Single-cell ATAC and RNA sequencing reveal pre-existing and persistent cells associated with prostate cancer relapse [RNA-seq]

| PRJNA716242 | ENA

Single-cell ATAC and RNA sequencing reveal pre-existing and persistent cells associated with prostate cancer relapse [FAIRE-seq]

Project description:Single-cell ATAC and RNA sequencing reveal pre-existing and persistent cells associated with prostate cancer relapse [FAIRE-seq]

| PRJNA713357 | ENA

Single-cell RNA sequencing reveal pre-existing and persistent subpopulations of cells associated with relapse of prostate cancer [scRNA-seq 2]

Project description:Prostate cancer is heterogeneous and patients would benefit from methods that stratify clinically indolent from more aggressive forms of the disease. We employed single-cell RNA sequencing in models of early treatment response and resistance to enzalutamide. In doing so, we identified pre-existing and treatment-persistent cell subpopulations that possess transcriptional stem-like features and regenerative potential when subjected to treatment. We found distinct chromatin landscapes associated with enzalutamide treatment and resistance that are linked to alternative transcriptional programs. Transcriptional profiles characteristic of persistent stem-like cells were able to stratify the treatment response of patients. Ultimately, we show that defining changes in chromatin and gene expression in single-cell populations from pre-clinical models can reveal hitherto unrecognized molecular predictors of treatment response. This suggests that high analytical resolution of pre-clinical models may powerfully inform clinical decision-making.

2021-08-16 | GSE168733 | GEO

Single-cell RNA sequencing reveal pre-existing and persistent subpopulations of cells associated with relapse of prostate cancer [scRNA-seq 2]

Project description:Single-cell RNA sequencing reveal pre-existing and persistent subpopulations of cells associated with relapse of prostate cancer [scRNA-seq 2]

| PRJNA713791 | ENA

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