Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Drug resistant changes at the level of single cells

ABSTRACT: Drug resistant changes at the level of single cells

PROVIDER: PRJNA628589 | ENA |

REPOSITORIES: ENA

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
	SRR11523540_1.fastq.gz	Fastqsanger.gz
	SRR11523540_2.fastq.gz	Fastqsanger.gz
	SRR11523541_1.fastq.gz	Fastqsanger.gz
	SRR11523541_2.fastq.gz	Fastqsanger.gz
	SRR11523542_1.fastq.gz	Fastqsanger.gz

Items per page:

1 - 5 of 66

Similar Datasets

GNPS Proteomic Changes of Antimony Resistant Leishmania Growing Under Drug Challenge

Project description:Here, we used shotgun proteomics (LC-MS/MS) to identify changes in the proteome of antimony resistant parasites growing under drug challenge. We used a Leishmania tropica strain that was selected in vitro to resist high levels of trivalent antimony. Two experimental conditions were evaluated: a resistant strain grown without drug challenge (control), and a resistant strain grown under drug challenge (treatment). Three independent biological replicates were used per experimental condition.

2022-06-07 | MSV000089617 | GNPS

Single cell RNA-seq profiles of primary, metastatic, drug-resistant and drug-holiday cells

Project description:We employed Single cell RNA-seq to identify the transcriptome of cisplatin sensitive, resistant and drug-holiday cells from patient-derived OSCC cells isolated from primary and metastatic sites.

2018-11-22 | GSE117872 | GEO

Single cell RNA-seq profiles of primary, metastatic, drug-resistant and drug-holiday cells

Project description:Single cell RNA-seq profiles of primary, metastatic, drug-resistant and drug-holiday cells

| PRJNA483471 | ENA

Drug-resistant acute myeloid leukemia

Project description:Drug-resistant acute myeloid leukemia

| PRJNA828404 | ENA

Pre-determined diversity in resistant fates emerges from homogenous cells after anti-cancer drug treatment (single-cell data)

Project description:Even amongst genetically identical cancer cells, therapy resistance often only emerges from a very small subset of those cells. Much effort has gone into uncovering the molecular differences in rare individual cells in the initial population that may allow certain cells to become therapy resistant; however, comparatively little is known about variability in the resistant outcomes themselves. Here, we develop and apply FateMap, a framework that combines DNA barcoding with single-cell RNA sequencing to reveal the fates of hundreds of thousands of clones exposed to anti-cancer therapies. We show that resistant clones emerging from single-cell-derived cancer cells adopt molecularly, morphologically, and functionally distinct fate types. These different resistant types are largely predetermined by molecular differences between cells before addition of drug and not by extrinsic cell-specific microenvironmental factors. Changes in dose and kind of drug can, however, switch the resistant fate type of an initial cell, even resulting in the generation and elimination of certain fate types. Diversity in resistant fates was observed across several single-cell-derived cancer cell lines and types treated with a variety of drugs. Cell fate diversity as a result of variability in intrinsic cell states may be a generic feature of response to external cues.

2023-06-03 | GSE233766 | GEO

Human BRAF-V600E melanoma cell lines drug sensitive vs drug resistant

Project description:aCGH of human melanoma cell lines comparing parental (drug sensitve) vs isogenic drug resistant-derived subline Two condition experiment: two BRAF-V600E mutant cell lines (drug sensitive - parental baseline) vs two derived sublines after chronic exposure to the MEK inhibitor trametinib (drug resistant) are compared

2014-04-21 | E-GEOD-49430 | biostudies-arrayexpress

TooManyPeaks identifies drug-resistant-specific regulatory elements from single-cell leukemic epigenomes [ATAC-seq]

Project description:Purpose: To characterize epigenomic heterogeneity in GSI-responsive and -resistant T-ALL cells Method: We generated GSI-resistant T-ALL DND41 cells and profiled their epigenome using single-cell RNA sequencing. Result: We report here the presence of resistant-like subpopulation in drug naïve DND41 T-ALL cells. Conclusion: While other popular scRNA-seq clustering algorithms failed, TooManyPeaks, a suite of clustering and visualization algorithm developed in our lab, could identify rare resistant-like DND41 T-ALL cells.

2023-08-07 | GSE155916 | GEO

Identification of differentially expressed miRNAs in drug resistant and drug sensitive breast cancer tissues

Project description:To identify miRNAs involved in drug resistance of human breast cancer, a miRNA microarray was performed on 5 cases of drug resistant tissues and 5 cases of drug sensitive tissues.The expression levels of totally 2019 miRNAs in 5 pairs of matched, drug resistant and drug sensitive tissues were examined by microarray. There were 27 differentially expressed miRNAs between drug resistant and drug sensitive tissues were identified of which there were 11 significantly up-regulated while the other 16 were down-regulated in drug resistant tissues compared to drug sensitive tissues. It was found that miR-489 was one of the most downregulated miRNAs in drug resistant tissues.

2017-08-01 | GSE71142 | GEO

Drug resistant changes at the level of single cells

Project description:This SuperSeries is composed of the SubSeries listed below.

2020-12-19 | GSE149383 | GEO

Mycobacterium tuberculosis clinical isolates in China: extensively drug-resistant tuberculosis vs drug sensitive one

Project description:Transcriptional profiling of mycobacterium tuberculosis clinical isolates in China comparing extensively drug-resistant tuberculosis with drug sensitive one. The same condition experiment. The samples were from the different drug-resistant strains. Only one replicate.

2009-04-04 | E-GEOD-15540 | 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