Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Acquired resistance to combined BET and CDK4/6 inhibition in triple-negative breast cancer [RNA-Seq]

ABSTRACT: Acquired resistance to combined BET and CDK4/6 inhibition in triple-negative breast cancer [RNA-Seq]

PROVIDER: PRJNA545509 | ENA |

REPOSITORIES: ENA

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
	SRR9162830.fastq.gz	Fastqsanger.gz
	SRR9162840.fastq.gz	Fastqsanger.gz
	SRR9162831.fastq.gz	Fastqsanger.gz
	SRR9162841.fastq.gz	Fastqsanger.gz
	SRR9162832.fastq.gz	Fastqsanger.gz

Items per page:

1 - 5 of 18

Similar Datasets

Acquired resistance to combined BET and CDK4/6 inhibition in triple-negative breast cancer [Exome]

Project description:BET inhibitors are promising therapeutic agents for the treatment of triple-negative breast cancer (TNBC), but the rapid emergence of resistance necessitates investigation of combination therapies and their effects on tumor evolution. Here, we show that palbociclib, a CDK4/6 inhibitor, and paclitaxel, a microtubule inhibitor, synergize with the BET inhibitor JQ1 in TNBC lines. High-complexity DNA barcoding and mathematical modeling indicate a high rate of de novo acquired resistance to these drugs relative to pre-existing resistance. We demonstrate that the combination of JQ1 and palbociclib induces cell division errors, which can increase the chance of developing aneuploidy. Characterizing acquired resistance to combination treatment at single cell level shows heterogeneous mechanisms including activation of G1-S and senescence pathways. Our results establish a rationale for further investigation of combined BET and CDK4/6 inhibition in TNBC and suggest novel mechanisms of action for these drugs, and new vulnerabilities in cells after emergence of resistance.

2020-04-08 | GSE131980 | GEO

Acquired resistance to combined BET and CDK4/6 inhibition in triple-negative breast cancer [Barcode]

2020-04-08 | GSE131977 | GEO

Acquired resistance to combined BET and CDK4/6 inhibition in triple-negative breast cancer [scRNA-Seq]

2020-04-08 | GSE131984 | GEO

Acquired resistance to combined BET and CDK4/6 inhibition in triple-negative breast cancer [RNA-Seq]

2020-04-08 | GSE131983 | GEO

Acquired resistance to combined BET and CDK4/6 inhibition in triple-negative breast cancer

Project description:Acquired resistance to combined BET and CDK4/6 inhibition in triple-negative breast cancer

| PRJNA545501 | ENA

Acquired resistance to combined BET and CDK4/6 inhibition in triple-negative breast cancer [Barcode]

Project description:Acquired resistance to combined BET and CDK4/6 inhibition in triple-negative breast cancer [Barcode]

| PRJNA545507 | ENA

Acquired resistance to combined BET and CDK4/6 inhibition in triple-negative breast cancer [Exome]

Project description:Acquired resistance to combined BET and CDK4/6 inhibition in triple-negative breast cancer [Exome]

| PRJNA545506 | ENA

Acquired resistance to combined BET and CDK4/6 inhibition in triple-negative breast cancer [scRNA-Seq]

Project description:Acquired resistance to combined BET and CDK4/6 inhibition in triple-negative breast cancer [scRNA-Seq]

| PRJNA545508 | ENA

Acquired resistance to combined BET and CDK4/6 inhibition in triple-negative breast cancer.

Project description:BET inhibitors are promising therapeutic agents for the treatment of triple-negative breast cancer (TNBC), but the rapid emergence of resistance necessitates investigation of combination therapies and their effects on tumor evolution. Here, we show that palbociclib, a CDK4/6 inhibitor, and paclitaxel, a microtubule inhibitor, synergize with the BET inhibitor JQ1 in TNBC lines. High-complexity DNA barcoding and mathematical modeling indicate a high rate of de novo acquired resistance to these drugs relative to pre-existing resistance. We demonstrate that the combination of JQ1 and palbociclib induces cell division errors, which can increase the chance of developing aneuploidy. Characterizing acquired resistance to combination treatment at a single cell level shows heterogeneous mechanisms including activation of G1-S and senescence pathways. Our results establish a rationale for further investigation of combined BET and CDK4/6 inhibition in TNBC and suggest novel mechanisms of action for these drugs and new vulnerabilities in cells after emergence of resistance.

| S-EPMC7214447 | biostudies-literature

Response and resistance to BET bromodomain inhibitors in triple negative breast cancer [ChIP-Seq]

Project description:Triple negative breast cancer (TNBC) is a heterogeneous and clinically aggressive disease for which there is no targeted therapy. Here we report the preferential and high sensitivity of TNBCs to BET bromodomain inhibitors such as JQ1 manifested by cell cycle arrest in early G1, apoptosis, and induction of markers of luminal epithelial differentiation in vitro and in vivo. The sensitivity of TNBC and other tumor types to BET inhibition establishes a rationale for clinical investigation, and a motivation to understand mechanisms of resistance. After engendering acquired resistance to BET inhibition in previously sensitive TNBCs, we utilized integrative approaches to identify a unique mechanism of epigenomic resistance to this epigenetic therapy. Resistant cells remain dependent on BRD4, confirmed by RNA interference. However, TNBC cells adapt to BET bromodomain inhibition by re-recruitment of unmutated BRD4 to super-enhancers, now in a bromodomain-independent manner. Proteomic studies of resistant TNBC identify hyper-phosphorylation of BRD4 and strong association with MED1. Together, these studies provide a rationale for BET inhibition in TNBC and argue for combination strategies to anticipate clinical drug resistance. ChIP-seq in parental and JQ1 resistant triple negative breast cancer (TNBC) in response to DMSO or JQ1 treatment

2016-01-07 | E-GEOD-63581 | 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