Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Transcriptional heterogeneity overcomes super-enhancer disrupting drug combinations in multiple myeloma [RNA-seq]

ABSTRACT: Transcriptional heterogeneity overcomes super-enhancer disrupting drug combinations in multiple myeloma [RNA-seq]

PROVIDER: PRJNA1020850 | ENA |

REPOSITORIES: ENA

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
	SRR26172363_1.fastq.gz	Fastqsanger.gz
	SRR26172363_2.fastq.gz	Fastqsanger.gz
	SRR26172364_1.fastq.gz	Fastqsanger.gz
	SRR26172364_2.fastq.gz	Fastqsanger.gz
	SRR26172365_1.fastq.gz	Fastqsanger.gz

Items per page:

1 - 5 of 64

Similar Datasets

Transcriptional heterogeneity overcomes super-enhancer disrupting drug combinations in multiple myeloma

Project description:Transcriptional heterogeneity overcomes super-enhancer disrupting drug combinations in multiple myeloma

| PRJNA1020864 | ENA

Transcriptional heterogeneity overcomes super-enhancer disrupting drug combinations in multiple myeloma [ATAC-seq]

Project description:Transcriptional heterogeneity overcomes super-enhancer disrupting drug combinations in multiple myeloma [ATAC-seq]

| PRJNA1020836 | ENA

Transcriptional heterogeneity overcomes super-enhancer disrupting drug combinations in multiple myeloma [ChIP-seq]

Project description:Transcriptional heterogeneity overcomes super-enhancer disrupting drug combinations in multiple myeloma [ChIP-seq]

| PRJNA1020862 | ENA

Transcriptional heterogeneity overcomes super-enhancer disrupting drug combinations in multiple myeloma [ChIP-seq]

Project description:Multiple myeloma (MM) is a malignancy that is often driven by MYC and that is sustained by IRF4, which are upregulated by super-enhancers. IKZF1 and IKZF3 bind to super-enhancers and can be degraded using immunomodulatory imide drugs (IMiDs). Successful IMiD responses downregulate MYC and IRF4; however, this fails in IMiD-resistant cells. MYC and IRF4 downregulation can also be achieved in IMiD-resistant tumors using inhibitors of BET and EP300 transcriptional coactivator proteins; however, in vivo these drugs have a narrow therapeutic window. By combining IMiDs with EP300 inhibition, we demonstrate greater downregulation of MYC and IRF4, synergistic killing of myeloma in vitro and in vivo, and an increased therapeutic window. Interestingly, this potent combination failed where MYC and IRF4 expression was maintained by high levels of the AP-1 factor BATF. Our results identify an effective drug combination and a previously unrecognized mechanism of IMiD resistance.

2023-09-25 | GSE244002 | GEO

Transcriptional heterogeneity overcomes super-enhancer disrupting drug combinations in multiple myeloma [RNA-seq]

2023-09-25 | GSE243990 | GEO

Transcriptional heterogeneity overcomes super-enhancer disrupting drug combinations in multiple myeloma [ATAC-seq]

2023-09-25 | GSE243978 | GEO

Transcriptional heterogeneity overcomes super-enhancer disrupting drug combinations in multiple myeloma

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

2023-09-25 | GSE244003 | GEO

Targeting DNA2 Overcomes Metabolic Reprogramming in Multiple Myeloma

Project description:Targeting DNA2 Overcomes Metabolic Reprogramming in Multiple Myeloma

| PRJNA807285 | ENA

SUMOylation inhibition overcomes dexamethasone resistance in multiple myeloma

Project description:SUMOylation inhibition overcomes dexamethasone resistance in multiple myeloma

| PRJNA687056 | ENA

Biomarker discovery and subtype classification within Multiple Myeloma by Super-SILAC

Project description:Multiple Myeloma (MM) is the second most prevalent blood cancer (10%) after non-Hodgkin's lymphoma and represents approximately 1% of all cancers and 2% of all cancer deaths. MM is a complex disease characterized by numerous genetic alterations and recent mRNA profiling studies have attempted to subclassify the disease to build pathogenetic and prognostic models Correct classification of cancer patients into subtypes is a prerequisite for acute diagnosis and effective treatment. Here we use high accuracy, quantitative proteomics to segregate cancer subtypes directly at the level of expressed proteins. Multiple myeloma is a heterogeneous disease in its initial clinical features as well as its outcome. We investigated two subtypes of Multiple Myeloma: multiple myeloma associated with t(4;14) chromosomal translocation as well as t(4;14)-negative MM subtype. The t(4;14) translocation, found in 15% of multiple myeloma cases, indicates a poor prognosis. Super-SILAC mix was combined of cell lysates from 8 diverse cell lines labelled with heavy amino acids (Lys8 and Arg10). The Super-SILAC library is mixed with samples (lysates), and quantitative mass spectrometric analysis is performed using a setup consisting of LC and on a linear ion trap Orbitrap mass spectrometer with high mass accuracy at the MS and MS/MS levels. This way we have analysed 20 patient samples from present MM. Shotgun proteomic analysis yielded a proteome of more than 5300 quantified proteins overall (3000 on an average per individual sample). High accuracy of quantification allowed robust separation of subtypes by hierarchical clustering on the protein level.

2024-07-15 | PXD003138 | Pride

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