Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Dissecting Super-enhancer driven Transcriptional Dependencies Reveals Novel Oncogenes and Therapeutic Strategies of Group 3 Subtype Medulloblastoma

ABSTRACT: Dissecting Super-enhancer driven Transcriptional Dependencies Reveals Novel Oncogenes and Therapeutic Strategies of Group 3 Subtype Medulloblastoma

PROVIDER: PRJNA767390 | ENA |

REPOSITORIES: ENA

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
	SRR16119411_1.fastq.gz	Fastqsanger.gz
	SRR16119411_2.fastq.gz	Fastqsanger.gz
	SRR16119412_1.fastq.gz	Fastqsanger.gz
	SRR16119412_2.fastq.gz	Fastqsanger.gz
	SRR16119415_1.fastq.gz	Fastqsanger.gz

Items per page:

1 - 5 of 58

Similar Datasets

Dissecting Super-enhancer driven Transcriptional Dependencies Reveals Novel Oncogenes and Therapeutic Strategies of Group 3 Subtype Medulloblastoma [RNA-seq]

Project description:Medulloblastoma (MB) is the most common malignant pediatric brain tumor and group 3 subtype (G3-MB) exhibits the worst prognosis. Dissecting super-enhancer (SE) driven transcriptional dependencies of cancer has been shown to facilitate identifying novel oncogenic mechanisms and therapeutic targets or strategies. In this study, our integrative SE analyses of primary tissues and patient-derived tumor cell lines of G3-MB revealed their partially conserved SE-associated transcripts were enriched of subtype-specific tumor-dependent genes and MB patients harboring enrichment of those transcripts exhibited worse prognosis. Fourteen such conserved SE-associated genes were identified to be members of SE-driven core transcriptional regulatory network of G3-MB, including three well-recognized master TFs and eleven newly identified effector oncogenes. ARL4D, one of the effector oncogenes, was further demonstrated to exert its oncogenic role via maintaining cell-cycle progression and stemness of G3-MB cells. Moreover, BET inhibition with CDK7 inhibition or proteasome inhibition, two combinatory strategies of targeting SE complex components (BRD4, CDK7) or SE-associated effector oncogene (PSMB5), were shown to exhibit synergistic therapeutic effects against G3-MB. Taken together, our study verifies the oncogenic role and therapeutic potential of SE-driven transcriptional dependencies of G3-MB, resulting in better understanding of its tumor biology and identification of novel SE-associated therapeutic targets or strategies.

2021-10-04 | GSE185024 | GEO

Dissecting Super-enhancer driven Transcriptional Dependencies Reveals Novel Oncogenes and Therapeutic Strategies of Group 3 Subtype Medulloblastoma [ChIP-seq]

2021-10-04 | GSE185003 | GEO

Dissecting Super-enhancer driven Transcriptional Dependencies Reveals Novel Oncogenes and Therapeutic Strategies of Group 3 Subtype Medulloblastoma [ChIP-seq]

Project description:Dissecting Super-enhancer driven Transcriptional Dependencies Reveals Novel Oncogenes and Therapeutic Strategies of Group 3 Subtype Medulloblastoma [ChIP-seq]

| PRJNA767359 | ENA

Dissecting Super-enhancer driven Transcriptional Dependencies Reveals Novel Oncogenes and Therapeutic Strategies of Group 3 Subtype Medulloblastoma [RNA-seq]

Project description:Dissecting Super-enhancer driven Transcriptional Dependencies Reveals Novel Oncogenes and Therapeutic Strategies of Group 3 Subtype Medulloblastoma [RNA-seq]

| PRJNA767392 | ENA

Dissecting Super-enhancer driven Transcriptional Dependencies Reveals Novel Oncogenes and Therapeutic Strategies of Group 3 Subtype Medulloblastoma

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

2021-10-04 | GSE185025 | GEO

KRASG12C inhibition produces a driver-limited state revealing collateral dependencies

Project description:Inhibitors targeting KRASG12C are a promising new class of oncogene-specific therapeutics for the treatment of tumors driven by KRASG12C mutations. These molecules react with the mutant cysteine residue by binding covalently to the switch-II pocket present only in the inactive-GDP state of KRASG12C, sparing the wild type protein. We systematically probe genetic interactions with direct KRASG12C inhibition in cellular models of KRASG12C mutant lung and pancreatic cancer using a genome-scale CRISPR interference (CRISPRi) functional genomics platform. Our data reveal that repression of genes selectively essential in an oncogenic driverlimited cell state, which we term collateral dependencies (CDs), enhances cellular susceptibility to direct KRASG12C inhibition. We nominate two classes of combination therapies targeting CDs that increase KRASG12C target engagement or block residual survival pathways. We demonstrate in vitro and in vivo that both classes enhance response to anti-KRASG12C therapy and propose a new framework for assessing genetic dependencies with driver oncogenes.

2020-03-23 | PXD013075 | Pride

Enhancer hijacking activates GFI1 family oncogenes in medulloblastoma.

Project description:Medulloblastoma is a highly malignant paediatric brain tumour currently treated with a combination of surgery, radiation and chemotherapy, posing a considerable burden of toxicity to the developing child. Genomics has illuminated the extensive intertumoral heterogeneity of medulloblastoma, identifying four distinct molecular subgroups. Group 3 and group 4 subgroup medulloblastomas account for most paediatric cases; yet, oncogenic drivers for these subtypes remain largely unidentified. Here we describe a series of prevalent, highly disparate genomic structural variants, restricted to groups 3 and 4, resulting in specific and mutually exclusive activation of the growth factor independent 1 family proto-oncogenes, GFI1 and GFI1B. Somatic structural variants juxtapose GFI1 or GFI1B coding sequences proximal to active enhancer elements, including super-enhancers, instigating oncogenic activity. Our results, supported by evidence from mouse models, identify GFI1 and GFI1B as prominent medulloblastoma oncogenes and implicate 'enhancer hijacking' as an efficient mechanism driving oncogene activation in a childhood cancer.

| S-EPMC4201514 | biostudies-literature

Dissecting the genomic complexity underlying medulloblastoma.

Project description:Medulloblastoma is an aggressively growing tumour, arising in the cerebellum or medulla/brain stem. It is the most common malignant brain tumour in children, and shows tremendous biological and clinical heterogeneity. Despite recent treatment advances, approximately 40% of children experience tumour recurrence, and 30% will die from their disease. Those who survive often have a significantly reduced quality of life. Four tumour subgroups with distinct clinical, biological and genetic profiles are currently identified. WNT tumours, showing activated wingless pathway signalling, carry a favourable prognosis under current treatment regimens. SHH tumours show hedgehog pathway activation, and have an intermediate prognosis. Group 3 and 4 tumours are molecularly less well characterized, and also present the greatest clinical challenges. The full repertoire of genetic events driving this distinction, however, remains unclear. Here we describe an integrative deep-sequencing analysis of 125 tumour-normal pairs, conducted as part of the International Cancer Genome Consortium (ICGC) PedBrain Tumor Project. Tetraploidy was identified as a frequent early event in Group 3 and 4 tumours, and a positive correlation between patient age and mutation rate was observed. Several recurrent mutations were identified, both in known medulloblastoma-related genes (CTNNB1, PTCH1, MLL2, SMARCA4) and in genes not previously linked to this tumour (DDX3X, CTDNEP1, KDM6A, TBR1), often in subgroup-specific patterns. RNA sequencing confirmed these alterations, and revealed the expression of what are, to our knowledge, the first medulloblastoma fusion genes identified. Chromatin modifiers were frequently altered across all subgroups. These findings enhance our understanding of the genomic complexity and heterogeneity underlying medulloblastoma, and provide several potential targets for new therapeutics, especially for Group 3 and 4 patients.

| S-EPMC3662966 | biostudies-literature

KRASG12C inhibition produces a driver-limited state revealing collateral dependencies

Project description:Inhibitors targeting KRASG12C, a mutant form of the guanosine triphosphatase (GTPase) KRAS, are a promising new class of oncogene-specific therapeutics for the treatment of tumors driven by the mutant protein. These molecules react with the mutant cysteine residue by binding covalently to the switch-II pocket (S-IIP) that is present only in the inactive guanosine diphosphate (GDP)-bound state of KRASG12C, sparing the wild-type protein. We used a genome-scale CRISPR interference (CRISPRi) functional genomics platform to systematically identify genetic interactions with the KRASG12C inhibitor in cellular models of KRASG12C mutant lung and pancreatic cancer. Our data revealed genes that were selectively essential in this oncogenic driver-limited cell state, meaning their loss enhanced cellular susceptibility to direct KRASG12C inhibition. We termed such genes “collateral dependencies” (CDs), and identified two classes of combination therapies targeting these CDs that increased KRASG12C target engagement or blocked residual survival pathways in cells and in vivo. From our findings, we also propose a new framework for assessing genetic dependencies with driver oncogenes.

2019-05-03 | GSE130616 | GEO

Dissecting the regulatory strategies of NFkB RelA target genes in the inflammatory response reveals differential transactivation logics

Project description:Dissecting the regulatory strategies of NFkB RelA target genes in the inflammatory response reveals differential transactivation logics

| PRJNA549287 | 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