Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Gastrointestinal Stromal Tumor Enhancers Support a Transcription Factor Network Predictive of Clinical Outcome

ABSTRACT: Gastrointestinal Stromal Tumor Enhancers Support a Transcription Factor Network Predictive of Clinical Outcome

PROVIDER: PRJNA378612 | ENA |

REPOSITORIES: ENA

ACCESS DATA

Json Xml

Similar Datasets

Gastrointestinal Stromal Tumor Enhancers Support a Transcription Factor Network Predictive of Clinical Outcome

Project description:Activating mutations in the KIT or PDGFRA receptor tyrosine kinases are hallmarks of gastrointestinal stromal tumor (GIST). The biological underpinnings of recurrence following resection or disease progression beyond kinase mutation are poorly understood. Utilizing chromatin immunoprecipitation with sequencing (ChIP-seq) of tumor samples and cell lines, we describe the enhancer landscape of GIST, highlighting genes that reinforce and extend our understanding of these neoplasms. A group of core transcription factors can be distinguished from others unique to localized and metastatic disease. The transcription factor HAND1 emerges in metastatic disease, binds to established GIST-associated enhancers and is required for GIST cell proliferation and KIT gene expression. The pattern of transcription factor expression in primary tumors is predictive of metastasis-free survival in GIST patients. These results provide insight into the enhancer landscape and transcription factor network underlying GIST, and define a new strategy for predicting clinical behavior of this disease.

2018-05-21 | GSE95863 | GEO

Gastrointestinal Stromal Tumor Enhancers Support a Transcription Factor Network Predictive of Clinical Outcome

2018-05-21 | GSE95862 | GEO

Gastrointestinal Stromal Tumor Enhancers Support a Transcription Factor Network Predictive of Clinical Outcome

2018-05-21 | GSE95861 | GEO

Gastrointestinal stromal tumor enhancers support a transcription factor network predictive of clinical outcome.

Project description: Not available

| S-EPMC6016782 | biostudies-literature

Gastrointestinal Stromal Tumor Enhancers Support a Transcription Factor Network Predictive of Clinical Outcome

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

2018-05-21 | GSE95864 | GEO

Homo sapiens

Project description:Gastrointestinal Stromal Tumor Enhancers Support a Transcription Factor Network Predictive of Clinical Outcome

| PRJNA378618 | ENA

Homo sapiens

Project description:Gastrointestinal Stromal Tumor Enhancers Support a Transcription Factor Network Predictive of Clinical Outcome

| PRJNA378616 | ENA

Homo sapiens

Project description:Gastrointestinal Stromal Tumor Enhancers Support a Transcription Factor Network Predictive of Clinical Outcome

| PRJNA378619 | ENA

Quantitative LC-MS study of compounds found predictive of COVID-19 severity and outcome

Project description:<h4><strong>INTRODUCTION: </strong>Since the beginning of the SARS-CoV-2 pandemic in December 2019 multiple metabolomics studies have proposed predictive biomarkers of infection severity and outcome. Whilst some trends have emerged, the findings remain intangible and uninformative when it comes to new patients.</h4><h4><strong>OBJECTIVES: </strong>In this study, we accurately quantitate a subset of compounds in patient serum that were found predictive of severity and outcome.</h4><h4><strong>METHODS: </strong>A targeted LC-MS method was used in 46 control and 95 acute COVID-19 patient samples to quantitate the selected metabolites. These compounds included tryptophan and its degradation products kynurenine and kynurenic acid (reflective of immune response), butyrylcarnitine and its isomer (reflective of energy metabolism) and finally 3’,4’-didehydro-3’-deoxycytidine, a deoxycytidine analogue, (reflective of host viral defence response). We subsequently examine changes in those markers by disease severity and outcome relative to those of control patients’ levels.</h4><h4><strong>RESULTS & CONCLUSION: </strong>Finally, we demonstrate the added value of the kynurenic acid / tryptophan ratio for severity and outcome prediction and highlight the viral detection potential of ddhC.</h4>

2024-04-23 | MTBLS7429 | MetaboLights

Transcription profiling of human gastrointestinal stromal tumour is predictive of rapid response to imatinib mesylate

Project description:Gene expression profiling using oligonucleotide microarrays performed on tumor samples obtained before and after imatinib mesylate (IM) therapy. Rapid responding (to IM) samples were compared to non-responding/stable disease samples as measured by CT scan measurements to identify a gene signature that can predict rapid response to IM. Experiment Overall Design: 54 samples, 29 pre-treatment biopsy samples, 25 post-treatment/post-surgery tumor samples from Gastrointestinal Stromal Tumors

2009-12-02 | E-GEOD-15966 | biostudies-arrayexpress

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

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