Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Identifying a high-risk cellular signature in the multiple myeloma bone marrow microenvironment_3

ABSTRACT: Identifying a high-risk cellular signature in the multiple myeloma bone marrow microenvironment_3

PROVIDER: PRJNA563129 | ENA |

REPOSITORIES: ENA

ACCESS DATA

Json Xml

Similar Datasets

Identifying a high-risk cellular signature in the multiple myeloma bone marrow microenvironment_2

Project description:Identifying a high-risk cellular signature in the multiple myeloma bone marrow microenvironment_2

| PRJNA562264 | ENA

Identifying a high-risk cellular signature in the multiple myeloma bone marrow microenvironment_1

Project description:Identifying a high-risk cellular signature in the multiple myeloma bone marrow microenvironment_1

| PRJNA562265 | ENA

Identifying a high-risk cellular signature in the multiple myeloma bone marrow microenvironment

Project description:Identifying a high-risk cellular signature in the multiple myeloma bone marrow microenvironment

| PRJNA563125 | ENA

Identifying a high-risk cellular signature in the multiple myeloma bone marrow microenvironment_1

Project description:The multiple myeloma (MM) tumor microenvironment is thought to influence patient outcomes. To test this, we computationally enumerated relevant cell populations in 436 newly diagnosed MM patients. Unsupervised clustering identified 5 clusters, with patients in Cluster 5 having significantly worse outcomes: 13 fewer months of progression-free survival (P = 0.002) and 8 fewer months of overall survival (P = 0.040). Cell type analysis showed that patients in Cluster 5 had elevated CD8+ T cell and B cell populations, but low granulocyte levels. A granulocyte signature identified an additional 14% of patients with elevated risk but lacking International Staging System stage III or GEP-70 high- risk status

2019-08-31 | GSE136324 | GEO

Identifying a high-risk cellular signature in the multiple myeloma bone marrow microenvironment_2

2019-08-31 | GSE136337 | GEO

Identifying a high-risk cellular signature in the multiple myeloma bone marrow microenvironment_3

2019-08-31 | GSE136398 | GEO

Identifying a high-risk cellular signature in the multiple myeloma bone marrow microenvironment

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

2019-08-31 | GSE136400 | GEO

Identifying metabolic adaptations characteristic of multiple myeloma cells via amino acids concentrations from bone marrow plasma

Project description:Will be assessing the targeted amino acids concentrations of high risk versus low risk smoldering myeloma patients based on peripheral blood plasma and bone marrow plasma.

2017-07-11 | ST000791 | MetabolomicsWorkbench

A Gene Expression-Based Risk Stratification Model for Newly Diagnosed Multiple Myeloma

Project description:We recently defined a gene expression-based signature of high-risk multiple myeloma; this predictive signature was developed with and independently validated for newly diagnosed patients treated with high dose therapy and stem cell rescue. Here we use Phase 3 clinical trial data to show that this signature also predicts short survival in relapsed disease treated with single agent bortezomib or high dose dexamethasone. In addition, a survival signature derived with relapsed myeloma samples identified newly diagnosed patients with short survival. Taken together these data suggest that a similar biology underlies poor outcome in both newly diagnosed and relapsed myeloma and provide strong evidence that the high-risk signature is a powerful tool to identify patients who are candidates for new therapeutic regimens. Keywords: Model validation See above (Series_summary)

2011-08-19 | E-GEOD-8991 | biostudies-arrayexpress

Identifying metabolic adaptations characteristic of multiple myeloma cells via targeted sphingolipids concentrations from bone marrow and peripheral plasma

Project description:Will be assessing the targeted sphingolipids concentrations of high risk versus low risk smoldering myeloma patients based on peripheral blood plasma and bone marrow plasma.

2017-07-11 | ST000790 | MetabolomicsWorkbench

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