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

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

PROVIDER: PRJNA562265 | ENA |

REPOSITORIES: ENA

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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

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

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

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

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 | GSE136398 | 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_1

2019-08-31 | GSE136324 | 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

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