Identifying a high-risk cellular signature in the multiple myeloma bone marrow microenvironment_2
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PROVIDER: PRJNA562264 | ENA |
REPOSITORIES: ENA
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Project description:Identifying a high-risk cellular signature in the multiple myeloma bone marrow microenvironment_1
| PRJNA562265 | ENA
Project description:Identifying a high-risk cellular signature in the multiple myeloma bone marrow microenvironment
| PRJNA563125 | ENA
Project description:Identifying a high-risk cellular signature in the multiple myeloma bone marrow microenvironment_3
| PRJNA563129 | ENA
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
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
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 | GSE136337 | GEO
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
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
2011-08-20 | GSE8991 | GEO
Project description:Multiple myeloma is a plasma cell malignancy of the bone marrow. Despite therapeutic advances, multiple myeloma remains incurable and better risk stratification as well as new therapies are therefore highly needed. The proteome of multiple myeloma has not been systematically assessed before and holds the potential to uncover additional insight into disease biology and improved prognostic models. Here, we provide a comprehensive multi-omics analysis including deep tandem mass tags (TMT)-based quantitative global (phospho)proteomics, RNA sequencing and nanopore DNA sequencing of 138 primary patient-derived plasma cell malignancies encompassing treatment-naive multiple myeloma patients treated in clinical trials, plasma cell leukemia, and the premalignancy monoclonal gammopathy of undetermined significance (MGUS), as well as healthy controls. We found that the (phospho)proteome of malignant plasma cells is highly deregulated as compared to healthy plasma cells and is both defined by chromosomal alterations and extensive post-transcriptional regulation. A protein signature was identified that is associated with aggressive disease and more predictive for outcome than cytogenetic-based risk assessment in newly diagnosed multiple myeloma. Integration with functional genetics and single-cell sequencing revealed generally and genetic subtype-specific deregulated proteins and pathways in plasma cell malignancies that include novel potential targets for (immuno)therapies. These findings provide new insights in the biology of multiple myeloma and will be a unique resource for investigating new therapeutic approaches.
2024-07-09 | PXD038437 | Pride
Project description:Multiple myeloma is a plasma cell malignancy of the bone marrow. Despite therapeutic advances, multiple myeloma remains incurable and better risk stratification as well as new therapies are therefore highly needed. The proteome of multiple myeloma has not been systematically assessed before and holds the potential to uncover additional insight into disease biology and improved prognostic models. Here, we provide a comprehensive multi-omics analysis including deep tandem mass tag (TMT)-based quantitative global (phospho)proteomics, RNA sequencing and nanopore DNA sequencing of 138 primary patient-derived plasma cell malignancies encompassing treatment-naive multiple myeloma patients treated in clinical trials, plasma cell leukemia, and the premalignancy monoclonal gammopathy of undetermined significance (MGUS), as well as healthy controls. We found that the (phospho)proteome of malignant plasma cells is highly deregulated as compared to healthy plasma cells and is both defined by chromosomal alterations and extensive post-transcriptional regulation. A protein signature was identified that is associated with aggressive disease and more predictive for outcome than cytogenetic-based risk assessment in newly diagnosed multiple myeloma. Integration with functional genetics and single-cell sequencing revealed generally and genetic subtype-specific deregulated proteins and pathways in plasma cell malignancies that include novel potential targets for (immuno)therapies. These findings provide new insights in the biology of multiple myeloma and will be a unique resource for investigating new therapeutic approaches.
2024-07-09 | PXD043580 | Pride