Project description:The aims of this study were to assess the feasibility of prospective pharmacogenomics research in multicenter international clinical trials of bortezomib in multiple myeloma and to develop predictive classifiers of response and survival with bortezomib. Patients with relapsed myeloma enrolled in phase 2 and phase 3 clinical trials of bortezomib and consented to genomic analyses of pretreatment tumor samples. Bone marrow aspirates were subject to a negative-selection procedure to enrich for tumor cells, and these samples were used for gene expression profiling using DNA microarrays. Data quality and correlations with trial outcomes were assessed by multiple groups. Gene expression in this dataset was consistent with data published from a single-center study of newly diagnosed multiple myeloma. Response and survival classifiers were developed and shown to be significantly associated with outcome via testing on independent data. The survival classifier improved on the risk stratification provided by the International Staging System. Predictive models and biologic correlates of response show some specificity for bortezomib rather than dexamethasone. Informative gene expression data and genomic classifiers that predict clinical outcome can be derived from prospective clinical trials of new anticancer agents. Experiment Overall Design: Purified myeloma samples were collected prior to enrolment in clinical trials of bortezomib (PS-341). Samples were subject to replicate gene expression profiling using the Affymetrix 133A/B microarray. Data was normalized in MAS5.0 and the median of replicates is reported. Data was normalized to a Ttimmed mean of 15o and is NOT log transformed. Various patient parameters are reported as well as response, TTP and survival upon treatment with bortezomib or dexamethasone.

2008-06-17 | E-GEOD-9782 | biostudies-arrayexpress

Multiple Myeloma CoMMpass Study

Project description:The Multiple Myeloma Research Foundation (MMRF) CoMMpass (Relating Clinical Outcomes in MM to Personal Assessment of Genetic Profile) trial (NCT01454297) is a longitudinal observation study of 1000 newly diagnosed myeloma patients receiving various standard approved treatments that aim at collecting tissue samples, genetic information, Quality of Life (QoL) and various disease and clinical outcomes over 10 years.

| phs000748 | dbGaP

Gene expression profiling and correlation with outcome in clinical trials of the proteasome inhibitor bortezomib

Project description:The aims of this study were to assess the feasibility of prospective pharmacogenomics research in multicenter international clinical trials of bortezomib in multiple myeloma and to develop predictive classifiers of response and survival with bortezomib. Patients with relapsed myeloma enrolled in phase 2 and phase 3 clinical trials of bortezomib and consented to genomic analyses of pretreatment tumor samples. Bone marrow aspirates were subject to a negative-selection procedure to enrich for tumor cells, and these samples were used for gene expression profiling using DNA microarrays. Data quality and correlations with trial outcomes were assessed by multiple groups. Gene expression in this dataset was consistent with data published from a single-center study of newly diagnosed multiple myeloma. Response and survival classifiers were developed and shown to be significantly associated with outcome via testing on independent data. The survival classifier improved on the risk stratification provided by the International Staging System. Predictive models and biologic correlates of response show some specificity for bortezomib rather than dexamethasone. Informative gene expression data and genomic classifiers that predict clinical outcome can be derived from prospective clinical trials of new anticancer agents. Keywords: Gene expression profiling; correlation with outcome in clinical trials of the proteasome inhibitor bortezomib

2007-12-06 | GSE9782 | GEO

Proteogenomic landscape of multiple myeloma

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

Proteogenomic landscape of multiple myeloma

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

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_3

2019-08-31 | GSE136398 | GEO