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Metabolomics,Unknown,Transcriptomics,Genomics,Proteomics

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Genome-wide profiling of tumor cells in multiple myeloma

ABSTRACT: In multiple myeloma (MM), endothelial progenitor cells (EPCs) regulate tumor angiogenesis and disease progression. They share a common bone marrow microenvironment with myeloma tumor cells. CD138+ tumor plasma cells from 12 newly diagnosed patients with advanced MM were examined for genomic instability by RNA microarrays to assess changes in gene expression. Tumor cells were derived from single-cell suspensions of bone marrow (BM) aspirates from newly diagnosed MM patients, and RNA was extracted for microarray hybridization.

ORGANISM(S): Homo sapiens

SUBMITTER: Olcay Batuman

PROVIDER: E-GEOD-28327 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Genome-wide profiling of endothelial progenitor cells in multiple myeloma

Project description:In multiple myeloma (MM), endothelial progenitor cells (EPCs) regulate tumor angiogenesis and disease progression. EPCs from 20 newly diagnosed patients with advanced MM were examined for genomic instability by RNA microarrays to assess changes in gene expression. EPCs were derived from single-cell suspensions of bone marrow (BM) aspirates from newly diagnosed MM patients, and RNA was extracted for microarray hybridization.

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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)

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