Project description:Multiple myeloma is a multi-stage disease. Based on its laboratory and clinical presentation it can be summarized as MGUS, smoldering myeloma, and multiple myeloma. Previous studies have shown that the expression levels of miRNAs in different stages of the disease are different. This study analyzes the expression levels of miRNAs in healthy individuals and myeloma serum exosomes. We used microarrays to detail the miRNAs expressionin between 12 healthy individuals and 12 multiple myeloma and identified distinct classes of dys-regulated genes.
Project description:Multiple myeloma (MM) is a hematopoietic malignancy.Based on its laboratory and clinical presentation it can be summarized as MGUS, smoldering myeloma, and multiple myeloma. Previous studies have shown that the expression levels of miRNAs in different stages of the disease are different and exosomes are involved in modulating the progression and the metastasis of cancers through miRNAs. This study analyzes the expression levels of miRNAs in healthy individuals and myeloma bone marrow serum exosomes.
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
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)
Project description:In order to identify relevant, molecularly defined subgroups in Multiple Myeloma (MM), gene expression profiling (GEP) was performed on purified CD138+ plasma cells of 320 newly diagnosed myeloma patients included in the Dutch-Belgian/German HOVON-65/ GMMG-HD4 trial using Affymetrix Gene Chip U133 plus 2.0 arrays. Hierarchical clustering identified 10 distinct subgroups. Bone marrow plasma cell samples were obtained from 320 newly diagnosed multiple myeloma patients included in a large multicenter, prospective, randomized phase III trial (HOVON65/GMMG-HD4). Purified myeloma plasma cells samples with a monoclonal plasma cell purity > 80% were used for analysis.
Project description:It has been found that miRNA is related to the diagnosis and prognosis of multiple myeloma. In this project, we We used microarrays to detect the expression of miRNA in bone marrow of newly diagnosed multiple myeloma patients and healthy subjects, screened out differentially expressed miRNAs, and studied its role in multiple myeloma.
Project description:This gene expression set contains data from patients included in the HOVON143 clinical trial. Using this data the relation between circulating tumor cells and gene expression patterns was studied in newly diagnosed multiple myeloma patients.