Project description:This gene expression set contains data from 180 patients included in the HOVON-87/NMSG-18 clinical trial. Using this data the SKY92 classifier was validated in the elderly newly diagnosed multiple myeloma patients (median age = 72). Additional to its proven value in younger patients, the MMprofiler?s SKY92 classifier was found to be a robust marker of high risk patients in the elderly MM population.
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.
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:This gene expression set contains data from patients included in the HOVON95 clinical trial. Using this data the relation between a signature identifying patients with aggressive biology and clinical parameters was studied in newly diagnosed multiple myeloma patients. This dataset was used to identify the relationship between a signature for aggressive disease and clinical parameters.
Project description:This gene expression set contains data from patients included in the HOVON131 clinical trial. Using this data the relation between circulating tumor cells and gene expression patterns was studied in newly diagnosed multiple myeloma patients. Circulating tumor cells are a known prognostic factor in multiple myeloma. However, the causes of high circulating tumor cells have been insufficiently characterised. This study aimed to identify factors involved in high circulating tumor cell count, using a model to correct for important contributing factors to this phenotype, which is closely associated with aggressive disease.
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)
