The possible role of burden of therapy on the risk of myeloma extramedullary spread.

Extramedullary relapse (EMR) represents a poor prognostic marker in the course of multiple myeloma (MM). We reviewed data from 329 patients, diagnosed between 2000 and 2010, without extramedullary disease at onset to explore possible risk factors for EMR. The median overall survival of our study cohort was 6.4 years. The risk of EMR was 28 % with a median time from diagnosis to first EMR of 2.2 years (0.2-9.1 years). Patients with soft tissue masses located in extra-osseous organs (EMR-S) showed the worst outcome, compared to those with tumor masses arising from adjacent bone (EMR-B) (median OS 1.6 vs 2.4 years, p = 0.006). In addition, patients with EMR-S showed a significant trend for further development of extramedullary masses in a very short time (3.7 vs 5.7 months for EMR-B, p = 0.043). Multivariate analysis failed to identify any clinically presenting features predictive for EMR. The occurrence of EMR was higher in patients with more complex treatment history, defined on the basis of longer treatment duration (≥6 vs <6 months) and on elevated number of treatment lines administered (>2 vs ≤2 lines) (HR = 4.5, p < 0.001 and HR = 9.0, p < 0.001, respectively, when one or both factors are present).In conclusion, increasing burden of treatment might be a possible risk factor for EMR. MM patients with multiple relapses should be comprehensively investigated including, when possible, a whole-body-targeted radiologic technique to accurately detect EMR. Treatment choice should take into account the very poor outcome for patients with soft tissue involvement.

A DNA target-enrichment approach to detect mutations, copy number changes and immunoglobulin translocations in multiple myeloma.

Genomic lesions are not investigated during routine diagnostic workup for multiple myeloma (MM). Cytogenetic studies are performed to assess prognosis but with limited impact on therapeutic decisions. Recently, several recurrently mutated genes have been described, but their clinical value remains to be defined. Therefore, clinical-grade strategies to investigate the genomic landscape of myeloma samples are needed to integrate new and old prognostic markers. We developed a target-enrichment strategy followed by next-generation sequencing (NGS) to streamline simultaneous analysis of gene mutations, copy number changes and immunoglobulin heavy chain (IGH) translocations in MM in a high-throughput manner, and validated it in a panel of cell lines. We identified 548 likely oncogenic mutations in 182 genes. By integrating published data sets of NGS in MM, we retrieved a list of genes with significant relevance to myeloma and found that the mutational spectrum of primary samples and MM cell lines is partially overlapping. Gains and losses of chromosomes, chromosomal segments and gene loci were identified with accuracy comparable to conventional arrays, allowing identification of lesions with known prognostic significance. Furthermore, we identified IGH translocations with high positive and negative predictive value. Our approach could allow the identification of novel biomarkers with clinical relevance in myeloma.