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Institute
Myeloma is characterized by extensive inter-patient genomic heterogeneity due to multiple different initiating events. A recent multi-region sequencing study demonstrated spatial differences, with progression events, such as TP53 mutations, frequently being restricted to focal lesions. In this review article, we describe the clinical impact of these two types of tumor heterogeneity. Target mutations are often dominant at one site but absent at other sites, which poses a significant challenge to personalized therapy in myeloma. The same holds true for high-risk subclones, which can be locally restricted, and as such not detectable at the iliac crest, which is the usual sampling site. Imaging can improve current risk classifiers and monitoring of residual disease, but does not allow for deciphering the molecular characteristics of tumor clones. In the era of novel immunotherapies, the clinical impact of heterogeneity certainly needs to be re-defined. Yet, preliminary observations indicate an ongoing impact of spatial heterogeneity on the efficacy of monoclonal antibodies. In conclusion, we recommend combining molecular tests with imaging to improve risk prediction and monitoring of residual disease. Overcoming intra-tumor heterogeneity is the prerequisite for curing myeloma. Novel immunotherapies are promising but research addressing their impact on the spatial clonal architecture is highly warranted.
Patients with newly diagnosed multiple myeloma (NDMM) with high-risk disease are in need of new treatment strategies to improve the outcomes. Multiple clinical, cytogenetic, or gene expression features have been used to identify high-risk patients, each of which has significant weaknesses. Inclusion of molecular features into risk stratification could resolve the current challenges. In a genome-wide analysis of the largest set of molecular and clinical data established to date from NDMM, as part of the Myeloma Genome Project, we have defined DNA drivers of aggressive clinical behavior. Whole-genome and exome data from 1273 NDMM patients identified genetic factors that contribute significantly to progression free survival (PFS) and overall survival (OS) (cumulative R2 = 18.4% and 25.2%, respectively). Integrating DNA drivers and clinical data into a Cox model using 784 patients with ISS, age, PFS, OS, and genomic data, the model has a cumlative R2 of 34.3% for PFS and 46.5% for OS. A high-risk subgroup was defined by recursive partitioning using either a) bi-allelic TP53 inactivation or b) amplification (≥4 copies) of CKS1B (1q21) on the background of International Staging System III, comprising 6.1% of the population (median PFS = 15.4 months; OS = 20.7 months) that was validated in an independent dataset. Double-Hit patients have a dire prognosis despite modern therapies and should be considered for novel therapeutic approaches.