Moving From Cancer Burden to Cancer Genomics for Smoldering Myeloma: A Review

Abstract

Importance: All patients who develop multiple myeloma have a preceding asymptomatic expansion of clonal plasma cells, clinically recognized as monoclonal gammopathy of undetermined significance or smoldering multiple myeloma (SMM). During the past decade, significant progress has been made in the classification and risk stratification of SMM.

Observations: This review summarizes current clinical challenges and discusses available models for risk stratification in the context of SMM. Owing to several novel, more effective, and less toxic drugs, these aspects are becoming increasingly important to identify patients eligible for early treatment. However, all proposed criteria were built around indirect markers of disease burden and therefore are generally able to identify a fraction of patients with SMM in whom transformation to multiple myeloma and genomic subclonal diversification are already happening. In contrast, next-generation sequencing approaches have the potential to identify myeloma precursor disease that will progress even before the major clonal expansion and progression, providing a potential base for more effective treatment and better precision regarding the optimal timing of treatment initiation.

Conclusions and relevance: Owing to modern technologies, in the near future, prognostic models derived from genomic signatures independent of the disease burden will allow better identification of the optimal timing to treat a plasma cell clonal disorder at the very early stages, when the chances of eradication are higher.

Figure 1.

Clinical outcome of MM precursos. A) Three evolution trajectories for MGUS/SMM progression (adapted from Kyle et al NEJM 2007), potentially reflecting three different biological and genomic profiles. The first trajectories (1) reflect an ongoing transformation/progression. The second (2) reflect patients and clones with high predisposition to acquire new drivers and progress over the time. The third (3) is characterized by low predisposition to acquire new drivers and progress over the time, with a clinical outcome similar to MGUS (4). B) C) Risk of SMM/MGUS progression according to either Mayo or PETHEMA prognostic model. D) Comparison between Mayo and PETHEMA risk models for the identification of patients with high-risk SMM. Adapted from Cherry et al.

Figure 2.

MM precursor cytogenetic. The prevalence of the main cytogenetic aberration evaluated by either FISH or SNP array combining together different published cohort of MGUS, SMM and newly diagnosed MMs.^–

Figure 3.

MM precursors genomic landscape. A-B) Heatmap showing the prevalence of recurrent MM mutations among MGUS/SMM/MMS according to the 4 main next generation sequencing studies and among newly diagnosed MM enrolled within the COMMPASS trial.^,– The CoMMpass data were generated as part of the Multiple Myeloma Research Foundation Personalized Medicine Initiatives (https://research.themmrf.org and www.themmrf.org). C) Example of SMM whole genome landscape. All main genomic events are reported in this genome plot: mutations (external circle), indels (middle circle; dark green and brown lines represent insertion and deletion respectively), copy number variants (red = deletions, green = gain) and rearrangements (blue = inversion, red = deletions, green = ITD, black = translocation). This patients was a non-high risk SMM and progressed after 42 months.

Figure 4.

The rational of early treatment in SMM/MGUS patients. MM pathogenesis is characterized by a typical Darwinian evolution model, characterized by the accumulation over the time of different drivers along preferred evolutionary trajectories. When we treat MM (A), most of our patients achieve a good response and durable remission. However, a significant fraction still progresses, generally after a clonal/subclonal competition and selection induced by our treatment. This clonal heterogeneity and genomic complexity represent one of the main reasons why it is so hard to completely eradicate this cancer. B) A significant fraction of high risk SMM already have the key drivers and have already expanded their clonal and subclonal architecture, reducing our chance to eradicate the disease. C) Conversely, at the very early stage of MGUS/SMM clonal expansion, the genomic and clonal complexity is likely lower, potentially increasing the pre-malignant clone eradication chances.