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

52Citations
Citations of this article
48Readers
Mendeley users who have this article in their library.
Get full text

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.

Cite

CITATION STYLE

APA

Maura, F., Bolli, N., Rustad, E. H., Hultcrantz, M., Munshi, N., & Landgren, O. (2020, March 1). Moving from Cancer Burden to Cancer Genomics for Smoldering Myeloma: A Review. JAMA Oncology. American Medical Association. https://doi.org/10.1001/jamaoncol.2019.4659

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free