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Single-cell profiling of tumour evolution in multiple myeloma — opportunities for precision medicine

Abstract

Multiple myeloma (MM) is a haematological malignancy of plasma cells characterized by substantial intraclonal genetic heterogeneity. Although therapeutic advances made in the past few years have led to improved outcomes and longer survival, MM remains largely incurable. Over the past decade, genomic analyses of patient samples have demonstrated that MM is not a single disease but rather a spectrum of haematological entities that all share similar clinical symptoms. Moreover, analyses of samples from monoclonal gammopathy of undetermined significance and smouldering MM have also shown the existence of genetic heterogeneity in precursor stages, in some cases remarkably similar to that of MM. This heterogeneity highlights the need for a greater dissection of underlying disease biology, especially the clonal diversity and molecular events underpinning MM at each stage to enable the stratification of individuals with a high risk of progression. Emerging single-cell sequencing technologies present a superlative solution to delineate the complexity of monoclonal gammopathy of undetermined significance, smouldering MM and MM. In this Review, we discuss how genomics has revealed novel insights into clonal evolution patterns of MM and provide examples from single-cell studies that are beginning to unravel the mutational and phenotypic characteristics of individual cells within the bone marrow tumour, immune microenvironment and peripheral blood. We also address future perspectives on clinical application, proposing that multi-omics single-cell profiling can guide early patient diagnosis, risk stratification and treatment strategies.

Key points

  • Multiple myeloma (MM) is a clinically and biologically heterogeneous haematological malignancy characterized by extensive tumour heterogeneity.

  • Bulk genomic studies have revealed the presence of clonal heterogeneity throughout all stages of disease from monoclonal gammopathy of undetermined significance and smouldering MM to MM, providing clonal evolution models defined by clonal stability or branching evolution.

  • Despite the genetic architecture of MM being well characterized, precision medicine is yet to be effective in patients with MM, among whom disease relapse is inevitable owing to the presence and selection of pre-existing resistant clones or their emergence in response to selective pressure during therapy.

  • Emerging single-cell technologies are poised to dissect the clonal complexity of tumour cells and concerted changes in the immune microenvironment to enable the high-resolution mapping of dysregulation occurring between disease stages.

  • Multi-omic single-cell characterization and integration of genomic (DNA), phenotype (RNA and protein) and epigenomic data can provide a holistic picture of ongoing tumour dynamics and improve the molecular stratification of patients with MM.

  • By targeting tumour and immune cells, single-cell technologies and mapping could be applied clinically to provide improved strategies for the diagnosis, prognostication and monitoring of response to treatment and residual disease.

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Fig. 1: Continuum of progression and somatic mutations involved in MM.
Fig. 2: Clonal evolution models in MM progression.
Fig. 3: Single-cell multi-omics approaches to molecular profiling of MM.

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Acknowledgements

The authors acknowledge funding support from the Dr. Miriam and Sheldon G. Adelson Medical Research Foundation (AMRF), Multiple Myeloma Research Foundation (MMRF) and National Institutes of Health (NIH). The work of these authors is also supported by a Stand Up To Cancer Dream Team Research Grant (grant number: SU2C-AACR-DT-28-18). Stand Up To Cancer is a programme of the Entertainment Industry Foundation. Research grants are administered by the American Association for Cancer Research (ACS), the scientific partner of Stand Up To Cancer. Opinions, interpretations, conclusions and recommendations are those of the authors and are not necessarily endorsed by Stand Up To Cancer, the Entertainment Industry Foundation or the ACS. The authors thank A. V. Justis and O. C. Lomas (both at Dana-Farber Cancer Institute) for scientific writing support and review of the manuscript, respectively.

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A.K.D. researched data for this article and wrote the first draft. All the authors contributed substantially to discussions of content and reviewed and edited the manuscript before submission.

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Correspondence to Irene M. Ghobrial.

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A.K.D. and E.D.L. have acted as consultants for and received honoraria from Menarini Silicon Biosystems. G.G. receives research funding from IBM and Pharmacyclics; is an inventor on patent applications related to ABSOLUTE, MSIDetect, MSMutSig, MSMuTect, MutSig, MuTect, POLYSOLVER and TensorQTL; and is a founder, consultant and holds privately held equity in Scorpion Therapeutics. I.M.G. is a consultant for AbbVie, Adaptive, Aptitude, Bristol Myers Squibb, Cellectar, Curio Science, Genentech, GNS, GSK, Janssen, Karyopharm, Medscape, Oncopeptides, Sanofi, and Takeda and has received honoraria from Aptitude. J.-B.A. and R.S.-P. declare no competing interests.

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Dutta, A.K., Alberge, JB., Sklavenitis-Pistofidis, R. et al. Single-cell profiling of tumour evolution in multiple myeloma — opportunities for precision medicine. Nat Rev Clin Oncol 19, 223–236 (2022). https://doi.org/10.1038/s41571-021-00593-y

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