Blood cancers

SNVs – the more the nastier?

Wednesday, 13 Mar 2019

Speaking at the Amgen One conference in Melbourne, Senior Postdoctoral Researcher at the South Australian Health and Medical Research Institute (SAHMRI) Dr Duncan Hewett discussed his team’s work on subclonal heterogeneity and progression in multiple myeloma, noting that single nucleotide variant (SNV) load may not be as important as first thought.

Clonal plasma cells have subclonal heterogeneity, but the architecture does not change dramatically over time1

“Advances in technology are enhancing our understanding of the genetics of multiple myeloma,” began Dr Hewett, landing on next-generation (Next-Gen) sequencing of the exome and genome as the latest advancement that is helping to debunk previous dogmas in disease pathogenesis. “Single-cell genotyping has enabled us to look at the current hypotheses and discover that the lines between smouldering multiple myeloma (SMM), monoclonal gammopathy of undetermined significance (MGUS) and multiple myeloma (MM) are even more blurred than we had imagined. There’s heterogeneity not only within clones, but this changes over time, and seemingly differently from patient to patient, and single nucleotide variant (SNV) load may not be as important as first thought.”

Dr Hewett walked the audience through two theoretical models – one where SNVs were acquired sequentially, in a linear fashion and the other where subclonal heterogeneity changes depended on stage of the disease.2 However, looking at subclones in the same patients over time his laboratory and others have discovered that transition to malignancy was not necessarily associated with mutation load and that while SNVs can be common, few are unique to MM when compared with SMM.1,3,4 Instead, transformation from SMM to MM is more likely a result of outgrowth of several clones rather than an increase in genetic variation.

“What we found in our matched samples study was that MM was associated with a decrease in mutational load for a majority of patients. While there were some MM-specific mutations, a majority were subclonal in nature. Through modelling, we were able to confirm that subclonal evolution had already occurred prior to MGUS/SMM sampling and a majority of subclones responsible to MM were already present in patients at the asymptomatic stage,” explained Dr Hewett.

These findings are in line with findings from Bolli N, et al. 2018, which observed no significant increase in genetic complexity associated with disease progression.5This paper goes on to elegantly describe two models they observed in patients– spontaneous evolution, where some clones outgrow others and some become extinct with disease progression, and static progression, where the subclonal architecture is preserved with disease progression. We’ve been able to observe both of these phenomenon in our study,”1 noted Dr Hewett. He explained how these phenomenon are likely driven by the bone microenvironment itself.

Of course, subclonal heterogeneity likely won’t stop there. Where you look will almost certainly impact what you find in a SMM/MGUS/MM patient. Aside from heterogeneity from patient-to-patient, there is also subclonal heterogeneity from site-to-site.6 “Spatial genomic heterogeneity is another phenomenon we need to explore now that we have these advanced technologies available,” suggested Dr Hewett. “We’re really just scratching the surface of our understanding of disease progression and the role of subclones. What specifically in the bone microenvironment is driving clonal selection is the next question we need to look at.”


This article was sponsored by Amgen, which has no control over editorial content. The content is entirely independent and based on published studies and experts’ opinions, the views expressed are not necessarily those of Amgen.


  1. Dutta AK, et al. Leukemia 2019;33:457–468.
  2. Dutta AK, et al. Br J Haematol 2017;178:196–208.
  3. Zhao S, et al. Leukemia 2014;28:1548–1552.
  4. Walker BA, et al. Leukemia 2014;28, 384-390.
  5. Bolli N, et al. Nat Comm 2018;9:3363-3373.
  6. Rasche L, et al. Nat Comm 2017;8:268-278.

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