Whole-genome sequencing reveals progressive versus stable myeloma precursor conditions as two distinct entities
Open accessAbstract
Multiple myeloma (MM) is consistently preceded by precursor conditions recognized clinically as monoclonal gammopathy of undetermined significance (MGUS) or smoldering myeloma (SMM). We interrogate the whole genome sequence (WGS) profile of 18 MGUS and compare them with those from 14 SMMs and 80 MMs. We show that cases with a non-progressing, clinically stable myeloma precursor condition (n = 15) are characterized by later initiation in the patient’s life and by the absence of myeloma defining genomic events including: chromothripsis, templated insertions, mutations in driver genes, aneuploidy, and canonical APOBEC mutational activity. This data provides evidence that WGS can be used to recognize two biologically and clinically distinct myeloma precursor entities that are either progressive or stable.
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Neoplastic transformation occurs early in time.
“suggesting that the neoplastic transformation occurs early in time.9,11,79,80,85”
From Evolution of Multiple Myeloma from a Genomic Perspective (2026) · cites this paper as [11]
The Results section (‘Time lag between initiation and sample collection’; page not supplied) estimates early cancer-initiating multi-gain events in progressive myeloma precursors and myeloma, at median patient ages of 28 and 20.5 years. It does not establish that neoplastic transformation itself occurs early in all precursor conditions: the measured event occurred later in stable precursors, at a median age of 53.5 years. (LLM, conf=0.83)
Experimental — accuracy not yet measuredThe shorter time lag in stable MGUS/SMM suggests a later development.
“stable MGUS/SMM showed a much shorter time lag between initiation and diagnosis (~10-20 years), suggesting a later development. 9,11”
From Evolution of Multiple Myeloma from a Genomic Perspective (2026) · cites this paper as [11]
The Results section (‘Time lag between initiation and sample collection’; page unavailable) reports that early multi-gain events occurred later in stable precursors and concludes that stable disease is acquired later in life. It does not give the cited ~10–20-year interval between initiation and diagnosis; its timing comparison is with sample collection, not diagnosis. (LLM, conf=0.84)
Experimental — accuracy not yet measuredStable MGUS/SMM show a much shorter time lag between initiation and diagnosis (~10-20 years).
“stable MGUS/SMM showed a much shorter time lag between initiation and diagnosis (~10-20 years), suggesting a later development. 9,11”
From Evolution of Multiple Myeloma from a Genomic Perspective (2026) · cites this paper as [11]
The Results section, “Time lag between initiation and sample collection” (page unavailable), reports that initiating multi-gain events occurred later in stable precursors than in progressive precursors, while ages at sampling were not significantly different. This supports a shorter lag and later development, but our copy does not state a 10–20-year lag or equate sample collection with diagnosis. (LLM, conf=0.85)
Experimental — accuracy not yet measuredRAS mutations, MYC translocations, APOBEC mutagenesis, and patterns of genomic complexity are the most commonly reported alterations in progressing multiple myeloma.
“Among these, RAS mutations, MYC translocations, APOBEC mutagenesis, and patterns of genomic complexity are the most commonly reported.8,9,11,69,76-83,84”
From Evolution of Multiple Myeloma from a Genomic Perspective (2026) · cites this paper as [11]
The Results sections report frequent APOBEC activity in progressive myeloma precursors and multiple myeloma, MYC/PVT1 structural variants in progressive cases, and greater structural-variant complexity than in stable precursors (pages unavailable). The driver-gene Results discuss MAPK-pathway mutations but do not establish that RAS mutations specifically, or this four-item list, are the most commonly reported alterations. (LLM, conf=0.84)
Experimental — accuracy not yet measuredThe existence of three distinct groups is supported by the most recent temporal models and estimates developed using FISH and DNA sequencing on large sample sets.
“The existence of these three distinct groups is supported by the most recent temporal models and estimates developed using FISH and DNA sequencing on large sample sets.9,11,15,79,84”
From Evolution of Multiple Myeloma from a Genomic Perspective (2026) · cites this paper as [11]
The Results, “Time lag between initiation and sample collection” (page not provided), compare molecular timing across stable precursors, progressive precursors, and multiple myeloma, finding that stable cases differ from the other two. The paper does not establish all three as distinct biological groups: it describes progressive precursors as genomically similar to myeloma. Its timing analysis uses DNA sequencing, but the cited passages do not show a FISH-based temporal model or a large timing sample. (LLM, conf=0.84)
Experimental — accuracy not yet measured
High-risk features are underrepresented among high-risk smoldering multiple myeloma (SMM) compared with newly diagnosed multiple myeloma (MM).
“Specifically, it is peculiar that these high-risk features are underrepresented among high-risk SMM compared to newly diagnosed MM.9,11,69,76-79”
From Evolution of Multiple Myeloma from a Genomic Perspective (2026) · cites this paper as [11]
The Introduction (page not available) reports that driver-gene mutations and structural events are less frequent in myeloma precursor conditions than in MM. But the Results state that only one of the 14 SMM patients was classified as high-risk. The paper therefore does not establish the claimed comparison specifically between high-risk SMM and newly diagnosed MM. (LLM, conf=0.83)
Experimental — accuracy not yet measuredAll cases of multiple myeloma are preceded by precursor conditions such as smoldering multiple myeloma and monoclonal gammopathy of undetermined significance, often decades before diagnosis.
“MM is well-described to be universally preceded by precursor states, often decades before it is even diagnosed.”
From Evolution of Multiple Myeloma from a Genomic Perspective (2026) · cites this paper as [11]
Patterns of genomic complexity and neoplastic transformation can already be observed in some MGUS and low-risk SMM cases several years before progression.
“Interestingly, these patterns of genomic complexity and neoplastic transformation can already be observed in some MGUS and low-risk SMM cases several years before progression, suggesting that the neoplastic transformation occurs early in time.9,11,79,80,85”
From Evolution of Multiple Myeloma from a Genomic Perspective (2026) · cites this paper as [11]
In contrast to progressive SMM, MM genomic defining events are usually not seen in stable and indolent MGUS/SMM.
“In contrast to progressive SMM, these MM genomic defining events are usually not seen in stable and indolent MGUS/SMM.9,11”
From Evolution of Multiple Myeloma from a Genomic Perspective (2026) · cites this paper as [11]
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Cites
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Dutta, A. K., Alberge, J.-B., Lightbody, E. D., Boehner, C. J., Dunford, A., Sklavenitis-Pistofidis, R., Mouhieddine, T. H., Cowan, A. N., Su, N. K., Horowitz, E. M., et al. (2023) · Cancer Discovery · doi:10.1158/2159-8290.cd-22-0482 · Cited by 41 · see citing works
Temporal genomic dynamics shape clinical trajectory in multiple myeloma
Maura, F., Kaddoura, M., Poos, A. M., Baughn, L. B., Ziccheddu, B., Bärtsch, M.-A., Cirrincione, A., Maclachlan, K., Chojnacka, M., Diamond, B., et al. (2025) · Nature Genetics · doi:10.1038/s41588-025-02292-1 · Cited by 14 · see citing works
Self-citationMedina-Herrera, A., Vazquez, I., Cuenca, I., Rosa-Rosa, J. M., Ariceta, B., Jimenez, C., Fernandez-Mercado, M., Larrayoz, M. J., Gutierrez, N. C., Fernandez-Guijarro, M., et al. (2024) · Blood Cancer Journal · doi:10.1038/s41408-024-01053-3 · Cited by 11 · see citing works
Evolution of Multiple Myeloma from a Genomic Perspective
Maura, F., Samur, M., & Munshi, N. (2026) · Blood · doi:10.1182/blood.2024026313 · Cited by 8 · see citing works
Self-citation
- Authors
- Oben, B., Froyen, G., Maclachlan, K. H., Leongamornlert, D., Abascal, F., Zheng-Lin, B., Yellapantula, V., Derkach, A., Geerdens, E., Diamond, B. T., Arijs, I., Maes, B., Vanhees, K., Hultcrantz, M., Manasanch, E. E., Kazandjian, D., Lesokhin, A., Dogan, A., Zhang, Y., Mikulasova, A., Walker, B., Morgan, G., Campbell, P. J., Landgren, O., Rummens, J.-L., Bolli, N., & Maura, F.
- Affiliations
- Jessa Hospital (BE)
- Memorial Sloan Kettering Cancer Center (US)
- Wellcome Sanger Institute (GB)
- VIB-KU Leuven Center for Cancer Biology (BE)
- The University of Texas MD Anderson Cancer Center (US)
- National Institutes of Health (US)
- Indiana University School of Medicine (US)
- NYU Langone’s Laura and Isaac Perlmutter Cancer Center (US)
- University of Miami (US)
- University of Milan (IT)
- Corresponding author
- Landgren, Ola
- Maura, Francesco
- ORCID
- Oben, Bénedith
- Froyen, Guy
- Maclachlan, Kylee H.
- Leongamornlert, Daniel
- Abascal, Federico
- Zheng-Lin, Binbin
- Yellapantula, Venkata
- Derkach, Andriy
- Diamond, Benjamin T.
- Arijs, Ingrid
- Maes, Brigitte
- Vanhees, Kimberly
- Hultcrantz, Malin
- Manasanch, Elisabet E.
- Kazandjian, Dickran
- Lesokhin, Alexander
- Dogan, Ahmet
- Zhang, Yanming
- Walker, Brian
- Morgan, Gareth
- Campbell, Peter J.
- Landgren, Ola
- Bolli, Niccolò
- Maura, Francesco
- Venue
- Nature Communications
- Published
- 2021-03-25
- Volume
- 12
- Issue
- 1
- Pages
- 1861-1861
- ISSN
- 2041-1723 (ISSN-L)
- PMC
- PMC7994386
- OpenAlex
- W3136516050
- Cited by
- 129
- References
- 8
- Citations by year
- 2026: 11 · 2025: 27 · 2024: 22 · 2023: 22 · 2022: 29 · 2021: 17
- FWCI
- 14.66
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- Nature Communications (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Lirias (acceptedVersion, other-oa)
- IUScholarWorks (Indiana University) (submittedVersion, cc-by)
- RePEc: Research Papers in Economics (submittedVersion)
- Archivio Istituzionale della Ricerca (Universita Degli Studi Di Milano) (submittedVersion, other-oa)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Document Server@UHasselt (UHasselt) (submittedVersion, other-oa)
- Newcastle University ePrints (Newcastle Univesity) (cc-by)
- Funders
- U.S. Department of Health & Human Services | NIH | National Cancer Institute (P30 CA 008748)
- Topics
- Health Sciences › Medicine › Hematology › Multiple Myeloma Research and Treatments
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › Cancer Genomics and Diagnostics
- Health Sciences › Medicine › Genetics › Chronic Lymphocytic Leukemia Research
- Keywords
- multiple myeloma, monoclonal gammopathy of undetermined significance, smoldering multiple myeloma, disease progression, chromothripsis, aneuploidy, driver mutations, clonal evolution, whole genome sequencing
- MeSH terms
- Whole Genome Sequencing, Smoldering Multiple Myeloma, Humans, Monoclonal Gammopathy of Undetermined Significance, Multiple Myeloma, Risk Factors, Genome, Human, Disease Progression, Polymorphism, Single Nucleotide, DNA Copy Number Variations
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