MinimuMM-seq: genome sequencing of circulating tumor cells for minimally invasive molecular characterization of multiple myeloma pathology
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Abstract
Multiple myeloma (MM) develops from well-defined precursor stages; however, invasive bone marrow (BM) biopsy limits screening and monitoring strategies for patients. We enumerated circulating tumor cells (CTC) from 261 patients (84 monoclonal gammopathy of undetermined significance, 155 smoldering multiple myeloma, and 22 MM), with neoplastic cells detected in 84%. We developed a novel approach, MinimuMM-seq, which enables the detection of translocations and copy-number abnormalities through whole-genome sequencing of highly pure CTCs. Application to CTCs in a cohort of 51 patients, 24 with paired BM, was able to detect 100% of clinically reported BM biopsy events and could replace molecular cytogenetics for diagnostic yield and risk classification. Longitudinal sampling of CTCs in 8 patients revealed major clones could be tracked in the blood, with clonal evolution and shifting dynamics of subclones over time. Our findings provide proof of concept that CTC detection and genomic profiling could be used clinically for monitoring and managing disease in MM. Significance: In this study, we established an approach enabling the enumeration and sequencing of CTCs to replace standard molecular cytogenetics. CTCs harbored the same pathognomonic MM abnormalities as BM plasma cells. Longitudinal sampling of serial CTCs was able to track clonal dynamics over time and detect the emergence of high-risk genetic subclones. This article is highlighted in the In This Issue feature, p. 247
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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 [79]
The genomic-profiling section reports genetic abnormalities in five MGUS cases and high-risk events in SMM, supporting the presence of genomic changes at precursor stages. The longitudinal section follows SMM cases for up to 33 months, but does not establish that the reported patterns were present in MGUS or low-risk SMM several years before those patients progressed, or that neoplastic transformation had already occurred then. No page numbers were available in our copy. (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 [79]
In “CTC Sequencing Enables Cohort-Level Genomic Study of Mutational Signatures and Complex Structural Events” (page not provided), the paper calls RAS-MAPK mutations the most prevalent drivers in MM and reports that APOBEC signatures are enriched in patients with smoldering MM who progress. It also describes a MYC-involving structural event and complex rearrangements, but does not establish that MYC translocations and patterns of genomic complexity are among the most commonly reported alterations in progressing MM. (LLM, conf=0.86)
Experimental — accuracy not yet measuredNeoplastic 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 [79]
The Introduction (page unavailable) describes myeloma as developing from asymptomatic precursor stages, and the Discussion (page unavailable) reports initiating mutational profiles in the sampled clones. The paper also detects genetic abnormalities in MGUS, which it calls a very early stage. These findings support early neoplastic changes, but the cited passages do not establish when neoplastic transformation itself occurs. (LLM, conf=0.74)
Experimental — accuracy not yet measuredEither decreased efficacy of the immune system or selection of more aggressive and fit clones will eventually allow MGUS/SMM to progress into MM.
“Either the decreased efficacy of the immune system or the selection of more aggressive and fit clones will eventually allow the MGUS/SMM to progress into MM.76,78,79,104”
From Evolution of Multiple Myeloma from a Genomic Perspective (2026) · cites this paper as [79]
The longitudinal-analysis section (page unavailable) reports expansion of fitter subclones in SMM and describes one patient whose selected clone was followed by progression to MM. The paper does not identify decreased immune-system efficacy as a cause of progression. Its Discussion (page unavailable) describes SMM as having indolent as well as early-MM-like trajectories, so the claim that MGUS/SMM will eventually progress is stronger than the evidence supports. (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 [79]
The section on longitudinal liquid biopsy reports clonal changes in eight SMM cases, while the molecular-cytogenetics section compares FISH with sequencing results. Neither passage describes temporal models or estimates from large sample sets supporting the existence of three distinct groups (pages not available in our copy). Searches for temporal models, three groups, and large cohorts found no passage making that connection. (LLM, conf=0.72)
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 [79]
The genomic-profiling results describe high-risk features detected in patients with SMM, and the Discussion describes SMM as heterogeneous. Neither passage compares the prevalence of those features in high-risk SMM with newly diagnosed MM; searches for that comparison found none in our copy. (LLM, conf=0.71)
Experimental — accuracy not yet measured
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Nadeem, O., Aranha, M. P., Redd, R., Timonian, M., Magidson, S., Lightbody, E. D., Alberge, J.-B., Bertamini, L., Dutta, A. K., El-Khoury, H., et al. (2025) · Nature Communications · doi:10.1038/s41467-024-55308-5 · Cited by 20 · see citing works
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- Authors
- 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., Barr, H., Hevenor, L., Beckwith, J. B., Perry, J., Cao, A., Lin, Z., Kuhr, F. K., Mastro, R. G. D., Nadeem, O., Greipp, P. T., Stewart, C., Auclair, D., Getz, G., & Ghobrial, I. M.
- Affiliations
- Broad Institute (US)
- 1Center for Prevention of Progression of Blood Cancers, Dana-Farber Cancer Institute, Boston, Massachusetts.
- Harvard University (US)
- 4Menarini Silicon Biosystems, Huntingdon Valley, Pennsylvania.
- Mayo Clinic (US)
- Multiple Myeloma Research Foundation (US)
- Corresponding author
- Getz, Gad
- Ghobrial, Irene M.
- ORCID
- Dutta, Ankit K.
- Alberge, Jean-Baptiste
- Lightbody, Elizabeth D.
- Boehner, Cody J.
- Dunford, Andrew
- Sklavenitis-Pistofidis, Romanos
- Mouhieddine, Tarek H.
- Cowan, Annie N.
- Su, Nang Kham
- Horowitz, Erica M.
- Barr, Hadley
- Hevenor, Laura
- Beckwith, Jenna B.
- Perry, Jacqueline
- Cao, Amanda
- Lin, Ziao
- Kuhr, Frank K.
- Mastro, Richard G. Del
- Nadeem, Omar
- Greipp, Patricia T.
- Stewart, Chip
- Auclair, Daniel
- Getz, Gad
- Ghobrial, Irene M.
- Venue
- Cancer Discovery
- Published
- 2022-12-07
- Volume
- 13
- Issue
- 2
- Pages
- 348-363
- ISSN
- 2159-8274 (ISSN-L)
- 2159-8290
- OpenAlex
- W4310954181
- Cited by
- 41
- References
- 55
- Citations by year
- 2026: 10 · 2025: 16 · 2024: 13 · 2023: 2
- FWCI
- 5.64
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Cancer Discovery (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Institutes of Health (R01CA205954 and R35CA263817-01A1)
- Dr. Miriam and Sheldon G. Adelson Medical Research Foundation
- International Myeloma Society (Career Development Award)
- Stand Up To Cancer (SU2C-AACR-DT-28-18)
- 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, circulating tumor cells, clonal evolution, translocation, copy number abnormalities, smoldering multiple myeloma, monoclonal gammopathy of undetermined significance, bone marrow biopsy, long-term monitoring, risk classification, liquid biopsy
- MeSH terms
- Whole Genome Sequencing, Base Sequence, Bone Marrow, Humans, Multiple Myeloma, Neoplastic Cells, Circulating
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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