Genome-wide somatic alterations in multiple myeloma reveal a superior outcome group
Open accessAbstract
PURPOSE: Multiple myeloma (MM) is accompanied by heterogeneous somatic alterations. The overall goal of this study was to describe the genomic landscape of myeloma using deep whole-genome sequencing (WGS) and develop a model that identifies patients with long survival. METHODS: We analyzed deep WGS data from 183 newly diagnosed patients with MM treated with lenalidomide, bortezomib, and dexamethasone (RVD) alone or RVD + autologous stem cell transplant (ASCT) in the IFM/DFCI 2009 study (ClinicalTrials.gov identifier: NCT01191060 ). We integrated genomic markers with clinical data. RESULTS: We report significant variability in mutational load and processes within MM subgroups. The timeline of observed activation of mutational processes provides the basis for 2 distinct models of acquisition of mutational changes detected at the time of diagnosis of myeloma. Virtually all MM subgroups have activated DNA repair–associated signature as a prominent late mutational process, whereas APOBEC signature targeting C>G is activated in the intermediate phase of disease progression in high-risk MM. Importantly, we identify a genomically defined MM subgroup (17% of newly diagnosed patients) with low DNA damage (low genomic scar score with chromosome 9 gain) and a superior outcome (100% overall survival at 69 months), which was validated in a large independent cohort. This subgroup allowed us to distinguish patients with low- and high-risk hyperdiploid MM and identify patients with prolongation of progression-free survival. Genomic characteristics of this subgroup included lower mutational load with significant contribution from age-related mutations as well as frequent NRAS mutation. Surprisingly, their overall survival was independent of International Staging System and minimal residual disease status. CONCLUSION: This is a comprehensive study identifying genomic markers of a good-risk group with prolonged survival. Identification of this patient subgroup will affect future therapeutic algorithms and research planning.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Different patients might experience different exposure in time and intensity in the germinal center, potentially reflecting unique interaction with the external environment.
“Importantly, based on the different number of GC mutations observed across hundreds of WGS, it has been shown that different patients might experience different exposure in time and intensity, potentially reflecting unique interaction with the external environment.12,13,15,72,73”
From Evolution of Multiple Myeloma from a Genomic Perspective (2026) · cites this paper as [73]
The Results describe somatic-hypermutation mutations and variation in mutational processes across myeloma samples; the Discussion places AID-related mutations predominantly at an early, clonal stage. These passages do not establish that individual patients experienced different durations or intensities of germinal-center exposure, or link such exposure to interactions with the external environment. Page numbers were not available in our copy. (LLM, conf=0.78)
Experimental — accuracy not yet measured
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
Pan-cancer analysis of whole genomes
The ICGC/TCGA Pan-Cancer Analysis of Whole Genomes Consortium, Aaltonen, L. A., Abascal, F., Abeshouse, A., Aburatani, H., Adams, D. J., Agrawal, N., Ahn, K. S., Ahn, S.-M., Aikata, H., et al. (2020) · Nature · doi:10.1038/s41586-020-1969-6 · Cited by 3,064 · see citing works
Hoadley, K. A., Yau, C., Hinoue, T., Wolf, D. M., Lazar, A. J., Drill, E., Shen, R., Taylor, A. M., Cherniack, A. D., Thorsson, V., et al. (2018) · Cell · doi:10.1016/j.cell.2018.03.022 · Cited by 2,546 · see citing works
Heterogeneity of genomic evolution and mutational profiles in multiple myeloma
Bolli, N., Avet-Loiseau, H., Wedge, D. C., Van Loo, P., Alexandrov, L. B., Martincorena, I., Dawson, K. J., Iorio, F., Nik-Zainal, S., Bignell, G. R., et al. (2014) · Nature Communications · doi:10.1038/ncomms3997 · Cited by 875 · see citing works
Self-citationWalker, B. A., Wardell, C. P., Murison, A., Boyle, E. M., Begum, D. B., Dahir, N. M., Proszek, P. Z., Melchor, L., Pawlyn, C., Kaiser, M. F., et al. (2015) · Nature Communications · doi:10.1038/ncomms7997 · Cited by 313 · see citing works
Flagged first, then by citations
Research works printed but not linked: 43
- [1]Manier S Salem KZ Park J et al Genomic complexity of multiple myeloma and its clinical implications Nat Rev Clin Oncol 14 100 113 2017 27531699
- [2]Perrot A Corre J Avet-Loiseau H Risk stratification and targets in multiple myeloma: From genomics to the bedside Am Soc Clin Oncol Educ Book 38 675 680 2018 30231368
- [3]Robiou du Pont S Cleynen A Fontan C et al Genomics of multiple myeloma J Clin Oncol 35 963 967 2017 28297630
- [5]Bolli N Biancon G Moarii M et al Analysis of the genomic landscape of multiple myeloma highlights novel prognostic markers and disease subgroups Leukemia 32 2604 2616 2018 29789651 PMC6092251
- [6]Bolli N Maura F Minvielle S et al Genomic patterns of progression in smoldering multiple myeloma Nat Commun 9 3363 2018 30135448 PMC6105687
- [7]Walker BA, Mavrommatis K, Wardell CP, et al: Identification of novel mutational drivers reveals oncogene dependencies in multiple myeloma. Blood 132:587-597, 2018 [Erratum: Blood 132:1461, 2018] PMC6097138 29884741
- [8]Chapman MA Lawrence MS Keats JJ et al Initial genome sequencing and analysis of multiple myeloma Nature 471 467 472 2011 21430775 PMC3560292
- [9]Khurana E Fu Y Chakravarty D et al Role of non-coding sequence variants in cancer Nat Rev Genet 17 93 108 2016 26781813
- [10]Zhang W Bojorquez-Gomez A Velez DO et al A global transcriptional network connecting noncoding mutations to changes in tumor gene expression Nat Genet 50 613 620 2018 29610481 PMC5893414
- [11]Gloss BS Dinger ME Realizing the significance of noncoding functionality in clinical genomics Exp Mol Med 50 97 2018 30089779 PMC6082831
- [12]Piraino SW Furney SJ Beyond the exome: the role of non-coding somatic mutations in cancer Ann Oncol 27 240 248 2016 26598542
- [13]Rahman S, Mansour MR: The role of noncoding mutations in blood cancers. Dis Model Mech 12:dmm041988, 2019 PMC6899015 31771951
- [14]Zhu H Uusküla-Reimand L Isaev K et al Candidate cancer driver mutations in distal regulatory elements and long-range chromatin interaction networks Mol Cell 77 1307 1321.e10 2020 31954095
- [15]Hornshøj H Nielsen MM Sinnott-Armstrong NA et al Pan-cancer screen for mutations in non-coding elements with conservation and cancer specificity reveals correlations with expression and survival NPJ Genom Med 3 1 2018 29354286 PMC5765157
- [16]Corre J Cleynen A Robiou du Pont S et al Multiple myeloma clonal evolution in homogeneously treated patients Leukemia 32 2636 2647 2018 29895955 PMC6603429
- [17]Szalat R, Munshi NC: Genomic heterogeneity in multiple myeloma. Curr Opin Genet Dev 30:56-65, 2015 [Erratum: Curr Opin Genet Dev 37:158, 2016] 27321239
- [18]Aktas Samur A Minvielle S Shammas M et al Deciphering the chronology of copy number alterations in multiple myeloma Blood Cancer J 9 39 2019 30914633 PMC6435669
- [19]Attal M Lauwers-Cances V Hulin C et al Lenalidomide, bortezomib, and dexamethasone with transplantation for myeloma N Engl J Med 376 1311 1320 2017 28379796 PMC6201242
- [20]Cibulskis K Lawrence MS Carter SL et al Sensitive detection of somatic point mutations in impure and heterogeneous cancer samples Nat Biotechnol 31 213 219 2013 23396013 PMC3833702
- [21]Shen R Seshan VE FACETS: Allele-specific copy number and clonal heterogeneity analysis tool for high-throughput DNA sequencing Nucleic Acids Res 44 e131 2016 27270079 PMC5027494
- [22]Chen X Schulz-Trieglaff O Shaw R et al Manta: Rapid detection of structural variants and indels for germline and cancer sequencing applications Bioinformatics 32 1220 1222 2016 26647377
- [23]McLaren W Gil L Hunt SE et al The Ensembl Variant Effect Predictor Genome Biol 17 122 2016 27268795 PMC4893825
- [24]Rosales RA Drummond RD Valieris R et al signeR: An empirical Bayesian approach to mutational signature discovery Bioinformatics 33 8 16 2017 27591080
- [25]Sztupinszki Z Diossy M Krzystanek M et al Migrating the SNP array-based homologous recombination deficiency measures to next generation sequencing data of breast cancer NPJ Breast Cancer 4 16 2018 29978035 PMC6028448
- [28]Gonzalez-Perez A Sabarinathan R Lopez-Bigas N Local determinants of the mutational landscape of the human genome Cell 177 101 114 2019 30901533
- [29]Alexandrov LB Kim J Haradhvala NJ et al The repertoire of mutational signatures in human cancer Nature 578 94 101 2020 32025018 PMC7054213
- [30]Maura F Petljak M Lionetti M et al Biological and prognostic impact of APOBEC-induced mutations in the spectrum of plasma cell dyscrasias and multiple myeloma cell lines Leukemia 32 1044 1048 2018 29209044 PMC5886048
- [32]Hoang PH Cornish AJ Dobbins SE et al Mutational processes contributing to the development of multiple myeloma Blood Cancer J 9 60 2019 31387987 PMC6684612
- [33]Keats JJ Chesi M Egan JB et al Clonal competition with alternating dominance in multiple myeloma Blood 120 1067 1076 2012 22498740 PMC3412330
- [34]Affer M Chesi M Chen WG et al Promiscuous MYC locus rearrangements hijack enhancers but mostly super-enhancers to dysregulate MYC expression in multiple myeloma Leukemia 28 1725 1735 2014 24518206 PMC4126852
- [35]Maura F Rustad EH Yellapantula V et al Role of AID in the temporal pattern of acquisition of driver mutations in multiple myeloma Leukemia 34 1476 1480 2020 31836853
- [36]Walker BA Mavrommatis K Wardell CP et al A high-risk, Double-Hit, group of newly diagnosed myeloma identified by genomic analysis Leukemia 33 159 170 2019 29967379 PMC6326953
- [37]Palumbo A Avet-Loiseau H Oliva S et al Revised International Staging System for multiple myeloma: A report from International Myeloma Working Group J Clin Oncol 33 2863 2869 2015 26240224 PMC4846284
- [38]Barwick BG Neri P Bahlis NJ et al Multiple myeloma immunoglobulin lambda translocations portend poor prognosis Nat Commun 10 1911 2019 31015454 PMC6478743
- [39]Sonneveld P Avet-Loiseau H Lonial S et al Treatment of multiple myeloma with high-risk cytogenetics: A consensus of the International Myeloma Working Group Blood 127 2955 2962 2016 27002115 PMC4920674
- [40]Mikhael J Ismaila N Cheung MC et al Treatment of multiple myeloma: ASCO and CCO joint clinical practice guideline J Clin Oncol 37 1228 1263 2019 30932732
- [41]Perrot A Lauwers-Cances V Tournay E et al Development and validation of a cytogenetic prognostic index predicting survival in multiple myeloma J Clin Oncol 37 1657 1665 2019 31091136 PMC6804890
- [42]Avet-Loiseau H Li C Magrangeas F et al Prognostic significance of copy-number alterations in multiple myeloma J Clin Oncol 27 4585 4590 2009 19687334 PMC2754906
- [43]Weinhold N Kirn D Seckinger A et al Concomitant gain of 1q21 and MYC translocation define a poor prognostic subgroup of hyperdiploid multiple myeloma Haematologica 101 e116 e119 2016 26611471 PMC4815741
- [44]Miller A Asmann Y Cattaneo L et al High somatic mutation and neoantigen burden are correlated with decreased progression-free survival in multiple myeloma Blood Cancer J 7 e612 2017 28937974 PMC5709757
- [45]Samur MK Minvielle S Gulla A et al Long intergenic non-coding RNAs have an independent impact on survival in multiple myeloma Leukemia 32 2626 2635 2018 29749396 PMC6163089
- [46]Kuiper R, Broyl A, de Knegt Y, et al: A gene expression signature for high-risk multiple myeloma. Leukemia 26:2406-2413, 2012 [Erratum: Leukemia 28:1178-1180, 2014] 22722715
- [47]Kumar S, Fonseca R, Ketterling RP, et al: Trisomies in multiple myeloma: Impact on survival in patients with high-risk cytogenetics. Blood 119:2100-2105, 2012 [Erratum: Blood 123:1621, 2014] PMC3311247 22234687
Cited by
Sorted by citations
Genomic Classification and Individualized Prognosis in Multiple Myeloma
Maura, F., Rajanna, A. R., Ziccheddu, B., Poos, A. M., Derkach, A., Maclachlan, K., Durante, M., Diamond, B., Papadimitriou, M., Davies, F., et al. (2024) · Journal of Clinical Oncology · doi:10.1200/jco.23.01277 · Cited by 131 · 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
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
- Samur, M. K., Aktas Samur, A., Fulciniti, M., Szalat, R., Han, T., Shammas, M., Richardson, P., Magrangeas, F., Minvielle, S., Corre, J., Moreau, P., Thakurta, A., Anderson, K. C., Parmigiani, G., Avet-Loiseau, H., & Munshi, N. C.
- Affiliations
- Harvard University (US)
- Department of Data Sciences, Dana Farber Cancer Institute, Boston, MA
- Dana-Farber Cancer Institute (US)
- Centre National de la Recherche Scientifique (FR)
- Inserm UMR892, CNRS 6299, Université de Nantes, and Centre Hospitalier Universitaire de Nantes, Unité Mixte de Genomique du Cancer, Nantes, France
- University Cancer Center of Toulouse Institut National de la Santé, Toulouse, France
- Celgene (United States) (US)
- Corresponding author
- Samur, Mehmet Kemal
- ORCID
- Venue
- Journal of Clinical Oncology
- Published
- 2020-09-20
- Volume
- 38
- Issue
- 27
- Pages
- 3107-3118
- ISSN
- 0732-183X (ISSN-L)
- 1527-7755
- PMC
- PMC7499613
- OpenAlex
- W3043473017
- Cited by
- 70
- References
- 4
- Citations by year
- 2026: 2 · 2025: 10 · 2024: 18 · 2023: 12 · 2022: 11 · 2021: 14 · 2020: 3
- FWCI
- 6.32
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- cc-by-nc-nd
- Locations
- Journal of Clinical Oncology (publishedVersion, cc-by-nc-nd)
- Europe PMC (PubMed Central) (publishedVersion, cc-by-nc-nd)
- PubMed Central (publishedVersion, cc-by-nc-nd)
- PubMed (publishedVersion)
- HAL (submittedVersion)
- HAL (submittedVersion, other-oa)
- Funders
- U.S. Department of Veterans Affairs (I01 BX001584)
- Celgene
- Agence Nationale de la Recherche (ANR-16-IDEX-0007)
- National Cancer Institute (P50CA100707, P01CA155258)
- 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 › Hematology › Acute Myeloid Leukemia Research
- Keywords
- multiple myeloma, somatic alterations, mutational signatures, APOBEC signature, mutational load, NRAS mutation, prognostic subgroups, overall survival, progression-free survival, autologous stem cell transplantation
- MeSH terms
- Bortezomib, Whole Genome Sequencing, Lenalidomide, Progression-Free Survival, Adult, Aged, Antineoplastic Combined Chemotherapy Protocols, Combined Modality Therapy, Dexamethasone, DNA Mutational Analysis, DNA, Neoplasm, Female, Humans, Male, Membrane Proteins, Middle Aged, Multiple Myeloma, Biomarkers, Tumor, Survival Rate, Treatment Outcome, GTP Phosphohydrolases, Stem Cell Transplantation, INDEL Mutation
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 ›
Are you an author, or do you see a problem with this page? Request a review