Genome-Wide Somatic Alterations in Multiple Myeloma Reveal a Superior Outcome Group.
Adult
Aged
Antineoplastic Combined Chemotherapy Protocols
/ therapeutic use
Biomarkers, Tumor
/ genetics
Bortezomib
/ administration & dosage
Combined Modality Therapy
DNA Mutational Analysis
DNA, Neoplasm
Dexamethasone
Female
GTP Phosphohydrolases
/ genetics
Humans
INDEL Mutation
Lenalidomide
/ administration & dosage
Male
Membrane Proteins
/ genetics
Middle Aged
Multiple Myeloma
/ genetics
Progression-Free Survival
Stem Cell Transplantation
Survival Rate
Treatment Outcome
Whole Genome Sequencing
Journal
Journal of clinical oncology : official journal of the American Society of Clinical Oncology
ISSN: 1527-7755
Titre abrégé: J Clin Oncol
Pays: United States
ID NLM: 8309333
Informations de publication
Date de publication:
20 09 2020
20 09 2020
Historique:
pubmed:
21
7
2020
medline:
3
3
2021
entrez:
21
7
2020
Statut:
ppublish
Résumé
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. 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. 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 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.
Identifiants
pubmed: 32687451
doi: 10.1200/JCO.20.00461
pmc: PMC7499613
doi:
Substances chimiques
Biomarkers, Tumor
0
DNA, Neoplasm
0
Membrane Proteins
0
Bortezomib
69G8BD63PP
Dexamethasone
7S5I7G3JQL
GTP Phosphohydrolases
EC 3.6.1.-
NRAS protein, human
EC 3.6.1.-
Lenalidomide
F0P408N6V4
Banques de données
ClinicalTrials.gov
['NCT01191060']
Types de publication
Journal Article
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
Research Support, U.S. Gov't, Non-P.H.S.
Langues
eng
Sous-ensembles de citation
IM
Pagination
3107-3118Subventions
Organisme : BLRD VA
ID : I01 BX001584
Pays : United States
Organisme : NCI NIH HHS
ID : P01 CA155258
Pays : United States
Organisme : NCI NIH HHS
ID : P50 CA100707
Pays : United States
Références
Nucleic Acids Res. 2016 Sep 19;44(16):e131
pubmed: 27270079
Nat Genet. 2018 Apr;50(4):613-620
pubmed: 29610481
NPJ Genom Med. 2018 Jan 11;3:1
pubmed: 29354286
Genome Biol. 2016 Jun 06;17(1):122
pubmed: 27268795
Blood Cancer J. 2017 Sep 22;7(9):e612
pubmed: 28937974
Blood Cancer J. 2019 Mar 26;9(4):39
pubmed: 30914633
Nat Commun. 2015 Apr 23;6:6997
pubmed: 25904160
Nature. 2020 Feb;578(7793):94-101
pubmed: 32025018
Haematologica. 2016 Mar;101(3):e116-9
pubmed: 26611471
Nature. 2011 Mar 24;471(7339):467-72
pubmed: 21430775
Leukemia. 2018 Apr;32(4):1044-1048
pubmed: 29209044
Leukemia. 2018 Dec;32(12):2636-2647
pubmed: 29895955
Bioinformatics. 2017 Jan 1;33(1):8-16
pubmed: 27591080
Mol Cell. 2020 Mar 19;77(6):1307-1321.e10
pubmed: 31954095
Leukemia. 2020 May;34(5):1476-1480
pubmed: 31836853
Leukemia. 2012 Nov;26(11):2406-13
pubmed: 22722715
J Clin Oncol. 2019 May 10;37(14):1228-1263
pubmed: 30932732
Leukemia. 2019 Jan;33(1):159-170
pubmed: 29967379
Nat Rev Genet. 2016 Feb;17(2):93-108
pubmed: 26781813
NPJ Breast Cancer. 2018 Jul 2;4:16
pubmed: 29978035
Nat Biotechnol. 2013 Mar;31(3):213-9
pubmed: 23396013
Leukemia. 2018 Dec;32(12):2626-2635
pubmed: 29749396
J Clin Oncol. 2009 Sep 20;27(27):4585-90
pubmed: 19687334
J Clin Oncol. 2017 Mar 20;35(9):963-967
pubmed: 28297630
Nature. 2020 Feb;578(7793):82-93
pubmed: 32025007
J Clin Oncol. 2019 Jul 1;37(19):1657-1665
pubmed: 31091136
Bioinformatics. 2016 Apr 15;32(8):1220-2
pubmed: 26647377
Am Soc Clin Oncol Educ Book. 2018 May 23;38:675-680
pubmed: 30231368
Ann Oncol. 2016 Feb;27(2):240-8
pubmed: 26598542
Cell. 2019 Mar 21;177(1):101-114
pubmed: 30901533
Nat Commun. 2014;5:2997
pubmed: 24429703
Blood. 2012 Aug 2;120(5):1067-76
pubmed: 22498740
N Engl J Med. 2017 Apr 6;376(14):1311-1320
pubmed: 28379796
Curr Opin Genet Dev. 2016 Apr;37:158
pubmed: 27321239
Leukemia. 2014 Aug;28(8):1725-1735
pubmed: 24518206
Nat Commun. 2019 Apr 23;10(1):1911
pubmed: 31015454
Blood. 2016 Jun 16;127(24):2955-62
pubmed: 27002115
Blood. 2018 Sep 27;132(13):1461
pubmed: 30262586
Leukemia. 2018 Dec;32(12):2604-2616
pubmed: 29789651
Nat Commun. 2018 Aug 22;9(1):3363
pubmed: 30135448
Blood Cancer J. 2019 Aug 6;9(8):60
pubmed: 31387987
Cell. 2018 Apr 5;173(2):291-304.e6
pubmed: 29625048
Dis Model Mech. 2019 Nov 26;12(11):
pubmed: 31771951
Blood. 2012 Mar 1;119(9):2100-5
pubmed: 22234687
Nat Rev Clin Oncol. 2017 Feb;14(2):100-113
pubmed: 27531699
J Clin Oncol. 2015 Sep 10;33(26):2863-9
pubmed: 26240224
Exp Mol Med. 2018 Aug 7;50(8):97
pubmed: 30089779