Genome-Wide Somatic Alterations in Multiple Myeloma Reveal a Superior Outcome Group.


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
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

3107-3118

Subventions

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

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Auteurs

Mehmet Kemal Samur (MK)

Department of Data Sciences, Dana Farber Cancer Institute, Boston, MA.
Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA.
Department of Medical Oncology, Dana Farber Cancer Institute, Harvard Medical School, Boston, MA.

Anil Aktas Samur (A)

Department of Data Sciences, Dana Farber Cancer Institute, Boston, MA.
Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA.

Mariateresa Fulciniti (M)

Department of Medical Oncology, Dana Farber Cancer Institute, Harvard Medical School, Boston, MA.

Raphael Szalat (R)

Department of Medical Oncology, Dana Farber Cancer Institute, Harvard Medical School, Boston, MA.

Tessa Han (T)

Department of Data Sciences, Dana Farber Cancer Institute, Boston, MA.

Masood Shammas (M)

Department of Medical Oncology, Dana Farber Cancer Institute, Harvard Medical School, Boston, MA.

Paul Richardson (P)

Department of Medical Oncology, Dana Farber Cancer Institute, Harvard Medical School, Boston, MA.

Florence Magrangeas (F)

Inserm UMR892, CNRS 6299, Université de Nantes, and Centre Hospitalier Universitaire de Nantes, Unité Mixte de Genomique du Cancer, Nantes, France.

Stephane Minvielle (S)

Inserm UMR892, CNRS 6299, Université de Nantes, and Centre Hospitalier Universitaire de Nantes, Unité Mixte de Genomique du Cancer, Nantes, France.

Jill Corre (J)

University Cancer Center of Toulouse Institut National de la Santé, Toulouse, France.

Philippe Moreau (P)

Inserm UMR892, CNRS 6299, Université de Nantes, and Centre Hospitalier Universitaire de Nantes, Unité Mixte de Genomique du Cancer, Nantes, France.

Anjan Thakurta (A)

Celgene Corporation, Summit, NJ.

Kenneth C Anderson (KC)

Department of Medical Oncology, Dana Farber Cancer Institute, Harvard Medical School, Boston, MA.

Giovanni Parmigiani (G)

Department of Data Sciences, Dana Farber Cancer Institute, Boston, MA.
Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA.

Hervé Avet-Loiseau (H)

University Cancer Center of Toulouse Institut National de la Santé, Toulouse, France.

Nikhil C Munshi (NC)

Department of Medical Oncology, Dana Farber Cancer Institute, Harvard Medical School, Boston, MA.
VA Boston Healthcare System, Boston, MA.

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Classifications MeSH