Author
Listed:
- Kylee H. Maclachlan
(Memorial Sloan Kettering Cancer Center)
- Even H. Rustad
(Memorial Sloan Kettering Cancer Center
Oslo University Hospital Radiumhospitalet)
- Andriy Derkach
(Memorial Sloan Kettering Cancer Center)
- Binbin Zheng-Lin
(Memorial Sloan Kettering Cancer Center)
- Venkata Yellapantula
(Memorial Sloan Kettering Cancer Center)
- Benjamin Diamond
(Memorial Sloan Kettering Cancer Center
University of Miami)
- Malin Hultcrantz
(Memorial Sloan Kettering Cancer Center)
- Bachisio Ziccheddu
(University of Miami
University of Turin)
- Eileen M. Boyle
(Myeloma Research Program, NYU Langone, Perlmutter Cancer Center)
- Patrick Blaney
(Myeloma Research Program, NYU Langone, Perlmutter Cancer Center)
- Niccolò Bolli
(University of Milan
Hematology Unit, Fondazione IRCCS Ca’ Granda Ospedale Maggiore Policlinico)
- Yanming Zhang
(Memorial Sloan Kettering Cancer Center)
- Ahmet Dogan
(Memorial Sloan Kettering Cancer Center)
- Alexander M. Lesokhin
(Memorial Sloan Kettering Cancer Center
Weill Cornell Medical College)
- Gareth J. Morgan
(Myeloma Research Program, NYU Langone, Perlmutter Cancer Center)
- Ola Landgren
(University of Miami)
- Francesco Maura
(University of Miami)
Abstract
Chromothripsis is detectable in 20–30% of newly diagnosed multiple myeloma (NDMM) patients and is emerging as a new independent adverse prognostic factor. In this study we interrogate 752 NDMM patients using whole genome sequencing (WGS) to investigate the relationship of copy number (CN) signatures to chromothripsis and show they are highly associated. CN signatures are highly predictive of the presence of chromothripsis (AUC = 0.90) and can be used identify its adverse prognostic impact. The ability of CN signatures to predict the presence of chromothripsis is confirmed in a validation series of WGS comprised of 235 hematological cancers (AUC = 0.97) and an independent series of 34 NDMM (AUC = 0.87). We show that CN signatures can also be derived from whole exome data (WES) and using 677 cases from the same series of NDMM, we are able to predict both the presence of chromothripsis (AUC = 0.82) and its adverse prognostic impact. CN signatures constitute a flexible tool to identify the presence of chromothripsis and is applicable to WES and WGS data.
Suggested Citation
Kylee H. Maclachlan & Even H. Rustad & Andriy Derkach & Binbin Zheng-Lin & Venkata Yellapantula & Benjamin Diamond & Malin Hultcrantz & Bachisio Ziccheddu & Eileen M. Boyle & Patrick Blaney & Niccolò , 2021.
"Copy number signatures predict chromothripsis and clinical outcomes in newly diagnosed multiple myeloma,"
Nature Communications, Nature, vol. 12(1), pages 1-11, December.
Handle:
RePEc:nat:natcom:v:12:y:2021:i:1:d:10.1038_s41467-021-25469-8
DOI: 10.1038/s41467-021-25469-8
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