Copy number signatures predict chromothripsis and clinical outcomes in newly diagnosed multiple myeloma

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 Bolli, Yanming Zhang, Ahmet Dogan, Alexander M. Lesokhin, Gareth J. Morgan, Ola Landgren and Francesco Maura ()
Additional contact information
Kylee H. Maclachlan: Memorial Sloan Kettering Cancer Center
Even H. Rustad: Memorial Sloan Kettering Cancer Center
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
Malin Hultcrantz: Memorial Sloan Kettering Cancer Center
Bachisio Ziccheddu: University of Miami
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
Yanming Zhang: Memorial Sloan Kettering Cancer Center
Ahmet Dogan: Memorial Sloan Kettering Cancer Center
Alexander M. Lesokhin: Memorial Sloan Kettering Cancer Center
Gareth J. Morgan: Myeloma Research Program, NYU Langone, Perlmutter Cancer Center
Ola Landgren: University of Miami
Francesco Maura: University of Miami

Nature Communications, 2021, vol. 12, issue 1, 1-11

Abstract: 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.

Date: 2021
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DOI: 10.1038/s41467-021-25469-8

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