Abstract

We analyzed whole genomes of unique paired samples from smoldering multiple myeloma (SMM) patients progressing to multiple myeloma (MM). We report that the genomic landscape, including mutational profile and structural rearrangements at the smoldering stage is very similar to MM. Paired sample analysis shows two different patterns of progression: a “static progression model”, where the subclonal architecture is retained as the disease progressed to MM suggesting that progression solely reflects the time needed to accumulate a sufficient disease burden; and a “spontaneous evolution model”, where a change in the subclonal composition is observed. We also observe that activation-induced cytidine deaminase plays a major role in shaping the mutational landscape of early subclinical phases, while progression is driven by APOBEC cytidine deaminases. These results provide a unique insight into myelomagenesis with potential implications for the definition of smoldering disease and timing of treatment initiation.

Details

Title
Genomic patterns of progression in smoldering multiple myeloma
Author
Bolli, Niccolò 1   VIAFID ORCID Logo  ; Francesco, Maura 2 ; Minvielle, Stephane 3 ; Gloznik, Dominik 4 ; Szalat, Raphael 5 ; Fullam, Anthony 4   VIAFID ORCID Logo  ; Martincorena, Inigo 4 ; Dawson, Kevin J 4 ; Samur, Mehmet Kemal 5 ; Zamora, Jorge 4 ; Tarpey, Patrick 4 ; Davies, Helen 4 ; Fulciniti, Mariateresa 5 ; Shammas, Masood A 5 ; Yu Tzu Tai 5 ; Magrangeas, Florence 3 ; Moreau, Philippe 3 ; Corradini, Paolo 6 ; Anderson, Kenneth 5 ; Alexandrov, Ludmil 7 ; Wedge, David C 8 ; Avet-Loiseau, Herve 9 ; Campbell, Peter 10 ; Munshi, Nikhil 11 

1  Department of Oncology and Hemato-Oncology, University of Milan, Milan, Italy; Department of Oncology and Hematology, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy; Cancer Genome Project, Wellcome Trust Sanger Institute, Hinxton, Cambridgeshire, UK 
2  Department of Oncology and Hemato-Oncology, University of Milan, Milan, Italy; Cancer Genome Project, Wellcome Trust Sanger Institute, Hinxton, Cambridgeshire, UK 
3  CRCINA, INSERM, CNRS, Université de Nantes, Université d’Angers, Nantes, France; CHU de Nantes, Nantes, France 
4  Cancer Genome Project, Wellcome Trust Sanger Institute, Hinxton, Cambridgeshire, UK 
5  Jerome Lipper Multiple Myeloma Center, Dana–Farber Cancer Institute, Harvard Medical School, Boston, MA, USA 
6  Department of Oncology and Hemato-Oncology, University of Milan, Milan, Italy; Department of Oncology and Hematology, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy 
7  Department of Cellular and Molecular Medicine and Department of Bioengineering and Moores Cancer Center, University of California, San Diego, La Jolla, CA, USA 
8  Big Data Institute, Nuffield Department of Medicine, University of Oxford, Oxford, UK 
9  Genomics of Myeloma Laboratory, L’Institut Universitaire du Cancer Oncopole, Toulouse, France 
10  Department of Oncology and Hemato-Oncology, University of Milan, Milan, Italy 
11  Jerome Lipper Multiple Myeloma Center, Dana–Farber Cancer Institute, Harvard Medical School, Boston, MA, USA; Veterans Administration Boston Healthcare System, West Roxbury, MA, USA 
Pages
1-10
Publication year
2018
Publication date
Aug 2018
Publisher
Nature Publishing Group
e-ISSN
20411723
Source type
Scholarly Journal
Language of publication
English
DOI
https://doi.org/10.1038/s41467-018-05058-y
ProQuest document ID
2091750736
Copyright
© 2018. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.