Author
Listed:
- Michaela Gruber
(Dana-Farber Cancer Institute
Broad Institute of MIT and Harvard
Division of Haematology and Haemostaseology, Comprehensive Cancer Center, Medical University of Vienna
CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences)
- Ivana Bozic
(University of Washington)
- Ignaty Leshchiner
(Broad Institute of MIT and Harvard)
- Dimitri Livitz
(Broad Institute of MIT and Harvard)
- Kristen Stevenson
(Dana Farber Cancer Institute)
- Laura Rassenti
(University of California at San Diego Moores Cancer Center)
- Daniel Rosebrock
(Broad Institute of MIT and Harvard)
- Amaro Taylor-Weiner
(Broad Institute of MIT and Harvard)
- Oriol Olive
(Dana-Farber Cancer Institute)
- Reaha Goyetche
(Dana-Farber Cancer Institute)
- Stacey M. Fernandes
(Dana-Farber Cancer Institute)
- Jing Sun
(Dana-Farber Cancer Institute)
- Chip Stewart
(Broad Institute of MIT and Harvard)
- Alicia Wong
(Broad Institute of MIT and Harvard)
- Carrie Cibulskis
(Broad Institute of MIT and Harvard)
- Wandi Zhang
(Dana-Farber Cancer Institute)
- Johannes G. Reiter
(Harvard University)
- Jeffrey M. Gerold
(Harvard University)
- John G. Gribben
(University of London)
- Kanti R. Rai
(Hofstra North Shore-LIJ School of Medicine)
- Michael J. Keating
(MD Anderson Cancer Center)
- Jennifer R. Brown
(Dana-Farber Cancer Institute
Brigham and Women’s Hospital
Harvard Medical School)
- Donna Neuberg
(Dana Farber Cancer Institute)
- Thomas J. Kipps
(University of California at San Diego Moores Cancer Center)
- Martin A. Nowak
(Harvard University
Harvard University)
- Gad Getz
(Broad Institute of MIT and Harvard
Harvard Medical School
Massachusetts General Hospital
Massachusetts General Hospital)
- Catherine J. Wu
(Dana-Farber Cancer Institute
Broad Institute of MIT and Harvard
Brigham and Women’s Hospital
Harvard Medical School)
Abstract
How the genomic features of a patient’s cancer relate to individual disease kinetics remains poorly understood. Here we used the indolent growth dynamics of chronic lymphocytic leukaemia (CLL) to analyse the growth rates and corresponding genomic patterns of leukaemia cells from 107 patients with CLL, spanning decades-long disease courses. We found that CLL commonly demonstrates not only exponential expansion but also logistic growth, which is sigmoidal and reaches a certain steady-state level. Each growth pattern was associated with marked differences in genetic composition, the pace of disease progression and the extent of clonal evolution. In a subset of patients, whose serial samples underwent next-generation sequencing, we found that dynamic changes in the disease course of CLL were shaped by the genetic events that were already present in the early slow-growing stages. Finally, by analysing the growth rates of subclones compared with their parental clones, we quantified the growth advantage conferred by putative CLL drivers in vivo.
Suggested Citation
Michaela Gruber & Ivana Bozic & Ignaty Leshchiner & Dimitri Livitz & Kristen Stevenson & Laura Rassenti & Daniel Rosebrock & Amaro Taylor-Weiner & Oriol Olive & Reaha Goyetche & Stacey M. Fernandes & , 2019.
"Growth dynamics in naturally progressing chronic lymphocytic leukaemia,"
Nature, Nature, vol. 570(7762), pages 474-479, June.
Handle:
RePEc:nat:nature:v:570:y:2019:i:7762:d:10.1038_s41586-019-1252-x
DOI: 10.1038/s41586-019-1252-x
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