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Nature. 2019 Jun;570(7762):474-479. doi: 10.1038/s41586-019-1252-x. Epub 2019 May 29.

Growth dynamics in naturally progressing chronic lymphocytic leukaemia.

Author information

1
Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA.
2
Broad Institute of MIT and Harvard, Cambridge, MA, USA.
3
Department of Internal Medicine I, Division of Haematology and Haemostaseology, Comprehensive Cancer Center, Medical University of Vienna, Vienna, Austria.
4
CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Vienna, Austria.
5
Department of Applied Mathematics, University of Washington, Seattle, WA, USA.
6
Department of Biostatistics and Computational Biology, Dana Farber Cancer Institute, Boston, MA, USA.
7
Department of Medicine, University of California at San Diego Moores Cancer Center, La Jolla, CA, USA.
8
Program for Evolutionary Dynamics, Harvard University, Cambridge, MA, USA.
9
Barts Cancer Institute, Queen Mary, University of London, London, UK.
10
Hofstra North Shore-LIJ School of Medicine, Lake Success, NY, USA.
11
Department of Leukemia, MD Anderson Cancer Center, Houston, TX, USA.
12
Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA.
13
Harvard Medical School, Boston, MA, USA.
14
Department of Mathematics and Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA, USA.
15
Broad Institute of MIT and Harvard, Cambridge, MA, USA. gadgetz@broadinstitute.org.
16
Harvard Medical School, Boston, MA, USA. gadgetz@broadinstitute.org.
17
Department of Pathology, Massachusetts General Hospital, Boston, MA, USA. gadgetz@broadinstitute.org.
18
Center for Cancer Research, Massachusetts General Hospital, Boston, MA, USA. gadgetz@broadinstitute.org.
19
Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA. cwu@partners.org.
20
Broad Institute of MIT and Harvard, Cambridge, MA, USA. cwu@partners.org.
21
Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA. cwu@partners.org.
22
Harvard Medical School, Boston, MA, USA. cwu@partners.org.

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 correspondingĀ 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.

PMID:
31142838
PMCID:
PMC6630176
[Available on 2019-12-01]
DOI:
10.1038/s41586-019-1252-x

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