Growth dynamics in naturally progressing chronic lymphocytic leukaemia

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 CL...

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Published in	Nature (London) Vol. 570; no. 7762; pp. 474 - 479
Main Authors	Gruber, Michaela, Bozic, Ivana, Leshchiner, Ignaty, Livitz, Dimitri, Stevenson, Kristen, Rassenti, Laura, Rosebrock, Daniel, Taylor-Weiner, Amaro, Olive, Oriol, Goyetche, Reaha, Fernandes, Stacey M., Sun, Jing, Stewart, Chip, Wong, Alicia, Cibulskis, Carrie, Zhang, Wandi, Reiter, Johannes G., Gerold, Jeffrey M., Gribben, John G., Rai, Kanti R., Keating, Michael J., Brown, Jennifer R., Neuberg, Donna, Kipps, Thomas J., Nowak, Martin A., Getz, Gad, Wu, Catherine J.
Format	Journal Article
Language	English
Published	London Nature Publishing Group UK 01.06.2019 Nature Publishing Group
Subjects	631/67/1990/283/1895 631/67/69 631/67/70 692/699/1541/1990/283/1895 Blood Cancer Cell Proliferation - drug effects Chronic lymphocytic leukemia Clone Cells - drug effects Clone Cells - pathology Cohort Studies Development and progression Disease Progression Evolution Evolution & development Evolution, Molecular Female Genomes Growth rate High-Throughput Nucleotide Sequencing Humanities and Social Sciences Humans Leukemia Leukemia, Lymphocytic, Chronic, B-Cell - drug therapy Leukemia, Lymphocytic, Chronic, B-Cell - genetics Leukemia, Lymphocytic, Chronic, B-Cell - pathology Male multidisciplinary Mutation Neoplasm Recurrence, Local - genetics Neoplasm Recurrence, Local - pathology Next-generation sequencing Patients Reaction kinetics Recurrence Reproducibility of Results Science Science (multidisciplinary)
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ISSN	0028-0836 1476-4687 1476-4687
DOI	10.1038/s41586-019-1252-x

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Summary:	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. Analysis of growth dynamics in a dataset from 107 patients with chronic lymphocytic leukaemia (CLL) reveals both exponential and logistic patterns of growth, which are associated with differences in genetic attributes and clinical outcomes.
Bibliography:	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23 Present address: CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Vienna, Austria: Michaela Gruber These authors jointly supervised this work: Gad Getz and Catherine J. Wu These authors contributed equally to this work: Michaela Gruber, Ivana Bozic, Ignaty Leshchiner, Dimitri Livitz. M.G., I.B., I.L., D.L., D.N., M.A.N., G.G. and C.J.W. designed the study, analysed and interpreted data. I.B. modeled CLL growth patterns across patients. I.L., D.L., I.B., G.G. developed novel methods for analysis of genomic data and modeled the clonal structure, trees and growth dynamics of individual clones. I.L., D.L., M.G., G.G. performed analysis of genomic data. M.G., L.R., S.F., O.O. and R.G. collected samples and annotations. J.G.G., K.R.R., M.J.K., J.R.B. and T.J.K. oversaw patient care. M.G., L.R., W.Z, A.W. and C.C. performed sample isolation and analysis. K.S. and D.N. performed statistical analysis. D.R., C.S., J.S., J.G.R., J.M.G., A.T-W. contributed to genomic data analysis. M.G., I.B., I.L., D.L., K.S., D.N., G.G. and C.J.W wrote the manuscript. All authors read and approved the final manuscript Contributions
ISSN:	0028-0836 1476-4687 1476-4687
DOI:	10.1038/s41586-019-1252-x