Measuring single cell divisions in human tissues from multi-region sequencing data.
Journal
Nature communications
ISSN: 2041-1723
Titre abrégé: Nat Commun
Pays: England
ID NLM: 101528555
Informations de publication
Date de publication:
25 02 2020
25 02 2020
Historique:
received:
05
09
2019
accepted:
29
01
2020
entrez:
27
2
2020
pubmed:
27
2
2020
medline:
23
5
2020
Statut:
epublish
Résumé
Both normal tissue development and cancer growth are driven by a branching process of cell division and mutation accumulation that leads to intra-tissue genetic heterogeneity. However, quantifying somatic evolution in humans remains challenging. Here, we show that multi-sample genomic data from a single time point of normal and cancer tissues contains information on single-cell divisions. We present a new theoretical framework that, applied to whole-genome sequencing data of healthy tissue and cancer, allows inferring the mutation rate and the cell survival/death rate per division. On average, we found that cells accumulate 1.14 mutations per cell division in healthy haematopoiesis and 1.37 mutations per division in brain development. In both tissues, cell survival was maximal during early development. Analysis of 131 biopsies from 16 tumours showed 4 to 100 times increased mutation rates compared to healthy development and substantial inter-patient variation of cell survival/death rates.
Identifiants
pubmed: 32098957
doi: 10.1038/s41467-020-14844-6
pii: 10.1038/s41467-020-14844-6
pmc: PMC7042311
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
1035Subventions
Organisme : Wellcome Trust
ID : 209409/Z/17/Z
Pays : United Kingdom
Organisme : Cancer Research UK
ID : A19771
Pays : United Kingdom
Organisme : Cancer Research UK
ID : A22909
Pays : United Kingdom
Organisme : Wellcome Trust
ID : 202778/Z/16/Z
Pays : United Kingdom
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