Measuring single cell divisions in human tissues from multi-region sequencing data

Benjamin Werner (), Jack Case, Marc J. Williams, Ketevan Chkhaidze, Daniel Temko, Javier Fernández-Mateos, George D. Cresswell, Daniel Nichol, William Cross, Inmaculada Spiteri, Weini Huang, Ian P. M. Tomlinson, Chris P. Barnes, Trevor A. Graham () and Andrea Sottoriva ()
Additional contact information
Benjamin Werner: The Institute of Cancer Research
Jack Case: The Institute of Cancer Research
Marc J. Williams: Queen Mary University London
Ketevan Chkhaidze: The Institute of Cancer Research
Daniel Temko: Queen Mary University London
Javier Fernández-Mateos: The Institute of Cancer Research
George D. Cresswell: The Institute of Cancer Research
Daniel Nichol: The Institute of Cancer Research
William Cross: Queen Mary University London
Inmaculada Spiteri: The Institute of Cancer Research
Weini Huang: Sun Yat-sen University
Ian P. M. Tomlinson: University of Birmingham
Chris P. Barnes: University College London
Trevor A. Graham: Queen Mary University London
Andrea Sottoriva: The Institute of Cancer Research

Nature Communications, 2020, vol. 11, issue 1, 1-9

Abstract: Abstract 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.

Date: 2020
References: Add references at CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
https://www.nature.com/articles/s41467-020-14844-6 Abstract (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:nat:natcom:v:11:y:2020:i:1:d:10.1038_s41467-020-14844-6

Ordering information: This journal article can be ordered from
https://www.nature.com/ncomms/

DOI: 10.1038/s41467-020-14844-6

Access Statistics for this article

Nature Communications is currently edited by Nathalie Le Bot, Enda Bergin and Fiona Gillespie

More articles in Nature Communications from Nature
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().