Evidence map›Paper›PMID 32223898›Full record

ArticleeLife2020

Measuring the distribution of fitness effects in somatic evolution by combining clonal dynamics with dN/dS ratios.

Marc J Williams, Luis Zapata, Benjamin Werner, Chris P Barnes, Andrea Sottoriva, Trevor A Graham

Open access · goldAbstract read
In one paragraph

Article in eLife, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.

0numbers the graph read from it
0cells of the map it votes in
29citing papers in PubMed
6.1field-weighted citation impact, top 3% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

29 citing papers in PubMed, 60 citations in OpenAlex.

  1. Article
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  8. The adaptive state determines the impact of mutations on evolving populations.Proceedings of the National Academy of Sciences of the United States of America · 2025
    Article
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  16. Cancer driver mutations: predictions and reality.Trends in molecular medicine · 2023
    Review
  17. Article
  18. Article
  19. Article
  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors at 4 institutions in 2 countries.

Marc J WilliamsCentre for Genomics and Computational Biology, Barts Cancer Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, United Kingdom.ORCID 0000-0001-5524-4174
Luis ZapataEvolutionary Genomics and Modelling Lab, Centre for Evolution and Cancer, The Institute of Cancer Research, London, United Kingdom.ORCID 0000-0002-1386-2019
Benjamin WernerCentre for Genomics and Computational Biology, Barts Cancer Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, United Kingdom.ORCID 0000-0002-6857-8699
Chris P BarnesDepartment of Cell and Developmental Biology, University College London, London, United Kingdom.ORCID 0000-0002-9459-1395
Andrea SottorivaEvolutionary Genomics and Modelling Lab, Centre for Evolution and Cancer, The Institute of Cancer Research, London, United Kingdom.ORCID 0000-0001-6709-9533
Trevor A GrahamCentre for Genomics and Computational Biology, Barts Cancer Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, United Kingdom.ORCID 0000-0001-9582-1597
Institute of Cancer Research · GBQueen Mary University of London · GBMemorial Sloan Kettering Cancer Center · USUniversity College London · GB

Funding

X-RAY CRYSTALLOGRAPHYP30CA008748 · NCI · SLOAN-KETTERING INSTITUTE FOR CANCER RES · PI Hongbiao Carl Lekaye · 1985 to 2026
$347.4M
The Role of the Microbiome in Cancer Suppression and Susceptibility Across SpeciesU54CA217376 · NCI · ARIZONA STATE UNIVERSITY-TEMPE CAMPUS · PI MALEY, CARLO · 2018 to 2022
$8.6M
Cancer Research UK 19771Cancer Research UK 22909Cancer Research UK A19771Cancer Research UK A22909NCI NIH HHS P30 CA008748NCI NIH HHS U54 CA217376Wellcome Trust
6 · The paper itself

Abstract

The distribution of fitness effects (DFE) defines how new mutations spread through an evolving population. The ratio of non-synonymous to synonymous mutations (dN/dS) has become a popular method to detect selection in somatic cells. However the link, in somatic evolution, between dN/dS values and fitness coefficients is missing. Here we present a quantitative model of somatic evolutionary dynamics that determines the selective coefficients of individual driver mutations from dN/dS estimates. We then measure the DFE for somatic mutant clones in ostensibly normal oesophagus and skin. We reveal a broad distribution of fitness effects, with the largest fitness increases found for TP53 and NOTCH1 mutants (proliferative bias 1-5%). This study provides the theoretical link between dN/dS values and selective coefficients in somatic evolution, and measures the DFE of mutations in human tissues.

Indexed as

Clonal EvolutionEvolution, MolecularGenetic FitnessMutationEsophagusHumansModels, TheoreticalPhylogenyReceptor, Notch1SkinTumor Suppressor Protein p53NOTCH1 protein, humanReceptor, Notch1TP53 protein, humanTumor Suppressor Protein p53cancer evolutioncomputational biologydistribution of fitness effectsdn/dsgeneticsgenomicshumanpopulation geneticssomatic evolutionsystems biology

Identifiers

PMID32223898
PMCPMC7105384
OpenAlexW3013452103

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.