Evidence map›Paper›PMID 29347918›Full record

ArticleBMC cancer2018

Somatic evolutionary timings of driver mutations.

Karen Gomez, Sayaka Miura, Louise A Huuki, Brianna S Spell, Jeffrey P Townsend, Sudhir Kumar

Abstract read
In one paragraph

Article in BMC cancer, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed
–field-weighted citation impact
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

19 citing papers in PubMed.

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  19. Neutral Theory and the Somatic Evolution of Cancer.Molecular biology and evolution · 2018
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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.

Karen GomezInstitute for Genomics and Evolutionary Medicine, Sudhir Kumar, SERC 602A, 1925 N. 12th Street, Philadelphia, PA, 19122, USA.
Sayaka MiuraInstitute for Genomics and Evolutionary Medicine, Sudhir Kumar, SERC 602A, 1925 N. 12th Street, Philadelphia, PA, 19122, USA.
Louise A HuukiInstitute for Genomics and Evolutionary Medicine, Sudhir Kumar, SERC 602A, 1925 N. 12th Street, Philadelphia, PA, 19122, USA.
Brianna S SpellInstitute for Genomics and Evolutionary Medicine, Sudhir Kumar, SERC 602A, 1925 N. 12th Street, Philadelphia, PA, 19122, USA.
Jeffrey P TownsendDepartment of Biostatistics, Yale School of Public Health, New Haven, Connecticut, 06510, USA.
Sudhir KumarInstitute for Genomics and Evolutionary Medicine, Sudhir Kumar, SERC 602A, 1925 N. 12th Street, Philadelphia, PA, 19122, USA. s.kumar@temple.edu.

Funding

EVOLUTIONARY BIOINFORMATICS OF TUMOR PROFILESR01LM012487 · NLM · TEMPLE UNIV OF THE COMMONWEALTH · PI KUMAR, SUDHIR · 2016 to 2018
$1.0M
Bayesian Evolution-Aware Methods for tumor single cell sequencesR21LM012758 · NLM · TEMPLE UNIV OF THE COMMONWEALTH · PI MIURA, SAYAKA · 2017 to 2018
$392k
NLM NIH HHS R01 LM012487NLM NIH HHS R21 LM012758U.S. National Library of Medicine LM012487U.S. National Library of Medicine LM012758
6 · The paper itself

Abstract

backgroundA unified analysis of DNA sequences from hundreds of tumors concluded that the driver mutations primarily occur in the earliest stages of cancer formation, with relatively few driver mutation events detected in the late-arising subclones. However, emerging evidence from the sequencing of multiple tumors and tumor regions per individual suggests that late-arising subclones with additional driver mutations are underestimated in single-sample analyses.

methodsTo test whether driver mutations generally map to early tumor development, we examined multi-regional tumor sequencing data from 101 individuals reported in 11 published studies. Following previous studies, we annotated mutations as early-arising when all tumors/regions had those mutations (ubiquitous). We then inferred the fraction of mutations occurring early and compared it with late-arising mutations that were found in only single tumors/regions.

resultsWhile a large fraction of driver mutations in tumors occurred relatively early in cancers, later driver mutations occurred at least as frequently as the early drivers in a substantial number of patients. This result was robust to many different approaches to annotate driver mutations. The relative frequency of early and late driver mutations varied among patients of the same cancer type and in different cancer types. We found that previous reports of the preponderance of early driver mutations were primarily informed by analysis of single tumor variant allele profiles, with which it is challenging to clearly distinguish between early and late drivers.

conclusionsThe origin and preponderance of new driver mutations are not limited to early stages of tumor evolution, with different tumors and regions showing distinct driver mutations and, consequently, distinct characteristics. Therefore, tumors with extensive intratumor heterogeneity appear to have many newly acquired drivers.

Indexed as

Base SequenceCarcinogenesisClonal EvolutionGenetic HeterogeneityHumansMutationNeoplasmsSequence Analysis, DNADriver mutationPrivate mutationSomatic mutationUbiquitous mutation

Identifiers

PMID29347918
PMCPMC5774140

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Registered trials

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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.