Evidence map›Paper›PMID 39358357›Full record

ReviewNPJ systems biology and applications2024

Neutral evolution of rare cancer mutations in the computer and the clinic.

Robert A Beckman

Abstract readReview
In one paragraph

Review in NPJ systems biology and applications, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. 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

1 author.

Robert A BeckmanDepartment of Oncology, Georgetown University Medical Center, Washington, DC, USA. eniac1915@gmail.com.

Funding

U.S. Department of Defense (United States Department of Defense) #W81XWH-20-1-0760
6 · The paper itself

Abstract

A distinct model of neutral evolution of rare cancer mutations is described and contrasted with models relying on the infinite sites approximation (that a specific mutation arises in only one cell at any instant). An explosion of genetic diversity is predicted at clinical cell numbers and may explain the progressive refractoriness of cancers during a clinical course. The widely used infinite sites assumption may not be applicable for clinical cancers.

Indexed as

MutationNeoplasmsComputer SimulationEvolution, MolecularGenetic VariationHumansModels, Genetic

Identifiers

PMID39358357
PMCPMC11447017

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.