Evidence map›Paper›PMID 20656803›Full record

ArticleCancer research2010

Cell selection as driving force in lung and colon carcinogenesis.

Helmut Schöllnberger, Niko Beerenwinkel, Rudolf Hoogenveen, Paolo Vineis

Abstract read
In one paragraph

Article in Cancer research, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing 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

17 citing papers in PubMed.

  1. Article
  2. Dynamics of cell transformation in culture and its significance for tumor development in animals.Proceedings of the National Academy of Sciences of the United States of America · 2017
    Article
  3. Article
  4. Evolution of genetic instability in heterogeneous tumors.Journal of theoretical biology · 2016
    Article
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  6. Review
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  15. Article
  16. The early history of tumor virology: Rous, RIF, and RAV.Proceedings of the National Academy of Sciences of the United States of America · 2011
    Review
  17. 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

4 authors.

Helmut SchöllnbergerUniversity of Salzburg, Department of Materials Engineering and Physics, Salzburg, Austria. schoellnberger@helmholtz-muenchen.de
Niko Beerenwinkel
Rudolf Hoogenveen
Paolo Vineis

Funding

Austrian Science Fund FWF P 21630
6 · The paper itself

Abstract

Carcinogenesis is the result of mutations and subsequent clonal expansions of mutated, selectively advantageous cells. To investigate the relative contributions of mutation versus cell selection in tumorigenesis, we compared two mathematical models of carcinogenesis in two different cancer types: lung and colon. One approach is based on a population genetics model, the Wright-Fisher process, whereas the other approach is the two-stage clonal expansion model. We compared the dynamics of tumorigenesis predicted by the two models in terms of the time period until the first malignant cell appears, which will subsequently form a tumor. The mean waiting time to cancer has been calculated approximately for the evolutionary colon cancer model. Here, we derive new analytic approximations to the median waiting time for the two-stage lung cancer model and for a multistage approximation to the Wright-Fisher process. Both equations show that the waiting time to cancer is dominated by the selective advantage per mutation and the net clonal expansion rate, respectively, whereas the mutation rate has less effect. Our comparisons support the idea that the main driving force in lung and colon carcinogenesis is Darwinian cell selection.

Indexed as

Models, BiologicalModels, GeneticColonic NeoplasmsLung NeoplasmsStochastic Processes

Identifiers

PMID20656803
PMCPMC3085130

What OpenQuestion holds

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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.