Evidence map›Paper›PMID 24478797›Full record

ArticleEvolutionary applications2013

Dynamics of growth factor production in monolayers of cancer cells and evolution of resistance to anticancer therapies.

Marco Archetti

Open access · goldAbstract read
In one paragraph

Article in Evolutionary applications, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed
1.7field-weighted citation impact, top 18% 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

18 citing papers in PubMed, 33 citations in OpenAlex.

  1. Fraternal cooperation of hierarchical cancer parallels metazoan multicellularity and eusociality.Biological reviews of the Cambridge Philosophical Society · 2026
    Review
  2. Article
  3. Review
  4. Frequency-dependent returns in nonlinear public goods games.Journal of the Royal Society, Interface · 2024
    Article
  5. Spatial simulation of autologous cell defection for cancer treatment.Evolution, medicine, and public health · 2023
    Article
  6. Review
  7. Article
  8. Article
  9. Article
  10. Review
  11. Evolution of cooperation in an epithelium.Journal of the Royal Society, Interface · 2019
    Article
  12. Review
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. 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 at 1 institution in 1 country.

Marco ArchettiSchool of Biological Sciences, University of East Anglia Norwich, UK.
University of East Anglia · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Tumor heterogeneity is well documented for many characters, including the production of growth factors, which improve tumor proliferation and promote resistance against apoptosis and against immune reaction. What maintains heterogeneity remains an open question that has implications for diagnosis and treatment. While it has been suggested that therapies targeting growth factors are robust against evolved resistance, current therapies against growth factors, like antiangiogenic drugs, are not effective in the long term, as resistant mutants can evolve and lead to relapse. We use evolutionary game theory to study the dynamics of the production of growth factors by monolayers of cancer cells and to understand the effect of therapies that target growth factors. The dynamics depend on the production cost of the growth factor, on its diffusion range and on the type of benefit it confers to the cells. Stable heterogeneity is a typical outcome of the dynamics, while a pure equilibrium of nonproducer cells is possible under certain conditions. Such pure equilibrium can be the goal of new anticancer therapies. We show that current therapies, instead, can be effective only if growth factors are almost completely eliminated and if the reduction is almost immediate.

Indexed as

anticancer therapycancercooperationevolutionary game theorygrowth factorsheterogeneitypolymorphismpublic goodssomatic evolution

Identifiers

PMID24478797
PMCPMC3901545
OpenAlexW2043119216

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.