Evidence map›Paper›PMID 24511383›Full record

ReviewInterface focus2013

Exploiting ecological principles to better understand cancer progression and treatment.

David Basanta, Alexander R A Anderson

Abstract readReview
In one paragraph

Review in Interface focus, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 59 papers.

0numbers the graph read from it
0cells of the map it votes in
59citing 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

59 citing papers in PubMed.

  1. Review
  2. Review
  3. Review
  4. Review
  5. Article
  6. Article
  7. Review
  8. Review
  9. Article
  10. A modelling framework for cancer ecology and evolution.Journal of the Royal Society, Interface · 2024
    Article
  11. Modeling tumors as species-rich ecological communities.bioRxiv : the preprint server for biology · 2024
    Article
  12. Article
  13. Article
  14. Evolutionary Dynamics and Intermittent Therapy for Metastatic Cancers.Journal of clinical oncology : official journal of the American Society of Clinical Oncology · 2023
    Article
  15. Treatment of evolving cancers will require dynamic decision support.Annals of oncology : official journal of the European Society for Medical Oncology · 2023
    Review
  16. Article
  17. Article
  18. Review
  19. Review
  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

2 authors.

David BasantaIntegrated Mathematical Oncology , Moffitt Cancer Centre , Tampa, FL 33629 , USA.
Alexander R A AndersonIntegrated Mathematical Oncology , Moffitt Cancer Centre , Tampa, FL 33629 , USA.

Funding

Predicting Prostate Cancer AggressivenessU01CA151924 · NCI · H. LEE MOFFITT CANCER CTR & RES INST · PI ANDERSON, ALEXANDER ROBERTSON ALLAN, AYALA, GUSTAVO ENRIQUE · 2011 to 2015
$2.8M
NCI NIH HHS U01 CA151924
6 · The paper itself

Abstract

A small but growing number of people are finding interesting parallels between ecosystems as studied by ecologists (think of a savannah or the Amazon rainforest or a coral reef) and tumours. The idea of viewing cancer from an ecological perspective has many implications but, basically, it means that we should not see cancer just as a group of mutated cells. A more useful definition of cancer is to consider it a disruption in the complex balance of many interacting cellular and microenvironmental elements in a specific organ. This perspective means that organs undergoing carcinogenesis should be seen as sophisticated ecosystems in homoeostasis that cancer cells can disrupt. It also makes cancer seem even more complex but may ultimately provide insights that make it more treatable. Here, we discuss how ecological principles can be used to better understand cancer progression and treatment, using several mathematical and computational models to illustrate our argument.

Indexed as

cancerecologyheterogeneityhomoeostasisinteractionsmathematical model

Identifiers

PMID24511383
PMCPMC3915838

What OpenQuestion holds

Textmetadata
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.