Evidence map›Paper›PMID 36853375›Full record

ArticleMedical oncology (Northwood, London, England)2023

Modeling cancer's ecological and evolutionary dynamics.

Anuraag Bukkuri, Kenneth J Pienta, Ian Hockett, Robert H Austin, Emma U Hammarlund, Sarah R Amend, Joel S Brown

Abstract read
In one paragraph

Article in Medical oncology (Northwood, London, England), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Review
  5. Review
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

7 authors.

Anuraag BukkuriCancer Biology and Evolution Program and Department of Integrated Mathematical Oncology, Moffitt Cancer Center, Tampa, USA. anuraag.bukkuri@med.lu.se.ORCID http://orcid.org/0000-0002-3616-626X
Kenneth J PientaThe Brady Urological Institute, Johns Hopkins School of Medicine, Baltimore, USA.
Ian HockettThe Brady Urological Institute, Johns Hopkins School of Medicine, Baltimore, USA.
Robert H AustinDepartment of Physics, Princeton University, Princeton, USA.
Emma U HammarlundTissue Development and Evolution Research Group, Department of Laboratory Medicine, Lund University, Lund, Sweden.
Sarah R AmendThe Brady Urological Institute, Johns Hopkins School of Medicine, Baltimore, USA.
Joel S BrownCancer Biology and Evolution Program and Department of Integrated Mathematical Oncology, Moffitt Cancer Center, Tampa, USA.

Funding

TRANS_NETWORK PROJECTSU54CA143803 · NCI · PRINCETON UNIVERSITY · PI AUSTIN, ROBERT H. · 2009 to 2013
$14.2M
Eco-evolutionary drivers of clonal dynamics during UV-induced skin carcinogenesis (PQ3)R01CA258089 · NCI · H. LEE MOFFITT CANCER CTR & RES INST · PI BROWN, JOEL, TSAI, KENNETH Y · 2021 to 2025
$3.1M
Mechanisms That Regulate Dormancy of Disseminated Tumor Cells in the Bone MarrowU54CA163124 · NCI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI SHIOZAWA, YUSUKE · 2011 to 2015
$3.0M
Reactive Stroma and Tumor Associated Macrophages in Prostate Cancer ProgressionU01CA143055 · NCI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI PIENTA, KENNETH J., ROWLEY, DAVID R · 2010 to 2014
$2.7M
NCI NIH HHS 193489NCI NIH HHS CA093900NCI NIH HHS CA143055NCI NIH HHS CA163124NCI NIH HHS R01 CA258089NCI NIH HHS R01CA258089NCI NIH HHS U01 CA143055NCI NIH HHS U54CA143803NCI NIH HHS U54 CA163124
6 · The paper itself

Abstract

In this didactic paper, we present a theoretical modeling framework, called the G-function, that integrates both the ecology and evolution of cancer to understand oncogenesis. The G-function has been used in evolutionary ecology, but has not been widely applied to problems in cancer. Here, we build the G-function framework from fundamental Darwinian principles and discuss how cancer can be seen through the lens of ecology, evolution, and game theory. We begin with a simple model of cancer growth and add on components of cancer cell competition and drug resistance. To aid in exploration of eco-evolutionary modeling with this approach, we also present a user-friendly software tool. By the end of this paper, we hope that readers will be able to construct basic G function models and grasp the usefulness of the framework to understand the games cancer plays in a biologically mechanistic fashion.

Indexed as

CarcinogenesisCell Transformation, NeoplasticHumansSoftwareCancer evolutionEco-evolutionary dynamicsEvolutionary game theoryMathematical modelingResistance

Identifiers

PMID36853375
PMCPMC9974726

What Socratic 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 Socratic graph.