Evidence map›Paper›PMID 31953602›Full record

ArticleBulletin of mathematical biology2020

Mix and Match: Phenotypic Coexistence as a Key Facilitator of Cancer Invasion.

Maximilian A R Strobl, Andrew L Krause, Mehdi Damaghi, Robert Gillies, Alexander R A Anderson, Philip K Maini

Open access · hybridAbstract read
In one paragraph

Article in Bulletin of mathematical biology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
1.1field-weighted citation impact, top 26% 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

9 citing papers in PubMed, 23 citations in OpenAlex.

  1. Article
  2. Review
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  7. Travelling-wave analysis of a model of tumour invasion with degenerate, cross-dependent diffusion.Proceedings. Mathematical, physical, and engineering sciences · 2021
    Article
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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

6 authors at 2 institutions in 2 countries.

Maximilian A R StroblWolfson Centre for Mathematical Biology, Mathematical Institute, University of Oxford, Radcliffe Observatory Quarter, OX2 6GG, Oxford, UK. maximilian.strobl@maths.ox.ac.uk.
Andrew L KrauseWolfson Centre for Mathematical Biology, Mathematical Institute, University of Oxford, Radcliffe Observatory Quarter, OX2 6GG, Oxford, UK.
Mehdi DamaghiDepartment of Cancer Physiology, Moffitt Cancer Center, Magnolia Drive, Tampa, 12902, USA.
Robert GilliesDepartment of Cancer Physiology, Moffitt Cancer Center, Magnolia Drive, Tampa, 12902, USA.
Alexander R A AndersonDepartment of Integrated Mathematical Oncology, Moffitt Cancer Center, Magnolia Drive, Tampa, 12902, USA.
Philip K MainiWolfson Centre for Mathematical Biology, Mathematical Institute, University of Oxford, Radcliffe Observatory Quarter, OX2 6GG, Oxford, UK.
Moffitt Cancer Center · USUniversity of Oxford · GB

Funding

"Research Supplement to Promote Diversity in Health-Related Research", as part of Moffitt PS-OC, "Cancer as a Complex adaptive System"U54CA193489 · NCI · H. LEE MOFFITT CANCER CTR & RES INST · PI ANDERSON, ALEXANDER ROBERTSON ALLAN, GATENBY, ROBERT A · 2015 to 2020
$12.5M
Eco-Evolutionary dynamics of NSCLC to immunotherapy: Response and ResistanceU01CA232382 · NCI · H. LEE MOFFITT CANCER CTR & RES INST · PI ANDERSON, ALEXANDER ROBERTSON ALLAN, ANTONIA, SCOTT J. · 2018 to 2022
$3.3M
Medical Research CouncilNCI NIH HHS U01 CA232382NCI NIH HHS U54 CA193489
6 · The paper itself

Abstract

Invasion of healthy tissue is a defining feature of malignant tumours. Traditionally, invasion is thought to be driven by cells that have acquired all the necessary traits to overcome the range of biological and physical defences employed by the body. However, in light of the ever-increasing evidence for geno- and phenotypic intra-tumour heterogeneity, an alternative hypothesis presents itself: could invasion be driven by a collection of cells with distinct traits that together facilitate the invasion process? In this paper, we use a mathematical model to assess the feasibility of this hypothesis in the context of acid-mediated invasion. We assume tumour expansion is obstructed by stroma which inhibits growth and extra-cellular matrix (ECM) which blocks cancer cell movement. Further, we assume that there are two types of cancer cells: (i) a glycolytic phenotype which produces acid that kills stromal cells and (ii) a matrix-degrading phenotype that locally remodels the ECM. We extend the Gatenby-Gawlinski reaction-diffusion model to derive a system of five coupled reaction-diffusion equations to describe the resulting invasion process. We characterise the spatially homogeneous steady states and carry out a simulation study in one spatial dimension to determine how the tumour develops as we vary the strength of competition between the two phenotypes. We find that overall tumour growth is most extensive when both cell types can stably coexist, since this allows the cells to locally mix and benefit most from the combination of traits. In contrast, when inter-species competition exceeds intra-species competition the populations spatially separate and invasion arrests either: (i) rapidly (matrix-degraders dominate) or (ii) slowly (acid-producers dominate). Overall, our work demonstrates that the spatial and ecological relationship between a heterogeneous population of tumour cells is a key factor in determining their ability to cooperate. Specifically, we predict that tumours in which different phenotypes coexist stably are more invasive than tumours in which phenotypes are spatially separated.

Indexed as

Models, BiologicalAcidsCell MovementComputer SimulationExtracellular MatrixGlycolysisHumansMathematical ConceptsMatrix MetalloproteinasesNeoplasm InvasivenessPhenotypeStromal CellsTumor MicroenvironmentAcidsMatrix MetalloproteinasesCoexistence theoryCooperationReaction–diffusionTravelling wavesTumour invasion

Identifiers

PMID31953602
PMCPMC6968991
OpenAlexW3000324989

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.