Autocrine signaling can explain the emergence of Allee effects in cancer cell populations.


Journal

PLoS computational biology
ISSN: 1553-7358
Titre abrégé: PLoS Comput Biol
Pays: United States
ID NLM: 101238922

Informations de publication

Date de publication:
03 2022
Historique:
received: 09 07 2021
accepted: 17 01 2022
revised: 15 03 2022
pubmed: 4 3 2022
medline: 13 4 2022
entrez: 3 3 2022
Statut: epublish

Résumé

In many human cancers, the rate of cell growth depends crucially on the size of the tumor cell population. Low, zero, or negative growth at low population densities is known as the Allee effect; this effect has been studied extensively in ecology, but so far lacks a good explanation in the cancer setting. Here, we formulate and analyze an individual-based model of cancer, in which cell division rates are increased by the local concentration of an autocrine growth factor produced by the cancer cells themselves. We show, analytically and by simulation, that autocrine signaling suffices to cause both strong and weak Allee effects. Whether low cell densities lead to negative (strong effect) or reduced (weak effect) growth rate depends directly on the ratio of cell death to proliferation, and indirectly on cellular dispersal. Our model is consistent with experimental observations from three patient-derived brain tumor cell lines grown at different densities. We propose that further studying and quantifying population-wide feedback, impacting cell growth, will be central for advancing our understanding of cancer dynamics and treatment, potentially exploiting Allee effects for therapy.

Identifiants

pubmed: 35239640
doi: 10.1371/journal.pcbi.1009844
pii: PCOMPBIOL-D-21-01273
pmc: PMC8923455
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

e1009844

Déclaration de conflit d'intérêts

I have read the journal’s policy and the authors of this manuscript have the following competing interests: PA is consulting for CRISPR Therapeutics, Cambridge, MA and has received research funding (not for this work) from Kite Pharma (a Gilead company). PA’s funding from Kite Pharma does not constitute a conflict of interest for the current study.

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Auteurs

Philip Gerlee (P)

Mathematical Sciences, Chalmers University of Technology, Gothenburg, Sweden.
Mathematical Sciences, University of Gothenburg, Gothenburg, Sweden.

Philipp M Altrock (PM)

Department of Integrated Mathematical Oncology, Moffitt Cancer Center, Tampa, Florida, United States of America.
Department of Evolutionary Theory, Max Planck Institute for Evolutionary Biology, Plön, Germany.

Adam Malik (A)

Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden.

Cecilia Krona (C)

Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden.

Sven Nelander (S)

Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden.

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Classifications MeSH