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

Gerlee, P., Altrock, P. M., Malik, A., Krona, C., & Nelander, S. (2022). Autocrine signaling can explain the emergence of Allee effects in cancer cell populations. PLoS Computational Biology, 18(3): e1009844. doi:10.1371/journal.pcbi.1009844.

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Gerlee, Philip, Author
Altrock, Philipp M.1, Author                 
Malik, Adam, Author
Krona, Cecilia, Author
Nelander, Sven, Author
Affiliations:
1Department Evolutionary Theory (Traulsen), Max Planck Institute for Evolutionary Biology, Max Planck Society, ou_1445641              

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Free keywords: Allee effect; Growth factors; Cancers and neoplasms; Population density; Cell cycle and cell division; Autocrine signaling; Malignant tumors; Cell death
 Abstract: A common feature of tumour growth is the production, by the cancer cells themselves, of hormones known as growth factors that increase the rate of cell division. This type of signalling makes the growth rate of the tumour depend on the population size in a non-linear manner, and the growth rate might become low or negative for small population sizes. This is known as the Allee effect which has been studied extensively in ecology. We have developed a computational model that can explain the Allee effect in terms of growth factor signalling, and show by mathematical analysis of the model that the magnitude of the Allee effect depends on the ratio of cell death to proliferation, as well as the properties of the growth factor. In addition we show that the model is consistent with experimental observations from three different cell lines derived from the brain tumour glioblastoma. Our findings indicate that the Allee effect can be exploited in order to improve the treatment of glioblastoma patients.

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Language(s): eng - English
 Dates: 2021-07-092022-01-172022-03-03
 Publication Status: Published online
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
 Identifiers: DOI: 10.1371/journal.pcbi.1009844
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Title: PLoS Computational Biology
Source Genre: Journal
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Publ. Info: San Francisco, CA : Public Library of Science
Pages: - Volume / Issue: 18 (3) Sequence Number: e1009844 Start / End Page: - Identifier: ISSN: 1553-734X
CoNE: https://pure.mpg.de/cone/journals/resource/1000000000017180_1