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Cancer recurrence times from a branching process model
As cancer advances, cells often spread from the primary tumor to other parts of the body and form metastases. This is the main cause of cancer related mortality. Here we investigate a conceptually simple model of metastasis formation where metastatic lesions are initiated at a rate which depends on...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6871767/ https://www.ncbi.nlm.nih.gov/pubmed/31751332 http://dx.doi.org/10.1371/journal.pcbi.1007423 |
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author | Avanzini, Stefano Antal, Tibor |
author_facet | Avanzini, Stefano Antal, Tibor |
author_sort | Avanzini, Stefano |
collection | PubMed |
description | As cancer advances, cells often spread from the primary tumor to other parts of the body and form metastases. This is the main cause of cancer related mortality. Here we investigate a conceptually simple model of metastasis formation where metastatic lesions are initiated at a rate which depends on the size of the primary tumor. The evolution of each metastasis is described as an independent branching process. We assume that the primary tumor is resected at a given size and study the earliest time at which any metastasis reaches a minimal detectable size. The parameters of our model are estimated independently for breast, colorectal, headneck, lung and prostate cancers. We use these estimates to compare predictions from our model with values reported in clinical literature. For some cancer types, we find a remarkably wide range of resection sizes such that metastases are very likely to be present, but none of them are detectable. Our model predicts that only very early resections can prevent recurrence, and that small delays in the time of surgery can significantly increase the recurrence probability. |
format | Online Article Text |
id | pubmed-6871767 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-68717672019-12-08 Cancer recurrence times from a branching process model Avanzini, Stefano Antal, Tibor PLoS Comput Biol Research Article As cancer advances, cells often spread from the primary tumor to other parts of the body and form metastases. This is the main cause of cancer related mortality. Here we investigate a conceptually simple model of metastasis formation where metastatic lesions are initiated at a rate which depends on the size of the primary tumor. The evolution of each metastasis is described as an independent branching process. We assume that the primary tumor is resected at a given size and study the earliest time at which any metastasis reaches a minimal detectable size. The parameters of our model are estimated independently for breast, colorectal, headneck, lung and prostate cancers. We use these estimates to compare predictions from our model with values reported in clinical literature. For some cancer types, we find a remarkably wide range of resection sizes such that metastases are very likely to be present, but none of them are detectable. Our model predicts that only very early resections can prevent recurrence, and that small delays in the time of surgery can significantly increase the recurrence probability. Public Library of Science 2019-11-21 /pmc/articles/PMC6871767/ /pubmed/31751332 http://dx.doi.org/10.1371/journal.pcbi.1007423 Text en © 2019 Avanzini, Antal http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Avanzini, Stefano Antal, Tibor Cancer recurrence times from a branching process model |
title | Cancer recurrence times from a branching process model |
title_full | Cancer recurrence times from a branching process model |
title_fullStr | Cancer recurrence times from a branching process model |
title_full_unstemmed | Cancer recurrence times from a branching process model |
title_short | Cancer recurrence times from a branching process model |
title_sort | cancer recurrence times from a branching process model |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6871767/ https://www.ncbi.nlm.nih.gov/pubmed/31751332 http://dx.doi.org/10.1371/journal.pcbi.1007423 |
work_keys_str_mv | AT avanzinistefano cancerrecurrencetimesfromabranchingprocessmodel AT antaltibor cancerrecurrencetimesfromabranchingprocessmodel |