Cargando…

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...

Descripción completa

Detalles Bibliográficos
Autores principales: Avanzini, Stefano, Antal, Tibor
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2019
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
_version_ 1783472429381713920
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