Forecasting the Stochastic Vicious Cycle of Cancer Progression and Immune Response
Autor(a) principal: | |
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Data de Publicação: | 2021 |
Outros Autores: | , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | https://hdl.handle.net/10216/134160 |
Resumo: | It is accepted that cancer progression is a stochastic process, and there is a bifurcation in cancer cell count, which gets chaotic if not treated at preliminary stages. Therefore, strategies for fighting cancer at early stages are highly desired. However, the interaction of the immune system with cancer cells is not a straightforward process. The stochastic cell interactions lead to uncontrollable dynamics and sometimes to the death of the patient. A stochastic computational framework developed based on principles of the cancer-immune cell interaction is proposed in this article. The results obtained using the framework for breast cancer are close to the experimental findings, confirming that it can be a useful tool for identifying possible control measures. This study concludes that a control strategy based on stochastic modeling is promising and that a deep understanding of the interaction cell rates is essential for timely cancer control measures. (c) 2021 The Author(s) |
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Forecasting the Stochastic Vicious Cycle of Cancer Progression and Immune ResponseCiências Tecnológicas, Ciências médicas e da saúdeTechnological sciences, Medical and Health sciencesIt is accepted that cancer progression is a stochastic process, and there is a bifurcation in cancer cell count, which gets chaotic if not treated at preliminary stages. Therefore, strategies for fighting cancer at early stages are highly desired. However, the interaction of the immune system with cancer cells is not a straightforward process. The stochastic cell interactions lead to uncontrollable dynamics and sometimes to the death of the patient. A stochastic computational framework developed based on principles of the cancer-immune cell interaction is proposed in this article. The results obtained using the framework for breast cancer are close to the experimental findings, confirming that it can be a useful tool for identifying possible control measures. This study concludes that a control strategy based on stochastic modeling is promising and that a deep understanding of the interaction cell rates is essential for timely cancer control measures. (c) 2021 The Author(s)2021-072021-07-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleimage/pngapplication/pdfhttps://hdl.handle.net/10216/134160eng10.1016/j.rinp.2021.104420Muhammad IdreesAyesha SohailJoão Manuel R. S. Tavaresinfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-11-29T13:26:49Zoai:repositorio-aberto.up.pt:10216/134160Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T23:40:40.117726Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
Forecasting the Stochastic Vicious Cycle of Cancer Progression and Immune Response |
title |
Forecasting the Stochastic Vicious Cycle of Cancer Progression and Immune Response |
spellingShingle |
Forecasting the Stochastic Vicious Cycle of Cancer Progression and Immune Response Muhammad Idrees Ciências Tecnológicas, Ciências médicas e da saúde Technological sciences, Medical and Health sciences |
title_short |
Forecasting the Stochastic Vicious Cycle of Cancer Progression and Immune Response |
title_full |
Forecasting the Stochastic Vicious Cycle of Cancer Progression and Immune Response |
title_fullStr |
Forecasting the Stochastic Vicious Cycle of Cancer Progression and Immune Response |
title_full_unstemmed |
Forecasting the Stochastic Vicious Cycle of Cancer Progression and Immune Response |
title_sort |
Forecasting the Stochastic Vicious Cycle of Cancer Progression and Immune Response |
author |
Muhammad Idrees |
author_facet |
Muhammad Idrees Ayesha Sohail João Manuel R. S. Tavares |
author_role |
author |
author2 |
Ayesha Sohail João Manuel R. S. Tavares |
author2_role |
author author |
dc.contributor.author.fl_str_mv |
Muhammad Idrees Ayesha Sohail João Manuel R. S. Tavares |
dc.subject.por.fl_str_mv |
Ciências Tecnológicas, Ciências médicas e da saúde Technological sciences, Medical and Health sciences |
topic |
Ciências Tecnológicas, Ciências médicas e da saúde Technological sciences, Medical and Health sciences |
description |
It is accepted that cancer progression is a stochastic process, and there is a bifurcation in cancer cell count, which gets chaotic if not treated at preliminary stages. Therefore, strategies for fighting cancer at early stages are highly desired. However, the interaction of the immune system with cancer cells is not a straightforward process. The stochastic cell interactions lead to uncontrollable dynamics and sometimes to the death of the patient. A stochastic computational framework developed based on principles of the cancer-immune cell interaction is proposed in this article. The results obtained using the framework for breast cancer are close to the experimental findings, confirming that it can be a useful tool for identifying possible control measures. This study concludes that a control strategy based on stochastic modeling is promising and that a deep understanding of the interaction cell rates is essential for timely cancer control measures. (c) 2021 The Author(s) |
publishDate |
2021 |
dc.date.none.fl_str_mv |
2021-07 2021-07-01T00:00:00Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://hdl.handle.net/10216/134160 |
url |
https://hdl.handle.net/10216/134160 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.1016/j.rinp.2021.104420 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
image/png application/pdf |
dc.source.none.fl_str_mv |
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instname_str |
Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
instacron_str |
RCAAP |
institution |
RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
collection |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository.name.fl_str_mv |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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1799135720954134528 |