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Mathematical Modeling Support for Lung Cancer Therapy—A Short Review

The paper presents a review of models that can be used to describe dynamics of lung cancer growth and its response to treatment at both cell population and intracellular processes levels. To address the latter, models of signaling pathways associated with cellular responses to treatment are overview...

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Autor principal: Smieja, Jaroslaw
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10572824/
https://www.ncbi.nlm.nih.gov/pubmed/37833963
http://dx.doi.org/10.3390/ijms241914516
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author Smieja, Jaroslaw
author_facet Smieja, Jaroslaw
author_sort Smieja, Jaroslaw
collection PubMed
description The paper presents a review of models that can be used to describe dynamics of lung cancer growth and its response to treatment at both cell population and intracellular processes levels. To address the latter, models of signaling pathways associated with cellular responses to treatment are overviewed. First, treatment options for lung cancer are discussed, and main signaling pathways and regulatory networks are briefly reviewed. Then, approaches used to model specific therapies are discussed. Following that, models of intracellular processes that are crucial in responses to therapies are presented. The paper is concluded with a discussion of the applicability of the presented approaches in the context of lung cancer.
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spelling pubmed-105728242023-10-14 Mathematical Modeling Support for Lung Cancer Therapy—A Short Review Smieja, Jaroslaw Int J Mol Sci Review The paper presents a review of models that can be used to describe dynamics of lung cancer growth and its response to treatment at both cell population and intracellular processes levels. To address the latter, models of signaling pathways associated with cellular responses to treatment are overviewed. First, treatment options for lung cancer are discussed, and main signaling pathways and regulatory networks are briefly reviewed. Then, approaches used to model specific therapies are discussed. Following that, models of intracellular processes that are crucial in responses to therapies are presented. The paper is concluded with a discussion of the applicability of the presented approaches in the context of lung cancer. MDPI 2023-09-25 /pmc/articles/PMC10572824/ /pubmed/37833963 http://dx.doi.org/10.3390/ijms241914516 Text en © 2023 by the author. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Review
Smieja, Jaroslaw
Mathematical Modeling Support for Lung Cancer Therapy—A Short Review
title Mathematical Modeling Support for Lung Cancer Therapy—A Short Review
title_full Mathematical Modeling Support for Lung Cancer Therapy—A Short Review
title_fullStr Mathematical Modeling Support for Lung Cancer Therapy—A Short Review
title_full_unstemmed Mathematical Modeling Support for Lung Cancer Therapy—A Short Review
title_short Mathematical Modeling Support for Lung Cancer Therapy—A Short Review
title_sort mathematical modeling support for lung cancer therapy—a short review
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10572824/
https://www.ncbi.nlm.nih.gov/pubmed/37833963
http://dx.doi.org/10.3390/ijms241914516
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