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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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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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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. |
format | Online Article Text |
id | pubmed-10572824 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
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 |
work_keys_str_mv | AT smiejajaroslaw mathematicalmodelingsupportforlungcancertherapyashortreview |