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Tumor Biochemical Heterogeneity and Cancer Radiochemotherapy: Network Breakdown Zone-Model

Breakdowns of two-zone random networks of the Erdős–Rényi type are investigated. They are used as mathematical models for understanding the incompleteness of the tumor network breakdown under radiochemotherapy, an incompleteness that may result from a tumor’s physical and/or chemical heterogeneity....

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Autores principales: Dimou, Argyris, Argyrakis, Panos, Kopelman, Raoul
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9407148/
https://www.ncbi.nlm.nih.gov/pubmed/36010733
http://dx.doi.org/10.3390/e24081069
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author Dimou, Argyris
Argyrakis, Panos
Kopelman, Raoul
author_facet Dimou, Argyris
Argyrakis, Panos
Kopelman, Raoul
author_sort Dimou, Argyris
collection PubMed
description Breakdowns of two-zone random networks of the Erdős–Rényi type are investigated. They are used as mathematical models for understanding the incompleteness of the tumor network breakdown under radiochemotherapy, an incompleteness that may result from a tumor’s physical and/or chemical heterogeneity. Mathematically, having a reduced node removal probability in the network’s inner zone hampers the network’s breakdown. The latter is described quantitatively as a function of reduction in the inner zone’s removal probability, where the network breakdown is described in terms of the largest remaining clusters and their size distributions. The effects on the efficacy of radiochemotherapy due to the tumor micro-environment (TME)’s chemical make-up, and its heterogeneity, are discussed, with the goal of using such TME chemical heterogeneity imaging to inform precision oncology.
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spelling pubmed-94071482022-08-26 Tumor Biochemical Heterogeneity and Cancer Radiochemotherapy: Network Breakdown Zone-Model Dimou, Argyris Argyrakis, Panos Kopelman, Raoul Entropy (Basel) Article Breakdowns of two-zone random networks of the Erdős–Rényi type are investigated. They are used as mathematical models for understanding the incompleteness of the tumor network breakdown under radiochemotherapy, an incompleteness that may result from a tumor’s physical and/or chemical heterogeneity. Mathematically, having a reduced node removal probability in the network’s inner zone hampers the network’s breakdown. The latter is described quantitatively as a function of reduction in the inner zone’s removal probability, where the network breakdown is described in terms of the largest remaining clusters and their size distributions. The effects on the efficacy of radiochemotherapy due to the tumor micro-environment (TME)’s chemical make-up, and its heterogeneity, are discussed, with the goal of using such TME chemical heterogeneity imaging to inform precision oncology. MDPI 2022-08-02 /pmc/articles/PMC9407148/ /pubmed/36010733 http://dx.doi.org/10.3390/e24081069 Text en © 2022 by the authors. 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 Article
Dimou, Argyris
Argyrakis, Panos
Kopelman, Raoul
Tumor Biochemical Heterogeneity and Cancer Radiochemotherapy: Network Breakdown Zone-Model
title Tumor Biochemical Heterogeneity and Cancer Radiochemotherapy: Network Breakdown Zone-Model
title_full Tumor Biochemical Heterogeneity and Cancer Radiochemotherapy: Network Breakdown Zone-Model
title_fullStr Tumor Biochemical Heterogeneity and Cancer Radiochemotherapy: Network Breakdown Zone-Model
title_full_unstemmed Tumor Biochemical Heterogeneity and Cancer Radiochemotherapy: Network Breakdown Zone-Model
title_short Tumor Biochemical Heterogeneity and Cancer Radiochemotherapy: Network Breakdown Zone-Model
title_sort tumor biochemical heterogeneity and cancer radiochemotherapy: network breakdown zone-model
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9407148/
https://www.ncbi.nlm.nih.gov/pubmed/36010733
http://dx.doi.org/10.3390/e24081069
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