Cargando…

The Quest to Quantify Selective and Synergistic Effects of Plasma for Cancer Treatment: Insights from Mathematical Modeling

Cold atmospheric plasma (CAP) and plasma-treated liquids (PTLs) have recently become a promising option for cancer treatment, but the underlying mechanisms of the anti-cancer effect are still to a large extent unknown. Although hydrogen peroxide ([Formula: see text]) has been recognized as the major...

Descripción completa

Detalles Bibliográficos
Autores principales: Bengtson, Charlotta, Bogaerts, Annemie
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8126141/
https://www.ncbi.nlm.nih.gov/pubmed/34068601
http://dx.doi.org/10.3390/ijms22095033
_version_ 1783693711604973568
author Bengtson, Charlotta
Bogaerts, Annemie
author_facet Bengtson, Charlotta
Bogaerts, Annemie
author_sort Bengtson, Charlotta
collection PubMed
description Cold atmospheric plasma (CAP) and plasma-treated liquids (PTLs) have recently become a promising option for cancer treatment, but the underlying mechanisms of the anti-cancer effect are still to a large extent unknown. Although hydrogen peroxide ([Formula: see text]) has been recognized as the major anti-cancer agent of PTL and may enable selectivity in a certain concentration regime, the co-existence of nitrite can create a synergistic effect. We develop a mathematical model to describe the key species and features of the cellular response toward PTL. From the numerical solutions, we define a number of dependent variables, which represent feasible measures to quantify cell susceptibility in terms of the [Formula: see text] membrane diffusion rate constant and the intracellular catalase concentration. For each of these dependent variables, we investigate the regimes of selective versus non-selective, and of synergistic versus non-synergistic effect to evaluate their potential role as a measure of cell susceptibility. Our results suggest that the maximal intracellular [Formula: see text] concentration, which in the selective regime is almost four times greater for the most susceptible cells compared to the most resistant cells, could be used to quantify the cell susceptibility toward exogenous [Formula: see text]. We believe our theoretical approach brings novelty to the field of plasma oncology, and more broadly, to the field of redox biology, by proposing new ways to quantify the selective and synergistic anti-cancer effect of PTL in terms of inherent cell features.
format Online
Article
Text
id pubmed-8126141
institution National Center for Biotechnology Information
language English
publishDate 2021
publisher MDPI
record_format MEDLINE/PubMed
spelling pubmed-81261412021-05-17 The Quest to Quantify Selective and Synergistic Effects of Plasma for Cancer Treatment: Insights from Mathematical Modeling Bengtson, Charlotta Bogaerts, Annemie Int J Mol Sci Article Cold atmospheric plasma (CAP) and plasma-treated liquids (PTLs) have recently become a promising option for cancer treatment, but the underlying mechanisms of the anti-cancer effect are still to a large extent unknown. Although hydrogen peroxide ([Formula: see text]) has been recognized as the major anti-cancer agent of PTL and may enable selectivity in a certain concentration regime, the co-existence of nitrite can create a synergistic effect. We develop a mathematical model to describe the key species and features of the cellular response toward PTL. From the numerical solutions, we define a number of dependent variables, which represent feasible measures to quantify cell susceptibility in terms of the [Formula: see text] membrane diffusion rate constant and the intracellular catalase concentration. For each of these dependent variables, we investigate the regimes of selective versus non-selective, and of synergistic versus non-synergistic effect to evaluate their potential role as a measure of cell susceptibility. Our results suggest that the maximal intracellular [Formula: see text] concentration, which in the selective regime is almost four times greater for the most susceptible cells compared to the most resistant cells, could be used to quantify the cell susceptibility toward exogenous [Formula: see text]. We believe our theoretical approach brings novelty to the field of plasma oncology, and more broadly, to the field of redox biology, by proposing new ways to quantify the selective and synergistic anti-cancer effect of PTL in terms of inherent cell features. MDPI 2021-05-10 /pmc/articles/PMC8126141/ /pubmed/34068601 http://dx.doi.org/10.3390/ijms22095033 Text en © 2021 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
Bengtson, Charlotta
Bogaerts, Annemie
The Quest to Quantify Selective and Synergistic Effects of Plasma for Cancer Treatment: Insights from Mathematical Modeling
title The Quest to Quantify Selective and Synergistic Effects of Plasma for Cancer Treatment: Insights from Mathematical Modeling
title_full The Quest to Quantify Selective and Synergistic Effects of Plasma for Cancer Treatment: Insights from Mathematical Modeling
title_fullStr The Quest to Quantify Selective and Synergistic Effects of Plasma for Cancer Treatment: Insights from Mathematical Modeling
title_full_unstemmed The Quest to Quantify Selective and Synergistic Effects of Plasma for Cancer Treatment: Insights from Mathematical Modeling
title_short The Quest to Quantify Selective and Synergistic Effects of Plasma for Cancer Treatment: Insights from Mathematical Modeling
title_sort quest to quantify selective and synergistic effects of plasma for cancer treatment: insights from mathematical modeling
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8126141/
https://www.ncbi.nlm.nih.gov/pubmed/34068601
http://dx.doi.org/10.3390/ijms22095033
work_keys_str_mv AT bengtsoncharlotta thequesttoquantifyselectiveandsynergisticeffectsofplasmaforcancertreatmentinsightsfrommathematicalmodeling
AT bogaertsannemie thequesttoquantifyselectiveandsynergisticeffectsofplasmaforcancertreatmentinsightsfrommathematicalmodeling
AT bengtsoncharlotta questtoquantifyselectiveandsynergisticeffectsofplasmaforcancertreatmentinsightsfrommathematicalmodeling
AT bogaertsannemie questtoquantifyselectiveandsynergisticeffectsofplasmaforcancertreatmentinsightsfrommathematicalmodeling