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Model-Based Anticancer Effect of Botulinum Neurotoxin Type A1 on Syngeneic Melanoma Mice

In recent, Botulinum Neurotoxin A1 (BoNT/A1) has been suggested as a potential anticancer agent due to neuronal innervation in tumor cells. Although potential BoNT/A1’s mechanism of action for the tumor suppression has been gradually revealed so far, there were no reports to figure out the exposure-...

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Autores principales: Kang, Won-Ho, Ryu, Hyo-Jeong, Kwak, Seongsung, Yun, Hwi-Yeol
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8763961/
https://www.ncbi.nlm.nih.gov/pubmed/35058777
http://dx.doi.org/10.3389/fphar.2021.793349
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author Kang, Won-Ho
Ryu, Hyo-Jeong
Kwak, Seongsung
Yun, Hwi-Yeol
author_facet Kang, Won-Ho
Ryu, Hyo-Jeong
Kwak, Seongsung
Yun, Hwi-Yeol
author_sort Kang, Won-Ho
collection PubMed
description In recent, Botulinum Neurotoxin A1 (BoNT/A1) has been suggested as a potential anticancer agent due to neuronal innervation in tumor cells. Although potential BoNT/A1’s mechanism of action for the tumor suppression has been gradually revealed so far, there were no reports to figure out the exposure-response relationships because of the difficulty of its quantitation in the biological matrix. The main objectives of this study were to measure the anticancer effect of BoNT/A1 using a syngeneic mouse model transplanted with melanoma cells (B16-F10) and developed a kinetic-pharmacodynamic (K-PD) model for quantitative exposure-response evaluation. To overcome the lack of exposure information, the K-PD model was implemented by the virtual pharmacokinetic compartment link to the pharmacodynamic compartment of Simeoni’s tumor growth inhibition model and evaluated using curve-fitting for the tumor growth-time profile after intratumoral injection of BoNT/A1. The final K-PD model was adequately explained for a pattern of tumor growth depending on represented exposure parameters and simulation studies were conducted to determine the optimal dose under various scenarios considering dose strength and frequency. The optimal dose range and regimen of ≥13.8 units kg(−1) once a week or once every 3 days was predicted using the final model in B16-F10 syngeneic model and it was demonstrated with an extra in-vivo experiment. In conclusion, the K-PD model of BoNT/A1 was well developed to optimize the dosing regimen for evaluation of anticancer effect and this approach could be expandable to figure out quantitative interpretation of BoNT/A1’s efficacy in various xenograft and/or syngeneic models.
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spelling pubmed-87639612022-01-19 Model-Based Anticancer Effect of Botulinum Neurotoxin Type A1 on Syngeneic Melanoma Mice Kang, Won-Ho Ryu, Hyo-Jeong Kwak, Seongsung Yun, Hwi-Yeol Front Pharmacol Pharmacology In recent, Botulinum Neurotoxin A1 (BoNT/A1) has been suggested as a potential anticancer agent due to neuronal innervation in tumor cells. Although potential BoNT/A1’s mechanism of action for the tumor suppression has been gradually revealed so far, there were no reports to figure out the exposure-response relationships because of the difficulty of its quantitation in the biological matrix. The main objectives of this study were to measure the anticancer effect of BoNT/A1 using a syngeneic mouse model transplanted with melanoma cells (B16-F10) and developed a kinetic-pharmacodynamic (K-PD) model for quantitative exposure-response evaluation. To overcome the lack of exposure information, the K-PD model was implemented by the virtual pharmacokinetic compartment link to the pharmacodynamic compartment of Simeoni’s tumor growth inhibition model and evaluated using curve-fitting for the tumor growth-time profile after intratumoral injection of BoNT/A1. The final K-PD model was adequately explained for a pattern of tumor growth depending on represented exposure parameters and simulation studies were conducted to determine the optimal dose under various scenarios considering dose strength and frequency. The optimal dose range and regimen of ≥13.8 units kg(−1) once a week or once every 3 days was predicted using the final model in B16-F10 syngeneic model and it was demonstrated with an extra in-vivo experiment. In conclusion, the K-PD model of BoNT/A1 was well developed to optimize the dosing regimen for evaluation of anticancer effect and this approach could be expandable to figure out quantitative interpretation of BoNT/A1’s efficacy in various xenograft and/or syngeneic models. Frontiers Media S.A. 2022-01-04 /pmc/articles/PMC8763961/ /pubmed/35058777 http://dx.doi.org/10.3389/fphar.2021.793349 Text en Copyright © 2022 Kang, Ryu, Kwak and Yun. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Pharmacology
Kang, Won-Ho
Ryu, Hyo-Jeong
Kwak, Seongsung
Yun, Hwi-Yeol
Model-Based Anticancer Effect of Botulinum Neurotoxin Type A1 on Syngeneic Melanoma Mice
title Model-Based Anticancer Effect of Botulinum Neurotoxin Type A1 on Syngeneic Melanoma Mice
title_full Model-Based Anticancer Effect of Botulinum Neurotoxin Type A1 on Syngeneic Melanoma Mice
title_fullStr Model-Based Anticancer Effect of Botulinum Neurotoxin Type A1 on Syngeneic Melanoma Mice
title_full_unstemmed Model-Based Anticancer Effect of Botulinum Neurotoxin Type A1 on Syngeneic Melanoma Mice
title_short Model-Based Anticancer Effect of Botulinum Neurotoxin Type A1 on Syngeneic Melanoma Mice
title_sort model-based anticancer effect of botulinum neurotoxin type a1 on syngeneic melanoma mice
topic Pharmacology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8763961/
https://www.ncbi.nlm.nih.gov/pubmed/35058777
http://dx.doi.org/10.3389/fphar.2021.793349
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