Do mechanisms matter? Comparing cancer treatment strategies across mathematical models and outcome objectives

When eradication is impossible, cancer treatment aims to delay the emergence of resistance while minimizing cancer burden and treatment. Adaptive therapies may achieve these aims, with success based on three assumptions: resistance is costly, sensitive cells compete with resistant cells, and therapy...

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Autores principales:	Cassidy K. Buhler, Rebecca S. Terry, Kathryn G. Link, Frederick R. Adler
Formato:	article
Lenguaje:	EN
Publicado:	AIMS Press 2021
Materias:	adaptive therapy cancer ecology mathematical model competition allee effect androgen dynamics Biotechnology TP248.13-248.65 Mathematics QA1-939
Acceso en línea:	https://doaj.org/article/e0862ec0d0e14371aebb832f131c4a0d
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spelling	oai:doaj.org-article:e0862ec0d0e14371aebb832f131c4a0d2021-11-11T01:20:20ZDo mechanisms matter? Comparing cancer treatment strategies across mathematical models and outcome objectives10.3934/mbe.20213151551-0018https://doaj.org/article/e0862ec0d0e14371aebb832f131c4a0d2021-07-01T00:00:00Zhttps://www.aimspress.com/article/doi/10.3934/mbe.2021315?viewType=HTMLhttps://doaj.org/toc/1551-0018When eradication is impossible, cancer treatment aims to delay the emergence of resistance while minimizing cancer burden and treatment. Adaptive therapies may achieve these aims, with success based on three assumptions: resistance is costly, sensitive cells compete with resistant cells, and therapy reduces the population of sensitive cells. We use a range of mathematical models and treatment strategies to investigate the tradeoff between controlling cell populations and delaying the emergence of resistance. These models extend game theoretic and competition models with four additional components: 1) an Allee effect where cell populations grow more slowly at low population sizes, 2) healthy cells that compete with cancer cells, 3) immune cells that suppress cancer cells, and 4) resource competition for a growth factor like androgen. In comparing maximum tolerable dose, intermittent treatment, and adaptive therapy strategies, no therapeutic choice robustly breaks the three-way tradeoff among the three therapeutic aims. Almost all models show a tight tradeoff between time to emergence of resistant cells and cancer cell burden, with intermittent and adaptive therapies following identical curves. For most models, some adaptive therapies delay overall tumor growth more than intermittent therapies, but at the cost of higher cell populations. The Allee effect breaks these relationships, with some adaptive therapies performing poorly due to their failure to treat sufficiently to drive populations below the threshold. When eradication is impossible, no treatment can simultaneously delay emergence of resistance, limit total cancer cell numbers, and minimize treatment. Simple mathematical models can play a role in designing the next generation of therapies that balance these competing objectives.Cassidy K. Buhler Rebecca S. TerryKathryn G. LinkFrederick R. AdlerAIMS Pressarticleadaptive therapycancer ecologymathematical modelcompetitionallee effectandrogen dynamicsBiotechnologyTP248.13-248.65MathematicsQA1-939ENMathematical Biosciences and Engineering, Vol 18, Iss 5, Pp 6305-6327 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	adaptive therapy cancer ecology mathematical model competition allee effect androgen dynamics Biotechnology TP248.13-248.65 Mathematics QA1-939
spellingShingle	adaptive therapy cancer ecology mathematical model competition allee effect androgen dynamics Biotechnology TP248.13-248.65 Mathematics QA1-939 Cassidy K. Buhler Rebecca S. Terry Kathryn G. Link Frederick R. Adler Do mechanisms matter? Comparing cancer treatment strategies across mathematical models and outcome objectives
description	When eradication is impossible, cancer treatment aims to delay the emergence of resistance while minimizing cancer burden and treatment. Adaptive therapies may achieve these aims, with success based on three assumptions: resistance is costly, sensitive cells compete with resistant cells, and therapy reduces the population of sensitive cells. We use a range of mathematical models and treatment strategies to investigate the tradeoff between controlling cell populations and delaying the emergence of resistance. These models extend game theoretic and competition models with four additional components: 1) an Allee effect where cell populations grow more slowly at low population sizes, 2) healthy cells that compete with cancer cells, 3) immune cells that suppress cancer cells, and 4) resource competition for a growth factor like androgen. In comparing maximum tolerable dose, intermittent treatment, and adaptive therapy strategies, no therapeutic choice robustly breaks the three-way tradeoff among the three therapeutic aims. Almost all models show a tight tradeoff between time to emergence of resistant cells and cancer cell burden, with intermittent and adaptive therapies following identical curves. For most models, some adaptive therapies delay overall tumor growth more than intermittent therapies, but at the cost of higher cell populations. The Allee effect breaks these relationships, with some adaptive therapies performing poorly due to their failure to treat sufficiently to drive populations below the threshold. When eradication is impossible, no treatment can simultaneously delay emergence of resistance, limit total cancer cell numbers, and minimize treatment. Simple mathematical models can play a role in designing the next generation of therapies that balance these competing objectives.
format	article
author	Cassidy K. Buhler Rebecca S. Terry Kathryn G. Link Frederick R. Adler
author_facet	Cassidy K. Buhler Rebecca S. Terry Kathryn G. Link Frederick R. Adler
author_sort	Cassidy K. Buhler
title	Do mechanisms matter? Comparing cancer treatment strategies across mathematical models and outcome objectives
title_short	Do mechanisms matter? Comparing cancer treatment strategies across mathematical models and outcome objectives
title_full	Do mechanisms matter? Comparing cancer treatment strategies across mathematical models and outcome objectives
title_fullStr	Do mechanisms matter? Comparing cancer treatment strategies across mathematical models and outcome objectives
title_full_unstemmed	Do mechanisms matter? Comparing cancer treatment strategies across mathematical models and outcome objectives
title_sort	do mechanisms matter? comparing cancer treatment strategies across mathematical models and outcome objectives
publisher	AIMS Press
publishDate	2021
url	https://doaj.org/article/e0862ec0d0e14371aebb832f131c4a0d
work_keys_str_mv	AT cassidykbuhler domechanismsmattercomparingcancertreatmentstrategiesacrossmathematicalmodelsandoutcomeobjectives AT rebeccasterry domechanismsmattercomparingcancertreatmentstrategiesacrossmathematicalmodelsandoutcomeobjectives AT kathrynglink domechanismsmattercomparingcancertreatmentstrategiesacrossmathematicalmodelsandoutcomeobjectives AT frederickradler domechanismsmattercomparingcancertreatmentstrategiesacrossmathematicalmodelsandoutcomeobjectives
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Do mechanisms matter? Comparing cancer treatment strategies across mathematical models and outcome objectives

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