A mathematical model of tumor regression and recurrence after therapeutic oncogene inactivation

Abstract The targeted inactivation of individual oncogenes can elicit regression of cancers through a phenomenon called oncogene addiction. Oncogene addiction is mediated by cell-autonomous and immune-dependent mechanisms. Therapeutic resistance to oncogene inactivation leads to recurrence but can b...

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Autores principales:	Sharon S. Hori, Ling Tong, Srividya Swaminathan, Mariola Liebersbach, Jingjing Wang, Sanjiv S. Gambhir, Dean W. Felsher
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/5eaa4c551c6b436ebaa97bfaaabc2d0e
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spelling	oai:doaj.org-article:5eaa4c551c6b436ebaa97bfaaabc2d0e2021-12-02T14:12:40ZA mathematical model of tumor regression and recurrence after therapeutic oncogene inactivation10.1038/s41598-020-78947-22045-2322https://doaj.org/article/5eaa4c551c6b436ebaa97bfaaabc2d0e2021-01-01T00:00:00Zhttps://doi.org/10.1038/s41598-020-78947-2https://doaj.org/toc/2045-2322Abstract The targeted inactivation of individual oncogenes can elicit regression of cancers through a phenomenon called oncogene addiction. Oncogene addiction is mediated by cell-autonomous and immune-dependent mechanisms. Therapeutic resistance to oncogene inactivation leads to recurrence but can be counteracted by immune surveillance. Predicting the timing of resistance will provide valuable insights in developing effective cancer treatments. To provide a quantitative understanding of cancer response to oncogene inactivation, we developed a new 3-compartment mathematical model of oncogene-driven tumor growth, regression and recurrence, and validated the model using a MYC-driven transgenic mouse model of T-cell acute lymphoblastic leukemia. Our mathematical model uses imaging-based measurements of tumor burden to predict the relative number of drug-sensitive and drug-resistant cancer cells in MYC-dependent states. We show natural killer (NK) cell adoptive therapy can delay cancer recurrence by reducing the net-growth rate of drug-resistant cells. Our studies provide a novel way to evaluate combination therapy for personalized cancer treatment.Sharon S. HoriLing TongSrividya SwaminathanMariola LiebersbachJingjing WangSanjiv S. GambhirDean W. FelsherNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-14 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Sharon S. Hori Ling Tong Srividya Swaminathan Mariola Liebersbach Jingjing Wang Sanjiv S. Gambhir Dean W. Felsher A mathematical model of tumor regression and recurrence after therapeutic oncogene inactivation
description	Abstract The targeted inactivation of individual oncogenes can elicit regression of cancers through a phenomenon called oncogene addiction. Oncogene addiction is mediated by cell-autonomous and immune-dependent mechanisms. Therapeutic resistance to oncogene inactivation leads to recurrence but can be counteracted by immune surveillance. Predicting the timing of resistance will provide valuable insights in developing effective cancer treatments. To provide a quantitative understanding of cancer response to oncogene inactivation, we developed a new 3-compartment mathematical model of oncogene-driven tumor growth, regression and recurrence, and validated the model using a MYC-driven transgenic mouse model of T-cell acute lymphoblastic leukemia. Our mathematical model uses imaging-based measurements of tumor burden to predict the relative number of drug-sensitive and drug-resistant cancer cells in MYC-dependent states. We show natural killer (NK) cell adoptive therapy can delay cancer recurrence by reducing the net-growth rate of drug-resistant cells. Our studies provide a novel way to evaluate combination therapy for personalized cancer treatment.
format	article
author	Sharon S. Hori Ling Tong Srividya Swaminathan Mariola Liebersbach Jingjing Wang Sanjiv S. Gambhir Dean W. Felsher
author_facet	Sharon S. Hori Ling Tong Srividya Swaminathan Mariola Liebersbach Jingjing Wang Sanjiv S. Gambhir Dean W. Felsher
author_sort	Sharon S. Hori
title	A mathematical model of tumor regression and recurrence after therapeutic oncogene inactivation
title_short	A mathematical model of tumor regression and recurrence after therapeutic oncogene inactivation
title_full	A mathematical model of tumor regression and recurrence after therapeutic oncogene inactivation
title_fullStr	A mathematical model of tumor regression and recurrence after therapeutic oncogene inactivation
title_full_unstemmed	A mathematical model of tumor regression and recurrence after therapeutic oncogene inactivation
title_sort	mathematical model of tumor regression and recurrence after therapeutic oncogene inactivation
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/5eaa4c551c6b436ebaa97bfaaabc2d0e
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A mathematical model of tumor regression and recurrence after therapeutic oncogene inactivation

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