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A Dynamic Energy Budget (DEB) based modeling framework to describe tumor-in-host growth inhibition and cachexia onset during anticancer treatment in in vivo xenograft studies

Elena Maria Tosca, Maurizio Rocchetti and Paolo Magni _

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Oncotarget. 2021; 12:1434-1441. https://doi.org/10.18632/oncotarget.27960

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Abstract

Elena Maria Tosca1, Maurizio Rocchetti2 and Paolo Magni1

1 Department of Electrical, Computer and Biomedical Engineering, University of Pavia, Pavia I-27100, Italy

2 Consultant, Milano, Italy

Correspondence to:

Paolo Magni,email: paolo.magni@unipv.it

Keywords: PK-PD modeling; tumor-growth-inhibition model; dynamic energy budget theory; cancer cachexia; xenograft model

Received: April 06, 2021     Accepted: April 22, 2021     Published: July 06, 2021

Copyright: © 2021 Tosca et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

ABSTRACT

Cancer anorexia-cachexia syndrome (CACS) is a very severe complication of cancer for which an adequate therapeutic strategy has not yet been defined. Recently, a notable number of new animal models of human CACS has been made available for translational purposes. Under the assumption that tumor-induced adaptations of host metabolism and tumor-host energetic competition play a major role in CACS (together with possible toxicities induced by the anticancer treatment), we developed a new Dynamic Energy Budget (DEB)-based framework, modeling tumor-in-host growth dynamics and cachexia onset in preclinical animal models during anticancer treatments. The tumor-in-host modeling approach was successfully applied on a multitude of in vivo preclinical studies involving different host species, tumor cell lines, type of anticancer agents and experimental settings among which standard xenograft studies. Obtained results strongly suggested the adoption of the tumor-in-host DEB-based approach in the preclinical oncological setting for a joint assessment of drug efficacy and toxicity and for a better design of the experiments. Further applications of the DEB-based approach to the context of poly-targeted combination therapy, anti-cachectic treatments and preclinical to clinical translation are under investigation with extremely encouraging preliminary results.


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