A Population Dynamic Energy Budget-Based Tumor Growth Inhibition Model for Etoposide Effects on Wistar Rats

Rocchetti²,

Pesenti

et al. 2020

Cancer Research

Adequate energy intake and homeostasis are fundamental for the appropriate growth and maintenance of an organism; the presence of a tumor can break this equilibrium. Tumor energy requests can lead to extreme weight loss in animals and cachexia in cancer patients. Angiogenesis inhibitors, acting on tumor vascularization, counteract this tumor-host energy imbalance, with significant results in preclinical models and more limited results in the clinic. Current pharmacokinetic-pharmacodynamic models mainly focus on the antiangiogenic effects on tumor growth but do not provide information about host conditions. A model that can predict energetic conditions that provide significant tumor growth inhibition with acceptable host body weight reduction is therefore needed. We developed a new tumor-in-host dynamic energy budget (DEB)based model to account for the cytostatic activity of antiangiogenic treatments. Drug effect was implemented as an inhibition of the energy fraction subtracted from the host by the tumor. The model was tested on seven xenograft experiments involving bevacizumab and three different tumor cell lines. The model successfully predicted tumor and host body growth data, providing a quantitative measurement of drug potency and tumor-related cachexia. The inclusion of a hypoxia-triggered resistance mechanism enabled investigation of the decreased efficacy frequently observed with prolonged bevacizumab treatments. In conclusion, the tumor-inhost DEB-based approach has been extended to account for the effect of bevacizumab. The resistance model predicts the response to different administration protocols and, for the first time, the impact of tumor-related cachexia in different cell lines. Finally, the physiologic base of the model strongly suggests its use in translational human research.Significance: A mathematical model describes tumor growth in animal models, taking into consideration the energy balance involving both the growth of tumor and the physiologic functions of the host.

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Tumor-in-Host DEB-Based Approach for Modeling Cachexia and Bevacizumab Resistance

Rocchetti²,

Pesenti

et al. 2020

Cancer Research

“…This editorial aims to summarize the research that in the last 7-8 years has led to the development of a new DEB-based framework modeling the tumor-in-host growth dynamics and the cachexia onset in preclinical animal models during anticancer treatments [14][15][16]. The model was successfully tested on a multitude of in vivo preclinical studies involving different host species (mice and rats), tumor cell lines, type of anticancer agents (cytotoxic and cytostatic) and experimental settings between which standard xenograft studies typically performed to assess the anticancer efficacy of investigated compounds [17,18].…”

Section: Introductionmentioning

confidence: 99%

“…The second set of data regards an in vivo experiment performed to assess the Etoposide activity on Wistar rats [ 15 ]. The study was composed by five arms: the standard control group (tumor-bearing untreated animals), two tumor-bearing groups treated with Etoposide administered with two different protocols and two additional arms composed by treated and untreated tumor-free animals.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

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

Rocchetti²,

Magni

2021

Oncotarget

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-inhost 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.

Modeling restoration of gefitinib efficacy by co‐administration of MET inhibitors in an EGFR inhibitor‐resistant NSCLC xenograft model: A tumor‐in‐host DEB‐based approach

CPT Pharmacom & Syst Pharma

Gauderat

Fouliard

et al. 2021

MET receptor tyrosine kinase inhibitors (TKIs) can restore sensitivity to gefitinib, a TKI targeting epidermal growth factor receptor (EGFR), and promote apoptosis in non‐small cell lung cancer (NSCLC) models resistant to gefitinib treatment in vitro and in vivo. Several novel MET inhibitors are currently under study in different phases of development. In this work, a novel tumor‐in‐host modeling approach, based on the Dynamic Energy Budget (DEB) theory, was proposed and successfully applied to the context of poly‐targeted combination therapies. The population DEB‐based tumor growth inhibition (TGI) model well‐described the effect of gefitinib and of two MET inhibitors, capmatinib and S49076, on both tumor growth and host body weight when administered alone or in combination in an NSCLC mice model involving the gefitinib‐resistant tumor line HCC827ER1. The introduction of a synergistic effect in the combination DEB‐TGI model allowed to capture gefitinib anticancer activity enhanced by the co‐administered MET inhibitor, providing also a quantitative evaluation of the synergistic drug interaction. The model‐based comparison of the two MET inhibitors highlighted that S49076 exhibited a greater anticancer effect as well as a greater ability in restoring sensitivity to gefitinib than the competitor capmatinib. In summary, the DEB‐based tumor‐in‐host framework proposed here can be applied to routine combination xenograft experiments, providing an assessment of drug interactions and contributing to rank investigated compounds and to select the optimal combinations, based on both tumor and host body weight dynamics. Thus, the combination tumor‐in‐host DEB‐TGI model can be considered a useful tool in the preclinical development and a significant advance toward better characterization of combination therapies.