# Dose- and time-dependence of the host-mediated response to paclitaxel therapy: a mathematical modeling approach

Oncotarget. 2018; 9:2574-2590. https://doi.org/10.18632/oncotarget.23514

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## Abstract

Madeleine Benguigui1, Dror Alishekevitz1, Michael Timaner1, Dvir Shechter1, Ziv Raviv1, Sebastien Benzekry2 and Yuval Shaked1

1Cell Biology and Cancer Science, Rappaport Faculty of Medicine, Technion, Israel Institute of Technology, Haifa, Israel

2MONC Team, Inria Bordeaux Sud-Ouest and Institut de Mathématiques de Bordeaux, Talence, France

Correspondence to:

Sebastien Benzekry, email: [email protected]

Yuval Shaked, email: [email protected]

Keywords: chemotherapy; host effects; mathematical models; invasion and migration; metronomic chemotherapy

Received: October 18, 2017     Accepted: December 05, 2017     Published: December 20, 2017

ABSTRACT

It has recently been suggested that pro-tumorigenic host-mediated processes induced in response to chemotherapy counteract the anti-tumor activity of therapy, and thereby decrease net therapeutic outcome. Here we use experimental data to formulate a mathematical model describing the host response to different doses of paclitaxel (PTX) chemotherapy as well as the duration of the response. Three previously described host-mediated effects are used as readouts for the host response to therapy. These include the levels of circulating endothelial progenitor cells in peripheral blood and the effect of plasma derived from PTX-treated mice on migratory and invasive properties of tumor cells in vitro. A first set of mathematical models, based on basic principles of pharmacokinetics/pharmacodynamics, did not appropriately describe the dose-dependence and duration of the host response regarding the effects on invasion. We therefore provide an alternative mathematical model with a dose-dependent threshold, instead of a concentration-dependent one, that describes better the data. This model is integrated into a global model defining all three host-mediated effects. It not only precisely describes the data, but also correctly predicts host-mediated effects at different doses as well as the duration of the host response. This mathematical model may serve as a tool to predict the host response to chemotherapy in cancer patients, and therefore may be used to design chemotherapy regimens with improved therapeutic outcome by minimizing host mediated effects.