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Modeling the Impact of Anticancer Agents on Metastatic Spreading

Published online by Cambridge University Press:  25 January 2012

S. Benzekry ,
N. André ,
A. Benabdallah ,
J. Ciccolini ,
C. Faivre ,
F. Hubert  and
D. Barbolosi
S. Benzekry
Affiliation:
CMI-LATP, UMR 6632, Université de Provence, Technopôle Château-Gombert 39, rue F. Joliot-Curie, 13453 Marseille cedex 13, France Laboratoire de Toxicocinétique et Pharmacocinétique UMR INSERM 911, CRO2 27, boulevard Jean Moulin, 13005 Marseille, France
N. André
Affiliation:
Service d’Hématologie et Oncologie Pédiatrique, Hôpital pour enfants de La Timone Marseille, France Metronomics Global Health Initiative
A. Benabdallah
Affiliation:
CMI-LATP, UMR 6632, Université de Provence, Technopôle Château-Gombert 39, rue F. Joliot-Curie, 13453 Marseille cedex 13, France
J. Ciccolini
Affiliation:
Laboratoire de Toxicocinétique et Pharmacocinétique UMR INSERM 911, CRO2 27, boulevard Jean Moulin, 13005 Marseille, France
C. Faivre
Affiliation:
Laboratoire de Toxicocinétique et Pharmacocinétique UMR INSERM 911, CRO2 27, boulevard Jean Moulin, 13005 Marseille, France
F. Hubert
Affiliation:
CMI-LATP, UMR 6632, Université de Provence, Technopôle Château-Gombert 39, rue F. Joliot-Curie, 13453 Marseille cedex 13, France
D. Barbolosi*
Affiliation:
Laboratoire de Toxicocinétique et Pharmacocinétique UMR INSERM 911, CRO2 27, boulevard Jean Moulin, 13005 Marseille, France
*
⋆ Corresponding author. E-mail: fhubert@cmi.univ-mrs.fr
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Abstract

Treating cancer patients with metastatic disease remains an ultimate challenge in clinical oncology. Because invasive cancer precludes or limits the use of surgery, metastatic setting is often associated with (poor) survival, rather than sustained remission, in patients with common cancers like lung, digestive or breast carcinomas. Mathematical modeling may help us better identify non detectable metastatic status to in turn optimize treatment for patients with metastatic disease. In this paper we present a family of models for the metastatic growth. They are based on four principles : to be as simple as possible, involving the least possible number of parameters, the main informations are obtained from the primary tumor and being able to recover the variety of phenomena observed by the clinicians. Several simulations of therapeutic strategies are presented illustrating possible applications of modeling to the clinic.

Keywords

modelingmetastasesanti-angiogenic therapymetronomic chemotherapy
Type
Research Article
Information
Mathematical Modelling of Natural Phenomena , Volume 7 , Issue 1: Cancer modeling , 2012 , pp. 306 - 336
Copyright
© EDP Sciences, 2012

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