Abstract
With the aim of inhibiting cancer growth and reducing the risk of metastasis, pharmaceutical companies in the early 1990s developed anti-metastatic agents called inhibitors of metalloproteinases (MMPi). Despite the promising results obtained in pre-clinical studies, results of Phase III trials have been somewhat disappointing for late stage cancer patients. With the aim of mathematically investigating this therapeutic failure, we developed a mechanistically based model which integrates cell cycle regulation and macroscopic tumor dynamics. By simulating the model, we evaluated the efficacy of MMPi therapy. Simulation results predict the lack of efficacy of MMPi in advanced cancer patients. The theoretical model may aid in evaluating the efficacy of anti-metastatic therapies, thus benefiting the design of prospective clinical trials.
Highlights
Mathematical models of cancer have been extensively developed with the aim to predict tumor growth and therapeutic strategies efficacy [1; 2; 3; 4; 5]
We present a multiscale mathematical model of avascular tumor growth to investigate the role of MMPi treatment on cancer growth
MMPi were thought as promising therapeutic agents to slow down cancer growth and reduce the risk of metastasis
Summary
Mathematical models of cancer have been extensively developed with the aim to predict tumor growth and therapeutic strategies efficacy [1; 2; 3; 4; 5]. We’re interested in cytostatic agents called the inhibitors of metalloproteinases (MMPi), developed to slow down cancer growth and to reduce the risk of metastasis. These agents have been designed to inhibit metalloproteinases (MMP), a group of enzymes which are known to play a major role in the degradation of basal membranes and extra-cellular matrixes and in cancer invasion. Other studies are required to allow the resumption of further clinical trials
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