Background: Vascular endothelial growth factor (VEGF) is a potent regulator of angiogenesis, and its role in cancer\r\nbiology has been widely studied. Many cancer therapies target angiogenesis, with a focus being on VEGF-mediated\r\nsignaling such as antibodies to VEGF. However, it is difficult to predict the effects of VEGF-neutralizing agents. We\r\nhave developed a whole-body model of VEGF kinetics and transport under pathological conditions (in the\r\npresence of breast tumor). The model includes two major VEGF isoforms VEGF121 and VEGF165, receptors VEGFR1,\r\nVEGFR2 and co-receptors Neuropilin-1 and Neuropilin-2. We have added receptors on parenchymal cells (muscle\r\nfibers and tumor cells), and incorporated experimental data for the cell surface density of receptors on the\r\nendothelial cells, myocytes, and tumor cells. The model is applied to investigate the action of VEGF-neutralizing\r\nagents (called ââ?¬Å?anti-VEGFââ?¬Â) in the treatment of cancer.\r\nResults: Through a sensitivity study, we examine how model parameters influence the level of free VEGF in the\r\ntumor, a measure of the response to VEGF-neutralizing drugs. We investigate the effects of systemic properties\r\nsuch as microvascular permeability and lymphatic flow, and of drug characteristics such as the clearance rate and\r\nbinding affinity. We predict that increasing microvascular permeability in the tumor above 10-5 cm/s elicits the\r\nundesired effect of increasing tumor interstitial VEGF concentration beyond even the baseline level. We also\r\nexamine the impact of the tumor microenvironment, including receptor expression and internalization, as well as\r\nVEGF secretion. We find that following anti-VEGF treatment, the concentration of free VEGF in the tumor can vary\r\nbetween 7 and 233 pM, with a dependence on both the density of VEGF receptors and co-receptors and the rate\r\nof neuropilin internalization on tumor cells. Finally, we predict that free VEGF in the tumor is reduced following\r\nanti-VEGF treatment when VEGF121 comprises at least 25% of the VEGF secreted by tumor cells.\r\nConclusions: This study explores the optimal drug characteristics required for an anti-VEGF agent to have a\r\ntherapeutic effect and the tumor-specific properties that influence the response to therapy. Our model provides a\r\nframework for investigating the use of VEGF-neutralizing drugs for personalized medicine treatment strategies.
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