Pharmacokinetics and pharmacodynamics of VEGF-neutralizing antibodies

Stacey D Finley 0 Marianne O Engel-Stefanini 0 PI Imoukhuede 0 Aleksander S Popel 0 0 Department of Biomedical Engineering, Johns Hopkins University, School of Medicine , 720 Rutland Avenue, Baltimore, MD 21205 , USA Background: Vascular endothelial growth factor (VEGF) is a potent regulator of angiogenesis, and its role in cancer biology has been widely studied. Many cancer therapies target angiogenesis, with a focus being on VEGF-mediated signaling such as antibodies to VEGF. However, it is difficult to predict the effects of VEGF-neutralizing agents. We have developed a whole-body model of VEGF kinetics and transport under pathological conditions (in the presence of breast tumor). The model includes two major VEGF isoforms VEGF121 and VEGF165, receptors VEGFR1, VEGFR2 and co-receptors Neuropilin-1 and Neuropilin-2. We have added receptors on parenchymal cells (muscle fibers and tumor cells), and incorporated experimental data for the cell surface density of receptors on the endothelial cells, myocytes, and tumor cells. The model is applied to investigate the action of VEGF-neutralizing agents (called anti-VEGF) in the treatment of cancer. Results: Through a sensitivity study, we examine how model parameters influence the level of free VEGF in the tumor, a measure of the response to VEGF-neutralizing drugs. We investigate the effects of systemic properties such as microvascular permeability and lymphatic flow, and of drug characteristics such as the clearance rate and binding affinity. We predict that increasing microvascular permeability in the tumor above 10-5 cm/s elicits the undesired effect of increasing tumor interstitial VEGF concentration beyond even the baseline level. We also examine the impact of the tumor microenvironment, including receptor expression and internalization, as well as VEGF secretion. We find that following anti-VEGF treatment, the concentration of free VEGF in the tumor can vary between 7 and 233 pM, with a dependence on both the density of VEGF receptors and co-receptors and the rate of neuropilin internalization on tumor cells. Finally, we predict that free VEGF in the tumor is reduced following anti-VEGF treatment when VEGF121 comprises at least 25% of the VEGF secreted by tumor cells. Conclusions: This study explores the optimal drug characteristics required for an anti-VEGF agent to have a therapeutic effect and the tumor-specific properties that influence the response to therapy. Our model provides a framework for investigating the use of VEGF-neutralizing drugs for personalized medicine treatment strategies. - Background Angiogenesis, the formation of new capillaries from preexisting blood vessels, is a tightly regulated biological process and is involved in normal physiological function as well as in pathological conditions. Angiogenesis occurs in embryos during organ growth and development [1]. In adults, angiogenesis is essential for conditions requiring an increase in blood and oxygen supply, including reproduction, physiological repair (e.g., wound and tissue healing), and exercise [2,3]. In addition to its relevance in physiological conditions, angiogenesis has a prominent role in diseases such as preeclampsia, ischemic heart disease, and cancer. Neovascularization allows for cancer development, tumor growth, and metastasis whereby the tumor elicits the formation of capillaries to obtain its own blood supply [4]. Vascular endothelial growth factor (VEGF) is a potent regulator of angiogenesis, and its role in cancer biology has been widely studied. Clinically, cancer patients exhibit increased VEGF levels [5] although this finding remains controversial [6], and vascularization in tumors shows marked differences from physiological vessel architecture: increased leakiness and tortuosity, decreased pericyte coverage, and abnormal organization [7,8]. For these reasons, many cancer therapies target angiogenic pathways, with the major focus being on VEGF-mediated signaling in the form of antibodies to VEGF and its receptors, small molecule tyrosine kinase inhibitors, and peptides [9-11]. The human VEGF family includes five ligands (VEGFA through -D and placental growth factor, PlGF), three receptors (VEGFR1, VEGFR2, and VEGFR3), and two co-receptors, neuropilins (NRP1 and NRP2). VEGF binding to its receptors regulates vessel permeability [12] and expression of matrix metalloproteinases [13], involved in capillary sprout formation. Angiogenesis involves numerous molecular species and includes events that occur at the molecular, cellular, and tissue levels in sequence and in parallel. This complexity lends the process of angiogenesis to systems biology approaches [14,15]. Computational modeling, in particular, is useful in understanding angiogenesis and provides a framework to test biological hypotheses [16]. Additionally, the models can aid in the development and optimization of therapies targeting this process [16-19]. Our laboratory previously developed a whole-body model of VEGF kinetic and transport necessary for building models of VEGF-mediated angiogenesis [20,21]. One of the models predicts the distribution of VEGF in the body upon administration of the anti-VEGF recombinant humanized monoclonal antibody bevacizumab [21]. The findings suggest that anti-VEGF agents act to deplete tumor VEGF rather than blood (plasma) VEGF because the blood VEGF was predicted to decrease transiently and then increase above the baseline pre-treatment level. In the present study, we extend the previous computational model to include receptors on parenchymal cells. Our previous models were limited by a lack of quantitative measurements of cell surface receptor densities. Therefore, using quantitative flow cytometry, we have determined the density of VEGF receptors and coreceptors on the surface of endothelial cells, skeletal muscle myocytes, and tumor cells, and incorporated these key parameters into the current model. Additionally, we have included VEGF degradation and have utilized published in vitro data to establish a baseline for the rate of VEGF secretion by tumor cells. These significant model additions provide a physiologically-based computational framework to study VEGF kinetics and transport. We utilize the model to investigate how systemic properties, drug characteristics, and properties of the tumor microenvironment influence the response to the anti-VEGF agent. The simulations show that the level of VEGF in the tumor interstitium can decrease or, paradoxically, increase beyond even the baseline pre-treatment level as a result of anti-VEGF administration depending on the values of parameters. Importantly, we predict the ranges of parameter values which elicit the undesired effect of increasing tumor interstitial VEGF concentration. Thus, our model can be used to predict the optimal drug and tumor properties for which an anti-VEGF agent may have a therapeutic effect. Methods Computational methods Computational Model Here, we su (...truncated)