Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2011 Nov 21:5:193.
doi: 10.1186/1752-0509-5-193.

Pharmacokinetics and pharmacodynamics of VEGF-neutralizing antibodies

Stacey D Finley  1 , Marianne O Engel-Stefanini, P I Imoukhuede, Aleksander S Popel
Affiliations

Pharmacokinetics and pharmacodynamics of VEGF-neutralizing antibodies

Stacey D Finley et al. BMC Syst Biol. .

Abstract

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.

PubMed Disclaimer

Figures

Figure 1
Figure 1
Molecular interactions. The binding interactions between VEGF, surface receptors, extracellular matrix and basement membranes. VEGF165 binds to VEGFR1, VEGFR2, and co-receptors NRP1 and NRP2. VEGF165 also binds to glycosaminoglycan (GAG) chains in the extracellular matrix and basement membranes. VEGF121 binds to VEGFR1 and VEGFR2, but is unable to bind to NRPs. The molecular interactions between the VEGF isoforms and NRP1 or NRP2 are identical, but are governed by different kinetic parameters. The anti-VEGF agent binds to both isoforms. The receptors and co-receptors are inserted and internalized at the cell surface.
Figure 2
Figure 2
Effect of model parameters. The concentration of predicted free VEGF in the interstitium is sensitive to the presence and density of receptors on abluminal and luminal endothelial surfaces, and on myocytes and tumor cells. Baseline Model 1 is based on [20], and Baseline Model 2 is based on [34]. In the baseline models, receptor density is assumed to be: 10,000 VEGFR1, 10,000 VEGFR2, and 100,000 NRP1 molecules/endothelial cell. Experimental receptor density is based on in vitro in human cells using quantitative flow cytometry [31] and in vivo quantification in mouse skeletal muscle and tumor xenografts using the same technique. In each simulation, VEGF secretion is tuned to maintain blood free VEGF at 4.5 pM. Simulation cases are as follows: A, VEGFR1, VEGFR2, and NRP1 present on abluminal endothelial surface with assumed receptor density. B, VEGFR1, VEGFR2, and NRP1 present on abluminal endothelial surface with experimental receptor density. C, VEGFR1, VEGFR2, and NRP1 evenly distributed on abluminal and luminal endothelial surface with assumed receptor density. D, VEGFR1, VEGFR2, and NRP1 evenly distributed on abluminal and luminal endothelial surface with experimental receptor density. Cases E through K build upon the previous case by sequentially refining the model: E, Addition of NRP1 on myocytes. F, Addition of VEGFR1 on tumor cells. G, Addition of VEGFR2 present on tumor cells. H, Addition of NRP1 on tumor cells. I, Addition of NRP2 on tumor cells. J, Incorporation of VEGF degradation in normal tissue and tumor. K, Incorporation of experimental data for VEGF secretion by tumor cells (Current Model).
Figure 3
Figure 3
Effect of tumor VEGF secretion. The rate of VEGF secreted by tumor cells and the tumor isoform secretion ratio VEGF165:VEGF121 induces whole-body changes in the distribution of VEGF. A, Effect of tumor VEGF secretion rate on the steady-state free VEGF concentration in the body. Gray circles indicate the secretion rate used in the current model, 0.56 molecules/cell/s. B, Steady-state free VEGF concentration in the body. Gray circles indicate the ratio used in the current model, VEGF165:VEGF121 = 50%:50% in the tumor. C, Distribution of free, receptor-, and matrix-bound VEGF: black, unbound VEGF; light gray, receptor-bound VEGF; dark gray, VEGF bound to GAG chains in the extracellular matrix and basement membranes.
Figure 4
Figure 4
Whole-body changes in response to anti-VEGF treatment. Concentration profiles following a single intravenous injection of 10 mg/kg anti-VEGF given at time 0. A, VEGF concentration. B, Anti-VEGF concentration. C, Concentration of the VEGF/anti-VEGF complex.
Figure 5
Figure 5
Effect of systemic properties permeability. The concentration of free VEGF in the body following anti-VEGF treatment is predicted for various parameter values. A, Microvascular permeability to VEGF between the normal tissue and blood. B, Microvascular permeability to VEGF between the tumor and blood. C, Lymphatic flow from tumor to blood. From top to bottom: normal tissue (subscript N), blood (subscript B), and tumor (subscript T). Bold in the legend indicates parameter value used in the current model.
Figure 6
Figure 6
Effect of anti-VEGF properties. The concentration of free VEGF in the body following anti-VEGF treatment is predicted as properties of the anti-VEGF are varied. A, Effect of microvascular permeability to anti-VEGF between the normal tissue and blood. B, Effect of microvascular permeability to anti-VEGF between the tumor and blood. C, Effect of clearance rate of anti-VEGF and VEGF/anti-VEGF complex. D, Effect of anti-VEGF binding affinity for VEGF. From top to bottom: normal tissue, blood, and tumor. Bold in the legend indicates parameter value used in the current model.
Figure 7
Figure 7
Effect of anti-VEGF binding matrix-bound VEGF. Concentration profiles following a single intravenous injection of 10 mg/kg anti-VEGF given at time 0 when the anti-VEGF is able to bind matrix-bound VEGF. A, VEGF concentration. B, Anti-VEGF concentration. C, VEGF/anti-VEGF complex concentration.
Figure 8
Figure 8
VEGF distribution with anti-VEGF binding matrix-bound VEGF. VEGF distribution in the body. A, Normal tissue. B, Blood. C, Tumor.
Figure 9
Figure 9
Effect of systemic parameters and anti-VEGF properties on the response to anti-VEGF treatment. The fold-change in free VEGF concentration following anti-VEGF treatment as a function of various model parameters. A, Systemic parameters. B, Anti-VEGF properties. Color bar indicates range of values for each parameter, as given in Figures 5 and 6.
Figure 10
Figure 10
Effect of receptor density on tumor cells. The fold-change in free VEGF concentration following anti-VEGF treatment is predicted as a function of VEGFR1, VEGFR2, and neuropilin (NRP) expression. In all simulations, NRP1 = NRP2. A, NRP = 0 molecules/tumor cell. B, NRP = 5,000 molecules/tumor cell. C, NRP = 10,000 molecules/tumor cell. D, NRP = 15,000 molecules/tumor cell. E, NRP = 20,000 molecules/tumor cell. F, NRP = 39,500 molecules/tumor cell. The white circle indicates receptor densities used in the current model: VEGFR1 = 1,100 molecules/tumor cell, VEGFR2 = 550 molecules/tumor cell, NRP1 = NRP2 = 39,500 molecules/tumor cell. G, NRP = 80,000 molecules/tumor cell. H, NRP = 100,000 molecules/tumor cell. A-H, The gray dotted line in all panels is the isocline for a fold-change of 1.
Figure 11
Figure 11
Effect of tumor microenvironment on the response to the anti-VEGF treatment. The fold-change in free VEGF concentration following anti-VEGF treatment is predicted as a function of properties of the tumor microenvironment. A, Effect of neuropilin internalization. B, Effect of VEGF isoform-specific secretion.
See this image and copyright information in PMC

Similar articles

See all similar articles

Cited by

See all "Cited by" articles

References

    1. Carmeliet P. Angiogenesis in life, disease and medicine. Nature. 2005;438:932–936. doi: 10.1038/nature04478. - DOI - PubMed
    1. Egginton S. Invited review: activity-induced angiogenesis. Pflugers Archiv (European Journal of Physiology) 2009;457:963–977. doi: 10.1007/s00424-008-0563-9. - DOI - PubMed
    1. Sung H-K, Michael IP, Nagy A. Multifaceted role of vascular endothelial growth factor signaling in adult tissue physiology: an emerging concept with clinical implications. Curr Opin Hematol. 2010;17:206–212. - PubMed
    1. Carmeliet P, Jain RK. Molecular mechanisms and clinical applications of angiogenesis. Nature. 2011;473:298–307. doi: 10.1038/nature10144. - DOI - PMC - PubMed
    1. Kut C, Mac Gabhann F, Popel AS. Where is VEGF in the body? A meta-analysis of VEGF distribution in cancer. Br J Cancer. 2007;97:978–985. doi: 10.1038/sj.bjc.6603923. - DOI - PMC - PubMed

Publication types

MeSH terms

Substances

LinkOut - more resources