Dataset Information

Compartment model predicts VEGF secretion and investigates the effects of VEGF trap in tumor-bearing mice.

ABSTRACT: Angiogenesis, the formation of new blood vessels from existing vasculature, is important in tumor growth and metastasis. A key regulator of angiogenesis is vascular endothelial growth factor (VEGF), which has been targeted in numerous anti-angiogenic therapies aimed at inhibiting tumor angiogenesis. Systems biology approaches, including computational modeling, are useful for understanding this complex biological process and can aid in the development of novel and effective therapeutics that target the VEGF family of proteins and receptors. We have developed a computational model of VEGF transport and kinetics in the tumor-bearing mouse, which includes three-compartments: normal tissue, blood, and tumor. The model simulates human tumor xenografts and includes human (VEGF121 and VEGF165) and mouse (VEGF120 and VEGF164) isoforms. The model incorporates molecular interactions between these VEGF isoforms and receptors (VEGFR1 and VEGFR2), as well as co-receptors (NRP1 and NRP2). We also include important soluble factors: soluble VEGFR1 (sFlt-1) and ?-2-macroglobulin. The model accounts for transport via macromolecular transendothelial permeability, lymphatic flow, and plasma clearance. We have fit the model to available in vivo experimental data on the plasma concentration of free VEGF Trap and VEGF Trap bound to mouse and human VEGF in order to estimate the rates at which parenchymal cells (myocytes and tumor cells) and endothelial cells secrete VEGF. Interestingly, the predicted tumor VEGF secretion rates are significantly lower (0.007-0.023?molecules/cell/s, depending on the tumor microenvironment) than most reported in vitro measurements (0.03-2.65?molecules/cell/s). The optimized model is used to investigate the interstitial and plasma VEGF concentrations and the effect of the VEGF-neutralizing agent, VEGF Trap (aflibercept). This work complements experimental studies performed in mice and provides a framework with which to examine the effects of anti-VEGF agents, aiding in the optimization of such anti-angiogenic therapeutics as well as analysis of clinical data. The model predictions also have implications for biomarker discovery with anti-angiogenic therapies.

SUBMITTER: Finley SD

PROVIDER: S-EPMC3727077 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Compartment model predicts VEGF secretion and investigates the effects of VEGF trap in tumor-bearing mice.

Finley Stacey D SD Dhar Manjima M Popel Aleksander S AS

Frontiers in oncology 20130730

Angiogenesis, the formation of new blood vessels from existing vasculature, is important in tumor growth and metastasis. A key regulator of angiogenesis is vascular endothelial growth factor (VEGF), which has been targeted in numerous anti-angiogenic therapies aimed at inhibiting tumor angiogenesis. Systems biology approaches, including computational modeling, are useful for understanding this complex biological process and can aid in the development of novel and effective therapeutics that targ ...[more]

PMID: 23908970

Similar Datasets

Project description:Vascular endothelial growth factor (VEGF), through its activation of cell surface receptor tyrosine kinases including VEGFR1 and VEGFR2, is a vital regulator of stimulatory and inhibitory processes that keep angiogenesis--new capillary growth from existing microvasculature--at a dynamic balance in normal physiology. Soluble VEGF receptor-1 (sVEGFR1)--a naturally-occurring truncated version of VEGFR1 lacking the transmembrane and intracellular signaling domains--has been postulated to exert inhibitory effects on angiogenic signaling via two mechanisms: direct sequestration of angiogenic ligands such as VEGF; or dominant-negative heterodimerization with surface VEGFRs. In pre-clinical studies, sVEGFR1 gene and protein therapy have demonstrated efficacy in inhibiting tumor angiogenesis; while in clinical studies, sVEGFR1 has shown utility as a diagnostic or prognostic marker in a widening array of angiogenesis-dependent diseases. Here we developed a novel computational multi-tissue model for recapitulating the dynamic systemic distributions of VEGF and sVEGFR1. Model features included: physiologically-based multi-scale compartmentalization of the human body; inter-compartmental macromolecular biotransport processes (vascular permeability, lymphatic drainage); and molecularly-detailed binding interactions between the ligand isoforms VEGF(121) and VEGF(165), signaling receptors VEGFR1 and VEGFR2, non-signaling co-receptor neuropilin-1 (NRP1), as well as sVEGFR1. The model was parameterized to represent a healthy human subject, whereupon we investigated the effects of sVEGFR1 on the distribution and activation of VEGF ligands and receptors. We assessed the healthy baseline stability of circulating VEGF and sVEGFR1 levels in plasma, as well as their reliability in indicating tissue-level angiogenic signaling potential. Unexpectedly, simulated results showed that sVEGFR1 - acting as a diffusible VEGF sink alone, i.e., without sVEGFR1-VEGFR heterodimerization--did not significantly lower interstitial VEGF, nor inhibit signaling potential in tissues. Additionally, the sensitivity of plasma VEGF and sVEGFR1 to physiological fluctuations in transport rates may partially account for the heterogeneity in clinical measurements of these circulating angiogenic markers, potentially hindering their diagnostic reliability for diseases.

Project description:Vascular endothelial growth factor (VEGF) is a key regulator of angiogenesis--the growth of new microvessels from existing microvasculature. Angiogenesis is a complex process involving numerous molecular species, and to better understand it, a systems biology approach is necessary. In vivo preclinical experiments in the area of angiogenesis are typically performed in mouse models; this includes drug development targeting VEGF. Thus, to quantitatively interpret such experimental results, a computational model of VEGF distribution in the mouse can be beneficial. In this paper, we present an in silico model of VEGF distribution in mice, determine model parameters from existing experimental data, conduct sensitivity analysis, and test the validity of the model. The multiscale model is comprised of two compartments: blood and tissue. The model accounts for interactions between two major VEGF isoforms (VEGF(120) and VEGF(164)) and their endothelial cell receptors VEGFR-1, VEGFR-2, and co-receptor neuropilin-1. Neuropilin-1 is also expressed on the surface of parenchymal cells. The model includes transcapillary macromolecular permeability, lymphatic transport, and macromolecular plasma clearance. Simulations predict that the concentration of unbound VEGF in the tissue is approximately 50-fold greater than in the blood. These concentrations are highly dependent on the VEGF secretion rate. Parameter estimation was performed to fit the simulation results to available experimental data, and permitted the estimation of VEGF secretion rate in healthy tissue, which is difficult to measure experimentally. The model can provide quantitative interpretation of preclinical animal data and may be used in conjunction with experimental studies in the development of pro- and anti-angiogenic agents. The model approximates the normal tissue as skeletal muscle and includes endothelial cells to represent the vasculature. As the VEGF system becomes better characterized in other tissues and cell types, the model can be expanded to include additional compartments and vascular elements.

Dataset Information

Compartment model predicts VEGF secretion and investigates the effects of VEGF trap in tumor-bearing mice.

Publications

Compartment model predicts VEGF secretion and investigates the effects of VEGF trap in tumor-bearing mice.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets