A computational analysis of in vivo VEGFR activation by multiple co-expressed ligands

Abstract

The splice isoforms of vascular endothelial growth A (VEGF) each have different affinities for the extracellular matrix (ECM) and the coreceptor NRP1, which leads to distinct vascular phenotypes in model systems expressing only a single VEGF isoform. ECM-immobilized VEGF can bind to and activate VEGF receptor 2 (VEGFR2) directly, with a different pattern of site-specific phosphorylation than diffusible VEGF. To date, the way in which ECM binding alters the distribution of isoforms of VEGF and of the related placental growth factor (PlGF) in the body and resulting angiogenic signaling is not well-understood. Here, we extend our previous validated cell-level computational model of VEGFR2 ligation, intracellular trafficking, and site-specific phosphorylation, which captured differences in signaling by soluble and immobilized VEGF, to a multi-scale whole-body framework. This computational systems pharmacology model captures the ability of the ECM to regulate isoform-specific growth factor distribution distinctly for VEGF and PlGF, and to buffer free VEGF and PlGF levels in tissue. We show that binding of immobilized growth factor to VEGF receptors, both on endothelial cells and soluble VEGFR1, is likely important to signaling in vivo. Additionally, our model predicts that VEGF isoform-specific properties lead to distinct profiles of VEGFR1 and VEGFR2 binding and VEGFR2 site-specific phosphorylation in vivo, mediated by Neuropilin-1. These predicted signaling changes mirror those observed in murine systems expressing single VEGF isoforms. Simulations predict that, contrary to the ‘ligand-shifting hypothesis,’ VEGF and PlGF do not compete for receptor binding at physiological concentrations, though PlGF is predicted to slightly increase VEGFR2 phosphorylation when over-expressed by 10-fold. These results are critical to design of appropriate therapeutic strategies to control VEGF availability and signaling in regenerative medicine applications.

Systems Pharmacology of VEGF165b in Peripheral Artery Disease

“…We next “zoomed in” on the endothelial‐bound fraction of tissue VEGF and PlGF to examine growth factor binding to endothelial VEGFR1 and VEGFR2. With equal secretion of VEGF 165b and VEGF 165a in the PAD calf muscle, VEGF 165b is predicted to dominate binding to both VEGFR1 and VEGFR2 ( Figure a ), with higher (but still low) receptor occupancy ( Figure c ; 14% and 10% surface occupancy, respectively) than previously predicted in healthy tissue ( Supplementary Figure S3a ). This is a direct result of lack of binding to NRP1 and ECM by VEGF 165b (see Pharmacokinetics section, Supplementary Results ).…”

“…When VEGF 165a and VEGF 165b were secreted at equal rates in tissue (fractional VEGF 165b secretion = 50%), the model predicts that VEGF 165b protein is over‐represented compared to VEGF 165a in tissue ( Figure b ), both as extracellular ligand ( Supplementary Figure S2c ) and endothelial cell‐bound ligand ( Figure b, orange ). This over‐representation (relative to fractional secretion) results from: (a) lack of ECM‐binding, leading to 2.4‐fold more free VEGF 165b than VEGF 165a in the PAD calf muscle; combined with (b) lack of NRP1‐binding slowing binding to VEGFR2 and subsequent recycling, and thus slowing turnover of VEGF 165b ‐VEGFR2 complexes . The model predicts that this over‐representation of VEGF 165b in total tissue VEGF and free VEGF in blood ( Figure c ) is predicted to occur at all VEGF 165b levels, with a larger difference in blood than tissue due to secretion of VEGF 165b (e.g., by monocytes) into the bloodstream.…”

“…Our objective in building this model was to investigate in detail the implications of the experimentally measured properties of VEGF 165b —lack of ECM binding, lack of NRP1 binding, and weak phosphorylation of VEGFR2—on the role of this isoform in PAD. We leveraged a previously built and validated computational model that accounts explicitly for differences in ECM and NRP1 binding by VEGF isoforms, as well as simulating binding, trafficking, and tyrosine site‐specific phosphorylation of VEGFR2 as distinct, although related, processes . This framework enabled us to directly implement the unique properties of VEGF 165b , making predictions of disease‐specific in vivo concentrations and signaling that are difficult, if not impossible, to quantify experimentally.…”

“…To study the distribution of VEGF 165b within the human body, we modified our previously published three‐compartment model, which includes the blood, the main bulk of body tissue (main body mass), and a calf muscle (gastrocnemius + soleus) with PAD‐specific changes in geometry and molecular expression ( Figure ). Within the tissue compartments, the relative fractions of interstitial space, ECM and basement membrane, and endothelial and other cells (including myocytes) are estimated based on histology and other measurements ( Supplementary Figure S1 ).…”

Systems biology of the microvasculature

“…This allows for much more detailed understanding than would be possible using only in vivo data, which typically consists of plasma protein concentrations, plus some genetic and gene expression data. The scenarios examined to date include competition between ligands for binding to multiple receptors 59 ; coupling and enhancement of VEGF binding by Neuropilin co-receptors 60–62 ; dimerization of VEGF receptors 63 ; downstream signaling of the Akt and ERK pathways 64, 65 ; matrix-immobilized growth factors and VEGFR trafficking and phosphorylation 66, 67 . In addition to these detailed models of VEGF dynamics, models have been developed to directly predict VEGF production in skeletal muscle based on oxygen levels, both after exercise and in peripheral artery disease 33, 68–70 .…”