VEGF and soluble VEGF receptor-1 (sFlt-1) distributions in peripheral arterial disease: an in silico model

Abstract

Vascular endothelial growth factor (VEGF) is a key regulator of angiogenesis, the growth of new capillaries from existing microvasculature. In peripheral arterial disease (PAD), lower extremity muscle ischemia develops downstream of atherosclerotic obstruction. A working hypothesis proposed that the maladaptive overexpression of soluble VEGF receptor 1 (sVEGFR1) in ischemic muscle tissues, and its subsequent antagonism of VEGF bioactivity, may contribute to the deficient angiogenic response in PAD, as well as the limited success of therapeutic angiogenesis strategies where exogenous VEGF genes/proteins are delivered. The objectives of this study were to develop a computational framework for simulating the systemic distributions of VEGF and sVEGFR1 (e.g., intramuscular vs. circulating, free vs. complexed) as observed in human PAD patients and to serve as a platform for the systematic optimization of diagnostic tools and therapeutic strategies. A three-compartment model was constructed, dividing the human body into the ischemic calf muscle, blood, and the rest of the body, connected through macromolecular biotransport processes. Detailed molecular interactions between VEGF, sVEGFR1, endothelial surface receptors (VEGFR1, VEGFR2, NRP1), and interstitial matrix sites were modeled. Our simulation results did not support a simultaneous decrease in plasma sVEGFR1 during PAD-associated elevations in plasma VEGF reported in literature. Furthermore, despite the overexpression in sVEGFR1, our PAD control demonstrated increased proangiogenic signaling complex formation, relative to our previous healthy control, due to sizeable upregulations in VEGFR2 and VEGF expression, thus leaving open the possibility that impaired angiogenesis in PAD may be rooted in signaling pathway disruptions downstream of ligand-receptor binding.

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“…18 VEGF 165 and VEGF 121 interactions with their receptors (VEGFR 1 and VEGFR 2 ) and nonsignaling neuropilin-1 coreceptor have been extensively studied using validated computational models in the context of angiogenesis, 17,[19][20][21][22] including models relevant to PAD. 19,22,23 These models have demonstrated that in the absence of neuropilin-1, VEGF 165 and VEGF 121 behave similarly. When present, however, neuropilin-1 enhances the binding of VEGF 165 to VEGFR 2 , which is a major mediator of the angiogenic effects of VEGF-A.…”

“…17 Such models have also demonstrated that VEGF concentration in blood, but not in tissue, is dependent on the vascular permeability of healthy tissue. 17,23,83 The net arteriogenic/angiogenic effects of measured VEGF isoforms (165 and 121) would also be influenced by other VEGF isoforms and receptors not assessed in this study. These include the VEGF xxx b isoforms, generated through alternative splicing, which are generally antiangiogenic.…”

“…Although the absolute concentration of all measured biomarkers may vary between tissues and blood, there is evidence of significant correlations between concentrations in these different compartments. 17,23,[79][80][81][82] VEGF plasma concentration has been shown to vary approximately linearly with VEGF secretion rate in a biophysically accurate compartment model. 17 This model permits study the distribution of VEGF isoforms, including 165 and 121, in both tissue (matrix-bound, cell surface receptor-bound, and free VEGF isoforms) and blood.…”

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“…However, the predictive power of these models has previously been limited by insufficient knowledge of cell surface receptor levels. Therefore, the data that we report here provide critical parameters needed to advance systems biology models of ischemic disease (7,27,49,58,75).…”

“…Computational models, based on mass-action kinetics of the VEGF-VEGFR signaling axis, have predicted the distribution of soluble VEGFR1 in peripheral vascular disease (75) and the distribution of VEGF within diseased tissue, healthy tissue, and blood (67), and a recent computational model has included in vitro-and ex vivo-derived VEGFR surface levels on the endothelium (23). This experimentally associated model provided insights into the pharmacokinetics of an anti-VEGF agent in the treatment of metastatic breast cancer and suggested novel neoadjuvant treatment approaches (23,36,37).…”