Deciphering the Extracellular Inhibition of Pro‐angiogenic Signaling Using a Systems Biology Model
Authors: Li Ding , Finley Stacey D 
Published: June 2021

Introduction

Tumor angiogenesis is regulated by multiple endogenous pro‐ and anti‐angiogenic factors. Anti‐angiogenic cancer drugs target the interconnected network of angiogenic factors to inhibit neovascularization and tumor growth. Due to the complexity of this network, optimizing anti‐angiogenic drugs requires a detailed knowledge at the systems level. In this study, we aim to elucidate the extracellular regulation of the intricate network consisting of four main angiogenic factors ‐ two pro‐angiogenic factors (promoters): vascular endothelial growth factor (VEGF) and basic fibroblast growth factor (FGF2), and two anti‐angiogenic factors (inhibitors): thrombospondin‐1 (TSP1) and platelet factor 4 (PF4). In the network, inhibitors affect pro‐angiogenic signaling by: (a) sequestering the promoters, preventing promoters from binding to their cell‐surface receptors and (b) competing for binding to the co‐receptors heparan sulfate proteoglycans (HSPGs), which mediate crosstalk between all four families.

Methods and approach

Overall, these four species form a complex network in tumor tissue. To better understand how the angiogenic signal is regulated, we constructed a novel tissue‐based tumor model that predicts the concentrations of the angiogenic factors over time using ordinary differential equations. We used the model to investigate how the distributions of the promoters are influenced by HSPG expression and the secretion of the inhibitors. In addition, we simulated experimentally tested anti‐angiogenic treatments to understand how the tumor microenvironment affects the tissue response to therapies.

Results

First, the model predicts the distribution of angiogenic factors, showing that the majority of VEGF and FGF2 are bound to signaling receptors on the cell surface, while most of TSP1 and PF4 is trapped in interstitial spaces or in an inactive form (Fig. 1). Second, the model reveals that the HSPG levels directly influence the distribution of angiogenic factors (Fig. 2): increasing HSPG levels efficiently traps the inhibitors in the system, while increasing the percentage of pro‐angigoenic FGF2 signaling species. Interestingly, VEGF signaling shows a biphasic response to increasing HSPGs level, indicating that there is an optimal HSPG level that maximizes the VEGF‐bound pro‐angiogenic complexes. Third, the model predicts a counterintuitive situation, in which the secretion of the inhibitors can increase the level of unbound promoters (Fig. 3). Finally, the model elucidates the effect of HSPGs on anti‐angiogenic therapeutics, showing that HSPGs inhibition enhances the response to therapies targeting the promoters.

Conclusions

This study provides a computational framework to generate novel insight into the regulation of pro‐angiogenic signaling in the tissue extracellular space. We find that HSPGs significantly affect pro‐angiogenic signaling and that the effect of anti‐angiogenic treatment is due to multiple interactions that might result in counterintuitive outcomes. The knowledge generated from our model can be translated to inform and guide the design of anti‐angiogenic treatments.

Support or Funding Information

US National Science Foundation, American Cancer Society, and the USC Provost's PhD Fellowship

This abstract is from the Experimental Biology 2019 Meeting. There is no full text article associated with this abstract published in The FASEB Journal.