Predicting the Effects of Anti-angiogenic Agents Targeting Specific VEGF Isoforms
Vascular endothelial growth factor (VEGF) is a key mediator of angiogenesis, whose effect on cancer growth and development is well characterized. Alternative splicing of VEGF leads to several different isoforms, which are differentially expressed in various tumor types and have distinct functions in tumor blood vessel formation. Many cancer therapies aim to inhibit angiogenesis by targeting VEGF and preventing intracellular signaling leading to tumor vascularization; however, the effects of targeting specific VEGF isoforms have received little attention in the clinical setting. In this work, we investigate the effects of selectively targeting a single VEGF isoform, as compared with inhibiting all isoforms. We utilize a molecular-detailed whole-body compartment model of VEGF transport and kinetics in the presence of breast tumor. The model includes two major VEGF isoforms, VEGF121 and VEGF165, receptors VEGFR1 and VEGFR2, and co-receptors Neuropilin-1 and Neuropilin-2. We utilize the model to predict the concentrations of free VEGF, the number of VEGF/VEGFR2 complexes (considered to be pro-angiogenic), and the receptor occupancy profiles following inhibition of VEGF using isoform-specific anti-VEGF agents. We predict that targeting VEGF121 leads to a 54% and 84% reduction in free VEGF in tumors that secrete both VEGF isoforms or tumors that overexpress VEGF121, respectively. Additionally, 21% of the VEGFR2 molecules in the blood are ligated following inhibition of VEGF121, compared with 88% when both isoforms are targeted. Targeting VEGF121 reduces tumor free VEGF and is an effective treatment strategy. Our results provide a basis for clinical investigation of isoform-specific anti-VEGF agents.
Key wordsangiogenesis cancer drug target computational model pharmacokinetic model systems biology
The authors thank Gang Liu and Spyridon Stamatelos for helpful discussions. This work was supported by National Institutes of Health grant R01 CA138264 (ASP) and fellowship F32 CA154213 (SDF), and the UNCF/Merck Postdoctoral Fellowship (SDF).
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