Multiple promoters and inhibitors mediate angiogenesis, the formation of new blood vessels, and these factors represent potential targets for impeding vessel growth in tumors. Vascular endothelial growth factor (VEGF) is a potent angiogenic factor targeted in anti-angiogenic cancer therapies. In addition, thrombospondin-1 (TSP1) is a major endogenous inhibitor of angiogenesis, and TSP1 mimetics are being developed as an alternative type of anti-angiogenic agent. The combination of bevacizumab, an anti-VEGF agent, and ABT-510, a TSP1 mimetic, has been tested in clinical trials to treat advanced solid tumors.However, the patients' responses are highly variable and show disappointing outcomes. To obtain mechanistic insight into the effects of this combination anti-angiogenic therapy, we have constructed a novel whole-body systems biology model including the VEGF and TSP1 reaction networks. Using this molecular-detailed model, we investigated how the combination anti-angiogenic therapy changes the amounts of pro-angiogenic and anti-angiogenic complexes in cancer patients. We particularly focus on answering the question of how the effect of the combination therapy is influenced by tumor receptor expression, one aspect of patient-to-patient variability. Overall, this model complements the clinical administration of combination anti-angiogenic therapy, highlights the role of tumor receptor variability in the heterogeneous responses to anti-angiogenic therapy, and identifies the tumor receptor profiles that correlate with a high likelihood of a positive response to the combination therapy. Our model provides novel understanding of the VEGF-TSP1 balance in cancer patients at the systems-level and could be further used to optimize combination anti-angiogenic therapy.
Insight, innovation, integrationThis work reports a novel multi-compartment model integrating the reaction networks of VEGF and TSP1, two potent angiogenic factors, in human cancer patients. With the model, we gain new insight into the impact of tumor receptor heterogeneity on the response to a clinically tested combination antiangiogenic therapy targeting both VEGF and TSP1 signaling and we identify potential tissue biomarkers. The model predictions provide mechanistic explanations of several important results reported in clinical trials of anti-angiogenic therapy, including the heterogeneous response to treatment and the importance of VEGFR1 as a predictive biomarker. Overall, this computational framework can be applied to improve combination anti-angiogenic therapy by increasing our understanding of the heterogeneous response, identifying potential biomarkers, and optimizing the pre-clinical and clinical studies.