Effect of Tumor Microenvironment on Tumor VEGF During Anti-VEGF Treatment: Systems Biology Predictions

Finley, Stacey D.; Popel, Aleksander S.

doi:10.1093/jnci/djt093

Cited by 80 publications

(78 citation statements)

References 81 publications

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“…Because of the intrinsic properties of the two isoforms, they are present in the tissue compartments in very different forms: VEGF 165 is primarily bound to the extracellular matrix, whereas VEGF 121 is largely in soluble form in the plasma and interstitial spaces. Our model predicts these different distributions 15. Thus, we believe that the model must retain the current level of detail in order to capture the unique dynamics of the VEGF isoforms and aflibercept and provide novel mechanistic insight into the effects of the species' molecular interactions, which are not possible with less molecular‐detailed models.…”

Section: Discussionmentioning

confidence: 99%

“…The number of VEGFRs and co‐receptors are based on quantitative flow cytometry measurements from in vitro and in vivo studies in our laboratory 19, 20. In our previous publications,12, 13, 15, 21, 22 we have performed extensive sensitivity analyses to quantify how the model outputs (namely, the concentrations of VEGF in the three compartments) are affected when model parameters are varied. We found that most parameters do not significantly change the predicted VEGF concentrations over a wide range of values (i.e., up to an order of magnitude above or below the baseline value).…”

Section: Methodsmentioning

confidence: 99%

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Pharmacokinetics of Anti‐VEGF Agent Aflibercept in Cancer Predicted by Data‐Driven, Molecular‐Detailed Model

Finley

Angelikopoulos

Koumoutsakos

et al. 2015

CPT Pharmacometrics Syst. Pharmacol.

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Mathematical models can support the drug development process by predicting the pharmacokinetic (PK) properties of the drug and optimal dosing regimens. We have developed a pharmacokinetic model that includes a biochemical molecular interaction network linked to a whole‐body compartment model. We applied the model to study the PK of the anti‐vascular endothelial growth factor (VEGF) cancer therapeutic agent, aflibercept. Clinical data is used to infer model parameters using a Bayesian approach, enabling a quantitative estimation of the contributions of specific transport processes and molecular interactions of the drug that cannot be examined in other PK modeling, and insight into the mechanisms of aflibercept's antiangiogenic action. Additionally, we predict the plasma and tissue concentrations of unbound and VEGF‐bound aflibercept. Thus, we present a computational framework that can serve as a valuable tool for drug development efforts.

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Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Pharmacokinetics of Anti‐VEGF Agent Aflibercept in Cancer Predicted by Data‐Driven, Molecular‐Detailed Model

Finley

Angelikopoulos

Koumoutsakos

et al. 2015

CPT Pharmacometrics Syst. Pharmacol.

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“…Admittedly, there is a change in the number of healthy or diseased cells in human patients undergoing anti-angiogenic therapy, as a primary goal of treatment is to reduce tumor volume. However, as we have shown in our previous work, 34 that since the tumor is nearly 2000 times smaller than the normal compartment, the tumor volume must change by at least two orders of magnitude (to B3300 cm 3 ) for it to significantly influence the distributions of the soluble factors, which is a central focus of our PK/PD compartment model. Since this size of tumor is not physiologically realistic, we assume constant tumor volume and instead focus on the distribution of the soluble factors and the formation of proand anti-angiogenic complexes in each of the compartments.…”

Section: Methodsmentioning

confidence: 94%

“…32 We assume that the geometric characteristics of xenograft tumors in mice recapitulate human tumors, rather than relying on data from in vitro cell culture. The set of geometric parameters has been used in multiple previous studies, 21,23,34 and we adopt the parameters without changing their values. Kinetic parameters (47 parameters).…”

Section: Model Parameterizationmentioning

confidence: 99%

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The impact of tumor receptor heterogeneity on the response to anti-angiogenic cancer treatment

Ding

Finley

2018

Integrative Biology

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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.

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Quantitative fluorescent profiling ofVEGFRs reveals tumor cell and endothelial cell heterogeneity in breast cancer xenografts

Imoukhuede

Popel

2014

Cancer Medicine

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Plasma membrane-localized vascular endothelial growth factor receptors (VEGFR) play a critical role in transducing VEGF signaling toward pro and antiangiogenic outcomes and quantitative characterization of these receptors is critical toward identifying biomarkers for antiangiogenic therapies, understanding mechanisms of action of antiangiogenic drugs, and advancing predictive computational models. While in vitro analysis of cell surface-VEGFRs has been performed, little is known about the levels of cell surface-VEGFR on tumor cells. Therefore, we inoculate nude mice with the human triple-negative breast cancer, MDA-MB-231, cell line; isolate human tumor cells and mouse tumor endothelial cells from xenografts; and quantitatively characterize the VEGFR localization on these cells. We observe 15,000 surface-VEGFR1/tumor endothelial cell versus 8200 surface-VEGFR1/tumor endothelial cell at 3 and 6 weeks of tumor growth, respectively; and we quantify 1200–1700 surface-VEGFR2/tumor endothelial cell. The tumor cell levels of VEGFR1 and VEGFR2 are relatively constant between 3 and 6 weeks: 2000–2200 surface-VEGFR1/tumor cell and ∼1000 surface-VEGFR2/tumor cell. Cell-by-cell analysis provides additional insight into tumor heterogeneity by identifying four cellular subpopulations based on size and levels of cell membrane-localized VEGFR. Furthermore, when these ex vivo data are compared to in vitro data, we observe little to no VEGFRs on MDA-MB-231 cells, and the MDA-MB-231 VEGFR surface levels are not regulated by a saturating dose of VEGF. Overall, the quantification of these dissimilarities for the first time in tumor provides insight into the balance of modulatory (VEGFR1) and proangiogenic (VEGFR2) receptors.

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Effect of Tumor Microenvironment on Tumor VEGF During Anti-VEGF Treatment: Systems Biology Predictions

Cited by 80 publications

References 81 publications

Pharmacokinetics of Anti‐VEGF Agent Aflibercept in Cancer Predicted by Data‐Driven, Molecular‐Detailed Model

Pharmacokinetics of Anti‐VEGF Agent Aflibercept in Cancer Predicted by Data‐Driven, Molecular‐Detailed Model

The impact of tumor receptor heterogeneity on the response to anti-angiogenic cancer treatment

Quantitative fluorescent profiling ofVEGFRs reveals tumor cell and endothelial cell heterogeneity in breast cancer xenografts

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