{"title":"Mechanistic insights into the heterogeneous response to anti-VEGF treatment in tumors","authors":"Ding Li, Stacey D. Finley","doi":"10.1002/cso2.1013","DOIUrl":null,"url":null,"abstract":"<p>Vascular endothelial growth factor (VEGF) is a strong promoter of angiogenesis in tumors, and anti-VEGF treatment, such as a humanized antibody to VEGF, is clinically used as a monotherapy or in combination with chemotherapy to treat cancer patients. However, this approach is not effective in all patients or cancer types. To better understand the heterogeneous responses to anti-VEGF and the synergy between anti-VEGF and other anticancer therapies, we constructed a computational model characterizing angiogenesis-mediated growth of <i>in vivo</i> mouse tumor xenografts. The model captures VEGF-mediated cross-talk between tumor cells and endothelial cells and is able to predict the details of molecular- and cellular-level dynamics. The model predictions of tumor growth in response to anti-VEGF closely match the quantitative measurements from multiple preclinical mouse studies. We applied the model to investigate the effects of VEGF-targeted treatment on tumor cells and endothelial cells. We identified that tumors with lower tumor cell growth rate and higher carrying capacity have a stronger response to anti-VEGF treatment. The predictions indicate that the variation of tumor cell growth rate can be a main reason for the experimentally observed heterogeneous response to anti-VEGF. In addition, our simulation results suggest a new synergy mechanism where anticancer therapy can enhance anti-VEGF simply through reducing the tumor cell growth rate. Overall, this work generates novel insights into the heterogeneous response to anti-VEGF treatment and the synergy of anti-VEGF with other therapies, providing a tool that be further used to test and optimize anticancer therapy.</p>","PeriodicalId":72658,"journal":{"name":"Computational and systems oncology","volume":"1 2","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2021-03-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1002/cso2.1013","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computational and systems oncology","FirstCategoryId":"1085","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/cso2.1013","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Abstract
Vascular endothelial growth factor (VEGF) is a strong promoter of angiogenesis in tumors, and anti-VEGF treatment, such as a humanized antibody to VEGF, is clinically used as a monotherapy or in combination with chemotherapy to treat cancer patients. However, this approach is not effective in all patients or cancer types. To better understand the heterogeneous responses to anti-VEGF and the synergy between anti-VEGF and other anticancer therapies, we constructed a computational model characterizing angiogenesis-mediated growth of in vivo mouse tumor xenografts. The model captures VEGF-mediated cross-talk between tumor cells and endothelial cells and is able to predict the details of molecular- and cellular-level dynamics. The model predictions of tumor growth in response to anti-VEGF closely match the quantitative measurements from multiple preclinical mouse studies. We applied the model to investigate the effects of VEGF-targeted treatment on tumor cells and endothelial cells. We identified that tumors with lower tumor cell growth rate and higher carrying capacity have a stronger response to anti-VEGF treatment. The predictions indicate that the variation of tumor cell growth rate can be a main reason for the experimentally observed heterogeneous response to anti-VEGF. In addition, our simulation results suggest a new synergy mechanism where anticancer therapy can enhance anti-VEGF simply through reducing the tumor cell growth rate. Overall, this work generates novel insights into the heterogeneous response to anti-VEGF treatment and the synergy of anti-VEGF with other therapies, providing a tool that be further used to test and optimize anticancer therapy.