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

被引:73
作者
Finley, Stacey D. [1 ]
Popel, Aleksander S. [1 ,2 ]
机构
[1] Johns Hopkins Univ, Sch Med, Dept Biomed Engn, Baltimore, MD 21205 USA
[2] Johns Hopkins Univ, Sch Med, Sidney Kimmel Comprehens Canc Ctr, Baltimore, MD 21205 USA
来源
JNCI-JOURNAL OF THE NATIONAL CANCER INSTITUTE | 2013年 / 105卷 / 11期
基金
美国国家卫生研究院;
关键词
ENDOTHELIAL-GROWTH-FACTOR; MALIGNANT PLEURAL EFFUSION; PLATELET ALPHA-GRANULES; SPLICE VARIANTS; MATRIX-METALLOPROTEINASE; PROGNOSTIC-SIGNIFICANCE; ANTIANGIOGENIC THERAPY; ANGIOGENIC ISOFORMS; FACTOR EXPRESSION; CAPILLARY GROWTH;
D O I
10.1093/jnci/djt093
中图分类号
R73 [肿瘤学];
学科分类号
100214 ;
摘要
Vascular endothelial growth factor (VEGF) is known to be a potent promoter of angiogenesis under both physiological and pathological conditions. Given its role in regulating tumor vascularization, VEGF has been targeted in various cancer treatments, and anti-VEGF therapy has been used clinically for treatment of several types of cancer. Systems biology approaches, particularly computational models, provide insight into the complexity of tumor angiogenesis. These models complement experimental studies and aid in the development of effective therapies targeting angiogenesis. We developed an experiment-based, molecular-detailed compartment model of VEGF kinetics and transport to investigate the distribution of two major VEGF isoforms (VEGF(121) and VEGF(165)) in the body. The model is applied to predict the dynamics of tumor VEGF and, importantly, to gain insight into how tumor VEGF responds to an intravenous injection of an anti-VEGF agent. The model predicts that free VEGF in the tumor interstitium is seven to 13 times higher than plasma VEGF and is predominantly in the form of VEGF(121) (> 70%), predictions that are validated by experimental data. The model also predicts that tumor VEGF can increase or decrease with anti-VEGF treatment depending on tumor microenvironment, pointing to the importance of personalized medicine. This computational study suggests that the rate of VEGF secretion by tumor cells may serve as a biomarker to predict the patient population that is likely to respond to anti-VEGF treatment. Thus, the model predictions have important clinical relevance and may aid clinicians and clinical researchers seeking interpretation of pharmacokinetic and pharmacodynamic observations and optimization of anti-VEGF therapies.
引用
收藏
页码:802 / 811
页数:10
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