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Mechanistic insight into activation of MAPK signaling by pro-angiogenic factors
Min Song1, Stacey D Finley2,3,4
1Department of Biomedical Engineering, University of Southern California, Los Angeles, California, USA.
Background:
Angiogenesis is important in physiological and pathological conditions, as blood vessels provide nutrients and oxygen needed for tissue growth and survival. Therefore, targeting angiogenesis is a prominent strategy in both tissue engineering and cancer treatment. However, not all of the approaches to promote or inhibit angiogenesis lead to successful outcomes. Angiogenesis-based therapies primarily target pro-angiogenic factors such as vascular endothelial growth factor-A (VEGF) or fibroblast growth factor (FGF) in isolation. However, pre-clinical and clinical evidence shows these therapies often have limited effects. To improve therapeutic strategies, including targeting FGF and VEGF in combination, we need a quantitative understanding of the how the promoters combine to stimulate angiogenesis.
Results:
In this study, we trained and validated a detailed mathematical model to quantitatively characterize the crosstalk of FGF and VEGF intracellular signaling. This signaling is initiated by FGF binding to the FGF receptor 1 (FGFR1) and heparan sulfate glycosaminoglycans (HSGAGs) or VEGF binding to VEGF receptor 2 (VEGFR2) to promote downstream signaling. The model focuses on FGF- and VEGF-induced mitogen-activated protein kinase (MAPK) signaling and phosphorylation of extracellular regulated kinase (ERK), which promotes cell proliferation. We apply the model to predict the dynamics of phosphorylated ERK (pERK) in response to the stimulation by FGF and VEGF individually and in combination. The model predicts that FGF and VEGF have differential effects on pERK. Additionally, since VEGFR2 upregulation has been observed in pathological conditions, we apply the model to investigate the effects of VEGFR2 density and trafficking parameters. The model predictions show that these parameters significantly influence the response to VEGF stimulation.
Conclusions:
The model agrees with experimental data and is a framework to synthesize and quantitatively explain experimental studies. Ultimately, the model provides mechanistic insight into FGF and VEGF interactions needed to identify potential targets for pro- or anti-angiogenic therapies.
Insights
A mathematical model quantitatively explains how fibroblast growth factor (FGF) and vascular endothelial growth factor (VEGF) signaling interact to control cell proliferation, aiding in the development of improved angiogenesis therapies.
Area of Science:
- Biochemistry
- Cell Biology
- Mathematical Biology
Background:
- Angiogenesis is crucial for tissue growth and survival, making it a key target in tissue engineering and cancer therapy.
- Current therapies targeting individual pro-angiogenic factors like VEGF and FGF show limited efficacy.
- A quantitative understanding of combined FGF and VEGF signaling is needed to improve therapeutic strategies.
Purpose of the Study:
- To develop and validate a mathematical model characterizing the intracellular crosstalk between FGF and VEGF signaling pathways.
- To quantitatively analyze the combined effects of FGF and VEGF on downstream signaling, specifically MAPK/ERK pathway activation.
- To investigate the influence of VEGFR2 expression and trafficking on cellular response to VEGF.
Main Methods:
- Trained and validated a detailed mathematical model of FGF and VEGF intracellular signaling.
- Focused the model on FGF/FGFR1 and VEGF/VEGFR2 initiated MAPK signaling, leading to ERK phosphorylation.
- Applied the model to predict phosphorylated ERK (pERK) dynamics under individual and combined FGF/VEGF stimulation.
Main Results:
- The model quantitatively characterizes the crosstalk between FGF and VEGF signaling pathways.
- FGF and VEGF were predicted to have differential effects on ERK phosphorylation.
- Model simulations demonstrated that VEGFR2 density and trafficking significantly impact cellular response to VEGF.
Conclusions:
- The mathematical model aligns with experimental data, providing a framework for synthesizing and explaining experimental findings.
- The model offers mechanistic insights into FGF and VEGF interactions.
- This quantitative understanding can guide the identification of novel therapeutic targets for modulating angiogenesis.
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