A computational study of VEGF production by patterned retinal epithelial cell colonies as a model for neovascular macular degeneration

• Main Authors: Qanita Bani Baker, Gregory J. Podgorski, Elizabeth Vargis, Nicholas S. Flann
• Format: Article
• Language: English
• Published: BMC 2017-08-01
• Series: Journal of Biological Engineering
• Subjects: Micropatterning; Auto-regulation; Vascular endothelial growth factor; Age-related macular degeneration; Retinal pigment epithelial cells
• Online Access: http://link.springer.com/article/10.1186/s13036-017-0063-6

Abstract Background The configuration of necrotic areas within the retinal pigmented epithelium is an important element in the progression of age-related macular degeneration (AMD). In the exudative (wet) and non-exudative (dry) forms of the disease, retinal pigment epithelial (RPE) cells respond to adjacent atrophied regions by secreting vascular endothelial growth factor (VEGF) that in turn recruits new blood vessels which lead to a further reduction in retinal function and vision. In vitro models exist for studying VEGF expression in wet AMD (Vargis et al., Biomaterials 35(13):3999–4004, 2014), but are limited in the patterns of necrotic and intact RPE epithelium they can produce and in their ability to finely resolve VEGF expression dynamics. Results In this work, an in silico hybrid agent-based model was developed and validated using the results of this cell culture model of VEGF expression in AMD. The computational model was used to extend the cell culture investigation to explore the dynamics of VEGF expression in different sized patches of RPE cells and the role of negative feedback in VEGF expression. Results of the simulation and the cell culture studies were in excellent qualitative agreement, and close quantitative agreement. Conclusions The model indicated that the configuration of necrotic and RPE cell-containing regions have a major impact on VEGF expression dynamics and made precise predictions of VEGF expression dynamics by groups of RPE cells of various sizes and configurations. Coupled with biological studies, this model may give insights into key molecular mechanisms of AMD progression and open routes to more effective treatments.