Development of a Computationally Optimized Model of Cancer-induced Angiogenesis through Specialized Cellular Mechanics

TL;DR

This paper presents a specialized computational model of cancer-induced angiogenesis that incorporates cellular mechanics and patient-specific factors to predict tumor criticality and angiogenesis success.

Contribution

It introduces a novel, optimized cellular mechanics model for angiogenesis that accounts for intercellular interactions and patient-specific parameters, enhancing predictive accuracy.

Findings

Critical angiogenesis limits identified at 102 m and 153 m.

Cell density and extracellular matrix fibers inhibit angiogenesis.

Model can potentially assess tumor criticality using medical imaging.

Abstract

Angiogenesis, the development of new vasculature, is a critical process in the growth of new tumors. Driven by a goal to understand this aspect of cancer proliferation, I develop a discrete computationally optimized mathematical model of angiogenesis that specializes in intercellular interactions. I model vascular endothelial growth factor spread and dynamics of endothelial cell movement in a competitive environment, with parameters specific to our model calculated through Dependent Variable Sensitivity Analysis (DVSA) and experimentally observed data. Through simulation testing, we find the critical limits of angiogenesis to be 102 m and 153 m respectively, beyond which angiogenesis will not successfully occur. Cell density in the surrounding region and the concentration of extracellular matrix fibers are also found to directly inhibit angiogenesis. Through these three factors, we postulate a method for establishing criticality of a tumor based upon the likelihood of angiogenesis completing. This research expands on other work by choosing factors that are patient-dependent through our specialized Cellular Potts mode, which serves to optimize and increase accuracy of the model. By doing such, I establish a theoretical framework for analyzing lesions using angiogenetic properties, with the ability to potentially compute the criticality of tumors with the aid of medical imaging technology.