Understanding post-angiogenic tumor growth: Insights from vascular network properties in cellular automata modeling

Angiogenesis plays a crucial role in tumor progression and is a key target for cancer therapy. This study utilizes a novel cellular automata model to explore post-angiogenic tumor growth, focusing on vascular network properties. We simulate the effects of Vascular Disrupting Agents (VDA) and radiotherapy, analyzing how network parameters, such as clustering coefficient and degree distribution, influence tumor progression and treatment outcomes. Our model reveals that highly clustered vascular networks with low average path lengths are more resistant to VDA therapy and radiotherapy, whereas more homogeneous networks are more susceptible. Disruptions in network integrity significantly impair nutrient delivery, leading to heterogeneous tumor growth patterns. Quantitative analyses show strong correlations between network metrics and treatment response, suggesting that targeted modulation of vascular network properties could enhance therapeutic effectiveness. These findings offer new insights into tumor-vascular interactions and propose potential avenues for optimizing cancer treatment protocols.