A cellular automaton model for hypoxia effects on tumour growth dynamics

Cancer is one of the biggest killers in the western world; every two minutes someone is diagnosed with cancer in the UK. Tumour growth and progression is a complex biological process, normally beginning with genetic mutations in a single cell. It starts with the early or avascular phase where growth is limited by nutrient diffusion, then the vascular stage where angiogenesis occurs to stimulate blood vessel production by the secretion of tumour angiogenesis factors and finally the metastasitic phase where the tumour spreads from the site of origin to distant sites around the body. While considering these events at the cellular level, these processes involve many microenvironment parameters like oxygen concentration, hypoglycaemia, acidity, hypoxia (lack of oxygen), cell-cell adhesion, cell migration and cell-extracellular matrix interactions. In this paper, a computational model is proposed which considered hypoxia as a microenvironment constraint of tumour growth. The model is built on two dimensional cellular automata grid and artificial neural network is considered for establishing signaling network of tumour cells. Each tumour cell can take its own decision in this model. A hypoxia impact was implemented in the model by varying different oxygen concentrations. The results show that hypoxia was introduced in the tumour mass due to lack of oxygen. The model measured tumour invasion and the number of apoptotic cells to support that hypoxia has a critical impacts on avascular tumour growth. This model could inform a better understanding of the impacts of hypoxia in tumour growth from the computational point of view.