Metabolic symbiosis between oxygenated and hypoxic tumour cells: An agent-based modelling study
Fig 2
Agent-based mathematical model.
(A). The model is a multi-scale agent-based model implemented using the NetLogo platform. The extra-cellular scale models gradients of substances such as oxygen, glucose and lactate by using partial differential equations. The cellular scale models cell-cell interactions using a cellular automaton approach. The smallest scale, the intra-cellular scale, handles subcellular molecular interactions using a Boolean gene regulatory network. All scales communicate with each other and therefore the tumour growth is an emerging property of the sub-cellular molecular interactions. The model can be used to study tumour growth under different environmental conditions, gene alterations and heterogeneous cell populations (created with BioRender.com). (B). The model flow chart shows how the three different scales are connected. If the local oxygen and glucose levels are below their respective threshold values, the cell becomes necrotic. If the cell is not in the necrotic state, the intra-cellular regulatory network determines the cell fate which is Proliferation or Apoptosis or Growth Arrest. An apoptotic cell is removed from the simulation immediately. A proliferative cell can divide if there is empty space nearby, otherwise it can switch to growth arrest state and waits a TQ time before checking environmental conditions again to find its new phenotype. The cell phenotype can influence the gradients of the diffusible substances on the microenvironment through producing/consuming diffusible substances based on its phenotype. The altered environmental properties are fed to the intra-cellular network of the cell again through input nodes and then the network can decide its new phenotype according to altered microenvironmental conditions.