Inferring Growth Control Mechanisms in Growing Multi-cellular Spheroids of NSCLC Cells from Spatial-Temporal Image Data

摘要: We develop a quantitative single cell-based mathematical model for multi-cellular tumor spheroids (MCTS) of SK-MES-1 cells, non-small cell lung cancer (NSCLC) line, growing under various nutrient conditions: we confront the simulations performed with this data on growth kinetics and spatial labeling patterns proliferation, extracellular matrix (ECM), distribution death. start simple capturing part experimental observations. then show, by performing sensitivity analysis at each development stage that its complexity needs to be stepwise increased account further conditions. thus ultimately arrive mimics MCTS multiple conditions great extent. Interestingly, final model, is minimal capable explaining all simultaneously in sense, number mechanisms it contains sufficient explain missing out any did not permit fit between within physiological parameter ranges. Nevertheless, compared earlier models quite complex i.e., includes wide range discussed biological literature. In cells lacking oxygen switch from aerobe anaerobe glycolysis produce lactate. Too high concentrations lactate or too low ATP promote Only if density overcomes certain threshold, are able enter cycle. Dying diffusive inhibitor. Missing information would infer work. Our findings suggest iterative integration together intermediate stage, provide promising strategy predictive yet (in above sense) growth, as prospectively other tissue organization processes. Importantly, calibrating two nutriment-rich conditions, outcome nutriment-poor could predicted. As however complex, incorporating many mechanisms, space, time, stochastic processes, identification challenge. This calls more efficient strategies imaging image analysis, well agent-based simulations.