Inferring cell dynamics in stress-induced neuroblastoma cell cultures

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Abstract

Neuroblastoma is characterised by significant intratumoural heterogeneity which complicates treatments. Phenotypic plasticity, i.e., the ability of cells to alter their phenotype without genetic mutations, is a key factor contributing to this heterogeneity. In this study, we quantify cell actions and cell-to-cell interactions that lead to phenotypic adaptation in vitro under stress, specifically low-nutrient conditions. We initially record dynamic cell counts under various nutrient conditions for two neuroblastoma cell lines with known phenotype differences. Subsequently, we compile a list of plausible biological processes that could transpire within the aforementioned systems. We then construct candidate models employing mass-action kinetics. To quantitatively infer processes that lead to phenotypic adaptation, we perform a model selection based on computational Bayesian inference methods.Our results suggest that cell-to-cell interactions promote phenotypic adaptation and that the rate of this adaptation increases with decreasing nutrient concentrations. We perform flow cytometry-based experiments to corroborate changes in phenotype composition in response to both nutrient-deprived and treatmentinduced stress conditions.
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Abstract Neuroblastoma is characterised by significant intratumoural heterogeneity which complicates treatments. Phenotypic plasticity, i.e., the ability of cells to alter their phenotype without genetic mutations, is a key factor contributing to this heterogeneity. In this study, we quantify cell actions and cell-to-cell interactions that lead to phenotypic adaptation in vitro under stress, specifically low-nutrient conditions. We initially record dynamic cell counts under various nutrient conditions for two neuroblastoma cell lines with known phenotype differences. Subsequently, we compile a list of plausible biological processes that could transpire within the aforementioned systems. We then construct candidate models employing mass-action kinetics. To quantitatively infer processes that lead to phenotypic adaptation, we perform a model selection based on computational Bayesian inference methods.Our results suggest that cell-to-cell interactions promote phenotypic adaptation and that the rate of this adaptation increases with decreasing nutrient concentrations. We perform flow cytometry-based experiments to corroborate changes in phenotype composition in response to both nutrient-deprived and treatmentinduced stress conditions. Competing Interest Statement The authors have declared no competing interest. Footnotes Updated text and formatting; proper referencing updates whenever possible and manuscript detailing updated

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europepmc
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License: CC-BY-NC-ND-4.0