Constraint-based modeling and simulation of cell populations

TL;DR

This paper extends constraint-based modeling to simulate cancer cell populations, capturing heterogeneity and cooperation among cells, which can improve understanding of tumor metabolism and treatment resistance.

Contribution

It introduces a novel population modeling approach that accounts for interactions and heterogeneity among cancer cells using constraint-based methods.

Findings

Cancer cells in the model cooperate to achieve common goals.

Heterogeneity arises from mismatched objectives between individual cells and the population.

The model highlights the importance of cell interactions in tumor metabolism.

Abstract

The intratumor heterogeneity has been recognized to characterize cancer cells impairing the efficacy of cancer treatments. We here propose an extension of constraint-based modeling approach in order to simulate metabolism of cell populations with the aim to provide a more complete characterization of these systems, especially focusing on the relationships among their components. We tested our methodology by using a toy-model and taking into account the main metabolic pathways involved in cancer metabolic rewiring. This toy-model is used as individual to construct a population model characterized by multiple interacting individuals, all having the same topology and stoichiometry, and sharing the same nutrients supply. We observed that, in our population, cancer cells cooperate with each other to reach a common objective, but without necessarily having the same metabolic traits. We also noticed that the heterogeneity emerging from the population model is due to the mismatch between the objective of the individual members and the objective of the entire population.