Abstract

Multicellular tumour spheroids capture many characteristics of human tumour microenvironments, including hypoxia, and represent an experimentally tractable in vitro model for studying interactions between radiotherapy and anticancer drugs. However, interpreting spheroid data is challenging because of limited ability to observe cell fate within spheroids dynamically. To overcome this limitation, we have developed a hybrid continuum/agent-based model (ABM) for HCT116 tumour spheroids, parameterised using experimental models (monolayers and multilayers) in which reaction and diffusion can be measured directly. In the ABM, cell fate is simulated as a function of local oxygen, glucose and drug concentrations, determined by solving diffusion equations and intracellular reactions. The model is lattice-based, with cells occupying discrete locations on a 3D grid embedded within a coarser grid that encompasses the culture medium; separate solvers are employed for each grid. The generated concentration fields account for depletion in the medium and specify concentration-time profiles within the spheroid. Cell growth and survival are determined by intracellular oxygen and glucose concentrations, the latter based on direct measurement of glucose diffusion/reaction (in multilayers) for the first time. The ABM reproduces known features of spheroids including overall growth rate, its oxygen and glucose dependence, peripheral cell proliferation, central hypoxia and necrosis. We extended the ABM to describe in detail the hypoxia-dependent interaction between ionising radiation and a hypoxia-activated prodrug (SN30000), again using experimentally determined parameters; the model accurately simulated clonogenic cell killing in spheroids, while inclusion of reversible cell cycle delay was required to account for the marked spheroid growth delay after combined radiation and SN30000. This ABM of spheroid growth and response exemplifies the utility of integrating computational and experimental tools for investigating radiation/drug interactions, and highlights the critical importance of understanding oxygen, glucose and drug concentration gradients in interpreting activity of therapeutic agents in spheroid models.

Highlights

  • Mathematical modelling is gaining increasing attention in the field of cancer research because of advantages such as spatial and dynamic monitoring, visualisation and high-throughput testing [1,2]

  • We have developed a hybrid continuum/agent-based mathematical model, validated by experiments, to aid interpretation of spheroid experiments in developing drugs designed to eliminate radiation-resistant hypoxic cells

  • This model includes key features of the tumour microenvironment including oxygen and glucose transport and regions of hypoxia where the cells are resistant to radiation, but sensitive to hypoxia-activated prodrugs such as SN30000

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Summary

Introduction

Mathematical modelling is gaining increasing attention in the field of cancer research because of advantages such as spatial and dynamic monitoring, visualisation and high-throughput testing [1,2]. Development of 3D multiscale agent-based models that capture key features of the tumour microenvironment have the potential to significantly improve the interpretation of responses to therapeutic agents and to speed up drug development, regimen optimisation and understanding of therapeutic interactions. In vitro three-dimensional (3D) cell cultures, including multicellular tumour spheroids and multicellular layers (MCLs), capture many features of real tumours, and have advantages over monolayer cell culture for developing drugs. In particular they experimentally model key aspects of the tumour microenvironment that influence therapeutic response including oxygen, nutrient, pH and prodrug/drug diffusion gradients and the resulting microregional variations in gene expression, cell cycle kinetics and cell death [3,4]. Advances in spheroid culture techniques enable highthroughput production of uniform spheroids, it has proved technically challenging to use spheroids to test complex schedules of drug or radiation combinations and to interpret the data, due to the lack of available non-destructive quantitative endpoints [5,6]

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