RT Journal Article
SR Electronic
T1 A stochastic mathematical model of 4D tumour spheroids with real-time fluorescent cell cycle labelling
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 2021.11.28.470300
DO 10.1101/2021.11.28.470300
A1 Jonah J. Klowss
A1 Alexander P. Browning
A1 Ryan J. Murphy
A1 Elliot J. Carr
A1 Michael J. Plank
A1 Gency Gunasingh
A1 Nikolas K. Haass
A1 Matthew J. Simpson
YR 2021
UL http://biorxiv.org/content/early/2021/11/29/2021.11.28.470300.abstract
AB In vitro tumour spheroid experiments have been used to study avascular tumour growth and drug design for the last 50 years. Unlike simpler two-dimensional cell cultures, tumour spheroids exhibit heterogeneity within the growing population of cells that is thought to be related to spatial and temporal differences in nutrient availability. The recent development of real-time fluorescent cell cycle imaging allows us to identify the position and cell cycle status of individual cells within the growing population, giving rise to the notion of a four-dimensional (4D) tumour spheroid. In this work we develop the first stochastic individual-based model (IBM) of a 4D tumour spheroid and show that IBM simulation data qualitatively and quantitatively compare very well with experimental data from a suite of 4D tumour spheroid experiments performed with a primary human melanoma cell line. The IBM provides quantitative information about nutrient availability within the spheroid, which is important because it is very difficult to measure these data in standard tumour spheroid experiments. Software required to implement the IBM is available on GitHub, https://github.com/ProfMJSimpson/4DFUCCI.Competing Interest StatementThe authors have declared no competing interest.