SMITH: spatially constrained stochastic model for simulation of intra-tumour heterogeneity

• Published in: Bioinformatics (Oxford, England) Vol. 39; no. 3
• Main Authors: Streck, Adam, Kaufmann, Tom L, Schwarz, Roland F
• Format: Journal Article
• Language: English
• Published: England Oxford University Press 01-03-2023
• Subjects: Computer Simulation; Humans; Neoplasms - genetics; Original Paper; Software
• ISSN: 1367-4803; 1367-4811
• DOI: 10.1093/bioinformatics/btad102

Abstract
Motivation
Simulations of cancer evolution are highly useful to study the effects of selection and mutation rates on cellular fitness. However, most methods are either lattice-based and cannot simulate realistically sized tumours, or they omit spatial constraints and lack the clonal dynamics of real-world tumours.
Results
Stochastic model of intra-tumour heterogeneity (SMITH) is an efficient and explainable model of cancer evolution that combines a branching process with a new confinement mechanism limiting clonal growth based on the size of the individual clones as well as the overall tumour population. We demonstrate how confinement is sufficient to induce the rich clonal dynamics observed in spatial models and cancer samples across tumour types, while allowing for a clear geometric interpretation and simulation of 1 billion cells within a few minutes on a desktop PC.
Availability and implementation
SMITH is implemented in C# and freely available at https://bitbucket.org/schwarzlab/smith. For visualizations, we provide the accompanying Python package PyFish at https://bitbucket.org/schwarzlab/pyfish.
Supplementary information
Supplementary data are available at Bioinformatics online.