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

被引：5
|
作者：
Streck, Adam [1 ,2 ,3 ]
Kaufmann, Tom L. [1 ,2 ,3 ,4 ]
Schwarz, Roland F. [1 ,2 ,3 ,4 ]
机构：
[1] Berlin Inst Med Syst Biol, Max Delbruck Ctr Mol Med Helmholtz Assoc, Berlin, Germany
[2] Univ Hosp Cologne, Inst Computat Canc Biol ICCB, Fac Med, Ctr Integrated Oncol CIO,Canc Res Ctr Cologne Esse, Cologne, Germany
[3] Univ Cologne, Univ Hosp Cologne, Cologne, Germany
[4] BIFOLD Berlin Inst Fdn Learning & Data, Berlin, Germany
来源：
BIOINFORMATICS | 2023年 / 39卷 / 03期
关键词：
PASSENGER MUTATIONS; EVOLUTION; CANCER; NUMBER;
D O I：
10.1093/bioinformatics/btad102
中图分类号：
Q5 [生物化学];
学科分类号：
071010 ; 081704 ;
摘要：
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.
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收藏
页数：8
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