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史密斯:用于模拟肿瘤内异质性的空间约束随机模型。

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

机构信息

Max Delbrück Center for Molecular Medicine in the Helmholtz Association, Berlin Institute for Medical Systems Biology, Berlin, Germany.

Institute for Computational Cancer Biology (ICCB), Center for Integrated Oncology (CIO), Cancer Research Center Cologne Essen (CCCE), Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany.

出版信息

Bioinformatics. 2023 Mar 1;39(3). 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.

摘要

动机

癌症进化的模拟对于研究选择和突变率对细胞适应性的影响非常有用。然而,大多数方法要么基于晶格,无法真实模拟肿瘤的大小,要么忽略空间约束,缺乏真实肿瘤的克隆动力学。

结果

肿瘤内异质性的随机模型(SMITH)是一种有效的、可解释的癌症进化模型,它将分支过程与一种新的限制机制相结合,根据个体克隆的大小以及整个肿瘤群体来限制克隆的生长。我们证明了限制是如何足以诱导在空间模型和癌症样本中观察到的丰富的克隆动力学的,同时允许对 10 亿个细胞进行清晰的几何解释和模拟,并且可以在桌面 PC 上在几分钟内完成。

可用性和实现

SMITH 是用 C#实现的,并在 https://bitbucket.org/schwarzlab/smith 上免费提供。对于可视化,我们在 https://bitbucket.org/schwarzlab/pyfish 上提供了配套的 Python 包 PyFish。

补充信息

补充数据可在《生物信息学》在线获取。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8baa/10010604/b14ac186341b/btad102f1.jpg

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