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单细胞基因表达适应性的随机建模揭示了肿瘤亚克隆进化的非基因组贡献。

Stochastic modeling of single-cell gene expression adaptation reveals non-genomic contribution to evolution of tumor subclones.

作者信息

Hirsch M G, Pal Soumitra, Rashidi Mehrabadi Farid, Malikic Salem, Gruen Charli, Sassano Antonella, Pérez-Guijarro Eva, Merlino Glenn, Sahinalp S Cenk, Molloy Erin K, Day Chi-Ping, Przytycka Teresa M

机构信息

National Library of Medicine (NLM), National Institutes of Health (NIH), Bethesda, MD 20892, USA; Department of Computer Science, University of Maryland, College Park, MD 20742, USA.

Neurobiology Neurodegeneration and Repair Lab, National Eye Institute (NEI), National Institutes of Health (NIH), Bethesda, MD 20892, USA.

出版信息

Cell Syst. 2025 Jan 15;16(1):101156. doi: 10.1016/j.cels.2024.11.013. Epub 2024 Dec 18.

DOI:10.1016/j.cels.2024.11.013
PMID:39701099
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11867576/
Abstract

Cancer progression is an evolutionary process driven by the selection of cells adapted to gain growth advantage. We present a formal study on the adaptation of gene expression in subclonal evolution. We model evolutionary changes in gene expression as stochastic Ornstein-Uhlenbeck processes, jointly leveraging the evolutionary history of subclones and single-cell expression data. Applying our model to sublines derived from single cells of a mouse melanoma revealed that sublines with distinct phenotypes are underlined by different patterns of gene expression adaptation, indicating non-genetic mechanisms of cancer evolution. Sublines previously observed to be resistant to anti-CTLA4 treatment showed adaptive expression of genes related to invasion and non-canonical Wnt signaling, whereas sublines that responded to treatment showed adaptive expression of genes related to proliferation and canonical Wnt signaling. Our results suggest that clonal phenotypes emerge as the result of specific adaptivity patterns of gene expression. A record of this paper's transparent peer review process is included in the supplemental information.

摘要

癌症进展是一个由适应获得生长优势的细胞选择驱动的进化过程。我们对亚克隆进化中基因表达的适应性进行了一项正式研究。我们将基因表达的进化变化建模为随机奥恩斯坦-乌伦贝克过程,联合利用亚克隆的进化历史和单细胞表达数据。将我们的模型应用于源自小鼠黑色素瘤单细胞的亚系,发现具有不同表型的亚系由不同的基因表达适应模式所支撑,这表明癌症进化的非遗传机制。先前观察到对抗CTLA4治疗有抗性的亚系显示出与侵袭和非经典Wnt信号相关的基因的适应性表达,而对治疗有反应的亚系显示出与增殖和经典Wnt信号相关的基因的适应性表达。我们的结果表明,克隆表型是基因表达特定适应性模式的结果。本文透明同行评审过程的记录包含在补充信息中。

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本文引用的文献

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Messing with cancer therapy: how the melanoma phenotype predicts checkpoint inhibitor response.干预癌症治疗:黑色素瘤表型如何预测免疫检查点抑制剂反应。
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Stochastic Modeling of Gene Expression Evolution Uncovers Tissue- and Sex-Specific Properties of Expression Evolution in the Genus.基因表达进化的随机建模揭示了属中表达进化的组织和性别特异性特征。
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