西班牙Trevor A. Graham课题组揭示了波动的DNA甲基化在临床尺度上追踪癌症的演变。相关论文于2025年9月10日发表在《自然》杂志上。

在这里，该团队开发了一种名为EVOFLUx的新方法，该方法基于随时间波动的天然DNA甲基化条形码，可以定量地推断进化动力学，仅将大量的甲基化谱作为输入。研究小组将EVOFLUx应用于1976个特征明确的淋巴样癌样本，涵盖了广泛的疾病，结果显示，不同疾病类型的初始肿瘤生长速度、恶性肿瘤年龄和上皮化率存在数量级差异。课题组测量亚克隆选择只在大量样本中很少发生，并且偶尔检测到多个独立原发肿瘤的例子。在临床上，该研究组观察到更具侵袭性的疾病亚型的初始肿瘤生长更快，并且在两种慢性淋巴细胞白血病系列中，进化历史是强大的独立预后因素。使用EVOFLUx对侵袭性里希特转化慢性淋巴细胞白血病样本进行系统发育分析，发现转化克隆的种子在出现前几十年就存在了。EVOFLUx推论的正交验证提供了额外的遗传数据，包括长读纳米孔测序和临床变量。总的来说，研究组展示了广泛可用的、低成本的大量DNA甲基化数据如何精确地测量癌症的进化动态，并为癌症生物学和临床行为提供了新的见解。

据介绍，癌症的发展和对治疗的反应是一个进化过程，但在临床有意义的尺度上描述进化动力学仍然具有挑战性。

附：英文原文

Title: Fluctuating DNA methylation tracks cancer evolution at clinical scale

Author: Gabbutt, Calum, Duran-Ferrer, Mart, Grant, Heather E., Mallo, Diego, Nadeu, Ferran, Househam, Jacob, Villamor, Neus, Mller, Madlen, Heath, Simon, Raineri, Emanuele, Krali, Olga, Nordlund, Jessica, Zenz, Thorsten, Gut, Ivo G., Campo, Elias, Lopez-Guillermo, Armando, Fitzgibbon, Jude, Barnes, Chris P., Shibata, Darryl, Martin-Subero, Jos I., Graham, Trevor A.

Issue&Volume: 2025-09-10

Abstract: Cancer development and response to treatment are evolutionary processes1,2, but characterizing evolutionary dynamics at a clinically meaningful scale has remained challenging3. Here we develop a new methodology called EVOFLUx, based on natural DNA methylation barcodes fluctuating over time4, that quantitatively infers evolutionary dynamics using only a bulk tumour methylation profile as input. We apply EVOFLUx to 1,976 well-characterized lymphoid cancer samples spanning a broad spectrum of diseases and show that initial tumour growth rate, malignancy age and epimutation rates vary by orders of magnitude across disease types. We measure that subclonal selection occurs only infrequently within bulk samples and detect occasional examples of multiple independent primary tumours. Clinically, we observe faster initial tumour growth in more aggressive disease subtypes, and that evolutionary histories are strong independent prognostic factors in two series of chronic lymphocytic leukaemia. Using EVOFLUx for phylogenetic analyses of aggressive Richter-transformed chronic lymphocytic leukaemia samples detected that the seed of the transformed clone existed decades before presentation. Orthogonal verification of EVOFLUx inferences is provided using additional genetic data, including long-read nanopore sequencing, and clinical variables. Collectively, we show how widely available, low-cost bulk DNA methylation data precisely measure cancer evolutionary dynamics, and provides new insights into cancer biology and clinical behaviour.

DOI: 10.1038/s41586-025-09374-4

Source: https://www.nature.com/articles/s41586-025-09374-4