Esentürk Emre, Sahli Atef, Haberland Valeriia, Ziuboniewicz Aleksandra, Wirth Christopher, Bova G Steven, Bristow Robert G, Brook Mark N, Brors Benedikt, Butler Adam, Cancel-Tassin Géraldine, Cheng Kevin Cl, Cooper Colin S, Corcoran Niall M, Cussenot Olivier, Eeles Ros A, Favero Francesco, Gerhauser Clarissa, Gihawi Abraham, Girma Etsehiwot G, Gnanapragasam Vincent J, Gruber Andreas J, Hamid Anis, Hayes Vanessa M, He Housheng Hansen, Hovens Christopher M, Imada Eddie Luidy, Jakobsdottir G Maria, Jung Chol-Hee, Khani Francesca, Kote-Jarai Zsofia, Lamy Philippe, Leeman Gregory, Loda Massimo, Lutsik Pavlo, Marchionni Luigi, Molania Ramyar, Papenfuss Anthony T, Pellegrina Diogo, Pope Bernard, Queiroz Lucio R, Rausch Tobias, Reimand Jüri, Robinson Brian, Schlomm Thorsten, Sørensen Karina D, Uhrig Sebastian, Weischenfeldt Joachim, Xu Yaobo, Yamaguchi Takafumi N, Zanettini Claudio, Lynch Andy G, Wedge David C, Brewer Daniel S, Woodcock Dan J
Nuffield Department of Medicine, University of Oxford, UK.
Manchester Cancer Research Centre, The University of Manchester, UK.
ArXiv. 2025 Mar 17:arXiv:2503.13189v1.
Cancer progression involves the sequential accumulation of genetic alterations that cumulatively shape the tumour phenotype. In prostate cancer, tumours can follow divergent evolutionary trajectories that lead to distinct subtypes, but the causes of this divergence remain unclear. While causal inference could elucidate the factors involved, conventional methods are unsuitable due to the possibility of unobserved confounders and ambiguity in the direction of causality. Here, we propose a method that circumvents these issues and apply it to genomic data from 829 prostate cancer patients. We identify several genetic alterations that drive divergence as well as others that prevent this transition, locking tumours into one trajectory. Further analysis reveals that these genetic alterations may cause each other, implying a positive-feedback loop that accelerates divergence. Our findings provide insights into how cancer subtypes emerge and offer a foundation for genomic surveillance strategies aimed at monitoring the progression of prostate cancer.
癌症进展涉及基因改变的逐步积累,这些改变共同塑造了肿瘤表型。在前列腺癌中,肿瘤可能遵循不同的进化轨迹,导致不同的亚型,但这种差异的原因仍不清楚。虽然因果推断可以阐明其中涉及的因素,但由于存在未观察到的混杂因素以及因果关系方向的模糊性,传统方法并不适用。在此,我们提出一种方法来规避这些问题,并将其应用于829名前列腺癌患者的基因组数据。我们确定了几种驱动差异的基因改变以及其他阻止这种转变的改变,从而将肿瘤锁定在一种轨迹上。进一步分析表明,这些基因改变可能相互影响,这意味着存在一个加速差异的正反馈回路。我们的研究结果为癌症亚型如何出现提供了见解,并为旨在监测前列腺癌进展的基因组监测策略奠定了基础。