基因组进化塑造了前列腺癌的疾病类型。

IF 11.1 Q1 CELL BIOLOGY Cell genomics Pub Date : 2024-03-13 Epub Date: 2024-02-29 DOI:10.1016/j.xgen.2024.100511
Dan J Woodcock, Atef Sahli, Ruxandra Teslo, Vinayak Bhandari, Andreas J Gruber, Aleksandra Ziubroniewicz, Gunes Gundem, Yaobo Xu, Adam Butler, Ezequiel Anokian, Bernard J Pope, Chol-Hee Jung, Maxime Tarabichi, Stefan C Dentro, J Henry R Farmery, Peter Van Loo, Anne Y Warren, Vincent Gnanapragasam, Freddie C Hamdy, G Steven Bova, Christopher S Foster, David E Neal, Yong-Jie Lu, Zsofia Kote-Jarai, Michael Fraser, Robert G Bristow, Paul C Boutros, Anthony J Costello, Niall M Corcoran, Christopher M Hovens, Charlie E Massie, Andy G Lynch, Daniel S Brewer, Rosalind A Eeles, Colin S Cooper, David C Wedge
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引用次数: 0

摘要

癌症的发展是一个进化过程,涉及基因改变的连续获得,这些改变破坏了正常的生物过程,使肿瘤细胞迅速增殖,并最终侵入和转移到其他组织。我们通过应用三种不同的分类方法研究了前列腺癌的基因组进化,每种方法都旨在研究肿瘤进化的不同方面。综合这些结果,我们发现前列腺癌存在两种不同的类型,它们产生于不同的进化轨迹,分别被称为 "典型进化疾病类型 "和 "替代进化疾病类型"。因此,我们提出了前列腺癌进化的 evotype 模型,在该模型中,Alternative Evotype 肿瘤通过与雄激素受体 DNA 结合中断相关的基因改变的随机积累,从 Canonical Evotype 肿瘤中分化出来。我们的模型统一了以前的许多分子观察结果,为研究前列腺癌的疾病进展提供了一个强大的新框架。
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Genomic evolution shapes prostate cancer disease type.

The development of cancer is an evolutionary process involving the sequential acquisition of genetic alterations that disrupt normal biological processes, enabling tumor cells to rapidly proliferate and eventually invade and metastasize to other tissues. We investigated the genomic evolution of prostate cancer through the application of three separate classification methods, each designed to investigate a different aspect of tumor evolution. Integrating the results revealed the existence of two distinct types of prostate cancer that arise from divergent evolutionary trajectories, designated as the Canonical and Alternative evolutionary disease types. We therefore propose the evotype model for prostate cancer evolution wherein Alternative-evotype tumors diverge from those of the Canonical-evotype through the stochastic accumulation of genetic alterations associated with disruptions to androgen receptor DNA binding. Our model unifies many previous molecular observations, providing a powerful new framework to investigate prostate cancer disease progression.

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