利用 DNA 测序数据检测到的拷贝数改变进行癌症系统发育推断

Bingxin Lu
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引用次数: 0

摘要

癌症是一个进化过程,涉及多种体细胞突变和克隆进化的积累。从单个患者身上获得的样本进行系统发育推断,为揭示癌症复杂的进化史提供了有力的方法,并为癌症治疗提供了见解。体细胞拷贝数改变(CNAs)在癌症进化中很重要,通常作为标记,单独或与其他体细胞突变一起用于系统发育推断,特别是在低覆盖率的DNA测序数据中。多年来,许多系统发育推断方法都是利用从大量或单细胞DNA测序数据中检测到的CNAs进行的。然而,目前还没有对这些方法进行系统的综述。为了总结该领域的最新进展并为未来的发展提供信息,本文对推理中的主要挑战、不同类型的方法以及这些方法的应用进行了全面的调查。从输入数据、进化模型和推理算法等方面讨论了这些挑战。不同的方法根据用于推理的标记和重建树的类型进行分组。应用包括使用系统发育推断来了解肿瘤内异质性、转移、治疗耐药性和早期癌症发展。这篇综述还揭示了使用CNAs进行癌症系统发育推断的未来方向,包括可扩展性的提高、新型数据的利用以及更现实的进化模型的发展。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Cancer phylogenetic inference using copy number alterations detected from DNA sequencing data

Cancer phylogenetic inference using copy number alterations detected from DNA sequencing data
Cancer is an evolutionary process involving the accumulation of diverse somatic mutations and clonal evolution over time. Phylogenetic inference from samples obtained from an individual patient offers a powerful approach to unraveling the intricate evolutionary history of cancer and provides insights that can inform cancer treatment. Somatic copy number alterations (CNAs) are important in cancer evolution and are often used as markers, alone or with other somatic mutations, for phylogenetic inferences, particularly in low-coverage DNA sequencing data. Many phylogenetic inference methods using CNAs detected from bulk or single-cell DNA sequencing data have been developed over the years. However, there have been no systematic reviews on these methods. To summarize the state-of-the-art of the field and inform future development, this review presents a comprehensive survey on the major challenges in inference, different types of methods, and applications of these methods. The challenges are discussed from the aspects of input data, models of evolution, and inference algorithms. The different methods are grouped according to the markers used for inference and the types of the reconstructed trees. The applications include using phylogenetic inference to understand intra-tumor heterogeneity, metastasis, treatment resistance, and early cancer development. This review also sheds light on future directions of cancer phylogenetic inference using CNAs, including the improvement of scalability, the utilization of new types of data, and the development of more realistic models of evolution.
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来源期刊
Cancer pathogenesis and therapy
Cancer pathogenesis and therapy Surgery, Radiology and Imaging, Cancer Research, Oncology
CiteScore
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