基于肿瘤 DNA 测序数据重建肿瘤克隆异质性和进化关系。

IF 6.8 2区 生物学 Q1 BIOCHEMICAL RESEARCH METHODS
Zhen Wang, Yanhua Fang, Ruoyu Wang, Liwen Kong, Shanshan Liang, Shuai Tao
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引用次数: 0

摘要

肿瘤克隆的异质性推动了不同肿瘤细胞群的选择和进化,导致了错综复杂的动态肿瘤进化过程。虽然肿瘤大块DNA测序有助于阐明肿瘤内异质性,但拷贝数变异导致的突变多重性识别错误以及重建过程中的不确定性等挑战阻碍了肿瘤进化的准确推断。在这项研究中,我们引入了一种新方法--肿瘤克隆异质性和进化关系再构建(RETCHER),它通过准确识别突变多重性,同时考虑重建过程中的不确定性以及亚克隆聚类的可信度和合理性,来描述更真实的癌细胞组分。该方法全面准确地推断出多种形式的肿瘤克隆异质性和系统发育关系。RETCHER 在模拟数据上的表现优于现有方法,并能在五种肿瘤类型的真实多样本测序数据中推导出更清晰的亚克隆结构和进化关系。通过精确分析肿瘤内部复杂的克隆异质性,RETCHER 为肿瘤进化研究提供了一种新方法,并为制定精确的个性化治疗策略提供了科学依据。这种方法有望在肿瘤进化研究、临床诊断和治疗中发挥重要作用。RETCHER 可在 https://github.com/zlsys3/RETCHER 免费获取。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Reconstructing tumor clonal heterogeneity and evolutionary relationships based on tumor DNA sequencing data.

The heterogeneity of tumor clones drives the selection and evolution of distinct tumor cell populations, resulting in an intricate and dynamic tumor evolution process. While tumor bulk DNA sequencing helps elucidate intratumor heterogeneity, challenges such as the misidentification of mutation multiplicity due to copy number variations and uncertainties in the reconstruction process hinder the accurate inference of tumor evolution. In this study, we introduce a novel approach, REconstructing Tumor Clonal Heterogeneity and Evolutionary Relationships (RETCHER), which characterizes more realistic cancer cell fractions by accurately identifying mutation multiplicity while considering uncertainty during the reconstruction process and the credibility and reasonableness of subclone clustering. This method comprehensively and accurately infers multiple forms of tumor clonal heterogeneity and phylogenetic relationships. RETCHER outperforms existing methods on simulated data and infers clearer subclone structures and evolutionary relationships in real multisample sequencing data from five tumor types. By precisely analysing the complex clonal heterogeneity within tumors, RETCHER provides a new approach to tumor evolution research and offers scientific evidence for developing precise and personalized treatment strategies. This approach is expected to play a significant role in tumor evolution research, clinical diagnosis, and treatment. RETCHER is available for free at https://github.com/zlsys3/RETCHER.

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来源期刊
Briefings in bioinformatics
Briefings in bioinformatics 生物-生化研究方法
CiteScore
13.20
自引率
13.70%
发文量
549
审稿时长
6 months
期刊介绍: Briefings in Bioinformatics is an international journal serving as a platform for researchers and educators in the life sciences. It also appeals to mathematicians, statisticians, and computer scientists applying their expertise to biological challenges. The journal focuses on reviews tailored for users of databases and analytical tools in contemporary genetics, molecular and systems biology. It stands out by offering practical assistance and guidance to non-specialists in computerized methodologies. Covering a wide range from introductory concepts to specific protocols and analyses, the papers address bacterial, plant, fungal, animal, and human data. The journal's detailed subject areas include genetic studies of phenotypes and genotypes, mapping, DNA sequencing, expression profiling, gene expression studies, microarrays, alignment methods, protein profiles and HMMs, lipids, metabolic and signaling pathways, structure determination and function prediction, phylogenetic studies, and education and training.
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