TrAp：一种亚克隆肿瘤成分指纹树方法
TrAp: a Tree Approach for Fingerprinting Subclonal Tumor Composition
摘要：
揭示单个肿瘤的克隆组成对于鉴定原发性肿瘤中具有转移潜力或转移性肿瘤中对治疗具有抗性的细胞亚群至关重要。测序技术提供了大量细胞聚集体的概述，而不是畸变（如单核苷酸变异体（SNV））的亚克隆特异性定量。将来自肿瘤样品的混合细胞群体的单个集合信号解混成其单个组分的计算方法目前不可用。在这里，我们提出了一个框架，从一个单一的全基因组实验的数据去卷积，以推断肿瘤的基本细胞亚群的组成，丰度和进化路径。该方法基于合理的生物学假设，即肿瘤进展是一个进化过程，其中每个个体畸变事件源于独特的亚克隆，并且存在于其所有后代亚克隆中。我们已经开发了一个有效的算法（TrAp）解决这个混合问题。计算机模拟分析表明，当亚群数量和测量误差适中时，TrAp正确地对混合亚群进行去卷积。我们使用肿瘤核型和体细胞超突变数据集证明了该方法的适用性。我们将TrAp应用于来自肾细胞癌肿瘤样品的Exome-Seq实验的SNV频率谱，并将推断的亚群的突变谱与相同肿瘤的二十个单细胞的突变谱进行比较。尽管实验噪音很大，但在由TrAp推断的克隆中发现的特定共发生突变也存在于这些单细胞中的一些中。最后，我们对来自一个黑色素瘤患者的不同身体隔室的三个不同转移灶的Exome-Seq数据进行去卷积，并展示其亚群的进化关系。
英文摘要：
Revealing the clonal composition of a single tumor is essential for identifying cell subpopulations with metastatic potential in primary tumors or with resistance to therapies in metastatic tumors. Sequencing technologies provide an overview of an aggregate of numerous cells, rather than subclonal-specific quantification of aberrations such as single nucleotide variants (SNVs). Computational approaches to de-mix a single collective signal from the mixed cell population of a tumor sample into its individual components are currently not available. Herein we propose a framework for deconvolving data from a single genome-wide experiment to infer the composition, abundance and evolutionary paths of the underlying cell subpopulations of a tumor. The method is based on the plausible biological assumption that tumor progression is an evolutionary process where each individual aberration event stems from a unique subclone and is present in all its descendants subclones. We have developed an efficient algorithm (TrAp) for solving this mixture problem. In silico analyses show that TrAp correctly deconvolves mixed subpopulations when the number of subpopulations and the measurement errors are moderate. We demonstrate the applicability of the method using tumor karyotypes and somatic hypermutation datasets. We applied TrAp to SNV frequency profile from Exome-Seq experiment of a renal cell carcinoma tumor sample and compared the mutational profile of the inferred subpopulations to the mutational profiles of twenty single cells of the same tumor. Despite the large experimental noise, specific co-occurring mutations found in clones inferred by TrAp are also present in some of these single cells. Finally, we deconvolve Exome-Seq data from three distinct metastases from different body compartments of one melanoma patient and exhibit the evolutionary relationships of their subpopulations.
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