TrAp: a tree approach for fingerprinting subclonal tumor composition.
TrAp: a tree approach for fingerprinting subclonal tumor composition.
复制标题
陷阱：用于指纹下克隆肿瘤组成的树方法。
DOI：
10.1093/nar/gkt641
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发表时间：
2013-09
影响因子：
14.9
通讯作者：
Kluger Y
中科院分区：
文献类型：
--
作者：
Strino F;Parisi F;Micsinai M;Kluger Y
揭示单个肿瘤的克隆组成对于识别原发性肿瘤中具有转移潜力或转移性肿瘤中具有治疗耐药性的细胞亚群至关重要。测序技术仅提供大量细胞聚集体的概览。目前还没有将由肿瘤样本的混合细胞群的畸变组成的集体信号分解为其各个成分的计算方法。我们提出了一个进化框架，用于对来自单个全基因组实验的数据进行去卷积，以推断肿瘤基础细胞亚群的组成、丰度和进化路径。我们开发了一种算法（TrAp）来解决这个混合问题。计算机分析表明，当亚群数量和测量误差适中时，TrAp 可以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 应用于肾细胞癌肿瘤样本的外显子组测序实验，并将推断的亚群的突变谱与同一肿瘤的单细胞的突变谱进行比较。最后，我们对来自八名急性髓系白血病患者和一名黑色素瘤患者的三个不同转移的测序数据进行去卷积，以展示其亚群的进化关系。
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 only an overview of the aggregate of numerous cells. Computational approaches to de-mix a collective signal composed of the aberrations of a mixed cell population of a tumor sample into its individual components are not available. We propose an evolutionary 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. We have developed an 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 data sets. We applied TrAp to Exome-Seq experiment of a renal cell carcinoma tumor sample and compared the mutational profile of the inferred subpopulations to the mutational profiles of single cells of the same tumor. Finally, we deconvolve sequencing data from eight acute myeloid leukemia patients and three distinct metastases of one melanoma patient to exhibit the evolutionary relationships of their subpopulations.
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影响因子：
64.8
作者：
通讯作者：
--
影响因子：
4.9
作者：
Clement, M;Posada, D;Crandall, KA
通讯作者：
Crandall, KA
DOI：
10.1111/j.1749-6632.2009.04880.x
发表时间：
2009-01-01
期刊：
YEAR IN EVOLUTIONARY BIOLOGY 2009
影响因子：
--
作者：
Attolini, Camille Stephan-Otto;Michor, Franziska
通讯作者：
Michor, Franziska
影响因子：
1
作者：
Catanzaro, Daniele;Ravi, Ramamoorthi;Schwartz, Russell
通讯作者：
Schwartz, Russell
DOI：
10.1073/pnas.0801523105
发表时间：
2008-09-02
影响因子：
11.1
作者：
Campbell, Peter J.;Pleasance, Erin D.;Stratton, Michael R.
通讯作者：
Stratton, Michael R.