Estimating the probability of clonal relatedness of pairs of tumors in cancer patients.
Estimating the probability of clonal relatedness of pairs of tumors in cancer patients.
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DOI：
10.1111/biom.12710
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发表时间：
2018-03
期刊：
影响因子：
1.9
通讯作者：
Begg CB
中科院分区：
文献类型：
--
作者：
Mauguen A;Seshan VE;Ostrovnaya I;Begg CB
下一代测序面板正越来越多地被用于癌症研究，以研究肿瘤的进化。一个特殊的统计学挑战是比较患者不同肿瘤的突变情况，以确定肿瘤是克隆相关的证据的强度，即来自单个创建者克隆细胞。每个肿瘤中存在相同的突变提供了克隆相关性的证据，尽管来自匹配的证据的强度与所研究的肿瘤类型中突变的常见程度有关。这一证据必须与支持从非匹配突变中分离出独立肿瘤的证据进行权衡。在这篇文章中，我们使用一个新的随机效应模型在诊断的背景下框架这一挑战。这样，通过分析一组肿瘤对，我们可以估计样本中克隆相关病例的比例以及每个病例的单独诊断概率。该方法是使用一项研究的数据来说明的，该研究旨在确定小叶原位癌与随后的浸润性乳腺癌之间的克隆关系，其中每对肿瘤都进行了完整的外显子组测序。通过仿真对该方法的统计特性进行了评估，结果表明，在大多数构型中，关键模型参数的估计在小样本下只有适度的偏差。
Next generation sequencing panels are being used increasingly in cancer research to study tumor evolution. A specific statistical challenge is to compare the mutational profiles in different tumors from a patient to determine the strength of evidence that the tumors are clonally related, i.e. derived from a single, founder clonal cell. The presence of identical mutations in each tumor provides evidence of clonal relatedness, although the strength of evidence from a match is related to how commonly the mutation is seen in the tumor type under investigation. This evidence must be weighed against the evidence in favor of independent tumors from non-matching mutations. In this article we frame this challenge in the context of diagnosis using a novel random effects model. In this way, by analyzing a set of tumor pairs, we can estimate the proportion of cases that are clonally related in the sample as well as the individual diagnostic probabilities for each case. The method is illustrated using data from a study to determine the clonal relationship of lobular carcinoma in situ with subsequent invasive breast cancers where each tumor in the pair was subjected to whole exome sequencing. The statistical properties of the method are evaluated using simulations, demonstrating that the key model parameters are estimated with only modest bias in small samples in most configurations.
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DOI：
10.1186/s13058-016-0727-z
发表时间：
2016-06-23
期刊：
Breast cancer research : BCR
影响因子：
--
作者：
Begg CB;Ostrovnaya I;Carniello JV;Sakr RA;Giri D;Towers R;Schizas M;De Brot M;Andrade VP;Mauguen A;Seshan VE;King TA
通讯作者：
King TA
影响因子：
3.7
作者：
Witteveen, Annemieke;Kwast, Annemiek B. G.;Siesling, Sabine
通讯作者：
Siesling, Sabine
影响因子：
10.3
作者：
Bollet, Marc A.;Servant, Nicolas;Thiery, Jean-Paul
通讯作者：
Thiery, Jean-Paul
影响因子：
3.8
作者：
Klevebring, Daniel;Lindberg, Johan;Czene, Kamila
通讯作者：
Czene, Kamila
DOI：
10.1158/1078-0432.ccr-09-2398
发表时间：
2010-03-01
期刊：
Clinical cancer research : an official journal of the American Association for Cancer Research
影响因子：
--
作者：
Ostrovnaya I;Begg CB
通讯作者：
Begg CB