Allele-specific amplification in cancer revealed by SNP array analysis.
Allele-specific amplification in cancer revealed by SNP array analysis.
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DOI：
10.1371/journal.pcbi.0010065
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发表时间：
2005-11
影响因子：
4.3
通讯作者：
Meyerson M
中科院分区：
文献类型：
--
作者：
LaFramboise T;Weir BA;Zhao X;Beroukhim R;Li C;Harrington D;Sellers WR;Meyerson M
基因组DNA的扩增、缺失和杂合性丢失是癌症的标志。近年来，出现了以越来越高的分辨率测量总染色体拷贝数的各种研究。类似地，杂合性缺失事件已经使用高通量基因分型技术精细地作图。我们已经开发了一种探针水平的等位基因特异性定量程序，从单核苷酸多态性（SNP）阵列数据中提取拷贝数和等位基因型信息，以获得整个基因组的等位基因特异性拷贝数。我们的方法适用于期望最大化算法的模型来自一个新的分类SNP阵列探针。该方法是我们所知的第一个能够（a）确定每个SNP位点处的异常样品的广义基因型（例如，在扩增位点的CCCCT），和（B）推断基因组中每个亲本染色体的拷贝数。通过这种方法，我们不仅能够确定扩增和缺失发生的位置，还能够确定扩增或缺失区域的单体型。我们的模型和一般方法的优点是通过非常精确的正常样品的基因分型证明，我们的等位基因特异性拷贝数推断使用PCR实验进行验证。将我们的方法应用于肺癌样本的收集，我们能够得出结论，扩增基本上是单等位基因的，正如目前认为负责基因扩增的机制下所预期的那样。这表明，一个特定的亲本染色体可能是扩增的目标，无论是因为生殖系或体细胞变异。包含本文中描述的方法的R软件包可以在http://genome.dfci.harvard.edu/~tlaframb/PLASQ上免费获得。人类癌症是由基因组改变的获得驱动的。这些改变包括细胞中一条或两条染色体的部分扩增和缺失。这种拷贝数变化的定位是癌症基因组学研究中的一个重要目标，因为扩增区域通常含有致癌基因，而缺失区域通常含有肿瘤抑制基因。在本文中，作者提出了一种基于期望最大化的程序，当应用于单核苷酸多态性阵列的数据时，不仅可以在高分辨率下估计整个基因组的总拷贝数，还可以估计每个亲本染色体对拷贝数的贡献。将这种方法应用于来自100多个肺癌样本的数据，作者发现，基本上在所有情况下，扩增都是单等位基因的。也就是说，两个亲本染色体中只有一个有助于每个扩增区域中的拷贝数升高。这种现象使得有可能鉴定单倍型或单核苷酸多态性等位基因的模式，其可以用作靶向的肿瘤诱导遗传变异的标记。
Amplification, deletion, and loss of heterozygosity of genomic DNA are hallmarks of cancer. In recent years a variety of studies have emerged measuring total chromosomal copy number at increasingly high resolution. Similarly, loss-of-heterozygosity events have been finely mapped using high-throughput genotyping technologies. We have developed a probe-level allele-specific quantitation procedure that extracts both copy number and allelotype information from single nucleotide polymorphism (SNP) array data to arrive at allele-specific copy number across the genome. Our approach applies an expectation-maximization algorithm to a model derived from a novel classification of SNP array probes. This method is the first to our knowledge that is able to (a) determine the generalized genotype of aberrant samples at each SNP site (e.g., CCCCT at an amplified site), and (b) infer the copy number of each parental chromosome across the genome. With this method, we are able to determine not just where amplifications and deletions occur, but also the haplotype of the region being amplified or deleted. The merit of our model and general approach is demonstrated by very precise genotyping of normal samples, and our allele-specific copy number inferences are validated using PCR experiments. Applying our method to a collection of lung cancer samples, we are able to conclude that amplification is essentially monoallelic, as would be expected under the mechanisms currently believed responsible for gene amplification. This suggests that a specific parental chromosome may be targeted for amplification, whether because of germ line or somatic variation. An R software package containing the methods described in this paper is freely available at http://genome.dfci.harvard.edu/~tlaframb/PLASQ. Human cancer is driven by the acquisition of genomic alterations. These alterations include amplifications and deletions of portions of one or both chromosomes in the cell. The localization of such copy number changes is an important pursuit in cancer genomics research because amplifications frequently harbor cancer-causing oncogenes, while deleted regions often contain tumor-suppressor genes. In this paper the authors present an expectation-maximization-based procedure that, when applied to data from single nucleotide polymorphism arrays, estimates not only total copy number at high resolution across the genome, but also the contribution of each parental chromosome to copy number. Applying this approach to data from over 100 lung cancer samples the authors find that, in essentially all cases, amplification is monoallelic. That is, only one of the two parental chromosomes contributes to the copy number elevation in each amplified region. This phenomenon makes possible the identification of haplotypes, or patterns of single nucleotide polymorphism alleles, that may serve as markers for the tumor-inducing genetic variants being targeted.
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影响因子：
158.5
作者：
Lynch, TJ;Bell, DW;Haber, DA
通讯作者：
Haber, DA
DOI：
10.1073/pnas.011404098
发表时间：
2001-01-02
影响因子：
11.1
作者：
Li, C;Wong, WH
通讯作者：
Wong, WH
DOI：
10.1038/nrc1299
发表时间：
2004-03
期刊：
Nature reviews. Cancer
影响因子：
--
作者：
通讯作者：
--
影响因子：
30.8
作者：
Iafrate, AJ;Feuk, L;Lee, C
通讯作者：
Lee, C
影响因子：
56.9
作者：
Gabriel, SB;Schaffner, SF;Altshuler, D
通讯作者：
Altshuler, D