Genome-wide identification of somatic aberrations from paired normal-tumor samples.
Genome-wide identification of somatic aberrations from paired normal-tumor samples.
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配对正常肿瘤样本中体细胞畸变的全基因组鉴定
DOI：
10.1371/journal.pone.0087212
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发表时间：
2014
期刊：
影响因子：
3.7
通讯作者：
Wang M
中科院分区：
文献类型：
--
作者：
Li A;Liu Y;Zhao Q;Feng H;Harris L;Wang M
基因组拷贝数改变和等位基因失衡是肿瘤细胞的显著特征，近年来基因分型技术的进步极大地促进了肿瘤基因组的研究。然而，肿瘤的复杂性往往阻碍了SNP阵列的解剖。在这项研究中，我们描述了一种名为GIANT的生物信息学工具，用于用SNP阵列测量成对正常肿瘤样本的体细胞畸变的全基因组鉴定。通过有效地整合匹配正常样本的基因型信息，即使对于正常细胞污染严重的非整倍体肿瘤样本，也能准确地检测出癌症基因组中不同类型的畸变。此外，它允许通过使用统计显著性检验发现肿瘤发生中具有关键生物学特性的复发畸变。我们证明了该方法在各种数据集上的优越性能，包括肿瘤复制对、模拟SNP阵列和正常癌细胞系的稀释系列。结果表明，即使癌细胞比例低至5 ~ 10%，GIANT也具有检测基因组畸变的潜力。在大量成对肿瘤样本上的应用提供了各种畸变（包括扩增、缺失和LOH）的全基因组统计显著性图谱。我们相信GIANT是一种强大的生物信息学工具，可以解释复杂的基因组畸变，从而帮助癌症的学术研究和临床治疗。
Genomic copy number alteration and allelic imbalance are distinct features of cancer cells, and recent advances in the genotyping technology have greatly boosted the research in the cancer genome. However, the complicated nature of tumor usually hampers the dissection of the SNP arrays. In this study, we describe a bioinformatic tool, named GIANT, for genome-wide identification of somatic aberrations from paired normal-tumor samples measured with SNP arrays. By efficiently incorporating genotype information of matched normal sample, it accurately detects different types of aberrations in cancer genome, even for aneuploid tumor samples with severe normal cell contamination. Furthermore, it allows for discovery of recurrent aberrations with critical biological properties in tumorigenesis by using statistical significance test. We demonstrate the superior performance of the proposed method on various datasets including tumor replicate pairs, simulated SNP arrays and dilution series of normal-cancer cell lines. Results show that GIANT has the potential to detect the genomic aberration even when the cancer cell proportion is as low as 5∼10%. Application on a large number of paired tumor samples delivers a genome-wide profile of the statistical significance of the various aberrations, including amplification, deletion and LOH. We believe that GIANT represents a powerful bioinformatic tool for interpreting the complex genomic aberration, and thus assisting both academic study and the clinical treatment of cancer.
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影响因子：
64.8
作者：
通讯作者：
--
影响因子：
12.3
作者：
Mayrhofer M;DiLorenzo S;Isaksson A
通讯作者：
Isaksson A
核苷酸分辨率上杂合性丧失和单相表达的全基因组丧失的综合分析揭示了三阴性乳腺癌的途径中断。
影响因子：
7
作者：
Ha G;Roth A;Lai D;Bashashati A;Ding J;Goya R;Giuliany R;Rosner J;Oloumi A;Shumansky K;Chin SF;Turashvili G;Hirst M;Caldas C;Marra MA;Aparicio S;Shah SP
通讯作者：
Shah SP
影响因子：
64.8
作者：
通讯作者：
--
DOI：
10.1093/bioinformatics/btr670
发表时间：
2012-02-01
期刊：
Bioinformatics (Oxford, England)
影响因子：
--
作者：
Boeva V;Popova T;Bleakley K;Chiche P;Cappo J;Schleiermacher G;Janoueix-Lerosey I;Delattre O;Barillot E
通讯作者：
Barillot E