MutComFocal: an integrative approach to identifying recurrent and focal genomic alterations in tumor samples.
MutComFocal: an integrative approach to identifying recurrent and focal genomic alterations in tumor samples.
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DOI：
10.1186/1752-0509-7-25
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发表时间：
2013-03-25
影响因子：
--
通讯作者：
Rabadan R
中科院分区：
文献类型：
--
作者：
Trifonov V;Pasqualucci L;Dalla Favera R;Rabadan R
大多数肿瘤是体细胞中积累的基因组改变的结果。肿瘤中出现的变化谱是复杂的，相关基因和途径的鉴定仍然是一个挑战。此外，关键的癌症基因通常在含有许多其他基因的染色体区域中被扩增或缺失。另一方面，点突变提供了可能与致癌过程有关的氨基酸变化的精确信息。目前的大规模基因组计划在大量表征良好的肿瘤样品中提供高通量基因组数据。我们定义了一种贝叶斯方法，旨在通过整合拷贝数和点突变信息来识别候选癌症基因。我们的方法利用了这样一个概念，即肿瘤中的小的和复发性的改变在寻找癌症基因时提供更多的信息。因此，该算法（具有共同焦点改变的突变，或MutComFocal）在来自大组肿瘤样品的高通量数据内寻找焦点拷贝数改变和复发性点突变。我们将MutComFocal应用于来自四个不同高通量研究的弥漫性大B细胞淋巴瘤（DLBCL）数据，共78个样本通过单核苷酸多态性（SNP）阵列分析评估拷贝数改变，65个样本通过全外显子组/全转录组测序测定蛋白质改变点突变。除了概括已知的改变外，MutComFocal还将ARID 1B、ROBO 2和MRS 1鉴定为DLBCL中的候选肿瘤抑制基因，并将KLHL 6、IL 31和LRP 1鉴定为推定的癌基因。我们提出了一种贝叶斯方法，通过整合不同研究中收集的大量癌症患者的数据来识别候选癌症基因。当在经过充分研究的数据集上训练时，MutComFocal能够识别大多数报告的特征化改变。MutComFocal在大规模癌症数据中的应用提供了确定肿瘤中关键功能基因组改变的机会。
Most tumors are the result of accumulated genomic alterations in somatic cells. The emerging spectrum of alterations in tumors is complex and the identification of relevant genes and pathways remains a challenge. Furthermore, key cancer genes are usually found amplified or deleted in chromosomal regions containing many other genes. Point mutations, on the other hand, provide exquisite information about amino acid changes that could be implicated in the oncogenic process. Current large-scale genomic projects provide high throughput genomic data in a large number of well-characterized tumor samples. We define a Bayesian approach designed to identify candidate cancer genes by integrating copy number and point mutation information. Our method exploits the concept that small and recurrent alterations in tumors are more informative in the search for cancer genes. Thus, the algorithm (Mutations with Common Focal Alterations, or MutComFocal) seeks focal copy number alterations and recurrent point mutations within high throughput data from large panels of tumor samples. We apply MutComFocal to Diffuse Large B-cell Lymphoma (DLBCL) data from four different high throughput studies, totaling 78 samples assessed for copy number alterations by single nucleotide polymorphism (SNP) array analysis and 65 samples assayed for protein changing point mutations by whole exome/whole transcriptome sequencing. In addition to recapitulating known alterations, MutComFocal identifies ARID1B, ROBO2 and MRS1 as candidate tumor suppressors and KLHL6, IL31 and LRP1 as putative oncogenes in DLBCL. We present a Bayesian approach for the identification of candidate cancer genes by integrating data collected in large number of cancer patients, across different studies. When trained on a well-studied dataset, MutComFocal is able to identify most of the reported characterized alterations. The application of MutComFocal to large-scale cancer data provides the opportunity to pinpoint the key functional genomic alterations in tumors.
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影响因子：
64.8
作者：
通讯作者：
--
DOI：
10.1073/pnas.0710052104
发表时间：
2007-12-11
影响因子：
11.1
作者：
Beroukhim, Rameen;Getz, Gad;Sellers, William R.
通讯作者：
Sellers, William R.
影响因子：
56.9
作者：
Lenz, Georg;Davis, R. Eric;Staudt, Louis M.
通讯作者：
Staudt, Louis M.
体细胞突变改变生发中心起源的滤泡性和弥漫性大 B 细胞淋巴瘤中的 EZH2 (Tyr641)。
影响因子：
30.8
作者：
Morin, Ryan D.;Johnson, Nathalie A.;Severson, Tesa M.;Mungall, Andrew J.;An, Jianghong;Goya, Rodrigo;Paul, Jessica E.;Boyle, Merrill;Woolcock, Bruce W.;Kuchenbauer, Florian;Yap, Damian;Humphries, R. Keith;Griffith, Obi L.;Shah, Sohrab;Zhu, Henry;Kimbara, Michelle;Shashkin, Pavel;Charlot, Jean F.;Tcherpakov, Marianna;Corbett, Richard;Tam, Angela;Varhol, Richard;Smailus, Duane;Moksa, Michelle;Zhao, Yongjun;Delaney, Allen;Qian, Hong;Birol, Inanc;Schein, Jacqueline;Moore, Richard;Holt, Robert;Horsman, Doug E.;Connors, Joseph M.;Jones, Steven;Aparicio, Samuel;Hirst, Martin;Gascoyne, Randy D.;Marra, Marco A.
通讯作者：
Marra, Marco A.
影响因子：
64.8
作者：
Compagno, Mara;Lim, Wei Keat;Grunn, Adina;Nandula, Subhadra V.;Brahmachary, Manisha;Shen, Qiong;Bertoni, Francesco;Ponzoni, Maurilio;Scandurra, Marta;Califano, Andrea;Bhagat, Govind;Chadburn, Amy;Dalla-Favera, Riccardo;Pasqualucci, Laura
通讯作者：
Pasqualucci, Laura