Aberrant transcriptional regulations in cancers: genome, transcriptome and epigenome analysis of lung adenocarcinoma cell lines.
Aberrant transcriptional regulations in cancers: genome, transcriptome and epigenome analysis of lung adenocarcinoma cell lines.
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DOI：
10.1093/nar/gku885
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发表时间：
2014-12-16
影响因子：
14.9
通讯作者：
Suzuki Y
中科院分区：
文献类型：
--
作者：
Suzuki A;Makinoshima H;Wakaguri H;Esumi H;Sugano S;Kohno T;Tsuchihara K;Suzuki Y
在这里，我们进行了综合多组学分析，以了解癌症如何在基因组，表观基因组和转录水平上携带各种类型的畸变。为了阐明畸变的生物学相关性及其相互关系，我们对26个肺腺癌细胞系进行了全基因组测序、RNA-Seq、亚硫酸氢盐测序和ChIP-Seq。收集的多组学数据使我们能够将启动子或增强子区域中的平均536个编码突变和13，573个突变与异常转录调控相关联。我们检测到385个剪接位点突变和552个染色体重排，其中有代表性的情况下被验证会导致异常转录。其中61、217、3687和3112个突变位点分别位于调控区，表现出不同的DNA甲基化、H3 K4 me 3、H3 K4 me 1和H3 K27 ac标记。我们检测到不同模式的畸变转录调控依赖于基因。我们发现不规则的组蛋白标记是EGFR和CDKN 1A的特征，而大的基因组缺失和超DNA甲基化是CDKN 2A最常见的。我们还使用多组学数据对细胞系的致癌标志进行分类。我们的数据集应该为交错的基因组和表观基因组畸变的生物学解释提供有价值的基础。
Here we conducted an integrative multi-omics analysis to understand how cancers harbor various types of aberrations at the genomic, epigenomic and transcriptional levels. In order to elucidate biological relevance of the aberrations and their mutual relations, we performed whole-genome sequencing, RNA-Seq, bisulfite sequencing and ChIP-Seq of 26 lung adenocarcinoma cell lines. The collected multi-omics data allowed us to associate an average of 536 coding mutations and 13,573 mutations in promoter or enhancer regions with aberrant transcriptional regulations. We detected the 385 splice site mutations and 552 chromosomal rearrangements, representative cases of which were validated to cause aberrant transcripts. Averages of 61, 217, 3687 and 3112 mutations are located in the regulatory regions which showed differential DNA methylation, H3K4me3, H3K4me1 and H3K27ac marks, respectively. We detected distinct patterns of aberrations in transcriptional regulations depending on genes. We found that the irregular histone marks were characteristic to EGFR and CDKN1A, while a large genomic deletion and hyper-DNA methylation were most frequent for CDKN2A. We also used the multi-omics data to classify the cell lines regarding their hallmarks of carcinogenesis. Our datasets should provide a valuable foundation for biological interpretations of interlaced genomic and epigenomic aberrations.
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影响因子：
64.8
作者：
Ernst, Jason;Kheradpour, Pouya;Mikkelsen, Tarjei S.;Shoresh, Noam;Ward, Lucas D.;Epstein, Charles B.;Zhang, Xiaolan;Wang, Li;Issner, Robbyn;Coyne, Michael;Ku, Manching;Durham, Timothy;Kellis, Manolis;Bernstein, Bradley E.
通讯作者：
Bernstein, Bradley E.
来自1,092个人基因组的遗传变异的综合图。
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
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：
64.5
作者：
Hnisz D;Abraham BJ;Lee TI;Lau A;Saint-André V;Sigova AA;Hoke HA;Young RA
通讯作者：
Young RA