Integrated analyses of microRNAs demonstrate their widespread influence on gene expression in high-grade serous ovarian carcinoma.
Integrated analyses of microRNAs demonstrate their widespread influence on gene expression in high-grade serous ovarian carcinoma.
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DOI：
10.1371/journal.pone.0034546
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发表时间：
2012
期刊：
影响因子：
3.7
通讯作者：
Cancer Genome Atlas Research Network
中科院分区：
文献类型：
--
作者：
Creighton CJ;Hernandez-Herrera A;Jacobsen A;Levine DA;Mankoo P;Schultz N;Du Y;Zhang Y;Larsson E;Sheridan R;Xiao W;Spellman PT;Getz G;Wheeler DA;Perou CM;Gibbs RA;Sander C;Hayes DN;Gunaratne PH;Cancer Genome Atlas Research Network
癌症基因组图谱（TCGA）网络最近全面编目了487例高级别浆液性卵巢癌的分子畸变，关于microRNA（miRNAs）还有很多有待阐明。在这里，使用TCGA卵巢数据，我们调查了miRNAs，在其预测的基因靶点的背景下。整合的miRNA和基因模式产生的证据表明，近端对的miRNA的加工从多顺反子的初级转录，内含子的miRNA和它们的宿主基因mRNA来自共同的转录。miRNA表达模式揭示了多种肿瘤亚型和一组34种可预测患者总体生存率的miRNA。在一项全局分析中，肿瘤间表达反相关的miRNA：mRNA对显示，mRNA 3′-非翻译区中计算机模拟预测的靶位点频率较高（编码序列和5′-非翻译区观察到的频率较低）。miR-29家族和预测的靶基因是最强反相关的miRNA：mRNA对之一; miR-29 a在体外过表达抑制了几个反相关基因（包括DNMT 3A和DNMT 3B），并显著降低了卵巢癌细胞的活力。这项研究确定了miRNA对卵巢癌基因表达程序的广泛影响，进一步加强了我们对miRNA生物学的理解，因为它适用于人类癌症。与基因转录物一样，miRNA表现出高度多样性，反映了临床同质疾病人群中的基因组异质性。可以验证使用整合分析鉴定的推定的miRNA：mRNA相互作用。TCGA数据是鉴定卵巢癌和其他癌症中新型肿瘤抑制性miRNA的宝贵资源。
The Cancer Genome Atlas (TCGA) Network recently comprehensively catalogued the molecular aberrations in 487 high-grade serous ovarian cancers, with much remaining to be elucidated regarding the microRNAs (miRNAs). Here, using TCGA ovarian data, we surveyed the miRNAs, in the context of their predicted gene targets. Integration of miRNA and gene patterns yielded evidence that proximal pairs of miRNAs are processed from polycistronic primary transcripts, and that intronic miRNAs and their host gene mRNAs derive from common transcripts. Patterns of miRNA expression revealed multiple tumor subtypes and a set of 34 miRNAs predictive of overall patient survival. In a global analysis, miRNA:mRNA pairs anti-correlated in expression across tumors showed a higher frequency of in silico predicted target sites in the mRNA 3′-untranslated region (with less frequency observed for coding sequence and 5′-untranslated regions). The miR-29 family and predicted target genes were among the most strongly anti-correlated miRNA:mRNA pairs; over-expression of miR-29a in vitro repressed several anti-correlated genes (including DNMT3A and DNMT3B) and substantially decreased ovarian cancer cell viability. This study establishes miRNAs as having a widespread impact on gene expression programs in ovarian cancer, further strengthening our understanding of miRNA biology as it applies to human cancer. As with gene transcripts, miRNAs exhibit high diversity reflecting the genomic heterogeneity within a clinically homogeneous disease population. Putative miRNA:mRNA interactions, as identified using integrative analysis, can be validated. TCGA data are a valuable resource for the identification of novel tumor suppressive miRNAs in ovarian as well as other cancers.
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影响因子：
7
作者：
Lee, Inhan;Ajay, Subramanian S.;Athey, Brian D.
通讯作者：
Athey, Brian D.
影响因子：
11.5
作者：
Nam, Eun Ji;Yoon, Heejei;Kim, Sunghoon
通讯作者：
Kim, Sunghoon
影响因子：
64.5
作者：
Lewis, BP;Shih, IH;Burge, CB
通讯作者：
Burge, CB
影响因子：
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作者：
Creighton CJ;Fountain MD;Yu Z;Nagaraja AK;Zhu H;Khan M;Olokpa E;Zariff A;Gunaratne PH;Matzuk MM;Anderson ML
通讯作者：
Anderson ML
影响因子：
14.9
作者：
Betel D;Wilson M;Gabow A;Marks DS;Sander C
通讯作者：
Sander C