Dan L. Duncan Cancer Center, Baylor College of Medicine, Houston, Texas, United States of America.
PLoS One. 2012;7(3):e34546. doi: 10.1371/journal.pone.0034546. Epub 2012 Mar 29.
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.
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中的分子异常，关于 microRNAs（miRNAs）仍有许多需要阐明。在这里，我们使用 TCGA 卵巢数据，在其预测基因靶标的背景下调查了 miRNAs。
miRNA 和基因模式的整合提供了证据表明，miRNAs 是从多顺反子初级转录物中加工而来的，并且内含子 miRNAs 和它们的宿主基因 mRNA 来自共同的转录物。miRNA 表达模式揭示了多个肿瘤亚型和一组 34 个可预测总患者生存的 miRNAs。在全局分析中，在肿瘤之间表达呈反相关的 miRNA:mRNA 对在 mRNA 3'-非翻译区（在编码序列和 5'-非翻译区观察到的频率较低）中具有更高频率的计算机预测靶位点。miR-29 家族和预测的靶基因是表达最强烈反相关的 miRNA:mRNA 对之一；miR-29a 在体外过表达抑制了几个反相关基因（包括 DNMT3A 和 DNMT3B），并显著降低了卵巢癌细胞活力。
本研究确立了 miRNAs 对卵巢癌基因表达程序具有广泛的影响，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，miRNAs 表现出高度的多样性，反映了临床同质疾病人群中基因组的异质性。使用综合分析鉴定的推定 miRNA:mRNA 相互作用可以得到验证。TCGA 数据是鉴定卵巢癌以及其他癌症中新型肿瘤抑制性 miRNAs 的宝贵资源。
