The modularity and dynamicity of miRNA-mRNA interactions in high-grade serous ovarian carcinomas and the prognostic implication.
The modularity and dynamicity of miRNA-mRNA interactions in high-grade serous ovarian carcinomas and the prognostic implication.
复制标题
DOI：
10.1016/j.compbiolchem.2016.02.005
复制
发表时间：
2016-08
影响因子：
3.1
通讯作者：
Zhang K
中科院分区：
文献类型：
--
作者：
Zhang W;Edwards A;Fan W;Flemington EK;Zhang K
卵巢癌是美国女性癌症死亡的第五大原因。这种持续死亡率的主要原因包括对潜在生物学的了解不足和缺乏可靠的生物标志物。先前的研究表明，异常表达的MicroRNA (miRNA)通过转录后调节基因表达参与癌发生和肿瘤进展。然而，miRNA对肿瘤发生的干扰相当复杂，远未得到充分了解。在这项工作中，通过对癌症基因组图谱 (TCGA) 发表的 mRNA 表达、miRNA 表达和临床数据的综合分析，我们研究了 miRNA-mRNA 相互作用的模块化和动态性以及高级别浆液性卵巢癌的预后意义。以最高的转录相关性（Bonferroni 调整的 p 值 < 0.01）作为输入，我们确定了 5 个 miRNA-mRNA 模块对 (MP)，每个模块对包括一个正连接（相关）模块和一个负连接（相关）模块。每个模块中的miRNA或mRNA的数量从3到7个或2到873个不等。在四个主要的负连接模块中，其中三个非常符合广泛接受的miRNA介导的转录后调控理论。这些模块富含与细胞周期和免疫反应相关的基因。此外，我们提出了两种新颖的算法来揭示这两个 RNA 类别之间的组或样本特定动态调节。获得的 miRNA-mRNA 动态网络包含在不同癌症进展阶段或肿瘤等级中捕获的 3350 个相互作用。我们发现这些动态相互作用往往集中在少数 miRNA（例如 miRNA-936）上，并且更有可能存在于已发现模块之外的 miRNA-mRNA 对上。此外，我们还确定了由 56 个模块化蛋白编码基因组成的强大预后特征，其共表达模式可预测多个独立队列中卵巢癌患者的生存时间。
Ovarian carcinoma is the fifth-leading cause of cancer death among women in the United States. Major reasons for this persistent mortality include the poor understanding of the underlying biology and a lack of reliable biomarkers. Previous studies have shown that aberrantly expressed MicroRNAs (miRNAs) are involved in carcinogenesis and tumor progression by post-transcriptionally regulating gene expression. However, the interference of miRNAs in tumorigenesis is quite complicated and far from being fully understood. In this work, by an integrative analysis of mRNA expression, miRNA expression and clinical data published by The Cancer Genome Atlas (TCGA), we studied the modularity and dynamicity of miRNA-mRNA interactions and the prognostic implications in high-grade serous ovarian carcinomas. With the top transcriptional correlations (Bonferroni-adjusted p-value < 0.01) as inputs, we identified five miRNA-mRNA module pairs (MPs), each of which included one positive-connection (correlation) module and one negative-connection (correlation) module. The number of miRNAs or mRNAs in each module varied from 3 to 7 or from 2 to 873. Among the four major negative-connection modules, three fit well with the widely accepted miRNA-mediated post-transcriptional regulation theory. These modules were enriched with the genes relevant to cell cycle and immune response. Moreover, we proposed two novel algorithms to reveal the group or sample specific dynamic regulations between these two RNA classes. The obtained miRNA-mRNA dynamic network contains 3350 interactions captured across different cancer progression stages or tumor grades. We found that those dynamic interactions tended to concentrate on a few miRNAs (e.g. miRNA-936), and were more likely present on the miRNA-mRNA pairs outside the discovered modules. In addition, we also pinpointed a robust prognostic signature consisting of 56 modular protein-coding genes, whose co-expression patterns were predictive for the survival time of ovarian cancer patients in multiple independent cohorts.