BACKGROUND The established role miRNA-mRNA regulation of gene expression has in oncogenesis highlights the importance of integrating miRNA with downstream mRNA targets. These findings call for investigations aimed at identifying disease-associated miRNA-mRNA pairs. Hierarchical integrative models (HIM) offer the opportunity to uncover the relationships between disease and the levels of different molecules measured in multiple omic studies. METHODS The HIM model we formulated for analysis of mRNA-seq and miRNA-seq data can be specified with two levels: (1) a mechanistic submodel relating mRNAs to miRNAs, and (2) a clinical submodel relating disease status to mRNA and miRNA, while accounting for the mechanistic relationships in the first level. RESULTS mRNA-seq and miRNA-seq data were acquired by analysis of tumor and normal liver tissues from 30 patients with hepatocellular carcinoma (HCC). We analyzed the data using HIM and identified 157 significant miRNA-mRNA pairs in HCC. The majority of these molecules have already been independently identified as being either diagnostic, prognostic, or therapeutic biomarker candidates for HCC. These pairs appear to be involved in processes contributing to the pathogenesis of HCC involving inflammation, regulation of cell cycle, apoptosis, and metabolism. For further evaluation of our method, we analyzed miRNA-seq and mRNA-seq data from TCGA network. While some of the miRNA-mRNA pairs we identified by analyzing both our and TCGA data are previously reported in the literature and overlap in regulation and function, new pairs have been identified that may contribute to the discovery of novel targets. CONCLUSION The results strongly support the hypothesis that miRNAs are important regulators of mRNAs in HCC. Furthermore, these results emphasize the biological relevance of studying miRNA-mRNA pairs.

中文翻译：

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使用分级整合模型鉴定肝细胞癌中的 miRNA-mRNA 关联。

背景 miRNA-mRNA 调控基因表达在肿瘤发生中的既定作用突出了将 miRNA 与下游 mRNA 靶标整合的重要性。这些发现要求开展旨在识别疾病相关 miRNA-mRNA 对的研究。分层整合模型 (HIM) 提供了揭示疾病与多项组学研究中测量的不同分子水平之间关系的机会。方法 我们为分析 mRNA-seq 和 miRNA-seq 数据制定的 HIM 模型可以指定为两个级别：（1）将 mRNA 与 miRNA 相关联的机制子模型，以及（2）将疾病状态与 mRNA 和 miRNA 相关联的临床子模型，同时考虑第一级的机械关系。结果 通过分析 30 例肝细胞癌 (HCC) 患者的肿瘤和正常肝组织获得 mRNA-seq 和 miRNA-seq 数据。我们使用 HIM 分析了数据，并在 HCC 中鉴定了 157 个重要的 miRNA-mRNA 对。这些分子中的大多数已被独立确定为 HCC 的诊断、预后或治疗性生物标志物候选物。这些对似乎参与了促成 HCC 发病机制的过程，包括炎症、细胞周期的调节、细胞凋亡和代谢。为了进一步评估我们的方法，我们分析了来自 TCGA 网络的 miRNA-seq 和 mRNA-seq 数据。虽然我们通过分析我们的数据和 TCGA 数据确定的一些 miRNA-mRNA 对以前在文献中报道过，并且在调节和功能方面存在重叠，已经确定了可能有助于发现新靶标的新配对。结论 该结果有力地支持了 miRNA 是 HCC 中 mRNA 的重要调节因子的假设。此外，这些结果强调了研究 miRNA-mRNA 对的生物学相关性。