Diaz Diana, Donato Michele, Nguyen Tin, Draghici Sorin
Department of Computer Science, Wayne State University, Detroit, MI 48202, U.S.A.
Pac Symp Biocomput. 2017;22:390-401. doi: 10.1142/9789813207813_0037.
MicroRNAs play important roles in the development of many complex diseases. Because of their importance, the analysis of signaling pathways including miRNA interactions holds the potential for unveiling the mechanisms underlying such diseases. However, current signaling pathway databases are limited to interactions between genes and ignore miRNAs. Here, we use the information on miRNA targets to build a database of miRNA-augmented pathways (mirAP), and we show its application in the contexts of integrative pathway analysis and disease subtyping. Our miRNA-mRNA integrative pathway analysis pipeline incorporates a topology-aware approach that we previously implemented. Our integrative disease subtyping pipeline takes into account survival data, gene and miRNA expression, and knowledge of the interactions among genes. We demonstrate the advantages of our approach by analyzing nine sample-matched datasets that provide both miRNA and mRNA expression. We show that integrating miRNAs into pathway analysis results in greater statistical power, and provides a more comprehensive view of the underlying phenomena. We also compare our disease subtyping method with the state-of-the-art integrative analysis by analyzing a colorectal cancer database from TCGA. The colorectal cancer subtypes identified by our approach are significantly different in terms of their survival expectation. These miRNA-augmented pathways offer a more comprehensive view and a deeper understanding of biological pathways. A better understanding of the molecular processes associated with patients' survival can help to a better prognosis and an appropriate treatment for each subtype.
微小RNA在许多复杂疾病的发展过程中发挥着重要作用。鉴于其重要性，对包括微小RNA相互作用在内的信号通路进行分析，有望揭示此类疾病的潜在机制。然而，当前的信号通路数据库仅限于基因之间的相互作用，而忽略了微小RNA。在此，我们利用微小RNA靶标的信息构建了一个微小RNA增强通路数据库（mirAP），并展示了其在综合通路分析和疾病亚型分类中的应用。我们的微小RNA-信使核糖核酸综合通路分析流程采用了我们之前实施的一种拓扑感知方法。我们的综合疾病亚型分类流程考虑了生存数据、基因和微小RNA表达以及基因间相互作用的知识。我们通过分析九个提供了微小RNA和信使核糖核酸表达的样本匹配数据集，展示了我们方法的优势。我们表明，将微小RNA整合到通路分析中可带来更强的统计效力，并能更全面地展现潜在现象。我们还通过分析来自癌症基因组图谱（TCGA）的结直肠癌数据库，将我们的疾病亚型分类方法与当前最先进的综合分析方法进行了比较。我们的方法所识别出的结直肠癌亚型在生存预期方面存在显著差异。这些微小RNA增强通路能更全面地展现并更深入地理解生物通路。更好地理解与患者生存相关的分子过程，有助于为每种亚型实现更好的预后和恰当的治疗。
