Han Junwei, Liu Siyao, Zhang Yunpeng, Xu Yanjun, Jiang Ying, Zhang Chunlong, Li Chunquan, Li Xia
College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, PR China.
College of Basic Medical Science, Heilongjiang University of Chinese Medicine, Harbin 150040, PR China.
Oncotarget. 2016 Aug 23;7(34):55012-55025. doi: 10.18632/oncotarget.10839.
Recent studies have shown that dysfunctional microRNAs (miRNAs) are involved in the progression of various cancers. Dysfunctional miRNAs may jointly regulate their target genes and further alter the activities of canonical biological pathways. Identification of the pathways regulated by a group of dysfunctional miRNAs could help uncover the pathogenic mechanisms of cancer and facilitate development of new drug targets. Current miRNA-pathway analyses mainly use differentially-expressed miRNAs to predict the shared pathways on which they act. However, these methods fail to consider the level of differential expression level, which could improve our understanding of miRNA function. We propose a novel computational method, MicroRNA Set Enrichment Analysis (MiRSEA), to identify the pathways regulated by dysfunctional miRNAs. MiRSEA integrates the differential expression levels of miRNAs with the strength of miRNA pathway associations to perform direct enrichment analysis using miRNA expression data. We describe the MiRSEA methodology and illustrate its effectiveness through analysis of data from hepatocellular cancer, gastric cancer and lung cancer. With these analyses, we show that MiRSEA can successfully detect latent biological pathways regulated by dysfunctional miRNAs. We have implemented MiRSEA as a freely available R-based package on CRAN (https://cran.r-project.org/web/packages/MiRSEA/).
近期研究表明，功能失调的微小RNA（miRNA）参与了多种癌症的进展。功能失调的miRNA可能共同调控其靶基因，并进一步改变经典生物学途径的活性。鉴定一组功能失调的miRNA所调控的途径有助于揭示癌症的致病机制，并促进新药物靶点的开发。目前的miRNA-途径分析主要使用差异表达的miRNA来预测它们所作用的共同途径。然而，这些方法没有考虑差异表达水平，而这可能会增进我们对miRNA功能的理解。我们提出了一种新的计算方法，即微小RNA集富集分析（MiRSEA），以鉴定功能失调的miRNA所调控的途径。MiRSEA将miRNA的差异表达水平与miRNA途径关联强度相结合，利用miRNA表达数据进行直接富集分析。我们描述了MiRSEA方法，并通过对肝细胞癌、胃癌和肺癌数据的分析来说明其有效性。通过这些分析，我们表明MiRSEA能够成功检测出由功能失调的miRNA调控的潜在生物学途径。我们已将MiRSEA作为一个基于R的免费软件包在CRAN（https://cran.r-project.org/web/packages/MiRSEA/）上实现。
