Fan Lichao, Yu Xiaoting, Huang Ziling, Zheng Shaoqiang, Zhou Yongxin, Lv Hanjing, Zeng Yu, Xu Jin-Fu, Zhu Xuyou, Yi Xianghua
Department of Pathology, Tongji Hospital, Tongji University School of Medicine, Shanghai 200065, China.
Department of Respiratory and Critical Care Medicine, Shanghai Pulmonary Hospital, Tongji University School of Medicine, Shanghai 200443, China.
Mediators Inflamm. 2017;2017:1804240. doi: 10.1155/2017/1804240. Epub 2017 May 14.
The aim of this study was to identify potential microRNAs and genes associated with idiopathic pulmonary fibrosis (IPF) through web-available microarrays. The microRNA microarray dataset GSE32538 and the mRNA datasets GSE32537, GSE53845, and GSE10667 were downloaded from the Gene Expression Omnibus (GEO) database. Differentially expressed miRNAs (DE-miRNAs)/genes (DEGs) were screened with GEO2R, and their associations with IPF were analyzed by comprehensive bioinformatic analyses. A total of 45 DE-microRNAs were identified between IPF and control tissues, whereas 67 common DEGs were determined to exhibit the same expression trends in all three microarrays. Furthermore, functional analysis indicated that microRNAs in cancer and ECM-receptor interaction were the most significant pathways and were enriched by the 45 DE-miRNAs and 67 common DEGs. Finally, we predicted potential microRNA-target interactions between 17 DE-miRNAs and 17 DEGs by using at least three online programs. A microRNA-mediated regulatory network among the DE-miRNAs and DEGs was constructed that might shed new light on potential biomarkers for the prediction of IPF progression.
本研究的目的是通过可从网络获取的微阵列来鉴定与特发性肺纤维化(IPF)相关的潜在微小RNA和基因。从基因表达综合数据库(GEO)下载了微小RNA微阵列数据集GSE32538以及mRNA数据集GSE32537、GSE53845和GSE10667。使用GEO2R筛选差异表达的微小RNA(DE-miRNA)/基因(DEG),并通过综合生物信息学分析来分析它们与IPF的关联。在IPF组织和对照组织之间共鉴定出45个DE-微小RNA,而在所有三个微阵列中确定有67个常见DEG呈现相同的表达趋势。此外,功能分析表明癌症和细胞外基质-受体相互作用中的微小RNA是最显著的途径,并且被这45个DE-微小RNA和67个常见DEG所富集。最后,我们使用至少三个在线程序预测了17个DE-微小RNA与17个DEG之间潜在的微小RNA-靶标相互作用。构建了一个DE-微小RNA和DEG之间的微小RNA介导的调控网络,这可能为预测IPF进展的潜在生物标志物提供新的线索。