Analysis of Microarray-Identified Genes and MicroRNAs Associated with Idiopathic Pulmonary Fibrosis

被引:32
作者
Fan, Lichao [1 ,2 ]
Yu, Xiaoting [1 ]
Huang, Ziling [1 ]
Zheng, Shaoqiang [3 ]
Zhou, Yongxin [4 ]
Lv, Hanjing [5 ]
Zeng, Yu [1 ]
Xu, Jin-Fu [2 ]
Zhu, Xuyou [1 ]
Yi, Xianghua [1 ]
机构
[1] Tongji Univ, Tongji Hosp, Dept Pathol, Sch Med, Shanghai 200065, Peoples R China
[2] Tongji Univ, Sch Med, Shanghai Pulm Hosp, Dept Resp & Crit Care Med, Shanghai 200443, Peoples R China
[3] Tongji Univ, Sch Med, Tongji Hosp, Dept Radiol, Shanghai 200065, Peoples R China
[4] Tongji Univ, Tongji Hosp, Sch Med, Dept Thorac Cardiovasc Surg, Shanghai 200065, Peoples R China
[5] Tongji Univ, Shanghai Tongji Hosp, Sch Med, Dept Resp Med, Shanghai 200065, Peoples R China
基金
中国国家自然科学基金;
关键词
EXPRESSION PROFILES; ADHESION MOLECULES; EPITHELIAL-CELLS; PATHOGENESIS; BIOMARKERS; PATTERNS; DISEASE; LET-7D;
D O I
10.1155/2017/1804240
中图分类号
Q2 [细胞生物学];
学科分类号
071009 ; 090102 ;
摘要
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.
引用
收藏
页数:9
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