Inferring miRNA sponge co-regulation of protein-protein interactions in human breast cancer

BMC Bioinformatics

Research Article

Junpeng Zhang¹  Lin Liu²  Jiuyong Li²  Thuc Duy Le³ 

[1] School of Engineering, Dali University, 671003, Dali, Yunnan, People’s Republic of China;School of Information Technology and Mathematical Sciences, University of South Australia, 5095, Mawson Lakes, SA, Australia;School of Information Technology and Mathematical Sciences, University of South Australia, 5095, Mawson Lakes, SA, Australia;Centre for Cancer Biology, University of South Australia, 5000, Adelaide, SA, Australia;

关键词: miRNA sponge;    ceRNA;    miRNA sponge co-regulation;    lncRNA;    Protein-protein interaction;    Breast cancer;   

DOI  :  10.1186/s12859-017-1672-2

 received in 2017-03-14, accepted in 2017-05-03,  发布年份 2017

来源: Springer

【 摘 要 】

BackgroundRecent studies have shown that the crosstalk between microRNA (miRNA) sponges plays an important role in human cancers. However, the co-regulation roles of miRNA sponges in protein-protein interactions (PPIs) are still unknown.ResultsIn this study, we propose a multi-step method called miRSCoPPI to infer miRNA sponge co-regulation of PPIs. We focus on investigating breast cancer (BRCA) related miRNA sponge co-regulation, by integrating heterogeneous data, including miRNA, long non-coding RNA (lncRNA) and messenger RNA (mRNA) expression data, experimentally validated miRNA-target interactions, PPIs and lncRNA-target interactions, and the list of breast cancer genes. We find that the inferred BRCA-related miRSCoPPI network is highly connected and scale free. The top 10% hub genes in the BRCA-related miRSCoPPI network have potential biological implications in breast cancer. By utilizing a graph clustering method, we discover 17 BRCA-related miRSCoPPI modules. Through pathway enrichment analysis of the modules, we find that several modules are significantly enriched in pathways associated with breast cancer. Moreover, 10 modules have good performance in classifying breast tumor and normal samples, and can act as module signatures for prognostication. By using putative computationally predicted miRNA-target interactions, we have consistent results with those obtained using experimentally validated miRNA-target interactions, indicating that miRSCoPPI is robust in inferring miRNA sponge co-regulation of PPIs in human breast cancer.ConclusionsTaken together, the results demonstrate that miRSCoPPI is a promising tool for inferring BRCA-related miRNA sponge co-regulation of PPIs and it can help with the understanding of the co-regulation roles of miRNA sponges on the PPIs.

【 授权许可】

CC BY   
© The Author(s). 2017