Research Papers:

Identification of associations between small molecule drugs and miRNAs based on functional similarity

Jing Wang _, Fanlin Meng, EnYu Dai, Feng Yang, Shuyuan Wang, Xiaowen Chen, Lei Yang, Yuwen Wang and Wei Jiang

PDF  |  HTML  |  Supplementary Files  |  How to cite

Oncotarget. 2016; 7:38658-38669. https://doi.org/10.18632/oncotarget.9577

Metrics: PDF 1912 views  |   HTML 2293 views  |   ?  


Jing Wang1,*, Fanlin Meng1,*, EnYu Dai1, Feng Yang1, Shuyuan Wang1, Xiaowen Chen1, Lei Yang1, Yuwen Wang2, Wei Jiang1

1College of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, P. R. China

2The 2nd Affiliated Hospital, Harbin Medical University, Harbin 150081, P. R. China

*These authors have contributed equally to this work

Correspondence to:

Wei Jiang, email: [email protected]

Keywords: small molecule, miRNA, drug, functional similarity, microarray

Received: November 26, 2015    Accepted: May 08, 2016    Published: May 24, 2016


MicroRNAs (miRNAs) are a class of small non-coding RNA molecules that regulate gene expression at post-transcriptional level. Increasing evidences show aberrant expression of miRNAs in varieties of diseases. Targeting the dysregulated miRNAs with small molecule drugs has become a novel therapy for many human diseases, especially cancer. Here, we proposed a novel computational approach to identify associations between small molecules and miRNAs based on functional similarity of differentially expressed genes. At the significance level of p < 0.01, we constructed the small molecule and miRNA functional similarity network involving 111 small molecules and 20 miRNAs. Moreover, we also predicted associations between drugs and diseases through integrating our identified small molecule-miRNA associations with experimentally validated disease related miRNAs. As a result, we identified 2265 associations between FDA approved drugs and diseases, in which ~35% associations have been validated by comprehensive literature reviews. For breast cancer, we identified 19 potential drugs, in which 12 drugs were supported by previous studies. In addition, we performed survival analysis for the patients from TCGA and GEO database, which indicated that the associated miRNAs of 4 drugs might be good prognosis markers in breast cancer. Collectively, this study proposed a novel approach to predict small molecule and miRNA associations based on functional similarity, which may pave a new way for miRNA-targeted therapy and drug repositioning.

Creative Commons License All site content, except where otherwise noted, is licensed under a Creative Commons Attribution 4.0 License.
PII: 9577