Network-based identification of microRNAs as potential pharmacogenomic biomarkers for anticancer drugs
Tang, YunNote: Order does not necessarily reflect citation order of authors.
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CitationLi, Jie, Kecheng Lei, Zengrui Wu, Weihua Li, Guixia Liu, Jianwen Liu, Feixiong Cheng, and Yun Tang. 2016. “Network-based identification of microRNAs as potential pharmacogenomic biomarkers for anticancer drugs.” Oncotarget 7 (29): 45584-45596. doi:10.18632/oncotarget.10052. http://dx.doi.org/10.18632/oncotarget.10052.
AbstractAs the recent development of high-throughput technologies in cancer pharmacogenomics, there is an urgent need to develop new computational approaches for comprehensive identification of new pharmacogenomic biomarkers, such as microRNAs (miRNAs). In this study, a network-based framework, namely the SMiR-NBI model, was developed to prioritize miRNAs as potential biomarkers characterizing treatment responses of anticancer drugs on the basis of a heterogeneous network connecting drugs, miRNAs and genes. A high area under the receiver operating characteristic curve of 0.820 ± 0.013 was yielded during 10-fold cross validation. In addition, high performance was further validated in identifying new anticancer mechanism-of-action for natural products and non-steroidal anti-inflammatory drugs. Finally, the newly predicted miRNAs for tamoxifen and metformin were experimentally validated in MCF-7 and MDA-MB-231 breast cancer cell lines via qRT-PCR assays. High success rates of 60% and 65% were yielded for tamoxifen and metformin, respectively. Specifically, 11 oncomiRNAs (e.g. miR-20a-5p, miR-27a-3p, miR-29a-3p, and miR-146a-5p) from the top 20 predicted miRNAs were experimentally verified as new pharmacogenomic biomarkers for metformin in MCF-7 or MDA-MB-231 cell lines. In summary, the SMiR-NBI model would provide a powerful tool to identify potential pharmacogenomic biomarkers characterized by miRNAs in the emerging field of precision cancer medicine, which is available at http://lmmd.ecust.edu.cn/database/smir-nbi/.
Citable link to this pagehttp://nrs.harvard.edu/urn-3:HUL.InstRepos:30371077
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