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dc.contributor.authorLi, Jieen_US
dc.contributor.authorLei, Kechengen_US
dc.contributor.authorWu, Zengruien_US
dc.contributor.authorLi, Weihuaen_US
dc.contributor.authorLiu, Guixiaen_US
dc.contributor.authorLiu, Jianwenen_US
dc.contributor.authorCheng, Feixiongen_US
dc.contributor.authorTang, Yunen_US
dc.date.accessioned2017-02-18T01:58:46Z
dc.date.issued2016en_US
dc.identifier.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.en
dc.identifier.issn1949-2553en
dc.identifier.urihttp://nrs.harvard.edu/urn-3:HUL.InstRepos:30371077
dc.description.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/.en
dc.language.isoen_USen
dc.publisherImpact Journals LLCen
dc.relation.isversionofdoi:10.18632/oncotarget.10052en
dc.relation.hasversionhttp://www.ncbi.nlm.nih.gov/pmc/articles/PMC5216744/pdf/en
dash.licenseLAAen_US
dc.subjectpharmacogenomicsen
dc.subjectmiRNAen
dc.subjectnetwork-based inferenceen
dc.subjectmetforminen
dc.subjectbreast canceren
dc.titleNetwork-based identification of microRNAs as potential pharmacogenomic biomarkers for anticancer drugsen
dc.typeJournal Articleen_US
dc.description.versionVersion of Recorden
dc.relation.journalOncotargeten
dc.date.available2017-02-18T01:58:46Z
dc.identifier.doi10.18632/oncotarget.10052*
dash.authorsorderedfalse


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