Genome-wide screen for aberrantly expressed miRNAs reveals miRNA profile signature in breast cancer
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Dysregulation in the expression of miRNAs contributes to the occurrence and development of many human cancers. We herein attempted to obtain the potential association between miRNA expression profile and breast cancer by applying high-throughput sequencing technology. Small RNAs from seven paired tumor and adjacent normal tissue samples were sequenced. To determine the miRNA expression profiles in tissues and sera, another five equally pooled serum samples from 20 patients and 30 normal women were sequenced. Despite a similar number in abundantly expressed miRNAs across samples, we detected varying miRNA expression profiles. Some miRNAs showed inconsistent or opposite dysregulation trends across different tumor tissues, including some abundantly expressed miRNA gene clusters and gene families. Wilcoxon sign-rank test for paired samples analysis revealed that abnormal miRNAs showed a higher level of variation across the seven tumor samples. We also completely surveyed abnormal miRNAs expressed in tumor and serum tissues in the mixed datasets based on the relative expression levels. Most of these miRNAs were significantly down-regulated in tumor samples, but nine abnormal miRNAs (miR-18a, 19a, 20a, 30a, 103b, 126, 126*, 192, 1287) were consistently expressed in tumor tissues and serum samples. Based on experimentally validated target mRNAs, functional enrichment analysis indicated that these abnormal miRNAs and miRNA groups (miRNA gene clusters and gene families) have important roles in multiple biological processes. Dynamic miRNA expression profiles, various abnormal miRNA profiles and complexity of the miRNA regulatory network reveal that the miRNA expression profile is a potential biomarker for classifying or detecting human disease.
KeywordsMicroRNA (miRNA) Breast cancer miRNA profile
We appreciate all the patients and healthy controls who participated in this research. We thank Juncheng Dai, Yongyue Wei and Jianling Bai for their help in statistic analysis. The work was supported by National Natural Science Foundation of China (Nos. 30901232, 81072389 and 81102182), China Postdoctoral Science Foundation funded project (No. 2012M521100), University Science Research Project of Jiangsu Province (No. 12KJB310003), Jiangsu Planned Projects for Postdoctoral Research Funds (No. 1201022B), Science and Technology Development Fund Key Project of Nanjing Medical University (No. 2012NJMU001), and the Priority Academic Program Development of Jiangsu Higher Education Institutions (PAPD).
Conflict of interest
The authors declare no potential conflict of interests with respect to the authorship and/or publication of this paper.
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