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BioMed Research International
Volume 2015 (2015), Article ID 746970, 17 pages
Research Article

Identification of Novel Breast Cancer Subtype-Specific Biomarkers by Integrating Genomics Analysis of DNA Copy Number Aberrations and miRNA-mRNA Dual Expression Profiling

1Institute of Biomedical Engineering, Capital Medical University, Beijing 100069, China
2Institute of Basic Medical Science, Peking Union Medical College, Qinghua University, No. 5 Dong Dan San Tiao, Beijing 100005, China

Received 16 July 2014; Revised 15 September 2014; Accepted 22 September 2014

Academic Editor: Jiangning Song

Copyright © 2015 Dongguo Li et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Breast cancer is a heterogeneous disease with well-defined molecular subtypes. Currently, comparative genomic hybridization arrays (aCGH) techniques have been developed rapidly, and recent evidences in studies of breast cancer suggest that tumors within gene expression subtypes share similar DNA copy number aberrations (CNA) which can be used to further subdivide subtypes. Moreover, subtype-specific miRNA expression profiles are also proposed as novel signatures for breast cancer classification. The identification of mRNA or miRNA expression-based breast cancer subtypes is considered an instructive means of prognosis. Here, we conducted an integrated analysis based on copy number aberrations data and miRNA-mRNA dual expression profiling data to identify breast cancer subtype-specific biomarkers. Interestingly, we found a group of genes residing in subtype-specific CNA regions that also display the corresponding changes in mRNAs levels and their target miRNAs’ expression. Among them, the predicted direct correlation of BRCA1-miR-143-miR-145 pairs was selected for experimental validation. The study results indicated that BRCA1 positively regulates miR-143-miR-145 expression and miR-143-miR-145 can serve as promising novel biomarkers for breast cancer subtyping. In our integrated genomics analysis and experimental validation, a new frame to predict candidate biomarkers of breast cancer subtype is provided and offers assistance in order to understand the potential disease etiology of the breast cancer subtypes.