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Identification and Validation of Circulating MicroRNA Signatures for Breast Cancer Early Detection Based on Large Scale Tissue-Derived Data

  • Yu, Xiaokang (School of Biology and Biological Engineering, South China University of Technology) ;
  • Liang, Jinsheng (School of Biology and Biological Engineering, South China University of Technology) ;
  • Xu, Jiarui (Department of Laboratory Science, The Second Affiliated Hospital of Guangzhou University of Chinese Medicine) ;
  • Li, Xingsong (School of Biology and Biological Engineering, South China University of Technology) ;
  • Xing, Shan (Department of Laboratory Medicine, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center) ;
  • Li, Huilan (Department of Laboratory Medicine, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center) ;
  • Liu, Wanli (Department of Laboratory Medicine, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center) ;
  • Liu, Dongdong (Department of Laboratory Science, The Second Affiliated Hospital of Guangzhou University of Chinese Medicine) ;
  • Xu, Jianhua (Department of Laboratory Science, The Second Affiliated Hospital of Guangzhou University of Chinese Medicine) ;
  • Huang, Lizhen (School of Biology and Biological Engineering, South China University of Technology) ;
  • Du, Hongli (School of Biology and Biological Engineering, South China University of Technology)
  • Received : 2018.08.06
  • Accepted : 2018.11.09
  • Published : 2018.12.31

Abstract

Purpose: Breast cancer is the most commonly occurring cancer among women worldwide, and therefore, improved approaches for its early detection are urgently needed. As microRNAs (miRNAs) are increasingly recognized as critical regulators in tumorigenesis and possess excellent stability in plasma, this study focused on using miRNAs to develop a method for identifying noninvasive biomarkers. Methods: To discover critical candidates, differential expression analysis was performed on tissue-originated miRNA profiles of 409 early breast cancer patients and 87 healthy controls from The Cancer Genome Atlas database. We selected candidates from the differentially expressed miRNAs and then evaluated every possible molecular signature formed by the candidates. The best signature was validated in independent serum samples from 113 early breast cancer patients and 47 healthy controls using reverse transcription quantitative real-time polymerase chain reaction. Results: The miRNA candidates in our method were revealed to be associated with breast cancer according to previous studies and showed potential as useful biomarkers. When validated in independent serum samples, the area under curve of the final miRNA signature (miR-21-3p, miR-21-5p, and miR-99a-5p) was 0.895. Diagnostic sensitivity and specificity were 97.9% and 73.5%, respectively. Conclusion: The present study established a novel and effective method to identify biomarkers for early breast cancer. And the method, is also suitable for other cancer types. Furthermore, a combination of three miRNAs was identified as a prospective biomarker for breast cancer early detection.

Keywords

Acknowledgement

Supported by : Central Universities

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