Cailu Song: Department of Breast Oncology, Sun Yat-Sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, Guangdong, China.
Lijuan Zhang: Department of Breast Oncology, Sun Yat-Sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, Guangdong, China.
Jin Wang: Department of Breast Oncology, Sun Yat-Sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, Guangdong, China.
Zhongying Huang: Department of Nursing, Sun Yat-Sen University Cancer Center, Guangzhou, Guangdong, China.
Xing Li: Department of Breast Oncology, Sun Yat-Sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, Guangdong, China.
Mingqing Wu: Department of Cancer Prevention Center, Sun Yat-Sen University Cancer Center, Guangzhou, Guangdong, China.
Shuaijie Li: Department of Breast Oncology, Sun Yat-Sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, Guangdong, China.
Hailin Tang: Department of Breast Oncology, Sun Yat-Sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, Guangdong, China.
Xiaoming Xie: Department of Breast Oncology, Sun Yat-Sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, Guangdong, China.
More sensitive and effective diagnostic markers for the detection of breast cancer are urgently needed. The microRNA-183/182/96 cluster has been reported to be involved in tumorigenesis and progression in a variety of cancers, and it is a promising cancer prognostic biomarker. The goal of this study was to determine the expression levels of the miR-183/182/96 cluster in breast cancer tissues and evaluate its prognostic role in breast cancer. Real-time quantitative polymerase chain reaction analysis (qRT-PCR) was used to detect the expression levels of the miR-183/182/96 cluster in 41 breast cancer tissues and adjacent normal tissues (control tissues) and also in different mammary cell lines. In situ hybridization (ISH) of the miR-183/182/96 cluster on 131 tissue microarrays (TMAs) was used to statistically analyze its prognostic role. The miR-183/182/96 cluster levels were significantly higher in breast cancer tissues than in control tissues. The miR-183/182/96 cluster was also upregulated in human breast cancer cell lines. An increased miR-183/182/96 cluster level was correlated with local relapse, distant metastasis and poor clinical outcomes. Our findings improve our understanding of the expression level of the miR-183/182/96 cluster in breast cancer and clarify the role of the miR-183/182/96 cluster as a novel prognostic biomarker for breast cancer.
