Expression of microRNA-497 and its prognostic significance in human breast cancer
Department of General Surgery, Jinling Hospital, School of Medicine, Nanjing University, 315 Zhongshan East Road, Nanjing, Jiangsu 210002, PR China
Diagnostic Pathology 2013, 8:172 doi:10.1186/1746-1596-8-172Published: 21 October 2013
Dysregulation of microRNAs (miRNAs) plays critical roles in tumor progression. The aim of this study was to investigate the clinicopathologic and prognostic significance of miR-497 expression in human breast cancer (BC).
Taqman qRT-PCR assay was performed to detect the expression of microRNA (miR)-497 in 30 pairs of BC tissues and corresponding noncancerous breast tissues. Additionally, the expression of this miRNA was detected in another 128 BC tissues and its correlations with clinicopathologic features of patients were analyzed. Kaplan-Meier analyses were used to assess survival of patients. Univariate and multivariate analyses were performed using the Cox proportional hazards model to analyze the prognostic significance of miR-497 expression.
Our data indicated that the relative level of miR-497 expression in BC tissues was significantly lower than that in corresponding noncancerous breast tissues (P = 0.0046). Of 128 BC patients, 74 (57.8%) were placed in the high-miR-497 group and 54 (42.2%) were placed in the low-miR-497 group. By statistical analyses, low miR-497 expression was observed to be closely correlated with higher differentiation grade, positive HER-2 expression, higher incidence of lymph node metastasis and advanced clinical stage. Moreover, patients with high miR-497 expression had better 5-year disease-free and overall survival compared with the low miR-497 group (P = 0.0124 and 0.0018, respectively). Univariate and multivariate analyses indicated that low miR-497 expression was an independent poor prognostic factor for BC patients.
Our data provided the first evidence that downregulation of miR-497 was correlated with BC progression, and miR-497 might be a potential molecular biomarker for predicting the prognosis of patients.
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