OBJECTIVE: To investigate the expression of long non-coding RNA HOTAIR in the plasma of breast cancer patients and its value in the diagnosis of breast cancer. METHODS: HOTAIR levels were measured in 24 tumor tissues and 70 plasma samples from breast cancer patients using quantitative real-time PCR. The correlations of plasma HOTAIR level with the clinicopathological features of the patients were analyzed. A multivariate logistic regression model was established to analyze the value of plasma HOTAIR in comparison with plasma CA153 and CEA levels for breast cancer diagnosis. We further detected HOTAIR levels in the plasma and breast cancer tissues of 24 patients before and after operation and investigated their correlation. RESULTS: Breast cancer patients had increased expressions of HOTAIR in the tumor tissues and plasma, and plasma HOTAIR level was significantly correlated with estrogen receptor (ER) level (P=0.004) and lymph node metastasis (P=0.010). Receiver operating characteristic (ROC) curve and the multivariable logistic regression model showed that the area under ROC curve (AUC) of plasma HOTAIR was 0.82 (P<0.001) for breast cancer diagnosis with a diagnostic sensitivity and a specificity of 73.3% and 93.3%, respectively. The diagnostic power and specificity of plasma HOTAIR was much higher than those of CA153 (AUC=0.66, P=0.030) and CEA (AUC=0.52, P=0.001), and the combination of the 3 markers further enhanced the diagnostic power (AUC=0.84) and specificity (96.7%). Plasma HOTAIR level was significantly reduced in the patients after the operation (P<0.0001) and showed a moderate correlation with its expression in tumor tissues (r=0.62, P<0.0001). CONCLUSION: Plasma HOTAIR may serve as a potential biomarker for breast cancer diagnosis.
OBJECTIVE: To investigate the expression of long non-coding RNA HOTAIR in the plasma of breast cancerpatients and its value in the diagnosis of breast cancer. METHODS:HOTAIR levels were measured in 24 tumor tissues and 70 plasma samples from breast cancerpatients using quantitative real-time PCR. The correlations of plasma HOTAIR level with the clinicopathological features of the patients were analyzed. A multivariate logistic regression model was established to analyze the value of plasma HOTAIR in comparison with plasma CA153 and CEA levels for breast cancer diagnosis. We further detected HOTAIR levels in the plasma and breast cancer tissues of 24 patients before and after operation and investigated their correlation. RESULTS:Breast cancerpatients had increased expressions of HOTAIR in the tumor tissues and plasma, and plasma HOTAIR level was significantly correlated with estrogen receptor (ER) level (P=0.004) and lymph node metastasis (P=0.010). Receiver operating characteristic (ROC) curve and the multivariable logistic regression model showed that the area under ROC curve (AUC) of plasma HOTAIR was 0.82 (P<0.001) for breast cancer diagnosis with a diagnostic sensitivity and a specificity of 73.3% and 93.3%, respectively. The diagnostic power and specificity of plasma HOTAIR was much higher than those of CA153 (AUC=0.66, P=0.030) and CEA (AUC=0.52, P=0.001), and the combination of the 3 markers further enhanced the diagnostic power (AUC=0.84) and specificity (96.7%). Plasma HOTAIR level was significantly reduced in the patients after the operation (P<0.0001) and showed a moderate correlation with its expression in tumor tissues (r=0.62, P<0.0001). CONCLUSION: Plasma HOTAIR may serve as a potential biomarker for breast cancer diagnosis.