BACKGROUND: MicroRNA-21 (miR-21) has previously been demonstrated as a potential biomarker in diagnosis of various human tumors. This meta-analysis was performed to evaluate the possibility of miR-21 as a biomarker for early detection of lung cancer. METHODS: Relevant lung cancer-related miRNA microarray datasets were collected from the NCBI Gene Expression Omnibus (GEO) database and EBI ArrayExpress database up to February 2014. Quality control of the output data was estimated using Limma package and ExiMiR package in R. Standardized mean difference (SMD) with 95% confidence intervals (CIs) from selected datasets was pooled. Heterogeneity was assessed using Cochran's Q test and the I2 statistic, and a p value <0.0.05 or I2 >50% was defined as significant heterogeneity. Furthermore, sensitivity analysis was conducted to evaluate the stability of the pooled results. Four miRNA datasets (GSE24704, GSE17681, GSE27486 and GSE40738) from blood samples were selected, including 153 lung cancer patients and 109 healthy people. RESULTS: The pooled results generated by random-effects model revealed that no significant difference was observed between case and control groups (SMD = 0.58; 95% CI, -0.04 to 1.19; p = 0.07) with significant heterogeneity (p = 0.0032, I2 = 78.2%; p = 0.06). Sensitivity analysis indicated that the results of the meta-analysis were stable. CONCLUSIONS: MiR-21 expression levels in whole blood and peripheral blood cells did not show significant differences between lung cancer patients and healthy controls, and it might be ineffective to measure miR-21 expression to achieve an early diagnosis of lung cancer.
BACKGROUND:MicroRNA-21 (miR-21) has previously been demonstrated as a potential biomarker in diagnosis of various humantumors. This meta-analysis was performed to evaluate the possibility of miR-21 as a biomarker for early detection of lung cancer. METHODS: Relevant lung cancer-related miRNA microarray datasets were collected from the NCBI Gene Expression Omnibus (GEO) database and EBI ArrayExpress database up to February 2014. Quality control of the output data was estimated using Limma package and ExiMiR package in R. Standardized mean difference (SMD) with 95% confidence intervals (CIs) from selected datasets was pooled. Heterogeneity was assessed using Cochran's Q test and the I2 statistic, and a p value &lt;0.0.05 or I2 &gt;50% was defined as significant heterogeneity. Furthermore, sensitivity analysis was conducted to evaluate the stability of the pooled results. Four miRNA datasets (GSE24704, GSE17681, GSE27486 and GSE40738) from blood samples were selected, including 153 lung cancerpatients and 109 healthy people. RESULTS: The pooled results generated by random-effects model revealed that no significant difference was observed between case and control groups (SMD = 0.58; 95% CI, -0.04 to 1.19; p = 0.07) with significant heterogeneity (p = 0.0032, I2 = 78.2%; p = 0.06). Sensitivity analysis indicated that the results of the meta-analysis were stable. CONCLUSIONS:MiR-21 expression levels in whole blood and peripheral blood cells did not show significant differences between lung cancerpatients and healthy controls, and it might be ineffective to measure miR-21 expression to achieve an early diagnosis of lung cancer.