Hai-Biao Yan1, Jia-Cheng Huang1, You-Rong Chen1, Jian-Ni Yao1, Wei-Ning Cen1, Jia-Yi Li1, Yi-Fan Jiang1, Gang Chen2, Sheng-Hua Li1. 1. Department of Urology Surgery, First Affiliated Hospital of Guangxi Medical University, 6 Shuangyong Road, Nanning, Guangxi Zhuang Autonomous Region 530021, China. 2. Department of Pathology, First Affiliated Hospital of Guangxi Medical University, 6 Shuangyong Road, Nanning, Guangxi Zhuang Autonomous Region 530021, China.
Abstract
PURPOSE: To investigate the clinical value and potential molecular mechanisms of miR-1 in clear cell renal cell carcinoma (ccRCC). METHODS: We searched the Gene Expression Omnibus (GEO), ArrayExpress, several online publication databases and the Cancer Genome Atlas (TCGA). Continuous variable meta-analysis and diagnostic meta-analysis were conducted, both in Stata 14, to show the expression of miR-1 in ccRCC. Furthermore, we acquired the potential targets of miR-1 from datasets that transfected miR-1 into ccRCC cells, online prediction databases, differentially expressed genes from TCGA and literature. Subsequently bioinformatics analysis based on aforementioned selected target genes was conducted. RESULTS: The combined effect was -0.92 with the 95% confidence interval (CI) of -1.08 to -0.77 based on fixed effect model (I2 = 81.3%, P < 0.001). No publication bias was found in our investigation. Sensitivity analysis showed that GSE47582 and 2 TCGA studies might cause heterogeneity. After eliminating them, the combined effect was -0.47 (95%CI: -0.78, -0.16) with I2 = 18.3%. As for the diagnostic meta-analysis, the combined sensitivity and specificity were 0.90 (95%CI: 0.61, 0.98) and 0.63 (95%CI: 0.39, 0.82). The area under the curve (AUC) in the summarized receiver operating characteristic (SROC) curve was 0.83 (95%CI: 0.80, 0.86). No publication bias was found (P = 0.15). We finally got 67 genes which were defined the promising target genes of miR-1 in ccRCC. The most three significant KEGG pathways based on the aforementioned genes were Complement and coagulation cascades, ECM-receptor interaction and Focal adhesion. CONCLUSION: The downregulation of miR-1 might play an important role in ccRCC by targeting its target genes.
PURPOSE: To investigate the clinical value and potential molecular mechanisms of miR-1 in clear cell renal cell carcinoma (ccRCC). METHODS: We searched the Gene Expression Omnibus (GEO), ArrayExpress, several online publication databases and the Cancer Genome Atlas (TCGA). Continuous variable meta-analysis and diagnostic meta-analysis were conducted, both in Stata 14, to show the expression of miR-1 in ccRCC. Furthermore, we acquired the potential targets of miR-1 from datasets that transfected miR-1 into ccRCC cells, online prediction databases, differentially expressed genes from TCGA and literature. Subsequently bioinformatics analysis based on aforementioned selected target genes was conducted. RESULTS: The combined effect was -0.92 with the 95% confidence interval (CI) of -1.08 to -0.77 based on fixed effect model (I2 = 81.3%, P < 0.001). No publication bias was found in our investigation. Sensitivity analysis showed that GSE47582 and 2 TCGA studies might cause heterogeneity. After eliminating them, the combined effect was -0.47 (95%CI: -0.78, -0.16) with I2 = 18.3%. As for the diagnostic meta-analysis, the combined sensitivity and specificity were 0.90 (95%CI: 0.61, 0.98) and 0.63 (95%CI: 0.39, 0.82). The area under the curve (AUC) in the summarized receiver operating characteristic (SROC) curve was 0.83 (95%CI: 0.80, 0.86). No publication bias was found (P = 0.15). We finally got 67 genes which were defined the promising target genes of miR-1 in ccRCC. The most three significant KEGG pathways based on the aforementioned genes were Complement and coagulation cascades, ECM-receptor interaction and Focal adhesion. CONCLUSION: The downregulation of miR-1 might play an important role in ccRCC by targeting its target genes.