Abstract
To evaluate the diagnostic potential of a six microRNAs (miRNAs) panel consisting of miR-21, miR-144, miR-107, miR-342, miR-93 and miR-152 for esophageal cancer (EC) detection. The expression of miRNAs was analyzed in EC sera samples using quantitative real-time PCR. Risk score analysis was performed and linear regression models were then fitted to generate the six-miRNA panel. In addition, we made an effort to identify significantly dysregulated miRNAs and mRNAs in EC using theCancerGenome Atlas (TCGA) miRNAseq and RNAseq datasets, respectively. Further, we identified significantly correlated miRNA-mRNA target pairs by integrating TCGA EC miRNAseq dataset with RNAseq dataset. The panel of circulating miRNAs showed enhanced sensitivity (87.5%) and specificity (90.48%) in terms of discriminating EC patients from normal subjects (area under the curve [AUC]=0.968). Pathway enrichment analysis for potential targets of six miRNAs revealed 48 significant (P<0.05) pathways, viz. pathways in cancer, mRNA surveillance, MAPK, Wnt, mTOR signaling, and so on. The expression data for mRNAs and miRNAs, downloaded from TCGA database, lead to identification of 2309 differentially expressed genes and 189 miRNAs. Gene ontology and pathway enrichment analysis showed that cell-cycle processes were most significantly enriched for differentially expressed mRNA. Integrated analysis of TCGA miRNAseq and RNAseq datasets resulted in identification of 53063 significantly and negatively correlated miRNA-mRNA pairs. In summary, a novel and highly sensitive signature of serummiRNAswas identified for EC detection. Moreover, this is the first report identifying miRNA-mRNA target pairs from EC TCGA dataset, thus providing a comprehensive resource for understanding the interactions existing between miRNA and their target mRNAs in EC.
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