A 10-microRNA prognosis scoring system in esophageal squamous cell carcinoma constructed using bioinformatic methods

MicroRNA (miR) signatures may aid the diagnosis and prediction of cancer; therefore, miRs associated with the prognosis of esophageal squamous cell carcinoma (ESCC) were screened. miR-sequencing (seq) and mRNA-seq data from early-stage ESCC samples were downloaded from The Cancer Genome Atlas (TCGA) database, and samples from subjects with a >6-month survival time were assessed with Cox regression analysis for prognosis-associated miRs. A further two miR expression datasets of ESCC samples, GSE43732 and GSE13937, were downloaded from the Gene Expression Omnibus database. Common miRs between prognosis-associated miRs, and miRs in the GSE43732 and GSE13937, datasets were used for risk score calculations for each sample, and median risk scores were applied for the stratification of low- and high-risk samples. A prognostic scoring system of signature miRs was subsequently constructed and used for survival analysis for low- and high-risk samples. Differentially-expressed genes (DEGs) corresponding to all miRs were screened and functional annotation was performed. A total of 34 prognostic miRs were screened and a scoring system was created using 10 signature miRs (hsa-miR-140, −33b, −34b, −144, −486, −214, −129-2, −374a and −412). Using this system, low-risk samples were identified to be associated with longer survival compared with high-risk samples in the TCGA and GSE43732 datasets. Age, alcohol and tobacco use, and radiotherapy were prognostic factors for samples with different risk scores and the same clinical features. There were 168 DEGs, and the top 20 risk scores positively-correlated and the top 20 risk scores negatively-correlated DEGs were significantly enriched for six and 10 functional terms, respectively. ‘Tight junction’ and ‘melanogenesis’ were two significantly enriched pathways of DEGs. miR-214, miR-129-2, miR-37a and miR-486 may predict ESCC patient survival, although further studies to validate this hypothesis are required.