Recent research has tried to use exosomal RNAs (coding and noncoding) as potential diagnostic markers for hepatocellular carcinoma (HCC). Initially, by using bioinformatics, we selected an HCC-exosomal RNA-based biomarker panel. The choice of this panel depends on the integration of Ras-related in brain (RAB11A) gene expression and its competing endogenous network. This network includes long noncoding RNA RP11-513I15.6 (lncRNA-RP11-513I15.6) and microRNA-1262 (miR-1262). Secondly, we tried to validate the expression of this network in the sera of 60 patients with HCC in comparison with 42 chronic hepatitis C virus-infected patients and 18 healthy controls. Then we assessed the diagnostic efficiency of this panel using a receiver operating characteristic curve analysis. The panel of 3 exosomal RNA-based biomarkers (lncRNA-RP11-513I15.6, miR-1262, and RAB11A) showed excellent sensitivity and specificity in discriminating patients with HCC from patients with chronic hepatitis C virus and healthy controls. Among these 3 RNAs, serum RAB11A mRNA was the most independent prognostic factor. The selected circulatory exosomal RNA-based biomarker panel showed its ability to be used as a diagnostic and prognostic biomarker tool for HCC. Moreover, these biomarkers could be therapeutic targets.
Keywords: bioinformatics; competing endogenous RNA (ceRNA); diagnosis; exosomes hepatocellular carcinoma.
© 2018 Wiley Periodicals, Inc.