Serum micro RNA profiles as diagnostic biomarkers for HBV-positive hepatocellular carcinoma.

Background & Aims The discovery of effective and reliable biomarkers to detect hepatitis B virus ( HBV)-positive hepatocellular carcinoma ( HCC) at an early stage may improve the survival of HCC. The aim of this study was to establish serum micro RNA (mi RNA) profiles as diagnostic biomarkers for HBV-positive HCC. Methods We used deep sequencing to screen serum mi RNAs in a discovery cohort (n=100). Quantitative polymerase chain reaction ( qPCR) assays were then applied to evaluate the expression of selected mi RNAs. A diagnostic 2-mi RNA panel was established by a logistic regression model using a training cohort (n=182). The predicted probability of being detected as HCC was used to construct the receiver operating characteristic ( ROC) curve. Area under the ROC curve ( AUC) was used to assess the diagnostic performance of the selected mi RNA panel. Results The predicted probability of being detected as HCC by the 2-mi RNA panel was calculated by: logit P=−2.988 + 1.299 × miR-27b-3p + 1.245 × miR-192-5p. These results were further confirmed in a validation cohort (n=246).The mi RNA panel provided a high diagnostic accuracy of HCC ( AUC=0.842, P<.0001 for training set; AUC=0.836, P<.0001 for validation set respectively). In addition, the mi RNA panel showed better prediction of HCC diagnosis than did alpha-foetoprotein ( AFP). The mi RNA panel also differentiated HCC from healthy ( AUC=0.823, P<.0001), and cirrhosis patients ( AUC=0.859, P<.0001) respectively. Conclusions Differentially expressed serum mi RNAs may have considerable clinical value in HCC diagnosis, and be particularly helpful for AFP-negative HCC. [ABSTRACT FROM AUTHOR]