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 RNA s in a discovery cohort (n=100). Quantitative polymerase chain reaction ( qPCR ) assays were then applied to evaluate the expression of selected mi RNA s. 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 RNA s may have considerable clinical value in HCC diagnosis, and be particularly helpful for AFP ‐negative HCC .