Increasing evidence indicates that the expressions of messenger RNAs (mRNAs) and long non‐coding RNAs (lncRNAs) undergo a frequent and aberrant change in carcinogenesis and cancer development. But some research was carried out on mRNA‐lncRNA signatures for prediction of hepatocellular carcinoma (HCC) prognosis. We aimed to establish an mRNA‐lncRNA signature to improve the ability to predict HCC patients’ survival. The subjects from the cancer genome atlas (TCGA) data set were randomly divided into two parts: training data set (n = 246) and testing data set (n = 124). Using computational methods, we selected eight gene signatures (five mRNAs and three lncRNAs) to generate the risk score model, which were significantly correlated with overall survival of patients with HCC in both training and testing data set. The signature had the ability to classify the patients in training data set into a high‐risk group and low‐risk group with significantly different overall survival (hazard ratio = 4.157, 95% confidence interval = 2.648‐6.526, P < 0.001). The prognostic value was further validated in testing data set and the entire data set. Further analysis revealed that this signature was independent of tumor stage. In addition, Gene Set Enrichment Analysis suggested that high risk score group was associated with cell proliferation and division related pathways. Finally, we developed a well‐performed nomogram integrating the prognostic signature and other clinical information to predict 3‐ and 5‐year overall survival. In conclusion, the prognostic mRNAs and lncRNAs identified in our study indicate their potential role in HCC biogenesis. The risk score model based on the mRNA‐lncRNA may be an efficient classification tool to evaluate the prognosis of patients’ with HCC.

Aim: Flare-ups of chronic hepatitis B can sometimes be severe and even progress to acute-on-chronic liver failure (ACLF), with high short-term mortality. A timely estimation of the risk of death should be initiated early. The aim of the present study was to determine whether novel biomarkers add prognostic information beyond current clinical scoring systems.Methods: Patients with hepatitis B-associated ACLF were prospectively enrolled from five hospitals in China between August 2017 and March 2018. Their plasma was screened for soluble CD163 (sCD163), neutrophil gelatinase-associated lipocalin (NGAL), and copeptin. The association between these biomarkers and mortality was analyzed. The performance of the Model for End-stage Liver Disease, Asian-Pacific Association for the Study of the Liver-ACLF Research Consortium score, and the Chronic Liver Failure Consortium ACLF score, with or without biomarkers, were compared. Results: One hundred fifty one patients were enrolled. Advanced ACLF patients had significantly higher levels than early ACLF individuals of plasma biomarkers sCD163 (P = 0.001), NGAL (P = 0.006), and copeptin (P = 0.049). Thirty-four deaths occurred during the 28-day follow-up period (22.5%). Both sCD163 and NGAL showed a strong independent association with 28-day mortality, whereas copeptin did not. Scoring systems incorporating sCD163 and NGAL had better discrimination and calibration, as measured by area under the receiver operating characteristic curves, the Akaike information criteria, integrated discrimination improvement, and net reclassification improvement.Conclusions: Soluble CD163 and NGAL are independently associated with short-term mortality in hepatitis B-associated ACLF. Use of a combination of sCD163 and NGAL improves prognostication.

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