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Introduction: Due to the high recurrence, the HCC prognosis remains poor. Yet, the biomarkers for predicting the recurrence of high‐risk patients are currently lacking. We aimed to develop a signature to predict the recurrence of HCC based on NKG2D ligands. Methods: The multivariate Cox proportional hazards regression was used to select recurrence‐related variables of NKG2D ligands in HCC patients from The Cancer Genome Atlas (TCGA). HCC patients from the OEP000321 dataset and Guilin cohort were used to validate the predictive signature. The mRNA expression of NKG2D ligands was measured by QRT‐PCR. Immunohistochemistry analysis of HCC tissue microarray samples was used to identify the expression of NKG2D ligands. Results: In this study, NKG2D ligands expression in the mRNA and protein level was both abnormally expressed in HCC and associated with recurrence‐free survival (RFS). Then, the recurrence‐related variables of NKG2D ligands in HCC were selected by the multivariate Cox proportional hazards regression. Among the eight NKG2D ligands, MICA (HR = 1.347; 95% CI = 1.012–1.793; p = 0.041), ULBP3 (HR = 0.453; 95% CI = 0.231–0.889; p = 0.021) and ULBP5 (HR = 3.617; 95% CI = 1.819–7.194; p < 0.001) were significantly correlated with RFS in the TCGA‐LIHC cohort. Then, the signature was constructed by the three NKG2D ligands. The predictive effectiveness of this signature was also validated in the OEP000321 dataset and Guilin cohort. Further, HCC patients were classified into low‐risk and high‐risk subgroups by the predictive score. Compared with the low‐risk group, the high‐risk group had poor RFS in both training and validation cohorts. Importantly, compared with the low‐risk patients with the G1‐G2 stage, the levels of infiltrated NK‐activated cells and NKG2D expression were both lower in the high‐risk patients. Conclusions: The signature based on MICA, ULBP3, and ULBP5 could predict HCC recurrence. [ABSTRACT FROM AUTHOR]

Background: Hepatocarcinogenesis is reportedly correlated with abnormal m6A modifications; however, it is unknown whether m6A RNA methylation regulators facilitate the occurrence of hepatitis B virus (HBV)-related hepatocellular carcinoma (HCC). Thus, we constructed an m6A-related model that may enhance HBV-related HCC prognosis. Methods: Gene signatures of HNRNPA2B1 and RBM15 were generated by univariate and Lasso Cox regression analyses using the gene set and clinical information from The Cancer Genome Atlas (TCGA) database. High-risk and low-risk groups were confirmed based on the gene signature model. Furthermore, we validated the predictive roles of the two genes for overall survival (OS) in the GSE14520 dataset. The relative expression of 22 paired mRNAs was measured using quantitative real-time polymerase chain reaction (qRT-PCR) analysis to determine whether the two genes had a predictive role in our Guilin cohort. Results: The differences in OS between the high-risk and low-risk groups were statistically significant in the TCGA (p = 0.003) and GSE14520 (p = 0.045) datasets, but not in the Guilin cohort, owing to differences in clinical information among the three cohorts (mainly the TNM stage and survival state). Stratified analysis of TNM stages showed that the two-gene signature acted as a prognostic indicator of HBV-related HCC patients in the early TNM stage; both TCGA and GSE14520 cohorts showed statistical significance. Moreover, multivariate Cox regression analysis indicated that the two-gene signature was an independent factor for predicting prognosis (HR = 1.087, 95% CI: 1.007–1.172). Correlation analysis between the gene signature and clinical features revealed that the risk stratification was significantly correlated with grade and survival state. Finally, Gene Set Enrichment Analysis (GSEA) revealed that the KEGG pathways associated with the cell cycle, DNA replication, the spliceosome, repair, and metabolism-related processes were all significantly enriched in the high-risk group. Among the enriched genes, the expression levels of the replication protein RPA1 and the pre-mRNA splicing factor SF3B1 were significantly upregulated in the high-risk group. These results might help in elucidating the underlying molecular mechanisms of HBV-related HCC. Conclusions: Our data may provide new predictive signatures and potential therapeutic targets to identify and treat HBV-related HCC patients in the early disease stage. [ABSTRACT FROM AUTHOR]