Background The study examines the expression and function of hypoxia-inducible gene 2 (HIG2) in hepatocellular carcinoma (HCC) tissues and cells. Methods Forty patients with HCC were included in the study. Bioinformatic analysis was used to analyze the clinical relevance of HIG2 expression in HCC tissue samples. Immunohistochemistry was employed to determine the expression of target proteins in tumor tissues. Hepatic HepG2 and SMMC-7721 cells were transfected with HIG2 -targeting siRNA with Lipofectamine 2000. qRT-PCR was carried out to determine gene expression levels, while Western blotting was used to determine protein expression. A CCK-8 assay was performed to detect proliferation of cells, while migration and invasion of cells were studied by Transwell assay. Flow cytometry was carried out to detect surface markers and effector molecules in Nature killercells, as well as the killing effect of NK cells. Results HIG2 expression was upregulated in HCC. Silencing of HIG2 suppressed HCC cell migration and invasion. The killing effect of NK cells on HCC cells was enhanced after HIG2 was silenced in HCC cells. Conditioned media from HIG2 -silenced SMMC-7721 cells inhibited the phenotype and function of NK cells. HCC cells with silenced expression of HIG2 modulated the activity of NK cells via STAT3. HIG2 promoted the evasion of HCC cells from killing by NK cells through upregulation of IL-10 expression. Conclusion The study demonstrates that HIG2 activates the STAT3 signaling pathway in NK cells by promoting IL-10 release by HCC cells, thereby inhibiting the killing activity of NK cells, and subsequently promoting the recurrence and metastasis of HCC.

BackgroundThe NF-κB signaling pathway plays an important role in associating inflammation with tumor development and progression. However, few studies have reported that roles of genetic variants of the NF-κB signaling pathway genes in survival of patients with HBV-related hepatocellular carcinoma (HBV-HCC), especially with regards to potentially functional SNPs.MethodsWe used multivariate Cox proportional hazards regression to evaluate associations between 2,060 single nucleotide polymorphisms (SNPs) in 20 NF-κB signaling pathway genes and survival of 866 HBV-HCC patients, which were randomly split (1:1) into discovery and validation datasets. Expression quantitative trait loci (eQTL) analysis was conducted to identify associations between survival-associated SNPs and mRNA expression of corresponding genes. Furthermore, online database was used to assess mRNA expression of corresponding genes and survival. Finally, receiver operating characteristic (ROC) curves were used to assess the prediction accuracy of models integrating both clinical and genetic variables on HCC survival.ResultsA total of 6 SNPs in MAP3K14 remained significantly associated with OS of HBV-HCC patients (P<0.05, BFDP<0.8). Further eQTL analysis demonstrated that significant correlations between the rs2074292 (G>A) A allele was associated with higher mRNA expression levels of MAP3K14 (P=0.044) in normal liver tissue, which was associated with worse survival of HBV-HCC patients. In the additive model, after adjusting for age, sex, smoking status, drinking status, AFP level, cirrhosis, embolus and BCLC stage, the combined dataset showed that HBV-HCC patients carrying the rs2074292 AA and GA genotypes (HR=1.71, 95%CI= 1.29-2.27, P=0.000) (HR=1.40, 95%CI=1.10-1.77, P=0.005) have worse OS than GG genotype, respectively. The addition of risk genotypes to the prediction models increased the AUC significantly from 71.15% to 73.11% (P=0.012) and from 72.55% to 74.21% (P=0.010) for 1-year and 3-year OS, respectively.ConclusionOur study indicated that MAP3K14 rs2074292 A allele may be a potential predictor of HBV-HCC survival, likely regulating MAP3K14 mRNA expression.

BackgroundSuper-enhancer (SE) refers to a regulatory element with super transcriptional activity, which can enrich transcription factors and drive gene expression. SE-related genes play an important role in the pathogenesis of malignant tumors, including hepatocellular carcinoma (HCC).MethodsThe SE-related genes were obtained from the human super-enhancer database (SEdb). Data from the transcriptome analysis and related clinical information with HCC were obtained from The Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC) database. The upregulated SE-related genes from TCGA-LIHC were identified by the DESeq2R package. Multivariate Cox regression analysis was used to construct a four-gene prognostic signature. According to the median risk score, HCC patients were divided into high-risk and low-risk group patients.ResultsThe Kaplan-Meier (KM) curve showed that a significantly worse prognosis was found for the high-risk group (P<0.001). In the TCGA-LIHC dataset, the area under the curve (AUC) values were 0.737, 0.662, and 0.667 for the model predicting overall survival (OS) over 1-, 3-, and 5- years, respectively, indicating the good prediction ability of our prediction model. This model’s prognostic value was further validated in the LIRI-JP dataset and HCC samples (n=65). Furthermore, we found that higher infiltration level of M0 macrophages and upregulated of CTLA4 and PD1 in the high-risk group, implying that immunotherapy could be effective for those patients.ConclusionThese results provide further evidence that the unique SE-related gene model could accurately predict the prognosis of HCC.

BackgroundThe current study aims at using the whole genome expression profile chips for systematically investigating the diagnostic and prognostic values of excision repair cross-complementation (ERCC) genes in hepatitis B virus (HBV)-related hepatocellular carcinoma (HCC).Materials and methodsWhole genome expression profile chips were obtained from the GSE14520. The receiver-operating characteristic (ROC) curve, survival analysis, and nomogram were used to investigate the diagnostic and prognostic values of ERCC genes. Investigation of the potential function of ERCC8 was carried out by gene set enrichment analysis (GSEA) and genome-wide coexpression analysis.ResultsROC analysis suggests that six ERCC genes (ERCC1, ERCC2, ERCC3, ERCC4, ERCC5, and ERCC8) were dysregulated and may have potential to distinguish between HBV-related HCC tumor and paracancerous tissues (area under the curve of ROC ranged from 0.623 to 0.744). Survival analysis demonstrated that high ERCC8 expression was associated with a significantly decreased risk of recurrence (adjusted P=0.021; HR=0.643; 95% CI=0.442–0.937) and death (adjusted P=0.049; HR=0.631; 95% CI=0.399–0.998) in HBV-related HCC. Then, we also developed two nomograms for the HBV-related HCC individualized prognosis predictions. GSEA suggests that the high expression of ERCC8 may have involvement in the energy metabolism biological processes. As the genome-wide coexpression analysis and functional assessment of ERCC8 suggest, those coexpressed genes were significantly enriched in multiple biological processes of DNA damage and repair.ConclusionThe present study indicates that six ERCC genes (ERCC1, ERCC2, ERCC3, ERCC4, ERCC5, and ERCC8) were dysregulated between HBV-related HCC tumor and paracancerous tissues and that the mRNA expression of ERCC8 may serve as a potential biomarker for the HBV-related HCC prognosis.