Hepatocellular carcinoma (HCC) is a malignant tumor and is associated with necroinflammation driven by various immune cells, such as dendritic cells, macrophages and natural killer cells. Innate immune cells can directly affect HCC or regulate the T-cell responses that mediate HCC. In addition, innate immune cells and T cells are not isolated, which means the interaction between them is important in the HCC microenvironment. Considering the current unsatisfactory efficacy of immunotherapy in patients with HCC, understanding the relationship between innate immune cells and T cells is necessary. In the present review the roles and clinical value of innate immune cells that have been widely reported to be involved in HCC, including dendritic cells, macrophages (including kupffer cells), neutrophils, eosinophils, basophils and innate lymphoid cells and the crosstalk between the innate and adaptive immune responses in the antitumor process have been discussed. The present review will facilitate researchers in understanding the importance of innate immune cells in HCC and lead to innovative immunotherapy approaches for the treatment of HCC. Contents 1. Introduction 2. Role of innate immune cells in HCC 3. Innate immune cell regulation of the T-cell response in HCC 4. Clinical value of innate immune cells in HCC 5. Conclusion GUO-QING HONG 1 , DONG CAI 2 , JIAN-PING GONG 2 and XING LAI 1

Long-term survivals of patients with hepatocellular carcinoma (HCC) remain unfavorable, which is largely attributed to active carcinogenesis. Growing studies have suggested that the reliable gene signature could act as an independent prognosis factor for HCC patients. We tried to screen the survival-related genes and develop a prognostic prediction model for HCC patients based on the expression profiles of the critical survival-related genes. In this study, we analyzed TCGA datasets and identified 280 genes with differential expressions (125 increased genes and 155 reduced genes). We analyzed the prognosis value of the top 10 dysregulated genes in HCC patients and identified three critical genes, including FCN3, CDC20, and E2F1, which were confirmed to be associated with long-term survival in both TCGA and ICGC datasets. The results of the LASSO model screened CDC20 and FCN3 for the development of the prognostic model. The CDC20 expression was distinctly increased in HCC specimens, while the FCN3 expression was distinctly decreased in HCC. At a suitable cutoff, patients were divided into low-risk and high-risk groups. Survival assays revealed that patients in high-risk groups exhibited a shorter overall survival than those in low-risk groups. Finally, we examine the relationships between risk score and immune infiltration abundance in HCC and observed that risk score was positively correlated with infiltration degree of B cells, T cell CD4+ cells, neutrophil, macrophage, and myeloid dendritic cells. Overall, we identified three critical survival-related genes and used CDC20 and FCN3 to develop a novel model for predicting outcomes and immune landscapes for patients with HCC. The above three genes also have a high potential for targeted cancer therapy of patients with HCC.

Hepatocellular carcinoma (HCC) with high heterogeneity is one of the most frequent malignant tumors. However, there were no studies to create a clinical stage-related gene signature for HCC patients. Differentially expressed genes (DEGs) associated with clinical stage of HCC were analyzed based on TCGA datasets. Functional enrichment analysis was carried out by the use of stage-related DEGs. Then, the least absolute shrinkage and selection operator (LASSO) regression and univariate Cox regression were performed to reduce the overfit and the number of genes for further analysis. Next, survival and ROC assays were carried out to demonstrate the model using TCGA. Functional analysis and immune microenvironment analysis related to stage-related DEGs were performed. Reverse transcriptase polymerase chain reaction (RT-PCR) and Cell Counting Kit-8 (CCK-8) assays were applied to examine the expression and function of PNCK in HCC. In this research, there were 21 DEGs between HCC specimens with stage (I-II) and HCC specimens with stage (III-IV), including 20 increased genes and 1 decreased genes. A novel seven-gene signature (including PITX2, PNCK, GLIS1, SCNN1G, MMP1, ZNF488, and SHISA9) was created for the prediction of outcomes of HCC patients. The ROC curves confirmed the prognostic value of the new model. Cox assays demonstrated that the seven-gene signature can independently forecast overall survival. The immune analysis revealed that patients with low risk score exhibited more immune activities. Moreover, we confirmed that PNCK expressions were distinctly increased in HCC, and its silence suppressed the proliferation of HCC cells. Overall, our research offered a robust and reliable gene signature which displayed an important value in the prediction of overall survival of HCC patients and might deliver more effective personalized therapies.

Hepatocellular carcinoma (HCC) is a malignancy with one of the worst prognoses. Long noncoding RNAs (lncRNAs) may be important in cancer development and may serve as new biomarkers for the diagnosis and treatment of various tumors, according to mounting research. The purpose of this study was to investigate the expression of INKA2-AS1 and clinical importance in HCC patients. The TCGA database was used to obtain the human tumor samples, while the TCGA and GTEx databases were used to gather the human normal samples. We screened differentially expressed genes (DEGs) between HCC and nontumor tissues. Investigations were made into the statistical significance and clinical significance of INKA2-AS1 expression. A single-sample gene set enrichment analysis (ssGSEA) was used to examine potential relationships between immune cell infiltration and INKA2-AS1 expression. In this investigation, we found that HCC specimens had considerably greater levels of INKA2-AS1 expression than nontumor specimens. When utilizing the TCGA datasets and the GTEx database, high INKA2-AS1 expression showed an AUC value for HCC of 0.817 (95% confidence interval: 0.779 to 0.855). Pan-cancer assays revealed that numerous tumor types had dysregulated levels of INKA2-AS1. Gender, histologic grade, and pathologic stage were all substantially correlated with high INKA2-AS1 expression. A survival study indicated that HCC patients with high INKA2-AS1 expression have shorter OS, DSS, and PFI than those with low INKA2-AS1 expression. Multivariate analysis indicated that INKA2-AS1 expression was an independent prognostic factor for OS of patients with HCC. According to immune analysis, the expression of INKA2-AS1 was favorably correlated with T helper cells, Th2 cells, macrophages, TFH, and NK CD56bright cells and negatively correlated with Th17 cells, pDC, cytotoxic cells, DC, Treg, Tgd, and Tcm. The results of this study collectively suggest that INKA2-AS1 has the potential to be a novel biomarker for predicting the prognosis of HCC patients as well as a significant immune response regulator in HCC.