Study on the gene signature related to immune microenvironment on viral and nonviral infections of hepatocellular carcinoma.

The pathogenesis of hepatocellular carcinoma (HCC) can be divided into viral infection (VIR) and nonviral (NVIR) infection. Two types of HCC performed different tumor immune microenvironment (TIME) which directly affected prognosis of HCC. This study aimed to identify an effective 2 types of HCC prognostic gene signature that related to immune TIME.The differential expression genes (DEGs) were analyzed by Limma R package from the Cancer Genome Atlas. Immune related genes getting from IMMport database were matched to DEGs for testing prognosis. Prognostic index (PI) consisted of prognostic immune related genes was calculated in different types of HCC by COX regression and the correlation with the abundance of immune infiltrates, including 6 type cells, via gene modules. Tumor immune estimation resource database was applied to analyze TIME. Finally, the correlations between PI of DEGs and TIICs were analyzed by the Spearman method.Results showed that PI consisted of 11 messenger RNAs in VIR and 12 messenger RNAs in NVIR groups. The PI related to HCC prognosis has different correlations with immune infiltrating cells in VIR and NVIR groups. The PI value of DEGs has significant correlations with neutrophils (R = 0.22, P-value = .029) and dendritic (R = 0.21, P-value = .036) infiltration levels in VIR group. However, in NVIR group, the result showed there were no significant correlations between PI and other 5 type cell infiltration levels (P-value > .05).The 11-gene signature in VIR and 12-gene signature in NVIR group selected based on data from the Cancer Genome Atlas database had a different correlation with immune infiltrating cells of HCC patients.

Qian H ，Song S ，Tian Y ，Qi L ，Gao H ，Yuan L ... -  《-》

Study on the anti-tumor mechanism related to immune microenvironment of Bombyx Batryticatus on viral and non-viral infections of hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is a malignant primary liver cancer with poor prognosis. Most previous studies on anti-HCC effects of traditional Chinese medicines (TCM) have focused on the mechanism of direct action and few researchers considered that TCM can inhibit tumor progression and improve prognosis of HCC patients through regulating tumor microenvironment (TME). In this study, network pharmacology combined bioinformatics methods were employed to analysis mechanism of Bombyx batryticatus (B. batryticatus, one of the most frequently used traditional Chinese animal medicines, has been used in some Asian countries for centuries as an anticancer agent, anti-inflammatory agent, and antioxidant.) in regulating TME of HCC. The results showed that 24 core targets and 2 compounds were identified from overlapping between differential expression genes related to HCC in the cancer genome atlas (TCGA) database and targets of B. batryticatus in TCMSP database. For further analyzing the role of TME heterogeneity of HCC on anti-HCC mechanism of B. batryticatus, the correlation of core targets related with overall survival of HCC with TME cells in hepatitis C or hepatitis B virus-associated hepatocellular carcinoma (VIR) and non-hepatitis C or hepatitis B virus-associated hepatocellular carcinoma (NVIR) were calculated, respectively. The results showed that AKR1C3, SPP1 were significantly related with macrophages in VIR and other targets including NR1I2, CYP1A2 and CYP3A4 were significantly associated with macrophages in NVIR; the target protein AKR1C3 was significantly negative correlated with macrophages M1 in VIR (cor=-0.35, P-value<0.001) and the correlation between AKR1C3 and macrophages M1 was poor in NVIR group (cor = 0.064, P-value = 0.36). Additionally, survival curve of AKR1C3 showed that poor prognosis in VIR group can be related to high level of AKR1C3 (HR = 2.32, 95 % CI: 1.18-4.56, P-value = 0.012), and no signified gene can be found in NVIR group (P-value>0.05). In conclusion, the molecular mechanism of anti-HCC of B. batryticatus can be related to the tumor microenvironment to some extent. B. batryticatus may exert its anti-cancer effects and improve prognosis of patients by regulating macrophages M1 in VIR and NVIR through acting on different targets.

Yuan L ，Bing Z ，Han J ，An X ，Liu X ，Li R ，Wang C ，Sun X ，Yang L ，Yang K ... -  《-》

Identification of Prognostic Genes in the Tumor Microenvironment of Hepatocellular Carcinoma.

Background: Hepatocellular carcinoma (HCC) is one of the most common malignant tumors in the world. The efficacy of immunotherapy usually depends on the interaction of immunomodulation in the tumor microenvironment (TME). This study aimed to explore the potential stromal-immune score-based prognostic genes related to immunotherapy in HCC through bioinformatics analysis. Methods: ESTIMATE algorithm was applied to calculate the immune/stromal/Estimate scores and tumor purity of HCC using the Cancer Genome Atlas (TCGA) transcriptome data. Functional enrichment analysis of differentially expressed genes (DEGs) was analyzed by the Database for Annotation, Visualization, and Integrated Discovery database (DAVID). Univariate and multivariate Cox regression analysis and least absolute shrinkage and selection operator (LASSO) regression analysis were performed for prognostic gene screening. The expression and prognostic value of these genes were further verified by KM-plotter database and the Human Protein Atlas (HPA) database. The correlation of the selected genes and the immune cell infiltration were analyzed by single sample gene set enrichment analysis (ssGSEA) algorithm and Tumor Immune Estimation Resource (TIMER). Results: Data analysis revealed that higher immune/stromal/Estimate scores were significantly associated with better survival benefits in HCC within 7 years, while the tumor purity showed a reverse trend. DEGs based on both immune and stromal scores primarily affected the cytokine-cytokine receptor interaction signaling pathway. Among the DEGs, three genes (CASKIN1, EMR3, and GBP5) were found most significantly associated with survival. Moreover, the expression levels of CASKIN1, EMR3, and GBP5 genes were significantly correlated with immune/stromal/Estimate scores or tumor purity and multiple immune cell infiltration. Among them, GBP5 genes were highly related to immune infiltration. Conclusion: This study identified three key genes which were related to the TME and had prognostic significance in HCC, which may be promising markers for predicting immunotherapy outcomes.

Xiang S ，Li J ，Shen J ，Zhao Y ，Wu X ，Li M ，Yang X ，Kaboli PJ ，Du F ，Zheng Y ，Wen Q ，Cho CH ，Yi T ，Xiao Z ... -  《Frontiers in Immunology》

Immune- and metabolism-related gene signature analysis uncovers the prognostic and immune microenvironments of hepatocellular carcinoma.

Metabolic reprogramming is an emerging hallmark that influences the tumour microenvironment (TME) by regulating the behavior of cancer cells and immune cells. The relationship between metabolism and immunity remains elusive. The purpose of this study was to explore the predictive value of immune- and metabolism-related genes in hepatocellular carcinoma (HCC) and their intricate interplay with TME. We established the immune- and metabolism-related signature (IMRPS) based on the LIHC cohort from The Cancer Genome Atlas (TCGA) dataset. Kaplan-Meier analysis, receiver operating characteristic (ROC) curve analysis and Cox regression analysis confirmed the prognostic value of IMRPS. We investigated differences in immune cell infiltration, clinical features, and therapeutic response between risk groups. The quantitative real-time PCR (qPCR) was used to confirm the expression of signature genes. Immunohistochemical staining was performed to evaluate immune infiltration features in HCC tissue samples. We conducted cell experiments including gene knockout, cell counting kit-8 (CCK-8), and flow cytometry to explore the role of the IMRPS key gene UCK2 in HCC. RNA-seq was used to further investigate the potential underlying mechanism involved. The IMRPS, composed of four genes, SMS, UCK2, PFKFB4 and MAPT, exhibited significant correlations with survival, immune cell infiltration, clinical features, immune checkpoints and therapeutic response. The IMRPS was shown to be an excellent predictor of HCC prognosis. It could stratify patients appropriately and characterize the TME accurately. The high-risk HCC group exhibited an immunosuppressive microenvironment with abundant M2-like macrophage infiltration, which was confirmed by the immunohistochemistry results. The results of qPCR revealed that the expression of signature genes in 20 HCC tissues was significantly greater than that in adjacent normal tissues. After the key gene UCK2 was knocked out, the proliferation of the Huh7 cell line was significantly inhibited, and monocyte-derived macrophages polarized towards an M1-like phenotype in the coculture system. RNA-seq and GSEA suggested that the phenotypes were closely related to the negative regulation of growth and regulation of macrophage chemotaxis. This study established a new IMRS for the accurate prediction of patient prognosis and the TME, which is also helpful for identifying new targets for the treatment of HCC.

Gu Y ，Ma E ，Jiang S ，Shan Z ，Xia G ，Ma R ，Fu J ，Wang Z ... -  《-》

Construction of a risk score prognosis model based on hepatocellular carcinoma microenvironment.

Hepatocellular carcinoma (HCC) is a common cancer with a poor prognosis. Previous studies revealed that the tumor microenvironment (TME) plays an important role in HCC progression, recurrence, and metastasis, leading to poor prognosis. However, the effects of genes involved in TME on the prognosis of HCC patients remain unclear. Here, we investigated the HCC microenvironment to identify prognostic genes for HCC. To identify a robust gene signature associated with the HCC microenvironment to improve prognosis prediction of HCC. We computed the immune/stromal scores of HCC patients obtained from The Cancer Genome Atlas based on the ESTIMATE algorithm. Additionally, a risk score model was established based on Differentially Expressed Genes (DEGs) between high- and low-immune/stromal score patients. The risk score model consisting of eight genes was constructed and validated in the HCC patients. The patients were divided into high- or low-risk groups. The genes (Disabled homolog 2, Musculin, C-X-C motif chemokine ligand 8, Galectin 3, B-cell-activating transcription factor, Killer cell lectin like receptor B1, Endoglin and adenomatosis polyposis coli tumor suppressor) involved in our risk score model were considered to be potential immunotherapy targets, and they may provide better performance in combination. Functional enrichment analysis showed that the immune response and T cell receptor signaling pathway represented the major function and pathway, respectively, related to the immune-related genes in the DEGs between high- and low-risk groups. The receiver operating characteristic (ROC) curve analysis confirmed the good potency of the risk score prognostic model. Moreover, we validated the risk score model using the International Cancer Genome Consortium and the Gene Expression Omnibus database. A nomogram was established to predict the overall survival of HCC patients. The risk score model and the nomogram will benefit HCC patients through personalized immunotherapy.

Zhang FP ，Huang YP ，Luo WX ，Deng WY ，Liu CQ ，Xu LB ，Liu C ... -  《-》