CTNNB1 mutation suppresses infiltration of immune cells in hepatocellular carcinoma through miRNA-mediated regulation of chemokine expression

Nonalcoholic fatty liver disease (NAFLD) is a rising chronic liver disease and comprises a spectrum from simple steatosis to nonalcoholic steatohepatitis (NASH) to end-stage cirrhosis and risk of hepatocellular carcinoma (HCC). The pathogenesis of NAFLD is multifactorial, but inflammation is considered the key element of disease progression. The liver harbors an abundance of resident immune cells, that in concert with recruited immune cells, orchestrate steatohepatitis. While inflammatory processes drive fibrosis and disease progression in NASH, fueling the ground for HCC development, immunity also exerts antitumor activities. Furthermore, immunotherapy is a promising new treatment of HCC, warranting a more detailed understanding of inflammatory mechanisms underlying the progression of NASH and transition to HCC. Novel methodologies such as single-cell sequencing, genetic fate mapping, and intravital microscopy have unraveled complex mechanisms behind immune-mediated liver injury. In this review, we highlight some of the emerging paradigms, including macrophage heterogeneity, contributions of nonclassical immune cells, the role of the adaptive immune system, interorgan crosstalk with adipose tissue and gut microbiota. Furthermore, we summarize recent advances in preclinical and clinical studies aimed at modulating the inflammatory cascade and discuss how these novel therapeutic avenues may help in preventing or combating NAFLD-associated HCC.

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A prognostic model based on seven immune-related genes predicts the overall survival of patients with hepatocellular carcinoma

BioData Mining ◽

10.1186/s13040-021-00261-y ◽

2021 ◽

Vol 14 (1) ◽

Author(s):

Qian Yan ◽

Wenjiang Zheng ◽

Boqing Wang ◽

Baoqian Ye ◽

Huiyan Luo ◽

...

Keyword(s):

Hepatocellular Carcinoma ◽

Overall Survival ◽

High Risk ◽

Risk Score ◽

Immune Cells ◽

Prognostic Model ◽

Risk Groups ◽

Low Risk ◽

Prognostic Performance ◽

Immune Related Genes

Abstract Background Hepatocellular carcinoma (HCC) is a disease with a high incidence and a poor prognosis. Growing amounts of evidence have shown that the immune system plays a critical role in the biological processes of HCC such as progression, recurrence, and metastasis, and some have discussed using it as a weapon against a variety of cancers. However, the impact of immune-related genes (IRGs) on the prognosis of HCC remains unclear. Methods Based on The Cancer Gene Atlas (TCGA) and Immunology Database and Analysis Portal (ImmPort) datasets, we integrated the ribonucleic acid (RNA) sequencing profiles of 424 HCC patients with IRGs to calculate immune-related differentially expressed genes (DEGs). Survival analysis was used to establish a prognostic model of survival- and immune-related DEGs. Based on genomic and clinicopathological data, we constructed a nomogram to predict the prognosis of HCC patients. Gene set enrichment analysis further clarified the signalling pathways of the high-risk and low-risk groups constructed based on the IRGs in HCC. Next, we evaluated the correlation between the risk score and the infiltration of immune cells, and finally, we validated the prognostic performance of this model in the GSE14520 dataset. Results A total of 100 immune-related DEGs were significantly associated with the clinical outcomes of patients with HCC. We performed univariate and multivariate least absolute shrinkage and selection operator (Lasso) regression analyses on these genes to construct a prognostic model of seven IRGs (Fatty Acid Binding Protein 6 (FABP6), Microtubule-Associated Protein Tau (MAPT), Baculoviral IAP Repeat Containing 5 (BIRC5), Plexin-A1 (PLXNA1), Secreted Phosphoprotein 1 (SPP1), Stanniocalcin 2 (STC2) and Chondroitin Sulfate Proteoglycan 5 (CSPG5)), which showed better prognostic performance than the tumour/node/metastasis (TNM) staging system. Moreover, we constructed a regulatory network related to transcription factors (TFs) that further unravelled the regulatory mechanisms of these genes. According to the median value of the risk score, the entire TCGA cohort was divided into high-risk and low-risk groups, and the low-risk group had a better overall survival (OS) rate. To predict the OS rate of HCC, we established a gene- and clinical factor-related nomogram. The receiver operating characteristic (ROC) curve, concordance index (C-index) and calibration curve showed that this model had moderate accuracy. The correlation analysis between the risk score and the infiltration of six common types of immune cells showed that the model could reflect the state of the immune microenvironment in HCC tumours. Conclusion Our IRG prognostic model was shown to have value in the monitoring, treatment, and prognostic assessment of HCC patients and could be used as a survival prediction tool in the near future.

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Identification of Immune-Related Prognostic mRNA and lncRNA in Patients with Hepatocellular Carcinoma

Journal of Oncology ◽

10.1155/2022/5313149 ◽

2022 ◽

Vol 2022 ◽

pp. 1-16

Author(s):

Dan Chen ◽

Xiaoting Li ◽

Hui Li ◽

Kai Wang ◽

Xianghua Tian

Keyword(s):

Hepatocellular Carcinoma ◽

Flow Cytometry ◽

T Cells ◽

Regression Analysis ◽

Survival Analysis ◽

Immune Cells ◽

Cox Regression ◽

Differentially Expressed ◽

Cox Regression Analysis ◽

Immune Related Genes

Background. As the most common hepatic malignancy, hepatocellular carcinoma (HCC) has a high incidence; therefore, in this paper, the immune-related genes were sought as biomarkers in liver cancer. Methods. In this study, a differential expression analysis of lncRNA and mRNA in The Cancer Genome Atlas (TCGA) dataset between the HCC group and the normal control group was performed. Enrichment analysis was used to screen immune-related differentially expressed genes. Cox regression analysis and survival analysis were used to determine prognostic genes of HCC, whose expression was detected by molecular experiments. Finally, important immune cells were identified by immune cell infiltration and detected by flow cytometry. Results. Compared with the normal group, 1613 differentially expressed mRNAs (DEmRs) and 1237 differentially expressed lncRNAs (DElncRs) were found in HCC. Among them, 143 immune-related DEmRs and 39 immune-related DElncRs were screened out. These genes were mainly related to MAPK cascade, PI3K-AKT signaling pathway, and TGF-beta. Through Cox regression analysis and survival analysis, MMP9, SPP1, HAGLR, LINC02202, and RP11-598F7.3 were finally determined as the potential diagnostic biomarkers for HCC. The gene expression was verified by RT-qPCR and western blot. In addition, CD4 + memory resting T cells and CD8 + T cells were identified as protective factors for overall survival of HCC, and they were found highly expressed in HCC through flow cytometry. Conclusion. The study explored the dysregulation mechanism and potential biomarkers of immune-related genes and further identified the influence of immune cells on the prognosis of HCC, providing a theoretical basis for the prognosis prediction and immunotherapy in HCC patients.

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Identification of Biomarkers Related to Immune Cell Infiltration in Hepatocellular Carcinoma Using Gene Co-Expression Network

Pathology & Oncology Research ◽

10.3389/pore.2021.601693 ◽

2021 ◽

Vol 27 ◽

Author(s):

Wanbang Zhou ◽

Yiyang Chen ◽

Ruixing Luo ◽

Zifan Li ◽

Guanwei Jiang ◽

...

Keyword(s):

Hepatocellular Carcinoma ◽

Network Analysis ◽

Tumor Progression ◽

Protein Interactions ◽

Immune Cells ◽

Immune Cell ◽

Immune Microenvironment ◽

Hub Genes ◽

Expression Levels ◽

Immune Infiltration

Hepatocellular carcinoma (HCC) is a common cancer with poor prognosis. Due to the lack of effective biomarkers and its complex immune microenvironment, the effects of current HCC therapies are not ideal. In this study, we used the GSE57957 microarray data from Gene Expression Omnibus database to construct a co-expression network. The weighted gene co-expression network analysis and CIBERSORT algorithm, which quantifies cellular composition of immune cells, were used to identify modules related to immune cells. Four hub genes (EFTUD2, GAPDH, NOP56, PA2G4) were identified by co-expression network and protein-protein interactions network analysis. We examined these genes in TCGA database, and found that the four hub genes were highly expressed in tumor tissues in multiple HCC groups, and the expression levels were significantly correlated with patient survival time, pathological stage and tumor progression. On the other hand, methylation analysis showed that the up-regulation of EFTUD2, GAPDH, NOP56 might be due to the hypomethylation status of their promoters. Next, we investigated the correlations between the expression levels of four hub genes and tumor immune infiltration using Tumor Immune Estimation Resource (TIMER). Gene set variation analysis suggested that the four hub genes were associated with numerous pathways that affect tumor progression or immune microenvironment. Overall, our results showed that the four hub genes were closely related to tumor prognosis, and may serve as targets for treatment and diagnosis of HCC. In addition, the associations between these genes and immune infiltration enhanced our understanding of tumor immune environment and provided new directions for the development of drugs and the monitoring of tumor immune status.

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Identification and Validation of an Immune-Related eRNA Prognostic Signature for Hepatocellular Carcinoma

Frontiers in Genetics ◽

10.3389/fgene.2021.657051 ◽

2021 ◽

Vol 12 ◽

Author(s):

Shenglan Cai ◽

Xingwang Hu ◽

Ruochan Chen ◽

Yiya Zhang

Keyword(s):

Hepatocellular Carcinoma ◽

Immune Cells ◽

Cox Regression ◽

Expression Profiles ◽

Gene Expression Profiles ◽

Roc Curves ◽

The Cancer Genome Atlas ◽

Immune Checkpoints ◽

Immune Genes ◽

Normal Tissues

BackgroundEnhancer RNAs (eRNAs) are intergenic long non-coding RNAs (lncRNAs) that participate in the progression of malignancies by targeting tumor-related genes and immune checkpoints. However, the potential role of eRNAs in hepatocellular carcinoma (HCC) is unclear. In this study, we aimed to construct an immune-related eRNA prognostic model that could be used to prospectively assess the prognosis of patients with HCC.MethodsGene expression profiles of patients with HCC were downloaded from The Cancer Genome Atlas (TCGA). The eRNAs co-expressed from immune genes were identified as immune-related eRNAs. Cox regression analyses were applied in a training cohort to construct an immune-related eRNA signature (IReRS), that was subsequently used to analyze a testing cohort and combination of the two cohorts. Kaplan-Meier and receiver operating characteristic (ROC) curves were used to validate the predictive effect in the three cohorts. Gene Set Enrishment Analysis (GSEA) computation was used to identify an IReRS-related signaling pathway. A web-based cell type identification by estimating relative subsets of RNA transcripts (CIBERSORT) computation was used to evaluate the relationship between the IReRS and infiltrating immune cells.ResultsA total of sixty-four immune-related eRNAs (IReRNAs) was identified in HCC, and 14 IReRNAs were associated with overall survival (OS). Five IReRNAs were used for constructing an immune-related eRNA signature (IReRS), which was shown to correlate with poor survival and to be an independent prognostic biomarker for HCC. The GSEA results showed that the IReRS was correlated to cancer-related and immune-related pathways. Moreover, we found that IReRS was correlated to infiltrating immune cells, including CD8+ T cells and M0 macrophages. Finally, differential expressions of the five risk IReRNAs in tumor tissues vs. adjacent normal tissues and their prognostic values were verified, in which the AL445524.1 may function as an oncogene that affects prognosis partly by regulating CD4-CLTA4 related genes.ConclusionOur results suggest that the IReRS could serve as a biomarker for predicting prognosis in patients with HCC. Additionally, it may be correlated to the tumor immune microenvironment and could also be used as a biomarker in immunotherapy for HCC.

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Roles of Immune Cells in the Concurrence of Echinococcus Granulosus Infection and Hepatocellular Carcinoma

10.21203/rs.3.rs-98853/v1 ◽

2020 ◽

Author(s):

Aimaiti Yasen ◽

Bo Ran ◽

Maolin Wang ◽

Guodong Lv ◽

Renyong Lin ◽

...

Keyword(s):

Hepatocellular Carcinoma ◽

T Cell ◽

Immune Responses ◽

Nk Cells ◽

Echinococcus Granulosus ◽

Immune Cells ◽

Hepg2 Cells ◽

Control Group ◽

Cell Markers ◽

Hepg2 Cell Lines

Abstract Background/aims: Immune cells are pivotal players in the immune responses against both parasitic infection and malignancies. Substantial evidence demonstrated that there may exist possible relationship between Echinococcus granulosus (E.granulosus) infection and hepatocellular carcinoma (HCC) development. Thus, this study aimed to observe crucial roles of immune cells in the formation of subcutaneous lesions after transplanting HepG2 cell lines with or without E.granulosus protoscoleces (PSCs).Methods: HepG2 cell lines were subcutaneously injected into nude mice in the control group. In the co-transplantation group, HepG2 cells were subcutaneously co-injected with high dosage of E.granulosus PSCs. From the 25th day of transplantation, volume of subcutaneous lesions was measured every four days, which were removed at the 37th day for further studies. Basic pathological and functional changes were observed. Moreover, expression of Ki67, Bal-2, Caspase3, α-smooth muscle actin (α-SMA), T cell markers (CD3, CD4, CD8), PD1/PD-L1, nature killer (NK) cell markers (CD16, CD56) were further detected by immunohistochemistry.Results: Subcutaneous lesions were gradually increased in volume and there occurred pathologically heterogeneous tumor cells, which were more significant in the co-transplantation group. Compared to the control group, expression of proliferation markers Ki67 and Bcl-2 was at higher levels in the co-transplantation group. Reversely, apoptotic marker Caspase3 was highly detected in the control group, suggesting promoting effects of E.granulosus PSCs on HCC development. Interestingly, subcutaneous lesions of the co-transplantation group were more functional in synthesizing and storing glycogen. Collagen and α-SMA+ cells were also at higher levels in the co-transplantation group than those in the control group. Most importantly, co-transplantation of HepG2 cells with E.granulosus PSCs led to significant increase in the expression of T cell markers (CD3, CD4 and CD8), immune inhibitory checkpoint PD1/PD-L1 and NK cells markers (CD16 and CD56). Conclusions: E.granulosus may have promoting effects on HCC development, which was closely associated with the immune responses of T cells and NK cells.

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Mining TCGA Database for Tumor Microenvironment-Related Genes of Prognostic Value in Hepatocellular Carcinoma

BioMed Research International ◽

10.1155/2019/2408348 ◽

2019 ◽

Vol 2019 ◽

pp. 1-12 ◽

Cited By ~ 7

Author(s):

Zhenfeng Deng ◽

Jilong Wang ◽

Banghao Xu ◽

Zongrui Jin ◽

Guolin Wu ◽

...

Keyword(s):

Hepatocellular Carcinoma ◽

Tumor Microenvironment ◽

Immune Cells ◽

Malignant Tumors ◽

Public Access ◽

The Cancer Genome Atlas ◽

Functional Enrichment ◽

Protein Protein Interaction ◽

Potential Association ◽

Poor Outcomes

Hepatocellular carcinoma (HCC) is one of the most common and lethal malignancies. Recent studies reveal that tumor microenvironment (TME) components significantly affect HCC growth and progression, particularly the infiltrating stromal and immune cells. Thus, mining of TME-related biomarkers is crucial to improve the survival of patients with HCC. Public access of The Cancer Genome Atlas (TCGA) database allows convenient performance of gene expression-based analysis of big data, which contributes to the exploration of potential association between genes and prognosis of a variety of malignancies, including HCC. The “Estimation of STromal and Immune cells in MAlignant Tumors using Expression data” algorithm renders the quantification of the stromal and immune components in TME possible by calculating the stromal and immune scores. Differentially expressed genes (DEGs) were screened by dividing the HCC cohort of TCGA database into high- and low-score groups according to stromal and immune scores. Further analyses of functional enrichment and protein-protein interaction networks show that the DEGs are mainly involved in immune response, cell adhesion, and extracellular matrix. Finally, seven DEGs have significant association with HCC poor outcomes. These genes contain FABP3, GALNT5, GPR84, ITGB6, MYEOV, PLEKHS1, and STRA6 and may be candidate biomarkers for HCC prognosis.

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