scholarly journals Characterization of the Tumor Immune Microenvironment Identifies M0 Macrophage-Enriched Cluster as a Poor Prognostic Factor in Hepatocellular Carcinoma

2020 ◽  
pp. 1002-1013
Author(s):  
Mark Farha ◽  
Neil K. Jairath ◽  
Theodore S. Lawrence ◽  
Issam El Naqa
Keyword(s):  
Hepatocellular Carcinoma ◽  
Poor Prognosis ◽  
Prognostic Value ◽  
Immune Cell ◽  
Multivariable Analysis ◽  
Immune Microenvironment ◽  
Poor Prognostic Factor ◽  
Kaplan Meier ◽  
Programmed Death ◽  
Tumor Immune Microenvironment

PURPOSE Hepatocellular carcinoma (HCC) is characterized by a poor prognosis and a high recurrence rate. The tumor immune microenvironment in HCC has been characterized as shifted toward immunosuppression. We conducted a genomic data-driven classification of immune microenvironment HCC subtypes. In addition, we demonstrated their prognostic value and suggested a potential therapeutic targeting strategy. METHODS RNA sequencing data from The Cancer Genome Atlas–Liver Hepatocellular Carcinoma was used (n = 366). Abundance of immune cells was imputed using CIBERSORT and visualized using unsupervised hierarchic clustering. Overall survival (OS) was analyzed using Kaplan-Meier estimates and Cox regression. Differential expression and gene set enrichment analyses were conducted on immune clusters with poor OS and high programmed death-1 (PD-1)/programmed death-ligand 1 (PD-L1) coexpression. A scoring metric combining differentially expressed genes and immune cell content was created, and its prognostic value and immune checkpoint blockade response prediction was evaluated. RESULTS Two clusters were characterized by macrophage enrichment, with distinct M0Hi and M2Hi subtypes. M2Hi ( P = .038) and M0Hi ( P = .018) were independently prognostic for OS on multivariable analysis. Kaplan-Meier estimates demonstrated that patients in M0Hi and M2Hi treated with sorafenib had decreased OS ( P = .041), and angiogenesis hallmark genes were enriched in the M0Hi group. CXCL6 and POSTN were overexpressed in both the M0Hi and the PD-1Hi/PD-L1Hi groups. A score consisting of CXCL6 and POSTN expression and absolute M0 macrophage content was discriminatory for OS (intermediate: hazard ratio [HR], 1.59; P ≤ .001; unfavorable: HR, 2.08; P = .04). CONCLUSION Distinct immune cell clusters with macrophage predominance characterize an aggressive HCC phenotype, defined molecularly by angiogenic gene enrichment and clinically by poor prognosis and sorafenib response. This novel immunogenomic signature may aid in stratification of unresectable patients to receive checkpoint inhibitor and antiangiogenic therapy combinations.

scholarly journals TANK-Binding Kinase 1 (TBK1) Serves as a Potential Target for Hepatocellular Carcinoma by Enhancing Tumor Immune Infiltration

2021 ◽  
Vol 12 ◽  
Author(s):  
Yuchuan Jiang ◽  
Siliang Chen ◽  
Qiang Li ◽  
Junjie Liang ◽  
Weida Lin ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Overall Survival ◽  
T Cells ◽  
Cd8 T Cells ◽  
Prognostic Value ◽  
Immune Cell ◽  
Poor Prognostic Factor ◽  
Immune Infiltration ◽  
Kaplan Meier ◽  
Kaplan Meier Plotter

BackgroundNumerous cancer types present the aberrant TANK-binding kinase 1 (TBK1) expression, which plays an important role in driving inflammation and innate immunity. However, the prognostic role of TBK1 and its relationship with immune cell infiltration in hepatocellular carcinoma (HCC) remain unclear.MethodsThe expression and prognostic value of TBK1 was analyzed by Tumor Immune Estimation Resource (TIMER), Kaplan-Meier plotter and Gene Expression Profiling Interactive Analysis (GEPIA), Clinical Proteomic Tumor Analysis Consortium (CPTAC) and further confirmed in the present cohort of patients with HCC. The association between TBK1 and HCC immune infiltrates, and its potential mechanism were investigated via analyses of the Tumor Immune Estimation Resource, tumor-immune system interactions database (TISIDB), CIBERSORT, STRING, and Metascape. The effect of TBK1 on immune infiltrates and the therapeutic value of targeting TBK1 were further investigated in a HCC mouse model by treatment with a TBK1 antagonist.ResultsThe level of TBK1 expression in HCC was higher than that measured in normal tissues, and associated with poorer overall survival (GEPIA: hazard ratio [HR]=1.80, P=0.038; Kaplan–Meier plotter: HR=1.87, P<0.001; CPTAC: HR=2.23, P=0.007; Our cohort: HR=2.92, P=0.002). In addition, high TBK1 expression was found in HCC with advanced TNM stage and identified as an independent poor prognostic factor for overall survival among patients with HCC. In terms of immune infiltration, tumor tissues from HCC patients with high TBK1 expression had a low proportion of CD8+ T cells, and TBK1 expression did not show prognostic value in HCC patients with enriched CD8+ T cells. Furthermore, TBK1 expression was positively correlated with the markers of T cell exhaustion and immunosuppressive cells in the HCC microenvironment. Mechanistically, the promotion of HCC immunosuppression by TBK1 was involved in the regulation of inflammatory cytokines. In vivo experiments revealed that treatment with a TBK1 antagonist delayed HCC growth by increasing the number of tumor-infiltrating CD8+ T cells.ConclusionsThe up-regulated expression of TBK1 may be useful in predicting poor prognosis of patients with HCC. In addition, TBK1, which promotes the HCC immunosuppressive microenvironment, may be a potential immunotherapeutic target for patients with HCC.

scholarly journals The Expression of LIMK1 is Related to the Poor Prognosis and Immune Function of Hepatocellular Carcinoma

2021 ◽  
Author(s):  
Yisheng Peng ◽  
Jun Fan ◽  
Gang Zhu ◽  
Shunde Tan ◽  
Jianfei Chen ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Immune Function ◽  
Poor Prognosis ◽  
Immune Cell ◽  
Tnm Staging ◽  
Immune Infiltration ◽  
Protein Protein Interaction ◽  
Normal Tissues ◽  
The Poor ◽  
Kaplan Meier

Abstract Background: According to reports, LIMK1 may have the effect of promoting tumor progression. However, the effect of the expression of LIMK1 on the healing of patients with hepatocellular carcinoma and its effect on the immune function are still not clear. Therefore, we analyzed the effect of LIMK1 on the healing of patients with hepatocellular carcinoma and its correlation with immunity through bioinformatics analysis.Methods: Download the transcriptional expression profile of LIMK1 in hepatocellular carcinoma tissues and normal tissues in TCGA, and study its expression in hepatocellular carcinoma. Study the expression of LIMK1 in hepatocellular carcinoma through CPTAC and HPA database. The Kaplan-Meier method was used to evaluate the effect of LIMK1 expression on the survival of patients with hepatocellular carcinoma. Use the STRING database to construct a protein-protein interaction (PPI) network. Use the "ClusterProfiler" package for feature-rich analysis. Use TISIDB database and Xiantao platform to study the relationship between LIMK1 mRNA expression and immune infiltration.Results: The expression of LIMK1 in hepatocellular carcinoma tissues was significantly up-regulated. Increased expression of LIMK1 mRNA is related to high TNM staging. In the ROC curve, when the cut-off level is 1.813, the sensitivity and specificity of LIMK1 to distinguish hepatocellular carcinoma from adjacent controls are 80.7% and 86%, respectively.The Kaplan-Meier curve shows that the higher the expression of LIMK1, the worse the survival of patients with hepatocellular carcinoma (42.2 months vs. 70 months, P = 0.001). Correlation analysis studies have shown that the expression of LIMK1 mRNA in hepatocellular carcinoma is related to immune cell infiltration.Conclusion: Up-regulation of LIMK1 may affect the survival rate and immune invasion of hepatocellular carcinoma. Studies have shown that LIMK1 may be related to the poor prognosis of hepatocellular carcinoma, and has a certain relationship with the immune infiltration of hepatocellular carcinoma.

scholarly journals Identification of Prognostic Glycolysis-Related lncRNA Signature in Tumor Immune Microenvironment of Hepatocellular Carcinoma

2021 ◽  
Vol 8 ◽  
Author(s):  
Yang Bai ◽  
Haiping Lin ◽  
Jiaqi Chen ◽  
Yulian Wu ◽  
Shi’an Yu
Keyword(s):  
Hepatocellular Carcinoma ◽  
High Risk ◽  
Risk Score ◽  
Prognostic Value ◽  
Enrichment Analysis ◽  
Immune Microenvironment ◽  
Prognostic Accuracy ◽  
Tumor Immune Microenvironment ◽  
Cox Analysis

Purpose: The purpose of this study was to construct a novel risk scoring model with prognostic value that could elucidate tumor immune microenvironment of hepatocellular carcinoma (HCC).Samples and methods: Data were obtained through The Cancer Genome Atlas (TCGA) database. Univariate Cox analysis, least absolute shrinkage and selection operator (LASSO) analysis, and multivariate Cox analysis were carried out to screen for glycolysis-related long noncoding RNAs (lncRNAs) that could provide prognostic value. Finally, we established a risk score model to describe the characteristics of the model and verify its prediction accuracy. The receiver operating characteristic (ROC) curves of 1, 3, and 5 years of overall survival (OS) were depicted with risk score and some clinical features. ESTIMATE algorithm, single-sample gene set enrichment analysis (ssGSEA), and CIBERSORT analysis were employed to reveal the characteristics of tumor immune microenvironment in HCC. The nomogram was drawn by screening indicators with high prognostic accuracy. The correlation of risk signature with immune infiltration and immune checkpoint blockade (ICB) therapy was analyzed. After enrichment of related genes, active behaviors and pathways in high-risk groups were identified and lncRNAs related to poor prognosis were validated in vitro. Finally, the impact of MIR4435-2HG upon ICB treatment was uncovered.Results: After screening through multiple steps, four glycolysis-related lncRNAs were obtained. The risk score constructed with the four lncRNAs was found to significantly correlate with prognosis of samples. From the ROC curve of samples with 1, 3, and 5 years of OS, two indicators were identified with high prognostic accuracy and were used to draw a nomogram. Besides, the risk score significantly correlated with immune score, immune-related signature, infiltrating immune cells (i.e. B cells, etc.), and ICB key molecules (i.e. CTLA4,etc.). Gene enrichment analysis indicated that multiple biological behaviors and pathways were active in the high-risk group. In vitro validation results showed that MIR4435-2HG was highly expressed in the two cell lines, which had a significant impact on the OS of samples. Finally, we corroborated that MIR4435-2HG had intimate relationship with ICB therapy in hepatocellular carcinoma.Conclusion: We elucidated the crucial role of risk signature in immune cell infiltration and immunotherapy, which might contribute to clinical strategies and clinical outcome prediction of HCC.

scholarly journals Identification of Epithelial Mesenchymal Transition-Related lncRNAs Associated with Prognosis and Tumor Immune Microenvironment of Hepatocellular Carcinoma

2022 ◽  
Vol 2022 ◽  
pp. 1-17
Author(s):  
Yongjie Zhou ◽  
Liangwen Wang ◽  
Wen Zhang ◽  
Jingqin Ma ◽  
Zihan Zhang ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Clustering Analysis ◽  
Roc Curves ◽  
Unsupervised Clustering ◽  
Gene Set Enrichment Analysis ◽  
Prognostic Models ◽  
Immune Microenvironment ◽  
Mesenchymal Transition ◽  
Kaplan Meier ◽  
Tumor Immune Microenvironment

Purpose. The long noncoding RNAs (lncRNAs) play the important role in tumor occurrence and progression, and the epithelial to mesenchymal transition (EMT) is the critical process for tumor migration. However, the role of EMT-related lncRNA in hepatocellular carcinoma (HCC) has not been elucidated. Methods. In this study, we selected the EMT-related lncRNAs in HCC by using data from The Cancer Genome Atlas database (TCGA). Two prognostic models of the overall survival (OS) and relapse-free survival (RFS) were constructed and validated through Cox regression model, Kaplan-Meier analysis, and the receiver-operating characteristic (ROC) curves. The unsupervised clustering analysis was utilized to investigate the association between EMT-lncRNAs with tumor immune microenvironment. ESTIMATE algorithm and gene set enrichment analysis (GSEA) were used to estimate tumor microenvironment and associated KEGG pathways. Results. Two EMT-related lncRNA prognostic models of OS and RFS were constructed. Kaplan-Meier curves showed the dismal prognosis of OS and RFS in the group with high-risk score. The ROC curves and AUC values in two prognostic models indicated the discriminative value in the training set and validation set. Patients with HCC were clustered into two subgroups according the unsupervised clustering analysis. Lnc-CCNY-1 was selected as the key lncRNA. GSVA analysis showed that lnc-CCNY-1 was negatively associated with peroxisome proliferator-activated receptor (PPAR) signaling pathway and positively correlated with CELL cycle pathway. Conclusion. Two EMT-related lncRNA prognostic models of OS and RFS were constructed to discriminate patients and predict prognosis of HCC. EMT-related lncRNAs may play a role on prognosis of HCC by influencing the immune microenvironment. Lnc-CCNY-1 was selected as the key EMT-related lncRNA for further exploration.

scholarly journals Integrative Analysis of Neuregulin Family Members-Related Tumor Microenvironment for Predicting the Prognosis in Gliomas

2021 ◽  
Vol 12 ◽  
Author(s):  
Wei-jiang Zhao ◽  
Guan-yong Ou ◽  
Wen-wen Lin
Keyword(s):  
Prognostic Value ◽  
Immune Cell ◽  
Characteristic Curve ◽  
Family Members ◽  
The Cancer Genome Atlas ◽  
Lower Grade ◽  
Sequencing Data ◽  
Immune Microenvironment ◽  
Gene Set ◽  
Tumor Immune Microenvironment

Gliomas, including brain lower grade glioma (LGG) and glioblastoma multiforme (GBM), are the most common primary brain tumors in the central nervous system. Neuregulin (NRG) family proteins belong to the epidermal growth factor (EGF) family of extracellular ligands and they play an essential role in both the central and peripheral nervous systems. However, roles of NRGs in gliomas, especially their effects on prognosis, still remain to be elucidated. In this study, we obtained raw counts of RNA-sequencing data and corresponding clinical information from 510 LGG and 153 GBM samples from The Cancer Genome Atlas (TCGA) database. We analyzed the association of NRG1-4 expression levels with tumor immune microenvironment in LGG and GBM. GSVA (Gene Set Variation Analysis) was performed to determine the prognostic difference of NRGs gene set between LGG and GBM. ROC (receiver operating characteristic) curve and the nomogram model were constructed to estimate the prognostic value of NRGs in LGG and GBM. The results demonstrated that NRG1-4 were differentially expressed in LGG and GBM in comparison to normal tissue. Immune score analysis revealed that NRG1-4 were significantly related to the tumor immune microenvironment and remarkably correlated with immune cell infiltration. The investigation of roles of m6A (N6-methyladenosine, m6A)-related genes in gliomas revealed that NRGs were prominently involved in m6A RNA modification. GSVA score showed that NRG family members are more associated with prognosis in LGG compared with GBM. Prognostic analysis showed that NRG3 and NRG1 can serve as potential independent biomarkers in LGG and GBM, respectively. Moreover, GDSC drug sensitivity analysis revealed that NRG1 was more correlated with drug response compared with other NRG subtypes. Based on these public databases, we preliminarily identified the relationship between NRG family members and tumor immune microenvironment, and the prognostic value of NRGs in gliomas. In conclusion, our study provides comprehensive roles of NRG family members in gliomas, supporting modulation of NRG signaling in the management of glioma.

scholarly journals RNA N6-Methyladenosine Regulators Contribute to Tumor Immune Microenvironment and Have Clinical Prognostic Impact in Breast Cancer

2022 ◽  
Vol 12 ◽  
Author(s):  
Lan-Xin Mu ◽  
You-Cheng Shao ◽  
Lei Wei ◽  
Fang-Fang Chen ◽  
Jing-Wei Zhang
Keyword(s):  
Breast Cancer ◽  
Immune Cell ◽  
Risk Model ◽  
Cox Regression ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Prognostic Impact ◽  
Immune Microenvironment ◽  
Model Based ◽  
Tumor Immune Microenvironment

Purpose: This study aims to reveal the relationship between RNA N6-methyladenosine (m6A) regulators and tumor immune microenvironment (TME) in breast cancer, and to establish a risk model for predicting the occurrence and development of tumors.Patients and methods: In the present study, we respectively downloaded the transcriptome dataset of breast cancer from Gene Expression Omnibus (GEO) database and The Cancer Genome Atlas (TCGA) database to analyze the mutation characteristics of m6A regulators and their expression profile in different clinicopathological groups. Then we used the weighted correlation network analysis (WGCNA), the least absolute shrinkage and selection operator (LASSO), and cox regression to construct a risk prediction model based on m6A-associated hub genes. In addition, Immune infiltration analysis and gene set enrichment analysis (GSEA) was used to evaluate the immune cell context and the enriched gene sets among the subgroups.Results: Compared with adjacent normal tissue, differentially expressed 24 m6A regulators were identified in breast cancer. According to the expression features of m6A regulators above, we established two subgroups of breast cancer, which were also surprisingly distinguished by the feature of the immune microenvironment. The Model based on modification patterns of m6A regulators could predict the patient’s T stage and evaluate their prognosis. Besides, the low m6aRiskscore group presents an immune-activated phenotype as well as a lower tumor mutation load, and its 5-years survival rate was 90.5%, while that of the high m6ariskscore group was only 74.1%. Finally, the cohort confirmed that age (p < 0.001) and m6aRiskscore (p < 0.001) are both risk factors for breast cancer in the multivariate regression.Conclusion: The m6A regulators play an important role in the regulation of breast tumor immune microenvironment and is helpful to provide guidance for clinical immunotherapy.

scholarly journals CYSTM1: A Novel Biomarker for Hepatocellular Carcinoma Prognosis

2021 ◽  
Author(s):  
Jun Du ◽  
Jinguo Wang
Keyword(s):  
Hepatocellular Carcinoma ◽  
Poor Prognosis ◽  
Early Stage ◽  
Human Tumor ◽  
The Cancer Genome Atlas ◽  
Data Set ◽  
Kaplan Meier ◽  
Cancer Genome Atlas ◽  
Cox Proportional Hazard Regression ◽  
The Relationship

Abstract Background: The expression and molecular mechanism of cysteine rich transmembrane module containing 1 (CYSTM1) in human tumor cells remains unclear. The aim of this study was to determine whether CYSTM1 could be used as a potential prognostic biomarker for hepatocellular carcinoma (HCC).Methods: We first demonstrated the relationship between CYSTM1 expression and HCC in various public databases. Secondly, Kaplan–Meier analysis and Cox proportional hazard regression model were performed to evaluate the relationship between the expression of CYSTM1 and the survival of HCC patients which data was downloaded in the cancer genome atlas (TCGA) database. Finally, we used the expression data of CYSTM1 in TCGA database to predict CYSTM1-related signaling pathways through bioinformatics analysis.Results: The expression level of CYSTM1 in HCC tissues was significantly correlated with T stage (p = 0.039). In addition, Kaplan–Meier analysis showed that the expression of CYSTM1 was significantly associated with poor prognosis in patients with early-stage HCC (p = 0.003). Multivariate analysis indicated that CYSTM1 is a potential predictor of poor prognosis in HCC patients (p = 0.036). The results of biosynthesis analysis demonstrated that the data set of CYSTM1 high expression was mainly enriched in neurodegeneration and oxidative phosphorylation pathways.Conclusion: CYSTM1 is an effective biomarker for the prognosis of patients with early-stage HCC and may play a key role in the occurrence and progression of HCC.

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

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.

Sign in / Sign up

Export Citation Format

Share Document