scholarly journals The Landscape of Immune Cells Indicates Prognosis and Applicability of Checkpoint Therapy in Hepatocellular Carcinoma

2021 ◽  
Vol 11 ◽  
Author(s):  
Jiacheng Huang ◽  
Lele Zhang ◽  
Jianxiang Chen ◽  
Dalong Wan ◽  
Lin Zhou ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
T Cells ◽  
Immune Cells ◽  
The Cancer Genome Atlas ◽  
Prognostic Models ◽  
Host Immune System ◽  
Mrna Levels ◽  
M1 Macrophages ◽  
M1 Macrophage ◽  
The Relationship

BackgroundTumor-infiltrating immune cells are important components of tumor microenvironment (TME), and their composition reflects the confrontation between host immune system and tumor cells. However, the relationship between the composition of infiltrating immune cells, prognosis, and the applicability of anti-PD-1/PD-L1 therapy in hepatocellular carcinoma (HCC) needs systematic examination.MethodsCell-Type Identification by Estimating Relative Subsets of RNA Transcripts (CIBERSORT) was applied to evaluate the infiltration of immune cells based on The Cancer Genome Atlas (TCGA) liver hepatocellular carcinoma (LIHC) cohort. Diagnostic and prognostic models were constructed based on immune cells, and the models were validated by two external cohorts. The relationship between immune cells and PD-L1 was evaluated by Spearman correlation, and the finding was validated in our in-house HCC sample.ResultPatients in TCGA LIHC cohort were classified into six subtypes with different prognosis based on the proportion of tumor-infiltrating immune cells simulated via CIBERSORT. Among 22 types of immune cells, intratumoral PD-L1 mRNA level exhibited linear relationship with the fraction of five types of immune cells (M1 macrophages, plasma cells, CD8+ T cells, resting mast cells, and regulatory T cells), and M1 macrophages showed the strongest relevance (R = 0.26, p < 0.001). Immunohistochemistry of our in-house HCC specimens verified this conclusion. Moreover, intratumoral mRNA levels of M1 macrophage-associated cytokines were positively correlated with PD-L1 level.ConclusionsOur study demonstrated that the prognosis of HCC patients was associated with the pattern of infiltrating immune cells in TME, and macrophage-associated cytokines might be a potential non-invasive marker for predicting the PD-L1 level for HCC patients.

scholarly journals A dual immune signature of CD8+ T Cells and MMP9 improves the survival of hepatocellular carcinoma patients

2021 ◽  
Author(s):  
Huan Ding ◽  
Huan Hu ◽  
Feifei Tian ◽  
Huaping Liang
Keyword(s):  
Hepatocellular Carcinoma ◽  
T Cells ◽  
Cd8 T Cells ◽  
Immune Cells ◽  
Immune Cell ◽  
Cox Regression ◽  
Gene Expression Omnibus ◽  
The Cancer Genome Atlas ◽  
High Recurrence Rate ◽  
Immune Signature

The 5-year survival of hepatocellular carcinoma (HCC) is difficult due to the high recurrence rate and metastasis. Tumor infiltrating immune cells (TICs) and immune-related genes (IRGs) bring hope to improve survival and treatment of HCC patients. However, there are problems in predicting immune signatures and identifying novel therapeutic targets. In the study, the CIBERSORT algorithm was used to evaluate 22 immune cell infiltration patterns in gene expression omnibus (GEO) and the cancer genome atlas (TCGA) data. Eight immune cells were found to have significant infiltration differences between the tumor and normal groups. The CD8+ T Cells immune signature was constructed by least absolute shrinkage and selection operator (LASSO) algorithm. The high infiltration level of CD8+ T Cells could significantly improve survival of patients. The weighted gene co-expression network analysis (WGCNA) algorithm identified MMP9 was closely related to the overall survival of HCC patients. K-M survival and tROC analysis confirmed that MMP9 had an excellent prognostic prediction. Cox regression showed that a dual immune signature of CD8+ T Cells and MMP9 was independent survival factor in HCC. Therefore, a dual prognostic immune signature could improve the survival of patient and may provide a new strategy for the immunotherapy of HCC.

scholarly journals Exploration of the regulatory mechanism for hepatocellular carcinoma based on ceRNA networks analysis and immune infiltration

2021 ◽  
Author(s):  
Ning Huang ◽  
Qiang Chen ◽  
Xiaoyi Wang
Keyword(s):  
Hepatocellular Carcinoma ◽  
T Cells ◽  
Network Analysis ◽  
Correlation Analysis ◽  
Immune Cells ◽  
Regulatory Mechanism ◽  
Immune Cell ◽  
Risk Model ◽  
The Cancer Genome Atlas ◽  
Ppi Network

Abstract Background Hepatocellular carcinoma (HCC) as malignant cancer has been deeply investigated for its widespread distribution and extremely high mortality rate worldwide. Despite efforts to understand the regulatory mechanism in HCC, it remains largely unknown. Methods The RNA (mRNAs, lncRNAs, and miRNAs) profiles were downloaded from The Cancer Genome Atlas (TCGA) database. Based on the Weighted Gene Co-expression Network Analysis (WGCNA), the hub differentially expressed RNAs (DERNAs) were screened out. The competing endogenous RNA (ceRNA) and Protein and Protein Interaction (PPI) network were constructed based on the hub DERNAs. The Cox and LASSO regression analysis were used to find the independent prognostic ceRNAs. We performed the “CIBERSORT” algorithm estimate the abundance of immune cells. The correlation analysis was applied to determine the relationship between HCC-related immune cells and prognostic ceRNAs. GEPIA and TIMER database were used to explore the association of critical genes with survival and immune cell infiltration, respectively. Results A total of 524 hub RNAs (507 DEmRNAs, 13 DElncRNAs and 4 DEmiRNAs) were identified in the turquoise module (cor = 0.78, P = 4.7e − 198) using WGCNA algorithm. PPI network analysis showed that NDC80, BUB1B and CCNB2 as the critical genes in HCC. Subsequently, survival analysis revealed that the low expression of NDC80 and BUB1B resulted in a longer overall survival (OS) time for HCC patients in GEPIA database. These critical genes and several immune cells were all significantly positive correlated in TIMER database. The ceRNA network were establish, and were incorporated to risk model. Subsequently, ROC curve showed that the area under the curve (AUC) of the 1-, 3-, and 5-year were 0.762, 0.705, and 0.688, respectively. Out of the 22 cell types, T cells CD4 memory resting were identified as the HCC-related immune cells by systematic analysis. The correlation analysis shown that T cells CD4 memory resting is negatively associated with both AL021453.1 (R = − 0.44, P = 0.00049) and CCDC137 (R = − 0.47, P = 2e-04). Conclusion The current study provide potential prognostic signatures and therapeutic targets for HCC.

scholarly journals Iron Released after Cryo-Thermal Therapy Induced M1 Macrophage Polarization, Promoting the Differentiation of CD4+ T Cells into CTLs

2021 ◽  
Vol 22 (13) ◽  
pp. 7010
Author(s):  
Shicheng Wang ◽  
Man Cheng ◽  
Peng Peng ◽  
Yue Lou ◽  
Aili Zhang ◽  
...  
Keyword(s):  
T Cells ◽  
Cd4 T Cells ◽  
Antitumor Immunity ◽  
Macrophage Polarization ◽  
Thermal Therapy ◽  
High Plasticity ◽  
Antitumor Effects ◽  
M1 Macrophages ◽  
Splenic Macrophages ◽  
M1 Macrophage

Macrophages play critical roles in both innate and adaptive immunity and are known for their high plasticity in response to various external signals. Macrophages are involved in regulating systematic iron homeostasis and they sequester iron by phagocytotic activity, which triggers M1 macrophage polarization and typically exerts antitumor effects. We previously developed a novel cryo-thermal therapy that can induce the mass release of tumor antigens and damage-associated molecular patterns (DAMPs), promoting M1 macrophage polarization. However, that study did not examine whether iron released after cryo-thermal therapy induced M1 macrophage polarization; this question still needed to be addressed. We hypothesized that cryo-thermal therapy would cause the release of a large quantity of iron to augment M1 macrophage polarization due to the disruption of tumor cells and blood vessels, which would further enhance antitumor immunity. In this study, we investigated iron released in primary tumors, the level of iron in splenic macrophages after cryo-thermal therapy and the effect of iron on macrophage polarization and CD4+ T cell differentiation in metastatic 4T1 murine mammary carcinoma. We found that a large amount of iron was released after cryo-thermal therapy and could be taken up by splenic macrophages, which further promoted M1 macrophage polarization by inhibiting ERK phosphorylation. Moreover, iron promoted DC maturation, which was possibly mediated by iron-induced M1 macrophages. In addition, iron-induced M1 macrophages and mature DCs promoted the differentiation of CD4+ T cells into the CD4 cytolytic T lymphocytes (CTL) subset and inhibited differentiation into Th2 and Th17 cells. This study explains the role of iron in cryo-thermal therapy-induced antitumor immunity from a new perspective.

scholarly journals Expression and clinical significance of CMTM1 in hepatocellular carcinoma

Open Medicine ◽  
2021 ◽  
Vol 16 (1) ◽  
pp. 217-223
Author(s):  
Xin Song ◽  
Shidong Zhang ◽  
Run Tian ◽  
Chuanjun Zheng ◽  
Yuge Xu ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Transmembrane Domain ◽  
Disease Free Survival ◽  
Clinicopathological Characteristics ◽  
The Cancer Genome Atlas ◽  
High Expression ◽  
Chi Square ◽  
Tumor Tissues ◽  
The Relationship ◽  
Low Expression

Abstract Background CKLF Like Marvel Transmembrane Domain Containing 1 (CMTM1) plays a role in breast cancer and lung cancer, but studies on the occurrence and development of CMTM1 in hepatocellular carcinoma (HCC) have not been reported. Methods The Cancer Genome Atlas (TCGA) database and immunohistochemistry (IHC) were used to detect CMTM1 expression in HCC tissues. The relationship between CMTM1 expression and the clinicopathological characteristics of HCC patients was analyzed by chi-square test, and the relationship between CMTM1 expression and the prognosis of HCC patients was tested by the Kaplan–Meier model. Results Bioinformatics analysis showed that the mRNA expression of CMTM1 was upregulated in HCC tissues, and low expression of CMTM1 is associated with longer disease-free survival in patients with HCC. Similarly, the survival time of HCC patients in CMTM1 high expression group was significantly shorter than that in CMTM1 low expression group. IHC detection indicated that CMTM1 protein was highly expressed in both HCC and adjacent non-tumor tissues, with a positive expression in 84% (63/75) of HCC tissues and 89.3% (67/75) of adjacent non-tumor tissues. Moreover, CMTM1 expression was related to family history and TNM stage of HCC patients (P < 0.05), but had no relationship with other clinicopathological characteristics. The survival analysis based on IHC results showed that the prognosis of HCC patients in CMTM1 negative group was significantly poorer than that in CMTM1 positive group (P < 0.05). Conclusion CMTM1 has a high expression in HCC tissues and is related to the prognosis of HCC patients.

scholarly journals O9 M1 macrophages evoke an increase in PIGR expression in MDA-MB468 breast cancer cells through interlukin-1β

2021 ◽  
Vol 108 (Supplement_5) ◽  
Author(s):  
W Asanprakit ◽  
D N Lobo ◽  
O Eremin ◽  
A J Bennett
Keyword(s):  
Breast Cancer ◽  
Cancer Cells ◽  
Immune Cells ◽  
Breast Cancer Cells ◽  
Polarization State ◽  
M2 Macrophage ◽  
M1 Macrophages ◽  
M1 Macrophage ◽  
Macrophage Cytokine

Abstract Introduction The polymeric immunoglobulin receptor (PIGR) is a transmembrane protein, which transports polymeric immunoglobulin (pIg) across the epithelial cells. High expression of PIGR in breast cancer has been reported to associate with increased 5-year survival rate. In this study, the factors in tumour microenvironment which affected PIGR expression in breast cancer cell lines, were investigated. Method M1, M2 macrophage conditioned media (CM) and recombinant human cytokines were used to determine factors which increased PIGR expression in breast cancer cells. The level of PIGR expression in the cells and secreted PIGR free secretory component (SC) were evaluated by real time quantitative polymerase chain reaction and Western blotting. Results M1 macrophage CM induced a striking dose dependent increase in PIGR mRNA expression in MDA-MB468 cells, up to 20-fold in 100% CM. Interferon gamma (IFNγ) and interleukin (IL)-1β also increased PIGR expression in MDA-MB468 cells. However, IL-1β was demonstrated to increase in M1 macrophages, while IFNγ was not. The role of IL-1β secreted from M1 macrophages in increasing expression of PIGR was confirmed by IL-1 receptor blockade, indicating that IL-1β was the M1 macrophage cytokine that enhanced PIGR expression in breast cancer cells. Conclusions IL-1β was the M1 macrophage cytokine which enhanced PIGR expression in breast cancer cells. IFNγ was also shown to increase PIGR expression in the present study. These imply that elevated PIGR expression in breast cancer in vivo may reflect the polarization state of tumour associated immune cells. Take-home Message IL-1β secreted from M1 macrophage enhances PIGR expression in breast cancer cells. The elevated PIGR expression in breast cancer in vivo may reflect the polarization state of tumour associated immune cells.

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

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.

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 Prognostic Significance of NBEAL2 in Liver hepatocellular carcinoma

2021 ◽  
Author(s):  
Yanghui Wen ◽  
Hui Su ◽  
Wuke Wang ◽  
Feng Ren ◽  
Haitao Jiang ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Expression Profiles ◽  
Prognostic Significance ◽  
The Cancer Genome Atlas ◽  
Clinicopathological Parameters ◽  
Chi Square ◽  
Kaplan Meier ◽  
Chi Square Test ◽  
Liver Hepatocellular Carcinoma ◽  
The Relationship

Abstract Background: NBEAL2 is a member of the BEACH domain–containing protein (BDCP) family and little is known about the relationship between NBEAL2 and malignancy.Methods: We downloaded the Gene expression profiles and clinical data of Liver hepatocellular carcinoma(LIHC) form the Cancer Genome Atlas (TCGA) dataset. The expression difference of NBEAL2 in LIHC tissues and adjacent nontumor tissues was analyzed by R software. The relationship between NBEAL2 expression and clinicopathological parameters was evaluate by Chi-square test. The effect of NBEAL2 expression on survival were assessed by Kaplan–Meier survival analysis and Cox proportional hazards regression model. GSEA was used to explore the potential molecular mechanism of NBEAL2 in LIHC.Results: Up-regulation of NBEAL2 expression was detected in the LIHC tissue compared with adjacent nontumor tissues(P < 0.001). The chi-square test showed that no significant correlation between the expression level of NBEAL2 and various clinicopathological parameters (including T, N and M classifications) were detected. The Kaplan–Meier curves suggested that lower NBEAL2 expression was related with poor prognosis. The results of Multivariate analysis revealed that a lower expression of NBEAL2 in LIHC was an independent risk of poor overall survival (HR, 8.873; 95% CI, 1.159-67.936; P = 0.035). GSEA suggested that multiple tumor-related metabolic pathways were evidently enriched in samples with the low-NBEAL2 expression phenotype. Conlusion: NBEAL2 might act as an tumor suppressor gene in the progression of LIHC but the precise role of NBELA2 in LIHC needs further vertification.

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

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.

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

2019 ◽  
Vol 2019 ◽  
pp. 1-12 ◽  
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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