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 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 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.

scholarly journals Global immune characterization of HBV/HCV-related hepatocellular carcinoma identifies macrophage and T-cell subsets associated with disease progression

2020 ◽  
Vol 6 (1) ◽  
Author(s):  
Guohe Song ◽  
Yang Shi ◽  
Meiying Zhang ◽  
Shyamal Goswami ◽  
Saifullah Afridi ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
T Cells ◽  
T Cell ◽  
Single Cell ◽  
Immune Cells ◽  
Immune Cell ◽  
T Cell Subsets ◽  
M2 Macrophage ◽  
Advanced Hcc ◽  
Immune Cell Subsets

AbstractDiverse immune cells in the tumor microenvironment form a complex ecosystem, but our knowledge of their heterogeneity and dynamics within hepatocellular carcinoma (HCC) still remains limited. To assess the plasticity and phenotypes of immune cells within HBV/HCV-related HCC microenvironment at single-cell level, we performed single-cell RNA sequencing on 41,698 immune cells from seven pairs of HBV/HCV-related HCC tumors and non-tumor liver tissues. We combined bio-informatic analyses, flow cytometry, and multiplex immunohistochemistry to assess the heterogeneity of different immune cell subsets in functional characteristics, transcriptional regulation, phenotypic switching, and interactions. We identified 29 immune cell subsets of myeloid cells, NK cells, and lymphocytes with unique transcriptomic profiles in HCC. A highly complex immunological network was shaped by diverse immune cell subsets that can transit among different states and mutually interact. Notably, we identified a subset of M2 macrophage with high expression of CCL18 and transcription factor CREM that was enriched in advanced HCC patients, and potentially participated in tumor progression. We also detected a new subset of activated CD8+ T cells highly expressing XCL1 that correlated with better patient survival rates. Meanwhile, distinct transcriptomic signatures, cytotoxic phenotypes, and evolution trajectory of effector CD8+ T cells from early-stage to advanced HCC were also identified. Our study provides insight into the immune microenvironment in HBV/HCV-related HCC and highlights novel macrophage and T-cell subsets that could be further exploited in future immunotherapy.

scholarly journals Identification of immune-infiltrating cell-related biomarkers in hepatocellular carcinoma based on gene co-expression network analysis

2021 ◽  
Vol 16 (1) ◽  
Author(s):  
Yinghui Hou ◽  
Guizhi Zhang
Keyword(s):  
Hepatocellular Carcinoma ◽  
Network Analysis ◽  
Early Diagnosis ◽  
The Cancer Genome Atlas ◽  
Ppi Network ◽  
Sequencing Data ◽  
Hub Genes ◽  
Survival Prognosis ◽  
Expression Levels ◽  
Cancer Tissues

Abstract Background Hepatocellular carcinoma (HCC) is often caused by chronic liver infection or inflammation. Searching for potential immunotherapy targets will aid the early diagnosis and treatment of HCC. Methods Firstly, detailed HCC data were downloaded from The Cancer Genome Atlas database. GDCRNATools was used for the comprehensive analysis of RNA sequencing data. Subsequently, the CIBERSORT package was used to estimate infiltration scores of 22 types of immune cells in complex samples. Furthermore, hub genes were identified via weighted gene co-expression network analysis (WGCNA) and protein-protein interaction (PPI) network analysis. In addition, multiple databases were used to validate the expression of hub gene in the tumor tissue. Finally, prognostic, diagnostic and immunohistochemical analysis of key hub genes was performed. Results In the present study, 9 hub genes were identified using WGCNA and PPI network analysis. Furthermore, the expression levels of 9 genes were positively correlated with the infiltration levels of CD8-positive T (CD8+ T) cells. In multiple dataset validations, the expression levels of CCL5, CXCR6, CD3E, and LCK were decreased in cancer tissues. In addition, survival analysis revealed that patients with LCK low expression had a poor survival prognosis (P < 0.05). Immunohistochemistry results demonstrated that CCL5, CD3E and LCK were expressed at low levels in HCC cancer tissues. Conclusion The identification of CCL5, CXCR6, CD3E and LCK may be helpful in the development of early diagnosis and therapy of HCC. LCK may be a potential prognostic biomarker for immunotherapy for HCC.

scholarly journals A Four-Immune Gene Prognostic Risk Model for Colorectal Adenocarcinoma Based on the TCGA and Immport Data Sets

2020 ◽  
Author(s):  
Boyang Xu ◽  
Ziqi Peng ◽  
Yue An ◽  
Xue Yao ◽  
Mingjun Sun
Keyword(s):  
T Cells ◽  
Colorectal Adenocarcinoma ◽  
Immune Cell ◽  
Risk Model ◽  
The Cancer Genome Atlas ◽  
Differentially Expressed ◽  
Data Sets ◽  
Immune Gene ◽  
Immune Genes ◽  
Follicular Helper

Abstract BackgroundAs one of the hot spots in oncology field, immune research provides new ideas for the diagnosis and treatment of tumors. Different histological types of colorectal cancer are different. Adenocarcinoma, as the type with the highest proportion, has a high research value. This study aims to build an immune gene prognostic risk model for colorectal adenocarcinoma to improve the diagnosis and prognosis prediction of colorectal adenocarcinoma.MethodsThe differentially expressed immune genes could be obtained from the gene expression data downloaded from The Cancer Genome Atlas (TCGA) and the immune gene data downloaded from the ImmPort Database. Univariate COX and multivariate COX analyses were used to construct the immune gene prognostic risk model of and the clinical application potential of this model. The correlation between the model and the immune cells infiltration and the influence of each immune cell on the survival were analyzed.Results5975 differentially expressed genes were obtained, and 497 differentially expressed immune genes were selected by combining the information of immune genes. Among them, 36 immune genes were associated with prognosis, and 4 immune genes (THRB, IL1RL2, LGR6, LTB4R2) were included in the prognostic risk model of immune genes. Patients with higher Risk Score had shorter survival. Compared with gender, age and pathological stage, the model has better prediction potential. In addition, the model was correlated with Macrophages M0, Macrophages M1, T cells follicular helper and NK cells activated. Among them, T cells follicular helper and Macrophages M0 were related to the survival of patients.ConclusionWe developed a prognostic risk model containing four immune genes, THRB, IL1RL2, LGR6 and LTB4R2, which accurately described the prognosis of the patient, and affected the survival of patients by influencing the infiltration of Macrophages M0 and T cells follicular helper.

scholarly journals Investigation of Immune‐related Makers Associated with Tumor-infiltrating T Cells in Ovarian Cancer

2020 ◽  
Author(s):  
Haihong Liao ◽  
Shuwen Han ◽  
Yuefen Pan ◽  
Jiamin Xu ◽  
Quan Qi ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
T Cells ◽  
Network Analysis ◽  
The Cancer Genome Atlas ◽  
Cancer Prognosis ◽  
Ppi Network ◽  
Protein Protein Interaction ◽  
Ppi Networks ◽  
Target Network ◽  
Patient Prognosis

Abstract Background: Tumor-infiltrating T cells in the tumor microenvironment are the biological basis of immunotherapy and promising predictors of cancer prognosis. Aim: The aim of this study was to investigate immune‐related RNAs associated with tumor-infiltrating T cells in ovarian cancer (OV).Methods: The gene expression data of patients with OV were downloaded from The Cancer Genome Atlas (TCGA) database. The immune and stromal scores were calculated and the differentially expressed mRNAs (DEGs) were screened. The abundance of six types of infiltrating immune cells was investigated, and the immune-related DEGs associated with tumor-infiltrating CD4+ and CD8+ T cells were explored by correlation analyses. Subsequently, multiple analyses, i.e., protein-protein interaction (PPI) network analysis, competing endogenous RNA (ceRNA; lncRNA-miRNA-target) network analysis, and small-molecule target network analysis, were performed. Results: In total, 37 and 49 immune-related DEGs of CD4+ and CD8+ T cells were screened, respectively. PPI network results showed that granzyme B (GZMB) was a hub node in the two PPI networks constructed by immune-related DEGs of CD4+ and CD8+ T cells. Moreover, the ceRNA chr22-38_28785274-29006793.1/has-miR-1249-5p/CD3E was obtained from the two constructed ceRNA networks related to CD4+ and CD8+ T cells. Survival analysis revealed that key immune-related DEGs of CD4+ and CD8+ T cells, such as GZMB and CD3E, were positively correlated with patient prognosis. Conclusion: GZMB and ceRNAs, such as chr22-38_28785274-29006793.1/has-miR-1249-5p/CD3E, may mediate the role of tumor-infiltrating T cells in OV. GZMB and CD3E may be used as promising T cell-related biomarkers with prognostic value in OV.

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 &lt; 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 Uncovering of the Association Between m5C Regulator-Mediated Methylation Modification Patterns and Tumor Microenvironment Infiltration Characteristics in Hepatocellular Carcinoma

2021 ◽  
Author(s):  
Xinyu Gu ◽  
Haibo Zhou ◽  
Qingfei Chu ◽  
Qiuxian Zheng ◽  
Jing Wang ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Immune Cells ◽  
Immune Cell ◽  
Enrichment Analysis ◽  
Tumour Microenvironment ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Cell Infiltration ◽  
Gene Set ◽  
Normal Tissues

Abstract Background: 5-Methylcytosine (m5C) plays essential roles in hepatocellular carcinoma (HCC), but the association between m5C regulation and immune cell infiltration in HCC has not yet been clarified.Methods: In this study, we analysed 371 patients with HCC from The Cancer Genome Atlas (TCGA) database, and the expression of 13 m5C regulators was investigated. Additionally, gene set variation analysis (GSVA), unsupervised clustering analysis, single-sample gene set enrichment analysis (ssGSEA), correlation analysis, and immunohistochemical (IHC) staining were performed.Results: Among the 371 patients, 41 had mutations in m5C regulators, the frequency of which was 11.26%. Then, we identified three m5C modification patterns that had obvious tumour microenvironment (TME) cell infiltration characteristics. Cluster-1 had an immune rejection phenotype; Cluster-2 had an immunoinflammatory phenotype; and Cluster-3 had an immune desert phenotype. In addition, we found that DNMT1 was highly expressed in tumour tissues compared with normal tissues in a tissue microarray (TMA) and that it was positively correlated with many TME-infiltrating immune cells. High expression of the m5C regulator DNMT1 was related to a poor prognosis in patients with HCC. Furthermore, we developed three Immu-clusters that were consistent with the immune characteristics of the m5C methylation modification patterns. We also discovered differences in the levels of immune cells and expression of chemokines and cytokines among the three Immu-clusters.Conclusions: Our work revealed the association between m5C modification and immune regulators in the TME. These findings also suggest that DNMT1 has great potential as a prognostic biomarker and therapeutic target for HCC.

scholarly journals Exploration of the role of tumor mutation burden in clinical significance, immunotherapy response predictor and immune cell infiltration in colon cancer

2020 ◽  
Author(s):  
Zhengshui Xu ◽  
Chao Qu ◽  
Jing Guo ◽  
Xiaopeng Li ◽  
Yunhua Wu ◽  
...  
Keyword(s):  
Colon Cancer ◽  
T Cells ◽  
Immune Cells ◽  
Immune Cell ◽  
Mrna Level ◽  
The Cancer Genome Atlas ◽  
Immune Checkpoints ◽  
Mutation Burden ◽  
Pathologic Features

Abstract Backgroud:Tumor mutation burden has become a powerful bio-marker to predict prognosis and immunotherapy responsiveness to patients in various cancers, but the role of TMB in colon cancer is still unclear.Methods:The transcriptome profiling data of colon patients and the simple nucleotide variation data of colon cases were downloaded from the Cancer Genome Atlas (TCGA) database. The groups were divided into high TMB and low TMB group according to the median of TMB. Then we explored the relationship between immune checkpoints, immune cells and TMB, respectively. Results: Mutation profiles of 399 colon cancer samples were analyzed in TCGA database. The senior (age＞65) had a strong relationship with higher-TMB level(p=0.001). Low-TMB group correlated with advanced N stage (P＜0.001), M stage (P＜0.001), and pathologic stage(P＜0.001). High-TMB group had significantly higher mRNA level of PD-L1, TIGIT, HAVCR2, and LAG3 than low-TMB group, which indicated high-TMB referred to better immunotherapy responsiveness in colon cancer. And high-TMB level correlated with higher fractions of CD8T cells (p=0.021), higher CD4 memory T cells(p=0.039), follicular helper T cells (p=0.002)and M1 macrophages (p＜0.001), while the low-TMB groups correlated with higher regulator T cells (p=0.002). So high-TMB correlated with stronger immune cell infiltrationConclusions:The high TMB referred to better clinical pathologic features, better immunotherapy responsiveness and stronger immune cells infiltration in colon cancer. Hence TMB may be a very promising bio-marker to predict prognosis and immunotherapy responsiveness to patients in colon cancer.

scholarly journals A Tumor-Infiltrating Lymphocyte-Based Risk Model Predicts Prognosis of Colon Cancer

2021 ◽  
Author(s):  
Ziqi Sui ◽  
Yanli Zhu ◽  
Kejia Wu ◽  
Shuxiang Wang ◽  
Xixian Yuan ◽  
...  
Keyword(s):  
Gene Expression ◽  
Colon Cancer ◽  
Immune Cells ◽  
Immune Cell ◽  
Risk Model ◽  
Cox Regression ◽  
Cell Types ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Migration And Invasion

Abstract Tumor-infiltrating lymphocytes are relevant to the tumor prognosis and response to immunotherapy in colon cancer. The gene expression data of colon cancer was obtained from the cancer genome atlas (TCGA) database and the components of immune cell types were analyzed by CIBERSORT. Selection operator (LASSO) and multivariate Cox regression filtered immune cells and selected the most significant cell types to construct an immune risk model including memory B cells, plasma cells, T follicular helper (Tfh) cells, M0 macrophages and resting dendritic cells. Receiver operating characteristic (ROC) curves were used to verify the sensitivity and specificity of the model, which was validated in Gene Expression Omnibus (GEO) dataset. Combined with the clinical traits, a nomogram was established to predict the prognosis of colon cancer. According to function analyses through weighted correlation network analysis (WGCNA) and gene set enrichment analysis (GSEA), tumor-infiltrating immune cells showed significant importance in tumor immune-associated regulation, especially the adhesion, migration and invasion in colon cancer.

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