Disparity of Hepatocellular Carcinoma in Tumor Microenvironment-Related Genes and Infiltrating Immune Cells between Asian and Non-Asian Populations.
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ABSTRACT:
SUBMITTER: Huang LH
PROVIDER: S-EPMC8392256 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Background: The clinicopathological features and prognosis of breast cancer in Asia are different from those in the Western countries. Tumor-infiltrating immune cells can influence the outcome of patients with breast cancer, but they have not been systemically evaluated in Asian patients with breast cancer.Methods: We compared the immune score, composition, and prognostic impact of infiltrating immune cells between Asian and Western patients with breast cancer by analyzing gene expression profiles from eight Gene Expression Omnibus data sets and The Cancer Genome Atlas data set. The Estimation of Stromal and Immune Cells in Malignant Tumours Using Expression Data (ESTIMATE) and Cell Type Identification by Estimating Relative Subsets of Known RNA Transcripts (CIBERSORT) algorithms were used to determine the immune score and composition of tumor-infiltrating immune cells, respectively.Findings: This study included 462 Asian patients and 2,186 Western patients. Tumors of Asian patients had significantly higher immune score, particularly in the luminal B and HER2-enriched subtypes. High immune score was associated with favorable prognosis in both Asian and Western patients, and Asian race with a high ESTIMATE immune score provided additional power to predict longer disease-free survival. Activated CD4 T cells and M2 macrophages were the most strongly associated with survival in both Asian and Western patients.Interpretation: Our study highlights the difference in tumor immune microenvironments between Asian and Western patients. The higher ESTIMATE immune score, which represents more abundant tumor-infiltrating immune cells, in tumors of Asian patients partly explains their favorable prognosis.Implications for practice: The tumor microenvironment serves as an interface that affects the human body's reaction to cancer cells. Evidence has revealed that tumor-infiltrating immune cells were associated with patient prognosis. This study demonstrated the disparity of tumor microenvironments and their prognostic impact between Asian and Western patients with breast cancer. The differences in immune score partially explained the racial survival differences noted in recent studies. Integrated analysis of tumor cells, tumor microenvironment, and racial effect may significantly improve recurrence risk prediction for patients with stage I-III breast cancer. Because the effect of tumor microenvironment varies across different populations, a model of interaction between immune score and race/ethnicity is recommended in accessing the risk of patients with cancer.
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Project description:Hepatocellular carcinoma (HCC) is the most common primary liver malignancy and is the third leading cause of tumor-related mortality worldwide. In recent years, the emergency of immune checkpoint inhibitor (ICI) has revolutionized the management of HCC. Especially, the combination of atezolizumab (anti-PD1) and bevacizumab (anti-VEGF) has been approved by the FDA as the first-line treatment for advanced HCC. Despite great breakthrough in systemic therapy, HCC continues to portend a poor prognosis owing to drug resistance and frequent recurrence. The tumor microenvironment (TME) of HCC is a complex and structured mixture characterized by abnormal angiogenesis, chronic inflammation, and dysregulated extracellular matrix (ECM) remodeling, collectively contributing to the immunosuppressive milieu that in turn prompts HCC proliferation, invasion, and metastasis. The tumor microenvironment coexists and interacts with various immune cells to maintain the development of HCC. It is widely accepted that a dysfunctional tumor-immune ecosystem can lead to the failure of immune surveillance. The immunosuppressive TME is an external cause for immune evasion in HCC consisting of 1) immunosuppressive cells; 2) co-inhibitory signals; 3) soluble cytokines and signaling cascades; 4) metabolically hostile tumor microenvironment; 5) the gut microbiota that affects the immune microenvironment. Importantly, the effectiveness of immunotherapy largely depends on the tumor immune microenvironment (TIME). Also, the gut microbiota and metabolism profoundly affect the immune microenvironment. Understanding how TME affects HCC development and progression will contribute to better preventing HCC-specific immune evasion and overcoming resistance to already developed therapies. In this review, we mainly introduce immune evasion of HCC underlying the role of immune microenvironment, describe the dynamic interaction of immune microenvironment with dysfunctional metabolism and the gut microbiome, and propose therapeutic strategies to manipulate the TME in favor of more effective immunotherapy.
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Project description:AbstractGrowing evidence supports that the tumor microenvironment plays a key role in the development and progression of tumors. But immune microenvironment of hepatocellular carcinoma (HCC) has not yet been fully explored. In the present investigation, the clinical value and prognostic significance of immune-related genes in HCC were investigated.The immune and stromal scores of HCC were calculated through the application of Estimation of Stromal and Immune cells in Malignant Tumor tissues using Expression data Algorithm based on the Cancer Genome Atlas database. Differentially expressed genes were identified using the "edgeR" package of the R software. Functional annotation and pathway enrichment were performed using "ggplots2" and "clusterProfiler" packages in R software. Protein-protein interaction network was constructed using STRING, and the hub genes were identified through the Cytoscape. Survival analysis was performed using Kaplan-Meier methods. Tumor Immune Estimation Resource algorithm was used to view the immune landscape of the microenvironment in HCC.Firstly, the immune and stromal scores of HCC were calculated and we found that the immune and stromal scores of HCC were closely related to the patients' prognosis. Then the differentially expressed genes were identified respectively stratified by the median value of the immune and stromal scores, and the immune-related genes that related to the prognosis in HCC patients were further identified. Functional enrichment analysis and protein-protein interaction networks further showed that these genes mainly participated in immune-related biological process. In addition, dendritic cells were found to be the most abundant in the microenvironment of HCC through Tumor Immune Estimation Resource algorithm and were significantly associated with the patients' prognosis. To robust the results, the immune-related genes were validated in an independent dataset from the Gene Expression Omnibus database.We arrived at a more comprehensive understanding of the microenvironment of HCC and extracted 7 immune-related genes that were significantly associated with the recurrence survival of HCC.
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Project description:V-ATPase activity established a less immune-suppressive tumor microenvironment and reversed the mesenchymal features of HCC. Thus, targeting the unique cross-talk between tumor cells and the tumor microenvironment played by pH regulatory molecules holds promise as a strategy to control HCC progression and to reduce the immunosuppressive pressure mediated by the hypoxic/acidic metabolism, particularly considering the potential combination of this strategy with emerging immune checkpoint-based immunotherapies.
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Project description:Background Esophageal cancer (EC) is a highly aggressive malignancy that is classified as esophageal squamous cell carcinoma (ESCC) and esophageal adenocarcinoma (EAC). Infiltrating stromal/immune cells, a major component of the tumor immune microenvironment (TIME), have prognostic significance in various cancers. Methods In this study we investigated genes and immune factors in the tumor microenvironment (TME) of ESCC and EAC that can serve as prognostic biomarkers. Stromal and immune scores were calculated using the Estimation of Stromal and Immune Cells in Malignant Tumor Tissues Using Expression Data (ESTIMATE) algorithm based on gene expression profiles of patient-derived tumor tissues in The Cancer Genome Atlas database. The correlation between ESTIMATE scores and survival rates in EC were analyzed. A comparison of high and low stromal/immune score groups revealed multiple differentially expressed genes (DEGs) as candidate prognostic genes; their role in immune-related biological processes was evaluated by functional and protein-protein interaction (PPI) network analyses, and the genes were validated using Gene Expression Omnibus datasets. Additionally, 22 tumor-infiltrating immune cell (TIIC) subsets were analyzed using the CIBERSORT algorithm. Results Median stromal score was higher whereas immune score was lower in ESCC than in EAC (both P<0.01). Stromal score was lower in female as compared to male ESCC patients (P<0.05), and was significantly correlated with T stage (P<0.05). In EAC, median immune score was higher in female as compared to male patients (P<0.05) and was correlated with tumor-node-metastasis stage (P<0.05). The identified DEGs were mainly involved in lymphocyte (especially T-lymphocyte) activation and carbohydrate binding. Moreover, the levels of infiltrating resting-stage dendritic cells, CD8+ T cells, naïve B cells, activated mast cells, and resting memory CD4+ T cells were significantly correlated with EC prognosis (P<0.05). Conclusions The immune microenvironment of ESCC and EAC are quite different. We have found genes with prognostic value in multiple tumor databases.
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Project description:Background: The tumor immune microenvironment (TIME) is an external immune system that regulates tumorigenesis. However, cellular interactions involving the TIME in hepatocellular carcinoma (HCC) are poorly characterized. Methods: In this study, we used multidimensional bioinformatic methods to comprehensively analyze cellular TIME characteristics in 735 HCC patients. Additionally, we explored associations involving TIME molecular subtypes and gene types and clinicopathological features to construct a prognostic signature. Results: Based on their characteristics, we classified TIME and gene signatures into three phenotypes (TIME T1-3) and two gene clusters (Gene G1-2), respectively. Further analysis revealed that Gene G1 was associated with immune activation and surveillance and included CD8+ T cells, natural killer cell activation, and activated CD4+ memory T cells. In contrast, Gene G2 was characterized by increased M0 macrophage and regulatory T cell levels. After calculation of principal component algorithms, a TIME score (TS) model, including 78 differentially expressed genes, was constructed based on TIME phenotypes and gene clusters. Furthermore, we observed that the Gene G2 cluster was characterized by high TS, and Gene G1 was characterized by low TS, which correlated with poor and favorable prognosis of HCC, respectively. Correlation analysis showed that TS had a positive association with several clinicopathologic signatures [such as grade, stage, tumor (T), and node (N)] and known somatic gene mutations (such as TP53 and CTNNB1). The prognostic value of the TS model was verified using external data sets. Conclusion: We constructed a TS model based on differentially expressed genes and involving immune phenotypes and demonstrated that the TS model is an effective prognostic biomarker and predictor for HCC patients.
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Project description:The tumor microenvironment is closely related to the progression and immune escape of tumor cells. Tumor-infiltrating immune cells (TIICs) and immune-related genes (IRGs) are indispensable components of the tumor microenvironment and have been demonstrated to be highly valuable in determining the prognosis of multiple cancers. To elucidate the prognostic value of TIICs and IRGs in gastric cancer, we conducted a comprehensive analysis focusing on the abundances of 22 types of TIICs and differentially expressed IRGs based on a dataset from The Cancer Genome Atlas (TCGA). The results showed that great composition differences in TIICs and immune cell subfractions were associated with survival outcomes in different stages. Additionally, 29 hub genes were characterized from 345 differentially expressed IRGs and found to be significantly associated with survival outcomes. Then, an independent prognostic indicator based on ten IRGs was successfully constructed after multivariate adjustment for some clinical parameters. Further validation revealed that these hub IRGs could reflect the infiltration levels of immune cells. Thus, our results confirmed the clinical significance of TIICs and IRGs in gastric cancer and may establish a foundation for further exploring immune cell and gene targets for personalized treatment.
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Project description:Liver cancer has the fourth highest mortality rate of all cancers worldwide, with hepatocellular carcinoma (HCC) being the most prevalent subtype. Despite great advances in systemic therapy, such as molecular-targeted agents, HCC has one of the worst prognoses due to drug resistance and frequent recurrence and metastasis. Recently, new therapeutic strategies such as cancer immunosuppressive therapy have prolonged patients' lives, and the combination of an immune checkpoint inhibitor (ICI) and VEGF inhibitor is now positioned as the first-line therapy for advanced HCC. Since the efficacy of ICIs depends on the tumor immune microenvironment, it is necessary to elucidate the immune environment of HCC to select appropriate ICIs. In this review, we summarize the findings on the immune microenvironment and immunosuppressive approaches focused on monoclonal antibodies against cytotoxic T lymphocyte-associated protein 4 and programmed cell death protein 1 for HCC. We also describe ongoing treatment modalities, including adoptive cell transfer-based therapies and future areas of exploration based on recent literature. The results of pre-clinical studies using immunological classification and animal models will contribute to the development of biomarkers that predict the efficacy of immunosuppressive therapy and aid in the selection of appropriate strategies for HCC treatment.
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Project description:It is crucial to grasp the characteristics of tumour immune microenvironment to improve effects of immunotherapy. In this study, the immune and stromal scores of 371 cases were calculated for quantitative analysis of immune and stromal cell infiltration in the tumour microenvironment of hepatocellular carcinoma (HCC). The weighted gene co-expression network analysis and protein-protein interaction network were analysed to identify immune microenvironment-related genes. The results showed that patients with high immune scores had a higher 4-year recurrence-free rate. TP53, CTNNB1, and AXIN1 mutations significantly varied with immune scores. In immune score-related modules analysis, Kyoto encyclopaedia of genes and genomes pathways and gene ontology terms were closely related to immune processes, tumorigenesis, and metastasis. Twelve new immune microenvironment-related genes were identified and had significantly positive correlations with seven immune checkpoint genes. In prognostic analysis, eleven immune microenvironment-related genes exhibited high expression, nine of which were validated in the GSE62232 dataset and were significantly associated with a good prognosis. Our findings suggest that calculating immune score and stromal score could help to determine tumour purity and immune cell infiltration in the tumour microenvironment. Nine immune microenvironment-related genes identified in this study had potential as prognostic markers for HCC.
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Project description: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.
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