scholarly journals USH2A Mutation is Associated With Tumor Mutation Burden and Antitumor Immunity in Patients With Colon Adenocarcinoma

2021 ◽  
Vol 12 ◽  
Author(s):  
Yuanyuan Sun ◽  
Long Li ◽  
Wenchao Yao ◽  
Xuxu Liu ◽  
Yang Yang ◽  
...  
Keyword(s):  
Immune Response ◽  
Immune Checkpoint ◽  
Antitumor Immunity ◽  
Gene Mutations ◽  
Colon Adenocarcinoma ◽  
Cancer Genome ◽  
Gene Set Enrichment Analysis ◽  
Cox Analysis ◽  
Immune Score ◽  
Differential Genes

Colon adenocarcinoma (COAD) is one of the diseases with the highest morbidity and mortality in the world. At present, immunotherapy has become a valuable method for the treatment of COAD. Tumor mutational burden (TMB) is considered to be the most common biomarker for predicting immunotherapy. According to reports, the mutation rate of COAD ranks third. However, whether these gene mutations are related to TMB and immune response is still unknown. Here, COAD somatic mutation data were downloaded from The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) databases. Bioinformatics methods were used to study the relationships among gene mutations, COAD survival prognosis, and tumor immune response. A total of 22 of the top 40 mutations in TCGA and ICGC databases were the same. Among them, the USH2A mutation was associated with high TMB and poor clinical prognosis. According to Gene Set Enrichment Analysis (GSEA) and the CIBERSORT algorithm, we determined that the USH2A mutation upregulates signaling pathways involved in the immune system and the antitumor immune response. In cases with a USH2A mutation, the immune score and MSI score of TCGA samples increased, the expression of immune checkpoint genes decreased significantly, and the TIDE score decreased significantly. Dependent on the presence or absence of a USH2A mutation, TCGA COAD samples were analyzed for differentially expressed genes, 522 of which were identified. Using a univariate Cox analysis and LASSO COX analysis of these differential genes, a prediction model was established, which established significant differences in the infiltration of immune cells, immune checkpoint gene expression, immune score, MSI score, TMB, and TIDE in patients in high- and low-risk groups. In conclusion, mutation of USH2A is frequent in COAD and is related to an increase in TMB and the antitumor immunity. The differential genes screened by USH2A mutation allowed the construction of a risk model for predicting the survival and prognosis of cancer patients, in addition to providing new ideas for COAD immunotherapy.

scholarly journals Analysis of Interleukin-1 Signaling Alterations of Colon Adenocarcinoma Identified Implications for Immunotherapy

2021 ◽  
Vol 12 ◽  
Author(s):  
Xiaogang Zhou ◽  
Yu Liu ◽  
Jing Xiang ◽  
Yuntao Wang ◽  
Qiqian Wang ◽  
...  
Keyword(s):  
Immune Response ◽  
T Cells ◽  
Immune Checkpoint ◽  
Cox Regression ◽  
Independent Predictor ◽  
Colon Adenocarcinoma ◽  
Gene Set Enrichment Analysis ◽  
Clinical Effects ◽  
Proinflammatory Mediators ◽  
Mutation Data

Immune checkpoint inhibitors (ICIs) have made breakthrough progress in the treatment of various malignant tumors. However, only some patients receiving ICIs obtain long-lasting clinical effects, and some patients still do not achieve remission. Improving the treatment benefits of this part of the population has become a concern of clinicians. IL-1 signaling plays an important role in the tumor microenvironment (TME). However, the relationship between the IL-1 signaling mutation status and the prognosis of colon adenocarcinoma (COAD) patients receiving ICIs has not been reported. We downloaded the data of a COAD cohort receiving ICIs, including prognostic data and mutation data. Additionally, we downloaded the data of a COAD cohort from The Cancer Genome Atlas (TCGA) database, including clinical data, expression data and mutation data. Gene set enrichment analysis (GSEA) was used to assess differences in the activity of some key physiological pathways between the IL-1 signaling mutated-type (IL-1-MT) and IL-1 signaling wild-type (IL-1-WT) groups. The CIBERSORT algorithm was used to evaluate the contents of immune cells in the TME of COAD patients. The multivariate Cox regression model results suggested that IL-1-MT can be used as an independent predictor of a better prognosis in COAD patients receiving ICIs (P = 0.03, HR = 0.269, 95% CI: 0.082-0.883). Additionally, IL-1-MT COAD patients had significantly longer overall survival (OS) (log-rank P = 0.015). CIBERSORT analysis showed that the IL-1-MT group had high infiltration levels of activated dendritic cells (DCs), M1 macrophages, neutrophils, activated natural killer (NK) cells, activated CD4+ memory T cells and CD8+ T cells. Similarly, the IL-1-MT group had significantly upregulated immunogenicity, including in terms of the tumor mutation burden (TMB), neoantigen load (NAL) and number of mutations in DNA damage repair (DDR) signaling. GSEA showed that the IL-1-MT group was highly enriched in the immune response and proinflammatory mediators. Additionally, the expression levels of immune-related genes, immune checkpoint molecules and immune-related signatures were significantly higher in the IL-1-MT group than in the IL-1-WT group. IL-1-MT may be an independent predictor of a good prognosis in COAD patients receiving ICIs, with significantly longer OS in IL-1-MT COAD patients. Additionally, IL-1-MT was associated with significantly increased immunogenicity, activated immune cell and inflammatory mediator levels and immune response-related scores.

scholarly journals Identification Sixteen Metabolic Genes as Potential Biomarkers for Colon Adenocarcinoma 

2020 ◽  
Author(s):  
Binbin Cui ◽  
Fuqiang Zhao ◽  
Yanlong Liu ◽  
Xinyue Gu ◽  
Bomiao Zhang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Overall Survival ◽  
Risk Score ◽  
Cox Regression ◽  
Colon Adenocarcinoma ◽  
Curve Analysis ◽  
Gene Set Enrichment Analysis ◽  
Risk Scores ◽  
Metabolic Genes ◽  
Cox Analysis

Abstract Purpose Colon adenocarcinoma (COAD) is the most common primary malignant tumor of the digestive tract. It is still important to find important markers that affect the prognosis of COAD. This research aims to identify some key prognosis-related metabolic genes (PRMG) and establish a clinical prognosis model for COAD patients. Method We used The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) to obtain gene expression profiles of COAD, and then identified differentially expressed prognostic-related metabolic genes through R language and Perl software, Through univariate Cox analysis and least absolute shrinkage and selection operator (LASSO) Cox analysis to obtain target genes, established metabolic genes prognostic models and risk scores. Through COX regression analysis, independent risk factors affecting the prognosis of COAD were analyzed, and Receiver Operating Characteristic (ROC) curve analysis of independent prognostic factors was performed and a nomogram for predicting overall survival was constructed. Perform the consistency index (C-index) test and decision curve analysis (DCA) on the nomogram, and use Gene Set Enrichment Analysis (GSEA) to identify the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway of model genes. Result We selected PRMG based on the expression of metabolic genes, and used LASSO Cox regression to construct 16 metabolic gene (SEPHS1, P4HA1, ENPP2, PTGDS, GPX3, CP, ASPA, POLR3A, PKM, POLR2D , XDH, EPHX2, ADH1B, HMGCL, GPD1L and MAOA) models. The risk score generated from our model can well predict the survival prognosis of COAD. A nomogram based on the clinicopathological characteristics and risk scores of COAD can personally predict the overall survival rate of COAD patients. Conclusion We comprehensively identified metabolic genes related to the prognosis of COAD. The risk score based on the expression of 16 metabolic genes can effectively predict the prognosis of patients with COAD.

scholarly journals MUC4 mutation correlates with tumor mutation burden and the immune microenvironment in colorectal cancer

2020 ◽  
Author(s):  
Ting Li ◽  
Wenjia Hui ◽  
Halina Halike ◽  
Feng Gao
Keyword(s):  
Colorectal Cancer ◽  
Immune Response ◽  
T Cells ◽  
Immune Cells ◽  
Gene Mutations ◽  
Cancer Genome ◽  
Immune Microenvironment ◽  
Tumor Mutation Burden ◽  
Mutation Burden ◽  
Mutant Genes

Abstract Background: Immunotherapy is a new strategy for Colorectal cancer (CRC) treatment. Tumor mutation burden (TMB) may act as an emerging biomarker for predicting responses to immunotherapy. Nevertheless, no studies investigate if these gene mutations correlate to TMB and tumor-infiltrating immune cells. Methods: Somatic mutation data for CRC samples were obtained from The Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC) datasets. Then, we investigated the relationship between these mutant genes, TMB and overall survival outcomes. GSEA analysis was performed to explore the underlying mechanism of mutant gene. Finally, we further verified the connection between gene mutations and immune response.Results: We identified 17 common mutant genes shared by both two cohorts. Further analysis found that MUC4 mutation was strongly related to higher TMB and predicted a poorer prognosis. Moreover, functional enrichment analysis of samples with MUC4 mutation revealed that they were involved in regulating the natural killer cell mediated cytotoxicity signaling pathway. Significant changes in the proportion of the immune cells of CD8 T cells, activated NK cells, M1 macrophages and resting memory CD4 T cells were observed using the CIBERSORT algorithm. Conclusions: Our research revealed that MUC4 mutation significantly correlated with increased TMB, a worse prognosis and modulating the immune microenvironment, which may be considered a biomarker to predict the outcome of the immune response in colorectal cancer.

scholarly journals Prognostic Biomarker MUC4 Mutations in Colon Adenocarcinoma Correlating with Tumor Microenvironment

2021 ◽  
Author(s):  
Ting Li ◽  
Wenjia Hui ◽  
Feng Gao
Keyword(s):  
Colorectal Cancer ◽  
Immune Response ◽  
T Cells ◽  
Immune Cells ◽  
Killer Cell ◽  
Gene Mutations ◽  
Cancer Genome ◽  
The Cancer Genome Atlas ◽  
Functional Enrichment ◽  
Mutant Genes

Abstract Background: Immunotherapy is a new strategy for Colorectal cancer (CRC) treatment. Tumor mutation burden (TMB) may act as an emerging biomarker for predicting responses to immunotherapy. Nevertheless, no studies investigate if these gene mutations correlate to TMB and tumor-infiltrating immune cells. Methods: Somatic mutation data for CRC samples were obtained from The Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC) datasets. Then, we investigated the relationship between these mutant genes, TMB and overall survival outcomes. GSEA analysis was performed to explore the underlying mechanism of mutant gene. Finally, we further verified the connection between gene mutations and immune response.Results: We identified 17 common mutant genes shared by both two cohorts. Further analysis found that MUC4 mutation was strongly related to higher TMB and predicted a poorer prognosis. Moreover, functional enrichment analysis of samples with MUC4 mutation revealed that they were involved in regulating the natural killer cell mediated cytotoxicity signaling pathway. Significant changes in the proportion of the immune cells of CD8+ T cells, activated NK cells, M1 macrophages and resting memory CD4+ T cells were observed using the CIBERSORT algorithm. Conclusions: Our research revealed that MUC4 mutation significantly correlated with increased TMB, a worse prognosis and modulating the immune microenvironment, which may be considered a biomarker to predict the outcome of the immune response in colorectal cancer.

scholarly journals Bioinformatic Analysis of Immune Significance of RYR2 Mutation in Breast Cancer

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Zhiquan Xu ◽  
Ling Xiang ◽  
Rong Wang ◽  
Yongfu Xiong ◽  
He Zhou ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Immune Response ◽  
T Cells ◽  
Immune Cell ◽  
Cox Regression ◽  
Cancer Genome ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Specific Gene ◽  
Clinical Prognosis

Background. Currently, immunotherapy is widely used for breast cancer (BC) patients, and tumor mutation burden (TMB) is regarded as a valuable independent predictor of response to immunotherapy. However, specific gene mutations and their relationship with TMB and tumor-infiltrating immune cells in BC are not fully understood. Methods. Comprehensive bioinformatic analyses were performed using data from The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) datasets. Survival curves were analyzed via Kaplan-Meier analysis. Univariate and multivariate Cox regression analyses were used for prognosis analysis. Gene set enrichment analysis (GSEA) was performed to explore regulatory mechanisms and functions. The CIBERSORT algorithm was used to calculate the tumor-infiltrating immune cell fractions. Results. We analyzed somatic mutation data of BC from TCGA and ICGC datasets and found that 19 frequently mutated genes were reported in both cohorts, namely, SPTA1, TTN, MUC17, MAP3K1, CDH1, FAT3, SYNE1, FLG, HMCN1, RYR2 (ryanodine receptor 2), GATA3, MUC4, PIK3CA, KMT2C, TP53, PTEN, ZFHX4, MUC16, and USH2A. Among them, we observed that RYR2 mutation was significantly associated with higher TMB and better clinical prognosis. Moreover, GSEA revealed that RYR2 mutation-enriched signaling pathways were related to immune-associated pathways. Furthermore, based on the CIBERSORT algorithm, we found that RYR2 mutation enhanced the antitumor immune response by enriching CD8+ T cells, activated memory CD4+ T cells, and M1 macrophages. Conclusion. RYR2 is frequently mutated in BC, and its mutation is related to increased TMB and promotes antitumor immunity; thus, RYR2 may serve as a valuable biomarker to predict the immune response.

scholarly journals Significance of KDM6A mutation in bladder cancer immune escape

BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Xingxing Chen ◽  
Xuehua Lin ◽  
Guofu Pang ◽  
Jian Deng ◽  
Qun Xie ◽  
...  
Keyword(s):  
Immune Response ◽  
Bladder Cancer ◽  
Immune Escape ◽  
Tumour Progression ◽  
Mrna Level ◽  
Enrichment Analysis ◽  
Cancer Genome ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Recurrence Rates

Abstract Background Bladder cancer (BC) is the fourth most prevalent neoplasm in men and is associated with high tumour recurrence rates, leading to major treatment challenges. Lysine-specific demethylase 6A (KDM6A) is frequently mutated in several cancer types; however, its effects on tumour progression and clinical outcome in BC remain unclear. Here, we explored the potential role of KDM6A in regulating the antitumor immune response. Methods We mined The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) databases for somatic mutation and clinical data in patients with BC. Results We found frequent mutations in 12 genes in both cohorts, including TP53, KDM6A, CSMD3, MUC16, STAG2, PIK3CA, ARID1A, RB1, EP300, ERBB2, ERBB3, and FGFR3. The frequency o KDM6A mutations in the TCGA and ICGC datasets was 25.97 and 24.27%, respectively. In addition, KDM6A mutation was associated with a lower number of tumour-infiltrating immune cells (TIICs) and indicated a state of immune tolerance. KDM6A mutation was associated with lower KDM6A mRNA level compared with that in samples carrying the wild-type gene. Further, survival analysis showed that the prognosis of patients with low KDM6A expression was worse than that with high KDM6A expression. Using the CIBERSORT algorithm, Tumor Immune Estimation Resource site, and Gene Set Enrichment Analysis, we found that KDM6A mutation downregulated nine signalling pathways that participate in the immune system and attenuated the tumour immune response. Conclusion Overall, we conclude that KDM6A mutation is frequent in BC and promotes tumour immune escape, which may serve as a novel biomarker to predict the immune response.

scholarly journals Identification of Metabolism-Associated Prostate Cancer Subtypes and Construction of a Prognostic Risk Model

2020 ◽  
Vol 10 ◽  
Author(s):  
Yanlong Zhang ◽  
Ruiqiao Zhang ◽  
Fangzhi Liang ◽  
Liyun Zhang ◽  
Xuezhi Liang
Keyword(s):  
Prostate Cancer ◽  
Drug Sensitivity ◽  
Risk Model ◽  
External Validation ◽  
Disease Free Survival ◽  
Cancer Genome ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Predictive Values ◽  
Cox Analysis

BackgroundDespite being the second most common tumor in men worldwide, the tumor metabolism-associated mechanisms of prostate cancer (PCa) remain unclear. Herein, this study aimed to investigate the metabolism-associated characteristics of PCa and to develop a metabolism-associated prognostic risk model for patients with PCa.MethodsThe activity levels of PCa metabolic pathways were determined using mRNA expression profiling of The Cancer Genome Atlas Prostate Adenocarcinoma cohort via single-sample gene set enrichment analysis (ssGSEA). The analyzed samples were divided into three subtypes based on the partitioning around medication algorithm. Tumor characteristics of the subsets were then investigated using t-distributed stochastic neighbor embedding (t-SNE) analysis, differential analysis, Kaplan–Meier survival analysis, and GSEA. Finally, we developed and validated a metabolism-associated prognostic risk model using weighted gene co-expression network analysis, univariate Cox analysis, least absolute shrinkage and selection operator, and multivariate Cox analysis. Other cohorts (GSE54460, GSE70768, genotype-tissue expression, and International Cancer Genome Consortium) were utilized for external validation. Drug sensibility analysis was performed on Genomics of Drug Sensitivity in Cancer and GSE78220 datasets. In total, 1,039 samples and six cell lines were concluded in our work.ResultsThree metabolism-associated clusters with significantly different characteristics in disease-free survival (DFS), clinical stage, stemness index, tumor microenvironment including stromal and immune cells, DNA mutation (TP53 and SPOP), copy number variation, and microsatellite instability were identified in PCa. Eighty-four of the metabolism-associated module genes were narrowed to a six-gene signature associated with DFS, CACNG4, SLC2A4, EPHX2, CA14, NUDT7, and ADH5 (p <0.05). A risk model was developed, and external validation revealed the strong robustness our risk model possessed in diagnosis and prognosis as well as the association with the cancer feature of drug sensitivity.ConclusionsThe identified metabolism-associated subtypes reflected the pathogenesis, essential features, and heterogeneity of PCa tumors. Our metabolism-associated risk model may provide clinicians with predictive values for diagnosis, prognosis, and treatment guidance in patients with PCa.

scholarly journals Significance of KDM6A Mutation in Bladder Cancer Immune Escape

2020 ◽  
Author(s):  
Xingxing Chen ◽  
Zhengrong Zhang ◽  
Guofu Pang ◽  
Xuehua Lin ◽  
Qun Xie ◽  
...  
Keyword(s):  
Immune Response ◽  
Bladder Cancer ◽  
Immune Escape ◽  
Tumour Progression ◽  
Enrichment Analysis ◽  
Cancer Genome ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Recurrence Rates ◽  
Frequent Mutations

Abstract Background: Bladder cancer (BC)is the fourth most prevalent neoplasm in menand is associated with high tumour recurrence rates, leading to major treatment challenges. Lysine-specific demethylase 6A (KDM6A) is frequently mutated in several cancer types; however, its effects on tumour progression and clinical outcome in BCremain unclear. Here, we explored the potential role of KDM6A in regulating the antitumor immune response. Methods: We mined The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) databases for somatic mutation and clinical data in patients with BC.Results: We found frequent mutations in 12 genes in both cohorts, including TP53, KDM6A, CSMD3, MUC16, STAG2, PIK3CA, ARID1A, RB1, EP300, ERBB2, ERBB3, and FGFR3. The frequency of KDM6A mutationsin the TCGA and ICGC datasets was 25.97% and 24.27%, respectively. In addition, KDM6A mutation was associated with a lower number oftumour-infiltrating lymphocytes and indicated a state ofimmunetolerance. KDM6A mutation was associated with lower KDM6A expression level compared with that in samples carrying the wild-type gene. Further, survival analysis showed that the prognosis of patients with low KDM6Aexpression was worse than that withhigh KDM6A expression. Using the CIBERSORT algorithm, Tumor Immune Estimation Resource site, and Gene Set Enrichment Analysis, we found that KDM6A mutation downregulated nine signalling pathways that participate in the immune system and attenuated the tumour immune response. Conclusion: Overall, we conclude that KDM6A mutation is frequent in BC and promotes tumour immune escape, which may serve as a novel biomarker to predict the immune response.

scholarly journals EPHA5 mutation predicts the durable clinical benefit of immune checkpoint inhibitors in patients with lung adenocarcinoma

2020 ◽  
Author(s):  
Weimei Huang ◽  
Anqi Lin ◽  
Peng Luo ◽  
Weiliang Zhu ◽  
Ting Wei ◽  
...  
Keyword(s):  
Gene Expression ◽  
Immune Response ◽  
Lung Adenocarcinoma ◽  
Immune Checkpoint ◽  
Clinical Benefit ◽  
Drug Sensitivity ◽  
Checkpoint Inhibitors ◽  
Gene Set Enrichment Analysis ◽  
Wild Type ◽  
Multiple Drugs

Abstract Background: Immune checkpoint inhibitor (ICI ) therapy has shown remarkable clinical benefit in lung adenocarcinoma (LUAD) patients. Genomic mutations may be applicable to predict the response to ICIs. Eph receptor A5 (EPHA5) is frequently mutated in breast cancer, lung cancer and other tumors; however, its association with outcome in patients who receive immunotherapy remains unknown. Methods: Somatic mutation data, gene expression data and clinicopathologic information were curated from patients with LUAD who were treated with ICI therapy (MSKCC ICI-treated cohort) and patients with LUAD who did not receive ICI therapy (TCGA-LUAD cohort). The CIBERSORT and gene set enrichment analysis (GSEA) algorithms were separately used to infer the relative abundance of leukocytes and significantly enriched pathways in the defined subgroups. Tumor mutation burden (TMB), tumor neoantigen load, the fraction of copy number variants (CNVs), the mutation frequency of DNA damage repair (DDR) genes, and the prognosis of patients were compared between the EPHA5-mutated subgroup and the EPHA5 wild - type subgroup. Whole-exome sequencing (WES) data and drug sensitivity data downloaded from the Genomics of Drug Sensitivity in Cancer (GDSC) database were used to evaluate the relationship of the 50% inhibitory concentration (IC50) of multiple drugs and the EPHA5 mutation status in LUAD cells. Results: EPHA5 mutations were associated with increased TMB, neoantigen load, levels of immune - related gene expression signatures, and enhanced tumor-infiltrating lymphocytes (TILs). Patients with EPHA5 mutations in the immunotherapy cohort achieved a longer progression - free survival (PFS) time than patients with wild-type EPHA5. Immune response pathways were among the top enriched pathways in samples with EPHA5 mutations. In addition , patients with EPHA5 mutations tended to be more sensitive to certain targeted molecular inhibitors , including serdemetan, lox2 and PF1-1. Conclusion: Our results suggest that identifying mutations in the EPHA5 gene may provide insight into the genome-wide mutational burden and may serve as a biomarker to predict the immune response of patients with LUAD.

scholarly journals Identification of Immune Subtypes for Predicting the Prognosis of Patients in Head and Neck Squamous Cell Carcinoma

2021 ◽  
Vol 20 ◽  
pp. 153303382110458
Author(s):  
Jing Sun ◽  
Guiqing Fang ◽  
Zhibin Zuo ◽  
Xijiao Yu ◽  
Lande Xue ◽  
...  
Keyword(s):  
Gene Expression ◽  
Immune Response ◽  
Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Head And Neck ◽  
Squamous Cell ◽  
Immune Checkpoint ◽  
Gene Set Enrichment Analysis ◽  
Neck Squamous Cell Carcinoma ◽  
The Relationship

Head and neck squamous cell carcinoma (HNSCC) is a common malignancy with poor prognosis and immune response, which plays an important role in tumor progression. Recently, immunotherapies have revolutionized the therapeutic means of malignancies including HNSCC. However, the relationship between immunophenotypes of HNSCC and its clinical response to immune-checkpoint inhibitors remains unclear. We aim to identify molecular subtyping related to distinct immunophenotypes in HNSCC. Consensus clustering algorithm was conducted for subtyping. Immunophenotypes between subtypes were compared according to infiltrating immunocytes, immune reactions, major histocompatibility complex (MHC) family, immunoinhibitory, immunostimulatory and immune scores. The relationship between immunophenotype and genotype was investigated from gene mutation and tumor mutation burden. The potential response of Immune-checkpoint blockade (ICB) therapy was estimated with TIDE and ImmuCellAI algorithms, and immune-checkpoint genes. The immune characteristics were also investigated. Biological functions were annotated by the gene-set enrichment analysis (GSEA) algorithm. Two distinct immune subtypes of HNSCC with different survival outcomes, biological characteristics, immunophenotype, and ICB response were identified. The subtype-1 was featured with better prognosis, more infiltrated immunocytes, stronger immune reaction, higher immune-related gene expression, higher immune-checkpoint gene expression (PD-1, PD-L1, and CTLA-4), and better ICB response. A higher immune response in subtype-1 was also revealed by GSEA. Subtype-1 possessed a higher immune response and more sensitivity to ICB therapy leading to a better prognosis. These findings may shed promising light on the immunotherapy strategy in HNSCC

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