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

scholarly journals Gene Model Related to m6A Predicts the Prognostic Effect of Immune Infiltration on Head and Neck Squamous Cell Carcinoma

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Yaping Deng ◽  
Kehua Li ◽  
Fengwu Tan ◽  
Hanbo Liu
Keyword(s):  
Immune Response ◽  
Squamous Cell Carcinoma ◽  
High Risk ◽  
Cell Carcinoma ◽  
Head And Neck ◽  
Risk Score ◽  
Squamous Cell ◽  
Immune Checkpoint ◽  
Neck Squamous Cell Carcinoma ◽  
Immune Microenvironment

Head and neck squamous cell carcinoma (HNSCC) is a highly aggressive solid tumor. Because most studies have focused on the intrinsic carcinogenic pathways of tumors, we focused on the relationship between N6-methyladenosine (m6A) and the prognosis of HNSCC in the tumor immune microenvironment. We downloaded RNA-seq data from the TCGA dataset and used univariate Cox regression to screen m6A-related lncRNAs. The expression value of LASSO-screened genes was the sum of LASSO regression coefficients. We then evaluated relationships between the risk score and cellular components or cellular immune response. Differences in immune response under various algorithms were visualized with heat maps. The GSVA package in R was used to analyze GO, BP, KEGG, and hallmark gene sets of immune checkpoint clusters and immune checkpoint scores. The GSEA analysis was performed with the cluster profile package, yielding 21 m6A genes. Related lncRNAs were screened with Pearson’s correlations, and the resulting 442 lncRNAs were screened using single-factor analysis. Eight lncRNAs closely related to prognosis were identified through survival random forest. Survival analysis showed that patients with a high risk score had a poor prognosis. Low- and high-risk-score groups differed significantly in m6A gene expression. Prognostic scores from different algorithms were significantly correlated with B cells, T cells, and memory cells in the immune microenvironment. Expression of immune checkpoints and signal pathways differed significantly across risk-score groups, suggesting that m6A could mediate lncRNA-induced immune system dysfunction and affect HNSCC development. A comprehensive study of tumor-cell immune characteristics should provide more insight into the complex immune microenvironment, thus contributing to the development of new immunotherapeutic agents.

scholarly journals Fifteen mRNA-lncRNA expression-based signature predicted the survival of late-staged head and neck squamous cell carcinoma

2020 ◽  
Vol 40 (7) ◽  
Author(s):  
He Ren ◽  
Huaping Li ◽  
Ping Li ◽  
Yuhui Xu ◽  
Gang Liu ◽  
...  
Keyword(s):  
Gene Expression ◽  
Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Head And Neck ◽  
Median Survival ◽  
Squamous Cell ◽  
Gene Set Enrichment Analysis ◽  
The Other ◽  
Neck Squamous Cell Carcinoma ◽  
Better Than

Abstract Background: Gene expression is necessary for regulation in almost all biological processes, at the same time, it is related to the prognosis for head and neck squamous cell carcinoma (HNSCC). The prognosis of late-staged HNSCC is important because of its guiding significance on the therapy strategies. Methods: In this work, we analyzed the relationship between gene expression and HNSCC in The Cancer Genome Atlas (TCGA) cohort, and optimized the panel with random forest survival analysis. Subsequently, a Cox multivariate regression-based model was developed to predict the clinical outcome of HNSCC. The performance of the model was assayed in the training cohort and validated in another three independent cohorts (GSE41614, E-TABM-302, E-MTAB-1328). The underlying pathways significantly associated with the model were identified. According to the results, patients of low-score group (median survival months: 27.4, 95% CI: 18.2–43) had a significant poor survival than those of high-score group (median survival months: 69.4, 95% CI: 58.7–72.1, P=2.7e-5), and the observation was repeatable in the other validation cohorts. Further analysis revealed that the model performed better than the other clinical indicators and is independent of these indicators. Results: Comparison revealed that the model performed better than existing models for late HNSCC prognosis. Gene set enrichment analysis (GSEA) elucidated that the model was significantly associated with various cell processes and pathways.

scholarly journals HLF is a Potential Prognostic Biomarker in Head and Neck Squamous Cell Carcinoma Based on Bioinformatic Analysis and Experimental Validation

2020 ◽  
Author(s):  
Wei Fang ◽  
Di Wan ◽  
Jun Chen ◽  
Weiqun Ma ◽  
Zhen Luo ◽  
...  
Keyword(s):  
Gene Expression ◽  
Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Head And Neck ◽  
Squamous Cell ◽  
Immunohistochemical Staining ◽  
Prognostic Biomarker ◽  
Neck Squamous Cell Carcinoma ◽  
Rt Pcr ◽  
The Relationship

Abstract BackgroundHead and neck squamous cell carcinoma (HNSCC) is one of the most frequent cancers worldwide, with an increasing incidence. However, the underlying molecular mechanisms of HNSCC are poorly understood.MethodIn this work, 5 original datasets (GSE23558, GSE13601, GSE30784, GSE9844, GSE78060) of Head and neck squamous cell carcinoma (HNSCC) were selected from Gene Expression Omnibus (GEO) database. To identify differentially expressed genes (DEGs) in HNSCC and adjacent tissues. The common DEGs were acquired by Venn diagram. The sensitivity and specificity of HLF were determined by Receiver operating characteristic curves (ROC). Then, In order to further confirm the relationship between HLF and HNSCC patient’s prognosis, the expression and survival analysis of HLF was performed by Gene Expression Profiling Interactive Analysis (GEPIA), Cell culture, reverse transcription polymerase chain reaction (RT-PCR), western blotting and immunohistochemical staining.ResultsSeventeen DEGs were screened from five sets of HNSCC functional gene expression series in GEO datasets. The low expression of HLF was indicated might be correlated with poor prognosis of HNSCC patients based on the bioinformatics analysis. According to the results of Cell culture, RT-PCR, western blotting, immunohistochemical staining, it was confirmed that the low level of HLF expression correlated with poor prognosis of HNSCC patients.ConclusionThe study effectively revealed useful information about the relationship of the low level of HLF expression and HNSCC. In summary, we identified HLF as a potential prognostic biomarker and therapeutic target for HNSCC.

scholarly journals Bioinformatics analysis of DNMT1 expression and its role in head and neck squamous cell carcinoma prognosis

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Jili Cui ◽  
Lian Zheng ◽  
Yuanyuan Zhang ◽  
Miaomiao Xue
Keyword(s):  
Gene Expression ◽  
Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Head And Neck ◽  
Squamous Cell ◽  
Immune Cell ◽  
Neck Squamous Cell Carcinoma ◽  
Hub Genes ◽  
Significant Difference ◽  
Dnmt1 Expression

AbstractHead and neck squamous cell carcinoma (HNSCC) is the sixth most common type of malignancy in the world. DNA cytosine-5-methyltransferase 1 (DNMT1) play key roles in carcinogenesis and regulation of the immune micro-environment, but the gene expression and the role of DNMT1 in HNSCC is unknown. In this study, we utilized online tools and databases for pan-cancer and HNSCC analysis of DNMT1 expression and its association with clinical cancer characteristics. We also identified genes that positively and negatively correlated with DNMT1 expression and identified eight hub genes based on protein–protein interaction (PPI) network analysis. Enrichment analyses were performed to explore the biological functions related with of DNMT1. The Tumor Immune Estimation Resource (TIMER) database was performed to explore the relationship between DNMT1 expression and immune-cell infiltration. We demonstrated that DNMT1 gene expression was upregulated in HNSCC and associated with poor prognosis. Based on analysis of the eight hub genes, we determined that DNMT1 may be involved in cell cycle, proliferation and metabolic related pathways. We also found that significant difference of B cells infiltration based on TP 53 mutation. These findings suggest that DNMT1 related epigenetic alterations have close relationship with HNSCC progression, and DNMT1 could be a novel diagnostic biomarker and a promising therapeutic target for HNSCC.

scholarly journals YRNAs: New Insights and Potential Novel Approach in Head and Neck Squamous Cell Carcinoma

Cells ◽  
2020 ◽  
Vol 9 (5) ◽  
pp. 1281 ◽  
Author(s):  
Kacper Guglas ◽  
Tomasz Kolenda ◽  
Maciej Stasiak ◽  
Magda Kopczyńska ◽  
Anna Teresiak ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Head And Neck ◽  
Cell Lines ◽  
Squamous Cell ◽  
Gene Set Enrichment Analysis ◽  
Neck Squamous Cell Carcinoma ◽  
High Expression ◽  
Ribonucleoprotein Particle ◽  
Hnscc Cell

YRNAs are a class of non-coding RNAs that are components of the Ro60 ribonucleoprotein particle and are essential for initiation of DNA replication. Ro60 ribonucleoprotein particle is a target of autoimmune antibodies in patients suffering from systemic lupus erythematosus and Sjögren’s syndrome. Deregulation of YRNAs has been confirmed in many cancer types, but not in head and neck squamous cell carcinoma (HNSCC). The main aim of this study was to determine the biological role of YRNAs in HNSCC, the expression of YRNAs, and their usefulness as potential HNSCC biomarkers. Using quantitative reverse transcriptase (qRT)-PCR, the expression of YRNAs was measured in HNSCC cell lines, 20 matched cancer tissues, and 70 FFPETs (Formaline-Fixed Paraffin-Embedded Tissue) from HNSCC patients. Using TCGA (The Cancer Genome Atlas) data, an analysis of the expression levels of selected genes, and clinical-pathological parameters was performed. The expression of low and high YRNA1 expressed groups were analysed using gene set enrichment analysis (GSEA). YRNA1 and YRNA5 are significantly downregulated in HNSCC cell lines. YRNA1 was found to be significantly downregulated in patients’ tumour sample. YRNAs were significantly upregulated in T4 stage. YRNA1 showed the highest sensitivity, allowing to distinguish healthy from cancer tissue. An analysis of TCGA data revealed that expression of YRNA1 was significantly altered in the human papilloma virus (HPV) infection status. Patients with medium or high expression of YRNA1 showed better survival outcomes. It was noted that genes correlated with YRNA1 were associated with various processes occurring during cancerogenesis. The GSEA analysis showed high expression enrichment in eight vital processes for cancer development. YRNA1 influence patients’ survival and could be used as an HNSCC biomarker. YRNA1 seems to be a good potential biomarker for HNSCC, however, more studies must be performed and these observations should be verified using an in vitro model.

scholarly journals HLF is a Potential Prognostic Biomarker in Head and Neck Squamous Cell Carcinoma Based on Bioinformatic Analysis and Experimental Validation

2021 ◽  
Author(s):  
Wei Fang ◽  
Di Wan ◽  
Jun Chen ◽  
Weiqun Ma ◽  
Zhen Luo ◽  
...  
Keyword(s):  
Gene Expression ◽  
Cell Culture ◽  
Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Poor Prognosis ◽  
Prognostic Biomarker ◽  
Neck Squamous Cell Carcinoma ◽  
Rt Pcr ◽  
The Relationship

Abstract BackgroundHead and neck squamous cell carcinoma (HNSCC) is one of the most frequent cancers worldwide, with an increasing incidence. However, the underlying molecular mechanisms of HNSCC are poorly understood.MethodIn this work, 5 original datasets (GSE23558, GSE13601, GSE30784, GSE9844, GSE78060) of Head and neck squamous cell carcinoma (HNSCC) were selected from Gene Expression Omnibus (GEO) database. To identify differentially expressed genes (DEGs) in HNSCC and adjacent tissues. The common DEGs were acquired by Venn diagram. The sensitivity and specificity of HLF were determined by Receiver operating characteristic curves (ROC). Then, In order to further confirm the relationship between HLF and HNSCC patient’s prognosis, the expression and survival analysis of HLF was performed by Gene Expression Profiling Interactive Analysis (GEPIA), Cell culture, reverse transcription polymerase chain reaction (RT-PCR), western blotting and immunohistochemical staining.ResultsSeventeen DEGs were screened from five sets of HNSCC functional gene expression series in GEO datasets. The low expression of HLF was indicated might be correlated with poor prognosis of HNSCC patients based on the bioinformatics analysis. According to the results of Cell culture, RT-PCR, western blotting, immunohistochemical staining, it was confirmed that the low level of HLF expression correlated with poor prognosis of HNSCC patients.ConclusionThe study effectively revealed useful information about the relationship of the low level of HLF expression and HNSCC. In summary, we identified HLF as a potential prognostic biomarker and therapeutic target for HNSCC.

scholarly journals Functional Genomics Screen with Pooled shRNA Library and Gene Expression Profiling with Extracts of Azadirachta indica Identify Potential Pathways for Therapeutic Targets in Head and Neck Squamous Cell Carcinoma

2018 ◽  
Author(s):  
Neeraja M Krishnan ◽  
Hiroto Katoh ◽  
Vinayak Palve ◽  
Manisha Pareek ◽  
Reiko Sato ◽  
...  
Keyword(s):  
Gene Expression ◽  
Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Head And Neck ◽  
Cancer Cell ◽  
Squamous Cell ◽  
Azadirachta Indica ◽  
Neck Squamous Cell Carcinoma ◽  
Neem Extract ◽  
Infected Cells

AbstractTumor suppression by the extracts of Azadirachta indica (neem) works via anti-proliferation, cell cycle arrest, and apoptosis, demonstrated previously using cancer cell lines and live animal models. However, very little is known about the molecular targets and pathways that the neem extracts and the associated compounds act through. Here, we address this using a genome-wide functional pooled shRNA screen on head and neck squamous cell carcinoma cell line treated with crude neem leaf extracts, known for their anti-tumorigenic activity. By analyzing differences in global clonal sizes of the shRNA-infected cells cultured under no treatment and treatment with neem leaf extract conditions, assayed using next-generation sequencing, we found 225 genes affected the cancer cell growth in the shRNA-infected cells treated with neem extract. Pathway enrichment analyses of whole-genome gene expression data from cells temporally treated with neem extract revealed important roles played by the TGF-β pathway and HSF-1-related gene network. Our results indicate that neem extract simultaneously affects various important molecular signaling pathways in head and neck cancer cells, some of which may be therapeutic targets for this devastating tumor.

scholarly journals The Identification of Stemness-Related Genes in the Risk of Head and Neck Squamous Cell Carcinoma

2021 ◽  
Vol 11 ◽  
Author(s):  
Guanying Feng ◽  
Feifei Xue ◽  
Yingzheng He ◽  
Tianxiao Wang ◽  
Hua Yuan
Keyword(s):  
Gene Expression ◽  
Squamous Cell Carcinoma ◽  
Network Analysis ◽  
Cell Carcinoma ◽  
Head And Neck ◽  
Risk Score ◽  
Squamous Cell ◽  
Neck Squamous Cell Carcinoma ◽  
Potential Biomarker ◽  
Score Model

ObjectivesThis study aimed to identify genes regulating cancer stemness of head and neck squamous cell carcinoma (HNSCC) and evaluate the ability of these genes to predict clinical outcomes.Materials and MethodsThe stemness index (mRNAsi) was obtained using a one-class logistic regression machine learning algorithm based on sequencing data of HNSCC patients. Stemness-related genes were identified by weighted gene co-expression network analysis and least absolute shrinkage and selection operator analysis (LASSO). The coefficient of LASSO was applied to construct a diagnostic risk score model. The Cancer Genome Atlas database, the Gene Expression Omnibus database, Oncomine database and the Human Protein Atlas database were used to validate the expression of key genes. Interaction network analysis was performed using String database and DisNor database. The Connectivity Map database was used to screen potential compounds. The expressions of stemness-related genes were validated using quantitative real‐time polymerase chain reaction (qRT‐PCR).ResultsTTK, KIF14, KIF18A and DLGAP5 were identified. Stemness-related genes were upregulated in HNSCC samples. The risk score model had a significant predictive ability. CDK inhibitor was the top hit of potential compounds.ConclusionStemness-related gene expression profiles may be a potential biomarker for HNSCC.

Sign in / Sign up

Export Citation Format

Share Document