scholarly journals An Immune Feature-Based, Three-Gene Scoring System for Prognostic Prediction of Head-and-Neck Squamous Cell Carcinoma

2022 ◽  
Vol 11 ◽  
Author(s):  
Yamin Zhang ◽  
Xiayan Luo ◽  
Jing Yu ◽  
Kejia Qian ◽  
Huiyong Zhu
Keyword(s):  
Squamous Cell Carcinoma ◽  
T Cells ◽  
Cell Carcinoma ◽  
Head And Neck ◽  
Candidate Genes ◽  
Risk Score ◽  
Squamous Cell ◽  
Scoring System ◽  
Cox Regression ◽  
Neck Squamous Cell Carcinoma

Head-and-neck squamous cell carcinoma (HNSCC) is characterized by a high frequency of neck lymph node metastasis (LNM), a key prognostic factor. Therefore, identifying the biological processes during LNM of HNSCC has significant clinical implications for risk stratification. This study performed Gene Ontology enrichment analysis of differentially expressed genes between tumors with LNM and those without LNM and identified the involvement of immune response in the lymphatic metastasis of HNSCC. We further identified greater infiltrations of CD8+ T cells in tumors than in adjacent normal tissues through immunochemistry in the patient cohort (n = 62), indicating the involvement of CD8+ T cells in the antitumor immunity. Hierarchical clustering analysis was conducted to initially identify the candidate genes relevant to lymphocyte-mediated antitumor response. The candidate genes were applied to construct a LASSO Cox regression analysis model. Three genes were eventually screened out as progression‐related differentially expressed candidates in HNSCC and a risk scoring system was established based on LASSO Cox regression model to predict the outcome in patients with HNSCC. The score was calculated using the formula: 0.0636 × CXCL11 − 0.4619 × CXCR3 + 0.2398 × CCR5. Patients with high scores had significantly worse overall survival than those with low scores (p < 0.001). The risk score showed good performance in characterizing tumor-infiltrating lymphocytes and provided a theoretical basis for stratifying patients receiving immune therapies. Additionally, a nomogram including the risk score, age, and TNM stage was constructed. The prediction model displayed marginally better discrimination ability and higher agreement in predicting the survival of patients with HNSCC compared with the TNM stage.

scholarly journals Prognostic value of novel immune-related genomic biomarkers identified in head and neck squamous cell carcinoma

2020 ◽  
Vol 8 (2) ◽  
pp. e000444
Author(s):  
Yao Yao ◽  
Zhongyi Yan ◽  
Senlin Lian ◽  
Liangnian Wei ◽  
Chao Zhou ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
T Cells ◽  
Cell Carcinoma ◽  
Head And Neck ◽  
Rna Sequencing ◽  
Squamous Cell ◽  
Cox Regression ◽  
Neck Squamous Cell Carcinoma ◽  
Kaplan Meier ◽  
Immune Related Genes

BackgroundThe immune response within the tumor microenvironment plays a key role in tumorigenesis and determines the clinical outcomes of head and neck squamous cell carcinoma (HNSCC). However, to date, a paucity of robust, reliable immune-related biomarkers has been identified that are capable of estimating prognosis in HNSCC patients.MethodsHigh-throughput RNA sequencing was performed in tumors and matched adjacent tissues from five HNSCC patients, and the immune signatures expression of 730 immune-related transcripts selected from the nCounter PanCancer Immune Profiling Panel were assessed. Survival analyzes were performed in a training cohort, consisting of 416 HNSCC cases, retrieved from The Cancer Genome Atlas (TCGA) database. A prognostic signature was built, using elastic net-penalized Cox regression and backward, stepwise Cox regression analyzes. The outcomes were validated by an independent cohort of 115 HNSCC patients, using tissue microarrays and immunohistochemistry staining. Cell-type identification by estimating relative subsets of RNA transcripts (CIBERSORT) was also used to estimate the relative fractions of 22 immune-cell types and their correlations coefficients with prognostic biomarkers.ResultsCollectively, 248 immune-related genes were differentially expressed in paired tumors and normal tissues using RNA sequencing. After process screening in the training TCGA cohort, four immune-related genes (PVR, TNFRSF12A, IL21R, and SOCS1) were significantly associated with overall survival (OS). Integrating these genes with Path_N stage, a multiplex model was built and suggested better performance in determining 5 years OS (receiver operating characteristic (ROC) analysis, area under the curve (AUC)=0.709) than others. Further protein-based validation was conducted in 115 HNSCC patients. Similarly, high expression of PVR and TNFRSF12A were associated with poor OS (Kaplan-Meier p=0.017 and 0.0032), while high expression of IL21R and SOCS1 indicated favorable OS (Kaplan-Meier p<0.0001 and =0.0018). The integrated model with Path_N stage still demonstrated efficacy in OS evaluation (Kaplan-Meier p<0.0001, ROC AUC=0.893). Besides, the four prognostic genes were significantly correlated with activated CD8+ T cells, CD4+ T cells, follicular helper T cells and regulatory T cells, implying the possible involvement of these genes in the immunoregulation and development of HNSCC.ConclusionsThe well-established model encompassing both immune-related biomarkers and clinicopathological factor might serve as a promising tool for the prognostic prediction of HNSCC.

Three Autophagy-Related lncRNA are Prognostic Biomarkers for Patients with Head and Neck Squamous Cell Carcinoma

2021 ◽  
Author(s):  
Haoyue Xu ◽  
Xiangpu Wang ◽  
Zhien Feng ◽  
Renji Chen ◽  
Zhengxue Han
Keyword(s):  
Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Head And Neck ◽  
Risk Score ◽  
Squamous Cell ◽  
Cox Regression ◽  
Neck Squamous Cell Carcinoma ◽  
Regression Analyses ◽  
Good Ability ◽  
Non Coding Rnas

Abstract Background: Currently, no systematic analysis has been conducted to assess the potential of multiple autophagy-related long non-coding RNAs (lncRNA) to predict the prognosis of head and neck squamous cell carcinoma (HNSCC). we investigated the prognostic potential of autophagy-related long non-coding RNAs (lncRNA) in HNSCC patients. Methods: Patient information and Autophagy-associated genes were obtained from The Cancer Genome Atlas (TCGA) and Human Autophagy data resource. Autophagy-related lncRNAs were determined through Lasso and Cox regression analyses. Then, on the basis of autophagy- related lncRNAs, a risk score and a nomogram were constructed for estimation of prognostic outcomes for HNSCC patients. These models were verified internally using the TCGA and. Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) were used for gene functional analyses. Results: Three autophagy-related lncRNAs (AC002401.4, AC245041.2 and TMEM44-AS1) that are associated with HNSCC were identified. Univariate and multivariate Cox regression analyses revealed that the risk score is an independent prognostic indicator (p ≤ 0.001), with its ability to predict prognosis being higher than that of other clinicopathological indicators (AUC=0.732). Concordance index of the nomogram was 0.712, and AUC values for one-year, three-year and five-year survival rates were 0.730, 0.745 and 0.728, respectively. Internal verifications revealed that this nomogram had a good ability to predict prognosis. Functional analysis showed that the genes were mostly enriched in autophagy and tumor-related cascades. Conclusion: The autophagy-related lncRNAs model can predict the prognosis of patients with HNSCC.Trial registration: Prospective, Observational, Real-world Oral Malignant Tumors Study (POROMS), NCT02395367. Registered 23 March 2015, https://clinicaltrials.gov/ct2/show/NCT02395367

scholarly journals Identification of Immune-Related LncRNA Pairs for Predicting Prognosis and Immunotherapeutic Response in Head and Neck Squamous Cell Carcinoma

2021 ◽  
Vol 12 ◽  
Author(s):  
Xueying Wang ◽  
Kui Cao ◽  
Erliang Guo ◽  
Xionghui Mao ◽  
Lunhua Guo ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
T Cells ◽  
Clinical Outcome ◽  
Cell Carcinoma ◽  
Head And Neck ◽  
Squamous Cell ◽  
Immune Cell ◽  
Cox Regression ◽  
Checkpoint Inhibitors ◽  
Neck Squamous Cell Carcinoma

Long noncoding RNAs (lncRNAs) have multiple functions with regard to the cancer immunity response and the tumor microenvironment. The prognosis of head and neck squamous cell carcinoma (HNSCC) is still poor currently, and it may be effective to predict the clinical outcome and immunotherapeutic response of HNSCC by immunogenic analysis. Therefore, by using univariate COX analysis and Lasso Cox regression, we identified a signature consisting of 21 immune-related lncRNA pairs (IRLPs) that predicted clinical outcome and Immunotherapeutic response in HNSCC. Specifically, it was associated with immune cell infiltration (i.e., T cells CD4 memory resting, CD8 T cells, macrophages M0, M2, and NK cells), and more importantly this signature was strongly related with immune checkpoint inhibitors (ICIs) [such as PDCD1 (r = -0.35, P &lt; 0.001), CTLA4 (r = -0.26, P &lt; 0.001), LAG3 (r = -0.22, P &lt; 0.001) and HAVCR2 (r = -0.2, P &lt; 0.001)] and immunotherapy-related biomarkers (MMR and HLA). The present study highlighted the value of the 21 IRLPs signature as a predictor of prognosis and immunotherapeutic response in HNSCC.

scholarly journals Tumor hypoxia is associated with resistance to PD-1 blockade in squamous cell carcinoma of the head and neck

2021 ◽  
Vol 9 (5) ◽  
pp. e002088
Author(s):  
Dan P Zandberg ◽  
Ashley V Menk ◽  
Maria Velez ◽  
Daniel Normolle ◽  
Kristin DePeaux ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
T Cells ◽  
Cell Carcinoma ◽  
Head And Neck ◽  
Squamous Cell ◽  
Cd8 T Cells ◽  
Oxidative Metabolism ◽  
Cox Regression ◽  
Tumor Hypoxia ◽  
Parental Line

The majority of patients with recurrent/metastatic squamous cell carcinoma of the head and neck (HNSCC) (R/M) do not benefit from anti-PD-1 therapy. Hypoxia induced immunosuppression may be a barrier to immunotherapy. Therefore, we examined the metabolic effect of anti-PD-1 therapy in a murine MEER HNSCC model as well as intratumoral hypoxia in R/M patients. In order to characterize the tumor microenvironment in PD-1 resistance, a MEER cell line was created from the parental line that are completely resistant to anti-PD-1. These cell lines were then metabolically profiled using seahorse technology and injected into C57/BL6 mice. After tumor growth, mice were pulsed with pimonidazole and immunofluorescent imaging was performed to analyze hypoxia and T cell infiltration. To validate the preclinical results, we analyzed tissues from R/M patients (n=36) treated with anti-PD-1 mAb, via immunofluorescent imaging for number of CD8+ T cells (CD8), Tregs and the percent area (CAIX) and mean intensity (I) of carbonic anhydrase IX in tumor. We analyzed disease control rate (DCR), progression free survival (PFS), and overall survival (OS) using proportional odds and proportional hazards (Cox) regression. We found that anti-PD-1 resistant MEER has significantly higher oxidative metabolism, while there was no difference in glycolytic metabolism. Intratumoral hypoxia was significantly increased and CD8+ T cells decreased in anti-PD-1 resistant tumors compared with parental tumors in the same mouse. In R/M patients, lower tumor hypoxia by CAIX/I was significantly associated with DCR (p=0.007), PFS, and OS, and independently associated with response (p=0.028) and PFS (p=0.04) in a multivariate model including other significant immune factors. During PD-1 resistance, tumor cells developed increased oxidative metabolism leading to increased intratumoral hypoxia and a decrease in CD8+ T cells. Lower tumor hypoxia was independently associated with increased efficacy of anti-PD-1 therapy in patients with R/M HNSCC. To our knowledge this is the first analysis of the effect of hypoxia in this patient population and highlights its importance not only as a predictive biomarker but also as a potential target for therapeutic intervention.

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.

Autophagy regulation patterns characterization identifies immune phenotypes and immunotherapy response in head and neck squamous cell carcinoma (HNSCC)

2020 ◽  
Author(s):  
Bo Ma ◽  
Hui Li ◽  
Mingzhu Zheng ◽  
Rui Cao ◽  
Riyue Yu
Keyword(s):  
Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Head And Neck ◽  
Squamous Cell ◽  
Scoring System ◽  
Clustering Algorithm ◽  
Neck Squamous Cell Carcinoma ◽  
Integrated Analysis ◽  
Molecular Characteristics ◽  
Immune Phenotypes

Abstract BackgroundAutophagy degraded and recycled cytoplasmic components to maintain cellular homeostasis under stress conditions, which was recognized as double-edged sword in oncogenesis and novel target in cancer treatment. However, comprehensive analysis of the relationship between autophagy regulation and immunity has not been reported yet. MethodsUnsupervised consensus clustering algorithm was used to identify autophagy regulation patterns. LASSO cox regression algorithm was used to build a scoring system (ATGscore) to represent the individual autophagy regulation pattern. Then integrated analysis of autophagy regulation patterns and ATGscore was performed.ResultsWe have successful depicted five autophagy regulation patterns and established a scoring system (ATGscore) to represent it, which was shown to be significantly correlated with TIME infiltration, immune phenotypes, molecular subtypes, and genetic variation, etc. in 1165 head and neck squamous cell carcinoma (HNSCC) patients. Moreover, ATGscore was an independent prognostic factor and potent predictor for clinical response to immune-checkpoint inhibitors (ICIs) targeting immunotherapy. ConclusionUnderstanding the molecular characteristics of autophagy regulation patterns in HNSCC could help us to depict the underlying mechanism of tumour immunity and lay a solid foundation on combination of autophagy targeting therapies and immunotherapies for clinical application in HNSCC.

scholarly journals Seven LncRNA-mRNA based risk score predicts the survival of head and neck squamous cell carcinoma

2017 ◽  
Vol 7 (1) ◽  
Author(s):  
Zhi-Li Zhang ◽  
Li-jing Zhao ◽  
Liang Chai ◽  
Shui-Hong Zhou ◽  
Feng Wang ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Head And Neck ◽  
Risk Score ◽  
Squamous Cell ◽  
Neck Squamous Cell Carcinoma

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.

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