The Potential of Oxidative Stress Related Genes as Prognostic Biomarkers in Head and Neck Squamous Cell Carcinoma

Author(s):  
Xin Wang ◽  
Gang Zhou

Background: The occurrence of oxidative stress is an important hallmark of tumorigenesis and the development of cancers, including head and neck squamous cell carcinoma (HNSCC). The purpose of this study was to identify a robust oxidative stress-related prognostic model in HNSCC. Methods: Oxidative stress genes related to the prognosis of HNSCC were identified through multiple bioinformatics methods. Results: The expression profile of differential genes related to oxidative stress and functional enrichment analysis were obtained from the HNSCC cohort of The Cancer Genome Atlas (TCGA-HNSC). Then, the HNSCC prognostic risk model was constructed of thirteen screened genes through univariate Cox analysis, the least absolute shrinkage and selection operator (LASSO) Cox regression, and multivariate Cox analysis. Kaplan–Meier curve indicated that the low-risk group had a better survival outcome than the high-risk group. The clinical utility of the risk model was validated in the GSE41613 dataset. The risk score was an independent prognostic indicator in the training and validation sets. In addition, the risk score was in a positive correlation with tumor stage, lymph node infiltration, and the status of the primary site. Gene set enrichment analysis (GSEA) illustrated that many biological processes associated with immunity were significantly enriched in the low-risk group of the training cohort. Conclusion:: The oxidative stress-related risk signature was a promising predictor for the prognosis of HNSCC patients, which might assist in making individualized therapy programs.

BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Congyu Shi ◽  
Shan Liu ◽  
Xudong Tian ◽  
Xiaoyi Wang ◽  
Pan Gao

Abstract Background Tumor protein p53 (TP53) is the most frequently mutated gene in head and neck squamous cell carcinoma (HNSC), and TP53 mutations are associated with inhibited immune signatures and poor prognosis. We established a TP53 mutation associated risk score model to evaluate the prognosis and therapeutic responses of patients with HNSC. Methods Differentially expressed genes between patients with and without TP53 mutations were determined by using data from the HNSC cohort in The Cancer Genome Atlas database. Patients with HNSC were divided into high- and low-risk groups based on a prognostic risk score that was generated from ten TP53 mutation associated genes via the multivariate Cox regression model. Results TP53 was the most common mutant gene in HNSC, and TP53 mutations were associated with immunogenic signatures, including the infiltration of immune cells and expression of immune-associated genes. Patients in the high-risk group had significantly poorer overall survival than those in the low-risk group. The high-risk group showed less response to anti-programmed cell death protein 1 (PD-1) therapy but high sensitivity to some chemotherapies. Conclusion The risk score based on our TP53 mutation model was associated with poorer survival and could act as a specific predictor for assessing prognosis and therapeutic response in patients with HNSC.


2021 ◽  
Vol 11 ◽  
Author(s):  
Guangsheng Hu ◽  
Qingshan Jiang ◽  
Lijun Liu ◽  
Hong Peng ◽  
Yaya Wang ◽  
...  

RNA-binding proteins (RBPs) interacting with target RNAs play essential roles in RNA metabolism at the post-transcription level. Perturbations of RBPs can accelerate cancer development and cause dysregulation of the immune cell function and activity leading to evade immune destruction of cancer cells. However, few studies have systematically analyzed the potential prognostic value and functions of RBPs in squamous cell carcinoma of head and neck (SCCHN). Here, for the first time, we comprehensively identified 92 differentially expressed RBPs from The Cancer Genome Atlas (TCGA) database. In the training set, a prognosis risk model was constructed with six RBPs, including NCBP2, MKRN3, MRPL47, AZGP1, IGF2BP2, and EZH2, and validated by the TCGA test set, the TCGA all set, and the GEO data set. In addition, the risk score was related to the clinical stage, T classification, and N classification. Furthermore, the high-risk score was significantly correlated with immunosuppression, and low expression of EZH2 and AZGP1 and high expression of IGF2BP2 were the main factors. Thus, the risk model may serve as a prognostic signature and offer highlights for individualized immunotherapy in SCCHN patients.


Author(s):  
Dongsheng He ◽  
Shengyin Liao ◽  
Linlin Xiao ◽  
Lifang Cai ◽  
Mengxing You ◽  
...  

Background: Ferroptosis is an iron-dependent programmed cell death (PCD) form that plays a crucial role in tumorigenesis and might affect the antitumor effect of radiotherapy and immunotherapy. This study aimed to investigate distinct ferroptosis-related genes, their prognostic value and their relationship with immunotherapy in patients with head and neck squamous cell carcinoma (HNSCC).Methods: The differentially expressed ferroptosis-related genes in HNSCC were filtered based on multiple public databases. To avoid overfitting and improve clinical practicability, univariable, least absolute shrinkage and selection operator (LASSO) and multivariable Cox algorithms were performed to construct a prognostic risk model. Moreover, a nomogram was constructed to forecast individual prognosis. The differences in tumor mutational burden (TMB), immune infiltration and immune checkpoint genes in HNSCC patients with different prognoses were investigated. The correlation between drug sensitivity and the model was firstly analyzed by the Pearson method.Results: Ten genes related to ferroptosis were screened to construct the prognostic risk model. Kaplan-Meier (K-M) analysis showed that the prognosis of HNSCC patients in the high-risk group was significantly lower than that in the low-risk group (P < 0.001), and the area under the curve (AUC) of the 1-, 3- and 5-year receiver operating characteristic (ROC) curve increased year by year (0.665, 0.743, and 0.755). The internal and external validation further verified the accuracy of the model. Then, a nomogram was build based on the reliable model. The C-index of the nomogram was superior to a previous study (0.752 vs. 0.640), and the AUC (0.729 vs. 0.597 at 1 year, 0.828 vs. 0.706 at 3 years and 0.853 vs. 0.645 at 5 years), calibration plot and decision curve analysis (DCA) also shown the satisfactory predictive capacity. Furthermore, the TMB was revealed to be positively correlated with the risk score in HNSCC patients (R = 0.14; P < 0.01). The differences in immune infiltration and immune checkpoint genes were significant (P < 0.05). Pearson analysis showed that the relationship between the model and the sensitivity to antitumor drugs was significant (P < 0.05).Conclusion: Our findings identified potential novel therapeutic targets, providing further potential improvement in the individualized treatment of patients with HNSCC.


2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Cheng Li ◽  
Zeng-hong Wu ◽  
Kun Yuan

Background. Head and neck squamous cell carcinoma (HNSCC) is one of the most common malignancies in the world, with low survival and poor quality of life. Autophagy-associated genes (ATGs) have been reported to be involved in the initiation and progression of malignancies. Here, we aimed to investigate the association between autophagy-associated genes and the outcomes in HNSCC patients. Methods. We obtained ATGs with prognostic values by analyzing the datasets from The Cancer Genome Atlas (TCGA) and Human Autophagy Database (HADb). The enrichment functions of autophagy differential genes were analyzed by Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG). The Kaplan-Meier method was applied to the survival curve analysis. A prognostic autophagy-related gene signature was established, and its independence was verified. Results. We acquired a total of 529 samples and 232 ATGs; further, we identified 45 genes associated with prognosis and built a prognosis autophagy signature based on risk score of 15 genes. Patients were divided into two groups based on risk scores. The Kaplan-Meier curve illustrated that the survival rate of the high-risk group was significantly lower than that of the low-risk group in both the training group and validation group. The ROC curve revealed that the risk score had the highest AUC value in the 3rd and 5th years, reaching 0.703 and 0.724, which are higher than other risk factors such as gender, age, and TNM stage. The nomogram further confirmed its weight in the prognosis of HNSCC patients. Through KEGG and GO enrichment analyses, we observed that ATGs were involved in the tumorigenesis and invasion of tumor by various mediating pathways. We gained 3 hub genes (MAP1LC3B, FADD, and LAMP1) and further analyzed the survival curves, mutations, differential expressions, and their roles in tumors on the online websites. Conclusion. We identified a novel autophagy-related signature that may provide promising biomarker genes for the treatment and prognosis of HNSCC. We need to validate its prognostic value by applying it to the clinic.


2021 ◽  
Vol 11 ◽  
Author(s):  
Guanying Feng ◽  
Feifei Xue ◽  
Yingzheng He ◽  
Tianxiao Wang ◽  
Hua Yuan

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.


2021 ◽  
Vol 8 ◽  
Author(s):  
Jiahang Song ◽  
Yanhu Liu ◽  
Xiang Guan ◽  
Xun Zhang ◽  
Wenda Yu ◽  
...  

Esophageal squamous cell carcinoma (ESCC) accounts for the main esophageal cancer (ESCA) type, which is also associated with the greatest malignant grade and low survival rates worldwide. Ferroptosis is recently discovered as a kind of programmed cell death, which is indicated in various reports to be involved in the regulation of tumor biological behaviors. This work focused on the comprehensive evaluation of the association between ferroptosis-related gene (FRG) expression profiles and prognosis in ESCC patients based on The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). ALOX12, ALOX12B, ANGPTL7, DRD4, MAPK9, SLC38A1, and ZNF419 were selected to develop a novel ferroptosis-related gene signature for GEO and TCGA cohorts. The prognostic risk model exactly classified patients who had diverse survival outcomes. In addition, this study identified the ferroptosis-related signature as a factor to independently predict the risk of ESCC. Thereafter, we also constructed the prognosis nomogram by incorporating clinical factors and risk score, and the calibration plots illustrated good prognostic performance. Moreover, the association of the risk score with immune checkpoints was observed. Collectively, the proposed ferroptosis-related gene signature in our study is effective and has a potential clinical application to predict the prognosis of ESCC.


2020 ◽  
Author(s):  
Lumeng Luo ◽  
Minghe Lv ◽  
Xuan Li ◽  
Tiankui Qiao ◽  
Kuaile Zhao ◽  
...  

Abstract Background: Recent advances in immune checkpoint inhibitors (ICIs) have dramatically changed the therapeutic strategy against lung squamous cell carcinoma (LUSC). In the era of immunotherapy, effective biomarkers to better predict outcomes and inform treatment decisions for patients diagnosed with LUSC are urgently needed. We hypothesized that immune contexture of LUSC is potentially dictated by tumor intrinsic events, such as autophagy. Thus, we attempted to construct an autophagy-related risk signature and examine its prediction value for immune phenotype in LUSC.Method: The expression profile of LUSC was obtained from the cancer genome atlas (TCGA) database and the profile of autophagy-related genes (ARGs) was extracted. The survival‑related ARGs (sARGs) was screened out through survival analyses. Random forest was performed to select the sARGs and construct a prognostic risk signature based on these sARGs. The signature was further validated by receiver operating characteristic (ROC) analysis and Cox regression. GEO dataset was used as an independent testing dataset. Patients were divided into high-risk and low-risk group based on the risk score. Then, gene set enrichment analysis (GSEA) was conducted between the two groups. The Single-Sample GSEA (ssGSEA) was introduced to quantify the relative infiltration of immune cells. The correlations between risk score and several main immune checkpoints were examined. And the ESTIMATE algorithm was used to calculate the estimate/immune/stromal scores of the LUSC. Results: Four ARGs (CFLAR, RGS19, PINK1 and CTSD) with the most significant prognostic values were enrolled to construct the risk signature. Patients in high-risk group had better prognosis than the low-risk group (P < 0.0001 in TCGA; P < 0.01 in GEO) and considered as an independent prognosis factor. We also found that high-risk group indicated an immune-suppression status and had higher levels of infiltrating regulatory T cells and macrophages, which are correlated with worse outcome. Besides, risk score showed a significantly positive correlation with the expression of PD-1 and CTLA4, as well as estimate score and immune score.Conclusion: This study established a novel autophagy-related four-gene prognostic risk signature, and the autophagy-related scores are associated with immune landscape of LUSC, with higher score indicating a stronger immune-suppression status.


2017 ◽  
Vol 7 (1) ◽  
Author(s):  
Zhi-Li Zhang ◽  
Li-jing Zhao ◽  
Liang Chai ◽  
Shui-Hong Zhou ◽  
Feng Wang ◽  
...  

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Yaping Deng ◽  
Kehua Li ◽  
Fengwu Tan ◽  
Hanbo Liu

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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