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Immune-related gene signature for predicting the prognosis of head and neck squamous cell carcinoma.

ABSTRACT: Background:Immune-related genes (IRGs) were linked to the prognosis of head and neck squamous cell carcinoma (HNSCC). This study aimed to identify the effects of an immune-related gene signature (IRGS) that can predict the of HNSCC prognosis. Methods:The expression data of 770 HNSCC patients from the TCGA database and the GEO database were used. To explore a predictive model, the Cox proportional hazards model was applied. The Kaplan-Meier survival analysis, as well as univariate and multivariate analyses were performed to evaluate the independent predictive value of IRGS. To explore biological functions of IRGS, enrichment analyses and pathway annotation for differentially expressed genes (DEGs) in different immune groups were applied, as well as the immune infiltration. Results:A prognostic signature comprising 27 IRGs was generated. IRGS significantly stratified HNSCC patients into high and low immune risk groups in regard to overall survival in the training cohort (HR?=?3.69, 95% CI 2.73-4.98, P?

SUBMITTER: She Y

PROVIDER: S-EPMC6969412 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Immune-related gene signature for predicting the prognosis of head and neck squamous cell carcinoma.

She Yangyang Y Kong Xiangbo X Ge Yaping Y Yin Ping P Liu Zhiyong Z Chen Jieyu J Gao Feng F Fang Silian S

Cancer cell international 20200117

<h4>Background</h4>Immune-related genes (IRGs) were linked to the prognosis of head and neck squamous cell carcinoma (HNSCC). This study aimed to identify the effects of an immune-related gene signature (IRGS) that can predict the of HNSCC prognosis.<h4>Methods</h4>The expression data of 770 HNSCC patients from the TCGA database and the GEO database were used. To explore a predictive model, the Cox proportional hazards model was applied. The Kaplan-Meier survival analysis, as well as univariate ...[more]

PMID: 31988638

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Project description:BackgroundThe mechanistic aspects of the involvement of long noncoding RNAs (lncRNAs) in NETosis, the process of neutrophil extracellular trap (NET) formation in head and neck squamous cell carcinoma (HNSCC), lack comprehensive elucidation. The involvement of these molecules in the immune microenvironment and plausible HNSCC prognosis remain to see the light of the day. The plausible functioning of NETosis-related lncRNAs with their plausible prognostic impact in HNSCC was probed in this work.MethodsThe scrutiny of lncRNAs linked to NETosis entailed the probing of twenty-four genes associated with the process employing Pearson's correlation analysis on HNSCC patients' RNA sequencing data from The Cancer Genome Atlas (TCGA) database. The application of univariate, least absolute shrinkage and selection operator (LASSO), and multivariate Cox regression analyses yielded a NETosis-related lncRNA signature that was subjected to probing for its suitability in prognosis employing survival and nomogram analyses.ResultsThe NETosis-related lncRNA signature inclusive of five lncRNAs facilitated patients to be segregated as high-risk and low-risk groups with the former documenting a poor prognosis. Regression unearthed that the risk score was an independent factor for prognosis. The receiver operating characteristic (ROC) or receiver operating characteristic curve analysis documented a one-year area under time-dependent ROC curve (AUC) value of 0.711 that is corroborative of the accuracy of this signature. Additional probing documented an evident enriching of immune-linked pathways in the low-risk patients, while the high-risk patients documented an immunologically "cold" profile as per the infiltration of immune cells. We verified lncRNA expression from our NETosis-related lncRNA signature in vitro, which reflects the reliability of our model to a certain extent. Moreover, we also verified the function of the lncRNA. We found that LINC00426 contributes to the innate immune cGAS-STING signaling pathway, which explain to some extent the role of our prognostic model in predicting "hot" and "cold" tumors.ConclusionsThe plausible prognostic relevance of the NETosis-related lncRNA signature (with five lncRNAs) emerges that is suggestive of its promise in targeting HNSCC.

Project description:Background: Long non-coding RNA (lncRNA) plays a significant role in the development, establishment, and progression of head and neck squamous cell carcinoma (HNSCC). This article aims to develop an immune-related lncRNA (irlncRNA) model, regardless of expression levels, for risk assessment and prognosis prediction in HNSCC patients. Methods: We obtained clinical data and corresponding full transcriptome expression of HNSCC patients from TCGA, downloaded GTF files to distinguish lncRNAs from Ensembl, discerned irlncRNAs based on co-expression analysis, distinguished differentially expressed irlncRNAs (DEirlncRNAs), and paired these DEirlncRNAs. Univariate Cox regression analysis, LASSO regression analysis, and stepwise multivariate Cox regression analysis were then performed to screen lncRNA pairs, calculate the risk coefficient, and establish a prognosis model. Finally, the predictive power of this model was validated through the AUC and the ROC curves, and the AIC values of each point on the five-year ROC curve were calculated to select the maximum inflection point, which was applied as a cut-off point to divide patients into low- or high-risk groups. Based on this methodology, we were able to more effectively differentiate between these groups in terms of survival, clinico-pathological characteristics, tumor immune infiltrating status, chemotherapeutics sensitivity, and immunosuppressive molecules. Results: A 13-irlncRNA-pair signature was built, and the ROC analysis demonstrated high sensitivity and specificity of this signature for survival prediction. The Kaplan-Meier analysis indicated that the high-risk group had a significantly shorter survival rate than the low-risk group, and the chi-squared test certified that the signature was highly related to survival status, clinical stage, T stage, and N stage. Additionally, the signature was further proven to be an independent prognostic risk factor via the Cox regression analyses, and immune infiltrating analyses showed that the high-risk group had significant negative relationships with various immune infiltrations. Finally, the chemotherapeutics sensitivity and the expression level of molecular markers were also significantly different between high- and low-risk groups. Conclusion: The signature established by paring irlncRNAs, with regard to specific expression levels, can be utilized for survival prediction and to guide clinical therapy in HNSCC.

Project description:Pyroptosis, as a novel identified programmed cell death, is closely correlated with tumor immunity and shows potential roles in cancer treatment. Discerning a pyroptosis-related gene signature and its correlations with tumor immune microenvironment is critical in head and neck squamous cell carcinoma (HNSCC). Transcriptome data and corresponding clinical data were downloaded from TCGA and GEO databases. Tumor mutation burden (TMB) data were obtained from TCGA database. Firstly, univariate and least absolute shrinkage and selection operator (LASSO) regression analyses were used to construct a six pyroptosis-related gene signature. Kaplan-Meier analysis, receiver operating characteristic (ROC) curves, and principal component analysis (PCA) results verified that the risk model has good performance in predicting the survival. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses revealed that the pyroptosis-related gene signature was immune related. Finally, the immune landscape and immunotherapy sensitivity prediction capabilities of the risk model were further explored. There were close correlations between the overall survival (OS) and various immune cells and immune functions. Single-sample gene set enrichment analysis (ssGSEA) showed that high risk group had decreased expression of various immune cells and lower activities of immune functions. Meanwhile, tumor mutation burden (TMB) data combining risk score could well predict the OS of HNSCC patients. However, tumor immune dysfunction and exclusion (TIDE) analysis revealed that there was no significant difference in the sensitivity to immunotherapies between high and low risk groups. Finally, a nomogram based on risk score and clinicopathological parameters was constructed. And, the risk model demonstrated better sensitivity and specificity than TIDE scores and T-cell-inflamed signature (TIS). In conclusion, although the risk model could not well predict the immune escape and response to immunotherapies, the signature established by pyroptosis-related genes, with better sensitivity and specificity than TIDE scores and TIS signature, could be used for predicting prognosis and immune status of HNSCC patients.

Dataset Information

Immune-related gene signature for predicting the prognosis of head and neck squamous cell carcinoma.

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Immune-related gene signature for predicting the prognosis of head and neck squamous cell carcinoma.

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