Construction and validation of a prognostic signature based on seven endoplasmic reticulum stress-related lncRNAs for patients with head and neck squamous cell carcinoma
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ABSTRACT:
SUBMITTER: Zhou M
PROVIDER: S-EPMC10725423 | biostudies-literature | 2023 Jan
REPOSITORIES: biostudies-literature
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Project description:Head and neck squamous carcinoma (HNSC) is a prevalent malignant disease, with the majority of patients being diagnosed at an advanced stage. Endoplasmic reticulum stress (ERS) is considered to be a process that promotes tumorigenesis and impacts the tumor microenvironment (TME) in various cancers. The study aims to investigate the predictive value of ERS in HNSC and explore the correlation between ERS-related genes and TME. A series of bioinformatics analyses were carried out based on mRNA and scRNA-seq data from the TCGA and GEO databases. We conducted RT-qPCR and western blot to validate the signature, and performed cell functional experiments to investigate the in vitro biological functions of the gene. We identified 63 ERS-related genes that were associated with outcome and stage in HNSC. A three-gene signature (ATF6, TRIB3, and UBXN6) was developed, which presents predictive value in the prognosis and immunotherapy response of HNSC patients. The high-risk group exhibited a worse prognosis but may benefit from immunotherapy. Furthermore, there was a significant correlation between the signature and immune infiltration. In the high-risk group, fibroblasts were more active in intercellular communication, and more T cells were observed at the end of the sequential phase. The genes in the ERS-related signature were overexpressed in HNSC cells, and the knockdown of TRIB3 significantly inhibited cell proliferation and migration. This study established a novel ERS-related signature that has potential implications for HNSC therapy and the understanding of TME.
| S-EPMC11266686 | biostudies-literature
Project description:In this study, we developed a long noncoding RNA (lncRNA)-based prognostic signature for stratification of patients with head a nd neck squamous cell carcinoma (HNSCC). In total, 493 HNSCC samples obtained from the Cancer Genome Atlas database were divided into training and testing cohorts (3:2 ratio). We identified 3913 immune-related lncRNAs in the HNSCC training cohort by Pearson correlation analysis; only seven were independently associated with overall survival and were used to develop an immune-related lncRNA prognostic signature (IRLPS) grouping of HNSCC patients into high- and low-IRLPS subgroups. Univariate and multivariate Cox analyses revealed that low-IRLPS patients had a better prognosis in all the cohorts, which was retained after stratification by sex, grade, and HPV status. Although the TNM stage was also an independent prognostic factor, the IRLPS had a better discriminability with higher AUC at the 3- and 5-year follow-ups in all cohorts. Low-IRLPS samples had more immune cell infiltration and were enriched in immune-related pathways, while high- IRLPS samples were enriched in metabolic pathways. A nomogram constructed including age, TNM stage, and IRLPS showed good calibration. Thus, IRLPS improves the prognostic prediction and also distinguishes different tumor microenvironment (TME) in HNSCC patients.
| S-EPMC7982618 | biostudies-literature
Project description:BackgroundRadiotherapy is an effective treatment for head and neck squamous cell carcinoma (HNSCC), however how to predict the prognosis is not clear.MethodsHere we collected 262 radiosensitivity-associated genes, screened and constructed a prognostic nine-gene risk model through univariate COX, lasso regression, stepwise regression and multivariate COX analysis for transcriptome and clinical information of HNSCC patients obtained from the cancer genome atlas (TCGA) and gene expression omnibus (GEO) databases.ResultsThe reliability and robustness of the risk model were verified by receiver operating characteristic (ROC) curves, risk maps, and Kaplan-Meier (KM) curves analysis. Differences in immune cell infiltration and immune-related pathway enrichment between high-risk and low-risk subgroups were determined by multiple immune infiltration analyses. Meanwhile, the mutation map and the responses to immunotherapy were also differentiated by the prognostic nine-gene signature associated with radiosensitivity. These nine genes expression in HNSCC was verified in the Human Protein Atlas (HPA) database. After that, these nine genes expression was verified to be related to radiation resistance through in-vitro cell experiments.ConclusionsAll results showed that the nine-gene signature associated with radiosensitivity is a potential prognostic indicator for HNSCC patients after radiotherapy and provides potential gene targets for enhancing the efficacy of radiotherapy.
| S-EPMC10579965 | biostudies-literature
Project description:BackgroundHead and neck squamous cell carcinoma (HNSCC) is a multisite malignancy that responds well to immunotherapy. Despite the initial enthusiasm, the clinical benefits of immunotherapy in HNSCC patients are overall limited. Endoplasmic reticulum stress (ERS) has been indicated to play a key role in the process of anti-tumor immune response mediation. However, ERS-related biomarkers which can accurately predict prognosis and immunotherapy response in HNSCC are still lacking.Methods and resultsIn this study, we identify and validate an ERS-related signature comprises of six genes (ASNS, EXOSC6, BAK1, TPP1, EXOSC8, and TATDN2) that can predict the prognosis of HNSCC patients. GSEA analysis indicates that the ERS-related signature is significantly correlated with tumor immunity in HNSCC. Moreover, the infiltration of naive B cells and CD8 + T cells are significantly diminished in patients with high-risk scores compared to those with low-risk scores, while macrophages and activated mast cells are remarkably enhanced. Furthermore, the ERS-related signature also displays a tremendous potential for predicting immunotherapy response in HNSCC.ConclusionsOur study identifies an ERS-related signature that can predict the prognosis of HNSCC patients and highlights its potential value as a predictive biomarker of immunotherapy response, potentially enabling more precise and personalized immunotherapy response and paving the way for further investigation of the prognostic and therapeutic potentials of ERS.
| S-EPMC10122290 | biostudies-literature
Project description:Endoplasmic reticulum stress (ERS) and cuproptosis have remarkable effects on hepatocellular carcinoma (HCC) leading to a poor prognosis. The current study aimed to explore credible signature for predicting the prognosis of HCC based on ERS and cuproptosis-related lncRNAs. In our study, clinical and transcriptomic profiles of HCC patients were obtained from the Cancer Genome Atlas (TCGA) database. An ERS and cuproptosis-related lncRNA prognostic signature, including NRAV, SNHG3, LINC00839 and AC004687.1, was determined by correlation tests, Cox regression analysis, least absolute shrinkage, and selection operator (LASSO) methods. Survival and predictive value were evaluated using Kaplan-Meier and receiver operating characteristic (ROC) curves, while calibration and nomograms curves were developed. Besides the enrichment analyses for ERS and cuproptosis-related lncRNAs, mutational status and immune status were assessed with TMB and ESTIMATE. Additionally, consensus cluster analysis was employed to compare cancer subtype differences, while drug sensitivity and immunologic efficacy were evaluated for further exploration. qRT-PCR and CCK-8 were utilized to verify the alteration of the prognostic lncRNAs expression and proliferation in vitro. High-risk groups exhibited poorer prognosis. The signature exhibited robust predictive value as an independent prognostic indicator and showed significant correlation with clinicopathological features. In the enriched analysis, biological membrane pathways were enriched. Low-risk patients had lower TMB and higher immune status. A cluster analysis revealed that cluster 2 had the best clinical immunological efficacy and most active immune function. In brief, our constructed signature with ERS and cuproptosis-related lncRNAs was associated survival outcomes of HCC, and can be used to predict the clinical classification and curative effect.
| S-EPMC11471205 | biostudies-literature
Project description:Background/purposeAnalysis of endoplasmic reticulum stress (ERS)-related long noncoding RNAs (LncRNAs) may enable prognostic stratification in patients with head and neck squamous cell carcinoma (HNSCC). This study aimed to comprehensively analyze the ERS-related LncRNAs signature and its effects on the prognosis, tumorigenesis, and tumor immune microenvironment in HNSCC.Materials and methodsThe transcriptome data of HNSCC were obtained from TCGA. Least absolute shrinkage selection operator algorithm, and multivariate Cox regression were used to screen LncRNAs for the signature construction. Somatic mutation, gene enrichment, and immune infiltration analyses were further performed.Results458 ERS-related LncRNAs were identified and 55 of which were correlated with HNSCC prognosis. Ten ERS-related LncRNAs were selected to establish a risk prediction signature. When dividing patients into high-risk and low-risk groups by signature score, high-risk group correlated with worse survival rates (hazard ratio = 1.211; 95% confidence interval 1.123-1.306, P < 0.001). The area under the curve was 0.751 and 0.716 in the training and validation cohorts at 3-year. Moreover, high-risk group have increased somatic mutation rates and reduced infiltration abundancy of B cells and CD8+ T cells.ConclusionThe prognostic signature based on ERS-related LncRNAs may serve as a predictor of altered oncogene mutations and immune microenvironment, which provided an insight into the relationship between ERS, LncRNAs, and tumor progression.
| S-EPMC10068581 | biostudies-literature
Project description:BackgroundHead and neck squamous cell carcinoma (HNSCC) is a malignancy of epithelial origin and with poor prognosis. Exploring the biomarkers and prognostic models that can contribute to early tumor detection is meaningful. A comprehensive analysis was conducted according to the stage-related signature genes of HNSCC, and a prognostic model was developed to validate their ability to predict the prognosis.MethodsThe transcriptome profiles and clinical information of HNSCC patients were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) respectively. mRNA expressions of differentially expressed genes (DEGs) were analyzed in stage I-II patients and stage III-IV patients from TCGA by R packages. A protein-protein interaction (PPI) network and core-gene network map were constructed, and Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed to examine pathway enrichment. Kaplan-Meier, least absolute shrinkage and selection operator (LASSO), and multivariate Cox regression were applied to establish a stage-associated signature model. A Spearman analysis was conducted to examine the correlations between the characteristic genes and immune cell infiltration. Kaplan-Meier analysis and a receiver operating characteristic (ROC) curve were used to test the effectiveness of the model. Univariate multivariate Cox regression analyses were used to assess whether the risk score was an independent prognostic indicator for HNSCC.ResultsIn TCGA cohort, 5 genes (i.e., BRINP1, IL17A, ALB, FOXA2, and ZCCHC12) in the constructed prognostic risk model were associated with prognosis. Patients in the low-risk group had a better prognosis outcome than those in the high-risk group. The predictive power was good because all the area under the curve (AUC) of the risk score was higher than 0.6. Risk score [hazard ratio (HR) =1.985; P<0.001] was an independent risk factor for the prognosis of HNSCC. The results in the GEO cohort were consistent with those in the TCGA cohort.ConclusionsWe constructed and verified a prognostic risk model of stage-related signature genes for HNSCC based on the GEO and TCGA data. Due to the good predictive accuracy of this model, the prognosis of and the tumor immune cell infiltration with patients can be estimated.
| S-EPMC9843360 | biostudies-literature
Project description:Long non-coding RNAs (lncRNAs) are promising cancer prognostic markers. However, the clinical significance of lncRNA signatures in evaluating overall survival (OS) outcomes of head and neck squamous cell carcinoma (HNSCC) has not been explored. This study aimed to assess the significance of lncRNA in HNSCC and to develop a lncRNA signature related to OS in HNSCC. LncRNA expression matrices were retrieved from the Cancer Genome Atlas (TCGA) data. Least Absolute Shrinkage and Selection of the Operator (LASSO), univariate and multivariate Cox regression were used for establishing a prognostic model. In vitro experiments were carried out to demonstrate the biological role of lncRNA. A prognosis model based on 7 DElncRNAs was finally established.The patients were then divided into high-risk and low-risk groups. Relative to the low-risk group, overall survival times for patients in the high-risk group were significantly low (P=2.466e-07). Risk score remained an independent prognostic factor in univariate (HR=1.329, 95%CI=1.239-1.425, p < 0.001) and multivariate (HR=1.279, 95%CI=1.184-1.382, p < 0.001) Cox regression analyses. The area under the curve (AUC) of the signature was as high as 0.78. Expressions of FOXD2-AS1 in tumor tissues were elevated, and significantly correlated with OS (P=0.008). FOXD2-AS1 silencing then significantly reduced HNSCC cell proliferation, invasion, and migration. In conclusion, a lncRNA signature was established for HNSCC prognostic prediction and FOXD2-AS1 was identified as an HNSCC oncogene.
| S-EPMC8809959 | biostudies-literature
Project description:Head and neck squamous cell carcinoma (HNSCC) is among the most destructive of tumors, leading to considerable morbidity and mortality. Abnormal immune microenvironment is closely associated with tumor progression. This study aimed to construct a robust immune prognostic model for HNSCC. The RNA-seq transcriptome data and clinical information of HNSCC were downloaded from The Cancer Genome Atlas (TCGA) database. The key pathways and transcriptional factors (TFs) that are correlated with significantly altered immune related genes were identified. A robust immune prognostic model was constructed and further validated using a discovery-validation cohort design. An immune prognostic signature-based nomogram model was also developed. We have identified 400 significantly changed immune related genes in HNSCC. In addition, functional analysis of the altered immune related genes revealed many biological functions and pathways that might affect the tumor immune microenvironment. FOXP3, SNAI2, and STAT1 were identified as the hub TFs for regulating immunological changes in HNSCC. Moreover, an immune related gene-based prognostic signature significantly associated with the overall survival (OS) of HNSCC was constructed in the discovery cohort, and successfully validated in the validation cohort. Finally, a nomogram model based on immune prognostic signature was built and exhibited good performance for predicting the OS of HNSCC. In conclusion, the immune prognostic model is robust for predicting the prognosis of HNSCC and may evolve as a promising tool for risk evaluation and therapeutic selection.
| S-EPMC7667274 | biostudies-literature
Project description:Primary risk factors of head and neck squamous cell carcinoma (HNSCC) include human papillomavirus (HPV) infection and exposure to tobacco and excessive alcohol. Despite currently available treatments, patients with recurrent HNSCC still have poor survival, highlighting the need for innovative therapies. PV-10, also known as rose bengal sodium (RBS, 4,5,6,7-tetrachloro-2′,4′,5′,7′-tetraiodofluorescein disodium), is a small molecule being developed as an intralesional (IL) therapeutic agent, exhibiting substantial anti-tumor activity across diverse cancer types, but current knowledge regarding the molecular mechanisms involved in response to PV-10 remains limited. We evaluated the cytotoxic effects of PV-10 in HNSCC and explored its molecular mechanisms. In vitro, we found that PV-10 induced cytotoxicity in mEER and MTE-RAS cell lines, primarily by increasing the production of reactive oxygen species and leading to apoptosis through a caspase-dependent mechanism. Additionally, we observed that PV-10 treatment increased the release of damage-associated molecular pattern molecules such as HMGB1 and ATP and enhanced expression of calreticulin, HSP-70, and HSP-90 indicating potent immunogenic cell death (ICD). In vivo, IL PV-10 injections led to significant tumor regression in both mEER and MTE-Ras models. Complete responses (CR) were observed in 7 of 21 (33%) mice in mEER although no CR was observed in MTE-Ras. Our data suggests that one of the possible mechanisms by which PV-10 triggers ICD is by inducing endoplasmic reticulum stress, autophagy, and apoptosis. Our findings contribute to further understanding of the underlying mechanisms of PV-10 induced cytotoxicity and to develop future clinical trials in locally recurrent HNSCC.
2025-08-13 | GSE289911 | GEO