Background Pyroptosis plays an essential function in carcinogenesis and the antitumor immune response. Herein, we constructed a pyroptosis‐related long noncoding RNA (prLncRNA) signature to predict therapeutic effects and outcomes for head and neck squamous cell carcinoma (HNSCC) patients. Methods Patients obtained from the TCGA‐HNSC project were divided randomly into the training as well as the validation sets at a ratio of 7:3. A novel prognostic prLncRNA signature was constructed from the results of the training set using the least absolute shrinkage and selection operation. The medium value was used as the basis for categorizing all HNSCC patients into a low‐ or high‐risk cohort. Cox regression and Kaplan–Meier (KM) survival analyses were executed to estimate the prognostic value. We also evaluated the functional enrichment, tumor microenvironment, immune cell infiltration, and the sensitivity to chemotherapy and immunotherapy between the high‐ and low‐risk cohorts. Results Nineteen prognostic prlncRNAs were identified to establish the prognostic signature. Multivariate Cox regression and KM survival analyses confirmed that this prlncRNA signature might serve as an independent prognostic indicator of patient survival, which was subsequently confirmed using a validating dataset. Multiple ROC curves indicated the prlncRNA signature presented a more predictive power than clinicopathological factors (age, sex, tumor grade, and tumor stage). GO, KEGG, and GSEA enrichment analysis disclosed several immune‐related pathways which appeared to be enhanced in the low‐risk cohort. ESTIMATE, CIBERSORT, and ssGSEA algorithms indicated considerable differences in the tumor microenvironment and immune cell infiltration in the low‐ and high‐risk cohorts. Furthermore, the low‐risk cohort was predicted to achieve a better response to immunotherapeutic drugs, while in contrast, the high‐risk cohort would be more sensitive to chemotherapy drugs. Conclusions Our findings robustly demonstrate that our constructed prlncRNA signature could serve as an efficient indicator of prognosis, immunotherapy response, and chemosensitivity for HNSCC patients.

Background: Pyroptosis plays an essential role in tumor immune responses and inflammation related to chemotherapy. Herein, we studied the characteristic patterns of pyroptosis in head and neck squamous cell carcinoma (HNSCC) to determine their prognostic and therapeutic effects. Methods: Consensus clustering analysis was performed to classify patients into pyroptosis or gene clusters. A novel pyroptosis score was constructed by principal component analysis. Kaplan-Meier survival curves were used to show the prognostic value. We also assessed the functional enrichment, tumor mutation burden, immune cell infiltration, and the sensitivity to chemotherapy and immunotherapy between high and low pyroptosis score group. Results: Two distinct pyroptosis clusters were defined based on the mRNA expression profiles of PRGs, which were related to immune activation in HNSCC. Notably, a pyroptosis score was constructed according to different expression gene signatures, and then, each HNSCC patient was classified into a low or high pyroptosis score group. Patients with low pyroptosis scores had better immunotherapeutic responses and higher sensitivities to chemotherapeutic agents (paclitaxel, docetaxel, and gemcitabine). Kaplan-Meier survival curves showed that the pyroptosis patterns were independent prognostic indicators regardless of the level of tumor mutation burden. Conclusions: Pyroptosis plays an essential role in immune infiltration in HNSCC. Quantifying the pyroptosis score of individual patients might suggest prognostic, immunotherapeutic, and chemotherapeutic strategies for HNSCC.

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Background Head and neck squamous cell carcinoma (HNSCC) is one of the most common malignant cancers, and few studies have demonstrated the value of ferroptosis-related genes in prognosis. Methods The original counts of RNA sequencing data and clinicopathological data were obtained from TCGA and GSE65858 datasets. Common ferroptosis-related genes related to prognosis were identified from the training set and were included in LASSO to determine the best prognosis. To evaluate the efficacy, time-dependent ROC and Kaplan–Meier (KM) survival analyses were applied. Moreover, univariate and multivariate Cox regression analyses were used to screen independent parameters of prognosis and build a nomogram. Eventually, possible biological pathways were proposed based on GSEA. Results Among 242 ferroptosis-related genes, we identified that the FLT3, IL6, Keap1, NQO1, SOCS1 and TRIB3 genes were significantly connected with HNSCC patient prognosis as a six-gene signature. After, the patients were divided into high- and low-risk groups based on the six-gene signature. The KM survival curves demonstrated that the high-risk group had worse OS (p < 0.0001) and higher AUC values (0.654, 0.735, and 0.679 for 1-, 3-, and 5-year survival, respectively) for the prognostic signature of the six genes compared with other genes, which were also validated in the GSE65858 dataset. Moreover, GSEA suggested that the epithelial mesenchymal transition pathway was abundant and that the mesenchymal status in the high-risk group was substantially higher than that in the low-risk group. Finally, the immune microenvironment and differences in the content of immune cell types were demonstrated. Conclusion We established a six-ferroptosis-related-gene model crossing clinical prognostic parameters that can predict HNSCC patient prognosis and provide a reliable prognostic evaluation tool to assist clinical treatment decisions.

Pyroptosis, a pro-inflammatory form of programmed cell death, is associated with carcinogenesis and progression. However, there is little information concerning pyroptosis-related genes (PRGs) in laryngeal squamous cell carcinoma (LSCC). Herein, we aim to explore the prognostic value of PRGs in LSCC. The expression and clinical data of 47 PRGs in LSCC patients were obtained from The Cancer Genome Atlas. A novel prognostic PRG signature was constructed using least absolute shrinkage and selection operator analysis. Receiver operating characteristic (ROC) curves were drawn, and Kaplan-Meier survival Cox proportional hazard regression analyses were performed to measure the predictive capacity of the PRG signature. Furthermore, we constructed a six-PRG signature to divide LSCC patients into high- and low-risk groups. Patients in the high-risk group had worse overall survival than the low-risk group. The area under the time-dependent ROC curve was 0.696 for 1 year, 0.784 for 3 years, and 0.738 for 5 years. We proved that the PRGs signature was an independent predictor for LSCC. Functional enrichment analysis indicated that several immune-related pathways were significantly enriched in the low-risk group. Consistent with this, patients with low-risk scores had higher immune scores and better immunotherapeutic responses than the high-risk group. In conclusion, we established a novel PRGs signature that can predict outcome and response to immunotherapy of LSCC, pyroptosis may be a potential target for LSCC.