Novel prognostic model established for patients with head and neck squamous cell carcinoma based on pyroptosis-related genes

• DOI: 10.1016/j.tranon.2021.101233
• Publication Date: 2021-09-29T11:13:03Z
• Authors: Yuchen Shen; Xinyu Li; Deming Wang; Liming Zhang; Xiao Li; Tong Xia; Xunjie Shang; Xitao Yang; Lixin Su; Xindong Fan
• Keywords: Univariate analysis; Pyroptosis

We aimed at establishing a risk - score model using pyroptosis-related genes to predict the prognosis of patients with head and neck squamous cell carcinoma (HNSCC). A total 33 were selected. then evaluated data 502 HNSCC 44 normal from TCGA database. Gene expression was profiled detect differentially expressed (DEGs). Using univariate, least absolute shrinkage selection operator (LASSO) Cox regression analyses, we generated model. Tissue samples neoplastic sites collected. qRT-PCR employed analyze mRNA level samples. Kaplan-Meier method used evaluate overall survival rate (OS). Enrichment analysis performed elucidate underlying mechanism patient's status perspective tumor immunology. 17 categorized as DEGs. GSDME, IL-6, CASP8, CASP6, NLRP1 NLRP6 establish Each in cohort calculated formula. The able independently OS (P = 0.02). showed that < 0.0001) more reliable than single gene, phenomenon verified by practical patient cohort. Additionally, enrichment indicated active immune activities low-risk group high-risk group. In conclusion, our has provided novel strategy for prediction patients' prognosis.