A pyroptosis-related gene expression signature predicts immune microenvironment and prognosis in head and neck
Wenyuan Zhou1, Mei Feng2, Fei Qi3
1Key Laboratory of Carcinogenesis and Translational Research, (Ministry of Education/Beijing), NMPA Key Laboratory for Research and Evaluation of Radiopharmaceuticals (National Medical Products Administration), Department of Nuclear Medicine, Peking University Cancer Hospital & Institute, Beijing, 100142, China.
Background:
Head and neck squamous cell carcinoma (HNSCC) is a highly heterogeneous and aggressive malignancy with a poor prognosis. Pyroptosis triggered by gasdermins family proteins is reported vital for tumor microenvironment and cancer progression. However, pyroptosis-related gene expression and its relationship with immune infiltration and prognosis of HNSCC have not been fully defined.
Material And Methods:
RNA-sequencing data of HNSCC patients were acquired from The Cancer Genome Atlas (TCGA) database. A pyroptosis-related gene expression signature and infiltrated immune cells were analyzed. Univariate, least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression and nomogram analyses were used to construct a clinical-molecular risk model for survival prognosis.
Results:
HNSCC was classified into three different molecular subtypes based on the expression information of pyroptosis-related genes. Immune cell infiltration was demonstrated to be distinct between the three subtypes. The segregation of patients into the high-risk group and low-risk group, were carried out using the signature of differential expression genes (DEGs) signature among the three molecular subtypes. The precision of this signature was corroborated by Receiver operating characteristic curve (ROC) analysis with the 3-year area under time-dependent ROC curve (AUC) reaching 0.711. The risk model was validated in another dataset from the Gene Expression Omnibus (GEO) database. Subsequently we established a clinical-molecular nomogram which combined the risk score with age and stage. The calibration plots for predicting the overall survival rate of 1-, 3-, and 5-years indicated that the nomogram performs well.
Conclusion:
The expression signature that encompasses pyroptosis-related genes could be used as molecular classification for HNSCC and pyroptosis might be a promising therapeutic target in HNSCC.
