A Ferroptosis-Related Prognostic Signature Based on Antitumor Immunity and Tumor Protein p53 Mutation Exploration for Guiding Treatment in Patients With Head and Neck Squamous Cell Carcinoma.

Due to the lack of accurate guidance of biomarkers, the treatment of head and neck squamous cell carcinoma (HNSCC) has not been ideal. Ferroptosis plays an important role in tumor suppression and treatment of patients. However, tumor protein p53 (TP53) mutation may promote tumor progression through ferroptosis. Therefore, it is particularly important to mine prognostic-related differentially expressed ferroptosis-related genes (PR-DE-FRGs) in HNSCC to construct a prognostic model for accurately guiding clinical treatment. First, the HNSCC data obtained from The Cancer Genome Atlas (TCGA) was used to identify PR-DE-FRGs for screening candidate genes to construct a prognostic model. We not only used a variety of methods to verify the accuracy of the model for predicting prognosis but also explored the role of ferroptosis in the development of HNSCC from the perspective of the immune microenvironment and mutation. Finally, we explored the correlation between the prognostic model and clinical treatment and drew a high-precision nomogram to predict the prognosis. Seventeen of the 29 PR-DE-FRGs were selected to construct a prognostic model with good predictive performance. Patients in the low-risk group were found to have a greater number of CD8 + T cells, follicular helper T cells, regulatory T cells, mast cells, T-cell costimulations, and type II interferon responses. A higher tumor mutation burden (TMB) was observed in the low-risk group and was associated with a better prognosis. A higher risk score was found in the TP53 mutation group and was associated with a worse prognosis. The risk score is closely related to the expression of immune checkpoint inhibitors (ICIs)-related genes such as PD-L1 and the IC50 of six chemotherapeutic drugs. The nomogram we constructed performs well in predicting prognosis. Ferroptosis may participate in the progression of HNSCC through the immune microenvironment and TP53 mutation. The model we built can be used as an effective predictor of immunotherapy and chemotherapy effects and prognosis of HNSCC patients.