Identification of cuproptosis‐related subtypes and characterization of the tumor microenvironment landscape in head and neck squamous cell carcinoma

Background: Cuproptosis is considered a novel copper-dependent cell death model. In this study, we established a novel scoring system based on 10 cuproptosis-related genes (CRGs) to predict the prognosis and immune landscape of head and neck squamous cell carcinoma (HNSCC). Methods: The RNA-seq data of HNSCC patients were downloaded from the GEO and TCGA databases and were merged into a novel HNSCC cohort. Multiomics landscape analyses were conducted, including tumor mutation burden (TMB), copy number variations and the interaction network of CRGs. Patients were then divided into different cuproptosis subtypes based on the expression of 10 CRGs and subsequently regrouped into novel gene clusters referring to differentially expressed genes. A cuproptosis score (CS) system was established using principal component analysis. The CIBERSORT, ssGSEA and ESTIMATE algorithms were used to assess the tumor immune microenvironment. Moreover, the immunotherapeutic and chemotherapeutic responses were assessed. Results: Patients were divided into three cuproptosis subtypes and subsequently regrouped into three gene clusters, reflecting different immune infiltration. Assessed by the CS system, those with higher CSs exhibited worse prognosis and higher TMB frequency. Nevertheless, the immune-related analysis revealed patients in the low-CS group appeared immunosuppressive and easily suffered from immune escape. High CSs possibly show high expression of immune checkpoint genes and enhance chemotherapy sensitivity to cisplatin, docetaxel, and gemcitabine. Conclusion: We established a novel scoring system to predict the prognosis and immune landscape of HNSCC patients. This signature exhibits satisfactory predictive effects and the potential to guide comprehensive treatment for patients.