Abstract
Disulfidptosis is a newfound programmed cell death (PCD) mode characterized by disulfide stress. Nevertheless, the characteristics and functional significance of disulfidptosis-related genes in head and neck squamous cell carcinoma (HNSCC) are still largely unknown. In this study, several computer-aided bioinformatic analyses were performed. The Nonnegative Matrix Factorization (NMF) method classified The Cancer Genome Atlas (TCGA) patients into two clusters according to the expression of disulfidptosis-related genes. The relative compositions of cells in the tumor microenvironment (TME), mutant landscape, lasso regression analysis, and predicted clinical outcome were performed by analyzing bulk RNA-sequencing data. Besides, single-cell sequencing data (scRNA) was analyzed by Seurat, CopyKAT, and monocle2 to reveal the expression characteristics of disulfidptosis-related genes. Moreover, the spatial distribution characteristics of each cell subgroup in the section and the functional significance of cancer-associated fibroblasts (CAFs) were elucidated by STUtility, SpaCET, and SPATA2. Here, two clusters with different expression characteristics of disulfidptosis-related genes were identified. Cluster 1 (C1) patients had a worse prognosis and a higher proportion of stromal cells but lower effector T cell infiltration than cluster 2 (C2). A novel prognostic model was established and verified in our patient cohort. Additionally, diploid and inflammatory CAFs (iCAFs) showed higher disulfidptosis-related gene expression levels. Furthermore, the CCNC and CHMP1B expressions significantly changed following CAFs differentiation. Disulfidptosis-related genes exhibited extensive and differential spatial expression on tissue sections. Collectively, our study may contribute to revealing the function of disulfidptosis, and improve the expansion of knowledge of crosstalk between cancer cells and CAFs.