Peroxisome proliferator‐activated receptors signature reveal the head and neck squamous cell carcinoma energy metabolism phenotype and clinical outcome

Abstract Background Peroxisome proliferator activating receptors (PPARs) are important regulators of nuclear hormone receptor function, and they play a key role in biological processes such as lipid metabolism, inflammation and cell proliferation. However, their role in head and neck squamous cell carcinoma (HNSC) is unclear. Methods We used multiple datasets, including TCGA‐HNSC, GSE41613, GSE139324, PRJEB23709 and IMVigor, to perform a comprehensive analysis of PPAR‐related genes in HNSC. Single‐cell sequencing data were preprocessed using Seurat packets, and intercellular communication was analyzed using CellChat packets. Functional enrichment analysis of PPAR‐related genes was performed using ClusterProfile and GSEA. Prognostic models were constructed using LASSO and Cox regression models, and immunohistochemical analyses were performed using human protein mapping (The Human Protein Atlas). Results Our single‐cell RNA sequencing analysis revealed distinct cell populations in HNSC, with T cells having the most significant transcriptome differences between tumors and normal tissues. The PPAR features were higher in most cell types in tumor tissues compared with normal tissues. We identified 17 PPAR‐associated differentially expressed genes between tumors and normal tissues. A prognostic model based on seven PPAR‐associated genes was constructed with high accuracy in predicting 1, 2 and 3 year survival in patients with HNSC. In addition, patients with a low risk score had a higher immune score and a higher proportion of T cells, CD8+ T cells and cytotoxic lymphocytes. They also showed higher immune checkpoint gene expression, suggesting that they might benefit from immunotherapy. PPAR‐related genes were found to be closely related to energy metabolism. Conclusions Our study provides a comprehensive understanding of the role of PPAR related genes in HNSC. The identified PPAR features and constructed prognostic models may serve as potential biomarkers for HNSC prognosis and treatment response. In addition, our study found that PPAR‐related genes can differentiate energy metabolism and distinguish energy metabolic heterogeneity in HNSC, providing new insights into the molecular mechanisms of HNSC progression and therapeutic response.