A prognostic model built on amino acid metabolism patterns in HPV-associated head and neck squamous cell carcinoma.

Objectives: To compare amino acid metabolism patterns between HPV-positive and HPV-negative head and neck squamous cell carcinoma (HNSCC) patients and identify key genes for a prognostic model.
Design: Utilizing the Cancer Genome Atlas dataset, we analyzed amino acid metabolism genes, differentiated genes between HPV statuses, and selected key genes via LASSO regression for the prognostic model. The model's gene expression was verified through immunohistochemistry in clinical samples. Functional enrichment and CIBERSORTx analyses explored biological functions, molecular mechanisms, and immune cell correlations. The model's prognostic capability was assessed using nomograms, calibration, and decision curve analysis.
Results: We identified 1157 key genes associated with amino acid metabolism in HNSCC and HPV status. The prognostic model, featuring genes like IQCN, SLC22A1, SYT12, and TLX3, highlighted functions in development, metabolism, and pathways related to receptors and enzymes. It significantly correlated with immune cell infiltration and outperformed traditional staging in prognosis prediction, despite immunohistochemistry results showing limited clinical identification of HPV-related HNSCC.
Conclusions: Distinct amino acid metabolism patterns differentiate HPV-positive from negative HNSCC patients, underscoring the prognostic model's utility in predicting outcomes and guiding therapeutic strategies.
Competing Interests: Declaration of Competing Interest All authors declare that they have no competing interests.
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