<p>Altered metabolism plays a crucial role in the development of lymph node metastasis (LNM) in head and neck cancer (HNC). Despite significant advancements in diagnostic technologies, only one-third of HNC cases are diagnosed at an early stage, while the majority are diagnosed at advanced stages, resulting in poor clinical outcome. Therefore, the identification of reliable, non-invasive biomarkers is essential for early detection and improved prognosis. The present study aims to identify differential serum metabolic profiles in HNC patients with and without LNM using an untargeted liquid chromatography–mass spectrometry (LC–MS)-based metabolomics approach, in order to discover potential biomarkers for early diagnosis, disease progression, and prognostic evaluation. Serum samples from 10 HNC patients without LNM, 10 HNC patients with LNM, and 10 healthy controls were analyzed. LC–MS profiling identified approximately 200 metabolites, and the generated RAW files were processed using Compound Discoverer 3.2 software. Metabolite annotation was performed using ChemSpider and mzCloud databases, incorporating HMDB and KEGG resources. Statistical analyses, including t-test, one-way ANOVA, and principal component analysis (PCA), heatmap and boxplot were performed to assess metabolic differences. Significant alterations were observed in metabolites, including L-arginine, ricinoleic acid, 1-monoacylglycerol, DL-2-aminooctanoic acid, N-decanoylglycine, piperine, LysoPE (18:2), leucylphenylalanine, TG (64:17), and trimethyllysine TML. These findings may serve as potential biomarkers for early detection and targeted therapeutic strategies in HNC, providing valuable insights into disease progression and prognosis.</p> Graphical abstract <p>Schematic presentation of the workflow of metabolomics analysis of serum sample by LC–MS.</p> <p></p>