Oral cavity squamous cell carcinoma (OSCC), the most common malignancy of the oral cavity, is associated with poor prognosis and high mortality worldwide. Moreover, knowledge of the metabolic alterations that occur in OSCC is still limited. In the present study, we used a quantitative metabolomic approach with chemical isotope labeling (CIL) to analyze alterations in the metabolite levels in paired cancerous (T) and adjacent noncancerous (AN) tissues from 31 OSCC patients. Using volcano plot and orthogonal projections to latent structure-discriminant analysis (OPLS-DA), we uncovered 99 dysregulated metabolites in OSCC and verified the identities of seven metabolites via comparison with authenticated standards. From these seven metabolites, we constructed a 3-marker panel, consisting of putrescine, glycyl-leucine, and phenylalanine, using a support vector machine (SVM) model that can discriminate T from AN with high sensitivity and specificity based on receiver operator characteristic (ROC) analysis. Furthermore, by integrating the metabolomics profiles with transcriptomics data obtained from the same sample set, we revealed the dysregulation of the polyamine pathway in OSCC. Our findings provide insights into the metabolic perturbations present in OSCC and have uncovered potential metabolic biomarkers and therapeutic targets for use in the treatment of OSCC.
Keywords: Cancer biomarker; Cancer tissue; Chemical isotope labeling; Metabolomics; Oral cavity squamous cell carcinoma; Polyamine pathway.
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