This work is licensed under Creative Commons Attribution–NonCommercial International License
(CC BY-NC 4.0).
Background:Oral lichen planus (OLP) and oral leukoplakia (OLK) are among the most prevalent oral
potentially malignant disorders (OPMDs), yet they differ in biological behavior and malignant
transformation risk. Metabolomic profiling of saliva offers a non-invasive method for detecting
biochemical alterations that may discriminate between inflammatory and dysplastic lesions.
Aim:To compare the salivary metabolomic signatures of OLP and OLK using capillary electrophoresis–
time-of-flight mass spectrometry (CE–TOF–MS) and to identify discriminatory metabolites with
diagnostic potential.
Materials and Methods:This cross-sectional comparative study included 60 participants: 20 with
histopathologically confirmed OLP, 20 with OLK, and 20 healthy controls. Unstimulated whole saliva
was collected, centrifuged, and stored at −80 °C. Metabolomic profiling was performed using CE–TOF–
MS, and metabolites were annotated with the Human Metabolome Database (HMDB). Multivariate
statistical analyses (PCA, PLS-DA) and ROC curve modeling were used to identify discriminatory
metabolites and assess diagnostic performance.
Results:A total of 178 salivary metabolites were detected, of which 34 differed significantly between
groups (p < 0.05). OLK exhibited upregulation of ornithine, indole-3-acetate, N-acetylglucosamine, and
choline, whereas OLP showed higher putrescine, ethanolamine phosphate, and alanine levels. Pathway
enrichment indicated disturbances in polyamine, amino acid, and choline metabolism. ROC analysis
identified ornithine, indole-3-acetate, and putrescine as key discriminatory metabolites (AUC = 0.93,
sensitivity 88%, specificity 85%).
Conclusion:Salivary metabolomic profiling revealed distinct biochemical signatures between OLP and
OLK. Elevated polyamine and choline metabolites in OLK reflect dysplastic metabolic reprogramming,
whereas OLP shows an inflammatory metabolic phenotype. A combined salivary metabolite panel
demonstrates high diagnostic accuracy, supporting saliva as a promising non-invasive biomarker source
for differentiating oral potentially malignant disorders.