Saliva metabolomics, a promising tool for advanced diagnostics. A breakthrough in leukoplakia diagnosis

Background: Saliva is a complex matrix produced by fluids secreted from salivary glands. It represents an informative body fluid offering insights into both health and diseases of the oral cavity and systemic alterations. Due to its non-invasive collection method, numerous studies have used saliva to identify specific biomarkers linked to pathological and physiological changes. While extensive genomic and proteomic salivary profiles for early diagnosis of oral diseases have been reported, metabolic analysis is a more recent topic. Metabolomics is a systematic and comprehensive analysis of metabolites in a biological system, which provides a functional snapshot of an organism’s condition. It can be employed for various applications, including biomarker identification and the discovery of new therapeutic targets. Leukoplakia is characterized by white patches on the inner surfaces of the oral cavity and can potentially progress to oral squamous cell carcinoma. This underscores the need for effective screening and early diagnostic procedures. In this pilot study, we employed salivary metabolomics to identify potential biomarkers for leukoplakia, both with and without dysplasia. Methods: Unstimulated saliva was collected from 26 patients with oral leukoplakia, either with or without dysplasia, and 12 healthy subjects. 1H-NMR spectroscopy enabled the identification and quantification of 72 salivary metabolites. Univariate and multivariate statistical methods were applied to evaluate metabolite concentration profiles. Results: The salivary metabolite profile of leukoplakia (w/wo dysplasia) exhibited specific alterations compared to healthy subjects. These metabolic changes were more pronounced in cases of dysplastic lesions. Multivariate ROC curve analysis, based on selected metabolites, ascribed the highest diagnostic accuracy to the model, which discriminated dysplastic leukoplakia from healthy cases. Conclusions: Our metabolomic approach and the resulting salivary models offer promising non-invasive biomarkers for the clinical diagnosis of leukoplakia. With validation in larger cohorts, these tools could improve clinical monitoring and support precision diagnosis throughout disease progression.