Salivary metabolomics for oral leukoplakia with and without dysplasia
Kenichiro Kitabatake1, Shigeo Ishikawa1, Masahiro Sugimoto2
1Department of Dentistry, Oral and Maxillofacial - Plastic and Reconstructive Surgery Faculty of Medicine, Yamagata University, Yamagata 990-9585, Japan.
Purpose:
Oral leukoplakia (OL) is a common potentially malignant oral disorder. Therefore, there is a need for simple screening methods for OL before its transformation into oral cancer. Furthermore, because invasive open biopsy is the sole method to determine if an OL lesion is dysplastic, there is also a clinical need for non-invasive methods to differentiate dysplastic OL from non-dysplastic OL. This study aimed to identify salivary metabolites that can help differentiate patients with OL from healthy controls (HC) and also dysplastic OL from non-dysplastic OL.
Material & Methods:
Whole unstimulated saliva samples were collected from patients with OL (n = 30) and HCs (n = 29). The OL group included nine patients with dysplastic OL and 20 with non-dysplastic OL. Hydrophilic metabolites in the saliva samples were comprehensively analyzed through capillary electrophoresis mass spectrometry. To evaluate the discrimination ability of a combination of multiple markers, a multiple logistic regression (MLR) model was developed to differentiate patients with OL from HCs and dysplastic OL from non-dysplastic OL.
Results:
Twenty-eight metabolites were evidently different between patients with OL and HCs. Finally, three metabolites (guanine, carnitine, and N-acetylputrescine) were selected to develop the MLR model, which resulted in a high area under curve (AUC) of the receiver operating characteristic (ROC) to differentiate patients with OL from HCs (AUC = 0.946, p < 0.001, 95% confidential interval [CI] = 0.889- 1.000). Similarly, two metabolites were evidently different between patients with dysplastic and non-dysplastic OL. Finally, only one metabolite (7-methylguanine) was selected in the MLR model, which revealed a moderate discrimination ability for dysplastic and non-dysplastic OL (AUC = 0761, p = 0.027, 95% CI = 0.551-0.972).
Conclusion:
Our candidate salivary metabolites showed potential not only to discriminate OL from HC, but also to discriminate dysplastic OL from non-dysplastic OL.
