| Primary information |
|---|
| SALID | SAL_16508 |
| Biomarker name | N-Acetylglucosamine-1-phosphate |
| Biomarker Type | NA |
| Sampling Method | The patients included OSCC (n = 6), OED (n = 10), and PSOML (n = 32). |
| Collection Method | About 4-5 ml unstimulated whole saliva was collected over 5-15 min. |
| Analysis Method | CE-TOFMS |
| Collection Site | Saliva |
| Disease Category | Premalignant Disorder |
| Disease/Condition | Oral epithelial dysplasia |
| Disease Subtype | NA |
| Fold Change/ Concentration | NA |
| Up/Downregulated | NA |
| Exosomal | NA |
| Organism | Homo sapiens |
| PMID | 30539290 |
| Year of Publication | 2019 |
| Biomarker ID | 440272 |
| Biomarker Category | Metabolite |
| Sequence | CC(=O)N[C@@H]1[C@H]([C@@H]([C@H](OC1OP(=O)(O)O)CO)O)O |
| Title of study | Identification of salivary metabolites for oral squamous cell carcinoma and oral epithelial dysplasia screening from persistent suspicious oral mucosal lesions |
| Abstract of study | OBJECTIVE: To identify salivary metabolite biomarkers to differentiate patients with oral squamous cell carcinoma and oral epithelial dysplasia (OSCC/OED) from those with persistent suspicious oral mucosal lesions (PSOML).SUBJECTS AND METHODS: Whole unstimulated saliva samples were collected from age-, sex-, and race-matched patients who had a lesion in the oral cavity and for whom open biopsies were performed. The patients included OSCC (n = 6), OED (n = 10), and PSOML (n = 32). Hydrophilic metabolites in saliva samples were comprehensively analyzed using 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 OSCC/OED from PSOML.RESULTS: Six metabolites were significantly different in OSCC/OED compared with PSOML. From these six metabolites, ornithine, o-hydroxybenzoate, and ribose 5-phosphate (R5P) were used to develop the MLR model, which resulted in a high value for the area under receiver operating characteristic curve (AUC 0.871, 95% confidential interval (CI) 0.760-0.982; p < 0.001) to discriminate OSCC/OED from PSOML.CONCLUSIONS: This is the first study to identify salivary metabolites that discriminate OSCC/OED from PSOML rather than from healthy controls. The profiles of salivary metabolites were significantly different between OSCC/OED and PSOML. The ability to discriminate OSCC/OED from PSOML is important for dentists who are not oral surgery specialists. These salivary metabolites showed potential for non-invasive screening to discriminate OSCC/OED from PSOML.CLINICAL RELEVANCE: Salivary metabolites in this study showed potential for non-invasive screening to discriminate OSCC/OED from PSOML. |