ObjectiveThis study was conducted to distinguish salivary metabolites in oral squamous cell carcinoma (OSCC) from those in oral lichen planus (OLP) to identify practical biomarkers for the discrimination of OSCC from OLP.Subjects and MethodsWhole unstimulated saliva samples were collected from patients with OSCC (n = 34) and OLP (n = 26). Hydrophilic metabolites in the saliva samples were comprehensively analysed by 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 from OLP.ResultsFourteen metabolites were found to be significantly different between the OSCC and OLP groups. Among them, indole‐3‐acetate and ethanolamine phosphate were used to develop the MLR model. The combination of these two metabolites showed a high area under the receiver operating characteristic curve (0.856, 95% confidential interval: 0.762–0.950; p < .001) for discriminating OSCC from OLP.ConclusionsWe identified salivary metabolites for discerning between OSCC and OLP, which is clinically important for detecting the malignant transformation of OLP by both dentists and oral surgery specialists. Our candidate salivary metabolites show potential for non‐invasive screening of OSCC versus OLP.

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Background Saliva is often used as a biomarker for the diagnosis of some oral and systematic diseases, owing to the non‐invasive attribute of the fluid. In this study, we aimed to identify salivary biomarkers for distinguishing lung cancer (LC) from benign lung lesion (BLL). Materials and Methods Unstimulated saliva samples were collected from 41 patients with LC and 21 with BLL. Salivary metabolites were comprehensively analyzed using capillary electrophoresis mass spectrometry. To differentiate between patients with LCs and BLLs, the discriminatory ability of each biomarker was assessed. Furthermore, a multiple logistic regression (MLR) model was developed for evaluating discriminatory ability of each salivary metabolite. Results The profiles of 10 salivary metabolites were remarkably different between the LC and BLL samples. Among them, the concentration of salivary tryptophan was significantly lower in the samples from patients with LC than in those from patients with BLL, and the area under the curve (AUC) for discriminating patients with LC from those with BLL was 0.663 (95% confidence interval [CI] = 0.516–0.810, p = 0.036). Furthermore, from the MLR model developed using these metabolites, diethanolamine, cytosine, lysine, and tyrosine, were selected using the back‐selection regression method. The MLR model based on these four metabolites had a high discriminatory ability for patients with LC and those with BLL (AUC = 0.729, 95% CI = 0.598–0.861, p = 0.003). Conclusion The four salivary metabolites can serve as potential non‐invasive biomarkers for distinguishing LC from BLL.

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This study aimed to identify salivary metabolomic biomarkers for predicting the prognosis of oral squamous cell carcinoma (OSCC) based on comprehensive metabolomic analyses. Quantified metabolomics data of unstimulated saliva samples collected from patients with OSCC (n = 72) were randomly divided into the training (n = 35) and validation groups (n = 37). The training data were used to develop a Cox proportional hazards regression model for identifying significant metabolites as prognostic factors for overall survival (OS) and disease-free survival. Moreover, the validation group was used to develop another Cox proportional hazards regression model using the previously identified metabolites. There were no significant between-group differences in the participants’ characteristics, including age, sex, and the median follow-up periods (55 months [range: 3–100] vs. 43 months [range: 0–97]). The concentrations of 5-hydroxylysine (p = 0.009) and 3-methylhistidine (p = 0.012) were identified as significant prognostic factors for OS in the training group. Among them, the concentration of 3-methylhistidine was a significant prognostic factor for OS in the validation group (p = 0.048). Our findings revealed that salivary 3-methylhistidine is a prognostic factor for OS in patients with OSCC.