AIM The present multicenter pilot study aimed to evaluate salivary metabolomic changes across the progression from healthy mucosa to oral leukoplakia (OL) and oral squamous cell carcinoma (OSCC), identifying potential biomarkers for early diagnosis and clinical monitoring. METHODS Fifty-two subjects were enrolled in three centers, two based in Modena (Dermatology and Dentistry Units, University Hospital - Italy) and one in Parma (University Dentistry Center - Italy): 13 with non-dysplastic OL, 13 with dysplastic OL, 13 with OSCC, and 13 healthy controls (HC). According to the Declaration of Helsinki, written consent was obtained from all the volunteers who participated in this study. Demographic, anamnestic, clinical data, and risk factors were recorded for each patient. Tissues (OSCC and HCs) and saliva samples (the four groups) were collected prior to surgery and analyzed by High Resolution Magic-Angle Spinning (HR-MAS) and Hydrogen Nuclear Magnetic Resonance spectroscopies, respectively. Multivariate and univariate analyses were performed using MetaboAnalyst 6.0. RESULTS In tissues, 32 metabolites were deconvoluted. ROC curves identified four relevant metabolites with AUCs ≥ 0.80 for HCs vs. OSCC comparison: glycerol, choline, fumarate, and glutamate. In saliva, total of 72 salivary metabolites were identified. PLS-DA showed a progressive shift in salivary metabolic profiles was observed by groups, with a clear separation of the groups. Some of the metabolites, such as pyroglutamate, desaminotyrosine, succinate, and glycerol, showed progressively varying average concentrations across the groups (from HC to OSCC). On the other hand, N-acetyl-glucosamine, and indole-3 acetate were detected only in HCs and 4-OH-phenyllactate was in all the groups except in OSCC. CONCLUSIONS Overall, valuable tissue biomarkers of OSCC emerged from ROC analysis of tissue samples. Salivary metabolomic profiling may support risk stratification and a potential early detection of OSCC. Furthermore, exclusive metabolites appear as potential OSCC biomarkers. Larger studies are needed to validate these biomarkers and their clinical application.
Salivary Metabolic Profile From Healthy Mucosa To Squamous Cell Carcinoma / Antonelli, R., Setti, G., Pertinhez, T.a., Ferrari, E., Gallo, M., Mucci, A., Righi, V., Gambini, A., Magnoni, C., Vescovi, P., Meleti, M.. - (2026). (33° Congresso Nazionale del Collegio dei Docenti Universitari di discipline Odontostomatologiche Ancona 11-13 giugno 2026).
Salivary Metabolic Profile From Healthy Mucosa To Squamous Cell Carcinoma
Antonelli R;Pertinhez TA;Ferrari E;Gallo M;Gambini A;Vescovi P;Meleti M
2026-01-01
Abstract
AIM The present multicenter pilot study aimed to evaluate salivary metabolomic changes across the progression from healthy mucosa to oral leukoplakia (OL) and oral squamous cell carcinoma (OSCC), identifying potential biomarkers for early diagnosis and clinical monitoring. METHODS Fifty-two subjects were enrolled in three centers, two based in Modena (Dermatology and Dentistry Units, University Hospital - Italy) and one in Parma (University Dentistry Center - Italy): 13 with non-dysplastic OL, 13 with dysplastic OL, 13 with OSCC, and 13 healthy controls (HC). According to the Declaration of Helsinki, written consent was obtained from all the volunteers who participated in this study. Demographic, anamnestic, clinical data, and risk factors were recorded for each patient. Tissues (OSCC and HCs) and saliva samples (the four groups) were collected prior to surgery and analyzed by High Resolution Magic-Angle Spinning (HR-MAS) and Hydrogen Nuclear Magnetic Resonance spectroscopies, respectively. Multivariate and univariate analyses were performed using MetaboAnalyst 6.0. RESULTS In tissues, 32 metabolites were deconvoluted. ROC curves identified four relevant metabolites with AUCs ≥ 0.80 for HCs vs. OSCC comparison: glycerol, choline, fumarate, and glutamate. In saliva, total of 72 salivary metabolites were identified. PLS-DA showed a progressive shift in salivary metabolic profiles was observed by groups, with a clear separation of the groups. Some of the metabolites, such as pyroglutamate, desaminotyrosine, succinate, and glycerol, showed progressively varying average concentrations across the groups (from HC to OSCC). On the other hand, N-acetyl-glucosamine, and indole-3 acetate were detected only in HCs and 4-OH-phenyllactate was in all the groups except in OSCC. CONCLUSIONS Overall, valuable tissue biomarkers of OSCC emerged from ROC analysis of tissue samples. Salivary metabolomic profiling may support risk stratification and a potential early detection of OSCC. Furthermore, exclusive metabolites appear as potential OSCC biomarkers. Larger studies are needed to validate these biomarkers and their clinical application.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
