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SAL_16468 details
Primary information
SALIDSAL_16468
Biomarker nameProline
Biomarker TypeNA
Sampling MethodA total of 45 consecutive patients with HNSCC were recruited to the longitudinal case control clinical study.
Collection MethodEach subject was asked to let the naturally produced saliva drain into a sterile glass cup for a period of 5 min.
Analysis MethodH-NMR
Collection SiteSupernatant Saliva
Disease CategoryCancer
Disease/ConditionHead and Neck Cancer
Disease SubtypeHead and Neck Squamous Cell Carcinoma (HNSCC)
Fold Change/ ConcentrationNA
Up/DownregulatedDecrease
ExosomalNA
OrganismHomo sapiens
PMID30344764
Year of Publication2018
Biomarker ID145742
Biomarker CategoryMetabolite
SequenceC1C[C@H](NC1)C(=O)O
Title of studyPotential role of nuclear magnetic resonance spectroscopy to identify salivary metabolite alterations in patients with head and neck cancer
Abstract of studyThe analysis of the salivary metabolomic profile may offer an early phase approach to assess the changes associated with a wide range of diseases including head and neck cancer. The aim of the present study was to investigate the potential of nuclear magnetic resonance (NMR) spectroscopy for detecting the salivary metabolic changes associated with head and neck squamous cell carcinoma (HNSCC). Unstimulated whole-mouth saliva samples collected from HNSCC patients (primary tumour was located either in the larynx or in the oral cavity) and healthy controls were analysed by 1H-NMR spectroscopy. Reliably identified salivary metabolites were quantified and the determined concentration values were compared group-wise using a Mann-Whitney U-test. Multivariate discrimination function analysis (DFA) was conducted to identify such a combination of metabolites, when considered together, that gives maximum discrimination between the groups. HNSCC patients exhibited significantly increased concentrations of 1,2-propanediol (P=0.032) and fucose (P=0.003), while proline levels were significantly decreased (P=0.043). In the DFA model, the most powerful discrimination was achieved when fucose, glycine, methanol and proline were considered as combined biomarkers, resulting in a correct classification rate of 92.1%, sensitivity of 87.5% and specificity of 93.3%. To conclude, NMR spectrometric analysis was revealed to be a feasible approach to study the metabolome of saliva that is sensitive to metabolic changes in HNSCC and straightforward to collect in a non-invasive manner. Salivary fucose was of particular interest and therefore, controlled longitudinal studies are required to assess its clinical relevance as a diagnostic biomarker in HNSCC.