The 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 by1H-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.
|Número de páginas||6|
|Estado||Publicada - nov. 2018|
|Publicado de forma externa||Sí|
Nota bibliográficaFunding Information:
The present study was supported by the Finnish Funding Agency for Technology and Innovation (Tekes) project ‘Novel spectroscopic methods for early detection and screening of oral cancer’ (grant no. 52/31/2014).
The authors acknowledge the contribution of NMR Metabolomics Laboratory at the University of Eastern Finland (Kuopio, Finland).The present study was supported by the Finnish Funding Agency for Technology and Innovation (Tekes) project ‘Novel spectroscopic methods for early detection and screening of oral cancer’ (grant no. 52/31/2014).
© 2018, Spandidos Publications. All rights reserved.