| Primary information |
|---|
| SALID | SAL_16390 |
| Biomarker name | N,N-Dimethylglycine |
| Biomarker Type | NA |
| Sampling Method | Patients with oral cancer and healthy controls were recruited at the Department of Dentistry, Oral and Maxillofacial Plastic and Reconstructive Surgery of Yamagata University Hospital from 2012 to 2014. |
| Collection Method | Approximately 400 microliter unstimulated whole saliva was collected over 5-10 min. After collection, the saliva samples were immediately stored at -80 degreeC. |
| Analysis Method | CE-TOFMS |
| Collection Site | Whole Saliva |
| Disease Category | Cancer |
| Disease/Condition | Oral Cancer |
| Disease Subtype | Oral squamous cell carcinoma (OSCC) |
| Fold Change/ Concentration | 3.67 |
| Up/Downregulated | Increase |
| Exosomal | NA |
| Organism | Homo sapiens |
| PMID | 27539254 |
| Year of Publication | 2016 |
| Biomarker ID | 673 |
| Biomarker Category | Metabolite |
| Sequence | CN(C)CC(=O)O |
| Title of study | Identification of salivary metabolomic biomarkers for oral cancer screening |
| Abstract of study | The objective of this study was to explore salivary metabolite biomarkers by profiling both saliva and tumor tissue samples for oral cancer screening. Paired tumor and control tissues were obtained from oral cancer patients and whole unstimulated saliva samples were collected from patients and healthy controls. The comprehensive metabolomic analysis for profiling hydrophilic metabolites was conducted using capillary electrophoresis time-of-flight mass spectrometry. In total, 85 and 45 metabolites showed significant differences between tumor and matched control samples, and between salivary samples from oral cancer and controls, respectively (P < 0.05 correlated by false discovery rate); 17 metabolites showed consistent differences in both saliva and tissue-based comparisons. Of these, a combination of only two biomarkers yielded a high area under receiver operating characteristic curves (0.827; 95% confidence interval, 0.726-0.928, P < 0.0001) for discriminating oral cancers from controls. Various validation tests confirmed its high generalization ability. The demonstrated approach, integrating both saliva and tumor tissue metabolomics, helps eliminate pseudo-molecules that are coincidentally different between oral cancers and controls. These combined salivary metabolites could be the basis of a clinically feasible method of non-invasive oral cancer screening. |