Effect of storage conditions on salivary polyamines quantified via liquid chromatography-mass spectrometry.

Salivary polyamines are potential non-invasive tools for screening various types of cancers. For clinical use, the reproducibility of these metabolites should be evaluated under various storage conditions, including duration and temperature, to establish standard operating protocols. Polyamines and amino acids in unstimulated whole saliva were quantified via liquid chromatography-mass spectrometry. Concentrations of time course samples were analysed after short-term storage for up to 240 min and long-term storage for up to 8 days under various storage conditions. As expected, storage at the lowest temperature (-18 °C) exerted the least pronounced effects on the quantified values in both tests. At a higher temperature, polyamines were more stable than amino acids, as evident from polyamine profiling. Addition of ethanol significantly stabilized polyamine profiles even at a higher temperature. Comparative processing of saliva revealed a minor effect of the solvent, whereas drying had a more prominent effect on polyamine profiles. Computational analyses evaluated the ability of polyamines to discriminate pancreatic cancer from controls. Repeated noise added tests were designed on the basis of the results of the storage tests; these analyses confirmed that the discriminative abilities were robust. These data contribute to the standardization of salivary storage conditions, thereby highlighting the clinical utility of saliva.

Urinary Polyamine Biomarker Panels with Machine-Learning Differentiated Colorectal Cancers, Benign Disease, and Healthy Controls.

Colorectal cancer (CRC) is one of the most daunting diseases due to its increasing worldwide prevalence, which requires imperative development of minimally or non-invasive screening tests. Urinary polyamines have been reported as potential markers to detect CRC, and an accurate pattern recognition to differentiate CRC with early stage cases from healthy controls are needed. Here, we utilized liquid chromatography triple quadrupole mass spectrometry to profile seven kinds of polyamines, such as spermine and spermidine with their acetylated forms. Urinary samples from 201 CRCs and 31 non-CRCs revealed the N1,N12-diacetylspermine showing the highest area under the receiver operating characteristic curve (AUC), 0.794 (the 95% confidence interval (CI): 0.704-0.885, p < 0.0001), to differentiate CRC from the benign and healthy controls. Overall, 59 samples were analyzed to evaluate the reproducibility of quantified concentrations, acquired by collecting three times on three days each from each healthy control. We confirmed the stability of the observed quantified values. A machine learning method using combinations of polyamines showed a higher AUC value of 0.961 (95% CI: 0.937-0.984, p < 0.0001). Computational validations confirmed the generalization ability of the models. Taken together, polyamines and a machine-learning method showed potential as a screening tool of CRC.

Effect of timing of collection of salivary metabolomic biomarkers on oral cancer detection.

The aim of this study is to evaluate the effect of duration after meals for saliva collections for oral cancer detection using metabolomics. Saliva samples were collected from oral cancer patients (n = 22) and controls (n = 44). Saliva from cancer patients was collected 12 h after dinner, and 1.5 and 3.5 h after breakfast. Control subjects fasted >1.5 h prior to saliva collection. Hydrophilic metabolites were analyzed using capillary electrophoresis mass spectrometry. Levels of 51 metabolites differed significantly in controls vs. oral cancer patients at the 12-h fasting time point (P < 0.05). Fifteen and ten metabolites differed significantly at the 1.5- and 3.5-h time points, respectively. The area of under receiver operating characteristic curve for discriminating oral cancer patients from controls was greatest at the 12-h fasting time point. The collection time after meals affects levels of salivary metabolites for oral cancer screening. The 12-h fasting after dinner time point is optimal. This study contributes to design of saliva collection protocols for metabolomics-based biomarker discovery.

Identification of salivary metabolomic biomarkers for oral cancer screening.

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.