Diagnostic approach to breast cancer patients based on target metabolomics in saliva by liquid chromatography with tandem mass spectrometry

Abstract Background Breast cancer is one of the most fearful diseases due to its increasing worldwide prevalence. A number of screening tests has been employed including clinical examinations and mammography. However, another screening method, which is a simple, not embarrassing, and low cost, is highly desired. Based on these findings, we are currently investigating the determination of polyamines including their acetylated structures for the diagnosis of breast cancer patients. We established a diagnostic approach to breast cancer patients based on the ratios of polyamines in saliva by a UPLC-MS/MS analysis. Methods Twelve polyamines including their acetylated form were labeled with DBD-F, separated by a reversed-phase chromatography and detected by a Xevo TQ-S tandem mass spectrometer. Results Eight polyamines (e.g., SPM, CAD, Ac-SPM, N1-Ac-SPD, N8-Ac-SPD) strongly correlated with the cancer patients. A simple 1-order equation was developed for the discrimination of the breast cancer patients and healthy persons (Y = 0.5X SPM  − 3X Ac-SPM  − 0.15X SPD  − 3.5X N8-Ac-SPD  + 0.5X N1-Ac-SPD  + 0.04X CAD ). The concordance rate of the breast cancer patients and the healthy persons by the equation was 88% and 76% on the training set, respectively, whereas those on the validation set was both 88%. The score Y in the equation tended to correlate with the cancer stage of the patients and increased with the more serious conditions. The determination of polyamines in the saliva after the cancer patient operations was also performed to identify the concentration change before and after the surgical treatment. The discriminant analysis using 6 polyamines (i.e., N8-Ac-SPD, N1-Ac-SPD, CAD, DAc-SPD, PUT, and Ac-PUT), which were the most influenced molecules derived from the ROC analysis, was performed using the relative percentage. Both the sensitivity and specificity indicated nearly 80% from the ROC analysis result using the ratio of N8-Ac-SPD/(N1-Ac-SPD + N8-Ac-SPD). Conclusion The discrimination equation appears to be useful for the diagnosis of breast cancer patients. Furthermore, the ratio of N8-Ac-SPD/(N1-Ac-SPD + N8-Ac-SPD) may be adopted as an index of the health status after the surgical treatment.