Dergi makalesi Açık Erişim

Optimization and validation of a HILIC-LC-ESI-MS/MS method for the simultaneous analysis of targeted metabolites: Cross validation of untargeted metabolomic studies for early diagnosis of breast cancer

2020    Recber, Tuba; Nemutlu, Emirhan; Beksac, Kemal; Aksoy, Sercan; Kir, Sedef

The best preventive method for breast cancer, which accounts for 18% of the most common cancer-related deaths among women, is early diagnosis. Metabolomic analysis plays an important role in both early diagnosis and tracking of the disease progress. In this study, targeted metabolomic analyses were performed on twenty-six selected metabolites, which were proposed in the literature for use in the early diagnosis of breast cancer, by examining the plasma samples of 105 healthy volunteers, 172 early stage and 92 metastatic breast cancer patients. To this purpose, an LC-ESI-MS/MS method was developed, validated, and applied to the analysis of the above plasma samples. Measurements were performed on a Merck SeQuant ZIC-HILIC column (50 x 4.6 mm, 5 mu m) with the mobile phase run in the gradient mode with 0.1% formic acid in water and 0.1% formic acid in acetonitrile at a flow rate of 0.3 mL min(-1) and 40 degrees C. The correlation coefficient values between 0.991 and 0.999 in the study range where each metabolite is linear shows the linearity of the method. The LOD and LLOQ values of the metabolites were between 5.9 x 10(-5)-1.0 x 10(-2) mu g mL(-1) and 1.8 x 10(-4)-5.3 x 10(-2) mu g mL(-1), respectively. The validation studies revealed that the method was linear, sensitive, precise, accurate, and selective. Our results showed that the metabolite identification based exclusively on the m/z values obtained from untargeted metabolomic studies must conform with standards before their clinical usage. Since only nine (citrulline, malic acid, glyceric acid, 3-hydroxybutyric acid, glutamine, proline, choline, fumaric acid and lactic acid) out of the twenty-six metabolites changed significantly among breast cancer patients. Therefore untargeted metabolomic analyses should be confirmed by targeted analyses before suggesting metabolites as biomarkers to avoid possible mismatches.