Quantitative Analysis of Amino Acid Biomarkers for Medulloblastoma Based on Quadrupole-Linear Ion Trap Isotope Dilution Mass Spectrometry

A method of liquid chromatography-tandem mass spectrometry (LC-MS/MS) was developed based on the self-developed QLIT-6610MD quadrupole-linear ion trap liquid chromatography-mass spectrometry for the accurate quantification of amino acid biomarkers including leucine, phenylalanine, tyrosine, and cystine in plasma for medulloblastoma research. Plasma samples were processed by proteins precipitation with isopropanol, and the supernatant was quantified using a QLIT-6610MD quadrupole-linear ion trap tandem mass spectrometer after amino acid derivatization with 6-aminoquinolinyl-N-hydroxysuccinimidylformate (AQC). Leucine, phenylalanine and tyrosine were quantified by an isotope internal standard method, and the linearity is good in the range of 1-400 μmol/L with the determination coefficients (R²) of 0.9964, 0.9935, 0.9995, respectively, and the limit of quantification (LOQ) is 1 μmol/L. The precision of the quality control samples is less than 15%, and the accuracies are within the range of ±14%. Cystine was quantified by an external standard method, the LOQ is 1 μmol/L, and R² of the target is not less than 0.9979 in the range of 1-400 μmol/L, and the precision of the quality control samples ranges from 1.2% to 11.6%, the accuracy is within the range of −7.4% to 10.8%. Two liquid chromatography-mass spectrometry instruments, QLIT-6610MD and AB QTRAP 6500+, were used to analyze 60 clinical plasma samples, in which the concentrations of leucine, phenylalanine, tyrosine, cystineis are in the range of 17.16-127.06, 13.21-57.89, 11.14-60.97, 4.70-22.97 μmol/L, respectively. Data correlation was analyzed using the Pearson coefficient, and the correlation coefficient (R) between QLIT-6610MD and AB QTRAP 6500+ is ≥0.996, indicating a significant positive correlation (P<0.01). Data consistency was analyzed using Bland-Altman, and the percentage of data out-of-bounds points is ≤10%, indicating that the data consistency is good and meets the actual clinical monitoring needs.