Preliminary studies on changes in the amount of tryptophan metabolites in human glioma tissues.

Background: We have developed and validated methods for the determination of three major tryptophan metabolites metabolized by the kynurenine pathway, namely kynurenine (KYN), 3-hydroxykynurenine (3-HK), and 3-hydroxyanthranilic acid (3-HAA). KYN and 3-HK were determined using RP-HPLC-UV, and 3-HAA using RP-HPLC-FL. We then developed a comparative method based on CE-UV. The developed methods were validated and 36 samples of human brain glioma tissue homogenates were assayed in all 4 grades of malignancy, and the concentration levels of assayed metabolites were compared with available clinical data.

Results: Each of the methods is characterized by high precision, accuracy and repeatability, and the determined LOQ values indicate the possibility of performing quantitative analysis on the available samples of human glioma tumors (36 samples in grades G1-G4). The concentration values of selected metabolites obtained using HPLC methods were subjected to statistical analysis and preliminary clinical data processing. We found statistically significant differences in the concentrations of KYN, 3-HK and 3-HAA between the various grades of the disease, and characterized these differences more precisely by means of the Dunn-Bonferroni post hoc test. We did not find that the patient's environment or habits significantly affected the metabolites concentration of the study samples population. In addition, we showed a high positive correlation between KYN, 3-HK and 3-HAA, which appears to be a characteristic that describes metabolic changes of Trp in relation to KYN, 3-HK and 3-HAA, and indicates potential diagnostic value.

Significance: The preliminary studies carried out contribute new knowledge on the molecular basis of human brain glioma. They also provide valuable information useful for the development of glioma diagnostics, differentiation of disease grades and assessment of the patient's condition. The obtained relationships between metabolite concentrations and the grade of malignancy of the disease and correlations between metabolite concentrations constitute the basis for further broader biochemical and clinical analysis.