Biogenic Amines Profile Characterization in Glioblastoma Patients Undergoing Standard of Care Treatment

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Abstract
Introduction: This study aims to characterize changes in biogenic amines patterns in glioblasto-ma patients undergoing surgery and concurrent chemoradiation to illustrate how this class of metabolites changes during different stages of standard care treatment protocol. Methods: We examined 138 plasma specimens (before surgery, 2 days after surgical resection, before starting concurrent chemoradiation, immediately after chemoradiation, and after adju-vant chemotherapy treatment) from 36 patients with isocitrate dehydrogenase (IDH) wildtype glioblastoma. Untargeted GC-TOF mass spectrometry-based metabolomics of biogenic amines was used given its superiority for identifying and quantitating small metabolites; this yielded 340 structurally identified metabolites. Results: Comparing post-surgery to pre-surgery showed increased level of 12 metabolites: Gly-codeoxycholic acid (P=7.79E-05), Betonicine (P=9.23E-05), Glycocholic acid (P=3.18E-03), 3-Cysteinylaectaminophen (P=4.95E-03), S-Methyl-3-thioacetaminophen (P=5.77E-03), Tau-rocholic acid (P=9.97E-03), N-glycine (P=0.0013), p-acetamidophenyl.beta.-D-glucuronide (P=0.0048), 2-Hydroxy-5-sulfopyridine-3-carboxylic acid (P=0.0074), Acetaminophen sulfate (P=0.0095), 2-Amino-3-methoxybenzoic acid (P=0.02), and Dehydrofelodipine (P=0.024). There were 11 compounds that were downregulated, which included Mannitol (P=1.96E-19), Sorbitol (P=2.75E-019), Linoleic acid (P=1.51E-10), 1-Methylnicotinamide (P=1.78E-09), Nudifloramide (P=2.81E-08), Hexadecanedioic acid (P=5.49E-05), 3-Hydroxybutyric acid (P=0.0002), Riluzole (0.0036), Bupivacaine (P=0.0041), Lactitol (P=0.008), and 1-hydroxymidazolam.beta.-D-glucuronide (P=0.0414). After chemoradiation, significant de-crease was uncovered in Famotidine (P=0.0074), N-Isovalerylglycine (P=0.012), and 3-Methylcrotonylglycine (P=0.0131). While significant increase was detected in N-Methylisoleucine (P=0.0011), 4-Methyl-5-thiazoleethanol (P=0.042), and 6-Hydroxycaproic acid (P=0.049). Ensemble learning models, specifically random forest (RF) and AdaBoost (AB), accurately classified treatment phases with high accuracy (RF: 0.81 ± 0.04, AB: 0.78 ± 0.05). One significant insight gleamed from these models were that the metabolites Sorbitol and N-methylisoleucine were identified as important predictive features and confirmed by SHAP analysis. Conclusion: To our knowledge, this is the first study to describe plasma biogenic amines signa-tures during different treatment phases in patients with glioblastoma. A larger study is needed to confirm the results and the potential application of this algorithm for classification of treatment responses.

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