Untargeted metabolomics predicts delayed elimination of methotrexate in pediatric patients with intracranial tumors

doi:10.5246/jcps.2026.04.022

Abstract

Abstract:

This study aimed to identify biomarkers associated with intracranial tumors in children undergoing high-dose methotrexate (HDMTX) chemotherapy, using untargeted metabolomics to enable early detection of delayed drug elimination. Leveraging ultra-performance liquid chromatography coupled with quadrupole time-of-flight tandem mass spectrometry (UPLC-QTOF-MS/MS), serum samples from children with medulloblastoma were analyzed prior to drug administration. We developed an orthogonal partial least squares discriminant analysis (OPLS-DA)–based pattern recognition approach to characterize differences in metabolic profiles between children exhibiting normal MTX elimination and those with delayed elimination. A total of 48 distinct serum metabolites were identified. Metabolic pathway analysis revealed significant perturbations in sphingolipid and glycerophospholipid metabolism between the two groups. Among these, 10 differential metabolites demonstrated an AUC > 0.8 and were thus selected as candidate biomarkers for further validation. The biomarkers identified in this study effectively distinguished between normal and delayed MTX elimination, providing a potential early-warning tool for delayed drug clearance.

Key words: Untargeted metabolomics, Intracranial tumor in children, High-dose methotrexate, Delayed elimination, Biomarker

Supporting:

Zhengyuan Shi, Chunjing Yang, Xiqiao Xu, Jingfeng Li, Li Bao. Untargeted metabolomics predicts delayed elimination of methotrexate in pediatric patients with intracranial tumors[J]. Journal of Chinese Pharmaceutical Sciences, 2026, 35(4): 329-339.

Figures/Tables 8

Table 1. Clinical characteristics of the patient cohort.

Table 2. Identification of metabolites between the normal elimination group and the delayed elimination group.

References 19

[1]	Liu, X.H.; Ding, C.Y.; Tan, W.F.; Zhang, A. Medulloblastoma: Molecular understanding, treatment evolution, and new developments. Pharmacol. Ther. 2020, 210, 107516.
[2]	Plard, C.; Bressolle, F.; Fakhoury, M.; Zhang, D.L.; Yacouben, K.; Rieutord, A.; Jacqz-Aigrain, E. A limited sampling strategy to estimate individual pharmacokinetic parameters of methotrexate in children with acute lymphoblastic leukemia. Cancer Chemother. Pharmacol. 2007, 60, 621.
[3]	Bauters, T.; Lammens, T.; Belin, P.; Benoit, Y.; Robays, H.; de Moerloose, B. Delayed elimination of methotrexate by cola beverages in a pediatric acute lymphoblastic leukemia population. Leuk. Lymphoma. 2013, 54, 1094–1096.
[4]	Yu, C.P.; Hsieh, Y.C.; Shia, C.S.; Hsu, P.W.; Chen, J.Y.; Hou, Y.C.; Hsieh, Y.W. Increased systemic exposure of methotrexate by a polyphenol-rich herb via modulation on efflux transporters multidrug resistance–associated protein 2 and breast cancer resistance protein. J. Pharm. Sci. 2016, 105, 343–349.
[5]	Beechinor, R.J.; Thompson, P.A.; Hwang, M.F.; Vargo, R.C.; Bomgaars, L.R.; Gerhart, J.G.; Dreyer, Z.E.; Gonzalez, D. The population pharmacokinetics of high-dose methotrexate in infants with acute lymphoblastic leukemia highlight the need for bedside individualized dose adjustment: a report from the children’s oncology group. Clin. Pharmacokinet. 2019, 58, 899–910.
[6]	Panetta, J.C.; Roberts, J.K.; Huang, J.; Lin, T.; Daryani, V.M.; Harstead, K.E.; Patel, Y.T.; Onar-Thomas, A.; Campagne, O.; Ward, D.A.; Broniscer, A.; Robinson, G.; Gajjar, A.; Stewart, C.F. Pharmacokinetic basis for dosing high-dose methotrexate in infants and young children with malignant brain tumours. Br. J. Clin. Pharmacol. 2020, 86, 362–371.
[7]	Howard, S.C.; McCormick, J.; Pui, C.H.; Buddington, R.K.; Harvey, R.D. Preventing and managing toxicities of high-dose methotrexate. Oncologist. 2016, 21, 1471–1482.
[8]	Lima, A.; Bernardes, M.; Azevedo, R.; Medeiros, R.; Seabra, V. Pharmacogenomics of methotrexate membrane transport pathway: can clinical response to methotrexate in rheumatoid arthritis be predicted? Int. J. Mol. Sci. 2015, 16, 13760–13780.
[9]	Martinez, D.; Muhrez, K.; Woillard, J.B.; Berthelot, A.; Gyan, E.; Choquet, S.; Andrès, C.R.; Marquet, P.; Barin-Le Guellec, C. Endogenous metabolites-mediated communication between OAT1/OAT3 and OATP1B1 may explain the association between SLCO1B1 SNPs and methotrexate toxicity. Clin. Pharmacol. Ther. 2018, 104, 687–698.
[10]	Phapale, P.B.; Kim, S.D.; Lee, H.W.; Lim, M.; Kale, D.D.; Kim, Y.L.; Cho, J.H.; Hwang, D.; Yoon, Y.R. An integrative approach for identifying a metabolic phenotype predictive of individualized pharmacokinetics of tacrolimus. Clin. Pharmacol. Ther. 2010, 87, 426–436.
[11]	Muhrez, K.; Benz-de Bretagne, I.; Nadal-Desbarats, L.; Blasco, H.; Gyan, E.; Choquet, S.; Montigny, F.; Emond, P.; Barin-Le Guellec, C. Endogenous metabolites that are substrates of organic anion transporter’s (OATs) predict methotrexate clearance. Pharmacol. Res. 2017, 118, 121–132.
[12]	Shi, Z.Y.; Li, J.F.; Yang, C.J.; Xu, X.Q.; Jiang, D.C. Comparative analysis of UPLC-MS/MS and chemiluminescence microparticle immunoassay for serum methotrexate measurement in pediatric intracranial tumor patients. J. Chin. Pharm. Sci. 2025, 34, 423–431.
[13]	Amitai, I.; Rozovski, U.; El-Saleh, R.; Shimony, S.; Shepshelovich, D.; Rozen-Zvi, B.; Raanani, P.; Gafter-Gvili, A.; Gurion, R. Risk factors for high-dose methotrexate associated acute kidney injury in patients with hematological malignancies. Hematol. Oncol. 2020, 38, 584–588.
[14]	Bielack, S.S.; Soussain, C.; Fox, C.P.; Houillier, C.; Murciano, T.; Osborne, W.; Zinzani, P.L.; Rizzari, C.; Schwartz, S. A European consensus recommendation on the management of delayed methotrexate elimination: supportive measures, leucovorin rescue and glucarpidase treatment. J. Cancer Res. Clin. Oncol. 2024, 150, 441.
[15]	Friedman, B.; Cronstein, B. Methotrexate mechanism in treatment of rheumatoid arthritis. Jt. Bone Spine. 2019, 86, 301–307.
[16]	Luengo, A.; Gui, D.Y.; Vander Heiden, M.G. Targeting metabolism for cancer therapy. Cell Chem. Biol. 2017, 24, 1161–1180.
[17]	Cheng, Y.; Chen, M.H.; Zhuang, Q.; Li, H.D.; Chen, H.Y.; Lin, Z.B.; Zhao, F.L.; Xu, H.M.; Huang, M.; Chen, J.S. Metabolomic profiling reveals the mechanisms underlying the nephrotoxicity of methotrexate in children with acute lymphoblastic leukemia. Pediatr. Blood Cancer. 2023, 70, e30578.
[18]	Ke, J.T.; Zhang, H.; Bu, Y.H.; Gan, P.R.; Chen, F.Y.; Dong, X.T.; Wang, Y.; Wu, H. Metabonomic analysis of abnormal sphingolipid metabolism in rheumatoid arthritis synovial fibroblasts in hypoxia microenvironment and intervention of geniposide. Front. Pharmacol. 2022, 13, 969408.
[19]	Zeng, C.W.; Wen, B.; Hou, G.X.; Lei, L.; Mei, Z.L.; Jia, X.K.; Chen, X.M.; Zhu, W.; Li, J.; Kuang, Y.H.; Zeng, W.Q.; Su, J.; Liu, S.Q.; Peng, C.; Chen, X. Lipidomics profiling reveals the role of glycerophospholipid metabolism in psoriasis. GigaScience. 2017, 6, 11.