Discover oncology · 2025
Identification of metabolic biomarkers and therapeutic targets in the thymoma-associated myasthenia gravis treated with methylprednisolone.
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Gu Shanshan, Wang Xu, Yang Hongxia, Wang Yaxuan, Yan Congya, Lin Xiaoting, Liu Peng, Liu Lu, Meng Li, Qi Guoyan
Аннотация
OBJECTIVE: This study aims to screen and identify metabolic biomarkers and targets for methylprednisolone treatment of thymoma with myasthenia gravis (MG) through metabolomics and network pharmacology analysis, thereby improving guidance for clinical medication and treatment.
METHODS: Serum from 15 patients with thymoma accompanied by severe MG was collected. Changes in serum metabolite levels before and after methylprednisolone treatment were determined using liquid chromatography-mass spectrometry (LC-MS). The raw mass spectrometry fragment information obtained was integrated and interpreted using the metabolomics data analysis software Progenesis QI v2.3. Differential metabolites were screened and identified using univariate and multivariate statistical analysis methods. Subsequently, potential targets of methylprednisolone treatment were identified through network pharmacology, and the mechanism of action of methylprednisolone in treating thymoma with MG was explored in conjunction with metabolomics. Finally, key targets and the upstream synthetic enzymes of critical metabolites identified were validated using Enzyme-Linked Immunosorbent Assay (ELISA).
RESULTS: A total of 148 differential metabolites were identified in the metabolomics study, among which key metabolites ceramide (Cer) and sphingomyelin (SM) play a significant role in cell immune regulation, inflammatory response, and tumor control. Network pharmacology analysis revealed that tumor necrosis factor (TNF) could serve as a potential target for methylprednisolone treatment of thymoma with MG. ELISA validation results showed that the key target TNF and the upstream synthetic enzymes of the key metabolites SM and Cer were all downregulated after methylprednisolone treatment, with the differences being statistically significant (P < 0.05).
CONCLUSION: Our Study reveals that TNF could serve as a potential target for methylprednisolone treatment of Thymoma-associated MG, and Cer and SM could act as potential metabolic biomarkers to assess its treatment efficacy.
METHODS: Serum from 15 patients with thymoma accompanied by severe MG was collected. Changes in serum metabolite levels before and after methylprednisolone treatment were determined using liquid chromatography-mass spectrometry (LC-MS). The raw mass spectrometry fragment information obtained was integrated and interpreted using the metabolomics data analysis software Progenesis QI v2.3. Differential metabolites were screened and identified using univariate and multivariate statistical analysis methods. Subsequently, potential targets of methylprednisolone treatment were identified through network pharmacology, and the mechanism of action of methylprednisolone in treating thymoma with MG was explored in conjunction with metabolomics. Finally, key targets and the upstream synthetic enzymes of critical metabolites identified were validated using Enzyme-Linked Immunosorbent Assay (ELISA).
RESULTS: A total of 148 differential metabolites were identified in the metabolomics study, among which key metabolites ceramide (Cer) and sphingomyelin (SM) play a significant role in cell immune regulation, inflammatory response, and tumor control. Network pharmacology analysis revealed that tumor necrosis factor (TNF) could serve as a potential target for methylprednisolone treatment of thymoma with MG. ELISA validation results showed that the key target TNF and the upstream synthetic enzymes of the key metabolites SM and Cer were all downregulated after methylprednisolone treatment, with the differences being statistically significant (P < 0.05).
CONCLUSION: Our Study reveals that TNF could serve as a potential target for methylprednisolone treatment of Thymoma-associated MG, and Cer and SM could act as potential metabolic biomarkers to assess its treatment efficacy.