Evidence map›Paper›PMID 40418396›Full record

ArticleDiscover oncology2025

Identification of metabolic biomarkers and therapeutic targets in the thymoma-associated myasthenia gravis treated with methylprednisolone.

Shanshan Gu, Xu Wang, Hongxia Yang, Yaxuan Wang, Congya Yan, Xiaoting Lin, Peng Liu, Lu Liu, Li Meng, Guoyan Qi

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PubMed Full text at PMC Publisher
In one paragraph

Article in Discover oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Shanshan Gu *Department of Oncology, Hebei Medical University, Shijiazhuang, China.
Xu Wang *Department of Radiation Oncology, The Affiliated Tai'an City Central Hospital of Qingdao University, Taian, China.
Hongxia YangCenter of Treatment of Myasthenia Gravis, People's Hospital of Shijiazhuang Affiliated to Hebei Medical University, Shijiazhuang, China.
Yaxuan WangCenter of Treatment of Myasthenia Gravis, People's Hospital of Shijiazhuang Affiliated to Hebei Medical University, Shijiazhuang, China.
Congya YanCenter of Treatment of Myasthenia Gravis, People's Hospital of Shijiazhuang Affiliated to Hebei Medical University, Shijiazhuang, China.
Xiaoting LinCenter of Treatment of Myasthenia Gravis, People's Hospital of Shijiazhuang Affiliated to Hebei Medical University, Shijiazhuang, China.
Peng LiuCenter of Treatment of Myasthenia Gravis, People's Hospital of Shijiazhuang Affiliated to Hebei Medical University, Shijiazhuang, China.
Lu LiuThe Second Affiliated Hospital of Shandong First Medical University, Taian, China.
Li Meng *Department of Radiation Oncology, The Affiliated Tai'an City Central Hospital of Qingdao University, Taian, China. mengli1004@163.com.
Guoyan Qi *Department of Oncology, Hebei Medical University, Shijiazhuang, China. zzjwlsys@163.com.

Funding

Central guidance for local scientific and technological development funding projects No. 246Z7706GKey Laboratory Construction Subsidy Fund Project. No. 236790017HNational Natural Science Foundation of China No. 82274582Science and technology public relations project of Shandong Geriatric Society（2024） LKJGG2024W076Tai'an City Science and Technology Innovation Development Project (No.2021NS308)
6 · The paper itself

Abstract

objectiveThis 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.

methodsSerum 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).

resultsA 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).

conclusionOur 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.

Indexed as

LC–MSMetabolomicsMyasthenia gravisNetwork pharmacologyThymoma

Identifiers

PMID40418396
PMCPMC12106182

What Socratic holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.