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Data · dataset · 2026

Integrated Multi-Omics Profiling of Thymoma Identifies Subtype-Specific Remodeling and Myasthenia Gravis-Associated Targets

Listed in ZivaHub and Deakin Research Online and DMU Figshare — shown once because both records carry DOI 10.1021/acs.jproteome.6c00430.s001

Thymoma is a rare thymic epithelial tumor strongly associated with myasthenia gravis (MG), yet the tumor intrinsic molecular states underlying this link remain unclear.

Description

Here, we profiled paired thymoma and distant nontumorous thymic tissues using untargeted metabolomics, lipidomics, and label-free quantitative proteomics, integrating these layers with MG status, clinicopathologic data, immunohistochemistry, and external transcriptomic validation from The Cancer Genome Atlas (TCGA) cohort.

Thymomas exhibited a reproducible metabolic and lipidomic signature characterized by coordinated alterations in amino acid and nucleotide metabolism alongside structured changes in lipid subclasses that support membrane remodeling. Proteomic profiling distinguished tumors from distant nontumorous thymic tissue and identified three exploratory proteomic groups with distinct pathway patterns tightly coupled to lipid metabolic shifts.

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Integrated analyses identified HMGCS1 and SCP2 as subtype-enriched, lipid-linked hubs and uncovered an MG-associated molecular module comprising creatine, MePC(37:4), ACP5, AP1S1, NECTIN4, and fatty acid pathways. AP1S1 showed an independent association with the overall survival in the TCGA thymoma cohort. A derived 13-lipid panel showed high discrimination in an internal evaluation, supporting its potential as a candidate signature for further validation.

This tissue-based multi-omics study systematically maps coordinated molecular remodeling in thymoma, highlighting HMGCS1, SCP2, and AP1S1 as prioritized candidates for future mechanistic and translational research.

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Catalogue records · 1

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Inferred from text
Mass spectrometry 65%
Provenance · 3 source records, 30 field assertions
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ZivaHuboai:figshare.com:article/3404688013 d agoJSON v1
Deakin Research Onlineoai:figshare.com:article/3404688013 d agoJSON v1
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