Serum Metabolomics for Tumor-Induced Osteomalacia with 96 Patient and Control Samples

96 serum samples from 32 initial diagnosis tumor-induced osteomalacia (TIO) patients, paired post-resection samples, and 32 matched healthy controls were analyzed via liquid chromatography-tandem mass spectrometry (LC-MS). The work by Yiyi Gong identified a diagnostic panel of 5 oxylipins with high predictive accuracy (AUC=0.951). This dataset provides a global metabolomic profile and potential diagnostic biomarkers for TIO.

Use Cases

• Train diagnostic classifiers based on the identified panel of 5 oxylipins (4-HDoHE, leukotriene B4, 5-HETE, 17-HETE, 9,10,13-TriHOME).
• Validate predictive models for tumor-induced osteomalacia using the described random forest, SVM, and PLS algorithms.
• Investigate pathway enrichment in arachidonic acid metabolism using the differential metabolite profiles.
• Study metabolic alterations between patient and healthy control cohorts described in the metabolomic profiling.

Strengths

• Includes 96 serum samples with a matched case-control design (32 TIO patients, 32 controls).
• Identifies a specific diagnostic panel of 5 oxylipins with reported high predictive accuracy (AUC=0.951).
• Analysis performed using liquid chromatography-tandem mass spectrometry (LC-MS), a standard metabolomics technique.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• Last update date is unknown; freshness unverified.

Provenance

Source

Yiyi Gong

Collection Method

Liquid chromatography-tandem mass spectrometry (LC-MS) based metabolomics analysis of serum samples.