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Author Spotlight: Unlocking the Mysteries of Oral Potential Malignancies
Published on: August 11, 2023
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Serum Metabolomics for Prognostic Stratification in Resected Advanced-Stage Oral Cavity Cancer
Eric Yi-Liang Shen1,2, Li-Yu Lee3, Shu-Hang Ng4
1Department of Radiation Oncology and Proton Therapy Center, Chang Gung Memorial Hospital, Linkou and Chang Gung University, Taoyuan City, Taiwan, Republic of China.
JAMA Otolaryngology-- Head & Neck Surgery
|December 4, 2025
Summary
A novel MetaboScore effectively predicts recurrence in oral cavity squamous cell carcinoma (OCSCC). This metabolomic approach identifies patients at high risk for relapse, improving prognostic accuracy beyond current staging methods.
Area of Science:
- Oncology
- Metabolomics
- Cancer Prognostics
Background:
- Oral cavity squamous cell carcinoma (OCSCC) recurrence prediction requires improved methods.
- Current metabolomic studies have not fully addressed OCSCC relapse patterns and survival prediction.
Purpose of the Study:
- To identify serum metabolites associated with OCSCC recurrence.
- To develop and validate a prognostic scoring system (MetaboScore) for OCSCC.
Main Methods:
- Retrospective cohort study of advanced-stage OCSCC patients from betel quid-chewing areas.
- Preoperative serum metabolomic profiling using liquid chromatography-mass spectrometry.
- Development and validation of the MetaboScore based on relapse-predictive metabolites.
Main Results:
- A MetaboScore incorporating 19 metabolites was developed.
- A high MetaboScore (≥11) significantly correlated with increased risk of local recurrence, regional recurrence, and distant metastasis.
- Patients with high MetaboScores exhibited significantly worse 5-year disease-free and disease-specific survival.
- The MetaboScore provided independent prognostic value beyond pN3b staging.
Conclusions:
- A high MetaboScore is associated with higher recurrence rates and poorer survival in OCSCC.
- The MetaboScore offers additional prognostic information beyond conventional staging.
- Further validation in diverse populations is necessary for clinical implementation.
