Establishing a genetic mutation panel for predicting malignant transformation of oral leukoplakia: A prospective cohort study.

Authors

Yuhan Zhu, Zirui Wang, Chenxi Li, Linjun Shi, Wei Liu

Published in

Oral oncology. Volume 181. Pages 108110. Aug 10, 2026. Epub Aug 10, 2026.

Abstract

To investigate somatic mutations in the whole genes of tissue samples from patients with oral leukoplakia (OLK), as the most typical precursor of oral cancer; and identify the specific genes as a mutational panel for predicting OLK malignant transformation.
A total of 123 consecutive OLK patients with long-term follow-up (median, 73 months) were prospectively enrolled, and divided into training set (n = 92) and independent test set (n = 31) based on chronological order of enrollment. Genomic DNA was isolated from the fresh-frozen biopsy tissues and somatic mutations in all genes were measured by whole-exome sequencing.
We constructed a 3-gene (TP53, CASP8, and CYP2B6) mutational panel for risk stratification (any mutation vs. no mutation) of OLK malignant transformation. Kaplan-Meier analysis showed that the prognostic power of the 3-gene panel (log-rank P < 0.0001) for risk stratification in malignant progression was better than that of pathological grade in the training and test set, respectively. Multivariate Cox regression analysis revealed that this panel was an independent variable significantly associated with progression in the training (hazard ratio [HR] = 8.05; P < 0.001) and test set (HR = 11.26; P = 0.0421), respectively. The area under the curve (AUC) with 95 % confidence interval was 0.770 (0.648-0.892) and 0.877 (0.705-1.000) in the training and test set, respectively, for predicting malignant transformation in OLK patients.
We established a 3-gene (TP53, CASP8, and CYP2B6) mutational panel as risk stratification model could effectively predict OLK malignant transformation, outperforming pathological grading-based assessment. Such genetic markers may provide a foundation for developing personalized management strategies.

PMID:
42574788
Bibliographic data and abstract were imported from PubMed on 11 Aug 2026.

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