Oral and laryngeal epithelial lesions are currently diagnosed using histological criteria based on the World Health Organization (WHO) classification, which can cause interobserver variability. An integrated diagnostic approach based on immunohistochemistry (IHC) would aid in the interpretation of ambiguous histological findings of epithelial lesions. In the present study, IHC was used to evaluate the expression of p53 and Ki-67 in 114 cases of oral and laryngeal epithelial lesions in 104 patients. Logistic regression analysis and decision tree algorithm were employed to develop a scoring system and predictive model for differentiating the epithelial lesions. Cohen’s kappa coefficient was used to evaluate interobserver variability, and next-generation sequencing (NGS) and IHC were used to compare TP53 mutation and p53 expression patterns. Two expression patterns for p53, namely, diffuse expression type (pattern HI) and null type (pattern LS), and the pattern HI for Ki-67 were significantly associated with high-grade dysplasia (HGD) or squamous cell carcinoma (SqCC). With an accuracy and area under the receiver operating characteristic curve (AUC) of 84.6% and 0.85, respectively, the scoring system based on p53 and Ki-67 expression patterns classified epithelial lesions into two types: non-dysplasia (ND) or low-grade dysplasia (LGD) and SqCC or HGD. The decision tree model constructed using the p53 and Ki-67 expression patterns classified epithelial lesions into ND, LGD, and group 2, including HGD or SqCC, with an accuracy and AUC of 75% and 0.87, respectively. The integrated diagnosis had a better correlation with near perfect agreement (weighted kappa 0.92, unweighted kappa 0.88). The patterns HI and LS for p53 were confirmed to be correlated with missense mutations and nonsense/frameshift mutations, respectively. A predictive model for diagnosis was developed based on the correlation between TP53 mutation and p53 expression patterns. These results indicate that the scoring system based on p53 and Ki-67 expression patterns can differentiate epithelial lesions, especially in cases when the morphological features are ambiguous.
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