Predicting the Malignant Transformation of Oral Submucous Fibrosis Using Quantitative Biomarkers p63 and CD31
Radhika Manoj Bavle, Konda Paremala, Makarala Sowmya and 3 more
Journal of Orofacial Sciences · 2020
doi:10.4103/jofs.jofs_6_20 (opens in a new tab)
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Abstract
Introduction: Oral submucous fibrosis (OSMF) is a pre-malignant condition highly prevalent in India with a malignant transformation rate of 2–8%. Its incidence amongst younger population has risen due to increased consumption of commercial preparations of areca. p63, a homolog of p53, has a role in epithelial proliferation and is frequently altered in dysplasia and associated with tumorigenesis. CD31 is a highly specific endothelial marker with varied expression in epithelial dysplasia and carcinoma. Epithelial proliferation and underlying angiogenic support are vital processes for malignant transformation. Therefore the present study aims to determine if p63 and CD31 expression is associated with increased malignant transformation of OSMF. Materials and Methods: A cross-sectional study wherein n = 36 OSMF samples were histologically graded into Group I (Early-Ea), II (Moderately advanced-MA) and III (Advanced-Ad) and analysed for anti-p63 and anti-CD31 antibodies. The expression was evaluated quantitatively and by pattern of distribution across the groups and statistically analysed with Chi-Square and Kruskal-Wallis tests (SPSS v2.0). Results: p63 expression of epithelium in Group I ∼100% (basal, suprabasal), II − 60.9% (basal, spinous), III − 62.5% (basal, spinous, granular) with a significant P-value < 0.001FNx01. Predominant pattern of CD31 positive vessels in Group I ∼60% (constricted), II > 50% (normal diameter) and III ∼ 75% (dilated) with a significant P-value of 0.02FNx01. Conclusion: A significant linear increase in nuclear staining of p63 and involvement of epithelial strata observed from Ea → MA → Ad grade of OSMF. CD31 expression exhibited more dilated vessels as OSMF grade increased from Ea → Ad. Therefore p63 and CD31 could be used as quantitative predictive biomarkers of malignant transformation of OSMF.
Abstract licence: CC BY-NC-SA
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