Department of Oral Pathology, Peking University School and Hospital of Stomatology & National Center of Stomatology & National Clinical Research Center for Oral Diseases & National Engineering Research Center of Oral Biomaterials and Digital Medical Devices, Beijing, China.
Research Unit of Precision Pathologic Diagnosis in Tumors of the Oral and Maxillofacial Regions, Chinese Academy of Medical Sciences (2019RU034), Beijing, China.
J Dent Res. 2024 Feb;103(2):138-146. doi: 10.1177/00220345231217160. Epub 2024 Jan 12.
Oral leukoplakia (OLK) is a common type of potentially malignant disorder. Early identification of the malignancy potential leads to a better management of OLK and prediction of development of oral squamous cell carcinoma (OSCC). However, there has been no effective biomarker to assess the risk of malignancy in OLK. Genomic copy number alteration (CNA) is a complex chromosomal structural variation in the genome and has been identified as a potential biomarker in multiple cancers. This study aimed to develop a predictive model for the malignant transformation risk of OLK by copy number analysis. A total of 431 OLK samples with long-term follow-up (median follow-up of 67 mo) from multiple academic centers were analyzed for CNAs. CNA events increased with the severity of hyperplasia, mild dysplasia, moderate dysplasia, and severe dysplasia. More CNA events were present in patients with OLK who later developed OSCC than in those with OLK who did not. By multivariate Cox regression analysis, the OLK of the CNA score group showed an increased risk of malignant transformation than the CNA score group ( < 0.001). A CNA score model was developed to accurately predict the prognosis (area under the receiver operating characteristic curve [AUC] = 0.879; 95% confidence interval [CI], 0.799-0.959) and was validated using data from 2 external centers (AUC = 0.836, 95% CI, 0.683-0.989; AUC = 0.876, 95% CI, 0.682-1.000), and all of them showed better prediction performances than histopathological grade in assessing the transformation risk of OLK. Furthermore, we performed CNA models among 4 subgroups of OLK with hyperplasia, mild dysplasia, moderate dysplasia, and severe dysplasia and found that CNA score can accurately predict malignant transformation of different subgroups. CNA score may be a useful biomarker to predict malignant transformation of OLK. Subtyping of OLK by the CNA score could contribute to better management of OLK and predicting development of OSCC.
口腔白斑病（OLK）是一种常见的潜在恶性疾病。早期识别恶性潜能可更好地管理 OLP，并预测口腔鳞状细胞癌（OSCC）的发展。然而，目前还没有有效的生物标志物来评估 OLP 的恶性风险。基因组拷贝数改变（CNA）是基因组中复杂的染色体结构变异，已被确定为多种癌症的潜在生物标志物。本研究旨在通过拷贝数分析为 OLP 的恶性转化风险建立预测模型。对来自多个学术中心的 431 例长期随访（中位随访时间为 67 个月）的 OLP 样本进行了拷贝数分析。CNA 事件随着增生、轻度发育不良、中度发育不良和重度发育不良的严重程度而增加。与 OLP 患者后来发展为 OSCC 相比，CNA 事件在 OLP 患者中更为常见。通过多变量 Cox 回归分析，CNA 评分组的 OLP 显示出比 CNA 评分组更高的恶性转化风险（<0.001）。建立了 CNA 评分模型来准确预测预后（接受者操作特征曲线下面积 [AUC] = 0.879；95%置信区间 [CI]，0.799-0.959），并使用来自 2 个外部中心的数据进行了验证（AUC = 0.836，95%CI，0.683-0.989；AUC = 0.876，95%CI，0.682-1.000），所有这些都比组织病理学分级在评估 OLP 的转化风险方面表现出更好的预测性能。此外，我们在具有增生、轻度发育不良、中度发育不良和重度发育不良的 OLP 的 4 个亚组中进行了 CNA 模型分析，发现 CNA 评分可以准确预测不同亚组的恶性转化。CNA 评分可能是预测 OLP 恶性转化的有用生物标志物。通过 CNA 评分对 OLP 进行亚型分类有助于更好地管理 OLP 并预测 OSCC 的发生。
