Oral Cancer Research Institute, Yonsei University College of Dentistry, Seoul, South Korea; Department of Pathology, Yanbian University Hospital, Yanji City, Jilin Province, China.
Brain Korea 21 Project, Yonsei University College of Dentistry, Seoul, South Korea.
Oral Oncol. 2017 Sep;72:132-139. doi: 10.1016/j.oraloncology.2017.07.015. Epub 2017 Jul 20.
Squamous cell carcinomas (SCC) are the most common malignancies in the oral mucosa; these carcinomas have been preceded by potentially malignant oral disorders (PMODs), mostly oral leukoplakia (OL). No specific biomarker has been widely accepted for predicting the risk of malignant transformation of PMODs. The aim of this study was to develop an accurate prediction model for the malignant transformation of OL using clinical variables and candidate biomarkers.
To achieve this goal, 10 candidate biomarkers that had previously been reported as useful molecules were investigated: P53, Ki-67, P16, β-catenin, c-jun, c-met, insulin like growth factor II mRNA-binding protein (IMP-3), cyclooxygenase (COX-2), podoplanin (PDPN) and carbonic anhydrase 9 (CA9). For this study, malignant transformed (n=22, median interval of malignant conversion: 3.3years) and untransformed (n=138) OL specimens with median follow-up period of 11.3years (range: 4.6-23.2years) were immunohistochemically stained.
Using univariate Cox regression analysis, all biomarkers were proven to be significant for predicting malignant transformation in OL. To reach the highest prediction accuracy, the repeated simulation was performed, revealing that the combination of P53 and CA9 with the clinical factors including age and degree of dysplasia achieved the highest prediction accuracy. We constructed a nomogram with the identified prognostic factors for predicting the 5-, 10-, and 15-year progression free survival of OL.
The proposed nomogram may be useful for the accurate and individual prediction of the transformation to SCC in OL patients and may help clinicians offer appropriate treatments and follow up.
鳞状细胞癌（SCC）是口腔黏膜最常见的恶性肿瘤；这些癌前病变是潜在的恶性口腔疾病（PMOD），主要是口腔白斑（OL）。目前还没有广泛接受的特定生物标志物来预测 PMOD 恶性转化的风险。本研究旨在使用临床变量和候选生物标志物开发一种准确预测 OL 恶性转化的模型。
为了实现这一目标，研究人员研究了之前报道为有用分子的 10 种候选生物标志物：P53、Ki-67、P16、β-连环蛋白、c-jun、c-met、胰岛素样生长因子 II mRNA 结合蛋白（IMP-3）、环氧化酶（COX-2）、 podoplanin（PDPN）和碳酸酐酶 9（CA9）。在这项研究中，对恶性转化（n=22，恶性转化中位数间隔：3.3 年）和未转化（n=138）OL 标本进行了免疫组织化学染色，中位随访时间为 11.3 年（范围：4.6-23.2 年）。
使用单变量 Cox 回归分析，所有生物标志物均证明对预测 OL 恶性转化具有重要意义。为了达到最高的预测准确性，进行了重复模拟，结果表明，P53 和 CA9 与包括年龄和异型增生程度在内的临床因素相结合，可达到最高的预测准确性。我们构建了一个列线图，用于预测 OL 患者 5、10 和 15 年无进展生存率的识别预后因素。
所提出的列线图可能有助于准确和个体化预测 OL 患者向 SCC 的转化，并有助于临床医生提供适当的治疗和随访。
