Wang Shu, Li Tiancheng, Liu Huan, Wei Wei, Yang Yang, Wang Chong, Li Bo, Han Zhengxue, Feng Zhien
Department of Oral and Maxillofacial-Head and Neck Oncology, Beijing Stomatological Hospital, Capital Medical University, Beijing, China.
Department of Stomatology, The Affiliated Hospital of Inner Mongolia Medical University, Hohhot, China.
Front Oncol. 2021 Apr 22;11:660615. doi: 10.3389/fonc.2021.660615. eCollection 2021.
Lymph node metastasis is the most important factor influencing the prognosis of oral squamous cell carcinoma (OSCC) patients. However, there is no proper method for predicting lymph node metastasis. This study aimed to construct and validate a preoperative prediction model for lymph node metastasis and guide personalized neck management based on the gene expression profile and clinicopathological parameters of OSCC.
Based on a previous study of related genes in OSCC, the mRNA expression of candidate genes was evaluated by real-time PCR in OSCC specimens. In this retrospective study, the gene expression profile and clinicopathological parameters of 112 OSCC patients were combined to construct the best prediction model for lymph node metastasis of OSCC. The model was validated with 95 OSCC samples in this study. Logistic regression analysis was used. The area under the curve (AUC) ultimately determined the diagnostic value of the prediction model.
The two genes CDKN2A + PLAU were closely related to lymph node metastasis of oral squamous cell carcinoma. The model with the combination of CDKN2A, PLAU, T stage and pathological grade was the best in predicting lymph node metastasis (AUC = 0.807, 95% CI: 0.713-0.881, P=0.0001). The prediction model had a specificity of 96% and sensitivity of 72.73% for stage T1 and T2 OSCC (AUC = 0.855, 95% CI: 0.697-0.949, P=0.0001).
High expression of CDKN2A and PLAU was associated with lymph node metastasis in OSCC. The prediction model including CDKN2A, PLAU, T stage and pathological grade can be used as the best diagnostic model for lymph node metastasis in OSCC.
淋巴结转移是影响口腔鳞状细胞癌（OSCC）患者预后的最重要因素。然而，目前尚无预测淋巴结转移的合适方法。本研究旨在基于OSCC的基因表达谱和临床病理参数构建并验证淋巴结转移的术前预测模型，以指导个性化的颈部管理。
基于先前对OSCC相关基因的研究，通过实时PCR评估OSCC标本中候选基因的mRNA表达。在这项回顾性研究中，结合112例OSCC患者的基因表达谱和临床病理参数，构建OSCC淋巴结转移的最佳预测模型。本研究中用95例OSCC样本对该模型进行验证。采用逻辑回归分析。曲线下面积（AUC）最终确定预测模型的诊断价值。
CDKN2A + PLAU这两个基因与口腔鳞状细胞癌的淋巴结转移密切相关。结合CDKN2A、PLAU、T分期和病理分级的模型在预测淋巴结转移方面表现最佳（AUC = 0.807，95%CI：0.713 - 0.881，P = 0.0001）。对于T1和T2期OSCC，该预测模型的特异性为96%，敏感性为72.73%（AUC = 0.855，95%CI：0.697 - 0.949，P = 0.0001）。
CDKN2A和PLAU的高表达与OSCC的淋巴结转移相关。包括CDKN2A、PLAU、T分期和病理分级的预测模型可作为OSCC淋巴结转移的最佳诊断模型。
