Shuai Yanjie, Duan Yuansheng, Zhou Mengqian, Yue Kai, Liu Dandan, Fang Yan, Wang Yuxuan, Wu Yansheng, Zhang Ze, Wang Xudong
Department of Maxillofacial & E.N.T oncology, Tianjin Medical University Cancer Institute & Hospital, Key Laboratory of Cancer Prevention and Therapy, Tianjin Cancer Institute, National Clinical Research Center of Cancer, Tianjin, China.
J Cancer. 2021 Jun 22;12(17):5153-5163. doi: 10.7150/jca.54475. eCollection 2021.
We aimed to develop a prognostic nomogram based on immunohistochemistry (IHC) biomarkers of patients with oral squamous cell carcinoma (OSCC). A total of 294 patients were enrolled in the study. The least absolute shrinkage and selection operator (LASSO) Cox regression model was performed to develop a combined IHC score (IHCs) classifier. Five biomarkers, specifically c-Met, Vimentin, HIF-2α, VEGF-c, and Bcl-2 were extracted. Then, an IHCs classifier was developed, and patients were stratified into high- and low-IHCs groups. In the training cohort, the 5-year overall survival (OS) was 62.1% in low-IHCs group and 28.2% in high-IHCs group (<0.001). The 5-year OS was 68.6% for the low-IHCs group and 28.4% for the high-IHCs group in the validation cohort (<0.001). The area under the ROC curve (AUROC) of the combination of the IHCs classifier and TNM stage was 0.746 (95% CI: 0.658-0.833) in the training cohort and 0.735 (95% CI: 0.651-0.818) in the validation cohort, respectively. The nomogram could effectively predict the prognosis for patients with OSCC and may be employed as a potential tool to guide the individual decision-making process.
我们旨在基于口腔鳞状细胞癌(OSCC)患者的免疫组化(IHC)生物标志物开发一种预后列线图。本研究共纳入294例患者。采用最小绝对收缩和选择算子(LASSO)Cox回归模型来开发一种联合免疫组化评分(IHCs)分类器。提取了五个生物标志物,分别为c-Met、波形蛋白、低氧诱导因子-2α(HIF-2α)、血管内皮生长因子-C(VEGF-c)和Bcl-2。然后,开发了一种IHCs分类器,并将患者分为高IHCs组和低IHCs组。在训练队列中,低IHCs组的5年总生存率(OS)为62.1%,高IHCs组为28.2%(<0.001)。在验证队列中,低IHCs组的5年OS为68.6%,高IHCs组为28.4%(<0.001)。在训练队列中,IHCs分类器与TNM分期联合的ROC曲线下面积(AUROC)为0.746(95%CI:0.658 - 0.833),在验证队列中为0.735(95%CI:0.651 - 0.818)。该列线图可以有效地预测OSCC患者的预后,并可作为指导个体决策过程的潜在工具。