State Key Laboratory of Oral Diseases, National Clinical Research Center for Oral Diseases, Department of Orthodontics, West China Hospital of Stomatology, Sichuan University, Chengdu, China.
J Cell Biochem. 2019 Dec;120(12):19482-19495. doi: 10.1002/jcb.29252. Epub 2019 Jul 1.
To help provide evidence for prognosis prediction and personalized targeted therapy for patients with head and neck squamous cell carcinoma (HNSCC), we investigated prognosis-specific methylation-driven genes in HNSCC. Survival time data, RNA sequencing data, and methylation data for HNSCC patients were downloaded from The Cancer Genome Atlas. The MethylMix R package based on the β mixture model was utilized to screen genes with different methylation statuses in tumor tissues and adjacent normal tissues, and a total of 182 HNSCC-related methylation-driven genes were then identified. A survival prediction scoring model based on multivariate Cox analysis was developed to screen the genes related to the prognosis of HNSCC, and a linear risk model of the methylation status of six genes (INA, LINC01354, TSPYL4, MAGEB2, EPHX3, and ZNF134) was constructed. The prognostic values of the six genes were further independently explored by survival analysis combined with methylation and gene expression analyses. The 5-year survival rate in the high-risk group of patients in the test set was 30.4% (95% CI: 22.7%-40.8%) and that in the low-risk group of patients was 65.5% (95% CI: 56.1%-76.5%). The area under the receiver operating characteristic curve for the model was 0.723, which further verified the specificity and sensitivity of the model. In addition, subsequent combined survival analysis revealed that all six genes could be used as independent prognostic markers and thus might be potential drug targets. The innovative method provides new insight into the molecular mechanism and prognosis of HNSCC.
为了帮助为头颈部鳞状细胞癌 (HNSCC) 患者的预后预测和个性化靶向治疗提供证据，我们研究了 HNSCC 中与预后相关的甲基化驱动基因。从癌症基因组图谱中下载了 HNSCC 患者的生存时间数据、RNA 测序数据和甲基化数据。利用基于β混合模型的 MethylMix R 包筛选肿瘤组织和相邻正常组织中具有不同甲基化状态的基因，共鉴定出 182 个与 HNSCC 相关的甲基化驱动基因。基于多变量 Cox 分析开发了一个基于生存预测的评分模型，用于筛选与 HNSCC 预后相关的基因，并构建了六个基因（INA、LINC01354、TSPYL4、MAGEB2、EPHX3 和 ZNF134）甲基化状态的线性风险模型。通过生存分析结合甲基化和基因表达分析进一步独立探索了这六个基因的预后价值。在测试集中，高风险组患者的 5 年生存率为 30.4%（95%CI：22.7%-40.8%），低风险组患者的 5 年生存率为 65.5%（95%CI：56.1%-76.5%）。模型的受试者工作特征曲线下面积为 0.723，进一步验证了模型的特异性和敏感性。此外，随后的联合生存分析表明，这六个基因都可以作为独立的预后标志物，因此可能是潜在的药物靶点。这种创新方法为 HNSCC 的分子机制和预后提供了新的见解。
