Chen Shu-Jen, Liu Hsuan, Liao Chun-Ta, Huang Po-Jung, Huang Yi, Hsu An, Tang Petrus, Chang Yu-Sun, Chen Hua-Chien, Yen Tzu-Chen
Department of Biomedical Sciences, Chang Gung University, Taoyuan, 33302, Taiwan.
Genomic Core Laboratory, Chang Gung University, Taoyuan, 33302, Taiwan.
Oncotarget. 2015 Jul 20;6(20):18066-80. doi: 10.18632/oncotarget.3768.
Patients with advanced oral squamous cell carcinoma (OSCC) have heterogeneous outcomes that limit the implementation of tailored treatment options. Genetic markers for improved prognostic stratification are eagerly awaited.
Herein, next-generation sequencing (NGS) was performed in 345 formalin-fixed paraffin-embedded (FFPE) samples obtained from advanced OSCC patients. Genetic mutations on the hotspot regions of 45 cancer-related genes were detected using an ultra-deep (>1000×) sequencing approach. Kaplan-Meier plots and Cox regression analyses were used to investigate the associations between the mutation status and disease-free survival (DFS).
We identified 1269 non-synonymous mutations in 276 OSCC samples. TP53, PIK3CA, CDKN2A, HRAS and BRAF were the most frequently mutated genes. Mutations in 14 genes were found to predict DFS. A mutation-based signature affecting ten genes (HRAS, BRAF, FGFR3, SMAD4, KIT, PTEN, NOTCH1, AKT1, CTNNB1, and PTPN11) was devised to predict DFS. Two different resampling methods were used to validate the prognostic value of the identified gene signature. Multivariate analysis demonstrated that presence of a mutated gene signature was an independent predictor of poorer DFS (P = 0.005).
Genetic variants identified by NGS technology in FFPE samples are clinically useful to predict prognosis in advanced OSCC patients.
晚期口腔鳞状细胞癌（OSCC）患者的预后存在异质性，这限制了个性化治疗方案的实施。人们急切期待能够改善预后分层的基因标志物。
在此，对从晚期OSCC患者获取的345份福尔马林固定石蜡包埋（FFPE）样本进行了二代测序（NGS）。采用超深度（>1000×）测序方法检测45个癌症相关基因热点区域的基因突变。使用Kaplan-Meier曲线和Cox回归分析来研究突变状态与无病生存期（DFS）之间的关联。
我们在276份OSCC样本中鉴定出1269个非同义突变。TP53、PIK3CA、CDKN2A、HRAS和BRAF是最常发生突变的基因。发现14个基因的突变可预测DFS。设计了一种基于影响10个基因（HRAS、BRAF、FGFR3、SMAD4、KIT、PTEN、NOTCH1、AKT1、CTNNB1和PTPN11）的突变特征来预测DFS。使用两种不同的重采样方法来验证所鉴定基因特征的预后价值。多变量分析表明，存在突变基因特征是DFS较差的独立预测因素（P = 0.005）。
通过NGS技术在FFPE样本中鉴定出的基因变异在临床上有助于预测晚期OSCC患者的预后。
