生物信息分析验证基于lncRNA标签预测HPV阴性头颈部鳞状细胞癌患者总生存率-《中国医学物理学杂志》

文章信息/Info

Title:: Bioinformatic analysis validates lncRNA signature as a predictor of overall survival in patients with HPV-negative head and neck squamous cell carcinoma

作者:: 黄宇1; 杨博2; 李伟忠1; 1.南方医科大学南方医院口腔颌面外科，广东广州 510000； 2.南方医科大学南方医院口腔综合科，广东广州 510000

Author(s):: HUANG Yu1; YANG Bo2; LI Weizhong1; 1. Department of Oral and Maxillofacial Surgery, Nanfang Hospital, Southern Medical University, Guangzhou 510000, China 2. Department of Stomatology, Nanfang Hospital, Southern Medical University, Guangzhou 510000, China

Keywords:: Keywords: head and neck squamous cell carcinoma long non-coding RNA human papillomavirus survival bioinformatics analysis

摘要:: 目的：采用生物信息分析方法研究影响HPV阴性头颈部鳞状细胞癌（HNSCC）患者总生存率的相关因素，为HNSCC患者的预后预测及治疗提供依据。方法：从TCGA数据库获取HPV阴性HNSCC患者的病变组织和癌旁组织的原始RNA测序数据以及相应病人的临床信息，Survival R工具包对所有差异表达的长链非编码RNA（lncRNA）进行单变量Cox回归分析，使用JAVA程序，利用MSigDB C2经典通路基因集集合进行基因集富集分析，采用LASSO方法的Cox回归对数据降维和模型构建，计算每个患者的风险评分。结果：研究发现153个lncRNA与HPV阴性HNSCC患者的总生存率显著相关，时间依赖性分析表明，13个lncRNA特征在训练集中具有良好的预测性能，多变量Cox回归和分层分析表明，基于13-lncRNA标签的风险评分可作为HPV阴性HNSCC患者的独立预后因素。结论：13-lncRNA标签可能是HPV阴性HNSCC预后的新型独立生物标志物。

Abstract:: Abstract: Objective To investigate the factors affecting the overall survival in patients with HPV-negative head and neck squamous cell carcinoma (HNSCC) by bioinformatics analysis, thereby providing evidence for the prognosis prediction and therapy in HNSCC. Methods The raw RNA sequencing data of the primary tumor and adjacent tissue of HPV-negative HNSCC patients were obtained from the TCGA database and the corresponding clinical information were collected. Survival R toolkit was used to perform univariate Cox regression analysis on all differentially expressed lncRNA a Java program was used to carry out gene set enrichment analysis using the MSigDB C2 classic pathway gene set collection and LASSO Cox regression was used for data dimensionality reduction and model building, and the risk score for each patient was calculated. Results There were 153 lncRNA which were significantly associated with overall survival in HPV-negative HNSCC patients. Time-dependent analysis showed that 13 lncRNA had good predictive performance in the training set. Multivariate Cox regression and stratified analysis revealed that the risk score based on the 13-lncRNA signature could be served as an independent prognostic factor for HPV-negative HNSCC patients. Conclusion The 13-lncRNA signature may be a novel independent biomarker for the prognosis of HPV-negative HNSCC.