Department of Endodontics, School and Hospital of Stomatology, China Medical University, Shenyang, China.
Liaoning Provincial Key Laboratory of Oral Diseases, Shenyang, China.
FEBS Open Bio. 2021 Jul;11(7):2060-2073. doi: 10.1002/2211-5463.13134. Epub 2021 May 21.
Head and neck squamous cell carcinoma (HNSCC) ranks as the sixth most common cancer among systemic malignant tumors, with 600 000 new cases occurring every year worldwide. Since HNSCC has high heterogeneity and complex pathogenesis, no effective prognostic indicator has yet been identified. Here, we aimed to identify a lncRNA signature associated with the prognosis of HNSCC as a potential new biomarker. LncRNA expression data were downloaded from The Cancer Genome Atlas database. A polygenic risk score model was constructed by using Lasso-Cox regression analysis. Weighted gene co-expression network analysis (WGCNA) was applied to analyze the co-expression modules of lncRNAs associated with the prognosis of HNSCC. The robustness of the signature was validated in testing and external cohorts. Polymerase chain reaction was performed to detect the expression levels of identified lncRNAs in cancer and adjacent tissues. We constructed an 8-lncRNA signature (LINC00567, LINC00996, MTOR-AS1, PRKG1-AS1, RAB11B-AS1, RPS6KA2-AS1, SH3BP5-AS1, ZNF451-AS1) that could be used as an independent prognostic factor of HNSCC. The signature showed strong robustness and had stable prediction performance in different cohorts. WGCNA results showed that modules related to risk score mainly participated in biological processes such as blood vessel development, positive regulation of catabolic processes, and regulation of growth. The prognostic risk score model based on lncRNA for HNSCC may help clinicians conduct individualized treatment plans.
头颈部鳞状细胞癌（HNSCC）是全身性恶性肿瘤中第六种最常见的癌症，全球每年有 60 万新发病例。由于 HNSCC 具有高度异质性和复杂的发病机制，目前尚未确定有效的预后指标。在这里，我们旨在确定与 HNSCC 预后相关的 lncRNA 特征，作为一种有潜力的新生物标志物。lncRNA 表达数据从癌症基因组图谱数据库中下载。通过 Lasso-Cox 回归分析构建多基因风险评分模型。应用加权基因共表达网络分析（WGCNA）分析与 HNSCC 预后相关的 lncRNA 的共表达模块。该特征在测试和外部队列中进行了验证。聚合酶链反应检测鉴定的 lncRNA 在癌症和相邻组织中的表达水平。我们构建了一个 8-lncRNA 特征（LINC00567、LINC00996、MTOR-AS1、PRKG1-AS1、RAB11B-AS1、RPS6KA2-AS1、SH3BP5-AS1、ZNF451-AS1），可作为 HNSCC 的独立预后因素。该特征在不同队列中表现出较强的稳健性和稳定的预测性能。WGCNA 结果表明，与风险评分相关的模块主要参与生物过程，如血管发育、分解代谢过程的正调节和生长的调节。基于 lncRNA 的 HNSCC 预后风险评分模型可能有助于临床医生制定个体化治疗计划。
