Department of Otolaryngology Head and Neck Surgery, Ningbo Medical Center Lihuili Hospital, The Affiliated Lihuili Hospital of Ningbo University, Ningbo, Zhejiang, China.
School of Medicine, Ningbo University, Ningbo, Zhejiang, China.
J Clin Lab Anal. 2022 Jun;36(6):e24480. doi: 10.1002/jcla.24480. Epub 2022 May 6.
Previous studies have determined that necroptosis-related genes are potential biomarkers in head and neck squamous cell carcinoma (HNSCC). Herein, we established a novel risk model based on necroptosis-related lncRNAs (nrlncRNAs) to predict the prognosis of HNSCC patients.
Transcriptome and related information were obtained from TCGA database, and an nrlncRNA signature was established based on univariate Cox analysis and least absolute shrinkage and selection operator Cox regression. Kaplan-Meier analysis and time-dependent receiver operating characteristic (ROC) analysis were used to evaluate the model, and a nomogram for survival prediction was established. Gene set enrichment analysis, immune analysis, drug sensitivity analysis, correlation with N6-methylandenosin (m6A), and tumor stemness analysis were performed. Furthermore, the entire set was divided into two clusters for further discussion.
A novel signature was established with six nrlncRNAs. The areas under the ROC curves (AUCs) for 1-, 3-, and 5-year overall survival (OS) were 0.699, 0.686, and 0.645, respectively. Patients in low-risk group and cluster 2 had a better prognosis, more immune cell infiltration, higher immune function activity, and higher immune scores; however, patients in high-risk group and cluster 1 were more sensitive to chemotherapy. Moreover, the risk score had negative correlation with m6A-related gene expression and tumor stemness.
According to this study, we constructed a novel signature with nrlncRNA pairs to predict the survival of HNSCC patients and guide immunotherapy and chemotherapy. This may possibly promote the development of individualized and precise treatment for HNSCC patients.
先前的研究已经确定,坏死性凋亡相关基因是头颈部鳞状细胞癌(HNSCC)的潜在生物标志物。在此,我们建立了一个基于坏死性凋亡相关长链非编码 RNA(nrlncRNA)的新型风险模型,以预测 HNSCC 患者的预后。
从 TCGA 数据库中获取转录组和相关信息,并基于单变量 Cox 分析和最小绝对值收缩和选择算子 Cox 回归建立 nrlncRNA 特征。Kaplan-Meier 分析和时间依赖的接收器操作特征(ROC)分析用于评估模型,并建立用于生存预测的列线图。进行基因集富集分析、免疫分析、药物敏感性分析、与 N6-甲基腺苷(m6A)的相关性以及肿瘤干性分析。此外,将整个数据集分为两个簇进行进一步讨论。
建立了一个包含六个 nrlncRNA 的新型特征。1 年、3 年和 5 年总生存(OS)的 ROC 曲线下面积(AUC)分别为 0.699、0.686 和 0.645。低风险组和簇 2 的患者预后较好,免疫细胞浸润较多,免疫功能活性较高,免疫评分较高;然而,高风险组和簇 1 的患者对化疗更敏感。此外,风险评分与 m6A 相关基因表达和肿瘤干性呈负相关。
根据本研究,我们构建了一个包含 nrlncRNA 对的新型特征,用于预测 HNSCC 患者的生存情况,并指导免疫治疗和化疗。这可能有助于促进 HNSCC 患者个体化和精准治疗的发展。