Huang Jing, Lu Rong, Zhong Dongta, Weng Youliang, Liao Lianming
Department of Pharmacy, Fujian Medical University Cancer Hospital and Fujian Cancer Hospital, Fuzhou, China.
Department of Laboratory Medicine, The First Affiliated Hospital of Xiamen University, Xiamen Key Laboratory of Genetic Testing, School of Medicine, Xiamen University, Xiamen, China.
Front Genet. 2022 Jun 8;13:907392. doi: 10.3389/fgene.2022.907392. eCollection 2022.
The prognosis of head and neck squamous cell carcinoma (HNSCC) is poor. Necroptosis is a novel programmed form of necrotic cell death. The prognostic value of necroptosis-associated lncRNAs expression in HNSCC has not been explored. We downloaded mRNA expression data of HNSCC patients from TCGA databases. Prognostic lncRNAs were identified by univariate Cox regression. LASSO was used to establish a model with necroptosis-related lncRNAs. Kaplan-Meier analysis and ROC were applied to verify the model. Finally, functional studies including gene set enrichment analyses, immune microenvironment analysis, and anti-tumor compound IC50 prediction were performed. We identified 1,117 necroptosis-related lncRNAs. The Cox regression showed 55 lncRNAs were associated with patient survival ( < 0.05). The risk model of 24- lncRNAs signature categorized patients into high and low risk groups. The patients in the low-risk group survived longer than the high-risk group ( < 0.001). Validation assays including ROC curve, nomogram and correction curves confirmed the prediction capability of the 24-lncRNA risk mode. Functional studies showed the two patient groups had distinct immunity conditions and IC50. The 24-lncRNA model has potential to guide treatment of HNSCC. Future clinical studies are needed to verify the model.
头颈部鳞状细胞癌（HNSCC）的预后较差。坏死性凋亡是一种新型的程序性坏死细胞死亡形式。尚未探讨坏死性凋亡相关长链非编码RNA（lncRNA）表达在HNSCC中的预后价值。我们从TCGA数据库下载了HNSCC患者的mRNA表达数据。通过单因素Cox回归鉴定预后lncRNA。使用LASSO建立与坏死性凋亡相关lncRNA的模型。应用Kaplan-Meier分析和ROC验证该模型。最后，进行了包括基因集富集分析、免疫微环境分析和抗肿瘤化合物IC50预测在内的功能研究。我们鉴定出1117个与坏死性凋亡相关的lncRNA。Cox回归显示55个lncRNA与患者生存相关（P<0.05）。24个lncRNA特征的风险模型将患者分为高风险组和低风险组。低风险组患者的生存期长于高风险组（P<0.001）。包括ROC曲线、列线图和校正曲线在内的验证试验证实了24-lncRNA风险模型的预测能力。功能研究表明，两组患者具有不同的免疫状态和IC50。24-lncRNA模型有指导HNSCC治疗的潜力。未来需要进行临床研究来验证该模型。
