Diao Xiayao, Guo Chao, Li Shanqing
Department of Thoracic Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Front Genet. 2022 Jul 22;13:833362. doi: 10.3389/fgene.2022.833362. eCollection 2022.
Long non-coding RNAs (lncRNAs) are drawing increasing attention as promising predictors of prognosis for lung adenocarcinoma (LUAD) patients. Necroptosis, a novel regulated mechanism of necrotic cell death, plays an important role in the biological process of cancer. The aim of this study was to identify the necroptosis-related lncRNAs (NRLRs) in a LUAD cohort and establish a necroptosis-related lncRNA signature (NRLSig) to stratify LUAD patients. NRLRs were identified in LUAD patients from The Cancer Genome Atlas (TCGA) database using Pearson correlation analysis between necroptosis-related genes and lncRNAs. Then the NRLSig was identified using univariate Cox regression analysis and LASSO regression analysis. Assessments of the signature were performed based on survival analysis, receiver operating characteristic (ROC) curve analysis and clustering analysis. Next, a nomogram containing the NRLSig and clinical information was developed through univariate and multivariate Cox regression analysis. Further, functional enrichment analysis of the selected lncRNAs in NRLSig and the association between NRLSig and the immune infiltration were also evaluated. A 4-lncRNA signature, incorporating LINC00941, AP001453.2, AC026368.1, and AC236972.3, was identified to predict overall survival (OS) and stratify LUAD patients into different groups. Survival analysis, ROC curve analysis and clustering analysis showed good performance in the prognostic prediction of the lncRNA signature. Then, a nomogram containing the NRLSig was developed and showed satisfactory predictive accuracy, calibration and clinical usefulness. The co-expressed genes of selected NRLRs were enriched in several biological functions and signaling pathways. Finally, differences in the abundance of immune cells were investigated among the high-risk group and low-risk group divided by the NRLSig. The proposed NRLSig may provide promising therapeutic targets or prognostic predictors for LUAD patients.
长链非编码RNA（lncRNAs）作为肺腺癌（LUAD）患者预后的有前景的预测指标，正受到越来越多的关注。坏死性凋亡是一种新型的坏死性细胞死亡调控机制，在癌症的生物学过程中起重要作用。本研究的目的是在LUAD队列中鉴定与坏死性凋亡相关的lncRNAs（NRLRs），并建立一个与坏死性凋亡相关的lncRNA特征（NRLSig）来对LUAD患者进行分层。使用坏死性凋亡相关基因与lncRNAs之间的Pearson相关性分析，在来自癌症基因组图谱（TCGA）数据库的LUAD患者中鉴定NRLRs。然后使用单变量Cox回归分析和LASSO回归分析鉴定NRLSig。基于生存分析、受试者工作特征（ROC）曲线分析和聚类分析对该特征进行评估。接下来，通过单变量和多变量Cox回归分析开发了一个包含NRLSig和临床信息的列线图。此外，还评估了NRLSig中所选lncRNAs的功能富集分析以及NRLSig与免疫浸润之间的关联。鉴定出一个包含LINC00941、AP001453.2、AC026368.1和AC236972.3的4-lncRNA特征，用于预测总生存期（OS）并将LUAD患者分层为不同组。生存分析、ROC曲线分析和聚类分析在lncRNA特征的预后预测中表现良好。然后，开发了一个包含NRLSig的列线图，其显示出令人满意地预测准确性、校准度和临床实用性。所选NRLRs的共表达基因在几种生物学功能和信号通路中富集。最后，研究了由NRLSig划分的高危组和低危组之间免疫细胞丰度的差异。所提出的NRLSig可能为LUAD患者提供有前景的治疗靶点或预后预测指标。
