Sun Xiaoming, Li Jia, Gao Xuedi, Huang Yubin, Pang Zhanyue, Lv Lin, Li Hao, Liu Haibo, Zhu Liangming
Department of Thoracic Surgery, Jinan Central Hospital, Jinan, Shandong 250013, P.R. China.
Department of Thoracic Surgery, Jinan Central Hospital, Shandong University, Jinan, Shandong 250013, P.R. China.
Oncol Lett. 2024 May 29;28(2):342. doi: 10.3892/ol.2024.14476. eCollection 2024 Aug.
Lung adenocarcinoma (LUAD) is the most common pathological type of lung cancer, and disulfidptosis is a newly discovered mechanism of programmed cell death. However, the effects of disulfidptosis-related lncRNAs (DR-lncRNAs) in LUAD have yet to be fully elucidated. The aim of the present study was to identify and validate a novel lncRNA-based prognostic marker that was associated with disulfidptosis. RNA-sequencing and associated clinical data were obtained from The Cancer Genome Atlas database. Univariate Cox regression and lasso algorithm analyses were used to identify DR-lncRNAs and to establish a prognostic model. Kaplan-Meier curves, receiver operating characteristic curves, principal component analysis, Cox regression, nomograms and calibration curves were used to assess the reliability of the prognostic model. Functional enrichment analysis, immune infiltration analysis, somatic mutation analysis, tumor microenvironment and drug predictions were applied to the risk model. Reverse transcription-quantitative PCR was subsequently performed to validate the mRNA expression levels of the lncRNAs in normal cells and tumor cells. These analyses enabled a DR-lncRNA prognosis signature to be constructed, consisting of nine lncRNAs; U91328.1, LINC00426, MIR1915HG, TMPO-AS1, TDRKH-AS1, AL157895.1, AL512363.1, AC010615.2 and GCC2-AS1. This risk model could serve as an independent prognostic tool for patients with LUAD. Numerous immune evaluation algorithms indicated that the low-risk group may exhibit a more robust and active immune response against the tumor. Moreover, the tumor immune dysfunction exclusion algorithm suggested that immunotherapy would be more effective in patients in the low-risk group. The drug-sensitivity results showed that patients in the high-risk group were more sensitive to treatment with crizotinib, erlotinib or savolitinib. Finally, the expression levels of AL157895.1 were found to be lower in A549. In summary, a novel DR-lncRNA signature was constructed, which provided a new index to predict the efficacy of therapeutic interventions and the prognosis of patients with LUAD.
肺腺癌(LUAD)是肺癌最常见的病理类型,而二硫化物诱导的细胞程序性坏死是一种新发现的程序性细胞死亡机制。然而,二硫化物诱导的细胞程序性坏死相关长链非编码RNA(DR-lncRNAs)在LUAD中的作用尚未完全阐明。本研究的目的是鉴定和验证一种与二硫化物诱导的细胞程序性坏死相关的基于长链非编码RNA的新型预后标志物。从癌症基因组图谱数据库中获取RNA测序及相关临床数据。采用单因素Cox回归和套索算法分析来鉴定DR-lncRNAs并建立预后模型。使用Kaplan-Meier曲线、受试者工作特征曲线、主成分分析、Cox回归、列线图和校准曲线来评估预后模型的可靠性。将功能富集分析、免疫浸润分析、体细胞突变分析、肿瘤微环境和药物预测应用于风险模型。随后进行逆转录定量PCR以验证正常细胞和肿瘤细胞中lncRNAs的mRNA表达水平。这些分析构建了一个由9个lncRNAs组成的DR-lncRNA预后特征,即U91328.1、LINC00426、MIR1915HG、TMPO-AS1、TDRKH-AS1、AL157895.1、AL512363.1、AC010615.2和GCC2-AS1。该风险模型可作为LUAD患者的独立预后工具。众多免疫评估算法表明,低风险组可能对肿瘤表现出更强有力和活跃的免疫反应。此外,肿瘤免疫功能障碍排除算法表明免疫疗法在低风险组患者中更有效。药物敏感性结果显示,高风险组患者对克唑替尼、厄洛替尼或赛沃替尼治疗更敏感。最后,发现A549中AL157895.1的表达水平较低。总之,构建了一种新型DR-lncRNA特征,为预测治疗干预效果和LUAD患者预后提供了新指标。