Department of Oncology, Wujin Hospital Affiliated with Jiangsu University, Changzhou, Jiangsu Province 213017, China.
Department of Oncology, Wujin Clinical College of Xuzhou Medical University, Changzhou, Jiangsu Province 213017, China.
Biomed Res Int. 2022 Oct 25;2022:9710540. doi: 10.1155/2022/9710540. eCollection 2022.
Several cancers, including lung adenocarcinoma (LUAD), are caused by genes related to necroptosis. However, it is still unknown how necroptosis-related long noncoding RNAs (lncRNAs) may be involved in LUAD. In order to predict the prognosis of LUAD patients and personalize immunotherapy, this study set out to construct a necroptosis-related lncRNA prognostic signature (NLPS).
The Cancer Genome Atlas (TCGA) database was used to download the LUAD transcriptome data and the associated clinical data. lncRNAs associated with necroptosis were screened using coexpression analysis. An NLPS was built using univariate and least absolute shrinkage and selection operator (LASSO) Cox regression analyses. The Gene Expression Omnibus (GEO) database's GSE30219 was used to validate the NLPS. The prognostic value of the risk score was assessed using Kaplan-Meier survival, receiver operating characteristic (ROC) Cox regression, multivariate Cox regression, and nomogram analyses. Then, we looked into the differences between the low- and high-risk groups in the tumor immune microenvironment, immunotherapy response, and half-maximal inhibitory concentration (IC50).
The 14 lncRNAs in a novel NLPS were created. With further validation in the GSE30219 dataset, the risk score according to the NLPS was an independent prognostic indicator for LUAD patients. Patients with better overall survival (OS) in the low-risk group, who were characterized by increased immune cell infiltration, tumor mutational burden (TMB), and immunophenoscore (IPS), may have hot tumors and higher immunotherapy response rates. In addition, the risk score was also closely linked to sensitivity to various anticancer medications.
We constructed a novel NLPS that could predict OS and sensitivity to immunotherapy in LUAD patients.
包括肺腺癌 (LUAD) 在内的几种癌症是由与坏死性凋亡相关的基因引起的。然而,目前尚不清楚坏死性凋亡相关的长链非编码 RNA (lncRNA) 如何参与 LUAD。为了预测 LUAD 患者的预后并实现免疫治疗的个体化,本研究旨在构建一个坏死性凋亡相关的 lncRNA 预后特征 (NLPS)。
使用癌症基因组图谱 (TCGA) 数据库下载 LUAD 转录组数据及其相关临床数据。使用共表达分析筛选与坏死性凋亡相关的 lncRNA。使用单变量和最小绝对值收缩和选择算子 (LASSO) Cox 回归分析构建 NLPS。使用基因表达综合数据库 (GEO) 数据库的 GSE30219 数据集验证 NLPS。使用 Kaplan-Meier 生存分析、ROC Cox 回归、多变量 Cox 回归和列线图分析评估风险评分的预后价值。然后,我们研究了低风险组和高风险组之间在肿瘤免疫微环境、免疫治疗反应和半最大抑制浓度 (IC50) 方面的差异。
在一个新的 NLPS 中构建了 14 个 lncRNA。通过在 GSE30219 数据集上进一步验证,NLPS 确定的风险评分是 LUAD 患者独立的预后指标。低风险组患者的总生存 (OS) 更好,其特征是免疫细胞浸润、肿瘤突变负荷 (TMB) 和免疫表型评分 (IPS) 增加,可能存在热肿瘤和更高的免疫治疗反应率。此外,风险评分还与对各种抗癌药物的敏感性密切相关。
我们构建了一个新的 NLPS,可预测 LUAD 患者的 OS 和对免疫治疗的敏感性。