Department of Respiratory and Critical Care Medicine, The Affiliated Changsha Hospital of Xiangya School of Medicine, Central South University, Changsha, 410005, Hunan, China.
Department of Respiratory and Critical Care Medicine, Shanghai Tenth People's Hospital, Tongji University School of Medicine, Shanghai, 200072, China.
Comb Chem High Throughput Screen. 2024;27(13):1969-1983. doi: 10.2174/0113862073282003240119064337.
Lung adenocarcinoma (LUAD) is one of the most common malignant cancers. Neutrophil extracellular traps (NETs) have been discovered to play a crucial role in the pathogenesis of LUAD. We aimed to establish an innovative prognostic model for LUAD based on the distinct expression patterns of NETs-related genes.
The TCGA LUAD dataset was utilized as the training set, while GSE31210, GSE37745, and GSE50081 were undertaken as the verification sets. The patients were grouped into clusters based on the expression signature of NETs-related genes. Differentially expressed genes between clusters were identified through the utilization of the random forest and LASSO algorithms. The NETs score model for LUAD prognosis was developed by multiplying the expression levels of specific genes with their corresponding LASSO coefficients and then summing them. The validity of the model was confirmed by analysis of the survival curves and ROC curves. Additionally, immune infiltration, GSEA, mutation analysis, and drug analysis were conducted. Silencing ABCC2 in A549 cells was achieved to investigate its effect.
We identified six novel NETs-related genes, namely , and , and developed a NETs score signature, which exhibited a significant correlation with the clinicopathological and immune traits of the LUAD patients. High-risk patients showed inhibition of immune-related processes. Mutation patterns exhibited variability among the different groups. AZD3759, lapatinib, and dasatinib have been identified as potential candidates for LUAD treatment. Moreover, the downregulation of ABCC2 resulted in the induction of apoptosis and suppression of migration and invasion in A549 cells.
Altogether, this study has identified a novel NET-score signature based on six novel NET-related genes to predict the prognosis of LUAD and ABCC2 and has also explored a new method for personalized chemo-/immuno-therapy of LUAD.
肺腺癌 (LUAD) 是最常见的恶性癌症之一。现已发现中性粒细胞胞外诱捕网 (NETs) 在 LUAD 的发病机制中发挥关键作用。我们旨在基于 NETs 相关基因的独特表达模式，为 LUAD 建立一种创新的预后模型。
利用 TCGA LUAD 数据集作为训练集，同时采用 GSE31210、GSE37745 和 GSE50081 作为验证集。根据 NETs 相关基因表达特征对患者进行聚类。通过随机森林和 LASSO 算法识别不同聚类之间差异表达的基因。通过将特定基因的表达水平与其对应的 LASSO 系数相乘，然后相加，建立 LUAD 预后的 NETs 评分模型。通过生存曲线和 ROC 曲线分析来验证模型的有效性。此外，还进行了免疫浸润、GSEA、突变分析和药物分析。通过沉默 A549 细胞中的 ABCC2 来研究其作用。
我们鉴定了六个新的 NETs 相关基因，即 、 、 和 ，并开发了一个 NETs 评分特征，该特征与 LUAD 患者的临床病理和免疫特征显著相关。高危患者表现出免疫相关过程的抑制。不同组之间的突变模式存在差异。AZD3759、拉帕替尼和达沙替尼已被确定为 LUAD 治疗的潜在候选药物。此外，下调 ABCC2 可诱导 A549 细胞凋亡，并抑制其迁移和侵袭。
总之，本研究基于六个新的 NET 相关基因鉴定了一个新的 NET 评分特征，用于预测 LUAD 的预后，并且还探索了 LUAD 个体化化疗/免疫治疗的新方法。
