Department of General Surgery, Aerospace Central Hospital, 15 Yuquan Road, Haidian District, Beijing, China.
Department of Medical Oncology, Senior Department of Oncology, Fengtai District, The Fifth Medical Center of PLA General Hospital, No. 100, West Fourth Ring Middle Road, Beijing, 100039, China.
Apoptosis. 2024 Aug;29(7-8):1090-1108. doi: 10.1007/s10495-024-01947-4. Epub 2024 Mar 22.
Neutrophil extracellular traps (NETs) are novel inflammatory cell death in neutrophils. Emerging studies demonstrated NETs contributed to cancer progression and metastases in multiple ways. This study intends to provide a prognostic NETs signature and therapeutic target for lung adenocarcinoma (LUAD) patients. Consensus cluster analysis performed by 38 reported NET-related genes in TCGA-LUAD cohorts. Then, WGCNA network was conducted to investigate characteristics genes in clusters. Seven machine learning algorithms were assessed for training of the model, the optimal model was picked by C-index and 1-, 3-, 5-year ROC value. Then, we constructed a NETs signature to predict the overall survival of LUAD patients. Moreover, multi-omics validation was performed based on NETs signature. Finally, we constructed stable knockdown critical gene LUAD cell lines to verify biological functions of Phospholipid Scramblase 1 (PLSCR1) in vitro and in vivo. Two NETs-related clusters were identified in LUAD patients. Among them, C2 cluster was provided as "hot" tumor phenotype and exhibited a better prognosis. Then, WGCNA network identified 643 characteristic genes in C2 cluster. Then, Coxboost algorithm proved its optimal performance and provided a prognostic NETs signature. Multi-omics revealed that NETs signature was involved in an immunosuppressive microenvironment and predicted immunotherapy efficacy. In vitro and in vivo experiments demonstrated that knockdown of PLSCR1 inhibited tumor growth and EMT ability. Besides, cocultural assay indicated that the knockdown of PLSCR1 impaired the ability of neutrophils to generate NETs. Finally, tissue microarray (TMA) for LUAD patients verified the prognostic value of PLSCR1 expression. In this study, we focus on emerging hot topic NETs in LUAD. We provide a prognostic NETs signature and identify PLSCR1 with multiple roles in LUAD. This work can contribute to risk stratification and screen novel therapeutic targets for LUAD patients.
中性粒细胞胞外诱捕网（NETs）是中性粒细胞的一种新型炎症细胞死亡方式。新出现的研究表明，NETs 通过多种方式促进癌症的进展和转移。本研究旨在为肺腺癌（LUAD）患者提供一个预后性 NETs 特征和治疗靶点。通过 TCGA-LUAD 队列中报告的 38 个 NET 相关基因进行共识聚类分析。然后，进行 WGCNA 网络分析以研究聚类中的特征基因。使用 7 种机器学习算法对模型进行训练，通过 C 指数和 1、3、5 年 ROC 值来选择最优模型。然后，我们构建了一个 NETs 特征来预测 LUAD 患者的总生存率。此外，还基于 NETs 特征进行了多组学验证。最后，我们构建了稳定敲低关键基因的 LUAD 细胞系，以验证磷脂爬行酶 1（PLSCR1）在体外和体内的生物学功能。在 LUAD 患者中鉴定出两个与 NETs 相关的聚类。其中，C2 聚类被认为是“热”肿瘤表型，预后较好。然后，WGCNA 网络鉴定出 C2 聚类中的 643 个特征基因。然后，Coxboost 算法证明了其最佳性能，并提供了一个预后性 NETs 特征。多组学研究表明，NETs 特征与免疫抑制微环境有关，并预测免疫治疗疗效。体外和体内实验表明，敲低 PLSCR1 可抑制肿瘤生长和 EMT 能力。此外，共培养试验表明，敲低 PLSCR1 会损害中性粒细胞生成 NETs 的能力。最后，对 LUAD 患者的组织微阵列（TMA）进行验证，证实了 PLSCR1 表达的预后价值。在本研究中，我们关注 LUAD 中新兴的热门话题 NETs。我们提供了一个预后性 NETs 特征，并确定了 PLSCR1 在 LUAD 中的多种作用。这项工作有助于 LUAD 患者的风险分层和筛选新的治疗靶点。
