Zhang Yongxiang, Chen Feng, Cao Yuqi, Zhang Hao, Zhao Lingling, Xu Yijun
Department of Respiratory and Critical Care Medicine, Tianjin chest Hospital, Tianjin, China.
Department of Thoracic surgery, Tianjin chest Hospital, Tianjin, China.
Cancer Biomark. 2025 Feb;42(2):18758592251317400. doi: 10.1177/18758592251317400. Epub 2025 Apr 3.
Lung cancer (LC) is the most common malignancy and the leading cause of cancer death. LC-derived exosomes have been found to play a critical role in tumor initiation, progression, metastasis and drug resistance. Therefore, the objective of this study is to identify prognostic markers based on lung cancer-derived exosomes in patients with different subtypes of lung cancer, including small cell lung cancer (SCLC), lung adenocarcinoma (LUAD), lung squamous cell carcinoma (LUSC) and large cell carcinoma (LCC). Additionally, we aim to develop corresponding prognostic models to predict the outcomes of these patients. In this study, the mRNAs information about LC-derived exosomes was collected from Vesiclependia database, and the mRNAs data of LCC, LUAD, LUSC and LCC tumors and paracancerous tissues was obtained from the GEO database and UCSC database. The prognostic models based on exosomes-related differential expression genes (ExoDEGs) by univariate Cox, LASSO, and multivariate Cox regression analyses. The independent prognostic value of the risk model was systematically analyzed. A LUAD prognostic risk model of 12 ExoDEGs (CDH17, DAAM2, FKBP3, FLNC, GSTM2, PGAM4, HPCAL1, FERMT2, LYPD1, SNRNP70, KIR3DL2 and GPX3) and a LUSC prognostic risk model of 7 ExoDEGs (FGA, ERH, HID1, CSNK2A1, SLC7A5, ACOT7 and FUNDC1) were constructed. Kaplan-Meier curve, ROC curve and stratification survival analysis confirmed that the LUAD and LUSC risk models both possessed reliable predictive value for the prognosis of LUAD and LUSC patients. The expression level of ExoDEGs for building the LUAD and LUSC risk models is significantly correlated with immunosuppressive activity of patients, and the immunosuppressive activity is lower in the high-risk groups. We established a LUAD prognostic model with 12 ExoDEGs and a LUSC prognostic model with 7 ExoDEGs, which can be used as independent prognostic indicators for patients LUAD and LUSC. The identified ExoDEGs have the potential to be as prognostic markers and may also serve as novel candidate targets for the treatment of LUAD and LUSC.
肺癌（LC）是最常见的恶性肿瘤，也是癌症死亡的主要原因。已发现源自肺癌的外泌体在肿瘤发生、进展、转移和耐药性中起关键作用。因此，本研究的目的是在不同亚型肺癌患者中，包括小细胞肺癌（SCLC）、肺腺癌（LUAD）、肺鳞状细胞癌（LUSC）和大细胞癌（LCC），基于源自肺癌的外泌体鉴定预后标志物。此外，我们旨在开发相应的预后模型来预测这些患者的预后。在本研究中，从Vesiclependia数据库收集了有关源自肺癌的外泌体的mRNA信息，并从GEO数据库和UCSC数据库获得了LCC、LUAD、LUSC和LCC肿瘤及癌旁组织的mRNA数据。通过单变量Cox、LASSO和多变量Cox回归分析建立基于外泌体相关差异表达基因（ExoDEGs）的预后模型。系统分析了风险模型的独立预后价值。构建了一个包含12个ExoDEGs（CDH17、DAAM2、FKBP3、FLNC、GSTM2、PGAM4、HPCAL1、FERMT2、LYPD1、SNRNP70、KIR3DL2和GPX3）的LUAD预后风险模型和一个包含7个ExoDEGs（FGA、ERH、HID1、CSNK2A1、SLC7A5、ACOT7和FUNDC1）的LUSC预后风险模型。Kaplan-Meier曲线、ROC曲线和分层生存分析证实，LUAD和LUSC风险模型对LUAD和LUSC患者的预后均具有可靠的预测价值。构建LUAD和LUSC风险模型的ExoDEGs表达水平与患者的免疫抑制活性显著相关，且高风险组的免疫抑制活性较低。我们建立了一个包含12个ExoDEGs的LUAD预后模型和一个包含7个ExoDEGs的LUSC预后模型，它们可作为LUAD和LUSC患者的独立预后指标。鉴定出的ExoDEGs有潜力作为预后标志物，也可能成为LUAD和LUSC治疗的新候选靶点。
