Xiao Lingyan, Li Qian, Huang Yongbiao, Fan Zhijie, Qin Wan, Liu Bo, Yuan Xianglin
Department of Oncology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Department of Pathophysiology, School of Basic Medicine, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Front Cell Dev Biol. 2022 Apr 26;10:835043. doi: 10.3389/fcell.2022.835043. eCollection 2022.
Lung adenocarcinoma (LUAD) accounts for the majority of lung cancers, and the survival of patients with advanced LUAD is poor. The extracellular matrix (ECM) is a fundamental component of the tumor microenvironment (TME) that determines the oncogenesis and antitumor immunity of solid tumors. However, the prognostic value of extracellular matrix-related genes (ERGs) in LUAD remains unexplored. Therefore, this study is aimed to explore the prognostic value of ERGs in LUAD and establish a classification system to predict the survival of patients with LUAD. LUAD samples from The Cancer Genome Atlas (TCGA) and GSE37745 were used as discovery and validation cohorts, respectively. Prognostic ERGs were identified by univariate Cox analysis and used to construct a prognostic signature by Least Absolute Shrinkage and Selection Operator (LASSO) regression analysis. The extracellular matrix-related score (ECMRS) of each patient was calculated according to the prognostic signature and used to classify patients into high- and low-risk groups. The prognostic performance of the signature was evaluated using Kaplan-Meier curves, Cox regression analyses, and ROC curves. The relationship between ECMRS and tumor immunity was determined using stepwise analyses. A nomogram based on the signature was established for the convenience of use in the clinical practice. The prognostic genes were validated in multiple databases and clinical specimens by qRT-PCR. A prognostic signature based on eight ERGs (, , , , , , , and ) was constructed. Patients with higher ECMRS had poorer survival, lower immune scores, and higher tumor purity in both the discovery and validation cohorts. The predictive power of the signature was independent of the clinicopathological parameters, and the nomogram could also predict survival precisely. We constructed an ECM-related gene signature which can be used to predict survival and tumor immunity in patients with LUAD. This signature can serve as a novel prognostic indicator and therapeutic target in LUAD.
肺腺癌（LUAD）占肺癌的大多数，晚期LUAD患者的生存率较低。细胞外基质（ECM）是肿瘤微环境（TME）的基本组成部分，它决定了实体瘤的肿瘤发生和抗肿瘤免疫。然而，细胞外基质相关基因（ERGs）在LUAD中的预后价值仍未得到探索。因此，本研究旨在探讨ERGs在LUAD中的预后价值，并建立一个分类系统来预测LUAD患者的生存情况。来自癌症基因组图谱（TCGA）的LUAD样本和GSE37745分别用作发现队列和验证队列。通过单变量Cox分析确定预后ERGs，并使用最小绝对收缩和选择算子（LASSO）回归分析构建预后特征。根据预后特征计算每个患者的细胞外基质相关评分（ECMRS），并用于将患者分为高风险和低风险组。使用Kaplan-Meier曲线、Cox回归分析和ROC曲线评估该特征的预后性能。使用逐步分析确定ECMRS与肿瘤免疫之间的关系。为方便临床实践，基于该特征建立了列线图。通过qRT-PCR在多个数据库和临床标本中验证了预后基因。构建了基于八个ERGs（、、、、、、和）的预后特征。在发现队列和验证队列中，ECMRS较高的患者生存率较低、免疫评分较低且肿瘤纯度较高。该特征的预测能力独立于临床病理参数，列线图也可以准确预测生存情况。我们构建了一个与ECM相关的基因特征，可用于预测LUAD患者的生存情况和肿瘤免疫。该特征可作为LUAD的一种新的预后指标和治疗靶点。
