肺腺癌（LUAD）作为肺癌的常见类型，在晚期肺癌患者中的5年总生存率低于20％。本研究旨在构建一个风险模型，以有效指导LUAD患者的免疫治疗。我们从The Cancer Genome Atlas（TCGA）和Gene Expression Omnibus（GEO）数据库中收集了用于模型构建的LUAD Bulk RNA-seq数据，用于细胞簇分析的单细胞RNA测序（scRNA-seq）数据（GSE203360），以及用于验证的微阵列数据（GSE31210）。我们使用Seurat R软件包对scRNA-seq数据进行筛选和处理。使用ConsensusClusterPlus R软件包进行样本聚类。使用Limma R软件包挖掘出两组之间的差异表达基因（DEGs）。使用MCP-counter，CIBERSORT，ssGSEA和ESTIMATE评估免疫特点。进行分步多变量分析，单变量Cox分析和Lasso回归分析以鉴定关键的预后基因，并用于构建风险模型。使用RT-qPCR和Western blot分析探索关键的预后基因表达。共确定了27个与预后相关的免疫细胞标记基因，用于将LUAD样本分为C3、C2和C1三个簇。C1具有最长的总生存期和最高的免疫浸润，其次是C2和C3。与其他两个簇相比，C3中的VEGF、EFGR和MAPK等致癌途径更为活跃。根据各簇之间的DEGs，我们确认了包括CPA3、S100P、PTTG1、LOXL2、MELTF、PKP2和TMPRSS11E在内的7个关键预后基因。由七基因风险模型定义的两个风险组在免疫治疗和化学治疗、免疫浸润和预后方面呈现出不同的反应。在临床肿瘤组织中，CPA3的mRNA和蛋白水平降低，而其他六个基因的水平升高。免疫细胞标记基因可有效将LUAD样本聚类为不同亚型，并在调节免疫微环境和癌症发展中发挥重要作用。此外，这个七基因风险模型可以作为LUAD患者个体化治疗的指导。版权所有 © 2023 Shu、Jiang和Zhao。

Lung adenocarcinoma (LUAD) as a frequent type of lung cancer has a 5-year overall survival rate of lower than 20% among patients with advanced lung cancer. This study aims to construct a risk model to guide immunotherapy in LUAD patients effectively.LUAD Bulk RNA-seq data for the construction of a model, single-cell RNA sequencing (scRNA-seq) data (GSE203360) for cell cluster analysis, and microarray data (GSE31210) for validation were collected from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database. We used the Seurat R package to filter and process scRNA-seq data. Sample clustering was performed in the ConsensusClusterPlus R package. Differentially expressed genes (DEGs) between two groups were mined by the Limma R package. MCP-counter, CIBERSORT, ssGSEA, and ESTIMATE were employed to evaluate immune characteristics. Stepwise multivariate analysis, Univariate Cox analysis, and Lasso regression analysis were conducted to identify key prognostic genes and were used to construct the risk model. Key prognostic gene expressions were explored by RT-qPCR and Western blot assay.A total of 27 immune cell marker genes associated with prognosis were identified for subtyping LUAD samples into clusters C3, C2, and C1. C1 had the longest overall survival and highest immune infiltration among them, followed by C2 and C3. Oncogenic pathways such as VEGF, EFGR, and MAPK were more activated in C3 compared to the other two clusters. Based on the DEGs among clusters, we confirmed seven key prognostic genes including CPA3, S100P, PTTG1, LOXL2, MELTF, PKP2, and TMPRSS11E. Two risk groups defined by the seven-gene risk model presented distinct responses to immunotherapy and chemotherapy, immune infiltration, and prognosis. The mRNA and protein level of CPA3 was decreased, while the remaining six gene levels were increased in clinical tumor tissues.Immune cell markers are effective in clustering LUAD samples into different subtypes, and they play important roles in regulating the immune microenvironment and cancer development. In addition, the seven-gene risk model may serve as a guide for assisting in personalized treatment in LUAD patients.Copyright © 2023 Shu, Jiang and Zhao.