Department of Thoracic Surgery, The First Affiliated Hospital, School of Medicine, Zhejiang University, China.
Biomed Res Int. 2020 Apr 3;2020:6472153. doi: 10.1155/2020/6472153. eCollection 2020.
A survival risk assessment model associated with a lung adenocarcinoma (LUAD) microenvironment was established and evaluated to identify effective independent prognostic factors for LUAD.
The public data were downloaded from the TCGA database, and ESTIMATE prediction software was used to score immune cells and stromal cells for tumor purity prediction. The samples were divided into the high-score group and the low-score group by the median value of the immune score (or stromal score). The Wilcoxon test was used for differential analysis. GO and KEGG enrichment analysis of differentially expressed genes (DEGs) was performed using "clusterProfiler" of R package. Meanwhile, univariate and multivariate regression analysis was performed on DEGs to construct a multivariate Cox risk regression model with variable gene expression levels as independent prognostic factors affecting a tumor microenvironment (TME) and tumor immunity.
This study found that LUAD patients with high immune cell (stromal cell) infiltration had better prognosis and were in earlier staging. Functional enrichment analysis revealed that most DEGs were related to the proliferation and activation of immune cells or stromal cells. A survival prediction model composed of 6 TME-related genes (CLEC17A, TAGAP, ABCC8, BCAN, FLT3, and CCR2) was established, and finally, the 6 feature genes closely related to the prognosis of LUAD were proved. The AUC value of the ROC curve in this model was 0.7, indicating that the model was reliable.
Six genes related to the LUAD microenvironment have a predictive prognostic value in LUAD.
建立并评估与肺腺癌（LUAD）微环境相关的生存风险评估模型，以确定 LUAD 的有效独立预后因素。
从 TCGA 数据库下载公共数据，使用 ESTIMATE 预测软件对免疫细胞和基质细胞进行评分，以预测肿瘤纯度。通过中位数将样本分为免疫评分（或基质评分）高分组和低分组。使用 Wilcoxon 检验进行差异分析。使用 R 包“clusterProfiler”对差异表达基因（DEGs）进行 GO 和 KEGG 富集分析。同时，对 DEGs 进行单因素和多因素回归分析，构建以基因表达水平为独立预后因素的多变量 Cox 风险回归模型，该模型影响肿瘤微环境（TME）和肿瘤免疫。
本研究发现，LUAD 患者中免疫细胞（基质细胞）浸润程度较高的患者预后较好，分期较早。功能富集分析表明，大多数 DEGs 与免疫细胞或基质细胞的增殖和激活有关。建立了一个由 6 个 TME 相关基因（CLEC17A、TAGAP、ABCC8、BCAN、FLT3 和 CCR2）组成的生存预测模型，最终证实了与 LUAD 预后密切相关的 6 个特征基因。该模型的 ROC 曲线 AUC 值为 0.7，表明该模型可靠。
与 LUAD 微环境相关的 6 个基因对 LUAD 具有预测预后价值。
