Du Minjun, Liang Yicheng, Liu Zixu, Li Xingkai, Liang Mei, Zhou Boxuan, Gao Yushun
Department of Thoracic Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Front Oncol. 2021 Sep 28;11:693353. doi: 10.3389/fonc.2021.693353. eCollection 2021.
CD8+ T cells are one of the central effector cells in the immune microenvironment. CD8+ T cells play a vital role in the development and progression of lung adenocarcinoma (LUAD). This study aimed to explore the key genes related to CD8+ T-cell infiltration in LUAD and to develop a novel prognosis model based on these genes.
With the use of the LUAD dataset from The Cancer Genome Atlas (TCGA), the differentially expressed genes (DEGs) were analyzed, and a co-expression network was constructed by weighted gene co-expression network analysis (WGCNA). Combined with the CIBERSORT algorithm, the gene module in WGCNA, which was the most significantly correlated with CD8+ T cells, was selected for the subsequent analyses. Key genes were then identified by co-expression network analysis, protein-protein interactions network analysis, and least absolute shrinkage and selection operator (Lasso)-penalized Cox regression analysis. A risk assessment model was built based on these key genes and then validated by the dataset from the Gene Expression Omnibus (GEO) database and multiple fluorescence hybridization experiments of a tissue microarray.
Five key genes (MZT2A, ALG3, ATIC, GPI, and GAPDH) related to prognosis and CD8+ T-cell infiltration were identified, and a risk assessment model was established based on them. We found that the risk score could well predict the prognosis of LUAD, and the risk score was negatively related to CD8+ T-cell infiltration and correlated with the advanced tumor stage. The results of the GEO database and tissue microarray were consistent with those of TCGA. Furthermore, the risk score was higher significantly in tumor tissues than in adjacent lung tissues and was correlated with the advanced tumor stage.
This study may provide a novel risk assessment model for prognosis prediction and a new perspective to explore the mechanism of tumor immune microenvironment related to CD8+ T-cell infiltration in LUAD.
CD8 + T细胞是免疫微环境中的核心效应细胞之一。CD8 + T细胞在肺腺癌(LUAD)的发生发展中起着至关重要的作用。本研究旨在探索与LUAD中CD8 + T细胞浸润相关的关键基因,并基于这些基因建立一种新的预后模型。
利用来自癌症基因组图谱(TCGA)的LUAD数据集,分析差异表达基因(DEG),并通过加权基因共表达网络分析(WGCNA)构建共表达网络。结合CIBERSORT算法,选择WGCNA中与CD8 + T细胞相关性最显著的基因模块进行后续分析。然后通过共表达网络分析、蛋白质-蛋白质相互作用网络分析和最小绝对收缩和选择算子(Lasso)惩罚的Cox回归分析来鉴定关键基因。基于这些关键基因建立风险评估模型,然后通过来自基因表达综合数据库(GEO)的数据和组织芯片的多重荧光杂交实验进行验证。
鉴定出五个与预后和CD8 + T细胞浸润相关的关键基因(MZT2A、ALG3、ATIC、GPI和GAPDH),并基于它们建立了风险评估模型。我们发现风险评分能够很好地预测LUAD的预后,且风险评分与CD8 + T细胞浸润呈负相关,并与肿瘤晚期相关。GEO数据库和组织芯片的结果与TCGA的结果一致。此外,肿瘤组织中的风险评分显著高于相邻肺组织,且与肿瘤晚期相关。
本研究可能为预后预测提供一种新的风险评估模型,并为探索LUAD中与CD8 + T细胞浸润相关的肿瘤免疫微环境机制提供新的视角。