Wang Xiaofei, Xiao Zengtuan, Gong Jialin, Liu Zuo, Zhang Mengzhe, Zhang Zhenfa
Department of Lung Cancer Surgery, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China.
Transl Lung Cancer Res. 2021 Jan;10(1):167-182. doi: 10.21037/tlcr-20-822.
Accumulating evidence suggests that lymphocyte infiltration in the tumor microenvironment is positively correlated with tumorigenesis and development, while the role of Tregs (regulatory T cells) has been controversial. Therefore, we attempted to discover the possible value of Tregs for lung adenocarcinoma (LUAD).
The gene-sequencing data of LUAD were applied from three Gene Expression Omnibus (GEO) datasets-GSE10072, GSE32863 and GSE43458; the corresponding fractions of tumor-infiltrating immune cells were extracted from the CIBERSORTx portal. Weighted gene coexpression network analysis (WGCNA) and protein-protein interaction (PPI) network analysis were conducted to identify the significant module and candidate genes related to Tregs. The role of candidate genes in LUAD was further verified using data from The Cancer Genome Atlas (TCGA) database. Finally, we constructed a nomogram model to predict the prognosis of LUAD by plotting Kaplan-Meier (K-M), receiver operating characteristic (ROC) and calibration curves, which elucidated the performance of the nomogram.
In total, 10,047 genes in 333 samples (196 tumor and 137 normal samples) from the GEO database were included. By WGCNA and PPI analysis, we identified a significant black module and 36 candidate genes related to Treg. Next, the candidate genes were verified using TCGA data by Cox regression analysis to screen 13 hub genes that stratified LUAD patients into low- or high-risk groups. Low-risk patients showed a significantly longer overall survival (OS) than high-risk patients (3-year OS: 70.2% 35.2%; 5-year OS: 36.6% 0; P=1.651E-09), and the areas under the ROC curves (AUCs) showed good (3-year AUC: 0.733; 5-year AUC: 0.777). Next, we constructed a survival nomogram combining the hub genes and clinical parameters; the low-risk patients still showed a favorable prognosis compared with that of the high-risk patients (P=7.073E-13), and the AUCs were better (3-year AUC: 0.763; 5-year AUC: 0.873).
We revealed the role of immune-infiltrating Treg-related genes in LUAD and constructed a prognostic nomogram, which may help clinicians make optimal therapeutic decisions and help patients obtain better outcomes.
越来越多的证据表明,肿瘤微环境中的淋巴细胞浸润与肿瘤发生发展呈正相关,而调节性T细胞(Tregs)的作用一直存在争议。因此,我们试图探索Tregs在肺腺癌(LUAD)中的潜在价值。
应用来自三个基因表达综合数据库(GEO)——GSE10072、GSE32863和GSE43458的LUAD基因测序数据;从CIBERSORTx门户提取相应的肿瘤浸润免疫细胞分数。进行加权基因共表达网络分析(WGCNA)和蛋白质-蛋白质相互作用(PPI)网络分析,以识别与Tregs相关的显著模块和候选基因。使用来自癌症基因组图谱(TCGA)数据库的数据进一步验证候选基因在LUAD中的作用。最后,我们通过绘制Kaplan-Meier(K-M)曲线、受试者工作特征(ROC)曲线和校准曲线构建了一个列线图模型,以预测LUAD的预后,从而阐明列线图的性能。
总共纳入了来自GEO数据库的333个样本(196个肿瘤样本和137个正常样本)中的10,047个基因。通过WGCNA和PPI分析,我们确定了一个显著的黑色模块和36个与Treg相关的候选基因。接下来,通过Cox回归分析使用TCGA数据对候选基因进行验证,以筛选出13个将LUAD患者分为低风险或高风险组的核心基因。低风险患者的总生存期(OS)明显长于高风险患者(3年OS:70.2%对35.2%;5年OS:36.6%对0;P = 1.651E - 09),ROC曲线下面积(AUC)显示良好(3年AUC:0.733;5年AUC:0.777)。接下来,我们构建了一个结合核心基因和临床参数的生存列线图;与高风险患者相比,低风险患者仍显示出良好的预后(P = 7.073E - 13),AUC更好(3年AUC:0.763;5年AUC:0.873)。
我们揭示了免疫浸润的Treg相关基因在LUAD中的作用,并构建了一个预后列线图,这可能有助于临床医生做出最佳治疗决策,并帮助患者获得更好的结果。