Duan Jin, Lei Youming, Lv Guoli, Liu Yinqiang, Zhao Wei, Yang Qingmei, Su Xiaona, Song Zhijian, Lu Leilei, Shi Yunfei
Department of Geriatric Thoracic Surgery, The First Hospital of Kunming Medical University, Kunming City, Yunnan Province, P.R. China.
Department of Cancer Center, Daping Hospital, Army Medical University, Chongqing, China.
PeerJ. 2021 Apr 21;9:e11074. doi: 10.7717/peerj.11074. eCollection 2021.
Lung adenocarcinoma (LUAD) is the most commonhistological lung cancer subtype, with an overall five-year survivalrate of only 17%. In this study, we aimed to identify autophagy-related genes (ARGs) and develop an LUAD prognostic signature.
In this study, we obtained ARGs from three databases and downloaded gene expression profiles from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database. We used TCGA-LUAD ( = 490) for a training and testing dataset, and GSE50081 ( = 127) as the external validation dataset.The least absolute shrinkage and selection operator (LASSO) Cox and multivariate Cox regression models were used to generate an autophagy-related signature. We performed gene set enrichment analysis (GSEA) and immune cell analysis between the high- and low-risk groups. A nomogram was built to guide the individual treatment for LUAD patients.
We identified a total of 83 differentially expressed ARGs (DEARGs) from the TCGA-LUAD dataset, including 33 upregulated DEARGs and 50 downregulated DEARGs, both with thresholds of adjusted < 0.05 and |Fold change| > 1.5. Using LASSO and multivariate Cox regression analyses, we identified 10 ARGs that we used to build a prognostic signature with areas under the curve (AUCs) of 0.705, 0.715, and 0.778 at 1, 3, and 5 years, respectively. Using the risk score formula, the LUAD patients were divided into low- or high-risk groups. Our GSEA results suggested that the low-risk group were enriched in metabolism and immune-related pathways, while the high-risk group was involved in tumorigenesis and tumor progression pathways. Immune cell analysis revealed that, when compared to the high-risk group, the low-risk group had a lower cell fraction of M0- and M1- macrophages, and higher CD4 and PD-L1 expression levels.
Our identified robust signature may provide novel insight into underlying autophagy mechanisms as well as therapeutic strategies for LUAD treatment.
肺腺癌（LUAD）是最常见的组织学肺癌亚型，总体五年生存率仅为17%。在本研究中，我们旨在鉴定自噬相关基因（ARGs）并开发一种LUAD预后特征。
在本研究中，我们从三个数据库中获取ARGs，并从癌症基因组图谱（TCGA）和基因表达综合数据库（GEO）下载基因表达谱。我们使用TCGA-LUAD（n = 490）作为训练和测试数据集，并使用GSE50081（n = 127）作为外部验证数据集。使用最小绝对收缩和选择算子（LASSO）Cox模型和多变量Cox回归模型生成自噬相关特征。我们在高风险组和低风险组之间进行了基因集富集分析（GSEA）和免疫细胞分析。构建了一个列线图以指导LUAD患者的个体化治疗。
我们从TCGA-LUAD数据集中共鉴定出83个差异表达的ARGs（DEARGs），包括33个上调的DEARGs和50个下调的DEARGs，两者的校正P< 0.05且|倍变化|> 1.5为阈值。使用LASSO和多变量Cox回归分析，我们鉴定出10个ARGs，用于构建预后特征，其1年、3年和5年的曲线下面积（AUC）分别为0.705、0.715和0.778。使用风险评分公式，将LUAD患者分为低风险组或高风险组。我们的GSEA结果表明，低风险组在代谢和免疫相关途径中富集，而高风险组参与肿瘤发生和肿瘤进展途径。免疫细胞分析显示，与高风险组相比，低风险组的M0和M1巨噬细胞比例较低，CD4和PD-L1表达水平较高。
我们鉴定出的稳健特征可能为LUAD治疗的潜在自噬机制以及治疗策略提供新的见解。
