基于ceRNAs和免疫细胞的两种肺腺癌预测模型。

Two predicted models based on ceRNAs and immune cells in lung adenocarcinoma.

作者信息

Zhang Miaomiao, Zheng Peiyan, Wang Yuan, Sun Baoqing

机构信息

The First Affiliated Hospital of Guangzhou Medical University, Guangzhou Institute of Respiratory Diseases, State Key Laboratory of Respiratory Disease, Guangzhou, China.

Department of Allergy and Clinical Immunology, Guangzhou Institute of Respiratory health, State Key Laboratory of Respiratory Disease, National Clinical Research Center of Respiratory Disease, First Affiliated Hospital of Guangzhou Medical University, State Key Laboratory of Respiratory Disease, Guangzhou, China.

出版信息

PeerJ. 2021 Mar 23;9:e11029. doi: 10.7717/peerj.11029. eCollection 2021.

DOI:10.7717/peerj.11029

PMID:33828913

原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7996073/

Abstract

BACKGROUND

It is well accepted that both competitive endogenous RNAs (ceRNAs) and immune microenvironment exert crucial roles in the tumor prognosis. The present study aimed to find prognostic ceRNAs and immune cells in lung adenocarcinoma (LUAD).

MATERIALS AND METHODS

More specifically, we explored the associations of crucial ceRNAs with the immune microenvironment. The Cancer Genome Atlas (TCGA) database was employed to obtain expression profiles of ceRNAs and clinical data. CIBERSORT was utilized to quantify the proportion of 22 immune cells in LUAD.

RESULTS

We constructed two cox regression models based on crucial ceRNAs and immune cells to predict prognosis in LUAD. Subsequently, seven ceRNAs and seven immune cells were involved in prognostic models. We validated both predicted models via an independent cohort GSE72094. Interestingly, both predicted models proved that the longer patients were smoking, the higher risk scores would be obtained. We further investigated the relationships between seven genes and immune/stromal scores via the ESTIMATE algorithm. The results indicated that CDC14A and H1F0 expression were significantly related to stromal scores/immune scores in LUAD. Moreover, based on the result of the ceRNA model, single-sample gene set enrichment analysis (ssGSEA) suggested that differences in immune status were evident between high- and low-risk groups.

摘要

背景

竞争性内源性RNA（ceRNA）和免疫微环境在肿瘤预后中发挥关键作用，这一点已被广泛接受。本研究旨在寻找肺腺癌（LUAD）中的预后ceRNA和免疫细胞。

材料与方法

更具体地说，我们探讨了关键ceRNA与免疫微环境之间的关联。利用癌症基因组图谱（TCGA）数据库获取ceRNA的表达谱和临床数据。使用CIBERSORT量化LUAD中22种免疫细胞的比例。

结果

我们基于关键ceRNA和免疫细胞构建了两个cox回归模型，以预测LUAD的预后。随后，7种ceRNA和7种免疫细胞参与了预后模型。我们通过独立队列GSE72094验证了这两个预测模型。有趣的是，两个预测模型均证明患者吸烟时间越长，获得的风险评分越高。我们通过ESTIMATE算法进一步研究了7个基因与免疫/基质评分之间的关系。结果表明，CDC14A和H1F0的表达与LUAD中的基质评分/免疫评分显著相关。此外，基于ceRNA模型的结果，单样本基因集富集分析（ssGSEA）表明，高风险组和低风险组之间的免疫状态差异明显。