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开发和验证一种新型与表观遗传学相关的肺腺癌患者预后标志和候选药物。

Development and validation of a novel epigenetic-related prognostic signature and candidate drugs for patients with lung adenocarcinoma.

机构信息

Institute of Pathology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China.

Department of Pharmacy, Hiser Medical Center of Qingdao, Qingdao 266033, China.

出版信息

Aging (Albany NY). 2021 Jul 20;13(14):18701-18717. doi: 10.18632/aging.203315.

DOI:10.18632/aging.203315
PMID:34285141
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8351720/
Abstract

BACKGROUND

Epigenetic dysregulation has been increasingly proposed as a hallmark of cancer. Here, the aim of this study is to establish an epigenetic-related signature for predicting the prognosis of lung adenocarcinoma (LUAD) patients.

RESULTS

Five epigenetic-related genes (ERGs) (ARRB1, PARP1, PKM, TFDP1, and YWHAZ) were identified as prognostic hub genes and used to establish a prognostic signature. According our risk score system, LUAD patients were stratified into high and low risk groups, and patients in the high risk group had a worse prognosis. ROC analysis indicated that the signature was precise in predicting the prognosis. A new nomogram was constructed based on the five hub genes, which can predict the OS of every LUAD patients. The calibration curves showed that the nomogram had better accuracy in prediction. Finally, candidate drugs that aimed at hub ERGs were identified, which included 47 compounds.

CONCLUSIONS

Our epigenetic-related signature nomogram can effectively and reliably predict OS of LUAD patients, also we provide precise targeted chemotherapeutic drugs.

METHODS

The genomic data and clinical data of LUAD cohort were downloaded from the TCGA database and ERGs were obtained from the EpiFactors database. GSE31210 and GSE50081 microarray datasets were included as independent external datasets. Univariate Cox, LASSO regression, and multivariate Cox analyses were applied to construct the epigenetic-related signature.

摘要

背景

表观遗传失调已被越来越多地提出是癌症的一个标志。本研究旨在建立一个与表观遗传相关的特征，用于预测肺腺癌 (LUAD) 患者的预后。

结果

鉴定出五个与表观遗传相关的基因 (ERGs)（ARRB1、PARP1、PKM、TFDP1 和 YWHAZ）作为预后关键基因，并用于建立预后特征。根据我们的风险评分系统，将 LUAD 患者分为高风险组和低风险组，高风险组患者的预后较差。ROC 分析表明该特征可准确预测预后。基于五个关键基因构建了一个新的列线图，可以预测每位 LUAD 患者的 OS。校准曲线表明，该列线图在预测方面具有更好的准确性。最后，鉴定出针对关键 ERGs 的候选药物，包括 47 种化合物。

结论

我们的与表观遗传相关的特征列线图可以有效可靠地预测 LUAD 患者的 OS，并且为精准靶向化疗药物提供了依据。

方法

从 TCGA 数据库下载 LUAD 队列的基因组数据和临床数据，并从 EpiFactors 数据库获取 ERGs。包含 GSE31210 和 GSE50081 微阵列数据集作为独立的外部数据集。应用单因素 Cox、LASSO 回归和多因素 Cox 分析构建与表观遗传相关的特征。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/66e7/8351720/e744d8003802/aging-13-203315-g013.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/66e7/8351720/470476a5fcf1/aging-13-203315-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/66e7/8351720/cfe8a2b2b2cf/aging-13-203315-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/66e7/8351720/431b0df88fdf/aging-13-203315-g010.jpg
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