高级检索
当前位置: 首页 > 详情页

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

| 认领 | 导出 |

文献详情

资源类型:
WOS体系:
Pubmed体系:

收录情况: ◇ SCIE ◇ 预警期刊

单位: [1]Huazhong Univ Sci & Technol,Tongji Hosp,Tongji Med Coll,Inst Pathol,Wuhan 430030,Peoples R China [2]Hiser Med Ctr Qingdao, Dept Pharm, Qingdao 266033, Peoples R China [3]Wuhan Univ, Tongren Hosp, Wuhan Hosp 3, Dept Pathol, Wuhan 430030, Peoples R China
出处:
ISSN:

关键词: lung adenocarcinoma epigenetic-related genes drugs prognostic TCGA

摘要:
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.

基金:
语种:
被引次数:
WOS:
PubmedID:
中科院(CAS)分区:
出版当年[2020]版:
大类 | 2 区 医学
小类 | 1 区 老年医学 3 区 细胞生物学
最新[2025]版:
JCR分区:
出版当年[2019]版:
Q1 GERIATRICS & GERONTOLOGY Q2 CELL BIOLOGY
最新[2023]版:
Q2 CELL BIOLOGY Q2 GERIATRICS & GERONTOLOGY

影响因子: 最新[2023版] 最新五年平均 出版当年[2019版] 出版当年五年平均 出版前一年[2018版] 出版后一年[2020版]

第一作者:
第一作者单位: [1]Huazhong Univ Sci & Technol,Tongji Hosp,Tongji Med Coll,Inst Pathol,Wuhan 430030,Peoples R China
通讯作者:
推荐引用方式(GB/T 7714):
APA:
MLA:

资源点击量:434 今日访问量:0 总访问量:419 更新日期:2025-05-01 建议使用谷歌、火狐浏览器 常见问题

版权所有:重庆聚合科技有限公司 渝ICP备12007440号-3 地址:重庆市两江新区泰山大道西段8号坤恩国际商务中心16层(401121)