Evidence map›Paper›PMID 36159424›Full record

ArticleWorld journal of clinical cases2022

Development and validation of an epithelial-mesenchymal transition-related gene signature for predicting prognosis.

De-Hua Zhou, Qian-Cheng Du, Zheng Fu, Xin-Yu Wang, Ling Zhou, Jian Wang, Cheng-Kai Hu, Shun Liu, Jun-Min Li, Meng-Li Ma and 1 more

Abstract read
In one paragraph

Article in World journal of clinical cases, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

11 authors.

De-Hua ZhouDepartment of General Surgery, Shanghai Fourth People's Hospital, School of Medicine, Tongji University, Shanghai 200434, China.
Qian-Cheng DuDepartment of Thoracic surgery, Shanghai Xuhui Central Hospital, Shanghai 200031, China.
Zheng FuDepartment of Thoracic surgery, Shanghai Xuhui Central Hospital, Shanghai 200031, China.
Xin-Yu WangDepartment of General Surgery, Shanghai Fourth People's Hospital, School of Medicine, Tongji University, Shanghai 200434, China.
Ling ZhouDepartment of General Surgery, Shanghai Fourth People's Hospital, School of Medicine, Tongji University, Shanghai 200434, China.
Jian WangDepartment of Thoracic surgery, Shanghai Xuhui Central Hospital, Shanghai 200031, China.
Cheng-Kai HuDepartment of Thoracic surgery, Shanghai Xuhui Central Hospital, Shanghai 200031, China.
Shun LiuDepartment of Thoracic surgery, Shanghai Xuhui Central Hospital, Shanghai 200031, China.
Jun-Min LiSurgical Intensive Care Unit, Shanghai Xuhui Central Hospital, Shanghai 200031, China.
Meng-Li MaSurgical Intensive Care Unit, Shanghai Xuhui Central Hospital, Shanghai 200031, China.
Hua YuDepartment of General Surgery, Shanghai Fourth People's Hospital, School of Medicine, Tongji University, Shanghai 200434, China. luckyyuhua@163.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCurrently, there are many therapeutic methods for lung adenocarcinoma (LUAD), but the 5-year survival rate is still only 15% at later stages. Epithelial- mesenchymal transition (EMT) has been shown to be closely associated with local dissemination and subsequent metastasis of solid tumors. However, the role of EMT in the occurrence and development of LUAD remains unclear.

aimTo further elucidate the value of EMT-related genes in LUAD prognosis.

methodsUnivariate, least absolute shrinkage and selection operator, and multivariate Cox regression analyses were applied to establish and validate a new EMT-related gene signature for predicting LUAD prognosis. The risk model was evaluated by Kaplan-Meier survival analysis, principal component analysis, and functional enrichment analysis and was used for nomogram construction. The potential structures of drugs to which LUAD is sensitive were discussed with respect to EMT-related genes in this model.

resultsThirty-three differentially expressed genes related to EMT were found to be highly associated with overall survival (OS) by using univariate Cox regression analysis (log2FC ≥ 1, false discovery rate < 0.001). A prognostic signature of 7 EMT-associated genes was developed to divide patients into two risk groups by high or low risk scores. Kaplan-Meier survival analysis showed that the OS of patients in the high-risk group was significantly poorer than that of patients in the low-risk group (

conclusionThe EMT-associated gene signature classifier could be used as a feasible indicator for predicting OS.

Indexed as

Epithelial–mesenchymal transitionGene signatureLung adenocarcinomaOverall survival

Identifiers

PMID36159424
PMCPMC9477694

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