Zhou DH, Du QC, Fu Z, Wang XY, Zhou L, Wang J, Hu CK, Liu S, Li JM, Ma ML, Yu H. Development and validation of an epithelial–mesenchymal transition-related gene signature for predicting prognosis. World J Clin Cases 2022; 10(26): 9285-9302 [PMID: 36159424 DOI: 10.12998/wjcc.v10.i26.9285]
Corresponding Author of This Article
Hua Yu, MM, Associate Chief Physician, Department of General Surgery, Shanghai Fourth People’s Hospital, School of Medicine, Tongji University, No. 1279 Sanmen Road, Shanghai 200434, China. luckyyuhua@163.com
Research Domain of This Article
Respiratory System
Article-Type of This Article
Retrospective Study
Open-Access Policy of This Article
This article is an open-access article which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/
De-Hua Zhou, Xin-Yu Wang, Ling Zhou, Hua Yu, Department of General Surgery, Shanghai Fourth People’s Hospital, School of Medicine, Tongji University, Shanghai 200434, China
Qian-Cheng Du, Zheng Fu, Jian Wang, Cheng-Kai Hu, Shun Liu, Department of Thoracic surgery, Shanghai Xuhui Central Hospital, Shanghai 200031, China
Jun-Min Li, Meng-Li Ma, Surgical Intensive Care Unit, Shanghai Xuhui Central Hospital, Shanghai 200031, China
Author contributions: Zhou DH and Du QC analyzed the data and wrote the manuscript, and both contributed equally to this work; Yu H designed the study; Wang XY, Fu Z, Zhou L, Wang J, Hu CK, Liu S, Li JM and Ma ML collected the data and revised the paper. All authors have read and approved the final manuscript.
Institutional review board statement: The data for the study came from public databases and did not involve blood or tissue samples from humans or animals. Therefore, there were no ethical issues involved in this study.
Conflict-of-interest statement: The authors declare no conflicts of interest.
Data sharing statement: No additional data are available.
Open-Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: https://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Hua Yu, MM, Associate Chief Physician, Department of General Surgery, Shanghai Fourth People’s Hospital, School of Medicine, Tongji University, No. 1279 Sanmen Road, Shanghai 200434, China. luckyyuhua@163.com
Received: April 2, 2022 Peer-review started: April 2, 2022 First decision: June 16, 2022 Revised: June 30, 2022 Accepted: July 20, 2022 Article in press: July 20, 2022 Published online: September 16, 2022 Processing time: 152 Days and 14.5 Hours
ARTICLE HIGHLIGHTS
Research background
The transformation between epithelial and stromal cells during cancer progression is important in cancer progression. Understanding the relationship between epithelial-mesenchymal transition (EMT)-related genes and lung adenocarcinoma is valuable for improving its prognosis.
Research motivation
To develop an EMT-related gene signature to predict the prognosis of lung adenocarcinoma.
Research objectives
To construct and validate prognostic polygenic signatures of differentially expressed genes associated with EMT.
Research methods
We constructed a prognostic model based on differentially expressed EMT-related genes from 445 lung adenocarcinoma samples and validated its feasibility with another 439 Lung adenocarcinoma samples.
Research results
Seven EMT-related prognostic gene signatures were developed and validated. Kaplan–Meier survival analysis showed that the overall survival of patients in the high-risk group was statistically significantly poorer than that of patients in the low-risk group. The risk score based on EMT-associated genes was an independent risk factor for overall survival.
Research conclusions
The EMT-related gene signature could be used as a feasible indicator to predict the overall survival of lung adenocarcinoma patients. The molecular structures of potential therapeutic agents associated with EMT genes that could be used to treat lung adenocarcinoma were identified.
Research perspectives
More accurate genetic markers and models are needed to predict prognosis because of the low survival rate of lung adenocarcinoma.
