Xia QL, He XM, Ma Y, Li QY, Du YZ, Wang J. 5-mRNA-based prognostic signature of survival in lung adenocarcinoma. World J Clin Oncol 2023; 14(1): 27-39 [PMID: 36699627 DOI: 10.5306/wjco.v14.i1.27]
Corresponding Author of This Article
Jin Wang, PhD, Professor, Scientific Research Center, Shanghai Public Health Clinical Center, Fudan University, No 2901 Caolang Road, Jinshan District, Shanghai 201508, China. wjincityu@yahoo.com
Research Domain of This Article
Oncology
Article-Type of This Article
Basic 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/
World J Clin Oncol. Jan 24, 2023; 14(1): 27-39 Published online Jan 24, 2023. doi: 10.5306/wjco.v14.i1.27
5-mRNA-based prognostic signature of survival in lung adenocarcinoma
Qian-Lin Xia, Xiao-Meng He, Yan Ma, Qiu-Yue Li, Yu-Zhen Du, Jin Wang
Qian-Lin Xia, Yu-Zhen Du, Laboratory Medicine, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai 200233, China
Xiao-Meng He, Yan Ma, Qiu-Yue Li, Jin Wang, Scientific Research Center, Shanghai Public Health Clinical Center, Fudan University, Shanghai 201508, China
Author contributions: Wang J, Du YZ, and Xia QL conceived and designed the experiments; Xia QL, He XM and Ma Y analyzed the data; Li QY contributed to analysis tools; Xia QL wrote the manuscript; Wang J and Xia QL revised the manuscript; all authors have read and approved the final manuscript.
Supported bythe Science and Technology Development Fund of the Pudong New Area, No. PKJ2021-Y53; and the National Natural Science Foundation of China, No. 81974315.
Institutional review board statement: The study was reviewed and approved by the Shanghai Public Health Clinical Center Laboratory Animal Welfare & Ethics Committee Institutional Review Board [(Approval No. 2020-A006-01]).
Conflict-of-interest statement: All the authors declare no competing financial interests.
Data sharing statement: The mRNA expression and clinical data of lung adenocarcinoma analyzed during the current study are available on the GEO (https://www.ncbi.nlm.nih.gov/geo/) and TCGA databases (https://www.cbioportal.org/). The protein expression of model-related genes of LUAD analyzed in this study is also available on the THPA database (http://www.proteinatlas.org).
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: Jin Wang, PhD, Professor, Scientific Research Center, Shanghai Public Health Clinical Center, Fudan University, No 2901 Caolang Road, Jinshan District, Shanghai 201508, China. wjincityu@yahoo.com
Received: October 5, 2022 Peer-review started: October 5, 2022 First decision: October 24, 2022 Revised: November 2, 2022 Accepted: December 13, 2022 Article in press: December 13, 2022 Published online: January 24, 2023 Processing time: 97 Days and 3.4 Hours
ARTICLE HIGHLIGHTS
Research background
Lung adenocarcinoma patients with localized or locally advanced disease have a high risk of death, and their 5-year overall survival rate is less than 15%.
Research motivation
To evaluate the prognosis of Lung adenocarcinoma (LUAD) patients and optimize treatment, effective clinical research prediction models.
Research objectives
To identify reliable prognostic biomarkers to predict clinical outcomes and to help clinicians to make accurate clinical treatment decisions.
Research methods
The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) were used to screen for differential genes for lung adenocarcinoma. Univariate regression analysis combined with LASSO regression analysis was used to screen for prognostic-related genes. Multivariate Cox regression analysis was applied to establish the risk score equation and construct the survival prognosis model.
Research results
We establish a prognostic risk model for lung adenocarcinoma based on 5 mRNAs (TCN1, CENPF, MAOB, CRTAC1, and PLEK2). These five new genes were significantly correlated with the prognosis of LUAD patients. To improve the prognostic predictive power of the five prognostic gene markers, a predictive nomogram combining risk scores and conventional clinical prognostic parameters (including age and tumor stage) was constructed to enable clinicians to determine the prognosis of each patient.
Research conclusions
A 5-mRNA-based model was constructed to predict the prognosis of lung adenocarcinoma, which may provide clinicians with reliable prognostic assessment tools and help clinical treatment decisions.
Research perspectives
Our study identified a 5-gene model and constructed a nomogram which may have important implications for clinical medical decision and personalized treatment of patients with lung adenocarcinoma.
