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;
10:9285-9302. [PMID:
36159424 PMCID:
PMC9477694 DOI:
10.12998/wjcc.v10.i26.9285]
[Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/02/2022] [Revised: 06/30/2022] [Accepted: 07/22/2022] [Indexed: 02/05/2023] Open
Abstract
BACKGROUND
Currently, 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.
AIM
To further elucidate the value of EMT-related genes in LUAD prognosis.
METHODS
Univariate, 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.
RESULTS
Thirty-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 (P < 0.05). Multivariate Cox regression analysis showed that the risk score was an independent risk factor for OS (HR > 1, P < 0.05). The results of receiver operator characteristic curve analysis suggested that the 7-gene signature had a perfect ability to predict prognosis (all area under the curves > 0.5).
CONCLUSION
The EMT-associated gene signature classifier could be used as a feasible indicator for predicting OS.
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