Research Paper Volume 13, Issue 1 pp 794—812

Systematic construction and validation of an epithelial–mesenchymal transition risk model to predict prognosis of lung adenocarcinoma

Yunliang Tang1,2, *, , Yanxia Jiang3, *, , Cheng Qing1, , Jiao Wang3, , Zhenguo Zeng1, ,

  • 1 Department of Critical Care Medicine, First Affiliated Hospital of Nanchang University, Nanchang 330006, Jiangxi, China
  • 2 Department of Rehabilitation Medicine, First Affiliated Hospital of Nanchang University, Nanchang 330006, Jiangxi, China
  • 3 Department of Endocrinology and Metabolism, First Affiliated Hospital of Nanchang University, Nanchang 330006, Jiangxi, China
* Equal contribution

Received: July 29, 2020       Accepted: October 5, 2020       Published: December 3, 2020
How to Cite

Copyright: © 2020 Tang et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.


Epithelial–mesenchymal transition (EMT) has been shown to be linked to a poor prognosis, particularly in patients with non-small-cell lung cancer. Nevertheless, little is known regarding the existence of EMT-related gene signatures and their prognostic values in lung adenocarcinoma (LUAD). In the current study, we systematically profiled the mRNA expression data of patients with LUAD in The Cancer Genome Atlas and Gene Expression Omnibus databases using a total of 1,184 EMT-related genes. The prognostic values of the EMT-related genes used to develop risk score models for overall survival were determined using LASSO and Cox regression analyses. A prognostic signature that consisted of nine unique EMT-related genes was generated using a training set. A nomogram, incorporating this EMT-related gene signature and clinical features of patients with LUAD, was constructed for potential clinical use. Calibration plots, decision-making curves, and receiver operating characteristic curve analysis showed that this model had a good ability to predict the survival of patients with LUAD. The EMT-associated gene signature and prognostic nomogram established in this study were reliable in predicting the survival of patients with LUAD. Thus, we first identified a novel EMT-related gene signature and developed a nomogram for predicting the prognosis of patients with LUAD.


ADM: adrenomedullin; ALK: anaplastic lymphoma kinase; AUC: area under the curve; CDH2: cadherin 2; CI: confidence interval; CTSL: cathepsin L; DCA: decision curve analysis; EGFR: epidermal growth factor receptor; EMT: epithelial–mesenchymal transition; ERG: epithelial–mesenchymal transition-related gene; FSCN1: fascin-1; FUT4: fucosyltransferase 4; GEO: Gene Expression Omnibus; GO: Gene Ontology; GSEA: gene set enrichment analysis; GSVA: gene set variation analysis; HPA: Human Protein Atlas; HR: hazard ratio; ITGB1: integrin beta-1; KEGG: Kyoto Encyclopedia of Genes and Genomes; KRAS: Kirsten rat sarcoma viral oncogene homolog; LGR4: leucine-rich repeat-containing G-protein-coupled receptor 4; LUAD: lung adenocarcinoma; NK: natural killer; NSCLC: non-small-cell lung cancer; OS: overall survival; RFS: relapse-free survival; ROC: receiver operating characteristic; TCGA: The Cancer Genome Atlas.