Research Paper Volume 13, Issue 12 pp 16144—16164

A novel ferroptosis-related gene signature for prognostic prediction of patients with lung adenocarcinoma

Jingjing Jin1, *, , Chuan Liu2, *, , Shanshan Yu3, *, , Lingyi Cai1, , Andriamifahimanjaka Sitrakiniaina1, , Ruihong Gu1, , Wenfeng Li3, , Fangfang Wu4, , Xiangyang Xue1, ,

  • 1 Department of Microbiology and Immunology, Institute of Molecular Virology and Immunology, School of Basic Medical Sciences, Wenzhou Medical University, Wenzhou, China
  • 2 China Medical University, Shenyang, China
  • 3 Department of Chemoradiation Oncology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, China
  • 4 Department of Emergency, The Second Affiliated Hospital and Yuying Children’s Hospital, Wenzhou Medical University, Wenzhou, China
* Equal contribution

Received: January 16, 2021       Accepted: May 14, 2021       Published: June 11, 2021
How to Cite

Copyright: © 2021 Jin 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.


Background: Lung adenocarcinoma (LUAD) is a heterogeneous disease characterized by high mortality and poor prognosis. Ferroptosis, a newly discovered iron-dependent type of cell death, has been found to play a crucial role in the development of cancers. However, little is known about the prognostic value of ferroptosis-related genes (FRGs) in LUAD.

Methods: In the present study, RNA-seq transcriptome data of LUAD patients were obtained from The Cancer Genome Atlas (TCGA) database. Cox regression analysis was used to construct a multigene signature. Kaplan–Meier survival and receiver operating characteristic (ROC) curves were utilized to assess the prognostic prediction efficiency of the constructed survival model. LUAD patients from the GSE30219 dataset were used for validation.

Results: We found 46 differentially expressed FRGs between LUAD and adjacent normal tissues. Via univariate and multivariate Cox regression analyses, 5 differentially expressed FRGs were identified as being highly correlated with LUAD. Patients were divided into low- and high-risk groups according to the risk score. We found that the overall survival (OS) of patients in the high-risk group was significantly worse than that of their low-risk counterparts. (P < 0.0001 in the TCGA dataset and P = 0.044 in the GSE30219 cohort). In addition, gene set variation analysis (GSVA) of the tumor microenvironment of the two groups may explain the different survival of LUAD patients.

Conclusions: Our study identified a novel FRG signature that could be used to evaluate and predict the prognosis of LUAD patients, which might provide a new therapeutic target for the treatment of LUAD patients.


FRGs: ferroptosis-related genes; LUAD: lung adenocarcinoma; TCGA: The Cancer Genome Atlas; TME: tumor microenvironment.