Open AccessPrognostic value of ferroptosis‐related genes in patients with lung adenocarcinoma
Author(s) -
Zhu Guangsheng,
Huang Hua,
Xu Songlin,
Shi Ruifeng,
Gao Zhouyong,
Lei Xi,
Zhu Shuai,
Zhou Ning,
Zu Lingling,
Mello Ramon A. De,
Chen Jun,
Xu Song
Publication year - 2021
Publication title -
thoracic cancer
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.823
H-Index - 28
eISSN - 1759-7714
pISSN - 1759-7706
DOI - 10.1111/1759-7714.13998
Subject(s) - medicine , adenocarcinoma , value (mathematics) , gene , lung , oncology , bioinformatics , genetics , cancer , machine learning , computer science , biology
Background The prevalence of lung adenocarcinomas (LUADs) has dramatically increased in recent decades. Ferroptosis is a process of iron‐dependent regulatory cell death. It is still unclear whether the expression of ferroptosis‐related genes (FRGs) is involved in the pathogenesis and survival of patients with LUAD. Methods We retrieved LUAD data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases and used LASSO Cox regression analysis to select the gene signature suitable for modeling. The risk score was calculated according to the model, and the patients were divided into high‐ and low‐risk groups according to the median risk score. Functional enrichment analysis was carried out by this group, and a model for predicting clinical prognosis was established by combining this group with clinical factors. Results Gene set enrichment analysis (GSEA) and single‐sample gene set enrichment analysis (ssGSEA) analysis showed that there were several immune‐related pathways and immune infiltration differences between high‐ and low‐risk groups. A prognostic model integrating 10 ferroptosis‐related genes (FR‐DEGs), and clinical factors were constructed and validated in an external cohort. Conclusions The FR‐DEGs signature was related to immune infiltration, and a model based on FR‐DEGs and clinical factors was established to predict the prognosis of patients with LUAD.