Identification the ferroptosis-related gene signature in patients with esophageal adenocarcinoma

Abstract

Background Ferroptosis is a recently recognized non-apoptotic cell death that is distinct from the apoptosis, necroptosis and pyroptosis. Considerable studies have demonstrated ferroptosis is involved in the biological process of various cancers. However, the role of ferroptosis in esophageal adenocarcinoma (EAC) remains unclear. This study aims to explore the ferroptosis-related genes (FRG) expression profiles and their prognostic values in EAC. Methods The FRG data and clinical information were downloaded from The Cancer Genome Atlas (TCGA) database. Univariate and multivariate cox regressions were used to identify the prognostic FRG, and the predictive ROC model was established using the independent risk factors. GO and KEGG enrichment analyses were performed to investigate the bioinformatics functions of significantly different genes (SDG) of ferroptosis. Additionally, the correlations of ferroptosis and immune cells were assessed through the single-sample gene set enrichment analysis (ssGSEA) and TIMER database. Finally, SDG were verified in clinical EAC specimens and normal esophageal mucosal tissues. Results Twenty-eight significantly different FRG were screened from 78 EAC and 9 normal tissues. Enrichment analyses showed these SDG were mainly related to the iron-related pathways and metabolisms of ferroptosis. Gene network demonstrated the TP53, G6PD, NFE2L2 and PTGS2 were the hub genes in the biology of ferroptosis. Cox regression analyses demonstrated four FRG (CARS1, GCLM, GLS2 and EMC2) had prognostic values for overall survival (OS) (all P < 0.05). ROC curve showed better predictive ability using the risk score (AUC = 0.744). Immune cell enrichment analysis demonstrated that the types of immune cells and their expression levels in the high-risk group were significant different with those in the low-risk group (all P < 0.05). The experimental results confirmed the ALOX5, NOX1 were upregulated and the MT1G was downregulated in the EAC tissues compared with the normal esophageal mucosal tissues (all P < 0.05). Conclusions We identified differently expressed ferroptosis-related genes that may involve in EAC. These genes have significant values in predicting the patients’ OS and targeting ferroptosis may be an alternative for therapy. Further studies are necessary to verify these results of our study.

A New Prognostic Risk Signature of Eight Ferroptosis-Related Genes in the Clear Cell Renal Cell Carcinoma

“…Recently, the prognosis prediction potential of FRGs has been explored in many human cancers. For example, Zhu et al demonstrated the utility of a 4-FRGs model in predicting the prognosis of esophageal adenocarcinoma (38). Zheng et al developed a 12-FRGs model to better predict the prognosis of patients with lower-grade gliomas (39).…”

Identification of a Novel Ferroptosis-Related Gene Prognostic Signature in Bladder Cancer

“…They also generated a genomic–clinicopathological nomogram integrating age, stage, and risk scores and demonstrated high predictive accuracy. Zhu et al ( 22 ) constructed the predictive model composed of four FRGs in esophageal adenocarcinoma, which had good predictive ability (AUC = 0.744). Furthermore, they performed the polymerase chain reaction and IHC validation in clinical specimens to verify significantly different genes expression profiles in esophageal adenocarcinoma and normal tissues.…”

Identification of the Novel Pyroptosis-Related Gene Signature in Patients with Esophageal Adenocarcinoma

“…As indicated by the ROC curves, the nomogram demonstrates high predictive accuracy and sensitivity, especially for the prediction of 5-year survival. Compared to the conventional TNM staging and previously developed ferroptosis-related gene-signature in EAC 44 , the pyroptosis-related gene signature-based nomogram, which integrates gene expression profiles and clinical parameters, more effectively predicts the prognosis of EAC patients. The use of nomogram based on integrated information can facilitate the prediction of prognosis, clinical decision-making and patient counseling 45 .…”