Identification and validation of a novel ferroptosis-related gene model for predicting the prognosis of gastric cancer patients.

<h4>Background</h4>Ferroptosis is a novel form of regulated cell death that plays a critical role in tumorigenesis. The purpose of this study was to establish a ferroptosis-associated gene (FRG) signature and assess its clinical outcome in gastric cancer (GC).<h4>Methods</h4>...

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Autores principales:	Gang Liu, Jian-Ying Ma, Gang Hu, Huan Jin
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/ea840b19598643fcbaa6912de2f53c53
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spelling	oai:doaj.org-article:ea840b19598643fcbaa6912de2f53c532021-12-02T20:09:15ZIdentification and validation of a novel ferroptosis-related gene model for predicting the prognosis of gastric cancer patients.1932-620310.1371/journal.pone.0254368https://doaj.org/article/ea840b19598643fcbaa6912de2f53c532021-01-01T00:00:00Zhttps://doi.org/10.1371/journal.pone.0254368https://doaj.org/toc/1932-6203<h4>Background</h4>Ferroptosis is a novel form of regulated cell death that plays a critical role in tumorigenesis. The purpose of this study was to establish a ferroptosis-associated gene (FRG) signature and assess its clinical outcome in gastric cancer (GC).<h4>Methods</h4>Differentially expressed FRGs were identified using gene expression profiles from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database. Univariate and least absolute shrinkage and selection operator (LASSO) Cox regression analyses were performed to construct a prognostic signature. The model was validated using an independent GEO dataset, and a genomic-clinicopathologic nomogram integrating risk scores and clinicopathological features was established.<h4>Results</h4>An 8-FRG signature was constructed to calculate the risk score and classify GC patients into two risk groups (high- and low-risk) according to the median value of the risk score. The signature showed a robust predictive capacity in the stratification analysis. A high-risk score was associated with advanced clinicopathological features and an unfavorable prognosis. The predictive accuracy of the signature was confirmed using an independent GSE84437 dataset. Patients in the two groups showed different enrichment of immune cells and immune-related pathways. Finally, we established a genomic-clinicopathologic nomogram (based on risk score, age, and tumor stage) to predict the overall survival (OS) of GC patients.<h4>Conclusions</h4>The novel FRG signature may be a reliable tool for assisting clinicians in predicting the OS of GC patients and may facilitate personalized treatment.Gang LiuJian-Ying MaGang HuHuan JinPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 16, Iss 7, p e0254368 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Gang Liu Jian-Ying Ma Gang Hu Huan Jin Identification and validation of a novel ferroptosis-related gene model for predicting the prognosis of gastric cancer patients.
description	<h4>Background</h4>Ferroptosis is a novel form of regulated cell death that plays a critical role in tumorigenesis. The purpose of this study was to establish a ferroptosis-associated gene (FRG) signature and assess its clinical outcome in gastric cancer (GC).<h4>Methods</h4>Differentially expressed FRGs were identified using gene expression profiles from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database. Univariate and least absolute shrinkage and selection operator (LASSO) Cox regression analyses were performed to construct a prognostic signature. The model was validated using an independent GEO dataset, and a genomic-clinicopathologic nomogram integrating risk scores and clinicopathological features was established.<h4>Results</h4>An 8-FRG signature was constructed to calculate the risk score and classify GC patients into two risk groups (high- and low-risk) according to the median value of the risk score. The signature showed a robust predictive capacity in the stratification analysis. A high-risk score was associated with advanced clinicopathological features and an unfavorable prognosis. The predictive accuracy of the signature was confirmed using an independent GSE84437 dataset. Patients in the two groups showed different enrichment of immune cells and immune-related pathways. Finally, we established a genomic-clinicopathologic nomogram (based on risk score, age, and tumor stage) to predict the overall survival (OS) of GC patients.<h4>Conclusions</h4>The novel FRG signature may be a reliable tool for assisting clinicians in predicting the OS of GC patients and may facilitate personalized treatment.
format	article
author	Gang Liu Jian-Ying Ma Gang Hu Huan Jin
author_facet	Gang Liu Jian-Ying Ma Gang Hu Huan Jin
author_sort	Gang Liu
title	Identification and validation of a novel ferroptosis-related gene model for predicting the prognosis of gastric cancer patients.
title_short	Identification and validation of a novel ferroptosis-related gene model for predicting the prognosis of gastric cancer patients.
title_full	Identification and validation of a novel ferroptosis-related gene model for predicting the prognosis of gastric cancer patients.
title_fullStr	Identification and validation of a novel ferroptosis-related gene model for predicting the prognosis of gastric cancer patients.
title_full_unstemmed	Identification and validation of a novel ferroptosis-related gene model for predicting the prognosis of gastric cancer patients.
title_sort	identification and validation of a novel ferroptosis-related gene model for predicting the prognosis of gastric cancer patients.
publisher	Public Library of Science (PLoS)
publishDate	2021
url	https://doaj.org/article/ea840b19598643fcbaa6912de2f53c53
work_keys_str_mv	AT gangliu identificationandvalidationofanovelferroptosisrelatedgenemodelforpredictingtheprognosisofgastriccancerpatients AT jianyingma identificationandvalidationofanovelferroptosisrelatedgenemodelforpredictingtheprognosisofgastriccancerpatients AT ganghu identificationandvalidationofanovelferroptosisrelatedgenemodelforpredictingtheprognosisofgastriccancerpatients AT huanjin identificationandvalidationofanovelferroptosisrelatedgenemodelforpredictingtheprognosisofgastriccancerpatients
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Identification and validation of a novel ferroptosis-related gene model for predicting the prognosis of gastric cancer patients.

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