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The prognostic significance of a novel ferroptosis-related gene model in breast cancer

BACKGROUND: Breast cancer (BRCA) is the most common malignancy with high heterogeneity in women, and the prognostic prediction for BRCA has remained poor. Ferroptosis, a recently identified iron-dependent form of programmed cell death, plays a significant role in BRCA treatment. Some BRCA cell lines...

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Autores principales: Lu, Yu-Jie, Gong, Yang, Li, Wen-Jing, Zhao, Chen-Yi, Guo, Feng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: AME Publishing Company 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8908135/
https://www.ncbi.nlm.nih.gov/pubmed/35280394
http://dx.doi.org/10.21037/atm-22-479
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author Lu, Yu-Jie
Gong, Yang
Li, Wen-Jing
Zhao, Chen-Yi
Guo, Feng
author_facet Lu, Yu-Jie
Gong, Yang
Li, Wen-Jing
Zhao, Chen-Yi
Guo, Feng
author_sort Lu, Yu-Jie
collection PubMed
description BACKGROUND: Breast cancer (BRCA) is the most common malignancy with high heterogeneity in women, and the prognostic prediction for BRCA has remained poor. Ferroptosis, a recently identified iron-dependent form of programmed cell death, plays a significant role in BRCA treatment. Some BRCA cell lines are proven to be sensitive to ferroptosis, and some ferroptosis-related genes have been identified as divers or suppressors in the progress of BRCA. This study aimed to explore the prognostic value of ferroptosis-related genes in BRCA. METHODS: A ferroptosis-related gene list, messenger RNA (mRNA) gene expression of BRCA patients, and corresponding clinicopathological data were collected from public databases. The patients of the Cancer Genome Atlas (TCGA) were identified as the training cohort, and the ones of the Gene Expression Omnibus (GEO) were looked as the validation cohort. Univariate Cox regression analysis was utilized to identify prognostic ferroptosis-related genes, and subsequent multivariate analysis further screened out important genes to establish a prognostic model. Receiver operating characteristic (ROC) curves were used to validate the model in both internal and external cohorts. Functional analysis was generated to evaluate the potential correlation between tumor immunity and ferroptosis-related genes in BRCA. RESULTS: A ferroptosis-related gene signature stratifying patients into 2 risk score groups was established based on the TCGA cohort, and validated in the GEO cohort. Patients with lower risk scores had better overall survival (OS) compared to those with higher risk scores (P<0.001, TCGA cohort; P<0.05, GEO cohort). The risk score was independently associated with the OS of BRCA patients (P<0.001, TCGA cohort; P<0.05, GEO cohort). The area under the curves (AUCs) of the model in the training and validation cohorts were all around 0.7. Immune-related biological pathways and immune status were significantly different between the 2 divided risk groups. CONCLUSIONS: The novel prognostic model composed of 9 ferroptosis-related genes accurately predicts the survival of BRCA patients. It might provide a new sight for ferroptosis-related BRCA therapy.
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spelling pubmed-89081352022-03-11 The prognostic significance of a novel ferroptosis-related gene model in breast cancer Lu, Yu-Jie Gong, Yang Li, Wen-Jing Zhao, Chen-Yi Guo, Feng Ann Transl Med Original Article BACKGROUND: Breast cancer (BRCA) is the most common malignancy with high heterogeneity in women, and the prognostic prediction for BRCA has remained poor. Ferroptosis, a recently identified iron-dependent form of programmed cell death, plays a significant role in BRCA treatment. Some BRCA cell lines are proven to be sensitive to ferroptosis, and some ferroptosis-related genes have been identified as divers or suppressors in the progress of BRCA. This study aimed to explore the prognostic value of ferroptosis-related genes in BRCA. METHODS: A ferroptosis-related gene list, messenger RNA (mRNA) gene expression of BRCA patients, and corresponding clinicopathological data were collected from public databases. The patients of the Cancer Genome Atlas (TCGA) were identified as the training cohort, and the ones of the Gene Expression Omnibus (GEO) were looked as the validation cohort. Univariate Cox regression analysis was utilized to identify prognostic ferroptosis-related genes, and subsequent multivariate analysis further screened out important genes to establish a prognostic model. Receiver operating characteristic (ROC) curves were used to validate the model in both internal and external cohorts. Functional analysis was generated to evaluate the potential correlation between tumor immunity and ferroptosis-related genes in BRCA. RESULTS: A ferroptosis-related gene signature stratifying patients into 2 risk score groups was established based on the TCGA cohort, and validated in the GEO cohort. Patients with lower risk scores had better overall survival (OS) compared to those with higher risk scores (P<0.001, TCGA cohort; P<0.05, GEO cohort). The risk score was independently associated with the OS of BRCA patients (P<0.001, TCGA cohort; P<0.05, GEO cohort). The area under the curves (AUCs) of the model in the training and validation cohorts were all around 0.7. Immune-related biological pathways and immune status were significantly different between the 2 divided risk groups. CONCLUSIONS: The novel prognostic model composed of 9 ferroptosis-related genes accurately predicts the survival of BRCA patients. It might provide a new sight for ferroptosis-related BRCA therapy. AME Publishing Company 2022-02 /pmc/articles/PMC8908135/ /pubmed/35280394 http://dx.doi.org/10.21037/atm-22-479 Text en 2022 Annals of Translational Medicine. All rights reserved. https://creativecommons.org/licenses/by-nc-nd/4.0/Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0 (https://creativecommons.org/licenses/by-nc-nd/4.0/) .
spellingShingle Original Article
Lu, Yu-Jie
Gong, Yang
Li, Wen-Jing
Zhao, Chen-Yi
Guo, Feng
The prognostic significance of a novel ferroptosis-related gene model in breast cancer
title The prognostic significance of a novel ferroptosis-related gene model in breast cancer
title_full The prognostic significance of a novel ferroptosis-related gene model in breast cancer
title_fullStr The prognostic significance of a novel ferroptosis-related gene model in breast cancer
title_full_unstemmed The prognostic significance of a novel ferroptosis-related gene model in breast cancer
title_short The prognostic significance of a novel ferroptosis-related gene model in breast cancer
title_sort prognostic significance of a novel ferroptosis-related gene model in breast cancer
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8908135/
https://www.ncbi.nlm.nih.gov/pubmed/35280394
http://dx.doi.org/10.21037/atm-22-479
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