Construction of a ferroptosis-based prognostic model for breast cancer helps to discriminate high/low risk groups and treatment priority.

GEO TCGA breast cancer ferroptosis prognostic model

Journal

Frontiers in immunology
ISSN: 1664-3224
Titre abrégé: Front Immunol
Pays: Switzerland
ID NLM: 101560960

Informations de publication

Date de publication:
2023
Historique:
received: 20 07 2023
accepted: 29 11 2023
medline: 28 12 2023
pubmed: 28 12 2023
entrez: 28 12 2023
Statut: epublish

Résumé

Breast cancer is a common malignant tumor associated with high morbidity and mortality. The role of ferroptosis, a regulated form of cell death, in breast cancer development and prognosis remains unclear. This study aims to investigate the relationship between ferroptosis-related genes and breast cancer and develop a prognostic model. RNA-seq expression datasets and clinical samples of breast cancer patients were obtained from public databases. Immunity- and drug resistance-related data were integrated. A preliminary screening was performed, resulting in the identification of 73 candidate ferroptosis factors. Univariate Cox regression analysis was conducted to select 12 genes, followed by LASSO Cox regression analysis to construct a prognostic risk prediction model consisting of 10 ferroptosis-related genes. The model was further characterized by immune cell infiltration. The expression levels of ferroptosis-related genes were validated in human breast cancer cell lines, and immunohistochemical (IHC) analysis was conducted on cancer specimens to assess ferroptosis-related protein expression. The study identified 10 ferroptosis-related genes that were significantly associated with breast cancer prognosis. The constructed prognostic risk prediction model showed potential for predicting the prognostic value of these genes. In addition, the infiltration of immune cells was observed to be a characteristic of the model. The expression levels of ferroptosis-related genes were confirmed in human breast cancer cell lines, and IHC analysis provided evidence of ferroptosis-related protein expression in cancer specimens. This study provides a novel prognostic model for breast cancer, incorporating 10 ferroptosis-related genes. The model demonstrates the potential for predicting breast cancer prognosis and highlights the involvement of immune cell infiltration. The expression levels of ferroptosis-related genes and proteins further support the association between ferroptosis and breast cancer development.

Identifiants

pubmed: 38152394
doi: 10.3389/fimmu.2023.1264206
pmc: PMC10751362
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

1264206

Informations de copyright

Copyright © 2023 Zhang, Zhao, Wu, Tian, Gao, Chen, Chen, Zhang, Wang, Qi and Sun.

Déclaration de conflit d'intérêts

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The author(s) declared that they were an editorial board member of Frontiers, at the time of submission. This had no impact on the peer review process and the final decision.

Auteurs

Liyong Zhang (L)

Department of Breast and Thyroid Surgery, Southwest Hospital, Army Medical University, Chongqing, China.

Tingting Zhao (T)

Department of Breast and Thyroid Surgery, Southwest Hospital, Army Medical University, Chongqing, China.

Xiujuan Wu (X)

Department of Breast and Thyroid Surgery, Southwest Hospital, Army Medical University, Chongqing, China.

Hao Tian (H)

Department of Breast and Thyroid Surgery, Southwest Hospital, Army Medical University, Chongqing, China.

Pingping Gao (P)

Department of Breast and Thyroid Surgery, Southwest Hospital, Army Medical University, Chongqing, China.

Qingqiu Chen (Q)

Department of Breast and Thyroid Surgery, Southwest Hospital, Army Medical University, Chongqing, China.

Ceshi Chen (C)

Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences and Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China.

Yi Zhang (Y)

Department of Breast and Thyroid Surgery, Southwest Hospital, Army Medical University, Chongqing, China.

Shushu Wang (S)

Department of Breast and Thyroid Surgery, Southwest Hospital, Army Medical University, Chongqing, China.

Xiaowei Qi (X)

Department of Breast and Thyroid Surgery, Southwest Hospital, Army Medical University, Chongqing, China.

Na Sun (N)

Department of Breast and Thyroid Surgery, Southwest Hospital, Army Medical University, Chongqing, China.

Classifications MeSH