ArticleFrontiers in immunology2023
Construction of a ferroptosis-based prognostic model for breast cancer helps to discriminate high/low risk groups and treatment priority.
Article in Frontiers in immunology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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4 citing papers in PubMed, 5 citations in OpenAlex.
- Integrated machine learning and bioinformatic analyses constructed a sulfur metabolism-related breast cancer risk model and identified heat-shock protein A9 as a potential therapeutic target for human breast cancer.Discover oncology · 2026Article
- Integrated bioinformatics analysis identifies cuproptosis and ferroptosis gene signatures via subgroup clustering: Prognostic and therapeutic implications in breast cancer.Biochemistry and biophysics reports · 2025Article
- Exploring Immune-Related Ferroptosis Genes in Thyroid Cancer: A Comprehensive Analysis.Biomedicines · 2025Article
- Identification of Cuproptosis-Associated Prognostic Gene Expression Signatures from 20 Tumor Types.Biology · 2024Article
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Authors and funding
11 authors at 3 institutions in 1 country.
Funding
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Abstract
Introduction: 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. Methods: 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. Results: 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. Discussion: 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.
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