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Peer-reviewedCC BYBrazilian journal of medical and biological research = Revista brasileira de pesquisas medicas e biologicas

Identification and validation of prognostic characteristics of survival risk marker genes associated with ferroptosis and iron metabolism in breast cancer

  • Mengxi Li1
  • Baoqing Zhao2
  • Zhenwang Zhang2
  1. 1Department of Biological Sciences, School of Nuclear Technology and Chemistry & Biology, Hubei University of Science and Technology, Xianning, Hubei Province, China
  2. 2Hubei Key Laboratory of Diabetes and Angiopathy, School of Pharmacy, Xianning Medical College, Hubei University of Science and Technology, Xianning, Hubei Province, China
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Abstract

This study developed a polygenic risk model for breast cancer (BRCA) prognosis using gene expression and clinical data from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Differentially expressed genes (DEGs) between tumor and normal tissues were identified using the “limma” R package, yielding 1,000 DEGs (396 upregulated, 604 downregulated). Weighted gene co-expression network analysis (WGCNA) and Lasso-Cox regression integrated ferroptosis- and iron metabolism-related genes, identifying eight key survival risk markers: ANO6, DPYD, MMD, EGR1, ACSL4, LIFR, PPARG, and CREB5. High-risk groups exhibited elevated ANO6, DPYD, and MMD expression, while EGR1, ACSL4, LIFR, PPARG, and CREB5 showed lower levels. Survival analysis confirmed that low ANO6 and high LIFR/PPARG expression correlated with prolonged survival, validated across cohorts. A nomogram incorporating these genes and clinical factors enabled personalized survival probability assessment. The eight-gene model independently stratified high- and low-risk BRCA patients, offering a reliable prognostic tool.

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Cite

BibTeXRIS
BibTeX
@article{li2026identification,
  title = {{Identification and validation of prognostic characteristics of survival risk marker genes associated with ferroptosis and iron metabolism in breast cancer}},
  author = {Mengxi Li and Baoqing Zhao and Zhenwang Zhang},
  journal = {Brazilian journal of medical and biological research = Revista brasileira de pesquisas medicas e biologicas},
  year = {2026},
  month = oct,
  doi = {10.1590/1414-431x2026e15313},
  url = {https://europepmc.org/article/PMC/PMC13722004},
  note = {CC BY},
}
RIS
TY  - JOUR
TI  - Identification and validation of prognostic characteristics of survival risk marker genes associated with ferroptosis and iron metabolism in breast cancer
AU  - Mengxi Li
AU  - Baoqing Zhao
AU  - Zhenwang Zhang
PY  - 2026
DA  - 2026/10/30
JO  - Brazilian journal of medical and biological research = Revista brasileira de pesquisas medicas e biologicas
DO  - 10.1590/1414-431x2026e15313
UR  - https://europepmc.org/article/PMC/PMC13722004
AB  - This study developed a polygenic risk model for breast cancer (BRCA) prognosis using gene expression and clinical data from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Differentially expressed genes (DEGs) between tumor and normal tissues were identified using the “limma” R package, yielding 1,000 DEGs (396 upregulated, 604 downregulated). Weighted gene co-expression network analysis (WGCNA) and Lasso-Cox regression integrated ferroptosis- and iron metabolism-related genes, identifying eight key survival risk markers: ANO6, DPYD, MMD, EGR1, ACSL4, LIFR, PPARG, and CREB5. High-risk groups exhibited elevated ANO6, DPYD, and MMD expression, while EGR1, ACSL4, LIFR, PPARG, and CREB5 showed lower levels. Survival analysis confirmed that low ANO6 and high LIFR/PPARG expression correlated with prolonged survival, validated across cohorts. A nomogram incorporating these genes and clinical factors enabled personalized survival probability assessment. The eight-gene model independently stratified high- and low-risk BRCA patients, offering a reliable prognostic tool.
SN  - 0100-879X
SN  - 1414-431X
ER  -