ArticleBMC cancer2022
An iron metabolism and immune related gene signature for the prediction of clinical outcome and molecular characteristics of triple-negative breast cancer.
Article in BMC cancer, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed, 9 citations in OpenAlex.
- Suppression of NGALR impedes TNBC cell survival, proliferation, invasion, and migration through Akt/mTOR and JAK/STAT3 pathway inhibition.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2026Article
- Absence of Cysteine and Iron Chelation Induces Ferroptosis in Triple-Negative Breast Cancer Cells.Breast cancer : basic and clinical research · 2025Article
- Construction of a stromal cell-related prognostic signature based on a 101-combination machine learning framework for predicting prognosis and immunotherapy response in triple-negative breast cancer.Frontiers in immunology · 2025Article
- Iron-Dependent Cell Death: Exploring Ferroptosis as a Unique Target in Triple-Negative Breast Cancer Management.Cancer management and research · 2025Review
- Ferroptosis as a promising targeted therapy for triple negative breast cancer.Breast cancer research and treatment · 2024Review
- Ferroptosis: the emerging player in remodeling triple-negative breast cancer.Frontiers in immunology · 2023Review
- Establishment and verification of a nomogram for predicting survival in patients with triple-positive breast cancer.Annals of translational medicine · 2022Article
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Authors and funding
4 authors at 2 institutions in 1 country.
Funding
Abstract
backgroundAn imbalance of intracellular iron metabolism can lead to the occurrence of ferroptosis. Ferroptosis can be a factor in the remodeling of the immune microenvironment and can affect the efficacy of cancer immunotherapy. How to combine ferroptosis-promoting modalities with immunotherapy to suppress triple-negative breast cancer (TNBC) has become an issue of great interest in cancer therapy. However, potential biomarkers related to iron metabolism and immune regulation in TNBC remain poorly understand.
methodsWe constructed an optimal prognostic TNBC-IMRGs (iron metabolism and immune-related genes) signature using least absolute shrinkage and selection operator (LASSO) cox regression. Survival analysis and ROC curves were analyzed to identify the predictive value in a training cohort and external validation cohorts. The correlations of gene signature with ferroptosis regulators and immune infiltration are also discussed. Finally, we combined the gene signature with the clinical model to construct a combined model, which was further evaluated using a calibration curve and decision curve analysis (DCA).
resultsCompared with the high-risk group, TNBC patients with low-risk scores had a remarkably better prognosis in both the training set and external validation sets. Both the IMRGs signature and combined model had a high predictive capacity, 1/3/5- year AUC: 0.866, 0.869, 0.754, and 1/3/5-yaer AUC: 0.942, 0.934, 0.846, respectively. The calibration curve and DCA also indicate a good predictive performance of the combined model. Gene set enrichment analysis (GSEA) suggests that the high-risk group is mainly enriched in metabolic processes, while the low-risk group is mostly clustered in immune related pathways. Multiple algorithms and single sample GSEA further show that the low-risk score is associated with a high tumor immune infiltration level. Differences in expression of ferroptosis regulators are also observed among different risk groups.
conclusionsThe IMRGs signature based on a combination of iron metabolism and immune factors may contribute to evaluating prognosis, understanding molecular characteristics and selecting treatment options in TNBC.
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