Related Experiment Video
Updated: Jun 30, 2026
09:21
Ferritinophagy: Assessing the Selective Degradation of Iron by Autophagy in Human Fibroblasts
Published on: February 23, 2024
Ferritinophagy-Related Genes in Breast Cancer: Insights from Multi-Omics Analysis
1The Comprehensive Breast Care Center, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.
Current Medicinal Chemistry
|June 29, 2026
Summary
A new prognostic model using ATG5, JUN, and TFRC offers improved breast cancer risk stratification. This ferritinophagy-based model aids in understanding tumor progression and developing targeted therapies.
Area of Science:
- Oncology
- Molecular Biology
- Genetics
Background:
- Breast cancer (BRCA) poses a significant health challenge.
- Ferritinophagy, a process regulating iron homeostasis via autophagy, is implicated in tumor progression.
- Identifying novel biomarkers for BRCA prognosis is crucial.
Purpose of the Study:
- To explore ferritinophagy-related genes (FeRDEGs) as potential biomarkers in breast cancer.
- To develop and validate an integrative multi-omics prognostic model for BRCA.
- To investigate the clinical utility of the prognostic model for risk stratification and personalized therapy.
Main Methods:
- Identified 30 differentially expressed FeRDEGs in BRCA.
- Utilized Cox and LASSO regression analyses to construct a prognostic risk model.
- Validated the model in an independent cohort, assessing mutation profiles, drug-gene interactions, and immune infiltration.
Main Results:
- Functional analyses linked FeRDEGs to cellular stress, autophagy, and metabolic pathways.
- ATG5, JUN, and TFRC were identified as key prognostic genes.
- The developed multi-gene model accurately stratified patients into distinct risk groups with significant survival differences.
- Distinct mutational landscapes and drug sensitivity profiles were observed between risk groups.
Conclusions:
- A prognostic model based on ATG5, JUN, and TFRC demonstrates robust risk stratification and clinical potential in breast cancer.
- The model supports personalized therapeutic strategies targeting iron metabolism and autophagy.
- Further validation in larger cohorts is recommended to enhance predictive performance.
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