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Identification and validation of STEAP3 as a ferroptosis-related biomarker in heart failure
1Department of Cardiology, The First Hospital of Changsha, Changsha, China.
Insights
This study identifies aging-related programmed cell death (PCD) gene signatures linked to heart failure (HF). These findings may offer new biomarkers for diagnosing HF and understanding its connection to aging processes.
Area of Science:
- Cardiology
- Molecular Biology
- Genetics
Background:
- Heart failure (HF) is a significant health concern, with aging and programmed cell death (PCD) being critical factors.
- The specific relationship between aging-related PCD genes and HF pathogenesis is not well understood.
Purpose of the Study:
- To investigate the association between aging-related PCD and heart failure.
- To identify potential diagnostic biomarkers for HF based on aging-related PCD signatures.
- To explore the functional role of specific genes, like STEAP3, in HF-related cellular processes.
Main Methods:
- Utilized single-sample gene-set enrichment analysis (ssGSEA) and random forest to analyze PCD types in HF.
- Applied machine learning algorithms, including LASSO, to develop a diagnostic model for HF.
- Investigated the immune microenvironment and constructed a gene regulatory network.
- Validated gene expression via qRT-PCR and conducted in vitro experiments on cardiomyocytes.
Main Results:
- Ferroptosis, autophagy, and necroptosis were significantly correlated with aging in HF patients.
- Identified 18 differentially expressed aging-related PCD genes, with the LASSO model demonstrating optimal diagnostic performance.
- Observed distinct immune microenvironment profiles between high and low aging-PCD index groups.
- STEAP3 was implicated in ferroptosis-related cardiomyocyte injury, potentially involving glutathione metabolism and iron homeostasis.
Conclusions:
- Identified novel aging-related PCD signatures in heart failure.
- These signatures represent potential candidate biomarkers for HF diagnosis and clinical validation.
- Provides insights into the molecular mechanisms linking aging, PCD, and HF progression.
Background:
Heart failure (HF) is a major health threat, with aging and programmed cell death (PCD) playing key roles. However, the link between aging-related PCD (aging-PCD) genes and HF remains unclear.
Methods:
We used ssGSEA and random forest to analyze PCD types in HF, identified aging-related PCDs via correlation analysis, and applied eight machine learning algorithms to develop a diagnostic model. SHAP and LIME were used to explain key features, and the relationship between the aging-PCD index and immune microenvironment was explored. Gene expression was verified by qRT-PCR, and the function of STEAP3 was further investigated in an H2O2-induced AC16 cell model. Ferroptosis-related changes were assessed by measuring reactive oxygen species (ROS), malondialdehyde (MDA), glutathione peroxidase (GSH-Px), and ferrous ion (Fe2+) levels.
Results:
Ferroptosis, autophagy, and necroptosis were strongly correlated with aging in HF. Eighteen differentially expressed aging-related PCD genes were identified. The LASSO model showed the best diagnostic performance. Significant differences in the immune microenvironment were observed between the aging-PCD index-high and index-low groups. A regulatory network of 15 key genes and 19 transcription factors was constructed. The qRT-PCR results validated the bioinformatics analysis. Functional experiments further suggested that STEAP3 may participate in ferroptosis-related injury in cardiomyocytes, potentially through glutathione metabolism (GPX4/SLC7A11 axis) and iron homeostasis.
Conclusion:
We identified aging-related PCD signatures in HF that may provide candidate biomarkers for further clinical validation.
