Cellular senescence and disulfide death-related genes as biological markers of breast cancer prognosis
- Yidan Zhang 1, Yan Ye 1, Jing Wang 2, Jintao Liu 3
- Yidan Zhang 1, Yan Ye 1, Jing Wang 2
- 1Department of Breast and Thyroid Surgery, Hainan Women and Children's Medical Center, Haikou, Hainan, People's Republic of China.
- 2Department of Breast and Thyroid Surgery, Hainan Women and Children's Medical Center, Haikou, Hainan, People's Republic of China. wangjinger9910@aliyun.com.
- 3Department of Breast and Thyroid Surgery, Hainan Women and Children's Medical Center, Haikou, Hainan, People's Republic of China. liujintao77@aliyun.com.
- 0Department of Breast and Thyroid Surgery, Hainan Women and Children's Medical Center, Haikou, Hainan, People's Republic of China.
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View abstract on PubMed
Summary
This summary is machine-generated.This study identified genes linked to cellular senescence and disulfide death in breast cancer. A predictive model using ACTN2 and CHD4 genes shows promise for forecasting patient prognosis.
Area Of Science
- Oncology
- Molecular Biology
- Genetics
Background
- Breast cancer is a complex disease with varied outcomes.
- Understanding molecular drivers of prognosis is crucial for personalized treatment.
Purpose Of The Study
- To identify genes associated with cellular senescence and disulfide death in breast cancer.
- To develop a predictive model for breast cancer prognosis using these genes.
- To explore potential clinical applications of these genetic markers.
Main Methods
- Screened differential genes related to cellular senescence and disulfide death.
- Constructed a protein-protein interaction network and performed functional enrichment analysis (GO, KEGG).
- Developed a prognostic risk model using TCGA-BRCA data and LASSO regression, validated with Cox regression and GSEA/GSVA.
Main Results
- Identified 17 differential genes. A LASSO regression model identified ACTN2 and CHD4 as key prognostic genes.
- The LASSO risk score and pathological stage significantly improved prognostic prediction.
- The multifactor Cox regression model demonstrated predictive utility for 1, 3, and 5-year survival.
Conclusions
- Genes involved in cellular senescence and disulfide death can be used to build predictive models for breast cancer prognosis.
- These findings offer potential for improved clinical decision-making and patient stratification.
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