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Integrative multidimensional analysis of age-associated synthetic lethal genes and development of a prognostic model
Qinqing Wu1,2, Dongxu Ma3, Heng Cao4
1Department of Preventive Medicine, Shantou University Medical College, Shantou, China.
Background:
Breast cancer (BRCA) is the most common malignancy and leading cause of mortality among women, with rising incidence in younger patients. Although treatments have advanced, outcomes for advanced BRCA remain poor. Synthetic lethality (SL) offers promise in precision oncology, but resistance limits its benefit.
Methods:
We integrated TCGA-BRCA and GEO datasets with SL gene sets to identify candidate genes. Differential expression analysis and WGCNA were performed, with key modules defined by clinical subgroups (≤40 vs. >40 years). Candidate genes were further validated by machine learning, Mendelian randomization (MR), and single-cell transcriptomic analysis. Functional experiments were conducted for confirmation.
Results:
Sixteen age-associated SL genes were identified. NEK2, IBSP, and PYCR1 showed strong diagnostic value (AUC > 0.90), enriched in cell cycle, DNA repair, and drug resistance pathways. MR consistently confirmed SLC7A5 as a robust candidate gene, linking metabolic regulation to BRCA risk.
Conclusions:
Age-associated SL genes play critical roles in BRCA, with SLC7A5 highlighted as a promising biomarker and therapeutic target. These findings provide insights for early diagnosis and metabolism-based precision therapy.
Insights
Synthetic lethality (SL) gene discovery identified age-associated targets for breast cancer (BRCA). SLC7A5 shows promise as a biomarker and therapeutic target for precision oncology.
Area of Science:
- Oncology
- Genetics
- Biomarker Discovery
Background:
- Breast cancer (BRCA) is a leading cause of mortality in women, with poor outcomes for advanced stages.
- Current treatments face limitations, especially resistance, highlighting the need for novel therapeutic strategies.
- Synthetic lethality (SL) presents a promising avenue for precision oncology in BRCA treatment.
Purpose of the Study:
- To identify novel age-associated synthetic lethality (SL) genes in breast cancer (BRCA).
- To validate candidate genes as potential biomarkers and therapeutic targets for BRCA.
- To explore the role of metabolic regulation in BRCA risk and treatment.
Main Methods:
- Integrated TCGA-BRCA and GEO datasets with SL gene sets.
- Performed differential expression analysis, Weighted Gene Co-expression Network Analysis (WGCNA), machine learning, and Mendelian randomization (MR).
- Utilized single-cell transcriptomic analysis and functional experiments for validation.
Main Results:
- Identified sixteen age-associated SL genes, with NEK2, IBSP, and PYCR1 demonstrating high diagnostic value (AUC > 0.90).
- These genes are enriched in cell cycle, DNA repair, and drug resistance pathways.
- MR confirmed SLC7A5 as a key candidate gene linking metabolic regulation to BRCA risk.
Conclusions:
- Age-associated SL genes are crucial in BRCA pathogenesis and progression.
- SLC7A5 emerges as a significant biomarker and therapeutic target for precision medicine in BRCA.
- Findings support early diagnosis and metabolism-based therapeutic strategies for breast cancer.
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