Integrated network toxicology and bioinformatics reveal PFAS-driven prognostic biomarkers and molecular mechanisms in breast cancer: insights from transcriptome analysis and molecular docking
- Yingqiang Fu 1, Yiyang Liu 1, Ziqi Sui 2
- Yingqiang Fu 1, Yiyang Liu 1, Ziqi Sui 2
- 1Department of Breast Surgery, Second Affiliated Hospital, Zhejiang University School of Medicine, Linping Campus, Hangzhou City, 311100, Zhejiang Province, China.
- 2Department of Gastroenterology, The Second Affiliated Hospital of Zhejiang Chinese Medical University, No. 318, Chaowang Road, Gongshu District, Hangzhou City, 310005, Zhejiang Province, China. suiziqi02503@aliyun.com.
- 0Department of Breast Surgery, Second Affiliated Hospital, Zhejiang University School of Medicine, Linping Campus, Hangzhou City, 311100, Zhejiang Province, China.
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View abstract on PubMed
Summary
This summary is machine-generated.Per- and polyfluoroalkyl substances (PFAS) exposure is linked to breast cancer development through altered gene expression and immune cell changes. This study identifies key genes and pathways, offering potential therapeutic targets for breast cancer management.
Area Of Science
- Environmental toxicology
- Bioinformatics
- Cancer research
Background
- Per- and polyfluoroalkyl substances (PFAS) are environmental contaminants increasingly associated with breast cancer.
- The molecular mechanisms underlying PFAS-induced breast cancer remain largely unknown.
- This study aims to clarify these mechanisms using network toxicology and bioinformatics.
Purpose Of The Study
- To identify genes and pathways affected by PFAS exposure in breast cancer.
- To discover prognostic biomarkers for breast cancer.
- To explore the relationship between PFAS, gene expression, and immune infiltration in breast cancer.
Main Methods
- Utilized TCGA-BRCA dataset to identify differentially expressed genes (DEGs) in breast cancer.
- Cross-referenced DEGs with PFAS-related genes from the Comparative Toxicogenomics Database (CTD).
- Performed enrichment analysis, network construction, survival analysis, immune cell infiltration assessment (CIBERSORT), and molecular docking.
Main Results
- Identified 141 common DEGs enriched in cytokine and growth factor pathways.
- Developed a prognostic risk model using six key genes (MRPL13, LEF1, ATP7B, IFNG, SFRP1, DNMT3B) that stratified patient survival.
- Observed distinct immune cell infiltration profiles and strong interactions between PFAS compounds and DNMT3B.
Conclusions
- PFAS exposure contributes to breast cancer development via altered gene expression and immune responses.
- Identified prognostic biomarkers and potential therapeutic targets for PFAS-related breast cancer.
- Highlights the importance of environmental factors in breast cancer etiology and management.
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