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This study investigates the relationship between gene expression and drug response in triple-negative breast cancer (TNBC) using single-cell RNA sequencing and machine learning to identify potential biomarkers for treatment response. By analyzing tumor and blood samples from TNBC patients, the researchers identified immune-related genes linked to therapeutic outcomes and achieved high predictive accuracy for treatment sensitivity. The integration of scRNA-seq with machine learning offers insights for person

Author

prem.pics9

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EN