Development and validation of a highly accurate multigene gene expression biomarker to predict chemotherapy response in primary triple-negative breast cancer

Key Points

• This research aims to develop and validate a multigene expression biomarker to predict chemotherapy response in triple-negative breast cancer (TNBC).
• Conducted transcriptomic profiling of tumor samples
• Applied machine learning techniques to identify relevant biomarkers
• Evaluated the accuracy of the biomarker in predicting treatment outcomes
• Identified a set of genes associated with chemotherapy response
• Machine learning model shows high accuracy in predictions
• Findings may enhance personalized treatment approaches for TNBC patients