Background
Standard treatment for early triple-negative breast cancer (eTNBC) often includes anthracycline-containing chemotherapy, which can have serious side effects. This study looked at tumor biopsies to find gene networks that could help predict treatment success and survival after a different type of chemotherapy that doesnât use anthracyclines.
Study Methods
In the WSG-ADAPT-TN trial, patients with eTNBC were divided into two groups to receive different chemotherapy combinations for 12 weeks. The main goal was to see how many patients achieved a complete pathological response (pCR). We also looked at survival rates and analyzed gene expressions in a subset of patients.
Results
Out of 135 patients, 36.3% achieved pCR. During a 5-year follow-up, 30 patients experienced invasive disease-free survival (iDFS) events. Key findings showed that genes related to immune response and viral defense were linked to achieving pCR, while metabolic pathways were associated with long-term survival. The study developed polygenic scores to help predict pCR and iDFS.
Conclusions
The study highlighted that immune-related genes can predict how well patients respond to chemotherapy and their chances of survival. This information could help doctors select patients for less aggressive treatment plans, potentially improving personalized care.
Opportunities for Clinics and Patients
- Define Measurable Outcomes: Set clear goals to evaluate how well the treatment works based on gene networks.
- Select AI Tools: Choose AI solutions that can analyze patient data and improve treatment strategies.
- Implement Step by Step: Start with pilot projects to test the effectiveness of the new methods and track real-world results.
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