Abstract 312P
Background
The incidence of breast cancer is steadily increasing, and many patients receive adjuvant chemotherapy before or after surgery. In particular, neoadjuvant drug therapy is commonly used to suppress microinvasive before surgery. In this study, the patient-derived organoids (PDOs) from breast cancer patient’s biopsies were used for drug sensitivity test. To predict patient’s neoadjuvant treatment outcome, we propose a new drug sensitivity evaluation method based on multi-factors such as Area Under Curve (AUC) of dose response curve, organoid growth rate.
Methods
Patient cells were obtained from core needle biopsy before surgery and mechanically dissociated before being mixed with extracellular matrix (ECM) to generate PDOs. Anti-cancer drug sensitivity testing was performed on these PDOs using a pillar-based organoid system, which involved single or combination treatments with anti-cancer drug with 384 plate-based high throughput screening. Area Under Curve (AUC) values of the dose-response curves (DRC) and organoid growth rate were calculated by pillar-based organoid system.
Results
The proposed multi-factor prediction model was verified by comparing drug sensitivity test with patient’s neoadjuvant outcome. We performed drug sensitivity test of 79 breast cancer patients. So far, 13 patients have finally been evaluated for neoadjuvant treatment results. Multi-factor prediction model ( C ancer O rganoid-based D iagnosis R eactivity P rediction, CODRP) shows 83 % sensitivity and 85 % specificity while conventional prediction model using only AUC shows 50 % sensitivity and 71 % specificity.
Conclusions
Therefore, Multi-factor prediction model (CODRP) may provide useful supplementary diagnostic information for individual breast cancer patients by selecting optimal anticancer drug candidates for patient treatment.
Clinical trial identification
Editorial acknowledgement
Legal entity responsible for the study
The authors.
Funding
Medical & Bio Decision Co., Ltd.
Disclosure
All authors have declared no conflicts of interest.
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