Drug Sensitivity of Hydrothorax and Ascite Organoids from Breast Cancer

Overview

Malignant hydrothorax and ascitic fluid in advanced breast cancer often arise from metastasis to the lungs, pleura, or liver. Patients with this condition experience rapid disease progression and multidrug resistance, facing limited treatment options. Clinical guidelines offer various therapies based on molecular subtypes; however, their effectiveness can be hindered by prior treatments, patient health, and tumor evolution. Current evaluations of treatment efficacy typically take two cycles, delaying the recognition of ineffective therapies and resulting in unnecessary side effects and costs. Organoid models present a promising solution, accurately replicating tumor structure and cellular diversity compared to traditional methods. These patient-derived models facilitate improved drug sensitivity testing, leading to more personalized treatment plans. In this study, 90 patients diagnosed with metastatic breast cancer accompanied by hydrothorax and ascitic fluid will be recruited. Patient-derived organoids will be used to assess the sensitivity of chemotherapy regimens, including Doxorubicin, Carboplatin, Cyclophosphamide, and Paclitaxel, along with targeted therapies such as Herceptin and Pertuzumab.

90 metastatic breast cancer patients with hydrothorax and ascitic fluid will be recruited. Baseline data, including medical history, ultrasound, and MRI records, will be collected both before and after two cycles of chemotherapy. Tumor samples from hydrothorax and ascitic fluid will be obtained and cultured to generate patient-derived organoids (PDOs). These PDOs will then be exposed to standard chemotherapeutic drugs used in breast cancer treatment. Organoid growth will be monitored post-treatment, and dose-response curves will be generated to assess drug sensitivity. To evaluate clinical outcomes, the RECIST criteria will be applied to measure tumor response in patients. Correlation analysis will be performed to determine the consistency between the treatment responses observed in the PDO models and the actual clinical outcomes of the patients.

Conditions