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Published on: December 16, 2022
Development of Patient-Derived Conditionally Reprogrammed 3D Breast Cancer Culture Models for Drug Sensitivity
Jing Cai1, Haoyun Zhu1, Weiling Guo1
1Research Institute of Medicine, The Sixth Affiliated Hospital, School of Medicine, South China University of Technology, Foshan, 528000, China.
Background:
Therapeutic responses of breast cancer vary among patients and lead to drug resistance and recurrence due to the heterogeneity. Current preclinical models, however, are inadequate for predicting individual patient responses towards different drugs. This study aimed to investigate the patient-derived breast cancer culture models for drug sensitivity evaluations.
Methods:
Tumor and adjacent tissues from female breast cancer patients were collected during surgery. Patient-derived breast cancer cells were cultured using the conditional reprogramming technique to establish 2D models. The obtained patient-derived conditional reprogramming breast cancer (CRBC) cells were subsequently embedded in alginate-gelatin methacryloyl hydrogel microspheres to form 3D culture models. Comparisons between 2D and 3D models were made using immunohistochemistry (tumor markers), MTS assays (cell viability), flow cytometry (apoptosis), transwell assays (migration), and Western blotting (protein expression). Drug sensitivity tests were conducted to evaluate patient-specific responses to anti-cancer agents.
Results:
2D and 3D culture models were successfully established using samples from eight patients. The 3D models retained histological and marker characteristics of the original tumors. Compared to 2D cultures, 3D models exhibited increased apoptosis, enhanced drug resistance, elevated stem cell marker expression, and greater migration ability-features more reflective of in vivo tumor behavior.
Conclusion:
Patient-derived 3D CRBC models effectively mimic the in vivo tumor microenvironment and demonstrate stronger resistance to anti-cancer drugs than 2D models. These hydrogel-based models offer a cost-effective and clinically relevant platform for drug screening and personalized breast cancer treatment.
Insights
Patient-derived 3D breast cancer models better predict drug resistance than 2D models. These models offer a cost-effective platform for personalized breast cancer treatment and drug screening.
Area of Science:
- Oncology
- Biotechnology
- Cancer Research
Background:
- Breast cancer heterogeneity leads to variable therapeutic responses, drug resistance, and recurrence.
- Current preclinical models fail to accurately predict individual patient drug responses.
- There is a need for improved models to evaluate patient-specific drug sensitivities.
Purpose of the Study:
- To develop and evaluate patient-derived breast cancer culture models for drug sensitivity testing.
- To compare the efficacy of 2D and 3D culture models in mimicking in vivo tumor characteristics.
- To assess the potential of these models for personalized breast cancer treatment.
Main Methods:
- Established patient-derived conditional reprogramming breast cancer (CRBC) cells using tumor samples.
- Developed 2D and 3D culture models, with 3D models embedded in alginate-gelatin methacryloyl hydrogel microspheres.
- Utilized immunohistochemistry, MTS assays, flow cytometry, transwell assays, and Western blotting for model characterization and drug sensitivity evaluation.
Main Results:
- Successfully established 2D and 3D CRBC models from eight patients.
- 3D models preserved tumor histological and marker characteristics.
- 3D models demonstrated increased apoptosis, enhanced drug resistance, elevated stem cell marker expression, and greater migration compared to 2D models, reflecting in vivo behavior.
Conclusions:
- Patient-derived 3D CRBC models accurately mimic the in vivo tumor microenvironment and exhibit greater drug resistance than 2D models.
- These hydrogel-based 3D models provide a cost-effective and clinically relevant platform for drug screening.
- The models support personalized breast cancer treatment strategies.
