Open Access

ARTICLE

Development of Patient-Derived Conditionally Reprogrammed 3D Breast Cancer Culture Models for Drug Sensitivity Evaluation

Jing Cai^1,#, Haoyun Zhu^1,#, Weiling Guo¹, Ting Huang¹, Pangzhou Chen^1,2, Wen Zhou¹, Ziyun Guan^1,3,*

1 Research Institute of Medicine, The Sixth Affiliated Hospital, School of Medicine, South China University of Technology, Foshan, 528000, China
2 Department of Breast Surgery, The Sixth Affiliated Hospital, School of Medicine, South China University of Technology, Foshan, 528000, China
3 Department of Emergency, The Sixth Affiliated Hospital, School of Medicine, South China University of Technology, Foshan, 528000, China

* Corresponding Author: Ziyun Guan. Email:
# These authors contributed equally to this work

(This article belongs to the Special Issue: Recent Advances in Cancer Pharmacology)

Oncology Research 2026, 34(1), . https://doi.org/10.32604/or.2025.069902

Received 02 July 2025; Accepted 15 September 2025; Issue published 30 December 2025

Abstract

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.

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