3D Bioprinted Tumor-Stroma Models of Triple-Negative Breast Cancer Stem Cells for Preclinical Targeted Therapy Evaluation

Abstract

3D bioprinting; Cancer stem cells; Triple-negative breast cancer

Bioimpresión 3D; Células madre cancerosas; Cáncer de mama triple negativo

Bioimpressió 3D; Cèl·lules mare cancerígenes; Càncer de mama triple negatiu

Breast cancer stem cells (CSCs) play a pivotal role in therapy resistance and tumor relapse, emphasizing the need for reliable in vitro models that recapitulate the complexity of the CSC tumor microenvironment to accelerate drug discovery. We present a bioprinted breast CSC tumor-stroma model incorporating triple-negative breast CSCs (TNB-CSCs) and stromal cells (human breast fibroblasts), within a breast-derived decellularized extracellular matrix bioink. Comparison of molecular signatures in this model with different clinical subtypes of bioprinted tumor-stroma models unveils a unique molecular profile for artificial CSC tumor models. We additionally demonstrate that the model can recapitulate the invasive potential of TNB-CSC. Surface-enhanced Raman scattering imaging allowed us to monitor the invasive potential of tumor cells in deep z-axis planes, thereby overcoming the depth-imaging limitations of confocal fluorescence microscopy. As a proof-of-concept application, we conducted high-throughput drug testing analysis to assess the efficacy of CSC-targeted therapy in combination with conventional chemotherapeutic compounds. The results highlight the usefulness of tumor-stroma models as a promising drug-screening platform, providing insights into therapeutic efficacy against CSC populations resistant to conventional therapies.

Funding Sources Financial support was provided by the European Research Council (ERC-AdG-2017 #787510 4DBIOSERS and ERC-2023-POC #101138255 3DTUMOUR). C.G.A. thanks the Spanish State Research Agency for a Juan de la Cierva Incorporación Fellowship (FJCI-2016-28887). I.A. is grateful for the SGR grant from the Catalan Government (2021 SGR 1173). Figures were created using BioRender.