Bioprinting and Differentiation of Adipose-Derived Stromal Cell Spheroids for a 3D Breast Cancer-Adipose Tissue Model.
Hannes HorderMar Guaza LasherasNadine GrummelAli NadernezhadJohannes HerbigSüleyman ErgünJoerg TessmarJuergen GrollBen FabryPetra Bauer-KreiselTorsten BlunkPublished in: Cells (2021)
Biofabrication, including printing technologies, has emerged as a powerful approach to the design of disease models, such as in cancer research. In breast cancer, adipose tissue has been acknowledged as an important part of the tumor microenvironment favoring tumor progression. Therefore, in this study, a 3D-printed breast cancer model for facilitating investigations into cancer cell-adipocyte interaction was developed. First, we focused on the printability of human adipose-derived stromal cell (ASC) spheroids in an extrusion-based bioprinting setup and the adipogenic differentiation within printed spheroids into adipose microtissues. The printing process was optimized in terms of spheroid viability and homogeneous spheroid distribution in a hyaluronic acid-based bioink. Adipogenic differentiation after printing was demonstrated by lipid accumulation, expression of adipogenic marker genes, and an adipogenic ECM profile. Subsequently, a breast cancer cell (MDA-MB-231) compartment was printed onto the adipose tissue constructs. After nine days of co-culture, we observed a cancer cell-induced reduction of the lipid content and a remodeling of the ECM within the adipose tissues, with increased fibronectin, collagen I and collagen VI expression. Together, our data demonstrate that 3D-printed breast cancer-adipose tissue models can recapitulate important aspects of the complex cell-cell and cell-matrix interplay within the tumor-stroma microenvironment.
Keyphrases
- adipose tissue
- single cell
- insulin resistance
- cell therapy
- poor prognosis
- hyaluronic acid
- high fat diet
- gene expression
- endothelial cells
- stem cells
- metabolic syndrome
- type diabetes
- squamous cell carcinoma
- mesenchymal stem cells
- machine learning
- binding protein
- oxidative stress
- extracellular matrix
- low cost
- electronic health record
- high glucose