Organotypic 3D decellularized matrix tumor spheroids for high-throughput drug screening

• Main Author: Ferreira, Luís P.
• Publication Date: 2021
• Other Authors: Gaspar, Vítor M., Mendes, Luís, Duarte, Iola F., Mano, João F.
• Format: Article
• Language: eng
• Source: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
• Download full: http://hdl.handle.net/10773/34743
• topic: Breast cancer; Decellularized extracellular matrix; Preclinical drug screening; Spheroids

Decellularized extracellular matrix (dECM) is emerging as a valuable tool for generating 3D in vitro tumor models that better recapitulate tumor-stroma interactions. However, the development of dECM-3D heterotypic microtumors exhibiting a controlled morphology is yet to be materialized. Precisely controlling microtumors morphologic features is key to avoid an inaccurate evaluation of therapeutics performance during preclinical screening. To address this, herein we employed ultra-low adhesion surfaces for bioengineering organotypic 3D metastatic breast cancer-fibroblast models enriched with dECM microfibrillar fragments, as a bottom-up strategy to include major matrix components and their associated biomolecular cues during the early stages of 3D microtissue spheroids assembly, simulating pre-existing ECM presence in the in vivo setting. This biomimetic approach enabled the self-assembly of dECM-3D tumor-stroma spheroids with tunable size and reproducible morphology. Along time, dECM enriched and stroma-rich microtumors exhibited necrotic core formation, secretion of key biomarkers and higher cancer-cell specific resistance to different chemotherapeutics in comparison to standard spheroids. Exometabolomics profiling of dECM-Spheroid in vitro models further identified important breast cancer metabolic features including glucose/pyruvate consumption and lactate excretion, which suggest an intense glycolytic activity, recapitulating major hallmarks of the native microenvironment. Such organotypic dECM-enriched microtumors overcome the morphologic variability generally associated with cell-laden dECM models, while providing a scalable testing platform that can be foreseeable leveraged for high-throughput screening of candidate therapeutics.