In living tissues, cell migration and growth occur within a three-dimensional, heterogeneous extracellular matrix (ECM), guided by biophysical and biochemical cues, such as interstitial fluid flow and cell-cell interactions. These factors regulate cell polarity, mechanotransduction, and coordinated movement, underpinning key biological processes including tissue repair and cancer invasion1,2,3,4.
Despite their importance, most in vitro migration assays, such as scratch and Transwell assays, evaluate single-cell movement on flat, static substrates. While simple and cost-effective, these 2D approaches poorly reproduce the structural and dynamic features of the in vivo microenvironment5,6. This limitation becomes particularly critical in the context of cancer metastasis, where tumor cells migrate collectively through mechanically and chemically diverse tissue matrices3,7,8. While 2D scratch assays remain popular as they are easy to perform, they do not reflect the complexity of the ECM or the effects of fluid flow6. Transwell-based approaches provide quantitative readouts, but only at fixed endpoints, preventing continuous observation of migration6,9.
Recent studies have shown that interstitial flow enhances metastatic potential, whereas ECM stiffness and composition promote epithelial-mesenchymal transition and collective migration4,10. More advanced 3D systems, such as spheroids and organoids, better approximate native ECM environments; however, their use is often constrained by variability, limited experimental accessibility, and difficulties in standardized analysis11,12. Microfluidic platforms offer superior control over mechanical and fluidic conditions, but their reliance on specialized fabrication methods and equipment limits their widespread use13. Hence, recreating these integrated cues in vitro in a controlled, accessible, non-invasive, and cost-effective manner remains a major challenge5,14.
To address those challenges and bridge the gap between conventional 2D assays and complex in vivo models, we developed a simple flow-enabled 3D cellular platform based on a silk fibroin sponge scaffold. The system employs a silk sponge with tunable mechanical properties as an ECM-like scaffold. Silk was selected for its porous structure, which allows gentle perfusion and supports physiologically relevant interstitial flow15. Its biocompatibility and established use in biomedical and tissue engineering make it a suitable material for this application. A recent publication further demonstrated the scaffold’s environmental sustainability and recycling potential16. In another study, we further showed their adaptability across different imaging modalities, such as positron emission tomography17. This prior work served as a foundation for the present methodology description, in which we build upon the same platform concept in a simplified in vivo optical imaging-based configuration. Together, these studies demonstrate the system's potential for multimodal imaging-based assessment of engineered tissue constructs and support its use as a versatile experimental platform for integrating in vitro culture and in vivo relevant readouts across different cancer cell models.
As a proof-of-concept, we cultured iRFP720-labeled 4T1 triple-negative breast cancer cells within the scaffold under two low-shear stress flow conditions for five days. Non-invasive in vivo optical imaging monitoring revealed distinct flow-directed growth patterns and significant changes in cell population dynamics compared with static controls. By emphasizing engineering simplicity and reproducibility, this model provides a practical bridge between 2D assays and in vivo studies, enabling researchers to examine, on a macroscopic scale and non-invasively, flow-mediated cellular characteristics in a physiologically relevant yet accessible format. Unlike prior methodologies that often rely on destructive endpoint analyses or lack standardized seeding criteria, this protocol introduces a systematic framework for optimizing scaffold production and, following that, cell seeding and imaging. This approach enhances experimental robustness and provides a more comprehensive, longitudinal view of collective cell dynamics within 3D matrices, representing a significant refinement over existing methods for monitoring growth and migration.