Current limitations in cancer research include pronounced intertumoral heterogeneity and a poor clinical translation of many candidate therapeutics, underscoring the need for more predictive preclinical platforms. While emerging in vitro systems have contributed to the development of personalized treatment strategies, they frequently fall short in reproducing the full biochemical and structural complexity of the tumor microenvironment, particularly the extracellular matrix (ECM), which plays a central role in tumor progression and therapy resistance.
In this work, we introduce advanced in vitro tumor models designed to more faithfully recapitulate microenvironmental features. These platforms integrate decellularized ECMs (dECMs) derived from skin and breast tissues with melanoma and breast cancer cells, respectively. In addition, we have recently expanded the system to incorporate breast tissue–derived organoids, enabling even more physiologically relevant modeling of patient specific tumor behavior. Comprehensive characterization of the dECMs confirmed their biological relevance and revealed key cell–matrix interactions. Using fluorescence confocal microscopy and surface enhanced Raman spectroscopy (SERS), we monitored cellular behavior within these 3D matrices, demonstrating the value of SERS for probing dynamic processes in complex tissue like environments.
Validation with multiple therapeutic compounds showed that these models can serve as robust predictive tools for drug screening and target discovery. Beyond their scientific impact, advancing precision oncology, supporting translational research, and reducing reliance on animal models, this project has also demonstrated strong industrial potential. The technology is now being developed into a dedicated spin off initiative aimed at enabling broader adoption within pharmaceutical R&D and accelerating the development of more effective cancer therapies.