Harnessing oxidized alginate microgels for rapid and self-assembling 3D tissue organogenesis In vitro and In vivo

Engineering physiologically relevant 3D tissues and disease models is frequently hindered by residual biomaterials that obstruct critical cell-cell interactions and cellular condensation. To overcome this, we present a dynamic bioengineering platform utilizing self-degrading oxidized alginate (OA) microgels to facilitate rapid cellular self-assembly and complex 3D tissue organogenesis. The core mechanism relies on controlled oxidation (e.g., 5% OA), providing initial mechanical support for high-density cell encapsulation before rapidly self-degrading in culture. This programmed degradation eliminates physical barriers, driving spontaneous cellular condensation, robust intercellular connectivity, and structural remodeling. We validated this modeling technique across two diverse applications: regenerative organogenesis and aggressive cancer. First, for craniofacial regeneration, embryonic dental epithelial and mesenchymal cells were encapsulated in OA microgels. Rapid degradation promoted vital epithelial-mesenchymal interactions (EMI) and 3D tissue formation in vitro. Subsequent in vivo transplantation yielded functional host integration, robust vascularization, and bone organogenesis within two weeks. Second, we modeled glioblastoma (GBM) invasion by engineering tumor-host assembloids. OA-encapsulated GBM cells rapidly self-aggregated and integrated with dorsal forebrain organoids. This degradation-driven assembly induced strong cell adhesion, nuclear compaction, and massive tumor infiltration into host tissues. Transcriptomic profiling revealed upregulated integrin clustering, mechanosensing, and PI3K-AKT-mTOR signaling, accurately reflecting the invasive shift and niche remodeling confirmed in vivo. Ultimately, by harnessing transient biomaterial degradation to drive cellular condensation, this scalable OA platform effectively recapitulates complex 3D architectures for regenerative medicine and oncological modeling.