ArticlebioRxiv : the preprint server for biology2026
Patient-Derived Organoids as a Model to Understand Tumor Microenvironment-Driven Nano-Bio Interactions - A Framework Towards Improved Nanomedicine Translation.
Article in bioRxiv : the preprint server for biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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4 authors.
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Abstract
Nanomedicines that perform well in conventional cell cultures often fail to translate into patients, in part due to the inability to reproduce the protein corona, and hence the biological identity, that nanoparticles acquire within the tumor microenvironment (TME). Here, we establish patient-derived colonic organoids (PDCOs) as a platform for profiling nano-bio interactions under physiologically tumor-relevant conditions using graphene quantum dots (GQD) and Silicon Quantum Dots (SiQD) as material-distinct probes. By combining spectral flow cytometry, confocal imaging, dynamic light scattering, and multi-spectral dimension-reduction analysis of single-cell uptake, we resolve how nanoparticle identity, uptake, and intracellular fate diverge between conventional culture and patient tissue. Conventional two-dimensional culture overestimated internalization by two-fold relative to ex vivo PDCOs, while TME-specific proteins directed nanoparticles to distinct organoid subpopulations. Exploiting this, we engineer the protein corona with tumor-specific proteins to redirect SiQDs to chemoresistant cells, from 3.8% to 70%, an 18-fold increase in targeted delivery to the cells that drive therapy resistance. Internalization was also model-dependent. PDCOs and fibroblasts favored clathrin/dynamin (DNM1)-mediated endocytosis into lysosomes, whereas cancer cells favored caveolae (CAV1)-mediated entry that bypasses lysosomal degradation. This distinction determines whether a nanocarrier is degraded or delivered intact. Collectively, these findings turn the protein corona into a programmable design tool and establish PDCOs as a next-generation platform for precision nano-oncology.
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