Visualization of host-guest interactions driven bioorthogonal homing effects at the single cell level in vivo

The clinical translation of anticancer nanomedicine is highly limited thus far, due to their various non-specific accumulation and relatively low targeting efficiency in the tumor. Herein, we established a bioorthogonal targeting strategy that relies on high specific, supramolecular recognition between β-cyclodextrin-modified tumor cells and adamantane-modified nanomedicine. The host-guest interactions driven targeting process was visualized in vivo at the single-cell level for the first time. In this study, host-molecule modified cancer cells were implanted into transparent zebrafish embryos, followed by intravenous injection of guest-molecule modified nanomedicine. Fluorescence micrographs confirmed that the guest-modified liposomes could rapidly adhere onto the surface of host-modified melanoma cells, deliver doxorubicin after internalization, and subsequently induce apoptosis of cancer cells in zebrafish. In addition, host-modified liposomes that were injected shortly after guest-modified liposomes could accumulate in the tumor site together with guest-modified liposomes mediated via host-guest interactions, serving as a secondary drug delivery system. These data provides important, most direct evidence showing the host-guest interactions driven bioorthogonal homing effects in vivo . We reported a facile bioorthogonal homing strategy via supramolecular recognition between host-modified tumor cells and guest-modified nanomedicine. Skillfully using zebrafish tumor model, the targeting process and therapeutic effect were directly visualized in vivo at the single-cell level for the first time. • Establishment of host-guest interactions driven bioorthogonal homing system. • Visualization of supramolecular recognition of nanomedicine by in situ or metastatic cancer cells at single cell level. • Implantation of artificial receptor-modified cancer cells in zebrafish embryos. • Monitoring of cancer cell apoptosis in vivo . • Prediction of targeting efficiency in zebrafish tumor model.