Accumulation of Small-Size, Highly Dispersive Mesoporous Silica Nanoparticles in a Tumor in Both Chorioallantoic Membrane and Mouse Models

在绒毛尿囊膜和鼠模型中,小尺寸、高分散性介孔二氧化硅纳米颗粒均在肿瘤中积累

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Abstract

(1) Background: The chorioallantoic membrane (CAM) model has the potential to contribute to the development of personalized medicine based on individual cancer patients. We previously established the CAM model using patient-derived CIC-DUX4 sarcoma cells. We also used the CAM model for characterization and a comparison with the mouse model by examining the tumor accumulation of small-size, highly dispersive mesoporous silica nanoparticles (MSNs). (2) Method: In this study, we transplanted a variety of cancer cell lines, including patient-derived osteosarcoma (OS) and extraskeletal osteosarcoma (ESOS) cells. Patient-derived OS, ESOS and other cell lines were transplanted onto CAMs. The proliferation of cancer cells within CAM tumors was confirmed using H&E staining. For the comparison of the CAM and mouse models, rhodamine B-labeled MSNs were administered intravenously to CAMs and to xenograft mice. Tumor accumulation was evaluated by examining fluorescence and by confocal microscopy. The biodistribution of MSNs was examined by measuring the Si content by ICP. (3) Results: H&E staining demonstrated the proliferation of cancer cells of OS, ESOS and others on CAMs. While growth patterns and morphologies varied among different cancer types, H&E staining confirmed the establishment of tumors. As for the tumor accumulation, both the CAM and mouse models showed that MSNs were selectively accumulated in the tumors in both the CAM and mouse models. (4) Conclusions: We have expanded the range of CAM models by using a variety of cancer cells, including patient-derived cell lines. We also report that the small-size, highly dispersive MSNs exhibit excellent tumor accumulation in both the CAM and mouse models. These results point to the usefulness of the CAM model for patient-derived cancer cells as well as for evaluating drug carriers for tumor targeting.

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