Therapeutic Effect of Bone Marrow Mesenchymal Stem Cells on Rat Bladder Cancer

Abstract

Objective: To analyze the effect of bone marrow mesenchymal stem cell therapy on rats with bladder cancer and provide a feasible direction for the treatment of human bladder cancer. Methods: An animal model was constructed, and Model 1 was used as an example. Two groups of rats were injected with anti-upconversion nanoparticles (UCNPs) (experimental group) and 0.9% normal saline (control group), respectively. In vivo imaging was performed to determine the accuracy of the anti-UCNPs method. Results: There were 15 rats in the experimental group with obvious bladder swelling. Among them, 11 rats had cauliflower-like and partially brown bladder tumors, whereas the other four rats had hard, nodular-like protrusions, with indistinct borders and adhesions to the anterior wall of the rectum. Small papillary masses were observed in two rats, local mucosal thickening without tumor formation was observed in two rats, and bladder stones were observed in six rats. The bladder specimens of 15 rats in the control group were pink and shiny, without any tumors. Fourteen rats in the experimental group and 12 rats in the control group had bladder cancer lesions, accounting for 93.33% and 80%, respectively. The detection accuracy of the experimental group was significantly better than that of the control group. Conclusion: Multimodal nanoprobes targeting bladder cancer stem cells in vivo were used to image the orthotopic tumor and lymph node metastasis models of animals by anti-UCNPs imaging to observe the distribution, migration, and differentiation process of bladder cancer stem cells in model mice. It is clear that rare earth upconversion luminescent nanomaterials, modified by BCMab1 and CD44 monoclonal antibodies, can be used as probes for the detection of bladder cancer, the tracking of lymph node metastasis in bladder cancer, and the comprehensive evaluation of the overall efficacy of nanoprobe-targeted therapy for bladder cancer stem cells.