Tumor microenvironment (TME)‐responsive intelligent photodynamic therapy (PDT) systems have attracted increasing interest in anticancer therapy, due to their potential to address significant and unsatisfactory therapeutic issues, such as limited tissue penetration, inevitable normal tissue damage, and excessive impaired vessels. Here, an H2O2‐triggered intelligent LCL/ZnO PDT nanodelivery system is elaborately designed. LCL/ZnO can selectively regulate tumor‐derived endothelial cells (TECs) and specifically kill tumor cells, by responding to different H2O2 gradients in TECs and tumor cells. The LCL/ZnO is able to normalize tumor vessels, thereby resulting in decreased metastases, and ameliorating the immunosuppressive TME. Further analysis demonstrates that singlet oxygen (1O2)‐activated transient receptor potential vanilloid‐4‐endothelial nitric oxide synthase signals generated in TECs by LCL/ZnO induce tumor vascular normalization, which is identified as a novel mechanism contributing to the increased ability of PDT to promote cancer therapy. In conclusion, designing an intelligent PDT nanodelivery system response to the TME, that includes both selective TECs regulation and specific tumor‐killing, will facilitate the development of effective interventions for future clinical applications.
Introduction: Because tumor-associated inflammation is a hallmark of cancer treatment, in the present study, sorafenib mesoporous silica nanomatrix (MSNM@SFN) co-administrated with flufenamic acid (FFA, a non-steroidal anti-inflammatory drug (NSAID)) was investigated to enhance the anti-tumor activity of MSNM@SFN. Methods: Metastatic breast tumor 4T1/luc cells and hepatocellular carcinoma HepG2 cells were selected as cell models. The effects of FFA in vitro on cell migration, PGE2 secretion, and AKR1C1 and AKR1C3 levels in 4T1/luc and HepG2 cells were investigated. The in vivo anti-tumor activity of MSNM@SFN co-administrating with FFA (MSNM@SFN +FFA) was evaluated in a 4T1/luc metastatic tumor model, HepG2 tumor-bearing nude mice model, and HepG2 orthotopic tumor-bearing nude mice model, respectively. Results: The results indicated that FFA could markedly decrease cell migration, PGE2 secretion, and AKR1C1 and AKR1C3 levels in both 4T1/luc and HepG2 cells. The enhanced anti-tumor activity of MSNM@SFN+FFA compared with that of MSNM@SFN was confirmed in the 4T1/luc metastatic tumor model, HepG2 tumor-bearing nude mice model, and HepG2 orthotopic tumor-bearing nude mice model in vivo, respectively. Discussion: MSNM@SFN co-administrating with FFA (MSNM@SFN+FFA) developed in this study is an alternative strategy for improving the therapeutic efficacy of MSNM@SFN via co-administration with NSAIDs.
Background: An ultrasound image tracking algorithm (UITA) was combined with four-dimensional computed tomography (4DCT) to create a real-time tumor motion-conversion model. The real-time position of a lung tumor phantom based on the real-time diaphragm motion trajectories detected by ultrasound imaging in the superior-inferior (SI) and medial-lateral (ML) directions were obtained.Methods: Three different tumor motion-conversion models were created using a respiratory motion simulation system (RMSS) combined with 4DCT. The tumor tracking error was verified using cone-beam computed tomography (CBCT). The tumor motion-conversion model was produced by using the UITA to monitor the motion trajectories of the diaphragm phantom in the SI direction, and using 4DCT to monitor the motion trajectories of the tumor phantom in the SI and ML directions over the same time period, to obtain parameters for the motion-conversion model such as the tumor center position and the amplitude and phase ratios.Results: The tumor movement was monitored for 90 s using CBCT to determine the real motion trajectories of the tumor phantom and using ultrasound imaging to simultaneously record the diaphragm movement. The absolute error of the motion trajectories of the real and estimated tumor varied between 0.5 and 2.1 mm in the two directions.Conclusions: This study has demonstrated the feasibility of using ultrasound imaging to track diaphragmatic motion combined with a 4DCT tumor motion-conversion model to track tumor motion in the SI and ML directions. The proposed method makes tracking a lung tumor feasible in real time, including under different breathing conditions.
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