免疫原性细胞死亡
癌症研究
肿瘤微环境
三阴性乳腺癌
免疫疗法
免疫系统
医学
免疫原性
光热治疗
癌症
免疫学
乳腺癌
材料科学
内科学
纳米技术
作者
Feng Yu,Yumei Xu,Zhaoyang Wen,Xin Ning,Jianlin Wang,Deping Wang,Ji-Min Cao,Xin Zhou
出处
期刊:Pharmaceutics
[Multidisciplinary Digital Publishing Institute]
日期:2023-04-21
卷期号:15 (4): 1309-1309
标识
DOI:10.3390/pharmaceutics15041309
摘要
Background: Triple-negative breast cancer (TNBC) was closely related to high metastatic risk and mortality and has not yet found a targeted receptor for targeted therapy. Cancer immunotherapy, especially photoimmunotherapy, shows promising potential in TNBC treatment because of great spatiotemporal controllability and non-trauma. However, the therapeutic effectiveness was limited by insufficient tumor antigen generation and the immunosuppressive microenvironment. Methods: We report on the design of cerium oxide (CeO2) end-deposited gold nanorods (CEG) to achieve excellent near-infrared photoimmunotherapy. CEG was synthesized through hydrolyzing of ceria precursor (cerium acetate, Ce(AC)3) on the surface of Au nanorods (NRs) for cancer therapy. The therapeutic response was first verified in murine mammary carcinoma (4T1) cells and then monitored by analysis of the anti-tumor effect in xenograft mouse models. Results: Under near-infrared (NIR) light irradiation, CEG can efficiently generate hot electrons and avoid hot-electron recombination to release heat and form reactive oxygen species (ROS), triggering immunogenic cell death (ICD) and activating part of the immune response. Simultaneously, combining with PD-1 antibody could further enhance cytotoxic T lymphocyte infiltration. Conclusions: Compared with CBG NRs, CEG NRs showed strong photothermal and photodynamic effects to destroy tumors and activate a part of the immune response. Combining with PD-1 antibody could reverse the immunosuppressive microenvironment and thoroughly activate the immune response. This platform demonstrates the superiority of combination therapy of photoimmunotherapy and PD-1 blockade in TNBC therapy.
科研通智能强力驱动
Strongly Powered by AbleSci AI