肿瘤微环境
化学
癌症研究
光动力疗法
胰腺癌
一氧化氮
光敏剂
胰腺肿瘤
细胞外基质
免疫疗法
肿瘤缺氧
癌症免疫疗法
肿瘤进展
肿瘤相关巨噬细胞
巨噬细胞
细胞外
超氧化物
活性氮物种
缺氧(环境)
活性氧
免疫系统
癌细胞
癌症
外体
细胞生物学
成纤维细胞
微泡
生物物理学
敏化
细胞培养
作者
Shuyu Xu (1576927),Xinxin Xie (2104246),Ping He (33281),Shiwei Zhu (7504379),Xiaoda Li (1651270),Qingfeng Chen (21555),Xiaotu Ma (44228),Xiaolong Liang (1651279)
出处
期刊:
[Figshare (United Kingdom)]
日期:2025-02-06
标识
DOI:10.1021/acsnano.4c16329.s001
摘要
The treatment of pancreatic cancer faces significant challenges due to connective tissue hyperplasia and severe hypoxia. Unlike oxygen-dependent Type II photosensitizers, Type I photosensitizers can produce a substantial amount of reactive oxygen species, even under hypoxic conditions, making them more suitable for photodynamic therapy of pancreatic cancer. However, the dense extracellular matrix of pancreatic cancer limits the penetration efficiency of photosensitizers, and the presence of immunosuppressive cells in the tumor microenvironment reduces the therapeutic effect. To address these challenges, we designed the photoimmunotherapeutic M1@PAP nanoparticles composed of Type I photosensitizer and anti-PD-L1 siRNA (siPD-L1), which was encapsulated into M1 macrophage membrane vesicles. In this system, pyropheophorbide-a (PPA) was covalently conjugated to poly-l-arginine (Arg9). Notably, it was capable of generating sufficient superoxide anions under hypoxic conditions, thereby functioning as a Type I photosensitizer. Furthermore, Arg9 acted as a nitric oxide (NO) donor, enhancing the penetration efficiency of the nanophotosensitizer by inhibiting cancer-associated fibroblast (CAF) activation and decomposing the tumor extracellular matrix. Additionally, M1 macrophage membrane vesicles provided active targeting capabilities and reeducated immunosuppressed M2 macrophages. The reversal of immunosuppressive microenvironment further promoted the efficacy of anti-PD-L1 siRNA immunotherapy, showing great potential in synergistic photodynamic immunotherapy against hypoxic pancreatic tumor.
科研通智能强力驱动
Strongly Powered by AbleSci AI