A Single-atom Manganese Nanozyme Mn-N/C Promotes Anti-tumor Immune Response via Eliciting Type I Interferon Signaling
收藏NIAID Data Ecosystem2026-05-01 收录
下载链接:
https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE249852
下载链接
链接失效反馈官方服务:
资源简介:
Tumor microenvironment (TME)-induced nanocatalytic therapy is a promising strategy for cancer treatment, but the low catalytic efficiency limits its therapeutic efficacy. Single-atom catalysts (SACs) are a new type of nanozyme with incredible catalytic efficiency. Here we construct a single-atom manganese (Mn)-N/C nanozyme. Mn-N/C catalyzes the conversion of cellular H2O2 to ∙OH through a Fenton-like reaction and enables the sufficient generation of reactive oxygen species (ROS), which induces immunogenic cell death (ICD) of tumor cells and significantly promotes CD8+T anti-tumor immunity. Moreover, RNA sequencing reveals that Mn-N/C treatment activates type I interferon (IFN) signaling which is critical for Mn-N/C-mediated anti-tumor immune response. Mechanistically, Mn-N/C-triggered releasing of cytosolic DNA from ICD tumor cells activates cGAS-STING pathway, consequently stimulating type I IFN induction. We propose a new promising single-atom nanozyme with extraordinary catalytic activity, which enhances anti-tumor immune response and exhibits synergistic therapeutic effects when combined with anti-PD-L1 blockade. Comparative gene expression profiling analysis of RNA-seq data for tumor tissues treated with saline or Mn-N/C
肿瘤微环境(Tumor microenvironment, TME)诱导的纳米催化治疗是一种极具潜力的癌症治疗策略,但其催化效率低下限制了治疗效果。单原子催化剂(Single-atom catalysts, SACs)是一类具备优异催化性能的新型纳米酶。本研究构建了一种单原子锰(Mn)-N/C纳米酶。Mn-N/C可通过类芬顿反应催化细胞内过氧化氢(H₂O₂)转化为羟基自由基(·OH),充分产生活性氧(Reactive oxygen species, ROS),进而诱导肿瘤细胞发生免疫原性细胞死亡(Immunogenic cell death, ICD),并显著促进CD8⁺T细胞介导的抗肿瘤免疫。此外,RNA测序(RNA sequencing)结果显示,Mn-N/C处理可激活I型干扰素(Type I interferon, IFN)信号通路,该通路对于Mn-N/C介导的抗肿瘤免疫应答至关重要。机制上,Mn-N/C触发免疫原性死亡的肿瘤细胞释放胞质DNA,进而激活cGAS-STING通路,最终诱导I型干扰素产生。本研究提出了一种具有优异催化活性的新型单原子纳米酶,其可增强抗肿瘤免疫应答,且与抗PD-L1阻断治疗联合使用时可发挥协同治疗效果。对经生理盐水或Mn-N/C处理的肿瘤组织的RNA测序数据进行比较基因表达谱分析。
创建时间:
2024-04-24



