化学
体内
免疫疗法
癌症免疫疗法
细胞生物学
癌症
免疫系统
体外
肿瘤进展
表型
癌症治疗
癌症研究
免疫分型
肿瘤细胞
癌细胞
巨噬细胞极化
细胞凋亡
分化群
锡克
离体
细胞
免疫学
计算生物学
流式细胞术
作者
Haoze Li,Rui Qu,Linrong Chen,Min Wu,Wenya Zhou,Shaopeng Liu,Yu Liu,XiQun JIANG,Xu Zhen
摘要
The success of cancer immunotherapy is strongly influenced by the tumor immunophenotype, which is categorized as inflamed, immune-excluded, or immune-desert. However, noninvasively differentiating these key immunophenotypes to predict therapeutic outcomes remains a major challenge. Here, we report a fluorescence-afterglow reporter (FAR) for the real-time, in vivo differentiation of these three immunophenotypes. FAR operates on a dual-signal logic, simultaneously reporting on M1 macrophage polarization via a nitric oxide (NO)-responsive near-infrared fluorescence (NIRF) signal and on tumor cell apoptosis via a Caspase-3-activatable afterglow signal. This logical integration enables the accurate differentiation of inflamed [NIRF (ON)-Afterglow (ON)], immune-excluded [NIRF (ON)-Afterglow (OFF)], and immune-desert [NIRF (OFF)-Afterglow (OFF)] phenotypes in living mice. FAR also sensitively monitored the therapeutic conversion of an immune-excluded tumor to an inflamed state following combination therapy. Notably, FAR's signal patterns, whether from direct tumor imaging or a complementary urinalysis enabled by its renal-clearable design, strongly correlated with therapeutic outcomes, providing early predictive value for immunotherapy efficacy. Thus, this dual-signal logic probe provides functional insights into the tumor immune microenvironment, offering a powerful tool to guide the development and application of personalized cancer immunotherapy.
科研通智能强力驱动
Strongly Powered by AbleSci AI