A Fluorescence-Afterglow Reporter for In Vivo Differentiation of Three Tumor Immunophenotypes

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.

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Publication Details

Journal
Journal of the American Chemical Society
Published
2025-12-23
DOI
https://doi.org/10.1021/jacs.5c17176
Citations
1
Primary Topic
Nanoplatforms for cancer theranostics
Type
article
Field-Weighted Citation Impact
0.67
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article

A Fluorescence-Afterglow Reporter for In Vivo Differentiation of Three Tumor Immunophenotypes

Rui Qu, XiQun JIANG, Mingda Wu, Linrong Chen et al.
1 citations
Journal of the American Chemical Society
Nanoplatforms for cancer theranostics
0.67
article

A Fluorescence-Afterglow Reporter for In Vivo Differentiation of Three Tumor Immunophenotypes

Rui Qu, XiQun JIANG, Mingda Wu, Linrong Chen, Haoze Li, Wenya Zhou, Shaopeng Liu, Xu Zhen, Yu Liu
article en
1 citations

Abstract

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.

Journal of the American Chemical SocietyVol. 148(1)
Nanjing University (CN)
Openalex Percentile: Top 23%
Nanoplatforms for cancer theranostics
0.67
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A Fluorescence-Afterglow Reporter for In Vivo Differentiation of Three Tumor Immunophenotypes — Rui Qu, XiQun JIANG, et al. · Journal of the American Chemical Society (2025) | TGRS Research Map | TGRS