A unimolecular near-infrared fluorescent probe for <i>in vivo</i> imaging of enzymes with minimized false-negative signals

Accurate imaging of specific enzymes is critical for the early diagnosis of ovarian cancer; however, conventional imaging agents often produce false-negative signals due to the heterogeneous expression of individual biomarkers, leading to delayed treatment and increased risk of disease progression. To address this limitation, we present Cy-GGT-β-gal, a unimolecular near-infrared (NIR) fluorescent probe engineered for the simultaneous detection of two key ovarian cancer biomarkers: γ-glutamyl transpeptidase (GGT) and β-galactosidase (β-gal). This dual-enzyme-responsive probe is designed to activate NIR fluorescence upon interaction with either GGT or β-gal through an intramolecular elimination mechanism, thereby significantly minimizing the likelihood of false-negative results. Compared to single-enzyme-targeting probes, Cy-GGT-β-gal demonstrates superior diagnostic reliability, enabling high-contrast discrimination (signal-to-noise ratio, SNR > 6.1) between multiple ovarian cancer cell lines (SHIN3, OVCAR3, OVCAR5, A2780, SKOV3) and normal cells. Furthermore, the probe successfully visualizes tumor lung metastases and nodular tissues with high specificity (SNR ∼ 11.2), underscoring its potential for precise <i>in vivo</i> imaging. This study not only introduces a robust unimolecular NIR fluorescent probe to mitigate false-negative diagnoses in ovarian cancer but also establishes a versatile design strategy for developing multi-enzyme-responsive imaging agents, offering a promising approach to enhance diagnostic accuracy in clinical settings.

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Publication Details

Journal
Chemical Science
Published
2025-12-05
DOI
https://doi.org/10.1039/d5sc07381b
Citations
1
Primary Topic
Nanoplatforms for cancer theranostics
Type
article
Field-Weighted Citation Impact
0.67

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article

A unimolecular near-infrared fluorescent probe for in vivo imaging of enzymes with minimized false-negative signals

Chengyuan Lv, Xiaojun Peng, Jinliang Han, Mingwang Yang et al.
1 citations
Chemical Science
Nanoplatforms for cancer theranostics
0.67
article

A unimolecular near-infrared fluorescent probe for in vivo imaging of enzymes with minimized false-negative signals

Chengyuan Lv, Xiaojun Peng, Jinliang Han, Mingwang Yang, Jiangli Fan, Kang Li
article en
1 citations

Abstract

Accurate imaging of specific enzymes is critical for the early diagnosis of ovarian cancer; however, conventional imaging agents often produce false-negative signals due to the heterogeneous expression of individual biomarkers, leading to delayed treatment and increased risk of disease progression. To address this limitation, we present Cy-GGT-β-gal, a unimolecular near-infrared (NIR) fluorescent probe engineered for the simultaneous detection of two key ovarian cancer biomarkers: γ-glutamyl transpeptidase (GGT) and β-galactosidase (β-gal). This dual-enzyme-responsive probe is designed to activate NIR fluorescence upon interaction with either GGT or β-gal through an intramolecular elimination mechanism, thereby significantly minimizing the likelihood of false-negative results. Compared to single-enzyme-targeting probes, Cy-GGT-β-gal demonstrates superior diagnostic reliability, enabling high-contrast discrimination (signal-to-noise ratio, SNR > 6.1) between multiple ovarian cancer cell lines (SHIN3, OVCAR3, OVCAR5, A2780, SKOV3) and normal cells. Furthermore, the probe successfully visualizes tumor lung metastases and nodular tissues with high specificity (SNR ∼ 11.2), underscoring its potential for precise <i>in vivo</i> imaging. This study not only introduces a robust unimolecular NIR fluorescent probe to mitigate false-negative diagnoses in ovarian cancer but also establishes a versatile design strategy for developing multi-enzyme-responsive imaging agents, offering a promising approach to enhance diagnostic accuracy in clinical settings.

Chemical ScienceVol. 17(5)
Dalian University of Technology (CN), Dalian University (CN), Liaoning Ocean and Fisheries Research Institute (CN)
National Natural Science Foundation of China, Fundamental Research Funds for the Central Universities
Openalex Percentile: Top 24%
Nanoplatforms for cancer theranostics
0.67
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