This research demonstrates a novel imaging probe that detects β-galactosidase in ovarian cancer, suggesting improvements for diagnosis and therapy.
β-Galactosidase (β-gal), overexpressed in primary ovarian tumors, serves as an important biomarker for ovarian cancer. Accurate and sensitive detection of β-gal is crucial for cancer diagnosis and therapy. Activatable multimodal probes that show enhancement of multiplex imaging signals upon interaction with their specific molecular target have become powerful tools for rapid and precise imaging of biological processes. Nevertheless, the rational design of such probes remains challenging. Herein, a novel β-gal-activated probe, named Gal-Cy-Gd-F, was designed and synthesized for trimodal imaging of its activity in vivo. Upon activation by β-gal, the probe underwent a unique quinone methide-mediated self-immobilization mechanism that covalently anchored onto the target enzyme or neighboring proteins, thereby effectively prolonging its retention time. Consequently, the longitudinal relaxivity increased from 8.67 ± 0.5 mM⁻¹ s⁻¹ to 13.85 ± 0.2 mM⁻¹ s⁻¹ in solution under a 0.5 T nuclear magnetic resonance relaxometer, which was 3.7 times higher than commercial Gd-DOTA. Additionally, the fluorescence intensity and ¹⁹F magnetic resonance (MR) signal recovery are closely related to the β-gal concentration which can be quantified using the fluorescence method at low concentrations (0.02-0.1 U/mL) and the ¹⁹F MR method at high concentrations (0.2-0.8 U/mL), enabling highly sensitive, selective, background-free, and quantitative detection of β-gal activity in vitro. Furthermore, in vivo experiments demonstrated that Gal-Cy-Gd-F enables the precise monitoring of β-gal in mice, resulting in a remarkable increase in fluorescence intensity, a 33% enhancement in ¹H MR signal contrast, and significant recovery of ¹⁹F MR signal. This platform effectively overcomes the limitations of current ovarian cancer diagnostic methods, providing a powerful tool for early detection, precise intraoperative navigation, and therapeutic monitoring of ovarian cancer.
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Li et al. (2026) studied this question.
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