State Key Laboratory of Chemo/Biosensing and Chemometrics, College of Chemistry and Chemical Engineering, Hunan University, Changsha, Hunan 410082, China.
Anal Chem. 2024 Aug 20;96(33):13447-13454. doi: 10.1021/acs.analchem.4c01551. Epub 2024 Aug 9.
Small-molecule fluorescent probes have emerged as potential tools for cancer cell imaging-based diagnostic and therapeutic applications, but their limited selectivity and poor imaging contrast hinder their broad applications. To address these problems, we present the design and construction of a novel near-infrared (NIR) biotin-conjugated and viscosity-activatable fluorescent probe, named as , for selective recognition and imaging of cancer cells. The designed probe exhibited a NIR emission at 680 nm, with a substantial Stokes shift of 100 nm and remarkably sensitive responses toward viscosity changes in solution. Importantly, provided an evidently enhanced signal-to-noise ratio (SNR: 6.2) for the discrimination of cancer cells/normal cells, as compared with the control probe without biotin conjugation (SNR: 1.8). Moreover, we validated the capability of for dynamic monitoring of stimulated viscosity changes within cancer cells and employed for distinguishing breast cancer tissues from normal tissues in live mice with improved accuracy (SNR: 2.5) in comparison with the control probe (SNR: 1.8). All these findings indicated that the cancer-targeting and viscosity-activatable NIR fluorescent probe not only enables the mechanistic investigations of mitochondrial viscosity alterations within cancer cells but also holds the potential as a robust tool for cancer cell imaging-based applications.
小分子荧光探针已成为基于癌细胞成像的诊断和治疗应用的潜在工具,但它们的选择性有限,成像对比度差,限制了其广泛应用。为了解决这些问题,我们设计并构建了一种新型的近红外(NIR)生物素缀合的、粘度激活的荧光探针,命名为 ,用于选择性识别和成像癌细胞。设计的探针在 680nm 处表现出近红外发射,具有 100nm 的显著斯托克斯位移和对溶液中粘度变化的显著敏感响应。重要的是,与没有生物素缀合的对照探针(SNR:1.8)相比, 为癌细胞/正常细胞的区分提供了明显增强的信噪比(SNR:6.2)。此外,我们验证了 用于动态监测癌细胞内刺激的粘度变化的能力,并在活体小鼠中使用 用于区分乳腺癌组织和正常组织,与对照探针(SNR:1.8)相比,准确性得到了提高(SNR:2.5)。所有这些发现表明,这种靶向癌细胞和可激活粘度的近红外荧光探针不仅能够研究癌细胞内线粒体粘度变化的机制,而且有可能成为一种强大的基于癌细胞成像的应用工具。