A NIR ratiometric fluorescent biosensor for sensitive detection and imaging of α‐L‐fucosidase in living cells and HCC tumor‐bearing mice. Issue 2 (23rd October 2022)

• Record Type: Journal Article
• Authors: Zhang, Guo‐Qiang; Feng, Weiwei; Gao, Zhiyuan; Zhang, Gao‐Lan; Wu, Xinying; Xiao, Yating; Li, Xun; Zheng, Lei; Ding, Dan; Guo, Jianshuang; Situ, Bo
• Is Part Of: Aggregate. Volume 4:Issue 2(2023)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2022-10-23
• Subjects: cell and tumor imaging -- NIR fluorescent nanoprobe -- α‐L‐fucosidase; Aggregation (Chemistry) -- Periodicals; Aggregation (Chemistry); Periodicals; 539.6
• DOI: 10.1002/agt2.286
• Languages: English
• ISSNs: 2692-4560

Abstract

Abstract: Detection and imaging of α‐L‐fucosidase (AFU) is of great value to understand its roles in hepatocellular carcinoma (HCC) and tumor early diagnosis, but ideal assays are still lacking. Herein, a near‐infrared (NIR) fluorescent biosensor (α‐Fuc‐DCM) was elaborately designed and synthesized for rapid and ratiometric detection of AFU activity in cells and HCC tumor mouse models. In the presence of AFU, this biosensor shows an enhancement in NIR emission in a ratiometric manner, which significantly improves the detection accuracy with the limit of detection as low as 4.8 mU/mL. Taking advantage of these merits, the activity of AFU in lysosomes could be visualized using ratiometric and NIR dual modality in living cells. Furthermore, its remarkable application for monitoring of endogenous AFU activity in HCC tumor‐bearing mouse model is also demonstrated with bright fluorescence signal, which indicated that the biosensor could clearly monitor the liver tumor in the early stage. Importantly, the α‐Fuc‐DCM probe can be utilized to detect the AFU in serum from HCC patients. This strategy offers a promising biosensor system for early diagnosis of HCC and studying the roles of AFU in cancers. Abstract : The NIR ratiometric α‐Fuc‐DCM nanoprobe could rapidly and sensitivity detect AFU activity in cells and HCC tumor mouse models.