Rapid tumor detection via a fibroblast activation protein-alpha activated fluorogenic probe
Fibroblast activation protein-alpha (FAPα) is an extensively known serine protease that participates in various important physiological processes and found to be highly related to tumor progression and invasion, and its high expression level in various human epithelial carcinomas makes it a potentia...
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Veröffentlicht in: | Dyes and pigments 2023-11, Vol.219, p.111606, Article 111606 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | Fibroblast activation protein-alpha (FAPα) is an extensively known serine protease that participates in various important physiological processes and found to be highly related to tumor progression and invasion, and its high expression level in various human epithelial carcinomas makes it a potential cancer biomarker. However, as a tumor-specific expression enzyme, only a few fluorescent probes targeting FAPα have been reported, and most of these probes possess either a low emission window or a short Stokes shift, which severely obstructs their application in tissue imaging. Thus, it is an urgent need to acquire more suitable FAPα-targeted fluorescent probes for cancer identification.
Herein, by incorporating a previously reported fluorophore that possesses a large Stokes shift (>190 nm) and long emission window (650–700 nm) with a specific recognition unit (N-acylated-glycine-proline, Ac-GP) for FAPα, we acquired a “turn-on” biosensor named TMN-AcGP for FAPα activity sensing. Owing to the high sensitivity and improved optical properties of the newly developed fluorescent probe, in vitro cultured cancer cells and ex vivo dissected tumor tissues were successfully detected and distinguished from normal cells and tissues with a high tumor-to-normal ratio rapidly and accurately.
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•A highly specific fluorescent probe (TMN-AcGP) for FAPα sensing was reported.•TMN-AcGP could distinguish tumor cells from normal cells with high contrast.•Ex vivo tumor tissues could be detected rapidly using TMN-AcGP based imaging. |
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ISSN: | 0143-7208 1873-3743 |
DOI: | 10.1016/j.dyepig.2023.111606 |