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Photostable Cascade Activatable Peptide Self-assembly on a Cancer Cell Membrane for High-Performance Identification of Human Bladder Cancer.

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Missed or residual tumor burden results in high risk for bladder cancer relapse. However, existing fluorescent probes cannot meet the clinical needs because of inevitable photobleaching properties. Performance could be… Click to show full abstract

Missed or residual tumor burden results in high risk for bladder cancer relapse. However, existing fluorescent probes cannot meet the clinical needs because of inevitable photobleaching properties. Performance could be improved by maintaining intensive and sustained fluorescence signals via resistance to intraoperative saline flushing and intrinsic fluorescent decay, providing surgeons with sufficiently clear and high-contrast surgical fields, avoiding residual tumors or missed diagnosis. This study designs and synthesizes a photostable cascade-activatable peptide, a target reaction-induced aggregation peptide (TRAP) system, which can construct polypeptide-based nanofibers in situ on the cell membrane to achieve long-term and stable imaging of bladder cancer. The probe has two parts: a target peptide (TP) targets CD44v6 to recognize bladder cancer cells, and a reaction-induced aggregation peptide (RAP) was introduced and effectively reacted with TP via a click reaction to enhance the hydrophobicity of the whole molecule, assembling into nanofibers and further nanonetworks. Accordingly, probe retention on the cell membrane was prolonged, and photostability was significantly improved. Finally, the TRAP system is successfully employed in the high-performance identification of human bladder cancer in ex vivo bladder tumor tissues. This cascade-activatable peptide molecular probe based on the TRAP system enables efficient and stable imaging of bladder cancer. This article is protected by copyright. All rights reserved.

Keywords: bladder; cascade activatable; activatable peptide; bladder cancer; cancer

Journal Title: Advanced materials
Year Published: 2023

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