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  5. Self-Adaptive Photodynamic-to-Photothermal Switch for Smart Antitumor Photoimmunotherapy

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Article
en
2024

Self-Adaptive Photodynamic-to-Photothermal Switch for Smart Antitumor Photoimmunotherapy

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en
2024
Vol 18 (20)
Vol. 18
DOI: 10.1021/acsnano.4c01600

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Ben Zhong Tang
Ben Zhong Tang

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Yuewen Yu
Honglin Wang
Zeyan Zhuang
+8 more

Abstract

Photodynamic therapy (PDT) and photothermal therapy (PTT) possess different merits in cancer phototherapy, but the tumor microenvironment becomes unfavorable during the phototheranostic progress. Herein, we report a self-adaptive cyanine derivative Cy5-TPA with the PDT-dominated state to PTT-dominated state autoswitch feature for enhanced photoimmunotherapy. The incorporation of rotatable triphenylamine (TPA) moiety renders Cy5-TPA with the temperature or intramolecular-motion regulated photoactivities, which shows preferable reactive oxygen species (ROS) generation at lower temperature while stronger photothermal conversion at higher ones. Such a promising feature permits the in situ switch from PDT-dominated state to PTT-dominated state along with intratumoral temperature increase during laser irradiation, which also works in line with the concurrently reduced intratumoral oxygen level, exhibiting a self-adaptive phototherapeutic behavior to maximize the phototherapeutic antitumor outcome. Most importantly, the self-adaptive PDT-dominated state to PTT-dominated state switch also facilitates the sequential generation and release of damage-associated molecular patterns during immunogenic cell death (ICD). Hence, Cy5-TPA demonstrates excellent photoimmunotherapy performance in ICD induction, dendritic cell maturation, and T cell activation for tumor eradication and metastasis inhibition.

How to cite this publication

Yuewen Yu, Honglin Wang, Zeyan Zhuang, Chao Ji, Le Zhang, Yulu Li, Zujin Zhao, Dan Ding, Guangxue Feng, Ben Zhong Tang, Ben Zhong Tang (2024). Self-Adaptive Photodynamic-to-Photothermal Switch for Smart Antitumor Photoimmunotherapy. , 18(20), DOI: https://doi.org/10.1021/acsnano.4c01600.

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Publication Details

Type

Article

Year

2024

Authors

11

Datasets

0

Total Files

0

Language

en

DOI

https://doi.org/10.1021/acsnano.4c01600

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