Nonemissive Iridium(III) Solvent Complex as a Self-Reporting Photosensitizer for Monitoring Phototherapeutic Efficacy in a "Signal on" Mode.

Chemical & Biomedical Imaging Pub Date : 2024-08-01 eCollection Date: 2024-12-23 DOI:10.1021/cbmi.4c00042
Manping Qian, Ke Wang, Peng Yang, Yu Liu, Meng Li, Chengxiao Zhang, Honglan Qi
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引用次数: 0

Abstract

Photodynamic therapy (PDT) has long been receiving increasing attention for the minimally invasive treatment of cancer. The performance of PDT depends on the photophysical and biological properties of photosensitizers (PSs). The always-on fluorescence signal of conventional PSs makes it difficult to real-time monitor phototherapeutic efficacy in the PDT process. Therefore, functional PSs with good photodynamic therapy effect and self-reporting properties are highly desired. Here, two nonemissive iridium(III) solvent complexes, [(dfppy)2Ir(DMSO)]Cl (Ir-DMSO, dfppy = 2,4-difluorophenyl)pyridine, DMSO = dimethyl sulfoxide) and [(dfppy)2Ir(ACN)]Cl (Ir-ACN, ACN = acetonitrile) as PSs, were synthesized. Both of them exhibit intense high-energy absorption bands, low photoluminescence (PL) emission, and low dark toxicity. Thanks to the lower dark toxicity of Ir-DMSO, we chose it as a PS for further PDT. In this work, Ir-DMSO functions as a specific PL "signal on" PS for self-reporting therapeutic efficacy during its own PDT process. Colocalization experiments indicated that Ir-DMSO accumulated in the endoplasmic reticulum and mitochondria. Under light irradiation, Ir-DMSO not only exhibited the ability to kill cancer cells but also presented a "signal on" PL response toward cell death. During Ir-DMSO-induced PDT, cell death modality was further investigated and immunogenic cell death was revealed, in which main hallmarks, including ROS generation, upregulation of surface-exposed calreticulin, high-mobility group box 1, and adenosine triphosphate secretion, were observed. Thanks to the specific coordination reaction between Ir-DMSO and histidine (His)/His-containing proteins, the phototherapeutic efficacy can be monitored in real time without other signal probes. This work provides a new and promising strategy for the development of PSs with self-reporting ability, which is of great importance for imaging-guided PDT.

非发射型铱(III)溶剂配合物作为自报告光敏剂,在“信号开启”模式下监测光疗效果。
光动力疗法(PDT)作为肿瘤的微创治疗方法,一直受到越来越多的关注。PDT的性能取决于光敏剂(ps)的光物理和生物特性。常规PSs的荧光信号一直处于开启状态,这使得在PDT过程中难以实时监测光疗效果。因此,迫切需要具有良好光动力治疗效果和自我报告特性的功能性ps。本文合成了[(dfppy)2Ir(DMSO)]Cl (Ir-DMSO, dfppy = 2,4-二氟苯基)吡啶,DMSO =二甲亚砜)和[(dfppy)2Ir(ACN)]Cl (Ir-ACN, ACN =乙腈)两种非发射型铱(III)溶剂配合物。两者都具有强的高能吸收带、低的光致发光(PL)发射和低的暗毒性。由于Ir-DMSO的暗毒性较低,我们选择它作为进一步PDT的PS。在这项工作中,Ir-DMSO在其自身的PDT过程中作为PS上的特定PL“信号”,用于自我报告治疗效果。共定位实验表明,Ir-DMSO在内质网和线粒体中积累。在光照射下,Ir-DMSO不仅表现出杀死癌细胞的能力,而且对细胞死亡表现出“信号开启”的PL反应。在ir - dmso诱导的PDT过程中,我们进一步研究了细胞的死亡方式,揭示了免疫原性细胞死亡,其主要标志包括ROS的产生、表面暴露钙调蛋白的上调、高迁移率组1和三磷酸腺苷分泌。由于Ir-DMSO与组氨酸(His)/含His蛋白之间的特异性配位反应,可以在没有其他信号探针的情况下实时监测光疗效果。本研究为具有自我报告能力的PDT的发展提供了一条新的、有前景的策略,对成像引导PDT具有重要意义。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Chemical & Biomedical Imaging
Chemical & Biomedical Imaging 化学与生物成像-
CiteScore
1.00
自引率
0.00%
发文量
0
期刊介绍: Chemical & Biomedical Imaging is a peer-reviewed open access journal devoted to the publication of cutting-edge research papers on all aspects of chemical and biomedical imaging. This interdisciplinary field sits at the intersection of chemistry physics biology materials engineering and medicine. The journal aims to bring together researchers from across these disciplines to address cutting-edge challenges of fundamental research and applications.Topics of particular interest include but are not limited to:Imaging of processes and reactionsImaging of nanoscale microscale and mesoscale materialsImaging of biological interactions and interfacesSingle-molecule and cellular imagingWhole-organ and whole-body imagingMolecular imaging probes and contrast agentsBioluminescence chemiluminescence and electrochemiluminescence imagingNanophotonics and imagingChemical tools for new imaging modalitiesChemical and imaging techniques in diagnosis and therapyImaging-guided drug deliveryAI and machine learning assisted imaging
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