靶向PD-L1的锝-99m标记放射性探针的研究进展
Research progress in technetium-99m labeled radioactive probes for PD-L1 imaging
许想 1茅译尹 1陆春雄 1谢敏浩1
作者信息
- 1. 南京医科大学药学院,江苏 南京 211166;国家卫生健康委员会核医学重点实验室,江苏省分子核医学重点实验室,江苏省原子医学研究所,江苏 无锡 214063
- 折叠
摘要
程序性死亡受体和程序性死亡配体(PD-1/PD-L1)通路免疫检查点抑制剂是肿瘤治疗的新方法,而且肿瘤PD-L1表达水平与这种免疫治疗的疗效密切相关.临床上以免疫组化法检测PD-L1的表达水平,但该方法是有创的,且 PD-L1在肿瘤部位的表达具有时空异质性,该方法不能全面的反映肿瘤PD-L1的表达情况.核医学分子影像技术可以无创、实时、动态、可视化监测机体内PD-L1的表达情况.锝-99m是单光子发射计算机断层扫描(SPECT)成像最常用的核素,具有价廉易得,能量和半衰期适中等特点,而SPECT是核医学最常用的影像设备,在全球范围内应用广泛.因此,靶向PD-L1的锝-99m标记分子探针有着广阔的应用前景.本文主要针对靶向PD-L1的锝-99m标记分子探针的研究进行综述,为寻找新型靶向PD-L1的SPECT显像探针提供指导.
Abstract
Immune checkpoint inhibitors that target the programmed death receptor(PD-1)and its ligand(PD-L1)pathway have emerged as a promising strategy for cancer therapy.The expression level of PD-L1 in tumors is strongly correlated with the effectiveness of this form of immunotherapy.Clinically,PD-L1 expression is typically evaluated through immunohistochemistry,an invasive technique that has significant limitations due to the spatial and temporal heterogeneity of PD-L1 expression within tumor tissues.Consequently,this method may not provide a comprehensive assessment of PD-L1 expression.In contrast,molecular imaging techniques in nuclear medicine offer a non-invasive,real-time,and dynamic means of visualizing PD-L1 expression.Technetium-99m is the most commonly used radionuclide for single-photon emission computed tomography(SPECT)imaging,as it is inexpensive,easily available,and possesses suitable energy and half-life characteristics.SPECT is the most frequently employed imaging modality in nuclear medicine globally.Accordingly,technetium-99m-labeled molecular probes targeting PD-L1 hold significant potential for widespread clinical application.This review aims to summarize current advancements in the development of technetium-99m-labeled molecular probes for PD-L1 to guide future efforts to identify novel probes for SPECT imaging of PD-L1.
关键词
锝-99m/PD-L1/单克隆抗体/肽/小分子/SPECTKey words
technetium-99m/PD-L1/monoclonal antibody/peptide/small molecule/SPECT引用本文复制引用
出版年
2024
国家科技期刊平台
NSTL
万方数据