Comprehensive Detection of PD-L1 Protein and mRNA in Tumor Cells and Extracellular Vesicles through a Real-Time qPCR Assay

信使核糖核酸 化学 免疫系统 分子生物学 细胞外小泡 适体 微泡 癌症免疫疗法 免疫疗法 细胞生物学 癌症研究 基因 小RNA 生物 免疫学 生物化学
作者
Wenbo Peng,Danyang Sun,Wei Lü,Shenyi Yin,Buqing Ye,Xiaoqi Wang,Yongan Ren,Zichen Hong,Wenyu Zhu,Pengfei Yu,Jianzhong Xi,Bo Yao
出处
期刊:Analytical Chemistry [American Chemical Society]
卷期号:95 (28): 10625-10633 被引量:7
标识
DOI:10.1021/acs.analchem.3c00975
摘要

A growing number of studies have shown that tumor cells secrete extracellular vesicles (EVs) containing programmed death-ligand 1 (PD-L1) protein. These vesicles can travel to lymph nodes and remotely inactivate T cells, thereby evading immune system attack. Therefore, the simultaneous detection of PD-L1 protein expression in cells and EVs is of great significance in guiding immunotherapy. Herein, we developed a method based on qPCR for the simultaneous detection of PD-L1 protein and mRNA in EVs and their parental cells (PREC-qPCR assay). Lipid probes immobilized on magnetic beads were used to capture EVs directly from samples. For RNA assay, EVs were directly broken by heating and quantified with qPCR. As to protein assay, EVs were recognized and bound with specific probes (such as aptamers), which were used as templates in subsequent qPCR analysis. This method was used to analyze EVs of patient-derived tumor clusters (PTCs) and plasma samples from patients and healthy volunteers. The results revealed that the expression of exosomal PD-L1 in PTCs was correlated with tumor types and significantly higher in plasma-derived EVs from tumor patients than that of healthy individuals. When extended to cells and PD-L1 mRNAs, the results showed that the expression of PD-L1 protein was consistent with mRNA in cancer cell lines, while PTCs demonstrated significant heterogeneity. This comprehensive detection of PD-L1 at four levels (cell, EVs, protein, and mRNA) is believed to enhance our understanding of the relationship among PD-L1, tumors, and the immune system and to provide a promising tool for predicting the benefits of immunotherapy.
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