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• W4383709885 abstract "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." @default.
• W4383709885 created "2023-07-11" @default.
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• W4383709885 date "2023-07-10" @default.
• W4383709885 modified "2023-10-15" @default.
• W4383709885 title "Comprehensive Detection of PD-L1 Protein and mRNA in Tumor Cells and Extracellular Vesicles through a Real-Time qPCR Assay" @default.
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• W4383709885 doi "https://doi.org/10.1021/acs.analchem.3c00975" @default.
• W4383709885 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/37424077" @default.
• W4383709885 hasPublicationYear "2023" @default.
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