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Identification of Tumor‐Specific Surface Proteins Enables Quantification of Extracellular Vesicle Subtypes for Early Detection of Pancreatic Ductal Adenocarcinoma
AbstractPancreatic ductal adenocarcinoma (PDAC) is a leading cause of cancer‐related mortality, largely due to late‐stage diagnosis. Reliable early detection methods are critically needed. PDAC‐derived extracellular vesicles (EVs) carry molecules that reflect their parental tumor cells and are detectable in early disease stages, offering a promising noninvasive diagnostic approach. Here, a streamlined PDAC EV Surface Protein Assay for quantifying PDAC EV subpopulations in 300‐µL plasma through a two‐step workflow is presented: i) click chemistry‐mediated EV enrichment using EV Click Beads and trans‐cyclooctene‐grafted antibodies targeting three PDAC EV‐specific surface proteins (MUC1, EGFR, and TROP2), and ii) quantification of enriched PDAC EVs through reverse transcription‐quantitative polymerase chain reaction. The three PDAC EV‐specific surface proteins are identified using a bioinformatics framework and validated on PDAC cell lines and tissue microarrays. The resultant PDAC EV Score, derived from signals of the three PDAC EV subpopulations, demonstrates robust differentiation of PDAC patients from noncancer controls, with area under the receiver operating characteristic curves of 0.94 in the training (n = 124) and 0.93 in the validation (n = 136) cohorts. This EV‐based diagnostic approach successfully exploits PDAC EV subpopulations as novel biomarkers for PDAC early detection, translating PDAC surface proteins into an EV‐based liquid biopsy platform.
Identification of Tumor‐Specific Surface Proteins Enables Quantification of Extracellular Vesicle Subtypes for Early Detection of Pancreatic Ductal Adenocarcinoma
AbstractPancreatic ductal adenocarcinoma (PDAC) is a leading cause of cancer‐related mortality, largely due to late‐stage diagnosis. Reliable early detection methods are critically needed. PDAC‐derived extracellular vesicles (EVs) carry molecules that reflect their parental tumor cells and are detectable in early disease stages, offering a promising noninvasive diagnostic approach. Here, a streamlined PDAC EV Surface Protein Assay for quantifying PDAC EV subpopulations in 300‐µL plasma through a two‐step workflow is presented: i) click chemistry‐mediated EV enrichment using EV Click Beads and trans‐cyclooctene‐grafted antibodies targeting three PDAC EV‐specific surface proteins (MUC1, EGFR, and TROP2), and ii) quantification of enriched PDAC EVs through reverse transcription‐quantitative polymerase chain reaction. The three PDAC EV‐specific surface proteins are identified using a bioinformatics framework and validated on PDAC cell lines and tissue microarrays. The resultant PDAC EV Score, derived from signals of the three PDAC EV subpopulations, demonstrates robust differentiation of PDAC patients from noncancer controls, with area under the receiver operating characteristic curves of 0.94 in the training (n = 124) and 0.93 in the validation (n = 136) cohorts. This EV‐based diagnostic approach successfully exploits PDAC EV subpopulations as novel biomarkers for PDAC early detection, translating PDAC surface proteins into an EV‐based liquid biopsy platform.
Identification of Tumor‐Specific Surface Proteins Enables Quantification of Extracellular Vesicle Subtypes for Early Detection of Pancreatic Ductal Adenocarcinoma
Advanced Science
Zhao, Chen (Autor:in) / Wang, Zhili (Autor:in) / Kim, Hyoyong (Autor:in) / Kong, Hui (Autor:in) / Lee, Junseok (Autor:in) / Yang, Jacqueline Ziqian (Autor:in) / Wang, Anmin (Autor:in) / Zhang, Ryan Y. (Autor:in) / Ju, Yong (Autor:in) / Kim, Jina (Autor:in)
25.03.2025
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
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