Analysis of cancer-derived extracellular vesicles (EVs) in biofluids potentially provides a source of disease biomarkers. At present there is no procedure to systematically identify which antigens should be targeted to differentiate cancer-derived from normal host cell-derived EVs. Here, we propose a computational framework that integrates information about membrane proteins in tumors and normal tissues from databases: UniProt, The Cancer Genome Atlas, the Genotype-Tissue Expression Project, and the Human Protein Atlas. We developed two methods to assess capture of EVs from specific cell types. (1) We used palmitoylated fluorescent protein (palmtdTomato) to label tumor-derived EVs. Beads displaying antibodies of interest were incubated with conditioned medium from palmtdTomato-expressing cells. Bound EVs were quantified using flow cytometry. (2) We also showed that membrane-bound Gaussia luciferase allows the detection of cancer-derived EVs in blood of tumor-bearing animals. Our analytical and validation platform should be applicable to identify antigens on EVs from any tumor type.
Pubmed ID: 30943406 RIS Download
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Collection of data of protein sequence and functional information. Resource for protein sequence and annotation data. Consortium for preservation of the UniProt databases: UniProt Knowledgebase (UniProtKB), UniProt Reference Clusters (UniRef), and UniProt Archive (UniParc), UniProt Proteomes. Collaboration between European Bioinformatics Institute (EMBL-EBI), SIB Swiss Institute of Bioinformatics and Protein Information Resource. Swiss-Prot is a curated subset of UniProtKB.
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