Dataset Information

Methods for Systematic Identification of Membrane Proteins for Specific Capture of Cancer-Derived Extracellular Vesicles.

ABSTRACT: 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.

SUBMITTER: Zaborowski MP

PROVIDER: S-EPMC6528836 | biostudies-literature | 2019 Apr

REPOSITORIES: biostudies-literature

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Methods for Systematic Identification of Membrane Proteins for Specific Capture of Cancer-Derived Extracellular Vesicles.

Zaborowski Mikołaj Piotr MP Lee Kyungheon K Na Young Jeong YJ Sammarco Alessandro A Zhang Xuan X Iwanicki Marcin M Cheah Pike See PS Lin Hsing-Ying HY Zinter Max M Chou Chung-Yu CY Fulci Giulia G Tannous Bakhos A BA Lai Charles Pin-Kuang CP Birrer Michael J MJ Weissleder Ralph R Lee Hakho H Breakefield Xandra O XO

Cell reports 20190401 1

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 ...[more]

PMID: 30943406

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Dataset Information

Methods for Systematic Identification of Membrane Proteins for Specific Capture of Cancer-Derived Extracellular Vesicles.

Publications

Methods for Systematic Identification of Membrane Proteins for Specific Capture of Cancer-Derived Extracellular Vesicles.

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