TY - JOUR
T1 - Methods for Systematic Identification of Membrane Proteins for Specific Capture of Cancer-Derived Extracellular Vesicles
AU - Zaborowski, Mikołaj Piotr
AU - Lee, Kyungheon
AU - Na, Young Jeong
AU - Sammarco, Alessandro
AU - Zhang, Xuan
AU - Iwanicki, Marcin
AU - Cheah, Pike See
AU - Lin, Hsing Ying
AU - Zinter, Max
AU - Chou, Chung Yu
AU - Fulci, Giulia
AU - Tannous, Bakhos A.
AU - Lai, Charles Pin Kuang
AU - Birrer, Michael J.
AU - Weissleder, Ralph
AU - Lee, Hakho
AU - Breakefield, Xandra O.
N1 - Publisher Copyright:
© 2019 The Authors
PY - 2019/4/2
Y1 - 2019/4/2
N2 - 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. Cancer cell-derived extracellular vesicles (EVs) can be used in diagnostics, but their enrichment remains challenging. Zaborowski et al. identify membrane proteins enriched on the surface of cancer cells compared with normal tissues using TCGA, the Human Protein Atlas, and GTEx and present methods to measure immunocapture of cancer EVs in vitro and in animal models.
AB - 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. Cancer cell-derived extracellular vesicles (EVs) can be used in diagnostics, but their enrichment remains challenging. Zaborowski et al. identify membrane proteins enriched on the surface of cancer cells compared with normal tissues using TCGA, the Human Protein Atlas, and GTEx and present methods to measure immunocapture of cancer EVs in vitro and in animal models.
KW - Genotype-Tissue Expression Project
KW - Human Protein Atlas
KW - The Cancer Genome Atlas
KW - biomarker
KW - extracellular vesicles
KW - membrane proteins
KW - membrane-bound Gaussia luciferase
KW - palmitoylated fluorescent protein
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U2 - 10.1016/j.celrep.2019.03.003
DO - 10.1016/j.celrep.2019.03.003
M3 - Article
C2 - 30943406
AN - SCOPUS:85063470000
VL - 27
SP - 255-268.e6
JO - Cell Reports
JF - Cell Reports
IS - 1
ER -