ArticleCell reports2019
Methods for Systematic Identification of Membrane Proteins for Specific Capture of Cancer-Derived Extracellular Vesicles.
Article in Cell reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
24 citing papers in PubMed, 44 citations in OpenAlex.
- Surface Proteomics of Cancer-Derived Extracellular Vesicles Reveals Universal Heat Shock Proteins and Cancer Signatures.Molecular & cellular proteomics : MCP · 2026Article
- Advancing Extracellular Vesicle Research: A Review of Systems Biology and Multiomics Perspectives.Proteomics · 2026Review
- Monitoring glioblastoma extracellular vesicle evolution using a nanodiagnostic platform to detect glioma stem cells driving recurrent disease.Science advances · 2026Article
- Surface Proteome of Extracellular Vesicles and Correlation Analysis Reveal Breast Cancer Biomarkers.Cancers · 2024Article
- Review
- Lineage specific extracellular vesicle-associated protein biomarkers for the early detection of high grade serous ovarian cancer.Scientific reports · 2023Article
- Selective enrichment of plasma cell-free messenger RNA in cancer-associated extracellular vesicles.Communications biology · 2023Article
- Multiplexed analysis of EV reveals specific biomarker composition with diagnostic impact.Nature communications · 2023Article
- Theragnostic Applications of Mammal and Plant-Derived Extracellular Vesicles: Latest Findings, Current Technologies, and Prospects.Molecules (Basel, Switzerland) · 2022Review
- Liquid Biopsies: Flowing Biomarkers.Advances in experimental medicine and biology · 2022Article
- Multiplexed Profiling of Extracellular Vesicles for Biomarker Development.Nano-micro letters · 2021Review
- Proteomic dissection of large extracellular vesicle surfaceome unravels interactive surface platform.Journal of extracellular vesicles · 2021Article
- Review
- Emerging methods in biomarker identification for extracellular vesicle-based liquid biopsy.Journal of extracellular vesicles · 2021Review
- Article
- Biological Functions Driven by mRNAs Carried by Extracellular Vesicles in Cancer.Frontiers in cell and developmental biology · 2021Review
- Article
- Exosome-templated nanoplasmonics for multiparametric molecular profiling.Science advances · 2020Article
- From tumor microenvironment communicants to biomarker discovery: Selectively packaged extracellular vesicular cargoes in pancreatic cancer.Cytokine & growth factor reviews · 2020Review
- Characterizing Extracellular Vesicles and Their Diverse RNA Contents.Frontiers in genetics · 2020Review
Corrections and comments
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Authors and funding
17 authors at 6 institutions in 5 countries.
Funding
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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.