Purification of HCC-specific extracellular vesicles on nanosubstrates for early HCC detection by digital scoring.
Aged
Biomarkers, Tumor
/ genetics
Carcinoma, Hepatocellular
/ blood
Case-Control Studies
Click Chemistry
/ instrumentation
Computational Chemistry
Computer Simulation
Diagnosis, Differential
Dimethylpolysiloxanes
/ chemistry
Disease Progression
Early Detection of Cancer
/ instrumentation
Extracellular Vesicles
/ genetics
Female
Hep G2 Cells
Humans
Lab-On-A-Chip Devices
Liquid Biopsy
/ instrumentation
Liver Cirrhosis
/ blood
Liver Neoplasms
/ blood
Male
Microfluidic Analytical Techniques
/ instrumentation
Middle Aged
Nanostructures
/ chemistry
Nanowires
/ chemistry
Neoplasm Staging
RNA, Messenger
/ genetics
ROC Curve
Reverse Transcriptase Polymerase Chain Reaction
/ instrumentation
Journal
Nature communications
ISSN: 2041-1723
Titre abrégé: Nat Commun
Pays: England
ID NLM: 101528555
Informations de publication
Date de publication:
07 09 2020
07 09 2020
Historique:
received:
13
12
2019
accepted:
06
08
2020
entrez:
8
9
2020
pubmed:
9
9
2020
medline:
2
10
2020
Statut:
epublish
Résumé
We report a covalent chemistry-based hepatocellular carcinoma (HCC)-specific extracellular vesicle (EV) purification system for early detection of HCC by performing digital scoring on the purified EVs. Earlier detection of HCC creates more opportunities for curative therapeutic interventions. EVs are present in circulation at relatively early stages of disease, providing potential opportunities for HCC early detection. We develop an HCC EV purification system (i.e., EV Click Chips) by synergistically integrating covalent chemistry-mediated EV capture/release, multimarker antibody cocktails, nanostructured substrates, and microfluidic chaotic mixers. We then explore the translational potential of EV Click Chips using 158 plasma samples of HCC patients and control cohorts. The purified HCC EVs are subjected to reverse-transcription droplet digital PCR for quantification of 10 HCC-specific mRNA markers and computation of digital scoring. The HCC EV-derived molecular signatures exhibit great potential for noninvasive early detection of HCC from at-risk cirrhotic patients with an area under receiver operator characteristic curve of 0.93 (95% CI, 0.86 to 1.00; sensitivity = 94.4%, specificity = 88.5%).
Identifiants
pubmed: 32895384
doi: 10.1038/s41467-020-18311-0
pii: 10.1038/s41467-020-18311-0
pmc: PMC7477161
doi:
Substances chimiques
Biomarkers, Tumor
0
Dimethylpolysiloxanes
0
RNA, Messenger
0
baysilon
63148-62-9
Types de publication
Journal Article
Observational Study
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
Validation Study
Langues
eng
Sous-ensembles de citation
IM
Pagination
4489Subventions
Organisme : NCI NIH HHS
ID : R01 CA246329
Pays : United States
Organisme : NCI NIH HHS
ID : U01 CA230705
Pays : United States
Organisme : NCI NIH HHS
ID : R21 CA216807
Pays : United States
Organisme : NIBIB NIH HHS
ID : U01 EB026421
Pays : United States
Organisme : NCI NIH HHS
ID : U01 CA198900
Pays : United States
Organisme : NCI NIH HHS
ID : R01 CA218356
Pays : United States
Organisme : NCI NIH HHS
ID : P30 CA016042
Pays : United States
Organisme : NCI NIH HHS
ID : R21 CA235340
Pays : United States
Organisme : NCI NIH HHS
ID : P01 CA233452
Pays : United States
Organisme : NCI NIH HHS
ID : R21 CA240887
Pays : United States
Organisme : NCI NIH HHS
ID : R01 CA253651
Pays : United States
Organisme : NCI NIH HHS
ID : R01 CA246304
Pays : United States
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