Zivko, Cristina; Fuhrmann, Kathrin; Fuhrmann, Gregor; Luciani, Paola (2022). Tracking matricellular protein SPARC in extracellular vesicles as a non-destructive method to evaluate lipid-based antifibrotic treatments. Communications biology, 5(1), p. 1155. Springer Nature 10.1038/s42003-022-04123-z
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Uncovering the complex cellular mechanisms underlying hepatic fibrogenesis could expedite the development of effective treatments and noninvasive diagnosis for liver fibrosis. The biochemical complexity of extracellular vesicles (EVs) and their role in intercellular communication make them an attractive tool to look for biomarkers as potential alternative to liver biopsies. We developed a solid set of methods to isolate and characterize EVs from differently treated human hepatic stellate cell (HSC) line LX-2, and we investigated their biological effect onto naïve LX-2, proving that EVs do play an active role in fibrogenesis. We mined our proteomic data for EV-associated proteins whose expression correlated with HSC treatment, choosing the matricellular protein SPARC as proof-of-concept for the feasibility of fluorescence nanoparticle-tracking analysis to determine an EV-based HSCs' fibrogenic phenotype. We thus used EVs to directly evaluate the efficacy of treatment with S80, a polyenylphosphatidylcholines-rich lipid, finding that S80 reduces the relative presence of SPARC-positive EVs. Here we correlated the cellular response to lipid-based antifibrotic treatment to the relative presence of a candidate protein marker associated with the released EVs. Along with providing insights into polyenylphosphatidylcholines treatments, our findings pave the way for precise and less invasive diagnostic analyses of hepatic fibrogenesis.
Item Type: |
Journal Article (Original Article) |
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Division/Institute: |
08 Faculty of Science > Department of Chemistry, Biochemistry and Pharmaceutical Sciences (DCBP) |
UniBE Contributor: |
Zivko, Cristina, Luciani, Paola |
Subjects: |
500 Science > 570 Life sciences; biology 500 Science > 540 Chemistry 000 Computer science, knowledge & systems |
ISSN: |
2399-3642 |
Publisher: |
Springer Nature |
Language: |
English |
Submitter: |
Pubmed Import |
Date Deposited: |
01 Nov 2022 13:09 |
Last Modified: |
05 Dec 2022 16:27 |
Publisher DOI: |
10.1038/s42003-022-04123-z |
PubMed ID: |
36310239 |
BORIS DOI: |
10.48350/174382 |
URI: |
https://boris.unibe.ch/id/eprint/174382 |
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