4.8 Article

Spatial exosome analysis using cellulose nanofiber sheets reveals the location heterogeneity of extracellular vesicles

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NATURE COMMUNICATIONS
卷 14, 期 1, 页码 -

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NATURE PORTFOLIO
DOI: 10.1038/s41467-023-42593-9

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In this study, cellulose nanofiber (CNF) sheets were used to capture and preserve extracellular vesicles (EVs) for analysis of bioactive molecules inside EVs. The results showed that CNF sheets allowed for the detection of cancer-associated miRNAs in the early phase of ovarian cancer, even before the appearance of ascites. Furthermore, EVs from different locations exhibited unique miRNA profiles, and location-based differences in EV miRNA profiles were identified in patient samples, reflecting disease conditions. Spatial exosome analyses using CNF sheets revealed location-dependent heterogeneity of ascites EVs from cancer patients.
Extracellular vesicles (EVs), including exosomes, are recognized as promising functional targets involved in disease mechanisms. However, the intravital heterogeneity of EVs remains unclear, and the general limitation for analyzing EVs is the need for a certain volume of biofluids. Here, we present cellulose nanofiber (CNF) sheets to resolve these issues. We show that CNF sheets capture and preserve EVs from similar to 10 mu L of biofluid and enable the analysis of bioactive molecules inside EVs. By attaching CNF sheets to moistened organs, we collect EVs in trace amounts of ascites, which is sufficient to perform small RNA sequence analyses. In an ovarian cancer mouse model, we demonstrate that CNF sheets enable the detection of cancer-associated miRNAs from the very early phase when mice did not have apparent ascites, and that EVs from different locations have unique miRNA profiles. By performing CNF sheet analyses in patients, we identify further location-based differences in EV miRNA profiles, with profiles reflecting disease conditions. We conduct spatial exosome analyses using CNF sheets to reveal that ascites EVs from cancer patients exhibit location-dependent heterogeneity. This technique could provide insights into EV biology and suggests a clinical strategy contributing to cancer diagnosis, staging evaluation, and therapy planning.

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