FRET imaging of glycoRNA on small extracellular vesicles enabling sensitive cancer diagnostics

Abstract Glycosylated RNAs (glycoRNAs), a recently discovered class of membrane-associated glyco-molecules, remain poorly understood in function and clinical value due to limited detection methods. Here, we show a dual recognition Förster resonance energy transfer (drFRET) strategy using nucleic aci...

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Main Authors: Tingju Ren, Yingzhi Zhang, Yuxiao Tong, Qi Zhang, Tianhao Wang, Yue Wang, Chunguang Yang, Zhangrun Xu
Format: Article
Language:English
Published: Nature Portfolio 2025-04-01
Series:Nature Communications
Online Access:https://doi.org/10.1038/s41467-025-58490-2
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author Tingju Ren
Yingzhi Zhang
Yuxiao Tong
Qi Zhang
Tianhao Wang
Yue Wang
Chunguang Yang
Zhangrun Xu
author_facet Tingju Ren
Yingzhi Zhang
Yuxiao Tong
Qi Zhang
Tianhao Wang
Yue Wang
Chunguang Yang
Zhangrun Xu
author_sort Tingju Ren
collection DOAJ
description Abstract Glycosylated RNAs (glycoRNAs), a recently discovered class of membrane-associated glyco-molecules, remain poorly understood in function and clinical value due to limited detection methods. Here, we show a dual recognition Förster resonance energy transfer (drFRET) strategy using nucleic acid probes to detect N-acetylneuraminic acid-modified RNAs, enabling sensitive, selective profiling of glycoRNAs on small extracellular vesicles (sEVs) from minimal biofluids (10 μl initial biofluid). Using drFRET, we identify 5 prevalent sEV glycoRNAs derived from 7 cancer cell lines. In a 100-patient cohort (6 cancer types and non-cancer controls), sEV glycoRNA profiles achieve 100% accuracy (95% confidence interval) in distinguishing cancers from non-cancer cases and 89% accuracy in classifying specific cancer types. Furthermore, drFRET reveal that sEV glycoRNAs specifically interact with Siglec proteins and P-selectin, which is critical for sEV cellular internalization. The drFRET strategy provides a versatile and sensitive platform for the imaging and functional analysis of sEV glycoRNAs, with promising implications for clinical applications.
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spelling doaj-art-b097ca4be60145e8b65b2ac07ad1f1c82025-08-20T03:10:13ZengNature PortfolioNature Communications2041-17232025-04-0116111910.1038/s41467-025-58490-2FRET imaging of glycoRNA on small extracellular vesicles enabling sensitive cancer diagnosticsTingju Ren0Yingzhi Zhang1Yuxiao Tong2Qi Zhang3Tianhao Wang4Yue Wang5Chunguang Yang6Zhangrun Xu7Research Center for Analytical Sciences, Department of Chemistry, College of Sciences, Northeastern UniversityNational Clinical Research Center for Laboratory Medicine, Department of Laboratory Medicine, The First Affiliated Hospital of China Medical UniversityResearch Center for Analytical Sciences, Department of Chemistry, College of Sciences, Northeastern UniversityResearch Center for Analytical Sciences, Department of Chemistry, College of Sciences, Northeastern UniversityResearch Center for Analytical Sciences, Department of Chemistry, College of Sciences, Northeastern UniversityResearch Center for Analytical Sciences, Department of Chemistry, College of Sciences, Northeastern UniversityResearch Center for Analytical Sciences, Department of Chemistry, College of Sciences, Northeastern UniversityResearch Center for Analytical Sciences, Department of Chemistry, College of Sciences, Northeastern UniversityAbstract Glycosylated RNAs (glycoRNAs), a recently discovered class of membrane-associated glyco-molecules, remain poorly understood in function and clinical value due to limited detection methods. Here, we show a dual recognition Förster resonance energy transfer (drFRET) strategy using nucleic acid probes to detect N-acetylneuraminic acid-modified RNAs, enabling sensitive, selective profiling of glycoRNAs on small extracellular vesicles (sEVs) from minimal biofluids (10 μl initial biofluid). Using drFRET, we identify 5 prevalent sEV glycoRNAs derived from 7 cancer cell lines. In a 100-patient cohort (6 cancer types and non-cancer controls), sEV glycoRNA profiles achieve 100% accuracy (95% confidence interval) in distinguishing cancers from non-cancer cases and 89% accuracy in classifying specific cancer types. Furthermore, drFRET reveal that sEV glycoRNAs specifically interact with Siglec proteins and P-selectin, which is critical for sEV cellular internalization. The drFRET strategy provides a versatile and sensitive platform for the imaging and functional analysis of sEV glycoRNAs, with promising implications for clinical applications.https://doi.org/10.1038/s41467-025-58490-2
spellingShingle Tingju Ren
Yingzhi Zhang
Yuxiao Tong
Qi Zhang
Tianhao Wang
Yue Wang
Chunguang Yang
Zhangrun Xu
FRET imaging of glycoRNA on small extracellular vesicles enabling sensitive cancer diagnostics
Nature Communications
title FRET imaging of glycoRNA on small extracellular vesicles enabling sensitive cancer diagnostics
title_full FRET imaging of glycoRNA on small extracellular vesicles enabling sensitive cancer diagnostics
title_fullStr FRET imaging of glycoRNA on small extracellular vesicles enabling sensitive cancer diagnostics
title_full_unstemmed FRET imaging of glycoRNA on small extracellular vesicles enabling sensitive cancer diagnostics
title_short FRET imaging of glycoRNA on small extracellular vesicles enabling sensitive cancer diagnostics
title_sort fret imaging of glycorna on small extracellular vesicles enabling sensitive cancer diagnostics
url https://doi.org/10.1038/s41467-025-58490-2
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