Landscape of extracellular small RNA and identification of biomarkers in multiple human cancers
Summary: Extracellular RNAs (exRNAs) in biofluids, sourced from diverse tissues, exhibit various biological functions and diagnostic potential. Small non-coding RNAs, such as rsRNAs and tsRNAs, are abundant in tissues and likely secreted into biofluids, contributing to exRNA profiles. To comprehensi...
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| Main Authors: | , , , , , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-08-01
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| Series: | iScience |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2589004225013598 |
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| Summary: | Summary: Extracellular RNAs (exRNAs) in biofluids, sourced from diverse tissues, exhibit various biological functions and diagnostic potential. Small non-coding RNAs, such as rsRNAs and tsRNAs, are abundant in tissues and likely secreted into biofluids, contributing to exRNA profiles. To comprehensively evaluate exRNAs, we employed traditional and enzymatic treatment RNA sequencing to systematically profile exRNAs across six human biofluids including serum, ascites, urine, milk, seminal plasma and saliva as well as sera from mice, rats, rabbits, and bovines. rsRNAs were identified as the most abundant exRNA species in human biofluids, with rsRNAs and tsRNAs showing high expression and species-specific profiles across animals. In serum samples from 51 healthy individuals and 69 cancer patients, exRNA-based machine learning model achieved 94.1% sensitivity and 100% specificity in cancer detection and accurately classified tumor origin. Altogether, this study reveals distinct rsRNA-abundant exRNA landscape across multiple biofluids and support the potential of exRNA signatures in pan-cancer diagnostics. |
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| ISSN: | 2589-0042 |