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Expert Reviews in Molecular Medicine
Article . 2024 . Peer-reviewed
License: CC BY
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Decoding bioactive signals of the RNA secretome: the cell-free messenger RNA catalogue

Authors: Rhys E. De Sota; Stephen R. Quake; John J. Sninsky; Shusuke Toden;

Decoding bioactive signals of the RNA secretome: the cell-free messenger RNA catalogue

Abstract

Abstract Despite gene-expression profiling being one of the most common methods to evaluate molecular dysregulation in tissues, the utilization of cell-free messenger RNA (cf-mRNA) as a blood-based non-invasive biomarker analyte has been limited compared to other RNA classes. Recent advancements in low-input RNA-sequencing and normalization techniques, however, have enabled characterization as well as accurate quantification of cf-mRNAs allowing direct pathological insights. The molecular profile of the cell-free transcriptome in multiple diseases has subsequently been characterized including, prenatal diseases, neurological disorders, liver diseases and cancers suggesting this biological compartment may serve as a disease agnostic platform. With mRNAs packaged in a myriad of extracellular vesicles and particles, these signals may be used to develop clinically actionable, non-invasive disease biomarkers. Here, we summarize the recent scientific developments of extracellular mRNA, biology of extracellular mRNA carriers, clinical utility of cf-mRNA as disease biomarkers, as well as proposed functions in cell and tissue pathophysiology.

Keywords

Extracellular Vesicles, Animals, Humans, Review, RNA, Messenger, Transcriptome, Cell-Free Nucleic Acids, Biomarkers

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
11
Top 10%
Average
Top 10%
Green
hybrid
Related to Research communities
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