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Isolation and Analysis of Traceable and Functionalized Extracellular Vesicles from the Plasma and Solid Tissues

Isolation and Analysis of Traceable and Functionalized Extracellular Vesicles from the Plasma and Solid Tissues

Published on: October 17, 2022

A total transcriptome profiling method for plasma-derived extracellular vesicles: applications for liquid biopsies.

Maria G Amorim¹, Renan Valieris², Rodrigo D Drummond²

¹Laboratory of Medical Genomics, A.C.Camargo Cancer Center, São Paulo, SP, Brazil.

Scientific Reports

|November 2, 2017

Summary

Researchers developed a new method for comprehensive RNA profiling in extracellular vesicles (EVs) from small patient samples. This technique enables unbiased characterization of the total EV transcriptome, aiding biomarker discovery.

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Exosomal miRNA Analysis in Non-small Cell Lung Cancer NSCLC Patients' Plasma Through qPCR: A Feasible Liquid Biopsy Tool

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Published on: May 27, 2016

Area of Science:

Biochemistry
Molecular Biology
Genomics

Background:

Extracellular vesicles (EVs) mediate intercellular communication through RNA cargo transfer.
EV-derived RNAs are promising biomarkers for diagnostics and prognostics.
The complete RNA landscape within EVs remains largely uncharacterized.

Purpose of the Study:

To develop a novel method for total transcriptome profiling of plasma-derived EVs.
To enable unbiased characterization of the complete RNA cargo (small and long RNAs) from limited clinical samples.
To facilitate the discovery of novel EV-based biomarkers and communication mechanisms.

Main Methods:

Development of a next-generation sequencing (NGS) method for total transcriptome profiling.
Application of the method to RNA extracted from EVs isolated by ultracentrifugation from human plasma.
Single-step library preparation for unbiased RNA cargo analysis.

Main Results:

Identification of a comprehensive RNA profile in plasma-derived EVs.
Abundant detection of small RNAs (tRNAs, miRNAs, miscellaneous RNAs) with largely unknown functions.
Characterization of protein-coding transcripts, long noncoding RNAs, and circular RNAs, with experimental validation.

Conclusions:

The developed NGS method provides the first full-spectrum transcriptome analysis from minute patient-derived EV samples.
This approach allows for unbiased characterization of the complete RNA cargo within EVs.
The method holds potential for identifying novel cell-to-cell communication mechanisms and diagnostic/prognostic biomarkers.