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Related Experiment Video

Updated: Aug 2, 2025

Optimization of a Multiplex RNA-based Expression Assay Using Breast Cancer Archival Material

Optimization of a Multiplex RNA-based Expression Assay Using Breast Cancer Archival Material

Published on: August 1, 2018

Assessing Breast Cancer Molecular Subtypes Using Extracellular Vesicles' mRNA.

Mengjia Hu^1,2,3,4, Virginia Brown^2,5, Joshua M Jackson^2,3

¹Department of Cancer Biology, The University of Kansas Medical Center, Cancer Center, Kansas City, Kansas 66160, United States.

Analytical Chemistry

|April 18, 2023

Summary

This summary is machine-generated.

This study introduces the EV microfluidic affinity purification (EV-MAP) chip for isolating extracellular vesicle (EV) subpopulations. The EV-MAP chip enables precise molecular subtyping of breast cancer patients, offering potential for improved precision medicine.

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Optimization of a Multiplex RNA-based Expression Assay Using Breast Cancer Archival Material

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An Enrichment Method for Small Extracellular Vesicles Derived from Liver Cancer Tissue

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Published on: February 3, 2023

Area of Science:

Biotechnology
Molecular Biology
Oncology

Background:

Extracellular vesicles (EVs) contain RNA cargo reflective of their cell of origin.
EVs are promising biomarkers for minimally invasive liquid biopsies.
Precision medicine requires accurate molecular information for treatment guidance.

Purpose of the Study:

To develop and validate a microfluidic chip for isolating specific EV subpopulations.
To assess the utility of isolated EV subpopulations for molecular subtyping of breast cancer.
To evaluate the potential of EV-derived RNA for prognostication.

Main Methods:

Affinity isolation of EV subpopulations using monoclonal antibodies on a microfluidic chip (EV-MAP).
Isolation of EV subpopulations EV^EpCAM (epithelial) and EV^FAPα (mesenchymal).
Analysis of exosomal mRNA (exo-mRNA) using real-time-droplet digital polymerase chain reaction and PAM50 gene expression profiling (exo-PAM50).

Main Results:

The EV-MAP chip achieved >80% recovery and 99% specificity.
EV subpopulations (EV^EpCAM and EV^FAPα) isolated from breast cancer patients' plasma yielded specific RNA quantities.
Profiling of exo-mRNA from EV^EpCAM and EV^FAPα using exo-PAM50 showed 100% concordance with tumor tissue for prognostication.

Conclusions:

The EV-MAP chip effectively isolates distinct EV subpopulations with high purity and recovery.
EV subpopulations carry molecular information that accurately reflects tumor tissue characteristics.
EV-derived RNA profiling holds significant potential for non-invasive breast cancer prognostication and guiding precision medicine.