Distribution profiling of circulating microRNAs in serum

Jonathan Ashby1, Kenneth Flack, Luis A Jimenez

  • 1Department of Chemistry; ‡Program in Biomedical Sciences; §Department of Statistics, University of California, Riverside , Riverside, California 92521, United States.

Analytical Chemistry
|September 6, 2014
PubMed

Insights

Analyzing circulating microRNAs (miRNAs) in serum carriers reveals distinct cancer biomarker profiles. This method enhances cancer diagnosis by differentiating miRNA distribution in exosomes and lipoprotein particles.

Area of Science:

  • Biochemistry
  • Molecular Biology
  • Cancer Research

Background:

  • Circulating microRNAs (miRNAs) are promising cancer biomarkers.
  • miRNAs are transported via carriers like proteins, lipoproteins, and exosomes.
  • The distribution of miRNAs within these carriers, not just total quantity, may correlate with cancer.

Purpose of the Study:

  • To develop a method for separating serum miRNA carriers.
  • To analyze miRNA distribution profiles in healthy individuals versus cancer patients.
  • To identify specific miRNA carriers as potential cancer biomarkers.

Main Methods:

  • Asymmetrical flow field flow fractionation (AF4) was used to separate serum miRNA carriers.
  • Six fractions enriched with different carriers (lipoproteins, exosomes) were collected.
  • Reverse transcription quantitative polymerase chain reaction (RT-qPCR) quantified eight selected miRNAs in each fraction.

Main Results:

  • Fractionated miRNA analysis revealed larger quantity changes between controls and cancer patients compared to total miRNA levels.
  • Statistical analysis showed significant differences in 4 miRNAs within specific fractions between groups.
  • Principal component analysis demonstrated clear separation between control and cancer groups based on fractionated miRNA amounts.

Conclusions:

  • The developed AF4 method effectively screens circulating miRNA distribution in serum carriers.
  • Analyzing miRNA distribution profiles enhances the detection of differences between healthy and cancer states.
  • This approach facilitates the discovery of specific miRNA biomarkers for improved cancer diagnosis.