Extracellular vesicle microRNAs – biomarker discovery in various diseases

In recent years, biomarker discovery based on extracellular microRNAs (miRNAs), especially exosome miRNAs, has drawn wide attention. While exosome isolation and identification technologies are increasingly sophisticated, the preanalytical process of exosome miRNAs seems to be no longer a crucial problem. Though next-generation sequencing, microarray and digital PCR have been recommended as good downstream analytical platforms for exosome miRNA quantification, they are still more constrained in clinical utility compared with RT-qPCR method at present. Here, the authors will trace back to the origin and summarize current studies of biomarker discovery based on extracellular vesicle miRNAs, and provide an overview and latest developments of RT-qPCR-based data normalization, in order to further assist the development of translational medicine.


Frequently used strategy for selection and evaluation of the candidate reference genes.

miRNA differential expression in extracellular vesicles

  • The phenomenon of miRNA differential expression is existed extensively in patients’ versus controls’ extracellular vesicles (EVs). Though it is still a controversy that the miRNA profiles of the parent cells and released EVs are the same. Some studies suggested they were the same, yet some suggested miRNAs were selectively packaged in EVs, and others showed evidences for the co-existence of this appearance.

The discovered EV-derived miRNA biomarkers associated with human diseases

  • Despite of the controversies, miRNA biomarker discovery based on EVs is still flourishing. Many diseases associated with EV miRNA biomarkers were identified.

  • However, the rationality of these biomarkers was challenged due to most of which were based on inappropriate data normalization when utilizing RTqPCR.

The algorithms & software for reference genes identification

  • This is an overview of the algorithms and software for reference genes identification, such as the commonly used geNorm, NormFinder, equivalence test, delta Ct algorithms and qbaseplus and GenEx software for comprehensive RTqPCR data process. Further clarification of the advantages and disadvantages and the conditions of usage of these algorithms and software compared with each other in detail.

The strategies for RTqPCR based data normalization

  • A frequently used strategy for selection and evaluation of the candidate reference genes for related researchers to justify their reference genes in use.

  • For high-throughput RTqPCR array analysis, some microarray methodology was adapted to substitute a single or a few of reference gene(s). The methodology used in this strategy is also compared with each other and the reference genes method in brief.

  • Finally, an new statistical method, which could propagate the bias while using an inappropriate normalization strategy into the final statistical summaries, is introduced.

Liu Y, Lu Q. (2015) Extracellular vesicle microRNAs: biomarker discovery in various diseases based on RT-qPCR. Biomark Med 9(8):791-805. [abstract]

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