MicroRNA expression studies: challenge of selecting reliable reference controls for data normalization

Cell Mol Life Sci. 2019 Sep;76(18):3497-3514. doi: 10.1007/s00018-019-03136-y. Epub 2019 May 14.

Abstract

Accurate determination of microRNA expression levels is a prerequisite in using these small non-coding RNA molecules as novel biomarkers in disease diagnosis and prognosis. Quantitative PCR is the method of choice for measuring the expression levels of microRNAs. However, a major obstacle that affects the reliability of results is the lack of validated reference controls for data normalization. Various non-coding RNAs have previously been used as reference controls, but their use may lead to variations and lack of comparability of microRNA data among the studies. Despite the growing number of studies investigating microRNA profiles to discriminate between healthy and disease stages, robust reference controls for data normalization have so far not been established. In the present article, we provide an overview of different reference controls used in various diseases, and highlight the urgent need for the identification of suitable reference controls to produce reliable data. Our analysis shows, among others, that RNU6 is not an ideal normalizer in studies using patient material from different diseases. Finally, our article tries to disclose the challenges to find a reference control which is uniformly and stably expressed across all body tissues, fluids, and diseases.

Keywords: Benign and malignant diseases; MicroRNA normalization; Plasma; Reference controls; Serum; Tissue.

Publication types

  • Review

MeSH terms

  • Biomarkers / metabolism
  • Cardiovascular Diseases / genetics
  • Cardiovascular Diseases / pathology
  • Central Nervous System Diseases / genetics
  • Central Nervous System Diseases / pathology
  • Hepatitis B / genetics
  • Hepatitis B / pathology
  • Humans
  • MicroRNAs / blood
  • MicroRNAs / metabolism*
  • Neoplasms / genetics
  • Neoplasms / pathology
  • Prognosis
  • RNA, Small Nuclear / blood
  • RNA, Small Nuclear / metabolism
  • Tuberculosis / genetics
  • Tuberculosis / pathology

Substances

  • Biomarkers
  • MicroRNAs
  • RNA, Small Nuclear