Circulating molecules that are released into the circulation in response to specific stimuli are considered potential biomarkers for physiological or pathological processes. Their effective usefulness as biomarkers resides in their stability and high availability in all the biological fluids, combined with the limited invasiveness of intervention. Among the circulating molecules, miRNAs represent a novel class of biomarkers as they possess all the required characteristics such as sensitivity, predictivity, specificity, robustness, translatability, and noninvasiveness. miRNAs are small non-coding RNAs, that act as inhibitors of protein translation, and intervene in the complex network of the post-transcriptional mechanisms finely regulating gene expression. The emerging role of miRNAs as potential biomarkers for clinical applications (e.g., cancer and cardiovascular diseases diagnosis and prediction, musculoskeletal disease diagnosis and bone fracture risk prediction), however, requires the standardization of miRNA processing, from sample collection and sample storage, to RNA isolation, RNA reverse-transcription, and data analyses. Normalization is one of the most controversial issues related to quantitative Real-Time PCR data analysis since no universally accepted normalization strategies and reference genes exist, even more importantly, for circulating miRNA quantification. As it is widely demonstrated that the choice of different normalization strategies influences the results of gene expression analysis, it is important to select the most appropriate normalizers for each experimental set. This review discloses on the different strategies adopted in RT-qPCR miRNA normalization and the concerning issues to highlight on the need of a universally accepted methodology to make comparable the results produced by different studies.
Keywords: Biomarkers; Normalization; RT-qPCR; Reference genes; microRNA.
Copyright © 2018 Elsevier Inc. All rights reserved.