Extracellular microRNAs (miRs) have been proposed as important blood‐based biomarkers for several diseases. Contrary to proteins and other RNA classes, miRs are stable and easily detectable in body fluids. In this respect, miRs represent a perfect candidate for minimal invasive biomarkers which can hopefully become a complement for invasive histological examinations of tumor tissue. Despite the high number of miR biomarker studies, the specificity and reproducibility of these studies is missing. Therefore, the standardization of pre‐analytical and analytical methods is urgently needed. Here, we validated miR analysis for RNA isolation and miR quantification by quantitative polymerase chain reaction (RT‐qPCR) based on good laboratory practice (GLP). Validation was carried out exemplarily on four miRs, which had already been described as potential biomarkers in previous studies. As basis for RNA analysis using RT‐qPCR, the Minimum Information for Publication of Quantitative Real‐Time PCR Experiments were applied and adapted on the analysis of circulating miRs from human plasma. In our study, we identified and solved several pitfalls from handling to normalization strategy in the analysis of extracellular miRs that lead to inconsistent and non‐repeatable data. Principles of GLP set a framework of experimental design, performance and monitoring to ensure high quality and reliable data. Within this study, we appointed first acceptance criteria for circulating miR quantification during validation which set standards for future miR quantification in blood samples.

Circulating microRNAs (miRs) represent promising diagnostic and prognostic biomarkers for various diseases. Despite the high number of biomarker studies, the results of these studies are hardly reproducible. This makes it difficult to transfer the results into clinical application. In this context, acceptance criteria for the quantification of miRs by reverse transcription quantitative real-time polymerase chain reaction (RT-qPCR) may help to standardize miR analysis and improve reproducibility.