"Future-Proofing" Blood Processing for Measurement of Circulating miRNAs in Samples from Biobanks and Prospective...

Background: Quantifying circulating nucleic acids is an important new approach to cancer diagnosis/monitoring.Methods: We compared the suitability of serum versus plasma for measuring miRNAs using qRT-PCR and assessed how preanalytic variables that can affect circulating tumor DNA (ctDNA) quantification in plasma also influence miRNA levels.Results: Across 62 blood-derived specimens, plasma samples in EDTA, Streck-DNA, and Streck-RNA tubes showed significantly higher C_t values for multiple housekeeping miRNAs, compared with serum samples. For the EDTA-plasma tubes, this difference was only seen when including the high-speed centrifugation protocol used to optimize ctDNA extraction. In plasma samples derived from blood stored at room temperature for up to 14 days (conditions that typically apply to samples processed for biobanking), levels of endogenous housekeeping miRNAs gradually increased, in parallel with the hemolysis marker hsa-miR-451a, consistent with release from blood cells/platelets. It was necessary to normalize levels of the housekeeping miRNAs to those of hsa-miR-451a, to obtain the stable values needed for referencing test miRNA levels.Conclusions: Our data indicate that plasma samples prepared for ctDNA extraction are suboptimal for miRNA quantification and require the incorporation of multiple data normalization steps. For prospective studies designed to measure both miRNAs and ctDNA, the most suitable approach would be to obtain both serum (for miRNAs) and plasma (for ctDNA). If only plasma can be collected, we recommend an initial low-speed centrifugation step, followed by aliquoting the supernatant into parallel samples, one for direct miRNA quantification, and the other for a further high-speed centrifugation step to optimize ctDNA retrieval.Impact: These recommendations will help "future-proof" clinical studies in which quantification of circulating miRNAs is a component. Cancer Epidemiol Biomarkers Prev; 27(2); 208-18. ©2017 AACR.