The DOI matches its Crossref record; 28 of the 28 references it cites were found in a registry or an index.
Assessing sample and miRNA profile quality in serum and plasma or other biofluids
Open accessAbstract
MicroRNAs (miRNAs) constitute a class of small cellular RNAs (typically 21-23nt) that function as post-transcriptional regulators of gene expression. Current estimates indicate that more than one third of the cellular transcriptome is regulated by miRNAs, although they are relatively few in number (less than 2000 human miRNAs). The high relative stability of miRNA in common clinical tissues and biofluids (e.g. plasma, serum, urine, saliva, etc.) and the ability of miRNA expression profiles to accurately classify discrete tissue types and disease states have positioned miRNA quantification as a promising new tool for a wide range of diagnostic applications. Furthermore miRNAs have been shown to be rapidly released from tissues into the circulation with the development of pathology. To facilitate discovery and clinical development of miRNA-based biomarkers, we developed a genome-wide Locked Nucleic Acid (LNA™)-based miRNA qPCR platform with unparalleled sensitivity and robustness. The platform allows high-throughput profiling of miRNAs from important clinical sources without the need for pre-amplification. Using this system, we have profiled thousands of biofluid samples including blood derived plasma and serum. An extensive quality control (QC) system has been implemented in order to secure technical excellence and reveal any unwanted bias coming from pre-analytical or analytical variables. We present our approaches to sample and RNA QC as well as data QC and normalization. Specifically we have developed normal reference ranges for circulating miRNAs in serum and plasma as well as a hemolysis indicator based on microRNA expression.
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Cites
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Metadata
- Authors
- Blondal, T., Jensby Nielsen, S., Baker, A., Andreasen, D., Mouritzen, P., Wrang Teilum, M., & Dahlsveen, I. K.
- Venue
- Methods
- Publisher
- Elsevier BV
- Published
- 2013-01
- Volume
- 59
- Issue
- 1
- Pages
- S1-S6
- ISSN
- 1046-2023 (ISSN-L)
- OpenAlex
- W2157793936
- Cited by
- 687
- References
- 28
- FWCI
- 10.18
- Type
- journal article
- Language
- en
- Open access
- hybrid
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