Abstract
IntroductionA prerequisite to accurate interpretation of RQ-PCR data is robust data normalization. A commonly used method is to compare the cycle threshold (CT) of target miRNAs with those of a stably expressed endogenous (EC) miRNA(s) from the same sample. Despite the large number of studies reporting miRNA expression patterns, comparatively few appropriate ECs have been reported thus far. The purpose of this study was to identify stably expressed miRNAs with which to normalize RQ-PCR data derived from human blood specimens.MethodsMiRNA profiling of approximately 380 miRNAs was performed on RNA derived from blood specimens from 10 women with breast cancer and 10 matched controls. Analysis of mean expression values across the dataset (GME) identified stably expressed candidates. Additional candidates were selected from the literature and analyzed by the geNorm algorithm. Further validation of three candidate ECs by RQ-PCR was performed in a larger cohort (n = 40 cancer, n = 20 control) was performed, including analysis by geNorm and NormFinder algorithms.ResultsMicroarray screening identified 10 candidate ECs with expression patterns closest to the global mean. Geometric averaging of candidate ECs from the literature using geNorm identified miR-425 as the most stably expressed miRNA. MiR-425 and miR-16 were the best combination, achieving the lowest V-value of 0.185. Further validation by RQ-PCR confirmed that miR-16 and miR-425 were the most stably expressed ECs overall. Their combined use to normalize expression data enabled the detection of altered target miRNA expression that reliably differentiated between cancers and controls in human blood specimens.ConclusionThis study identified that the combined use of 2 miRNAs, (miR-16 and miR-425) to normalize RQ-PCR data generated more reliable results than using either miRNA alone, or use of U6. Further investigation into suitable ECs for use in miRNA RQ-PCR studies is warranted.
Highlights
A prerequisite to accurate interpretation of RQ-PCR data is robust data normalization
Their combined use to normalize expression data enabled the detection of altered target miRNA expression that reliably differentiated between cancers and controls in human blood specimens
The aims of this study were to evaluate a panel of candidate ECs from which to validate the most stably expressed EC(s) to normalize RQ-PCR data derived from blood specimens in breast cancer
Summary
A prerequisite to accurate interpretation of RQ-PCR data is robust data normalization. Accumulating evidence has shown that miRNAs play pivotal roles in regulatory functions pertaining to cell growth, development and differentiation and are associated with a wide variety of human diseases. Comparison of cycle threshold (CT), the cycle number at which fluorescence signals are detected above background, to CT values to an endogenously expressed control RNA is used to determine miRNA expression levels by relative quantification (EC). The accuracy of this method is heavily reliant on the choice of endogenous control. The selection of a suitable EC(s), with which to normalize RQ-PCR data, is an important first step in the accurate and reliable determination of miRNA expression levels
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