Identification of suitable reference genes for qPCR analysis of serum microRNA in gastric cancer patients.

BACKGROUND

Circulating microRNA expression profiles may be promising biomarkers for diagnosis and assessment of the prognosis of cancer patients. Quantitative polymerase chain reaction (qPCR) is a sensitive technique for estimating expression levels of circulating microRNAs. However, there is no current consensus on the reference genes for qPCR analysis of circulating microRNAs.

AIMS

In this study we tried to identify suitable reference genes for qPCR analysis of serum microRNA in gastric cancer patients and healthy individuals.

METHODS

Six microRNAs (let-7a, miR-16, miR-93, miR-103, miR-192, and miR-451) and RNU6B were chosen as candidate reference genes on the basis of the literature. Expression levels of these candidates were analyzed by qPCR in serum samples from 40 gastric cancer patients and 20 healthy volunteers. The geNorm, Normfinder, bestkeeper, and comparative delta-Ct method algorithms were used to select the most suitable reference gene from the seven candidates. This was then validated by normalizing the expression levels of serum miR-21 across all gastric cancer patients and healthy volunteers.

RESULTS

The algorithms revealed miR-16 and miR-93 were the most stably expressed reference genes, with stability values of 1.778 and 2.213, respectively, for serum microRNA analysis across all the patients and healthy controls. The effect of different normalization strategies was compared; when normalized to the serum volume there were no significant differences between patients and controls. However, when the data were normalized to miR-93, miR-16, or miR-93 and miR-16 combined, significant differences were detected.

CONCLUSIONS

Our results demonstrated that reference gene choice for qPCR data analysis has a great effect on the study outcome, and that it is necessary to choose a suitable reference for reliable expression data. We recommend miR-16 and miR-93 as suitable reference genes for serum miRNA analysis for gastric cancer patients and healthy controls.