Abstract

BACKGROUND: Circulating microRNA (miRNA) are promising biomarkers for diagnosing and prognosticating numerous diseases. Reports have demonstrated controversial or even contradictory conclusions in studies on circulating microRNA. This study aimed to evaluate the potential bias of using different reference genes for analyzing circulating microRNAs in the same malignant digestive diseases.

MATERIAL AND METHODS: We measured plasma concentrations of U6-snRNA, let-7a, miRNA-21, miRNA-106a, miRNA-155, miRNA-219, miRNA-221, and miRNA-16 in patients with hepatocellular carcinoma (HCC), gastric carcinoma (GC), hepatic cirrhosis, hepatitis B, and healthy volunteers using quantitative real-time polymerase chain reaction (qPCR). The GeNorm, Normfinder, BestKeeper, and Comparative ΔCq algorithms integrated in RefFinder were used to screen the most suitable reference genes from the candidates. The 4 commonly used statistical evaluation software packages provided different results regarding the stability of the candidate reference genes.

RESULTS: RefFinder revealed miRNA-106a and miRNA-21 as the most stably expressed reference genes, with comprehensive stability values of 1.189 and 1.861, respectively. U6-snRNA was the most unstable nucleic acid in our data. When 5 normalization strategies were compared using U6-snRNA, serum volume, miRNA-106a, miRNA-21, or the mean value of miRNA-106a and miRNA-21, obvious expression bias was detected in almost all target microRNAs. Intriguingly, all these normalization strategies indicated that circulating miRNA-155 is greatly upregulated in patients with HCC and GC, but downregulated in benign hepatic disease.

CONCLUSIONS: Single reference genes used without justification in plasma microRNAs produce significant analysis bias or even erroneous results. Circulating miRNA-155 may be a promising non-invasive biomarker for discriminating malignant digestive tumors from the corresponding benign diseases.

Keywords: Case-Control Studies, Carcinoma, Hepatocellular - genetics, Genes, Neoplasm, MicroRNAs - genetics, Real-Time Polymerase Chain Reaction - standards, Reference Standards