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Quantitative real-time RT-PCR (RT-qPCR) is being widely used in microRNA expression research. However, few reports detailed a robust identification and validation strategy for suitable reference genes for normalisation in microRNA RT-qPCR studies. The aim of this study was to identify the most stable reference gene(s) for quantification of microRNA expression analysis in uterine cervical tissues. A microarray was performed on 6 pairs of uterine cervical tissues to identify the candidate reference genes. The stability of candidate reference genes was assessed by RT-qPCR in 23 pairs of uterine cervical tissues. The identified most stable reference genes were further validated in other cohort of 108 clinical uterine cervical samples: (HR-HPV- normal, n=21; HR-HPV+ normal, n=19; cervical intraepithelial neoplasia [CIN], n=47; cancer, n=21), and the effects of normalizers on the relative quantity of target miR-424 were assessed. In the array experiment, miR-26a, miR-23a, miR-200c, let-7a, and miR-1979 were identified as candidate reference genes for subsequent validation. MiR-23a was identified as the most reliable reference gene followed by miR-191. The use of miR-23a and miR-191 to normalize expression data enabled detection of a significant dereg-ulation of miR-424 between normal, CIN and cancer tissue. Our results suggested that miR-23a and miR-191 are the optimal reference microRNAs that can be used for normalization in profiling studies of cervical tissues; miR-23a is a novel microRNA normalizer.

Identification of miR-23a as a novel microRNA normalizer for relative quantification in human uterine cervical tissues