Identification of miR-23a as a novel microRNA normalizer for relative quantification in human uterine cervical tissues.
10.3858/emm.2011.43.6.039
- Author:
Yuanming SHEN
1
;
Yang LI
;
Feng YE
;
Fenfen WANG
;
Xiaoyun WAN
;
Weiguo LU
;
Xing XIE
Author Information
1. Women's Reproductive Health Laboratory of Zhejiang Province, Women's Hospital, School of Medicine, Zhejiang University, Hangzhou, 310006, China.
- Publication Type:Original Article ; Research Support, Non-U.S. Gov't
- Keywords:
gene expression profiling;
microRNAs;
real-time polymerase chain reaction;
uterine cervical neoplasms
- MeSH:
Cervical Intraepithelial Neoplasia/diagnosis/genetics/*metabolism/pathology;
Cervix Uteri/*metabolism/pathology;
Early Detection of Cancer;
Female;
Gene Expression Profiling/*standards;
Humans;
MicroRNAs/genetics/*metabolism/standards;
Microarray Analysis;
Reference Standards;
Reverse Transcriptase Polymerase Chain Reaction;
Uterine Cervical Neoplasms/diagnosis/genetics/*metabolism/pathology
- From:Experimental & Molecular Medicine
2011;43(6):358-366
- CountryRepublic of Korea
- Language:English
-
Abstract:
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 deregulation 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.
