Identification of suitable reference genes for the relative quantification of microRNAs in pleural effusion

Han,Hye‑Suk; Jo,Yeong  Nang; Lee,Jin  Yong; Choi,Song‑Yi; Jeong,Yusook; Yun,Jieun; Lee,Ok‑Jun

doi:10.3892/ol.2014.2404

Identification of suitable reference genes for the relative quantification of microRNAs in pleural effusion

Authors:
- Hye‑Suk Han
- Yeong Nang Jo
- Jin Yong Lee
- Song‑Yi Choi
- Yusook Jeong
- Jieun Yun
- Ok‑Jun Lee
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Affiliations: Department of Internal Medicine, College of Medicine, Chungbuk National University, Cheongju 361‑763, Republic of Korea, Bioevaluation Center, Korea Research Institute of Bioscience and Biotechnology, Cheongwon 363‑883, Republic of Korea, Public Health Medical Service, SMG‑SNU Boramae Medical Center, Seoul 156‑707, Republic of Korea, Department of Pathology, College of Medicine, Chungbuk National University, Cheongju 361‑763, Republic of Korea
Published online on: August 1, 2014 https://doi.org/10.3892/ol.2014.2404
Pages: 1889-1895

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Abstract

Circulating cell‑free microRNAs (miRNAs) are potential biomarkers of cancer. Reverse transcription‑quantitative polymerase chain reaction (RT‑qPCR) is widely used in miRNA expression studies. The aim of this study was to identify suitable reference genes for RT‑qPCR analyses of miRNA expression levels in pleural effusion. The expression levels of candidate reference miRNAs were investigated in 10 benign pleural effusion (BPE) and 10 lung adenocarcinoma‑associated malignant pleural effusion (LA‑MPE) samples using miRNA microarrays. The expression levels of candidate reference miRNAs, together with those of U6 small nuclear RNA (snRNA), RNU6B, RNU44 and RNU48 small RNAs, in 46 BPE and 45 LA‑MPE samples were validated by RT‑qPCR, and were analyzed using the NormFinder and BestKeeper algorithms. The impact of different normalization approaches on the detection of differential expression levels of miR‑198 in BPE and LA‑MPE samples was also assessed. As determined by the miRNA microarray data, five candidate reference miRNAs were identified. Following RT‑qPCR validation, U6 snRNA, miR‑192, miR‑20a, miR‑221, miR‑222 and miR‑16 were evaluated using the NormFinder and BestKeeper software programs. U6 snRNA and miR‑192 were identified as single reference genes and the combination of these genes was preferred for the relative quantification of miRNA expression levels in pleural effusion. Normalization of miR‑98 expression levels to those of U6 snRNA, miR‑192 or a combination of these genes enabled the detection of a significant difference between BPE and LA‑MPE samples. Therefore, U6 snRNA and miR‑192 are recommended as reference genes for the relative quantification of miRNA expression levels in pleural effusion.

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1	Bartel DP: MicroRNAs: genomics, biogenesis, mechanism, and function. Cell. 116:281–297. 2004.
2	Cho WC: MicroRNAs: potential biomarkers for cancer diagnosis, prognosis and targets for therapy. Int J Biochem Cell Biol. 42:1273–1281. 2010.
3	Zhou L, Zhao YP, Liu WJ, et al: Circulating microRNAs in cancer: diagnostic and prognostic significance. Expert Rev Anticancer Ther. 12:283–288. 2012.
4	Cortez MA, Bueso-Ramos C, Ferdin J, et al: MicroRNAs in body fluids - the mix of hormones and biomarkers. Nat Rev Clin Oncol. 8:467–477. 2011.
5	Tsim S, O’Dowd CA, Milroy R and Davidson S: Staging of non-small cell lung cancer (NSCLC): a review. Respir Med. 104:1767–1774. 2010.
6	Nance KV, Shermer RW and Askin FB: Diagnostic efficacy of pleural biopsy as compared with that of pleural fluid examination. Mod Pathol. 4:320–324. 1991.
7	Xie L, Chen X, Wang L, et al: Cell-free miRNAs may indicate diagnosis and docetaxel sensitivity of tumor cells in malignant effusions. BMC Cancer. 10:5912010.
8	Xie L, Wang T, Yu S, et al: Cell-free miR-24 and miR-30d, potential diagnostic biomarkers in malignant effusions. Clin Biochem. 44:216–220. 2011.
9	Han HS, Yun J, Lim SN, et al: Downregulation of cell-free miR-198 as a diagnostic biomarker for lung adenocarcinoma-associated malignant pleural effusion. Int J Cancer. 133:645–652. 2013.
10	Mestdagh P, Van Vlierberghe P, De Weer A, et al: A novel and universal method for microRNA RT-qPCR data normalization. Genome Biol. 10:R642009.
11	Ratert N, Meyer HA, Jung M, et al: Reference miRNAs for miRNAome analysis of urothelial carcinomas. PLoS One. 7:e393092012.
12	Song J, Bai Z, Han W, et al: Identification of suitable reference genes for qPCR analysis of serum microRNA in gastric cancer patients. Dig Dis Sci. 57:897–904. 2012.
13	Wotschofsky Z, Meyer HA, Jung M, et al: Reference genes for the relative quantification of microRNAs in renal cell carcinomas and their metastases. Anal Biochem. 417:233–241. 2011.
14	Chang KH, Mestdagh P, Vandesompele J, Kerin MJ and Miller N: MicroRNA expression profiling to identify and validate reference genes for relative quantification in colorectal cancer. BMC Cancer. 10:1732010.
15	Gee HE, Buffa FM, Camps C, et al: The small-nucleolar RNAs commonly used for microRNA normalisation correlate with tumour pathology and prognosis. Br J Cancer. 104:1168–1177. 2011.
16	Wang T, Lv M, Shen S, et al: Cell-free microRNA expression profiles in malignant effusion associated with patient survival in non-small cell lung cancer. PLoS One. 7:e432682012.
17	Andersen CL, Jensen JL and Ørntoft TF: Normalization of real-time quantitative reverse transcription-PCR data: a model-based variance estimation approach to identify genes suited for normalization, applied to bladder and colon cancer data sets. Cancer Res. 64:5245–5250. 2004.
18	Pfaffl MW, Tichopad A, Prgomet C and Neuvians TP: Determination of stable housekeeping genes, differentially regulated target genes and sample integrity: BestKeeper - Excel-based tool using pair-wise correlations. Biotechnol Lett. 26:509–515. 2004.
19	Song B, Wang Y, Kudo K, et al: miR-192 Regulates Dihydrofolate Reductase and Cellular Proliferation through the p53-microRNA Circuit. Clin Cancer Res. 14:8080–8086. 2008.
20	Wu H, Wang F, Hu S, et al: MiR-20a and miR-106b negatively regulate autophagy induced by leucine deprivation via suppression of ULK1 expression in C2C12 myoblasts. Cell Signal. 24:2179–2186. 2012.
21	Visone R, Russo L, Pallante P, et al: MicroRNAs (miR)-221 and miR-222, both overexpressed in human thyroid papillary carcinomas, regulate p27Kip1 protein levels and cell cycle. Endocr Relat Cancer. 14:791–798. 2007.
22	Cimmino A, Calin GA, Fabbri M, et al: miR-15 and miR-16 induce apoptosis by targeting BCL2. Proc Natl Acad Sci USA. 102:13944–13949. 2005.
23	Kiss T: Small nucleolar RNA-guided post-transcriptional modification of cellular RNAs. EMBO J. 20:3617–3622. 2001.
24	Dieci G, Preti M and Montanini B: Eukaryotic snoRNAs: a paradigm for gene expression flexibility. Genomics. 94:83–88. 2009.
25	Galardi S, Fatica A, Bachi A, et al: Purified box C/D snoRNPs are able to reproduce site-specific 2′-O-methylation of target RNA in vitro. Mol Cell Biol. 22:6663–6668. 2002.
26	Peltier HJ and Latham GJ: Normalization of microRNA expression levels in quantitative RT-PCR assays: identification of suitable reference RNA targets in normal and cancerous human solid tissues. RNA. 14:844–852. 2008.
27	Chen X, Ba Y, Ma L, et al: Characterization of microRNAs in serum: a novel class of biomarkers for diagnosis of cancer and other diseases. Cell Res. 18:997–1006. 2008.
28	Git A, Dvinge H, Salmon-Divon M, et al: Systematic comparison of microarray profiling, real-time PCR, and next-generation sequencing technologies for measuring differential microRNA expression. RNA. 16:991–1006. 2010.
29	Dong XY, Guo P, Boyd J, et al: Implication of snoRNA U50 in human breast cancer. J Genet Genomics. 36:447–454. 2009.
30	Mourtada-Maarabouni M, Pickard MR, Hedge VL, Farzaneh F and Williams GT: GAS5, a non-protein-coding RNA, controls apoptosis and is downregulated in breast cancer. Oncogene. 28:195–208. 2009.
31	Kroh EM, Parkin RK, Mitchell PS and Tewari M: Analysis of circulating microRNA biomarkers in plasma and serum using quantitative reverse transcription-PCR (qRT-PCR). Methods. 50:298–301. 2010.
32	Tricarico C, Pinzani P, Bianchi S, et al: Quantitative real-time reverse transcription polymerase chain reaction: normalization to rRNA or single housekeeping genes is inappropriate for human tissue biopsies. Anal Biochem. 309:293–300. 2002.