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Shen et al. Hepatoma Res 2016;2:305-15 Hepatoma Research
DOI: 10.20517/2394-5079.2016.28
www.hrjournal.net
Original Article Open Access

Evaluating normalization approaches for the

better identification of aberrant microRNAs

associated with hepatocellular carcinoma

Jing Shen , Qiao Wang , Irina Gurvich , Helen Remotti , Regina M. Santella 1
1
2
1
1
1 Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University Medical Center, New York, NY 10032, USA
2 Department of Pathology and Cell Biology, Columbia University Medical Center, New York, NY 10032, USA
Correspondence to: Dr. Jing Shen, Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University Medical
Center, 650 W. 168th St. Black Building Rm. 1608, New York, NY 10032, USA. E-mail: js2182@cumc.columbia.edu
How to cite this article: Shen J, Wang Q, Gurvich I, Remotti H, Santella RM. Evaluating normalization approaches for the better identification of
aberrant microRNAs associated with hepatocellular carcinoma. Hepatoma Res 2016;2:305-15.
ABSTRACT
Article history: Aim: Dysregulated microRNAs (miRNAs) have been identified in hepatocellular carcinoma
Received: 07-07-2016 (HCC), but only a small proportion have been confirmed. An appropriate normalizer is crucial
Accepted: 03-11-2016 to determining the accuracy and reliability of data from miRNA studies. Methods: Different
Published: 18-11-2016 normalization strategies were used to validate genome-wide miRNA profiles in HCC tumor and
non-tumor tissues, and to determine the consistency and discrepancy of data on dysregulated
Key words: miRNAs. Results: Two sets of stable miRNAs (miR-30c/miR-30b and miR-30c/miR-126)
MicroRNA, were identified in HCC tissues by geNorm and NormFinder tools, respectively. The mean of
stability, global miRNAs also showed good stability for ranking the top 1-2 miRNAs, but the stabilities
normalization, of the manufacturer-recommended ncRNAs controls were poor. Four panels of miRNAs were
hepatocellular carcinoma, significantly associated with HCC by separately using various normalizers, and 14 miRNAs
biomarkers were consistently identified by three normalization strategies. Although fewer miRNAs (17-
26) were dysregulated in HCC using the global mean or the 2 stable miRNAs as normalizers,
perfect clustering of tissues was also obtained with only 1 to 2 misclassifications, suggesting the
efficiency of the miRNA panels. Using global mean as the normalizer, the authors identified 7
miRNAs, including 2 novel (miR-324-5p and miR-550) significantly upregulated in HCC that
were omitted when using 3 endogenous controls as the normalizer. Conclusion: An optimal
normalization strategy to identify biologically important miRNAs in HCC tissue studies of
miRNA may be the combination of global mean and 2 stable miRNAs. Selection of appropriate
normalization strategies to adjust miRNAs levels is particularly important for epidemiological
studies dealing with large data sets and covering multiple experimental batches.

INTRODUCTION controlling multiple biological processes (DNA damage/
repair, apoptosis, proliferation, differentiation, etc.)
MicroRNAs (miRNAs) have important functions in involved in tumorigenesis and progression. [1,2]
negatively regulating coding genes’ expression and Genome-wide and candidate gene approaches have

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