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Researchers ID Reference Genes for qRT-PCR Validation of Colorectal Cancer miRNA Profiling


A team of researchers from Ghent University and the National University of Ireland has identified and validated a panel of six microRNAs ideal for use as reference genes in PCR-based miRNA expression analysis in colorectal cancer, according to a recently published research paper.

The researchers claim that the results of their study have important implications for colorectal cancer translational research, and that scientists conducting miRNA-based profiling of colorectal tumors should consider assessing the expression stability of the miRNAs to account for variations between different tumors and patients.

In a paper published online April 29 in BMC Cancer, the researchers, including Ghent University's Jo Vandesompele and NUI's Nicola Miller, described their method for identifying and validating the most stable reference genes for qRT-PCR-based miRNA expression studies.

The researchers used their method, first described in a study published last year in Genome Biology, to assess the mean expression value of all expressed miRNAs in a high-throughput miRNA profiling study of 10 pairs of colorectal cancer and normal tissues obtained from 40 patients at Galway University Hospital in Ireland.

To do this, they isolated small RNA from the tissue and extracted miRNA using RNeasy kits from Qiagen. Following qualitative analysis of the miRNA using an Agilent 2100 Bioanalyzer and small RNA assay, the researchers profiled a panel of 380 miRNAs and controls from the 10 tissue sample pairs using TaqMan Human MicroRNA array cards and the 7900HT Fast real-time PCR system from Life Technologies' Applied Biosystems business.

Using a global mean expression normalization algorithm powered by Qbase Plus software from Vandesompele's company Biogazelle, they identified eight candidate reference miRNAs. Then, they evaluated the expression patterns of the candidate genes in a cohort of 74 colorectal cancer tissues using qRT-PCR; and analyzed the genes' expression stability again using the Biogazelle software.

The analyses led the researchers to identify the six most stably expressed miRNAs: let-7a, miR-16, miR-26a, miR-345, miR-425, and miR-454.

The researchers believe that their study is the first to identify and validate suitable reference genes for normalizing miRNA qRT-PCR in human colorectal tissues. "While reference genes for mRNA [qRT-PCR] studies have been well-established, few miRNA [qRT-PCR] studies have detailed the validation of reference genes for normalization to date," the researchers wrote.

This is important because researchers are increasingly studying the role miRNAs play in modulating the expression patterns of messenger RNAs and governing biological processes such as differentiation, proliferation, and apoptosis, especially in diseases such as cancer.

For example, Rosetta Genomics has been developing a blood-based colorectal cancer test based on measurement of miRNA biomarkers, though for the time being it has put that project on the back burner due to technical obstacles, according to a December report from PCR Insider sister publication RNAi News (RNAi News, 12/31/2009).

RNAi News also previously reported that Asuragen and the Translational Genomics Institute are working on a test detect pancreatic cancer using blood-based microRNA biomarkers (RNAi News, 4/22/2010).

According to the work by Vandesompele, Miller, and colleagues, qRT-PCR is the most sensitive and reproducible method of quantifying gene expression and validating high-throughput studies (usually array-based) of miRNA expression in cancer. As such, "in order to achieve accurate, reproducible, and biologically relevant miRNA [qRT-PCR] data, non-biological sample-to-sample variation that could be introduced by protocol-dependent inconsistencies has to be corrected for by using reference genes," the researchers wrote.

"While it may not be feasible due to cost and sample availability, the stability of the top six most stably expressed miRNAs in colorectal tissues should be assessed to determine the most appropriate normalizers within each study as patient and tumor characteristics may vary between different study cohorts," they concluded.