"The mean expression value of all expressed microRNAs performs better than one based on only those microRNAs that are expressed in all samples," says Vandesompele. "This suggests a more accurate representation of input RNA fluctuations when all microRNAs are considered."

"Changes in microRNA expression are often very subtle but biologically relevant," says Pieter Mestdagh, working on the method in Vandesompele's lab. "Because microRNAs regulate genes acting in different pathways, deregulated microRNA expression can trigger a cascade of events that alter the biology of the cell. As a consequence, a proper normalization strategy that enables the detection of small changes is of utmost importance, especially when dealing with heterogeneous patient samples."

Reverse transcription quantitative PCR (RT-qPCR) has become the method of choice for measuring gene expression levels in terms of accuracy and specificity, both for coding and non-coding RNAs. However, result accuracy is largely dependent on effective data normalization.

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