Abstract
BackgroundQuantification and normalization of RT-qPCR data critically depends on the expression of so called reference genes. Our goal was to develop a strategy for the selection of reference genes that utilizes microarray data analysis and combines known approaches for gene stability evaluation and to select a set of appropriate reference genes for research and clinical analysis of breast samples with different receptor and cancer status using this strategy.MethodsA preliminary search of reference genes was based on high-throughput analysis of microarray datasets. The final selection and validation of the candidate genes were based on the RT-qPCR data analysis using several known methods for expression stability evaluation: comparative ∆Ct method, geNorm, NormFinder and Haller equivalence test.ResultsA set of five reference genes was identified: ACTB, RPS23, HUWE1, EEF1A1 and SF3A1. The initial selection was based on the analysis of publically available well-annotated microarray datasets containing different breast cancers and normal breast epithelium from breast cancer patients and epithelium from cancer-free patients. The final selection and validation were performed using RT-qPCR data from 39 breast cancer biopsy samples. Three genes from the final set were identified by the means of microarray analysis and were novel in the context of breast cancer assay. We showed that the selected set of reference genes is more stable in comparison not only with individual genes, but also with a system of reference genes used in commercial OncotypeDX test.ConclusionA selection of reference genes for RT-qPCR can be efficiently performed by combining a preliminary search based on the high-throughput analysis of microarray datasets and final selection and validation based on the analysis of RT-qPCR data with a simultaneous examination of different expression stability measures. The identified set of reference genes proved to be less variable and thus potentially more efficient for research and clinical analysis of breast samples comparing to individual genes and the set of reference genes used in OncotypeDX assay.
Highlights
Quantification and normalization of Reverse transcription quantitative real-time polymerase chain reaction (RT-qPCR) data critically depends on the expression of so called reference genes
We demonstrated that the selected set of 5 reference genes is more stable than the set of 5 reference genes used in Oncotype DX Breast Cancer diagnostic test
The strategy for the selection of reference genes that was used in this study consists of the following stages: the large-scale screening of an extended list of candidate reference genes based on microarray data series, the selection of a candidate gene set for validation by RT-qPCR, and the determination of the final set of reference genes
Summary
Quantification and normalization of RT-qPCR data critically depends on the expression of so called reference genes. RT-qPCR is used as a conventional routine method for expression profiling of a moderate number of genes and is highly suitable when only a small amount of sample is available [1,4]. High throughput thermal cyclers and PCR platforms help to overcome the limitation of RT-qPCR and to perform simultaneous expression analysis of tens and hundreds of genes for one or more samples depending on the platform [1]. In research practice these two technologies are able to solve a broad spectrum of questions supplementing each other. In clinical diagnostics RT-qPCR is still more popular with the advantage of speed and a relatively low cost [5]
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