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Evaluation of Reference Gene Stability for Investigations of Intracellular Signalling in Human Cancer and
Vera Kosheverova1, Alexander Schwarz2, Rimma Kamentseva1
1Laboratory of Intracellular Membranes Dynamics, Institute of Cytology of the Russian Academy of Sciences, 194064 Saint Petersburg, Russia.
Background:
Real-time reverse transcription quantitative polymerase chain reaction (RT-qPCR) is a powerful tool for analysing target gene expression in biological samples. To achieve reliable results by RT-qPCR, the most stable reference genes must be selected for proper data normalisation, particularly when comparing cells of different types. We aimed to choose the least variable candidate reference genes among eight housekeeping genes tested within a set of human cancer cell lines (HeLa, MCF-7, SK-UT-1B, A549, A431, SK-BR-3), as well as four lines of normal, non-malignant mesenchymal stromal cells (MSCs) of different origins.
Methods:
The reference gene stability was evaluated using four algorithms (BestKeeper, NormFinder, geNorm and the comparative ΔCt method) and ranked with the RefFinder web-based tool.
Results:
We found increased variability in the housekeeping genes' expression in the cancer cell lines compared to that in normal MSCs. POP4 and GAPDH were identified as the most suitable reference genes in cancer cells, while 18S and B2M were the most suitable in MSCs. POP4 and EIF2B1 were shown to be the least variable genes when analysing normal and cancer cell lines together. Epidermal growth factor receptor (EGFR) mRNA relative expression was normalised by the three most stable or three least stable reference genes to demonstrate the reliability of reference genes validation.
Conclusion:
We analysed and selected stable reference genes for RT-qPCR analysis in the wide panel of cancer cell lines and MSCs. The study provides a reliable tool for future research concerning the expression of genes involved in various intracellular signalling pathways and emphasises the need for careful selection of suitable references before analysing target gene expression.
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