Abstract

BackgroundReal-time reverse transcription quantitative PCR (RT-qPCR) has become the method of choice for quantification of gene expression changes. The most important limitations of RT-qPCR are inappropriate data normalization and inconsistent data analyses. Pituitary adenomas are common tumours, and the appropriate interpretation of increasingly published data within this field is prevented by the lack of a proper selection and validation of stably expressed reference genes. AimTo find and validate the optimal reference gene or gene combination for reliable RT-qPCR gene expression in both non-functioning (NFPA) and hormone secreting (GH and ACTH) pituitary adenomas. Material and methodsThirty commonly used reference genes (PCR array reference gene panel, BioRad, Hercules, CA) were quantified by RT-qPCR in 24 pituitary adenomas (12 NFPA, 8 GH and 4 ACTH). The data was analysed using three programs: geNorm (Qbase+), Normfinder and BestKeeper having different algorithms to identify the most stable reference gene or combination of reference genes. Three reference genes ALAS1, PSMC4 and GAPDH, were selected for further validation in a larger cohort of 223 adenomas (141 NFPA, 63 GH and 19 ACTH). ResultsIn all adenomas, ALAS1 and PSMC4 were the most stable reference genes as estimated by geNorm and Normfinder, whereas Bestkeeper ranked RPLP0 and ACTB as the two most stable out of 10 carefully selected genes. The best gene combination was PSMC4 and ALAS1 (geNorm) or PSMC4 and GAPDH (Normfinder). The validation experiment (geNorm) showed that the most stable gene combinations were ALAS1 and GAPDH in NFPA, and PSMC4 and GAPDH in hormone secreting adenomas. ConclusionsSeveral of the reference genes expressed good stability yielding several candidate genes. PSMC4 and ALAS1 were overall the most stably expressed genes in pituitary adenoma merely differing in ranking order. PSMC4 and ALAS1 have so far not been reported as reference genes in pituitary adenomas. The various reference gene algorithms showed a mixed selection of top ranked genes, thus suggesting a need for an individualised and rational choice of reference genes.

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