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Background Real-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. Aim To 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 methods Thirty 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). Results In 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. Conclusions Several 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. [ABSTRACT FROM AUTHOR]

Objective: Reliable biomarkers associated with aggressiveness of non-functioning gonadotroph adenomas (GAs) are lacking. As the growth of tumor remnants is highly variable, molecular markers for growth potential prediction are necessary. We hypothesized that fast- and slow-growing GAs present different gene expression profiles and reliable biomarkers for tumor growth potential could be identified, focusing on the specific role of epithelial-mesenchymal transition (EMT). Design and methods: Eight GAs selected for RNA sequencing were equally divided into fast- and slow-growing group by the tumor volume doubling time (TVDT) median (27.75 months). Data were analyzed by tophat2, cufflinks and cummeRbund pipeline. 40 genes were selected for RT-qPCR validation in 20 GAs based on significance, fold-change and pathway analyses. The effect of silencing MTDH (metadherin) and EMCN (endomucin) on in vitro migration of human adenoma cells was evaluated. Results: 350 genes were significantly differentially expressed (282 genes upregulated and 68 downregulated in the fast group, P-adjusted <0.05). Among 40 selected genes, 11 showed associations with TVDT (--0.669

Early detection and treatment of women at risk for gestational diabetes mellitus (GDM) could improve perinatal and long-term outcomes in GDM women and their offspring. We explored if a 75 g oral glucose tolerance test (OGTT) at 14-16 weeks of gestation could identify women who will (1) develop GDM or give birth to large-for-gestational-age (LGA) babies in 1031 pregnant women from the STORK study using different diagnostic criteria (WHO1999, IADPSG2010, WHO2013, NORWAY2017) and (2) develop pre-diabetes 5 years postpartum focusing on first trimester β-cell function in a separate study of 300 women from the STORK cohort. The sensitivity of the 14-16 week OGTT to identify women who would develop GDM or have LGA babies was low, and we could not identify alternative cut-offs to exclude women not at risk or identify women that could benefit from early intervention. First trimester β-cell function was a stronger determinant than third trimester β-cell function of predicting maternal pre-diabetes. In conclusion, in our normal low-risk population, the 75 g OGTT at 14-16 weeks is insufficient to identify candidates for early treatment of GDM or identify women not likely to develop GDM or have LGA babies. First trimester β-cell function may predict pre-diabetes 5 years postpartum. [ABSTRACT FROM AUTHOR]