Kjersti Ringvoll Normann1, Kristin Astrid Berland Øystese2, Jens Petter Berg3, Tove Lekva4, Jon Berg-Johnsen5, Jens Bollerslev2, Nicoleta Cristina Olarescu6. 1. Section of Specialized Endocrinology, Department of Endocrinology, Oslo University Hospital, Oslo, Norway; Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Oslo, Norway; Research Institute for Internal Medicine, Oslo University Hospital, Oslo, Norway. Electronic address: normann.kjersti@medisin.uio.no. 2. Section of Specialized Endocrinology, Department of Endocrinology, Oslo University Hospital, Oslo, Norway; Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Oslo, Norway. 3. Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Oslo, Norway; Department of Medical Biochemistry, Oslo University Hospital, Oslo, Norway. 4. Research Institute for Internal Medicine, Oslo University Hospital, Oslo, Norway. 5. Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Oslo, Norway; Department of Neurosurgery, Oslo University Hospital, Oslo, Norway. 6. Section of Specialized Endocrinology, Department of Endocrinology, Oslo University Hospital, Oslo, Norway; Research Institute for Internal Medicine, Oslo University Hospital, Oslo, Norway.
Abstract
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.
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.
Authors: Anders J Kolnes; Kristin A B Øystese; Nicoleta C Olarescu; Geir Ringstad; Jon Berg-Johnsen; Olivera Casar-Borota; Jens Bollerslev; Anders P Jørgensen Journal: J Clin Endocrinol Metab Date: 2020-08-01 Impact factor: 5.958
Authors: Marija M Janjic; Rafael M Prévide; Patrick A Fletcher; Arthur Sherman; Kosara Smiljanic; Daniel Abebe; Ivana Bjelobaba; Stanko S Stojilkovic Journal: Sci Rep Date: 2019-12-27 Impact factor: 4.379