Expression profiles of somatostatin, dopamine, and estrogen receptors in pituitary adenomas determined by means of synthetic multilocus calibrators

Aims: Pituitary adenomas (PA) are non-invasive benign tumors with a high autopsy prevalence. They are classified according to the type of hormone secreted (prolactin, growth hormone, adrenocorticotropin, thyrotropin, folitropin, or luteinizing hormone). Clinically non-functioning adenomas (CNFA) lacking the typical hypersecretion of hormones make up a significant portion of PA. The aim of the study was to determine the complete expression profiles of somatostatin receptors (SSTR1-SSTR5), dopamine receptors type 2 (D2R), and estrogen receptors (ER1) in various types of PA. Methods: Adenoma specimens were obtained from 206 patients during transsphenoidal resection. For quantitative analysis, reverse transcription and consequent real-time PCR with synthetic multilocus calibrators (SMC) were used. The obtained data were normalized to the number of transcripts of the beta-glucuronidase gene. Results: The use of SMC enabled the alignment of individual calibration functions for all the receptors. No relationships between the expression of the receptors and the tumor size, site of extension, gender or age at diagnosis were significant. In growth hormone-secreting adenomas, D2R and SSTR2 transcripts were extensively expressed, followed by ER1, SSTR5, SSTR3, and SSTR1. In patients with macroprolactinomas, transsphenoidal resection was indicated because dopamine agonists did not normalize prolactin levels. D2R, ER1 and SSTR1 transcripts were significantly transcribed. Corticotroph adenomas showed high levels of D2R and ER1 transcripts and lower amounts of SSTR2 and SSTR1 transcripts. SSTR5 transcripts were very low. Subjects with CNFA dominantly expressed D2R and ER1, followed by SSTR2 and SSTR3 mRNA. Conclusion: We evaluated SSTR1-SSTR5, D2R, and ER1 expressions in a large group of pituitary adenomas and we found that determining their individual expression profiles could help when choosing the optimal postoperative treatment.