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Determination of Intraprostatic and Intratesticular Androgens
Authors:Markta &#x;imkov  Ji&#x;í Her ek  Pavel Dra&#x;ar  Richard Hampl
Affiliation:1.Institute of Endocrinology, Narodni 8, 11694 Prague, Czech Republic;2.Department of Chemistry of Natural Compounds, University of Chemistry and Technology, Technicka 6, 16628 Prague, Czech Republic;3.Department of Urology, First Faculty of Medicine, Charles University, 12108 Prague, Czech Republic;4.Department of Urology, Military University Hospital, 16902 Prague, Czech Republic
Abstract:Androgens represent the main hormones responsible for maintaining hormonal balance and function in the prostate and testis. As they are involved in prostate and testicular carcinogenesis, more detailed information of their active concentration at the site of action is required. Since the introduction of the term intracrinology as the local formation of active steroid hormones from inactive precursors of the adrenal gland, mainly dehydroepiandrosterone (DHEA) and DHEA-S, it is evident that blood circulating levels of sex steroid hormones need not reflect their actual concentrations in the tissue. Here, we review and critically evaluate available methods for the analysis of human intraprostatic and intratesticular steroid concentrations. Since analytical approaches have much in common in both tissues, we discuss them together. Preanalytical steps, including various techniques for separation of the analytes, are compared, followed by the end-point measurement. Advantages and disadvantages of chromatography-mass spectrometry (LC-MS, GC-MS), immunoanalytical methods (IA), and hybrid (LC-IA) are discussed. Finally, the clinical information value of the determined steroid hormones is evaluated concerning differentiating between patients with cancer or benign hyperplasia and between patients with different degrees of infertility. Adrenal-derived 11-oxygenated androgens are mentioned as perspective prognostic markers for these purposes.
Keywords:prostate  testes  cancer  determination  androgens  biomarkers  disease prediction  methods
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