The metabolism of testosterone and dihydrotestosterone in an androgen-dependent tumour. A possible correlation between dihydrotestosterone and tumour growth in vivo

The effects of dihydrotestosterone (17β-hydroxy-5α-androstan-3-one) and testosterone on the growth of the androgen-dependent Shionogi SC-115 tumour in mice have been compared and the metabolites in the tumour arising from each steroid have been identified. After the transfer of SC-115 tumour cells to castrated male mice, treatment of the recipients with dihydrotestosterone produced a striking proliferative response that enabled earlier tumour detection and led to a higher tumour incidence than obtained with testosterone. At short intervals after the intravenous injection of 200μCi of [1,2-(3)H]testosterone the amounts of radioactivity in tumour, muscle and seminal vesicles were almost equal. The metabolism of [1,2-(3)H]testosterone in tumour and muscle was slight in comparison with the extensive metabolism in seminal vesciles. Whereas up to 7% of the total neutral steroid recovered from whole tumour tissue and isolated nuclei was in the form of [1,2-(3)H]dihydrotestosterone, the amount of this compound in the corresponding preparations from seminal vesciles was several times greater. When the metabolism of [1,2-(3)H]dihydrotestosterone in tumour tissue was studied, it was found that more than 60% of the total neutral steroid in both cytoplasm and nuclei consisted of [1,2-(3)H]dihydrotestosterone. Thus much higher intracellular concentrations of dihydrotestosterone occurred with the administration of this steroid than with testosterone. Tumour cell proliferation was suppressed by oestradiol and the amount of androgen in nuclei was significantly decreased by high doses of this hormone

Intermittent Androgen Suppression: Estimating Parameters for Individual Patients Based on Initial PSA Data in Response to Androgen Deprivation Therapy.

When a physician decides on a treatment and its schedule for a specific patient, information gained from prior patients and experience in the past is taken into account. A more objective way to make such treatment decisions based on actual data would be useful to the clinician. Although there are many mathematical models proposed for various diseases, so far there is no mathematical method that accomplishes optimization of the treatment schedule using the information gained from past patients or "rapid learning" technology. In an attempt to use this approach, we integrate the information gained from patients previously treated with intermittent androgen suppression (IAS) with that from a current patient by first fitting the time courses of clinical data observed from the previously treated patients, then constructing the prior information of the parameter values of the mathematical model, and finally, maximizing the posterior probability for the parameters of the current patient using the prior information. Although we used data from prostate cancer patients, the proposed method is general, and thus can be applied to other diseases once an appropriate mathematical model is established for that disease