Abnormalities in
steroid hormones are responsible for the development and prevention of
endocrine diseases. Due to their biochemical roles in endocrine system, the quantitative evaluation of
steroid hormones is needed to elucidate altered expression of
steroids. Gas chromatographic-mass spectrometric (GC-MS) profiling of 70 urinary
steroids, containing 22
androgens, 18
estrogens, 15
corticoids, 13
progestins, and 2
sterols, were validated and its quantitative data were visualized using hierarchically clustered heat maps to allow "
steroid signatures". The devised method provided a good linearity (r(2) > 0.994) with the exception of
cholesterol (r(2) = 0.983). Precisions (% CV) and accuracies (% bias) ranged from 0.9% to 11.2% and from 92% to 119%, respectively, for most
steroids tested. To evaluate metabolic changes, this method was applied to urine samples obtained from 59 patients with
benign prostatic hyperplasia (BPH) versus 41 healthy male subjects. Altered concentrations of urinary
steroids found and heat maps produced during this 70-compound study showed also differences between the ratios of
steroid precursors and their metabolites (representing
enzyme activity). Heat maps showed that
oxidoreductases clustered (5alpha-
reductase, 3alpha-HSD, 3beta-HSD, and 17beta-HSD, except for 20alpha-HSD). These results support that data transformation is valid, since 5alpha-reductase is a marker of BPH and 17beta-HSD is positively expressed in prostate cells. Multitargeted profiling analysis of
steroids generated quantitative results that help to explain correlations between
enzyme activities. The data transformation and visualization described may to be found in the integration with the mining
biomarkers of
hormone-dependent diseases.