No abstract

Supplementary data are available at Bioinformatics online.

Qualitative and quantitative profiling of six different categories of urinary phospholipids (PLs) from patients with prostate cancer was performed to develop an analytical method for the discovery of candidate biomarkers by shotgun lipidomics method. Using nanoflow liquid chromatography-electrospray ionization-tandem mass spectrometry, we identified the molecular structures of a total of 70 PL molecules (21 phosphatidylcholines (PCs), 11 phosphatidylethanolamines (PEs), 17 phosphatidylserines (PSs), 11 phosphatidylinositols (PIs), seven phosphatidic acids, and three phosphatidylglycerols) from urine samples of healthy controls and prostate cancer patients by data-dependent collision-induced dissociation. Identified molecules were quantitatively examined by comparing the MS peak areas. From statistical analyses, one PC, one PE, six PSs, and two PIs among the PL species showed significant differences between controls and cancer patients (p < 0.05, Student's t test), with concentration changes of more than threefold. Cluster analysis of both control and patient groups showed that 18:0/18:1-PS and 16:0/22:6-PS were 99% similar in upregulation and that the two PSs (18:1/18:0, 18:0/20:5) with two PIs (18:0/18:1 and 16:1/20:2) showed similar (>95%) downregulation. The total amount of each PL group was compared among prostate cancer patients according to the Gleason scale as larger or smaller than 6. It proposes that the current study can be utilized to sort out possible diagnostic biomarkers of prostate cancer.

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 Ͼ 0.994) with the exception of cholesterol (r 2 ϭ 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 (5␣-reductase, 3␣-HSD, 3␤-HSD, and 17␤-HSD, except for 20␣-HSD). These results support that data transformation is valid, since 5␣-reductase is a marker of BPH and 17␤-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. Many naturally occurring steroids with similar chemical structures could yield biological information [7]. Endogenous steroids are divided into five groups, namely, androgens, estrogens, corticoids, progestins, and sterols, which are generally synthesized from cholesterol in the adrenal cortex, ovaries, and testes (Scheme 1). In biosynthetic pathways of steroid hormone, two major types of enzymes are involved, cytochrome P450 and steroid oxidoreductase. Abnormalities of these enzymes often lead to hormonal imbalances that have serious consequences, and which are responsible for the development of hormone-dependent diseases (see Supplementary Table 1, which can be found in the electronic version of this article). For example, concentrations of corticoids and their metabolic ratios provide diagnostic evidence of apparent mineralocorticoid excesses caused by 11␤-HSD deficiency [8] and congenital adrenal hyperplasia, which are caused by deficiencies of enzymes like hydroxylase (at C-11, 17, and 21) or 3␤-HSD [9]. In addition, enhanced androgen activity generated by the conversion of testosterone to dihydrotestosterone (DHT) by 5␣-reductase was utilized to allow early therapeutic intervention in young men [10].Enzyme activity profiles can be used to describe the functional diversities of biological systems, which are d...