Androgen Metabolic Pathways Research Articles

Therapeutic potential of targeting AKR1C2 in the treatment of prostate cancer.

Prostate cancer development and progression are driven by androgens, and changes in androgen metabolic pathways can lead to prostate cancer progression or remission. AKR1C2 is a member of the aldo-keto reductase superfamily and plays an important role in the metabolism of steroids and prostaglandins.Alterations in the expression and activity of AKR1C2 affect the homeostasis of active androgens, which in turn affects the progression of prostate cancer. AKR1C2 reduces the highly active dihydrotestosterone to the less active 3α-diol in the prostate, resulting in lower androgen levels. Whereas the expression of AKR1C2 is significantly reduced in prostate cancer tissues relative to normal prostate tissues, this results in a weakening of the dihydrotestosterone metabolic inactivation pathway, leading to the retention of dihydrotestosterone in the prostate cancer cells, which promotes the progress of prostate cancer. Given the critical role of AKR1C2 in prostate cancer cells, targeting AKR1C2 for the treatment of prostate cancer may be an effective strategy. It has been demonstrated that curcumin and neem leaf extract effectively inhibit prostate cancer in vitro and in vivo by modulating AKR1C2.

Abstract 850: Androgenic alopecia and risks of overall and aggressive prostate cancer: An updated meta-analysis

Abstract Background: Androgenic alopecia, known as male pattern baldness (MPB), is a common hair loss disorder among men. MPB has similar risk factors with prostate cancer (PrCa) including advancing age, family history, and sex hormones. Several studies have examined the associations between MPB and PrCa but the evidence remains unclear. We carried out a meta-analysis of epidemiological studies that examined the relationship between patterns of baldness: frontal, vertex, or both and PrCa risk. Methods: A literature search was performed in October 2022 using PubMed and Web of Science databases for epidemiological studies published between 1/1/2000 and 10/31/2022, which examined the above hypothesis. From each eligible study, relevant data were extracted on study design, population, sample size, prevalence of MPB at various ages, and corresponding associations with risks of total and aggressive PrCa. Pooled relative risks (RR) and corresponding 95% confidence intervals (CI) were calculated using the DerSimonian and Laird random-effects models. Heterogeneity across studies was assessed by I2 statistic. Results: A total of 14 studies: 14,573 cases and 132,434 controls/non-cases were included. The prevalence of MPB increased from 5% to 70% with aging and varied across studies. Vertex MPB at ages 40 years or older was associated with a pooled RR of 1.08 (95%CI 1.00-1.17) of total PrCa, but there was no association with frontal MPB. The onset of MBP at younger ages was also associated with RR=1.10 (95% CI 0.93 - 1.29) of PrCa, although results were not statistically significant. Results were similar when data were stratified by clinical features of PrCa, although there was large heterogeneity in the definition of aggressive PrCa across studies. Conclusions: Men with vertex MPB may have modest increased risk of PrCa. However, the majority of studies were conducted in Caucasian men and they did not evaluate effect modifications by genetic variations in androgen metabolism pathway genes or changes in serum levels of androgens. Further, large well-designed prospective cohort studies are needed to better understand the complex relationship between genetic susceptibility, endogenous hormones, MBP and risk of PrCa. Citation Format: Sapir Amar, David Hanelin, Ilir Agalliu. Androgenic alopecia and risks of overall and aggressive prostate cancer: An updated meta-analysis [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 850.

FRI382 High Androgen And Progesterone Metabolite Concentrations In Naturally Matured Follicles Are Concurrent With High Serum Anti-Müllerian Hormone Concentrations

Abstract Disclosure: T. Du Toit: None. M. Von Wolff: None. A.C. Swart: None. M. Groessl: None. C.E. Flueck: None. Infertility in women is routinely evaluated with the assessment of circulating steroid levels. Profiling steroid levels in follicular fluid (FF) would provide a focused evaluation of the ovarian endocrine milieu and is therefore better suited to identify key hormones potentially involved in dysfunctional follicular growth. The anti-Müllerian hormone (AMH) level in serum is a well-established clinical marker to estimate the ovarian reserve in assisted reproductive technology, while the AMH level in FF serves as a new prognostic marker for oocyte developmental potential. However, AMH-linked changes in the follicular steroid milieu have not been fully explored. We conducted an AMH-dependent analysis of the FF endocrine milieu. Hormones were quantified using LC-MS (n=42) and ELISA (n=4) in FF of 83 women undergoing natural cycle in vitro fertilisation. Patients were age-matched and classified into 4 statistically different (p<0.0001) groups according to serum AMH levels: group A (<1.1 pmol/L, n=20); group B (1 - 7.14 pmol/L, n=21); group C (7.14 - 35.5 pmol/L, n=21); and group D (>35.5 pmol/L, n=21). Group D was designated as our polycystic ovary syndrome (PCOS)-like group, as high serum AMH is a marker for PCOS. We characterised androgen and progesterone metabolic pathways in FF. Androstenedione (A4) and testosterone (T) levels differed significantly between the groups (p<0.01) and were highest in group D at 60 nmol/L and 4.7 nmol/L, respectively. The levels of 11-ketoandrostenedione (11KA4) and 11β-hydroxyandrosterone (adrenal-origin) also differed between the groups (p<0.05), with higher 11KA4 levels (±2.7-fold) quantified in group D. In parallel with serum AMH, FF AMH differed between the groups (p<0.0001), together with luteinizing hormone/FSH, A4/dehydroepiandrosterone, estradiol(E2)/T and E2/A4 ratios. In comparison to groups A, B and C combined, the PCOS-like group D showed significantly increased downstream progesterone metabolite levels –11α-hydroxyprogesterone [OHP4], 17α,20α-diOHP4, 16α-OHP4 and 5α-pregnanolone, with lower FSH levels. Our results show that the follicular milieu is significantly different when high AMH levels are measured compared to when AMH levels are low, marked by: (i) higher progesterone metabolite levels in follicles and (ii) higher A4 and T levels, concomitant with unchanged E2 levels suggesting that androgens were not fully converted to estrogens in these follicles. Our study furthermore corroborates other studies reporting an intrafollicular hyperandrogenic state in women with increased circulatory AMH levels. In summary, our study not only provides data based on a broad steroid profile that the follicular androgen endocrine milieu is affected in women with high serum AMH levels, but it also provides a model for the premature progesterone increase in PCOS women which leads to a reduction in the embryo implantation rate. Presentation: Friday, June 16, 2023

The serum steroid signature of PCOS hints at the involvement of novel pathways for excess androgen biosynthesis

ContextPolycystic ovary syndrome (PCOS) is defined by androgen excess and ovarian dysfunction in the absence of a specific physiological diagnosis. The best clinical marker of androgen excess is hirsutism, while the best biochemical parameter is still a matter of debate. Current consensus guidelines recommend, among other hormones, serum free testosterone as an important serum parameter to measure androgen excess. Recently, however, novel active androgens and androgen metabolic pathways have been discovered. ObjectiveTo assess the contribution of novel androgens and related steroid biosynthetic pathways to the serum steroid pool in PCOS women in comparison to healthy controls. DesignThis is a case control study, wherein PCOS was diagnosed according to the AE-PCOS 2009 criteria. Serum steroid profiling was performed by liquid chromatography high-resolution mass spectrometry. SettingYeditepe University and associated clinics in Istanbul, Turkey, together with Bern University Hospital Inselspital, Bern, Switzerland. Participants42 PCOS women and 42 matched, healthy control women. Main outcome measuresAssessment of 34 steroids compartmentalized in four androgen related pathways: the classic androgen pathway, the backdoor pathway, the C11-oxy backdoor pathway, and the C11-oxy (11β-hydroxyandrostenedione) pathway. ResultsMetabolites of all four pathways were identified in healthy and PCOS women. Highest concentrations were found for progesterone in controls and androstenedione in PCOS. Lowest levels were found for 11-ketotestosterone in controls compared to PCOS, and for 20α-hydroxyprogesterone in PCOS compared to controls. PCOS also had higher serum testosterone levels compared to the controls. PCOS women had overall higher levels of steroid metabolites of all four androgen pathways compared to healthy controls. ConclusionsNovel alternative pathways contribute to the androgen production in healthy and PCOS women. Hyperandrogenism in PCOS is characterized by an overall increase of serum androgens in the classic, backdoor and C11-oxy pathways. While monogenetic disorders of steroid biosynthesis can be recognized by a specific pattern in the steroid profile, no diagnostic pattern or classifier was found in the serum for PCOS.

Androgen Metabolism and Response in Prostate Cancer Anti-Androgen Therapy Resistance.

All aspects of prostate cancer evolution are closely related to androgen levels and the status of the androgen receptor (AR). Almost all treatments target androgen metabolism pathways and AR, from castration-sensitive prostate cancer (CSPC) to castration-resistant prostate cancer (CRPC). Alterations in androgen metabolism and its response are one of the main reasons for prostate cancer drug resistance. In this review, we will introduce androgen metabolism, including how the androgen was synthesized, consumed, and responded to in healthy people and prostate cancer patients, and discuss how these alterations in androgen metabolism contribute to the resistance to anti-androgen therapy.

Urinary androgens excretion patterns and prostate cancer in Mexican men.

Epidemiological studies related to androgens and prostate cancer (PC) have focused on serum determination of testosterone, androstenedione (A4), and DHEA, with inconsistent results. Herein, we hypothesized that differences in androgen biosynthetic and metabolic pathways, rather than differences in specific androgen concentrations, are associated with prostatic carcinogenesis. Therefore, spot urine samples from 111 incident PC cases with Gleason score at diagnosis and 227 healthy population controls, were analyzed. Urinary androgen concentrations (nanograms/milligrams of creatinine) were determined by ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS). Using a factor analysis, we identified three androgen urinary excretion patterns. In a subsample, we evaluated a modification effect of the androgen receptor (AR) CAG polymorphism. Pattern I, characterized by A4 and testosterone hydroxylated metabolites (11β-OHT; 2β-OHT; 15β-OHT; 2α-OHT; 6β-OHT), was associated with high PC odds among carriers of AR gene (CAG)>19 repeats (OR: 3.67 95% CI: 1.23-11.0; P for interaction= 0.009). Conversely, higher testosterone excretion (pattern III), was marginally associated with lower (OR: 0.35 95% CI: 0.12-1.00, P for trend= 0.08) poorly differentiated PC (Gleason ≥8). No clear association was observed with pattern II (DHEA; 16α and 16β-OHT). Our results were consistent with the previous evidence which suggests that the C11-oxy backdoor pathway is important for prostatic carcinogenesis. Androgen urine excretion analysis could be useful for PC diagnosis, treatment, and prognosis; however, further studies with a larger number of samples and the urinary determination of 11-ketoandrogens are necessary.

Associations between blood cadmium and endocrine features related to PCOS-phenotypes in healthy women of reproductive age: a prospective cohort study

BackgroundCadmium is an endocrine disrupting chemical that affects the hypothalamic-pituitary-gonadal axis. Though evidence suggests its potential role in altering androgen synthesis and metabolic pathways that are characteristic of polycystic ovary syndrome (PCOS), its relation in healthy women of reproductive age is largely unknown. As women with mild sub-clinical features of PCOS who do not meet the diagnostic criteria of PCOS may still experience reduced fecundability, investigating associations between cadmium and PCOS-phenotypes among healthy women may provide unique insight into the reproductive implications for many on the PCOS spectrum. Therefore, the objective of this study was to evaluate associations between cadmium and androgens, anti-Müllerian hormone (AMH), and metabolic markers in women of reproductive age.MethodsThis was a prospective cohort study of 251 healthy premenopausal women without self-reported PCOS (mean age 27.3 years and BMI 24.1 kg/m2). Cadmium was measured in blood collected at baseline. Reproductive hormones and metabolic markers were measured in fasting serum 8 times per menstrual cycle for 2 cycles. Linear mixed models and Poisson regression with a robust error variance were used to examine associations between cadmium and reproductive hormones and metabolic markers and anovulation, respectively.ResultsMedian (interquartile range) blood cadmium concentrations at baseline were 0.30 (0.19–0.43) µg/L. Higher levels of testosterone (2.2 %, 95 % confidence interval [CI] 0.4, 4.1), sex hormone-binding globulin (2.9 %, 95 % CI 0.5, 5.5), and AMH (7.7 %, 95 % CI 1.1, 14.9) were observed per 0.1 µg/L increase in cadmium concentrations. An 18 % higher probability of a mild PCOS-phenotype (95 % CI 1.06, 1.31), defined by a menstrual cycle being in the highest quartile of cycle-averaged testosterone and AMH levels, was also found per 0.1 µg/L increase in cadmium levels. No associations were observed for insulin and glucose. These findings were consistent even after analyses were restricted to non-smokers or further adjusted for dietary factors to account for potential sources of exposure.ConclusionsOverall, among healthy reproductive-aged women, cadmium was associated with endocrine features central to PCOS, but not with metabolic markers. These suggest its potential role in the hormonal milieu associated with PCOS even at low levels of exposure.

Alterations in Pattern Baldness According to Sex: Hair Metabolomics Approach.

Pattern baldness has been associated with the male hormone, dihydrotestosterone. In this study, we tried to determine how the overall metabolic pathways of pattern baldness differ in patients and in normal controls. Our study aimed to identify alterations in hair metabolomic profiles in order to identify possible markers of pattern baldness according to sex. Untargeted metabolomics profiling in pattern baldness patients and control subjects was conducted using ultra-performance liquid chromatography-mass spectrometry. To identify significantly altered metabolic pathways, partial least squares discriminant analysis was performed. Our analysis indicated differences in steroid biosynthesis pathway in both males and females. However, there was a remarkable difference in the androgen metabolic pathway in males, and the estrogen metabolic and arachidonic acid pathways in females. For the first time, we were able to confirm the metabolic pathway in pattern baldness patients using hair samples. Our finding improves understanding of pattern baldness and highlights the need to link pattern baldness and sex-related differences.

Sex hormones and acne: State of the art

Acne is an androgen-dependent inflammatory disease of sebaceous follicles. Herein, we reviewed and discussed the underlying pathways of androgen biosynthesis and metabolism, non-genomic regulation of androgen receptor expression and function, posttranslational regulation of androgen excess in acne and acne-associated syndromes, such as polycystic ovary syndrome, and congenital adrenal hyperplasia. We provide insights into the involvement of sex hormones, particularly androgens, in skin homeostasis and acne pathogenesis, including comedogenesis, lipogenesis, microbiota, and inflammation. Advanced understanding of the action mechanisms of classical acne treatment and new development of antiandrogens, both topical and systemic, are also highlighted.

Acephate interferes with androgen synthesis in rat immature Leydig cells.

Acephate is an organophosphate pesticide. It is widely used. However, whether it inhibits androgen synthesis and metabolism remains unclear. In the current study, we investigated the effect of acephate on the inhibition of androgen synthetic and metabolic pathways in rat immature Leydig cells after 3-h culture. Acephate inhibited basal androgen output in a dose-dependent manner with the inhibition starting at 0.5μM. It significantly inhibited luteinizing hormone and 8-Br-cAMP stimulated androgen output at 50μM. It significantly inhibited progesterone-mediated androgen output at 50μM. Further study demonstrated that acephate down-regulated the expression of Hsd3b1 and its protein at ≥ 0.5μM, Lhcgr at 5μM and Star at 50μM. Acephate directly blocked rat testicular HSD3B1 activity at 50μM. Acephate did not affect other androgen synthetic and metabolic enzyme activities as well as ROS production, proliferation, and apoptosis of immature Leydig cells. In conclusion, acephate targets LHCGR, STAR, and HSD3B1, thus blocking androgen synthesis in rat immature Leydig cells and HSD3B1 is being the most sensitive target of acephate.

Case-only Methods Identified Genetic Loci Predicting a Subgroup of Men with Reduced Risk of High-grade Prostate Cancer by Finasteride.

In the Prostate Cancer Prevention Trial (PCPT), genotypes that may modify the effect of finasteride on the risk of prostate cancer have not been identified. Germline genetic data from 1,157 prostate cancer cases in PCPT were analyzed by case-only methods. Genotypes included 357 SNPs from 83 candidate genes in androgen metabolism, inflammation, circadian rhythm, and other pathways. Univariate case-only analysis was conducted to evaluate whether individual SNPs modified the finasteride effect on the risk of high-grade and low-grade prostate cancer. Case-only classification trees and random forests, which are powerful machine learning methods with resampling-based controls for model complexity, were employed to identify a predictive signature for genotype-specific treatment effects. Accounting for multiple testing, a single SNP in SRD5A1 gene (rs472402) significantly modified the finasteride effect on high-grade prostate cancer (Gleason score > 6) in PCPT (family-wise error rate < 0.05). Men carrying GG genotype at this locus had a 55% reduction of the risk in developing high-grade cancer when assigned to finasteride (RR = 0.45; 95% confidence interval, 0.27-0.75). Additional effect-modifying SNPs with moderate statistical significance were identified by case-only trees and random forests. A prediction model built by the case-only random forest method with 28 selected SNPs classified 37% of PCPT men to have reduced risk of high-grade prostate cancer when taking finasteride, while the others have increased risk. In conclusion, case-only methods identified SNPs that modified the effect of finasteride on the risk of high-grade prostate cancer and predicted a subgroup of men who had reduced cancer risk by finasteride.

Simultaneous measurement of 18 steroids in human and mouse serum by liquid chromatography–mass spectrometry without derivatization to profile the classical and alternate pathways of androgen synthesis and metabolism

BackgroundThe recently identified alternate, or backdoor, pathway of DHT synthesis provides important novel information on androgen biosynthesis beyond the classical pathway. We report a rapid and versatile liquid chromatography–tandem mass spectrometry (LC–MS/MS) method to simultaneously and accurately quantify key steroids in human or mouse serum involved in either the classical or backdoor androgen synthesis pathways. MethodsSerum (200 µL) fortified with isotopically labelled internal standards underwent liquid–liquid extraction (LLE) with MTBE and extracts were analysed on a LC–MS/MS. The targeted steroids for quantification were testosterone (T), dihydrotestosterone (DHT), 5α-androstane-3α,17β-diol (3α diol), 5α-androstane-3β,17β-diol (3β diol), dehydroepiandrosterone (DHEA), androstenedione (A4), androsterone (AD), estradiol (E2), estrone (E1), progesterone (P4), pregnenolone (P5), androstenediol (Adiol), 17-hydroxyprogesterone (17-OHP4) and 17-hydroxypregnenolone (17-OHP5), corticosterone (B), cortisol (F), allopregnanolone (Allo-P5) and dihydroprogesterone (DHP). ResultsThe limits of quantification (LOQ) were 5 pg/mL for E2 and E1, 25 pg/mL for T, 50 pg/mL for A4 and 0.10 ng/mL for DHT, 17OHP5, P4, P5, AD, Adiol, DHEA, AlloP5 and 0.20 ng/mL for 17OHP4, 3α diol, 3β diol, DHP, 0.25 ng/mL for B and 1 ng/mL for F. Accuracy, precision, reproducibility and recovery were within acceptable limits for bioanalytical method validation. The method is illustrated in human and mouse, male and female serum. ConclusionsThe presented method is sufficiently sensitive, specific and reproducible to meet the quality criteria for routine laboratory application for accurate quantitation of 18 steroid concentrations in male and female serum from humans or mice for the purpose of profiling androgen synthesis and metabolism pathways.

Mathematical modeling of intracrine androgen metabolism in prostate cancer: Methodological aspects.

Progression of castration-recurrent/resistant prostate cancer (CRPC) relies in part on dihydrotestosterone derived from intratumoral androgen metabolism. Mathematical modeling provides a valuable tool for studies of androgen metabolism in CRPC. This modeling approach integrates existing knowledge about complex biologic systems and provides a means of interrogating the effects of various interventions. We sought to model a single reaction in the androgen biosynthesis network, namely the oxidation of androsterone (AND) to androstanedione (5α-dione) by four 3α-oxidoreductase enzymes, as an initial effort to establish the feasibility of our modeling approach. Models were constructed for two cell culture systems, a non-prostate cancer cell line (CV-1) and a prostate cancer cell line (LAPC-4), using the SimBiology app (version 5.3) in MATLAB (version 8.6). The models included components for substrate (AND), product (5α-dione), each of the four enzymes, and each of the four enzyme-substrate complexes. Each enzymatic reaction consisted of a reversible enzyme-substrate binding step and an irreversible catalysis step. Rates of change for each component were described using ordinary differential equations. Mathematical models were developed with model parameter values derived from literature sources or from existing experimental data, which included gene expression measurements and substrate and product concentrations determined using liquid chromatography-tandem mass spectrometry. The models for both cell lines adequately described substrate and product concentrations observed after 12 h treatment with AND. This modeling approach represents an adaptable, extensible and mechanistic framework that reflects androgen metabolism. The models can be expanded systematically to describe the complex androgen metabolic pathways important for study of novel therapies for CRPC.

Transcriptome analysis reveals novel insights into the response of low-dose benzo(a)pyrene exposure in male tilapia

Despite a wide number of toxicological studies that describe benzo[a]pyrene (BaP) effects, the metabolic mechanisms that underlie these effects in fish are largely unknown. Of great concern is the presence of BaP in aquatic systems, especially those in close proximity to human activity leading to consumption of potentially contaminated foods. BaP is a known carcinogen and it has been reported to have adverse effects on the survival, development and reproduction of fish. The purpose of this study was to investigate if a low dose of BaP can alter genes and key metabolic pathways in the liver and testis in male adult tilapia, and whether these could be associated with biological endpoints disruption. We used both high-throughput RNA-Sequencing to assess whole genome gene expression following repeated intraperitoneal injections of 3 mg/kg of BaP (every 6 days for 26 days) and morphometric endpoints as indicators of general health. Condition factor (K) along with hepatosomatic and gonadosomatic indices (morphometric parameters) were significantly lower in BaP-treated fish than in controls. BaP exposure induced important changes in the gene expression pattern in liver and testis as revealed by both Pathway and Gene Ontology (GO) analyses. Alterations that were shared by both tissues included arachidonic acid metabolism, androgen receptor to prostate-specific antigen signaling, and insulin-associated effects on lipogenesis. The most salient liver-specific effects included: biological processes involved in detoxification, IL6-associated insulin resistance, mTOR hyperactivation, mitotic cytokinesis, spindle pole and microtubule binding. BaP effects that were confined to the testis included: immune system functions, inflammatory response, estrogen and androgen metabolic pathways. Taken together, gene expression and morphometric end point data indicate that the reproductive success of adult male tilapia could be compromised as a result of BaP exposure. These results constitute new insights on the mechanism of action of low dose BaP in a non-model organism (tilapia).

Case-only analyses for identifying genotypes that modify the effect of finasteride in the Prostate Cancer Prevention Trial (PCPT): SWOG S9217.

1551Background: The Prostate Cancer Prevention Trial (PCPT) reported decreased risk of all prostate cancers but increased risk of high-grade prostate cancer in the finasteride arm. The aim of the present analysis was to identify genotypes that modify the effect of finasteride using case-only methods for estimating gene-treatment interactions. Methods: Germline genetic data from 1157 prostate cancer cases in the Prostate Cancer Prevention Trial (PCPT, NCT00288106) were analyzed by case-only methods. Genotypes included 357 single nucleotide polymorphisms (SNPs) from 83 candidate genes in androgen metabolism, inflammation, circadian rhythm and other pathways. Univariate case-only analysis was conducted to evaluate whether individual SNPs modified the finasteride effect on the risk of high-grade and low-grade prostate cancer. Case-only classification trees and random forests, which are powerful machine learning methods with resampling-based controls for model complexity, were employed to identify a predictive...

Genetic association study from North India to analyze association of CYP19A1 and CYP17A1 with polycystic ovary syndrome.

Polycystic ovary syndrome (PCOS) is a complex multifactorial endocrine disorder affecting approximately 5-10% of women of reproductive age. Affected women have menstrual disturbances due to anovulation, infertility, and hyperandrogenism. Ovarian androgen overproduction is the key physiopathologic feature of PCOS. A number of genes encoding major enzymes of the androgen metabolic pathways, such as HSD17B6, CYP19A1, CYP11A1, CYP17A1, and INSR, have been examined. Very few studies have been done in North India. There is an increasing prevalence of PCOS in women in Punjab and it is the leading cause of female infertility. In view of the strong evidence implicating the importance of CYP19A1 and CYP17A1 in androgen metabolic pathways, we investigated the association of rs700519, rs2414096, and rs743572 (- 34T>C) polymorphisms on susceptibility of developing PCOS, in North India. A total of 500 subjects (women of reproductive age) including 250 PCOS cases and 250 healthy age-matched controls were included in the present study. DNA was extracted from venous blood for all samples, and association analysis for rs2414096, rs700519, and rs743572 was done by polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) technique. Lipid profile was done using a biochemical analyzer and body mass index (BMI) was measured for all cases. Statistical analysis was performed. Significant association of - 34T>C polymorphism of CYP17A1 was found with PCOS (p = 0.0005). BMI was statistically different between PCOS cases and controls (p = 0.000). Triglycerides were high in PCOS women. Variations of CYP19A1 were not statistically significant with PCOS. These data suggest that - 34T>C polymorphism in CYP17A1 is associated with PCOS in North India. No polymorphism of CYP19A1 was found to be associated.

A Novel Computational Method for Biomedical Binary Data Analysis: Development of a Thyroid Disease Index Using a Brute‐Force Search with MLR Analysis

The thyroid disease index (TDI), which estimates thyroid disease progress based on hormone concentration measurements and hormone pattern changes, was developed. In this study, we measured concentrations of hormone profiles in the androgen and estrogen metabolic pathways from 23 patients with thyroid disease, as well as 20 unaffected people. We illustrated that the hormones 2‐hydroxyestrone (2‐OH‐E1), 2‐hydroxyestradiol (2‐OH‐E2), 2‐methoxyestrone (2‐MeO‐E1), 2‐methoxyestradiol (2‐MeO‐E2), and 2‐methoxyestradiol‐3‐methylether (2‐MeO‐E2‐3‐methylether) are related to the development of thyroid disease through t‐tests. Though the concentration levels of these hormones generally increase as the disease progresses, big fluctuations cause the determining of a disease's progress by measuring hormone levels to be difficult. The differing patterns between the correlation matrices of the disease and control groups possibly indicates changes in hormone releasing patterns during the thyroid disease's progress. Because of a lack of progressive experimental data on thyroid disease, binary data for the two categories (the thyroid disease patients and the control group) was utilized. Binary logistic regression was used to analyze five risk factors associated with thyroid disease, and the highest overall accuracy was 97.7% with three risk factors. Logistic regression models, however, are unable to describe disease progress. Hence, the TDI was developed to estimate thyroid disease progress. An arbitrary ranking of disease progress was generated for the TDI equation. The ranking contained a total number of 29 030 400 entries with six stages from the control group and eight stages from the disease group. Multiple linear regression (MLR) analysis was performed with a brute‐force search. The best result among the MLR runs presented strong correlation (r2 values of 0.840 and q2 values of 0.663) between the selected hormones and the values of the disease progress in the training set. Overall accuracy of our novel method was 90.7%, which is worse than the 97.7% of logistic regression models. Brute‐force search with MLR analysis might classify different types of thyroid disease progress such as thyroid mass (0.8055), goiter (0.8806), thyroid mass which was a thyroid cancer before operation (0.8951 and 0.9112), and cancer (1.001–2.144). The results show that the TDI is a good indicator of thyroid disease progress and that brute‐force search with MLR analysis is useful for biomedical binary data analysis.

Characterization of Prostate Cancer in a Functional Eunuch

Eunuchs rarely, if ever, develop prostate cancer (CaP). This article reports on a 62-year-old functional eunuch from prepubertal mumps orchitis who developed clinically localized CaP. Serum and CaP and benign prostate tissue androgen levels were measured using a validated liquid chromatography-tandem mass spectrometry assay. The assay measures testosterone; dihydrotestosterone (DHT); the adrenal androgens, androstenedione and dehydroepiandrosterone; and the androgen metabolites, androsterone and androstanedione. Gene and protein expression levels of androgen metabolism enzymes, and androgen receptor and androgen-regulated genes were measured using quantitative reverse-transcription polymerase chain reaction and immunohistochemistry, respectively. Intracrine androgen metabolism produced tissue DHT when serum and tissue testosterone levels were castrate and undetectable, respectively. Androgen receptor, androgen-regulated, and androgen metabolism enzyme genes were expressed but at lower levels in CaP than benign tissues. DHT was synthesized using the primary backdoor androgen metabolism pathway and not using androstenedione or dehydroepiandrosterone via the frontdoor or secondary backdoor pathways.

Dihydrotestosterone synthesis pathways from inactive androgen 5α-androstane-3β,17β-diol in prostate cancer cells: Inhibition of intratumoural 3β-hydroxysteroid dehydrogenase activities by abiraterone.

Intratumoural dihydrotestosterone (DHT) synthesis could be an explanation for castration resistance in prostate cancer (PC). By using liquid chromatography-mass spectrometry, we evaluated the intratumoral DHT synthesis from 5α-androstane-3β,17β-diol (3β-diol), which is inactive androgen metabolized from DHT. 3β-diol had biochemical potential to be converted to DHT via three metabolic pathways and could stimulate PC cell growth. Especially, 3β-diol was not only converted back to upstream androgens such as dehydroepiandrosterone (DHEA) or Δ5-androstenediol but also converted directly to DHT which is the main pathway from 3β-diol to DHT. Abiraterone had a significant influence on the metabolism of DHEA, epiandrosterone and 3β-diol, by the inhibition of the intratumoural 3β-hydroxysteroid dehydrogenase (3β-HSD) activities which is one of key catalysts in androgen metabolic pathway. The direct-conversion of 3β-diol to DHT was catalysed by 3β-HSD and abiraterone could inhibit this activity of 3β-HSD. These results suggest that PC had a mechanism of intratumoural androgen metabolism to return inactive androgen to active androgen and intratumoural DHT synthesis from 3β-diol is important as one of the mechanisms of castration resistance in PC. Additionally, the inhibition of intratumoural 3β-HSD activity could be a new approach to castration-resistant prostate cancer treatment.

Inherited Variants in SULT1E1 and Response to Abiraterone Acetate by Men with Metastatic Castration Refractory Prostate Cancer

Germline variations in genes involved in androgen biosynthesis and metabolic pathways may predict the response to abiraterone acetate in men with metastatic, castration refractory prostate cancer. The variations may serve as prognostic and predictive biomarkers to allow for more individualized therapy. We evaluated 832 single nucleotide polymorphisms from the OmniExpress genotyping platform (Illumina®) in the boundaries of 61 candidate genes reported to be involved in the androgen metabolic pathway. The purpose was to investigate them for an association with time to treatment failure in 68 white men with metastatic, castration refractory prostate cancer undergoing treatment with abiraterone acetate. Cox proportional hazard analysis was used with Gleason score, age, level of alkaline phosphatase and prostate specific antigen at treatment initiation as covariates. Each single nucleotide polymorphism was assessed using an allele carriage genetic model in which carriage of 1 or more minor alleles contributes to increased risk. Subset analyses were done to determine whether metastasis site, or prior treatment with ketoconazole or docetaxel would interact with the single nucleotide polymorphisms investigated. Six single nucleotide polymorphisms in the estrogen sulfotransferase gene SULT1E1 were associated with time to treatment failure on abiraterone acetate therapy after false discovery rate (q value) correction for multiple testing while controlling for Gleason score, age, level of alkaline phosphatase and prostate specific antigen at treatment initiation (q <0.05). Single nucleotide polymorphisms in SULT1E1 were significantly associated with time to treatment failure in men on abiraterone acetate therapy. The single nucleotide polymorphisms may serve as predictive markers for treatment with abiraterone acetate.