Hyperglycemia has recently been described as a risk factor for the development of retinopathy of prematurity (ROP), a proliferative vascular disease of the retina that primarily affects premature infants. This study was to evaluate the relationship of hyperglycemia and the development of ROP in premature infants less than 32 weeks gestation.This was a retrospective cohort study of all infants less than 32 weeks gestation from 2003–2007 who survived to discharge in our NICU. Demographic data including birthweight, gestational age, Apgar scores, method of delivery, antenatal steroid use, neonatal steroid use, and size for gestational age was collected for each infant. Episodes of sepsis, grade of intraventricular hemorrhage, presence of a patent ductus arteriosus, number of days on the ventilator, and stage of necrotizing enterocolitis were assessed as well as days of hyperglycemia, defined as number of days with whole blood glucose > 150 mg/dl. In addition, the highest stage of ROP was recorded for each infant. A Student’s two tailed t-test or Fisher’s exact test was performed to identify significant clinical risk factors associated with the development of ROP. From this univariate analysis, a multiple logistic regression was performed to determine the effect of hyperglycemia on the development of ROP, adjusting for significant clinical risk factors. Statistical analysis was performed using SAS v.9.2.Univariate analysis demonstrated that infants with ROP were of lower birthweight and gestational age, and were affected by a patent ductus arteriosus, neonatal sepsis, intraventricular hemorrhage, have significant lung disease and received postnatal glucocorticoid therapy. Infants with ROP experienced more days with hyperglycemia . Using multiple logistic regression analysis to compare no ROP vs. all stages of ROP, gestational age , mean days of hyperglycemia , and mean days receiving mechanical ventilation  remained significantly associated with ROP after adjusting for other risk factors.Our data suggests that hyperglycemia is associated with the development of ROP in premature infants. Retinopathy of prematurity (ROP) is a proliferative vascular disease of the retina that primarily affects premature infants and is one of the leading causes of visual loss in children . Prematuet al., it was found that 86% of infants with a birthweight less than 1100 grams were hyperglycemic, with the highest risk of being hyperglycemic occurring within the first 24 hours of birth [In addition to genetic risk factors that are associated with the development of ROP -5, thereof birth . Data frRecent studies have shown an association between neonatal hyperglycemia and (1) increased risk of early death and morbidity in extremely low birth weight infants ,10, (2) We performed a retrospective cohort study examining the relationship between hyperglycemia and development of ROP, adjusting for multiple risk factors. A retrospective chart review was performed of all infants less than 32 weeks gestational age admitted to the Neonatal Intensive Care Unit at the University of Iowa Children’s Hospital from 2003–2007 who had ophthalmologic screening for ROP. Initial ophthalmologic screening was performed on all patients with gestational age less than 32 weeks or birthweight less than 1500 gram and follow up was at the discretion of the ophthalmologist. ROP severity was staged by the International Classification of ROP  and the Subject demographic information  was extracted from the patient’s medical records. Episodes of sepsis, presence of intraventricular hemorrhage (IVH), presence of a patent ductus arteriosus (PDA), necrotizing enterocolitis  , and numIn this study, hyperglycemia was defined as the number of days with at least one whole blood glucose level greater than 150 mg/dl. Glucose levels were determined from whole blood using the glucose oxidation technique . Days of hyperglycemia was chosen for analysis rather than highest recorded glucose level to minimize confounding due to differences in the number of laboratory measurements obtained in smaller, sicker infants as compared to larger, healthier preterm infants.Initial univariate analysis was performed to evaluate individual clinical risk factors associated with the development of ROP utilizing either a Student’s two tailed t-test for comparison of means or Fisher’s exact test for comparison of categorical values. From this initial univariate analysis, a multiple logistic regression analysis was performed to determine the effect of hyperglycemia on the development of ROP, adjusted for significant clinical risk factors. We first modeled the relationship between of any degree of ROP vs. no ROP, adjusting for clinical factors found to be associated with ROP in univariate analyses. This was the primary outcome of our study. In addition, further analyses were performed to evaluate the relationship of hyperglycemia to different degrees of ROP. All statistical analysis was performed using SAS v.9.2 . Approval of the University of Iowa Institutional Review Board was obtained to access the clinical information required for this study.We identified 582 infants less than 32 weeks gestation that underwent ophthalmologic screening for ROP. Overall, 412 infants had no ROP and 170 had ROP . There were no cases of Stage IV or V ROP in this study cohort. No infants in this trial received insulin therapy for hyperglycemia.Table From this univariate analysis, a multiple logistic regression analysis was performed to analyze the association of hyperglycemia with ROP while adjusting for other significant risk factors as shown in Tables We then undertook further analyses to explore the relationship of hyperglycemia to different degrees of ROP. We modeled risk factors associated with development of severe (Stage III) ROP among all infants Table . GestatiThis study demonstrates an association between duration of hyperglycemia (defined as number of days with whole blood glucose > 150 mg/dL) and the development of ROP in premature infants less than 32 weeks gestational age.et al. evaluating hyperglycemia and morbidity and mortality in extremely low birth weight (ELBW) infants, it was seen that there was a relationship between severe hyperglycemia (serum glucose > 180 mg/dL) and an increased risk of death or sepsis [et al., also evaluating hyperglycemia as a risk factor for early death and morbidity in ELBW infants, it was shown that neonatal hyperglycemia was significantly associated with an increased risk of death or the development of Grade III/IV IVH [There is emerging evidence that neonatal hyperglycemia is a significant risk factor in neonatal morbidity and mortality. In a study by Kao r sepsis . In anotI/IV IVH .et al. evaluating hyperglycemia and the development of Stage III or IV ROP, it was shown that for each 10 mg/dL increase of mean serum glucose, there was 2.7-fold increase in the risk of developing ROP [et al. also found that hyperglycemia was associated with a 4.5-fold increase in the incidence of ROP in a Hispanic population of ELBW infants [et al., hyperglycemia and insulin exposure was shown to be associated with higher stages of ROP [Hyperglycemia has also been previously shown to be associated with the development of ROP. In a study by Garg ping ROP . Blanco  infants . In a res of ROP . In our et al’s study, where hyperglycemia, as defined by highest measured blood glucose in the first month of life, was found to be associated with the development of Stage III or IV ROP, although they specifically chose to study the impact of glucose on Stages III and IV and included infants with Stage I in the control group of their case–control study. Similar to our results, they also demonstrated a significantly higher number of days with glucose measurements of > 150 mg/dl among patients with ROP , but did not include duration of hyperglycemia in multivariable analysis [Interestingly, however, we were unable to establish an association between duration of hyperglycemia and severe (Stage III) ROP. Utilizing two different multiple logistic regression models, duration of hyperglycemia was found to not be associated with the development of severe (Stage III) ROP. This is in contrast to Garg analysis .In adults, hyperglycemia has been shown to play a significant role in the development of proliferative diabetic retinopathy . Like ROin vitro assay of VEGF production in cultured bovine retinal pigmented epithelial cells, it was shown that those cells that were exposed to a prolonged period of hyperglycemia had significantly elevated level of VEGF production when compared to controls [Hyperglycemia may influence ROP through its significant effect on retinal blood flow . In diabcontrols . While tOur study is limited due to its retrospective nature. Although we have shown an association between hyperglycemia and the development of ROP, we have not presented evidence that is suggestive of causation. The question remains whether hyperglycemia itself is a definitive risk factor, or is a marker of significant illness. We did adjust for other known risk factors which are markers for more severe illness, but the possibility of residual confounders is likely. However, using proliferative diabetic retinopathy as a model of a proliferative vascular retinal disease, it has been shown that hyperglycemia has a significant impact on the development and progression of the disease.In conclusion, we have shown an association between duration of hyperglycemia and the development of ROP in premature infants less than 32 weeks gestation, adjusting for multiple risk factors. As hyperglycemia is a partially modifiable risk factor, further prospective studies are needed to fully evaluate the impact of hyperglycemia and the development of ROP.ROP: Retinopathy of prematurity; IVH: Intraventricular hemorrhage; PDA: Patent ductus arteriosus; NEC: Necrotizing enterocolitis.The authors declare that they have no competing interests.SM was involved in chart review, data synthesis, statistical analysis and drafted the manuscript. JCM and JMD were involved in study design and editing the manuscript. TC was involved in study design, statistical analysis, editing the manuscript, and oversaw the study. All authors have read and approved this manuscript.The pre-publication history for this paper can be accessed here:http://www.biomedcentral.com/1471-2431/13/78/prepub


Despite that a wealth of evidence links striatal dopamine to individualś reward learning performance in non-social environments, the neurochemical underpinnings of such learning during social interaction are unknown. Here, we show that the administration of 300 mg of the dopamine precursor L-DOPA to 200 healthy male subjects influences learning about a partners’ prosocial preferences in a novel social interaction task, which is akin to a repeated trust game. We found learning to be modulated by a well-established genetic marker of striatal dopamine levels, the 40-bp variable number tandem repeats polymorphism of the dopamine transporter (DAT1 polymorphism). In particular, we found that L-DOPA improves learning in 10/10R genoype subjects, who are assumed to have lower endogenous striatal dopamine levels and impairs learning in 9/10R genotype subjects, who are assumed to have higher endogenous dopamine levels. These findings provide first evidence for a critical role of dopamine in learning whether an interaction partner has a prosocial or a selfish personality. The applied pharmacogenetic approach may open doors to new ways of studying psychiatric disorders such as psychosis, which is characterized by distorted perceptions of others’ prosocial attitudes. Finding generic prosocial interaction partners and distinguishing them from selfish ones is of major importance in our social and economic well-being. People learn about a partner’s prosocial preferences by gathering information either through personal interactions or by using information about the reputation of the interaction partner Despite the fact that learning about a partners’ prosocial preferences is a fundamental aspect of our everyday social lives, little is yet known about the regional neurochemical systems that influence learning in social contexts. So far, basic research in non-human animals Striatal dopamine levels are dependent on the availability of the dopamine transporter (DAT) protein, as it reuptakes dopamine from the synaptic cleft into the pre-synaptic compartment after its release. Therefore, DAT is an important regulator of dopamine signaling, most primarily in the striatum, as it only occurs in low concentrations in other areas of the brain Here we explore how L-DOPA induced increases in brain dopamine levels interact with genetically determined individual differences in endogenous striatal dopamine levels to influence learning about a partners’ prosocial preferences. We administered 300 mg of L-DOPA to 205 subjects, who were all genotyped for their DAT1 polymorphism . As L-DO205 healthy young Swiss males with mean (SD) age of 23.5 years (3.6) took part in our double-blind, parallel group and placebo controlled experiment. The study was performed in accordance with the Declaration of Helsinki and approved by the Cantonal Ethic Commission Zurich. Subjects had no significant general psychiatric, medical, or neurological disorder based on the result of structured interviews; they were included in the study after having provided written informed consent. Three subjects were excluded due to self-reported nausea, and two because they did not understand the instructions.The polymorphism for the DAT-1 was characterized using PCR amplification procedure with the following primers:DAT-1:F5′-TGTGGTGTAGGGAACGGCCTG-3′.R5′-CTTCCTGGAGGTCACGGCTCA-3′.PCR reactions were performed using 5 µl Master Mix (Thermo scientific), 2 µl primers (0.5 µM), 0.6 µl Mg/Cl2 (2.5 mM), 0.4 µl DMSO 5% and 1 µl of water to total of 9 µl total volume and an additional 1 µl of genomic DNA was added to the mixture. All PCR reactions were employed on a Biometra T1 Thermocycler . PCR reaction conditions were as follows:Preheating step at 94.0°C for 5 min, 34 cycles of denaturation at 94.0°C for 30 s, reannealing at 55°C for 30 s and extension at 72°C for 90 s. The reaction proceeded to a hold at 72°C for 5 min. All reaction mixtures were electrophoresed on a 3% agarose gel (AMRESCO) with ethidium bromide to screen for genotype.The 9/10R and the 10/10R genotypes accounted for the majority of the observed genotypes in our sample  or a placebo. They then received a standardized meal and 100 ml of water. On the evening before the experiment and 30 min before L-DOPA administration, subjects were required to ingest 10 mg of domperidone in order to avoid possible peripheral dopaminergic side effects such as nausea and orthostatic hypotension. After subjects had read the instructions, we checked whether they had understood the rules of the game by providing control questions. All but two of the subjects answered these control questions correctly. Subjects performed the task 50 min after L-DOPA intake. The task was implemented in z-Tree software and presented on computer screens In our paradigm, two players, player A and player B, begin with an endowment of 10 monetary units (MUs). First, player A has to decide how much of his endowment he wants to transfer to player B, knowing that the transfer is tripled by the experimenter. The transfer has an 80% probability of reaching player B. In this case, B can choose to either make a repayment that equalizes payoffs, or to retain the entire amount. The transfer is “lost” in the remaining 20% of the cases, so that player B receives nothing and cannot make a repayment. Thus, in case of an omitted return, player A does not know with 100% certainty whether this was player B’s intention.To be able to observe learning over time, we let our subjects in the role of player A play several rounds of the task. Each player A plays 20 rounds of the task paired with the same player B in all rounds. Since an omitted return is an extremely powerful aversive social signal, we implemented the “lost transfer” possibility to avoid the problem that player As might immediately withhold positive transfers after observing a single non-repayment. All our subjects in the main experiment are in the role of player A. They are paired with player Bs for whom repayment decisions were pre-recorded, i.e. player Bs decided in how many of a total of 20 rounds they were going to make a repayment. Thus, player Bs made decisions in line with their true prosocial preferences. Player As were aware of the fact that they were paired with a player B whose decisions had been pre-recorded and also about the possibility that their transfers might get “lost” in 20% of the cases.The use of pre-recorded player B decisions is necessary to avoid an important confound. If player A would interact simultaneously with a given player B they could vary transfers strategically to influence player B’s future behavior All player As in our main experiment were matched with one of two types of player Bs: a prosocial one, from whom player As received a repayment in 14 out of the 20 rounds, and a relatively selfish one from whom player As received a repayment in only 6 out of 20 rounds. Player As were not aware of the fact that we deliberately pre-selected a prosocial and a more selfish partner. All transfer decisions had real monetary consequences for player As, and they were told in the instructions that their decisions also have an influence on player Bs’ payoff, which retains the social aspect if this experimental setting. Furthermore, as player As do not have any information about the social preferences of player Bs at the outset, they have to rely on their everyday knowledge about how people would behave in such a social interaction situation. They can then use this information and learn, trial by trial, through positive or negative social feedback about player Bs’ prosocial preferences.In sum, the fact that player As can not influence player Bs’ decisions allows us to exclude any strategic motives that might confound reward-learning behavior and allows to test in an clean way whether L-DOPA administration interacts with player As’ DAT1 polymorphism in modulating learning about a partner’s prosocial preferences.To pre-record the player Bs’ decisions, we conducted a session involving the same task design (without drug administration) several weeks before the main experiment. Each participant had to indicate in how many of 20 rounds he, in the role of player B, would make a repayment. After player B had decided how often he wanted to repay, the computer randomly distributed the repayment decisions across the 20 rounds of the experiment. This procedure allowed us to collect a large number of player B repayment decisions.x ∈ . Player B receives the transfer with probability of 0.8. In this case he can decide to retain all the money or to repay the amount of 2x to equalize payoffs. Player A’s transfer is lost with a probability of 0.2, meaning that player B cannot make a repayment. Player A’s optimal transfer x depends on the probability p with which player B repays when he receives the transfer. Player A’s expected profit E[π] is given as follows:Player A can choose transfers x as long as p>5/8. Thus, if p is larger than 5/8, then player A profits most if he always transfers his whole endowment . If p is smaller than 5/8, then it is best to always transfer nothing . If p equals 5/8, player A is indifferent, as all possible transfers yield the same expected payoff. From this follows that profit-maximizing player As who are matched with prosocial player B should transfer their full endowment in each round, whereas player As who are matched with a selfish player B should not transfer anything.The expected profit is strictly increasing in Side effects were assessed using visual analog scales Our statistical analysis is based on analysis of variance, Mann-Whitney tests and Spearman rank correlations. All tests are two-tailed tests. We examined the impact of partner type [with a binary indicator for partner type indicating whether the player A was confronted with the pre-recorded decisions of a prosocial player B ( = 1) or a ore selfish player B ( = 0)], L-DOPA [with a binary indicator for L-DOPA indicating whether the subject received L-DOPA ( = 1) or placebo ( = 0)], genotype [(with a binary indicator for subjects who carry a 9/10R genotype ( = 1) or a 10/10R genotype ( = 0)], and interactions between these variables in a univariate three-way ANOVA on the investor’s total earnings in the task. Further analyses included the reinforcement learning model parameters alpha and theta as dependent variables . = 10.20, p<0.001, partial eta-square = 0.049). Transfers began to differ according to partner type, on average, by the ninth trial . Applying a standard reinforcement learning model We found that subjects  successfully learn over time who is prosocial and who is not . Average = 4.65, p<0.032, partial eta-square = 0.026). When subjects faced a prosocial partner, we found a significant interaction effect of L-DOPA×DAT1 genotype on learning performance  = 9.66, p<0.003, partial eta-square = 0.098). Specifically, L-DOPA increased learning performance in subjects carrying the 10/10R genotype, assumed to be associated with lower endogenous striatal dopamine levels, with placebo subjects earning an average of 260.2 MUs, while subjects on L-DOPA earned 270.9 MUs . Conversely, we found that L-DOPA administration reversed this learning effect in those subjects carrying the 9/10R genotype, which is assumed to be associated with higher endogenous striatal dopamine levels, with placebo subjects earning 265.7 MUs and L-DOPA subjects earning an average of 249.3 MUs (p<0.050). We found no dopaminergic effects on learning performance when investors faced a more selfish partner .Having established that player As successfully learn about the prosocial preferences of their partners, we looked at the overall learning performance as measured by As’ total earnings in the task. The repayment probability of the pre-selected prosocial type ensured that transferring the full endowment (10 MUs) is the strategy maximizing expected profits , while the repayment probability of the pre-selected selfish type implied that transferring nothing would have maximized expected profits . We found that L-DOPA effects on earnings depend on DAT1 genotype and on partner type p values >0. 202). Finally, controlling for side effects of L-DOPA administration using visual analogue scales, the reported interaction effect of L-DOPA×DAT1 on player As’ learning performance about interactions with a prosocial partner remains significant  = 7.76, p<0.007, partial eta-square = 0.083).Because the observed pharmacogenetic effect on earnings might also result from player Aś level of prosociality before the task started , we checked whether there were differences across drug, player B type, and genotype in player Aś transfers in the first round of the task, but found no evidence for this  determines how strongly a given feedback from a player B (that is positive or no returns) changes the subjective value of the available transfer options (0–10 MUs). A low learning rate implies that the player Bs’ feedback has a relatively small impact on player As’ decision in the next round, whereas a high learning rate implies a relatively larger impact. The second process is captured by the sensitivity parameter. This parameter specifies the exploration-exploitation trade-off of reinforcement learning The total earnings in our task reflect an important outcome variable of the player As’ learning process, but this measure says little about p values >0.316). In contrast, we found a clear interaction of L-DOPA and player As’ DAT1 genotype on the sensitivity parameter . When expressing the sensitivity parameter for easier interpretation as the probability of choosing the transfer with the highest expected value  benefit the least from transfers to a prosocial partner is also intriguing from a clinical perspective. Psychotic patients exhibiting paranoia show pronounced distrust of others, even though they reside in a conducive environment as part of their treatment regimen in the clinic. Current theories hold that psychosis might result from a disturbance in error-related updating of inferences and beliefs about the world The fact that we found no dopaminergic effects on learning performance when player As’ faced a selfish partner adds novel pharmacogenetic evidence on the ongoing debate over dopamine’s role in appetitive and aversive instrumental learning The probabilistic learning paradigms in non-social contexts employed by research in Parkinsońs disease patients and healthy subjects have some commonality with our task in the sense that investors are required to make stimulus-outcome associations based on probabilistic feedback from the interaction partner. Thus, the fact that the DAT occurs mostly in the striatum, but only in low concentrations in other areas of the brain In sum, while dopaminergic drugs have been shown to affect human reward learning in non-social contexts via modulation of striatal activity, imaging studies of social interactions have shown that activation of the striatum tends to facilitate human cooperative behaviors. Here we show a causal role of the dopaminergic system in learning about otherś prosocial preferences. Exogenous dopamine improves learning performance in subjects who carry the 10/10R genotype, assumed to be associated with lower striatal dopamine levels, and impairs learning performance in people with the 9/10R genotype, assumed to confer higher striatal dopamine levels. These effects might not be related to specifically social situations, but may rather result from a dopaminergic modulation of a general reward learning mechanism. Our findings are not only relevant for fundamental research, but potentially constitute a stepping stone for new ways of understanding psychiatric disorders that link the dopaminergic system with distorted perceptions of otherś prosocial attitudes.Figure S1Estimated probability of choosing the option with the highest subjective value. .(EPS)Click here for additional data file.Figure S2BIC values of the different models employed.(EPS)Click here for additional data file.Materials S1.(DOC)Click here for additional data file.


The androgen receptor (AR) is important in the development of the prostate by regulating transcription, cellular proliferation, and apoptosis. AR undergoes posttranslational modifications that alter its transcription activity, translocation to the nucleus and stability. The posttranslational modifications that regulate these events are of utmost importance to understand the functional role of AR and its activity. The majority of these modifications occur in the activation function-1 (AF1) region of the AR, which contains the transcriptional activation unit 1 (TAU1) and 5 (TAU5). Identification of the modifications that occur to these regions may increase our understanding of AR activation in prostate cancer and the role of AR in the progression from androgen-dependent to castration-resistant prostate cancer (CRPC). Most of the posttranslational modifications identified to date have been determined using the full-length AR in androgen dependent cells. Further investigations into the role of posttranslational modifications in androgen-independent activation of full-length AR and constitutively active splicing variants are warranted, findings from which may provide new therapeutic options for CRPC. N-terminal domain (NTD) ), antiandrogen, or reagents that activate other signaling pathways and alter transcriptional activity, cellular localization, and stability of AR . Most of32P-phosphopeptide mapping, suggesting that PKA is not responsible for AR S16 phosphorylation. Given that forskolin treatment did increase the overall AR phosphorylation level in LNCaP cells [C-terminus of AR upon dimerization. Deletion of residues 14–150 impedes the dimerization of AR [Serine 16 (S16) phosphorylation is ligand dependent, as phosphorylation at this site increases upon treatment with ligand ,77,78. Son of AR . PhosphoH-pyrazolo[Phosphorylation of serine 81 (S81) is mediated by cyclin dependent kinases (CDKs), including CDK1, CDK5, and CDK9. CDK1, cyclin B1, cyclin B2 and cdc25 are upregulated in PCa –85. Acti-pyrazolo,4quinoxa-pyrazolo,81. In c-pyrazolo. These d-pyrazolo. HoweverAR S81 phosphorylation plays an important role in AR transactivation, cellular localization and stability as well as cell proliferation. Ectopic expression of the S81 phosphorylation-resistant mutant S81A failed to activate the ARE4-Luc reporter gene in androgen-treated HeLa and 293T cells . These dIt was reported that the S81A mutant remained in the cytoplasm, while a phosphomimicking mutant, S81D, localized in the nucleus in the absence of ligand . In LNCaEvidence suggests that serine 94 (S94) in AR is constitutively phosphorylated and hormone insensitive ,77,87,88Serine 213 (S213) phosphorylation has been studied extensively. To date, AKT  and PIM-Another kinase that regulates the phosphorylation of S213 is PIM-1 ,89. PIM-AR is also phosphorylated at serine 256 (S256) ,77,91. CTwo residues in close proximity of each other, threonine 280 and serine 291, are phosphorylated by Aurora A (AurA) in both the absence and presence of androgens. Expression of AurA is elevated in androgen refractory LNCaP derivative cells but not in the androgen sensitive parental LNCaP cells. Furthermore, higher levels of AurA were observed in LAPC-4, 22Rv1, DU-145, and PC-3 cells compared to LNCaP cells. In the absence of androgens, forced expression of AurA increased ARR3-Luc activity in LNCaP cells, while expression of an inactive AurA impeded ARR3-Luc activity. Treatment of LNCaP cells with R1881 had a minimal enhancement of luciferase activity in cells expressed either the active or inactive AurA. This data suggests that T280 and S291 are not critical for androgen induction of AR’s transcriptional activity, but that they may be important in androgen-independent AR activation. These two residues may also work in concert with other phosphorylated residues to enhance AR activity. For example, AurA regulates the activation of cyclin B1/CDK1 , which ip58, which decreases the AR’s transcriptional activity [p58 and/or cyclin D3 yielded a decrease in luciferase activity (MMTV-Luc) compared to control vector-transfected cells treated with DHT. A similar result was observed in LNCaP cells. An increase in cyclin D3/CDK11p58 activity was observed upon DHT treatment of LNCaP cells [p58 by DHT induces S308 phosphorylation and decreases AR activity although this effect can be surpassed by other mechanisms, resulting in overall activation of the AR by DHT.One residue identified in the TAU1 region to negatively regulate the transcriptional activity of AR is serine 308 (S308) ,93. S308activity . COS1 anSerine 424 (S424) is a phosphorylation site within the TAU5 region of AR ,77. AlteSerine 515 (S515) undergoes phosphorylation mediated by CDK7 and MAP kinase ,71. The Although serine 578 (S578) lies within a PKC consensus phosphorylation motif, the kinase responsible for phosphorylation at this site is still undetermined. Treatment of CWR-R1 and Ishikawa cells with EGF resulted in an increase in AR transcriptional activity, which coincided with an increase in phosphorylation of S578. Both FLAG-AR-(amino acids 507–660)-S578D (phosphomimetic) and FLAG-AR-(amino acids 507–660)-S578A (phosphorylation-resistant) were transfected into COS cells to investigate cellular localization of AR. The phosphomimetic mutant was equally distributed between the cytoplasm and the nucleus, while the alanine mutant exclusively resided in the nucleus . These fN-terminal kinase (JNK)1 or MKK6/p38α increased S650 phosphorylation. A minimal increase in phosphorylation was observed when MAPK/ERK (MEK) was overexpressed; but no decrease in S650 phosphorylation was observed upon inhibition of MEK with UO126. However, inhibition of either p38 (SB203580) or JNK1 (SP600125) significantly decreased the amount of S650 phosphorylation. Additionally, when MKK4 or MKK6 knocked down by siRNAs, there was an increase in the expression of PSA mRNA in the absence or presence of DHT [617RKCYEAGMTLGARKLKK633 sequence regulates the localization of AR into the nucleus [Phosphorylation of serine 650 (S650) occurs both in the presence and absence of androgens  and regue of DHT . The phoe of DHT . Thus, Se of DHT . S650 ise of DHT . This bi nucleus –97 and i nucleus . These dCIP1 via lack of AR binding to the promoter of p21CIP1[i.e., the half-life of AR protein decrease  and was restored with the proteasome inhibitor MG132. This suggests that phosphorylation of AR at S791 plays a role in the ubiquitination of AR and its degradation; this residue is the only modified residue within 50 amino acids of the ubiquitinated lysine 845 and 847 [Phosphorylation of serine 791 (S791) is similar to S213 in that it is dependent on AKT. The phosphomimetic mutant S791D exhibited reduced binding of ligand, a decrease in nuclear translocation, and reduced transcription of p21f p21CIP1. Phosphof p21CIP1. AR stab and 847 . IGF-1 t and 847 .Threonine 850 (T850) phosphorylation results in AR stabilization and mediates the low-androgen transcriptional activation of AR, due to recruitment of the E3 ubiquitin ligase RNF6. The phosphorylation of T850 is cycle-cycle dependent with increase phosphorylation during the G2 and M phase, which coincides with increased PIM-1 (S or L) expression. PIM-1L phosphorylates AR at T850, in COS-1 cells that expressed AR, and either the long (1L) or short (1S) isoform of PIM, only upon expression of PIM-1L was phosphorylation observed at T850. AR mutation at T850 resulted in lower AR protein levels during the M phase, these data suggest that phosphorylation at T850 stabilizes AR during the M phase. Upon overexpression of PIM-1L, there was no decrease in AR half-life while the overexpression of the 1S did. This suggests that phosphorylation of T850 protects AR from degradation . UbiquitTwo of the AR tyrosine (Y) residues that are phosphorylated are Y267 and Y363. Both sites are phosphorylated by Ack1, which promotes androgen-independent growth of LNCaP and LAPC4 xenografts in castrated mice. This androgen-independent growth may be a result of the increased recruitment of AR to AREs in the absence of androgens. The role of Ack1 in the proliferation of LNCaP cells in the absence of androgens was further supported by other studies, which showed that the expression of an inactive Ack1 (dAck1) had limited effect on tumor growth, and it was also shown that if the dAck1-expressing cells were exposed to DHT, AR failed to induce PSA expression. These data suggest that Ack1 plays an important role in the activation of AR as a transcription factor in both androgen dependent and independent cells. To confirm that Ack1 is critical for the activity of AR, a constitutively active Ack1 (ca-Ack1) was expressed in LNCaP cells. In the absence of ligand there was an increase in AR binding to the PSA promoter, and when cells were treated with low doses of androgen (levels at which no increase was observed when Ack1 was not constitutively active), there was an increase in PSA expression. This suggests that Ack1 sensitizes PCa cells to low levels of androgens and that Ack1 may facilitate progression from AD to AI phenotype . Anti-anAnother tyrosine residue in AR phosphorylated is tyrosine 534 (Y534), which is a highly conserved residue in AR among species ,72. ReceAdditional tyrosine residues, identified to be posttranslational modified in hormone-refractory prostate tumor xenografts, are Y223, Y307, Y46, Y357, Y362, Y393, Y551, and Y519 . Upon trMass spectroscopy identified both Y363 and Y362 were phosphorylated in the hormone-refractory xenograft. A single residue within the TAU5 region Y393 increased in its phosphorylation state upon treatment with SRC kinase. The increase in the SRC kinase activity has been correlated with the progression of PCa from the androgen-dependent state to the hormone refractory state ,100 incrOne tyrosine residue (Y551) is located within the DBD of AR and one in the LBD (Y915) was also identified by mass spectroscopy when SRC was overexpressed. The functional role of these phosphorylated tyrosine residues are unknown, but do require further investigation to determine if these modifications result in the constitutive activity of AR. The increase in SRC activity in CRPC and the increase in Tyr phosphorylation suggest that these are a possible therapeutic option to ablate the activity of AR and slow or inhibit the progression of PCa.There is an increase in tyrosine phosphorylation in CRPC . In andret al. showed that forced expression of Her-2/neu expression lead to androgen independence of PCa, suggesting that Tyr phosphorylation may play a pivotal role in this transformation [Craft ormation . Additioormation , forced ormation . In clinormation .Phosphorylation of tyrosine (Y) resides in AR have been implicated in the progression to CRPC . AlthougThe reversible process of phosphorylation of the AR has not been extensively studied. The dephosphorylation of AR occurs through protein phosphatases PP2A and PP1 ,78,91. PInhibition of PP2 with fostriecin  resulted in an increase in AR protein in LNCaP, HeLa, COS1 and 293T cells . InhibitAcetylation has been found on three residues within the hinge region of the AR. The three residues K630, K632, and K633 are important for the ligand–dependent activation of AR . MutatioDeacetylation of AR can be mediated by HDAC1. Inhibition of HDAC1 resulted in an increase in the amount of acetylated AR protein, which had increased activity in response to low concentrations of androgens . A seconSimilar to histones and other proteins, AR can be methylated. Methylation of AR occurs at two residues within the hinge region. These two residues, lysine 630 and 632, overlap with the acetylation residues . Both ofUbiquitination (Ub) is a small covalent modification that has been identified on two lysine residues in the LBD of the AR . UbiquitAR). The NESAR is located within the LBD (between residues 743–817) and is only found in the full-length and is absent in the variants [AR fusion protein had a decrease in half-life compared to GFP-tagged protein. There are no known residues that are ubiquitinated in AR within this sequence; however, these data suggest that this is a potential degron sequence. When GFP-NESAR protein was expressed in LNCaP or C4-2 cells, it had a shorter half-life compared to GFP protein alone. Treatment with MG132 rescued the loss of GFP-NESAR while it had no effect on the GFP alone in transfected cells. In PC3 cells transfected with His-tagged ubiquitin and GFP or GFP-NESAR, there was an increase in ubiquitinated GFP-NESAR fused protein. Interestingly, inhibition of the proteasome resulted in the aggregation of the NESAR in aggresomes. The two lysine residues that are known to be ubiquitinated are located downstream of the NES and only found in the full-length AR. The aggregation of the NESAR into aggresomes is a possible mechanism of protein degradation for the AR-variants as they lack the LBD and the residues that are known to be ubiquitinated [AR’s increase in expression and/or stability is hypothesized as being a possible mechanism that can sensitize androgen receptor to low levels of androgens, and possibly lead to castration resistance. One mechanism that could result in the increase in AR protein is the lack of ubiquitination and degradation of AR. A second possibility that could reduce AR’s transcriptional activity is AR’s cellular localization, which is regulated by its nuclear export signal  is a coactivator of AR, and upon knockdown by siRNA, there is an accumulation of AR at AREs, and decreased polyubiquitination. Knockdown of ZIPK reduces mRNA expression by 20%–40% due to the recruitment of AR to the promoter and enhancer regions of PSA and KLK2. Within 90 min of DHT treatment, ZIPK interacts with AR while in the second cycle (>180 min) there was no ZIPK. Knockdown of ZIPK yields similar results as inhibition of proteasome by MG132 rescues AR protein. Coexpression of ZIPK and Mdm2 in HEK293 cells yields enhanced luciferase activity, while coexpression of Mdm2 and a dead ZIPK (ZIPKD161A) had a decrease in Mdm2 phosphorylation. DHT treatment increased the amount of monoubiquitnation, while coexpression of Mdm2 enhanced polyubiquitination of AR; similarly, coexpression of ZIPK also resulted in an increase in polyubiquitination. The coexpression of the ZIPKD interfered with the increase of polyubiquitination and reintroduction of the ZIPK rescued AR polyubiquitination .AR can also undergo SUMOylation, which is the attachment of approximately 100 amino acids of small ubiquitin-like modifier (SUMO) to lysine residues . SUMOylaThe posttranslational regulation of the AR has been extensively studied in androgen dependent cells. However, there have been few studies that have investigated the role of these modifications in CRPC. The activation of AR in androgen dependent cells is well established upon androgen treatment. However, the question of how AR is constitutively activated in CRPC is not well understood. In addition to the activation of the full-length receptor in CRPC, there are several splice variants that are constitutively activated. The reviewed posttranslational modifications to AR described above are mostly completed using full-length AR that was either expressed in cells that do not endogenously express AR , or in androgen dependent cell lines (LNCaP). The identification of these modifications in androgen dependent PCa cells should also give insight into the potential role of these modifications in CRPC.The major posttranslational modification of the AR is phosphorylation, which regulates AR cellular localization, transcriptional activity, and stability. Since the majority of the modifications are known to enhance transcriptional activation, it would suggest that in CRPC cells, AR might also be phosphorylated at these sites, thereby promoting its constitutive activity. In androgen dependent cells, it was shown that S308 negatively regulates the activity of AR. This residue is located within the TAU1 region, which plays a pivotal role in regulation of androgen independent activation of the AR. In CRPC, AR regulation shifts from the TAU1 to the TAU5 region. Thus, it is important to determine in the future whether S308 phosphorylation plays a leverage role in this transition. Additionally, several residues are phosphorylated upon androgen treatment  and were phosphorylated upon deletion of the LBD. These data suggest that there are additional mechanisms mediating AR phosphorylation, which may be responsible for AR’s constitutive activity.The complexity of cross talk and cellular signaling may help explain the constitutive activity of AR. The PI3K inhibitor, PTEN, has been shown to be down regulated or lost in CRPC, which would allow for activation of PI3K and ultimately its downstream effector, AKT. The increase in cytokines  has the potential to activate signaling pathways that may stimulate the activity of AR by regulating its phosphorylation –133. SevThe AR-variants lack the LBD and are constitutively active. It would be important to define the phosphorylation spectrum of the AR-Vs under androgen deprivation conditions. Findings from this investigation should shed new light on our understanding of the mechanism underlying constitutive activation of the AR and, thereby, provide new avenues for better targeting aberrant activation of the AR in CRPC.


A one vs. all classification analysis showed that most emotional expressions that participants perceived could be reliably predicted from the neural pattern of activity in left and the right FFA, suggesting that the perception of different emotional expressions recruit partially non-overlapping neural mechanisms. In addition, emotional expressions could also be decoded from the pattern of activity in the early visual cortex (EVC), indicating that retinotopic cortex also shows a differential response to emotional expressions. These results cast doubt on the idea that the FFA is involved in expression invariant face processing, and instead indicate that emotional expressions evoke partially de-correlated signals throughout occipital and posterior temporal cortex.It is widely assumed that the fusiform face area (FFA), a brain region specialized for face perception, is not involved in processing emotional expressions. This assumption is based on the proposition that the FFA is involved in face identification and only processes features that are invariant across changes due to head movements, speaking and expressing emotions. The present study tested this proposition by examining whether the response in the human FFA varies across emotional expressions with functional magnetic resonance imaging and brain decoding analysis techniques ( Many functional models of face processing propose that the neural pathways involved in face identification are separate from the pathways that are involved in recognizing emotional expressions  has been described as the standard view in the area  that minimizes the prediction error  for a labeled dataset. Prediction involves calculating a weighted sum of input activation patterns from the learned parameters for each discriminant function. Typically, the predicted class corresponds to the discriminant function with the highest weighted sum. If the classifier can predict the category of stimulation from the activation patterns (at above chance levels), then this indicates that the brain region shows a distinct pattern of response to the different categories of stimuli. However, since classifiers are prone to over-fitting, classification performance can be over-estimated if the training data is used to evaluate the classifier. An unbiased estimate of classifier performance is obtained by training and testing the classifier on different sets of data.Our rationale for the present study is that if a classifier was able to accurately predict expressions from the pattern of activity within the FFA, then this would indicate that different emotional expressions evoke distinct patterns of activity in this region and so suggest that the face processing in the FFA codes emotional expression information.M = 25 years, 10 males). One participant that moved more than 4 mm across the complete scanning session was removed from the analysis. All participants were unaware of the aim of the study. The research was approved by the University of Western Sydney Human Ethics Committee and adhered to the principles contained within the Declaration of Helsinki.Twelve graduate students gave fully informed consent to participate in the study . Blocks of house images were also included to verify that the classifier could discriminate the patterns elicited by objects from different categories . Each category of stimulus appeared once per run and order of conditions was randomized across runs.Each block of stimulation (for both type of run) involved presenting the 16 face or house stimuli once in a random order. Each stimulus was presented for 500 ms followed by a 500 ms blank interval between stimuli. Two of the stimuli in each block were randomly selected to appear in consecutive trials. Participants were instructed to indicate detection of these repetitions by pressing a button. Participants completed two localizer runs, followed by 8–12 emotion runs.* weighted, gradient echo planar imaging sequence . Volumes consisted of 26 slices covering the ventral temporal and frontal lobes that were angled to minimize coverage of the sinus cavity. High resolution T1 weighted anatomical images was also acquired for each participant .Brain images were acquired in a Phillips Achieva 3.0T TX scanner with an 8 channel head coil. Functional images were collected with a T2http://www.fil.ion.ucl.ac.uk/spm/software/spm8/). The first four volumes of each run were automatically discarded before image processing. Images from the localizer and emotion runs were coregistered by aligning and unwarping all images to the first volume. Images from the localizer run were spatially smoothed with a 6 mm Gaussian filter, and the time series of each voxel was high pass filtered at 1/128 Hz. Correlations between scans and periods of face and house stimulation were modeled by a standard hemodynamic response function at each voxel. A t-test examining greater activity during face stimulation vs. house stimulation was used to localize the right and left FFA (p < 0.001 uncorrected). Additional spherical masks with the same volume as the FFA masks were also created for the purpose of a control analysis (see Results). These masks were centered on the left parahippocampal place area (lPPA), a region that selectively responds to images of scenes . Parahippocampal gyrus was identified as the most medial gyrus in the ventral temporal lobes, and the fusiform was identified as the gyrus lateral to the parahippcampal gyrus. Anatomical scans were used to construct the EVC masks by placing the spherical mask to cover as much of the occipital pole as possible. Face selective regions in the STS were not examined in the present study since the slice prescription did not cover the dorsal temporal lobes.Image pre-processing and localization of the regions of interest was performed in SPM8  were spatially normalized into MNI space for the purposes of reporting the coordinates of the peak voxels. All the remaining analysis was conducted in native space to preserve the fine patterns of activity.Statistical images (http://code.google.com/p/princeton-mvpa-toolbox/). The time-course data for all voxels within a region of interest was extracted. The time-course for each individual voxel was z-score transformed so that the mean and standard deviation of the signal across each run was zero and one (respectively). This transformation was applied independently to each voxel within a ROI to ensure that highly variable voxels did not bias the classifier, and to facilitate optimization of the classifier weights during training. Normalization was performed separately for each run. Time points within each block of stimulation were averaged to produce one pattern of activity for each condition in each run. To account for hemodynamic lag, only time points corresponding to data collected 9–18 s after block onset were averaged.Pattern analysis was conducted on the unsmoothed, realigned data from the emotion runs with the Princeton Multi-Voxel Pattern Analysis toolbox  for all but one run, and then using the trained classifier to predict the category of stimuli from the test patterns in the remaining run. The cross validation procedure was repeated until reach run was used as the test set, and classification performance was averaged over all iterations.p < 0.05) were not included in training or testing. Evaluating classifier performance with a cross validation procedure ensured that the classifier was tested on data that was independent from the data used for feature selection  and classifier training. Thus, this procedure provides a measure of classifier performance that is free from overfitting the dataset and so avoiding circular analysis.Prior to classifier training, a simple feature selection procedure was used to reject any voxel that did not show a significantly different response across the categories of stimuli. This involved entering the activation data for each voxel from all of the training patterns into a one way ANOVA with stimulus category as different levels of the factor. Any voxel that did not pass a liberal threshold  = 1.3, p = 0.39].Average one-back performance was high, with participants detecting 92.4% of all stimulus repetitions. A repeated measures analysis did not reveal any significant differences across the different categories of stimuli . The main effect of expression  and the interaction between region and expression was not significant . Classification performance was averaged over emotional expression for each participant and ROI to examine the main effect of region. Two-tailed, paired sample t-tests revealed that left FFA classification performance was higher than the left PPA  but not the EVC . Similarly, right FFA classification performance was higher than the right PPA  but not the EVC .Classification performance for each region and emotional expression was entered into a 5 (Region) × 6 (Expression) repeated measures ANOVA to examine whether there were any differences in the pattern of classification across the regions of interest. This analysis showed that there was a significant main effect of region [x 42, y −47, z −22) and left FFA . Table p-value for a single sample t-test (two tailed) comparing classifier performance against chance (50%). For a Bonnferoni corrected criteria (α = 0.0083) the results showed that all emotional expressions could be decoded in the right FFA, and all but happiness and anger could be decoded in the left FFA. These results indicate that most emotional expressions evoke partially non-overlapping mechanisms in the FFA. Classification performance in the EVC showed a similar pattern as the fusiform, with only fear failing to be classified more accurately than chance. Classification performance in left and right PPA was not significantly above chance for all emotional expressions.Classification analysis showed that most emotional expressions could be decoded from the patterns of activity in the right (mean MNI coordinates The present study showed that emotional expressions could be decoded from the pattern of activity in the FFA. Contrary to many models of face processing (Haxby et al., Evidence that the FFA is involved in processing changeable facial features raises the question of what role this region plays in the face processing network. It is possible that the FFA is functionally specialized to extract expression invariant face information but shows a differential response to emotions because this region occupies an intermediate stage in the face identification pathway (e.g., Rotshtein et al., An alternative proposal to the one described above is that the FFA contributes to both identification and emotion processing because this region is involved in processing the configural information associated with invariant and changeable facial features. There is considerable evidence that the FFA is involved in processing the configuration of facial features (Yovel and Kanwisher, The results of the present study may provide clues about which of these two accounts best explain the observed differential response to emotional expressions in the FFA. If the FFA was a part of a pathway that gradually extracts expression invariant information, then it should be the case that the FFA is less sensitive to emotion information than the EVC. However, the present study did not reveal any differences in classification performance for the FFA and EVC. So it might be possible that the FFA is involved in processing both identity and emotional expressions. Of course, to draw this conclusion it would also need to be shown that emotion and identity information are decoded at similar levels of accuracy in the FFA for stimuli that have been matched for visual similarity. If, on the other hand, such an experiment revealed that identity information evoked more distinct patterns than emotional expressions, then this would support the view that the FFA is partially invariant to emotion information.The finding that emotional expressions could also be distinguished from the patterns of activity in the visual cortex, indicates that emotional expressions evoke activity in partially non-overlapping mechanisms in the earliest stages of visual processing. Since EVC forms an image-like representation of incoming visual input, evidence of partially de-correlated signals in retinotopic cortex suggests that emotional expressions are somewhat visually distinct. This finding is consistent with the idea that emotional expressions have evolved to minimize the overlap between different expressions and so facilitate transmission of emotional information to observers (Smith et al., In conclusion, the present study found that emotional expressions evoke distinct patterns of activity throughout the occipito-temporal cortex, including the FFA. This finding runs against the widespread view that the FFA is involved in expression invariant processing. Indeed, the results of the one vs. all classification analysis showed that emotional expressions evoke partially separable neural mechanisms across early vision, suggesting that emotional expressions have evolved to support efficient signal decoding in the brain.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Chromatin immunoprecipitation confirmed STAT1, RHOA, ITGB5, MAPKAPK2, CSNK2A,1 and PIK3CB genes as novel AR targets in PCa disparities. Moreover, functional screens revealed that androgen-stimulated AR binding and upregulation of RHOA, ITGB5, and PIK3CB genes were associated with increased invasive activity of AA PCa cells, as siRNA-mediated knockdown of each gene caused a loss of androgen-stimulated invasion. In summation, our findings demonstrate that transcriptional changes have preferentially occurred in multiple signaling pathways converging  on AR signaling, thereby contributing to AR-target gene activation and PCa aggressiveness in AAs.The incidence and mortality rates of prostate cancer (PCa) are higher in African American (AA) compared to Caucasian American (CA) men. To elucidate the molecular mechanisms underlying PCa disparities, we employed an integrative approach combining gene expression profiling and pathway and promoter analyses to investigate differential transcriptomes and deregulated signaling pathways in AA versus CA cancers. A comparison of AA and CA PCa specimens identified 1,188 differentially expressed genes. Interestingly, these transcriptional differences were overrepresented in signaling pathways that converged on the androgen receptor (AR), suggesting that the AR may be a unifying oncogenic theme in AA PCa. Gene promoter analysis revealed that 382 out of 1,188 genes contained  Prostate cancer (PCa) is the most commonly diagnosed noncutaneous cancer and, after lung and bronchus cancers, the second leading cause of cancer deaths among American men , 2. In tThe human androgen receptor (AR) plays a critical role in the growth and differentiation of the normal prostate gland as well as in the development of PCa , 4. AR eα-reductase, are prevalent in AA men. In addition, these two polymorphisms were shown to correlate with the elevated 5-α-reductase activity [ In the US, the African American (AA) population exhibits higher incidence and mortality rates of PCa compared to the Caucasian American (CA) population . Accumulactivity  and highactivity , respectactivity . The CAGactivity , and preactivity , 19, 20.activity –23. TakeGene expression analysis by DNA microarrays, and more recently by next generation sequencing, has proven to be a useful tool in assigning genomic signatures to different subtypes and stages of cancers. The goal of these analyses has been to provide more precise diagnoses and improved predictions of clinical outcomes. To date, the majority of PCa microarray studies have been employed in the comparison of gene expression profiles in normal prostate and different stages of PCa –31, withIn this study, we have employed DNA microarrays and bioinformatics to compare the gene expression profiles between AA and CA cancers, and between PCa and patient-matched normal prostate from AAs and CAs. By integrating gene expression profiling and pathway analyses, multiple components within the AR signaling pathway were revealed to be upregulated in AA PCa specimens , portending that AR pathway activation is a key component of PCa health disparities. The upregulated AR signaling pathway was associated with 382 AR-responsive genes based on microarray and promoter analyses; selected AR-responsive genes were confirmed by chromatin immunoprecipitation and functionally validated to participate in AR-mediated invasive activity in AA PCa cell lines. These results provide a first glimpse of AR-responsive genes likely contributing to the more aggressive PCa phenotype in AA men.Prostate tissue procurement procedures implemented at The George Washington University Medical Faculty Associates (GWU-MFA) were in accordance with IRB approved protocols. A transrectal ultrasound biopsy of the prostate was performed in patients with an elevated serum PSA level of >7 ng/mL, or PSA level of >4 ng/mL in the presence of an abnormal digital rectal exam. Prostate needle biopsy cores were collected and immediately examined by a board certified pathologist at the GWU-MFA. PCa cores eligible for genomic analysis were determined to have a pathologic tumor stage of 2 and Gleason score of 6-7 (17 AA and 13 CA patients) or 8-9 (3 AA and 2 CA patients). There was no significant difference between the two racial groups with respect to age . In addition, there was no significant difference between the two groups with respect to tumor content in the biopsies . Paired normal biopsy cores were also collected from the same patients. Altogether in this study, each of the 20 AA and 15 CA patients contributed a PCa biopsy core along with a patient-matched normal core for DNA microarray analysis and qRT-PCR validation.μg) from each core was purified using the RNeasy micro kit  and interrogated for mRNA expression patterns with the Affymetrix Human Exon 1.0 ST GeneChip. High-quality, non-degraded total RNA was confirmed on the Agilent 2100 Bioanalyzer prior to performing expression profiling experiments. Affymetrix microarray data were normalized by quantile normalization with GC-RMA background correction, and data visualization and statistical analysis were performed by Partek Genomics Suite 6.5 software  as described previously [http://www.ingenuity.com/). Differentially expressed genes were tested for statistical overrepresentation in specific canonical pathways in the Ingenuity Knowledge Base. The significance of the association between gene data set and canonical pathway was determined by the ratio of number of differential expressed genes to the total number of molecules in the specific pathway and the P value determined by Fisher's exact test.Total RNA was isolated from PCa and patient-matched normal prostate biopsy cores. Total RNA . Maximum matrix dissimilarity rate was set at 5% as criterion to predict the conserved AR binding sites on the target genes as previously described [Prediction of AR binding sites on the promoter regions (within 1 kilobase upstream of the start codon) of genes differentially expressed between AA cancers versus CA cancers was performed using the ALGGEN-PROMO program , cells were removed from DMEM/10%FBS or BRFF-HPC1 medium and cultured in DMEM medium containing 0.1% FBS for 24 hr and subsequently treated with or without DHT (10 nM or 100 nM) for 18–24 hr. PCa cell lines VCaP and MDA PCa 2b were purchased from American Type Culture Collection . The E006AA cell line was kindly provided by Dr. Johng Rhim. VCaP and E006AA cells were maintained in DMEM medium  supplemented with 10% fetal bovine serum (FBS) and penicillin/streptomycin, while MDA PCa 2b cells were grown in BRFF-HPC-1 medium supplemented with 20% FBS and penicillin/streptomycin. All the cell lines were grown at 37°C and 5% COμg of RNA was used for cDNA synthesis. The reverse transcription was performed with random hexamer primer using TaqMan Reverse Transcription Reagents . Real-time PCR was performed using SYBR Green PCR Master Mix from Applied Biosystems . Three to five independent experiments were assayed in duplicate and normalized to levels of house-keeping genes EIF1AX and PPA1  [EIF1AX and PPA1 are stably expressed and resistant to expression changes under different conditions and hence serve as ideal endogenous control genes for qRT-PCR assays [PCa cell lines were grown to 70%–80% confluence, washed with PBS, scraped, centrifuged, and resuspended in Trizol reagent . RNAs from PCa biopsy specimens that were expression profiled by microarray analysis were also subjected to real-time RT-PCR validation assays. For PCa cell lines, RNA were isolated as described for PCa biopsy specimens . Two , resp.) . We haveR assays . Log2 raR assays . Primer β (sc-603) were purchased from Santa Cruz Biotechnology . Rabbit polyclonal antibodies for RHOA (ab54835) and β-actin (ab8227) were purchased from Abcam . Chromatin immunoprecipitation (ChIP) Assay Kit was purchased from Millipore , and ChIP assays were performed as previously described [Western blotting assays were performed as previously described . Rabbit HOA ab548 and β-acμL of growth media (with 10% FBS in DMEM or 20% FBS in BRFF-HPC1) was added into each bottom well of a 24-well plate and inserts were placed individually into each well. The E006AA cells or MDA PCa 2b cells in 200 μL serum-starved media (DMEM or BRFF-HPC1 with 0.1% FBS) were seeded into each top well. After 48 hr, the invading cells were fixed, stained, and counted under light microscope as previously described [RHOA, ITGB5, and PIK3CB were purchased from Dharmacon , and siRNA against human PRKD1 was purchased from Ambion . Cells were transfected with 50 nmol/L siRNA using DharmaFECT 4 reagent from Thermo Fisher Scientific  for 24 hr according to the manufacturer's protocol. Scrambled nonsense siRNA sequence served as a control. After 24 hr the cells were trypsinized and seeded in a matrigel invasion assay as described above. RNA from a portion of cells was retained for RT-PCR studies to verify knockdown efficiency . The target sequences of the siRNAs are as follows: RHOA, CGACAGCCCUGAUAGUUUA; ITGB5, GCUCGCAGGUCUCAACAUA; PIK3CB, GGAUUCAGUUGGAGUGAUU, and PRKD1, CGGCAAAUGUAGUGUAUUA. Experiments were conducted in duplicate repeats from at least three independent experiments.Invasion assay was performed using BD BioCoat Matrigel Invasion Chamber  as previously described , 38. BriP < 0.05), but not in the corresponding comparison involving the CA patients . These pathways included the phosphoinositide 3-kinase, protein kinase A, tumor necrosis factor receptor, and AR signaling pathways. As depicted in Supplemental Figure S2a, there were seven upregulated genes  and one down-regulated gene (CALR), leading to a statistically significant (P < 0.05) overrepresentation in the AR signaling pathway of AA PCa patients . In contrast, three upregulated genes  and two down-regulated genes (CALM1 and NFKB2) were identified in the AR signaling pathway of CA PCa patients, but this did not reach statistical significance for overrepresentation . It should be noted that the differentially expressed AR signaling genes in the cancer versus normal comparison of AA patients do not overlap with the corresponding set identified in the CA patients. qRT-PCR validation of ARA55, GNAO1, PRKCE, PRKD1, TBP, and CALR in AA PCa specimens and patient-matched normal tissues demonstrated a high degree of agreement with the microarray data . There is one caveat to these microarray and qRT-PCR findings. Namely, the magnitude of differential gene expression measured in cancer versus normal samples is likely compressed  due to the fact that the cancer biopsy specimens contain on average 50% noncancerous cells.Microarray analysis revealed that 1,169 genes were differentially expressed between AA PCa and patient-matched normal prostate. By comparison, a total of 865 differentially expressed genes were identified in the analysis of CA PCa versus patient-matched normal specimens. Principal Component Analysis (PCA) demonstrated clear separation and consistency of gene expression profiles in PCa specimens versus patient-matched normal tissues in both the AA and CA populations . The gene lists from these two comparisons  were imported into Ingenuity Pathway Analysis (IPA) to identify significant overrepresentation of differentially expressed genes residing in canonical pathways associated with PCa progression. IPA revealed 21 overrepresented canonical pathways in the cancer versus normal comparison of AA patients , which interacts with the AR in an androgen-dependent manner, enhancing AR transcriptional activity and ligand specificity [ARA55 expression is correlated with shorter recurrence-free survival and poorer overall survival in CRPCa [PRKCE) promotes conversion of androgen-dependent PCa cells to an androgen-independent phenotype [(o) subunit alpha (GNAO1) has been implicated in breast cancer [PRKD1 or called PKD1) is associated with PCa progression, whereby inhibition of PRKD1 reduces migratory and invasive properties of PCa cells [CALR) has been established in the PCa specimens, and overexpression of CALR suppresses tumor growth and metastasis [ Earlier biochemical and genetic studies have implicated either the AR and/or higher conversion of testosterone to DHT as culprits for PCa health disparities between the AA and CA populations –16. Our cificity . High ARin CRPCa . Other Ahenotype . An actit cancer . OverexpCa cells  , vascular endothelial growth factor (VEGF), and insulin-regulated growth factor-1 (IGF-1) signaling pathways , 382 out of 1,188 differentially expressed genes were identified as AR-target genes, with AR-binding sequences within 1-kb upstream of the start of transcription . The IPA results revealed that several cancer-associated pathways, including EGF, FGF, mTOR, integrin, JAK/STAT, and ERK/MAPK signaling pathways, were overrepresented in the AA PCa versus CA PCa comparison . Noteworthy, many of these pathways converge onto and regulate AR signaling. Taken together, these results suggest that differential expression of AR-target genes may contribute to the more aggressive cancer phenotype  reported in AA PCa.in vitro cell models for examining AR binding, gene regulation, and associated biological functions. VCaP is a bone metastasis derived from a 59-year-old CA PCa patient [STAT1, STAT2, ITGB5, PIK3CB, RHOA, RHOU, FGF13, EIF3B, MAPKAPK2, GIT1, and CSNK2A1). These 11 genes were originally shown to be differentially expressed in the AA cancer versus CA cancer comparison (from our microarray data) and were predicted as AR targets . We specifically selected these 11 genes for qRT-PCR validation based on their association with oncogenic pathways that were significantly overrepresented with differentially expressed genes . As an additional validation step, the original AA PCa and CA PCa biopsy RNA  were included for qRT-PCR analysis. qRT-PCR results indeed confirmed that all 11 genes were upregulated in the AA PCa specimens compared to CA PCa specimens  were used as  patient , represe patient , represe patient , represepecimens . In a copecimens . Hence, STAT1, RHOA, ITGB5, MAPKAPK2, CSNK2A1, and PIK3CB genes were shown to be basally upregulated in AA cell lines (MDA PCa 2b and E006AA) compared with the CA cell line VCaP  in E006AA cells compared to VCaP cells , a known AR-responsive gene [ACTB gene served as a negative control for these experiments  treated AA PCa cell lines (MDA PCa 2b and E006AA) incubated with 10 nM DHT for 48 hr compared to siNS-treated cells incubated with vehicle control  invasion potential of the AA cell lines by 20–40%  were seeded onto matrigel to examine their cell invasion potentials in response to DHT stimulation. After 48 hr incubation with 10 nM of DHT, a significant enhancement of invasion occurred in both MDA PCa 2b and E006AA cells . To vali cancers –55. In P cancers –60, but  control . Howeverβ-catenin, PI3 K/AKT, VEGF, and IGF-1 signaling pathways  in PCa specimens and cell lines, these earlier studies were not focused on PCa disparities and hence did not take into account the race/ethnicity of the patients from which the tissues were derived [The data resulting from our integrated approach of gene expression profiling, promoter analysis, pathway analysis, and functional validation has provided a novel genomic view of PCa disparities. This study highlights several potentially important genetic and molecular mechanisms underlying PCa disparities. We have identified a number of signaling pathways that have not been previously implicated in PCa disparities. Earlier microarray studies directly comparing AA and CA PCa specimens identified differentially expressed genes that were overrepresented in autoimmunity, inflammation, chromatin-mediated maintenance, and progesterone signaling pathways , 33. Oveways see , which w derived –65. Takeβ-catenin is an oncoprotein and a transcriptional coactivator of AR [β-catenin signaling has been implicated in advanced and metastatic PCa [α, and KGF) can also stimulate AR activation; the overexpression of growth factor proteins has been implicated in the transition to androgen-independent PCa [β-catenin, and IGF-1 signaling pathways may converge and contribute to the overall activation of AR signaling. Interestingly, these same pathways were observed in our study to be preferentially affected at the transcriptional level in comparisons of AA PCa versus CA PCa specimens. This strongly suggests that the AR signaling pathway may play a central role in the molecular regulation of PCa disparities. Thus, our genomic data offers a novel and unforeseen twist to the role of AR signaling in PCa disparities, beyond earlier genetic and biochemical evidence for increased levels of DHT and AR in the AA population [The regulation of the AR signaling pathway in PCa is complex. Previous studies suggest that PI3 K/AKT and AR signaling pathways play complementary roles in maintaining PCa proliferation in low-androgen environments , and thaor of AR –71, and atic PCa . Growth dent PCa . Furtherdent PCa . Taken apulation –14. We nSTAT1, RHOA, ITGB5, MAPKAPK2, CNSK2A1, and PIK3CB), exhibiting higher expression in AA PCa specimens and AA PCa cell lines compared to the corresponding CA counterpart tissues/cell line, also displayed higher AR binding to their gene promoters in the AA PCa cell line E006AA compared to the CA PCa cell line VCaP . These 6 genes were chosen because of their overrepresentation in oncogenic pathways for EGF, FGF, mTOR, and integrin signaling , and because they were not identified in the ChIP-chip study on CA PCa cell line LNCaP [RHOA, ITGB5, and PIK3CB, which corresponded to an increase in mRNA levels in the AA PCa cell lines MDA PCa and E006AA. These findings lend further support to the validity of our AR-target gene list.Given the general importance of the AR pathway in PCa progression, and the association of this pathway at the biochemical –16, genene LNCaP . Lastly,RHOA expression and its downstream effects on PCa progression remains elusive. Our study has conclusively demonstrated for the first time that (1) RHOA is upregulated in both PCa specimens and cell lines derived from AA patients compared to their corresponding CA counterparts, (2) AR can directly bind to the RHOA promoter, (3) AR binding to the RHOA promoter is higher in AA compared to CA PCa cell lines, (4) DHT can further stimulate AR binding to the RHOA promoter in AA PCa cell lines, and (5) DHT can stimulate invasion of AA PCa cells in a RHOA-dependent manner.As a small GTPase, RhoA plays an important role in promoting cell invasion and migration in PCa cells –60. A haα2, α6, β1, and β3, are overexpressed in PCa [ITGB5 (encoding integrin subunit β5) is overexpressed in prostate intraepithelial neoplasia (PIN) tissue, suggesting its potential role in the early-stage prostate tumorigenesis [ITGB5 expression has been linked to PKA activation in PCa [ITGB5 is a direct AR-target gene, and AR-stimulated ITGB5 mRNA up-regulation is a prerequisite for invasion by AA PCa cells.Deregulation of integrin proteins has been associated with PCa progression. Previous studies have revealed that a number of integrin subunits, including d in PCa –82. It higenesis . Moreoveigenesis , and up-n in PCa . ComplemPIK3CB encodes PI3Kβ (p110β), which is a class IA isoform of PI3 K. Accumulating evidence has suggested that PI3Kβ may play a critical role in PCa progression. Previous studies have revealed that PI3Kβ is overexpressed in PCa clinical specimens [β is required for AR-chromatin interaction and AR-mediated gene expression [β in PCa disparities has not to this point been investigated. Our results have demonstrated that AR directly targets the PIK3CB gene in an androgen-dependent manner in AA PCa cells. More importantly, AR-stimulated PIK3CB expression can be linked to an increase in AA PCa cell invasion, which may explain in part PCa aggressiveness in AA patients. Of interest, KIN-193 is a drug targeting the PIK3CB protein and under investigation for the treatment of breast and prostate cancers [pecimens  and is ipecimens –86. Morepression . However cancers .STAT1) represents one such example. Previous studies have demonstrated that STAT1 is overexpressed in several human cancers [STAT1 may act as a cancer driver gene; thus understanding its role in PCa health disparities would be warranted.Our list of 382 predicted AR-target genes could serve as a resource for future hypothesis-driven studies into the molecular underpinnings of PCa health disparities. Signal transducer and activator of transcription 1  and other AR-target genes residing in signaling pathways  may extend the range of potential therapeutic options for treatment of advanced PCa in AA men.An analogous principle might be applied to the treatment of population-specific PCa disease. Multiple pathways (including the AR pathway) have an overrepresentation of differential expressed genes in comparisons of AA PCa and CA PCa specimens, and many of these overrepresented pathways converge on the AR pathway. These findings strongly suggest that AR signaling and the AR-target genes may serve as promising drug targets for the treatment of advanced PCa in the AA population. In addition, the newly discovered AR-mediated invasion genes  of prostate tissue specimens based on mRNA expression, Supplemental Figure S2: Over-representation of differentially expressed genes in the AR signaling pathway of AA PCa specimens, Supplemental Figure S3: Venn diagram depicting differentially expressed genes derived from pairwise comparisons of AA cancer versus AA matched normal, CA cancer versus CA matched normal, and AA cancer versus CA cancer, Supplemental Figure S4: Canonical signaling pathways with a significant over-representation of differentially expressed AR-target genes, Supplemental Figure S5: Western blot analysis of AR protein levels in CA PCa cell line VCaP and AA PCa cell lines E006AA and MDA PCa 2b, Supplemental Figure S6: DHT-stimulated gene expression after 24-hr and 48-hr serum starvation, Supplemental Figure S7: Effect of DHT treatment on AR mRNA expression in AA PCa cell lines, Supplemental Figure S8: Knockdown efficiencies of siRNAs targeting RHOA, ITGB5 and PIK3CB in PCa cells.Click here for additional data file.


P < 0.0001). AR expression was associated with ER level, and it increased with age in ER-positive cases. The cut-off value was determined to be 75% , and AR expression was considered to be high in 155 (62%) cases. High AR expression significantly correlated with lower nuclear grade (P < 0.0001), ER and progesterone receptor (PR) positivity (P < 0.0001 and P = 0.0022), HER2 negativity (P = 0.0113), lower Ki67 index (P < 0.0001) and a longer disease-free survival (DFS) and distant metastasis-free survival (DMFS) (P = 0.0003 and 0.0107). This association between a high AR expression and a good DFS and DMFS was significant for ER-positive tumors (P < 0.0001 and P = 0.0018); however, no association existed between AR expression and prognosis for ER-negative tumors. In patients ≤51 years old, a high AR expression level significantly correlated with a better prognosis, but this was not significant in patients who were 50 or younger. Multivariate Cox hazard analyses revealed AR expression to be independently associated with a good prognosis in overall patients  and in the ER-positive cohort . AR expression is associated with a less aggressive phenotype and a good prognosis in patients with ER-positive breast cancer. This is considered to be a specific phenomenon for postmenopausal breast cancer patients.We evaluated the expression of the androgen receptor (AR) to determine its significance in breast cancer. AR expression levels were analyzed in 250 invasive breast cancers by immunohistochemistry and any association with the clinicopathological features was evaluated. AR expression was higher in estrogen receptor (ER)-positive cases than in ER-negative cases ( The androgen receptor (AR) is a member of the steroid receptor subfamily. There is emerging evidence that the androgen signaling pathway may also play a critical role in normal and malignant breast tissue . The AR Thus, the expression of AR is considered to be a good prognostic marker for ERα-positive breast cancer; however, there were some problems in previous studies. For example, the methods used to determine the positivity of AR expression were different among the studies –11. MoreThe role of androgens in the development and progression of breast cancer has not yet been fully elucidated. The mechanism underlying estrogen production dramatically changes before and after menopause. In postmenopausal females, adipose tissue is the primary source of endogenous estrogen production, rather than the ovary. After menopause, androgens  become an important source of estrogens . The ratFour hundred sixty-six primary breast cancer patients underwent surgery in the Department of Surgery and Science, Kyushu University Hospital, between 1997 and 2007. Among these patients, eight had stage IV disease, 29 cases were non-invasive ductal carcinoma and 34 cases were a special type of invasive cancer. Among the remaining invasive ductal carcinoma cases, a total of 250 cases for which archival tissue samples were available for an immunohistochemical analysis were included in this study. Written informed consent was obtained from all patients before collecting tissue samples. AJCC/UICC TNM Classification and Stage groupings were used.2O2 in methanol to block the endogenous peroxidase activity. Nonspecific antibody binding was blocked by incubating the sections with normal goat serum (Dako) for 10 min. The slides were then incubated with mouse monoclonal AR antibodies  [The expression of the AR was analyzed by IHC. Formalin-fixed, paraffin-embedded tissue specimens were used, and the sections were deparaffinized with xylene and rehydrated. AR expression was analyzed as follows: The sections were first treated with the target retrieval solution pH 9.0)  in a microwave at 99°C for 30 min for antigen retrieval. The slides were then treated for 30 min with 3% H.0  , 14 overThe ER, PR, and HER2 status was evaluated as described previously . The ER 2 tests. Survival curves were plotted using the Kaplan–Meier method and the log-rank test was used to determine the associations between individual variables and survival. The survival data were evaluated using a multivariate Cox proportional hazards model. Differences were considered to be significant at P < 0.05.All molecular and IHC analyses were performed by investigators blinded to the clinical data. The statistical analyses were done using the JMP software package, version 9.0.2 . The associations between AR expression and clinicopathological characteristics were assessed using χP < 0.0001; Fig. P < 0.0001; Fig. AR expression levels were analyzed by IHC. AR immunoreactivity was observed in the nuclei of tumor cells. Figures P = 0.0007; Fig. P = 0.0177; Fig. In addition, we found an intriguing phenomenon wherein AR expression was different by age only in ER-positive cases. The mean age at natural menopause in Japanese females is 50 years . TherefoP < 0.0001), ER and PR positivity (P < 0.0001 and P = 0.0022), HER2 negativity (P = 0.0113), and lower Ki67 index (P < 0.0001). Most of the tumors with high AR expression were hormone receptor-positive and HER2-negative cases . A high level of AR expression was associated with a significantly longer disease-free survival (DFS) and distant metastasis-free survival (DMFS) than a low AR expression (P = 0.0052) and the ER-positive cohort of patients , HER2 negativity (P = 0.0445), and a lower Ki67 index (P = 0.0015) , the PR positivity was 25%, 44.6%, and 61.9% (P = 0.0039), 83.3%, 45.2%, and 21.9% of tumors were nuclear grade 3 (P < 0.0001), and the Ki67 index was 43.0%, 20.9%, and 14.2%, respectively (P < 0.0001). There were no significant differences in tumor size and lymph node metastasis among these groups. These results suggest that the higher expression of the AR is associated with low-grade tumors. Therefore, an AR cut-off of 75% is considered to be suitable for our study. It is important to establish standard methods for detecting and evaluating the positivity of AR expression in the future.Most studies have come to the same conclusion that AR expression is related to a favorable prognosis in ER-positive breast cancer. The problem is that there has been high variability in the patient population, assay methods, and the analysis of the results of these previous studies. In terms of the methods used for IHC, large studies analyzed AR expression by IHC using TMA , 10, butThere are emerging data regarding AR expression in breast cancers and the efficacy of hormone therapy, tamoxifen, and AIs. A preclinical study using an ER-positive breast cancer cell line showed that overexpression of the AR may cause resistance to tamoxifen . If the In conclusion, AR expression is associated with a less aggressive phenotype and a good prognosis in patients with ERα-positive breast cancer. This is considered to be a specific phenomenon for postmenopausal breast cancer patients. The evaluation of AR expression may therefore be useful to provide more adequate adjuvant therapy for postmenopausal females with ER-positive breast cancer.