The second-generation antiandrogen enzalutamide was recently approved for patients with castration-resistant prostate cancer. Despite its success, the duration of response is often limited. For previous antiandrogens, one mechanism of resistance is mutation of the androgen receptor (AR). To prospectively identify AR mutations that might confer resistance to enzalutamide, we performed a reporter-based mutagenesis screen and identified a novel mutation, F876L, which converted enzalutamide into an AR agonist. Ectopic expression of AR F876L rescued the growth inhibition of enzalutamide treatment. Molecular dynamics simulations performed on antiandrogen–AR complexes suggested a mechanism by which the F876L substitution alleviates antagonism through repositioning of the coactivator recruiting helix 12. This model then provided the rationale for a focused chemical screen which, based on existing antiandrogen scaffolds, identified three novel compounds that effectively antagonized AR F876L (and AR WT) to suppress the growth of prostate cancer cells resistant to enzalutamide.DOI:http://dx.doi.org/10.7554/eLife.00499.001 Prostate cancer is the most commonly diagnosed cancer in men, and the second most lethal. All stages of prostate cancer depend upon male sex hormones, also known as androgens, to grow because these hormones bind and activate androgen receptors. A class of drugs termed ‘antiandrogens’ can effectively treat prostate cancer because they bind to androgen receptors without activating them, thereby preventing androgens from binding. However, the efficacy of even highly potent antiandrogen drugs, such as enzalutamide is short-lived in many patients, and understanding the biological mechanisms that cause drug resistance is one of the major objectives in translational prostate cancer research.Resistance can arise through mutations of the androgen receptor that result in the receptor being activated, rather than inhibited, by antiandrogen drugs. However, no such mutations are known yet for enzalutamide, and researchers are keen to understand whether they exist and, if so, to generate new drugs for prostate cancer that overcome them. To identify mutations that may lead to resistance, Balbas et al. designed a new screening method in human prostate cancer cells and showed that androgen receptors with a specific mutation  can be activated by enzalutamide. More comprehensive biological studies showed that prostate cancer cells harboring the mutation continued to grow when treated with the drug. Balbas et al. also showed that this mutation can arise spontaneously in human prostate cancer cells treated long term with enzalutamide.Balbas et al. reasoned that the mutation likely altered the way enzalutamide binds to the androgen receptor, and used computer-guided structural modeling of the complex formed by the receptor and the drug to investigate how this might occur. These studies indicated that the region of the androgen receptor containing the F876L mutation comes into direct contact with the drug, and provided a structural explanation for the loss of inhibition. Because these studies showed how enzalutamide might bind to the androgen receptor, they also suggested ways in which enzalutamide could be chemically modified to restore its inhibitory activity against the mutant receptor.Balbas et al. then designed and synthesized a set of novel compounds, which the modeling data suggested could act as inhibitors of the mutant receptor. Several of these compounds inhibited the activity of both mutant and wild-type forms of the androgen receptor, and suppressed the growth of both enzalutamide-resistant and nonresistant prostate cancer cells.The work of Balbas et al. outlines a general screening strategy for the discovery of clinically relevant mutations in cancer genes, and shows how in silico technologies can accelerate drug discovery in the absence of a crystal structure of a protein–drug complex. It also emphasizes how understanding the manner in which a drug binds its target can stimulate rational design of improved drug candidates.DOI:http://dx.doi.org/10.7554/eLife.00499.002 The recent FDA approval of enzalutamide (formerly MDV3100) confirms the continued critical role AR signaling plays in castration-resistant prostate cancer . In spitMutagenesis screens to identify kinase inhibitor-resistant alleles of kinase targets such as BCR-ABL have relied upon cytokine-dependent test cells that become cytokine independent after introduction of the target kinase. Cells expressing drug-resistant kinase alleles selectively expand in the presence of drug, allowing rapid identification of mutations that confer drug resistance. There is no comparable strategy available for antiandrogens because introduction of AR does not confer a comparable growth advantage in AR-negative cells. We instead chose to identify and select cell populations with persistent AR transcriptional activity in the presence of enzalutamide. We reasoned that targeting the biological process of interest , rather than a distal symptom of resistance to drug  might identify resistant clones more quickly. To this end, an AR-regulated EGFP reporter, with a probasin promoter and PSA enhancer elements driving EGFP expression (Pb.PSE.EGFP) , was useProof-of-concept studies were conducted with LNCaP cells cotransduced with Pb.PSE.EGFP and AR W741C, a well-characterized mutation that converts the AR antagonist bicalutamide into an agonist . With stWe next conducted the enzalutamide resistance screen with the Pb.PSE.EGFP reporter and a randomly mutagenized AR library. After five iterations of enzalutamide exposure and FACS sorting, we identified a population of cells with durable EGFP expression . MoreoveTo identify AR mutations in these cells, we amplified the exogenously expressed AR cDNA, and Sanger sequenced the PCR product. In two of three replicates, a single dominant point mutation emerged, resulting in the amino acid substitution F876L . Importa18F]fluoro-5α-DHT (18F-FDHT), to measure relative AR binding affinity , conferred agonism to both enzalutamide and ARN-509 .Notably, we observed that bicalutamide did not induce AR F876L transcriptional activity in our luciferase reporter assay, either at low  or at hiThat F876L so dramatically impacted the pharmacology of enzalutamide and ARN-509 suggested that a clear structural change in the drug–receptor complex might be occurring. This consideration prompted us to investigate the structural basis of this antagonism-to-agonism conversion. Because a crystal structure depicting AR bound to an antagonist does not yet exist, we performed structural modeling using ligand docking and molecular dynamics (MD) simulations . In desiThe docked enzalutamide and ARN-509 molecules demonstrated strikingly different interaction patterns with AR compared to bicalutamide . NotablyAnother notable insight from these simulations was that the substituent on position 4 of the B-ring -DR103. Remarkably, a compound with the gem-dimethyl group on position 4 (rather than 3/5) of the D-ring (DR104) was a modest agonist of AR F876L . Moreover, a compound with gem-dimethyl groups at the 3 and 5 positions of the D-ring (DR105) inhibited AR F876L (and AR WT) , furtherIn line with this pharmacology, (±)-DR103 inhibited the growth of prostate cancer cell lines expressing both the WT and mutant receptor . (±)-DR1S)-DR103 suggested that an agonist-like conformation of H12 cannot be achieved for either WT or mutant AR (S)-DR103 was capable of directly displacing the N-terminal residues of H12. A magnified view of the H12 pocket (S)-DR103 occupies a region in the H12 pocket that neither enzalutamide nor ARN-509 can access, thus imposing antagonist-like dislocation of helix 12. Whereas in the H11 pocket (S)-DR103 did not show a significant difference in binding with residue L876 compared to either enzalutamide or ARN-509, which suggests that the restored antagonism was not achieved by simply regaining interactions at the mutation site in AR. Similar MD simulations for the complex of AR F876L and (R)-DR103 showed a slightly less pronounced H12 dislocation -DR103 reinforced our pharmacological model for AR antagonism by bisaryl-thiohydantoins. Unlike the results for enzalutamide and ARN-509, MD simulations using -DR1location , suggestAs is evident from previous work with ABL kinase inhibitors for chronic myeloid leukemia and antivirals for HIV and hepatitis , understThat prostate cancer can spontaneously acquire gain-of-function mutations in AR (rather than acquiring mutations that simply preclude inhibitor binding) underscores the special challenge in pharmacologically overcoming this mechanism of resistance. By borrowing insight from studies of the progesterone receptor, showing that a single amino acid can determine sensitivity to RU486, and structural analyses of the estrogen receptor , our attBecause the discovery of this mutation and its companion pharmacology provided the basis for our structural model, it is difficult to envision how the importance of the D-ring might have otherwise emerged from previous (and ongoing) chemical screening efforts. Among the ∼100 bisaryl-thiohydantoins published to date, several compounds bearing structurally similar moieties to our bioactive series were essentially indistinguishable from enzalutamide, ARN-509, or other leading agents in conventional cell-based assays. Our own focused chemical screen further speaks to the unusually complicated pharmacobiology of AR F876L, as subtle changes in the position of geminal dimethyl moieties on DR103-5 radically impacted the respective bioactivity of the drugs.Our success predicting the pharmacology of candidate inhibitors with MD simulations argues for a novel workflow by which in silico screening could guide future antiandrogen drug discovery . The data indicating that ∼50% of patients fail to respond to enzalutamide has somewhat overshadowed the importance of the discovery of the bisaryl-thiohydantoin chemotype for AR, and the ongoing enthusiasm for developing better drugs based on this motif is most visibly reflected by the clinical trial with ARN-509. In this regard, our structural model provides a powerful tool to further refine the chemotype into drug candidates with improved properties.Collectively, these findings demonstrate the importance of coordinated mutagenesis, structural modeling, and medicinal chemistry studies in designing drugs against an important cancer target for which appropriate drug affinity and binding conformation are mutually indispensible for competent inhibition. We are optimistic that discovery of the AR F876L mutation will facilitate solution of the enzalutamide/AR complex by X-ray crystallography. As for the potential clinical impact of a priori discovery of drug–resistance mutations to novel cancer drugs, our previous experience with the ABL kinase inhibitor dasatinib in chronic myeloid leukemia serves as an example. Within 2 years of reporting dasatinib-resistant mutations in BCR-ABL in a preclinical model, analogous mutations were recovered from dasatinib-resistant chronic myeloid leukemia patients . We hopeFetal bovine serum (FBS) and charcoal-stripped dextran-treated fetal bovine serum (CSS) were purchased from Omega Scientific . Bicalutamide and hydroxyflutamide , DHT , and R1881  were commercially obtained; all other ligands were synthesized at MSKCC. Serial dilutions of all drugs were made using DMSO. Antibodies used for immunoblot assays were β-actin  PARP , FKBP5 , β-tubulin (D-10), and androgen receptor (N-20) . Protein lysates were prepared in M-PER protein extraction reagent . The chromatin immunoprecipitation assay was conducted using a kit . Nontarget and human AR siRNA pools were from the ON-TARGETplus collection . LNCaP/AR cells were previously described , and CWRFor the analogue syntheses, all chemicals were acquired from Sigma-Aldrich at highest purity available and were used without further purification. Chromatography was done using Merck grade silica gel 60, and reactions were monitored by LC-MS . Proton NMR experiments were executed on Bruker Advance DRX running at 500 MHz, and fluorine NMR was run on the same machine but at 235 MHz. Chemical shifts are reported in parts per million relative to tetramethylsilane.The human AR cDNA plasmid, pWZL-AR, was provided by William Hahn . All mutant AR constructs were generated in pWZL-AR with the QuikChange II XL site-directed mutagenesis kit  and primers designed using Agilent's online QuikChange Primer Design tool. Stable cell lines were generated by pantropic retroviral infection  and selected with blasticidin .LNCaP cells were infected with the lentiviral AR-regulated EGFP reporter construct, Pb.PSE.EGFP , provide4 cell events were collected and analysis was done using FlowJo software. FACS-sorting of LNCaP-Pb.PSE.EGFP cells was performed on a BD FACSVantage cell sorter. Dead cells were counterstained with DAPI (Invitrogen). EGFP expression was detected using the 488-nm laser and 530/30 bandpass filter, and DAPI-labeled dead cells were detected using the 355-nm laser and 450/50 bandpass filter.LNCaP-Pb.PSE.EGFP cells for flow cytometric analysis were treated with antiandrogens (1 or 10 µM) for 4–6 days, changing media and drug every 2–3 days. Cells were collected using Accumax dissociation solution , and dead cells were counterstained using TO-PRO3-Iodide . EGFP expression was measured using the BD-FACSCalibur flow cytometer using the 488-nm laser and 530/30 bandpass filter to detect EGFP expression, and the 633-nm laser and 661/16 bandpass filter to detect TO-PRO3-Iodide labeled dead cells. For each sample, 2–5 × 10We introduced four additional synonymous mutations into our pWZL-AR W741C construct to aid in distinguishing wild-type (WT) AR and AR W741C, using the QuikChange Multi Site-Directed Mutagenesis Kit (Agilent). We then designed and optimized quantitative PCR primers across these mutation sites, so that they specifically amplified AR W741C. We overexpressed AR WT or AR W741C in our LNCaP-Pb.PSE.EGFP reporter cells, mixed different ratios of cells expressing either WT or W471C, treated these cells with 1 µM bicalutamide for 4 days, and FACS-sorted the cells that maintained/induced EGFP expression. Gates for EGFP positivity were set using WT or W741C expressing cells treated with bicalutamide. Sorted cells were expanded in culture (without drug) until they reached approximately 60 million cells, we then isolated gDNA and froze down a small fraction, and the brief bicalutamide treatment and sorting was repeated on the remainder.Escherichia coli strain XL-1 Red (Agilent) with the pWZL-AR plasmid and plated them on ampicillin-agar bacterial plates. After a 36-hr incubation, colonies were collected by scraping, and plasmid DNA was purified using a plasmid MAXI kit . This mutagenized AR plasmid stock was used to make pantropic retrovirus (Clontech) and infect LNCaP-Pb.PSE.EGFP cells at a MOI < 1. Cells were selected for stable expression of our mutant pWZL-AR library using the blasticidin resistance cassette. Mutant library cells were cultured in 1 µM enzalutamide for 4–6 days, collected with Accumax and resuspended in Accumax containing 0.5% BSA and 10 mM HEPES. Cells that remained EGFP positive in the presence of enzalutamide were then FACS-sorted. Gates for EGFP positivity were set using LNCaP-Pb.PSE.EGFP cells transduced with the wild-type AR cDNA, treated with vehicle or 1 µM enzalutamide. Sorted cells were expanded in culture (without drug) until they reached approximately 60 million cells, we then isolated gDNA and froze down a small fraction, and the brief enzalutamide treatment and sorting was repeated on the remainder. We performed the screen in triplicate, with five rounds of FACS and expansion for each replicate.Our randomly mutagenized AR cDNA library was generated as follows: we transformed the DNA-repair-deficient Exons 2 through 8 of the exogenously expressed AR cDNA were amplified from genomic DNA isolated from cells after each sort, by high-fidelity PCR  on a Mastercycler (Eppendorf). The PCR product was subjected to bidirectional Sanger sequencing, using previously published primers . Alignme-ΔΔCt method with normalization to GAPDH as described (Applied Biosystems). All primers were used at a final concentration of 500 nM and are listed 5′ to 3′: GAPDH-Forward: GAAGGTGAAGGTCGGAGTC; GAPDH-Reverse: GAAGATGGTGATGGGATTTC; PSA-Forward: GGTGACCAAGTTCATGCTGTG; PSA-Reverse: GTGTCCTTGATCCACTTCCG; Tmprss2-Forward: CACTGTGCATCACCTTGACC; Tmprss2-Reverse: ACACGCCATCACACCAGTTA; Fkbp5-Forward: TCCCTCGAATGCAACTCTCT; Fkbp5-Reverse: GCCACATCTCTGCAGTCAAA; SGK1-Forward: GCAGAAGGACAGGACAAAGC; SGK1-Reverse: CAGGCTCTTCGGTAAACTCG.Total RNA was isolated using the QiaShredder kit (Qiagen) for cell lysis and the RNeasy kit (Qiagen) for RNA purification. We used the High Capacity cDNA Reverse Transcription Kit  to synthesize cDNA according to the manufacturer's protocol. Quantitative PCR was done in the Realplex MasterCycler (Eppendorf) using the Power SYBR Green PCR Mastermix (Applied Biosystems). Quantitative PCR for each sample was run in triplicate and each reaction contained 1 μl of cDNA in a total volume of 20 μl. PCR quantification was done using the 27 cells/condition) were grown in phenol red free RPMI media supplemented with 10% CSS for 4 days, then treated with DMSO, 10 µM antiandrogens, or 1 nM DHT for 4 hr. The cells were cross-linked using 1% paraformaldehyde  for 15 min, glycine was then added, and samples centrifuged  to stop further cross-linking. ChIP was performed according to manufacturer's protocols using a ChIP assay kit (Upstate) with an antibody for AR . Immunoprecipitated DNA was amplified by quantitative real-time PCR (ABI Power SYBR Green PCR mix). All primers were used at 500 nM and are listed 5′ to 3′: PSA enhancer-Forward: ATGTTCACATTAGTACACCTTGCC; PSA enhancer-Reverse: TCTCAGATCCAGGCTTGCTTACTGTC; FKBP5 enhancer-Forward: CCCCCTATTTTAATCGGAGTAC; FKBP5 enhancer-Reverse: TTTTGAAGAGCACAGAACACCT.LNCaP cells (106 cells/well of six-well plate) were transfected with 2 μg AR-EYFP plasmid  or AR.F876L-EYFP plasmid (QuikChange II XL site-directed mutagenesis kit) using FUGENE HD . 6 hr after transfection, media was removed and replaced with phenol red-free RPMI media supplemented with 10% CSS. The next day cells were split and plated onto poly-lysine-coated Nunc Labtek chamber slides in RPMI + 10% CSS containing DMSO, 1 µM antiandrogens, or 1 nM DHT. 24 hr later, the cells were counterstained with NucBlue Live Cell Stain Hoechst 33342  fixed with 4% paraformaldehyde, and mounted with a coverslip. Images were taken on a Leica TCS SP5-II Upright confocal microscope .LNCaP cells (106 cells/10 cm plate) were cotransfected with 50 ng of SV40 Renilla Luciferase, 5 μg of ARE(4X)-Luciferase, and 10 μg of one pWZL-AR expression construct using Lipofectamine 2000 (Invitrogen). Transfection media was removed 4–6 hr later and replaced with phenol red-free DMEM containing 10% CSS. The following day each plate was split into 48-well plates, in 10% CSS media, containing the indicated drugs in triplicate. Luciferase activity was assayed 24–48 hr later using Dual-Luciferase Reporter Assay System .CV1 cells , in triplicate. The solutions were shaken on an orbital shaker at ambient temperature for 1 hr, then isolated, and washed with ice-cold tris-buffered saline using a Brandel cell harvester . Samples were counted using a scintillation counter, and the specific uptake of 18F-FDHT was determined. These data were plotted against the concentration of the cold competitor to give sigmoidal displacement curves, and IC50 values were determined using a one-site model and a least squares curve fitting routine  with the R2 of the curve fit being >0.99.The binding affinity of enzalutamide to AR WT and AR F876L, relative to dihydro-testosterone (DHT), was determined using a competition assay in which increasing concentrations of cold competitor are added to cells preincubated with 6 LNCaP/AR cells ectopically expressing AR WT or AR F876L  into the flanks of castrated male SCID mice. Daily gavage treatment  was initiated on the day of injection. Once tumors were palpable, tumor size was measured weekly in three dimensions (l × w × d) with calipers. All animal experiments were performed in compliance with the guidelines of the Research Animal Resource Center of the Memorial Sloan-Kettering Cancer Center.In vivo xenograft experiments were done by subcutaneous injection of 2 × 106 LNCaP/AR cells  was isolated  from resistant CWR22Pc cell lines or LNCaP/AR xenograft tumors. With 20 ng of gDNA as template, exon 8 of AR was PCR amplified with Kapa HiFi Ready Mix . RNA was extracted from LNCaP/AR xenograft tumors, reverse transcribed , and exons 2 through 8 of AR was PCR amplified using 200 ng cDNA as template .PCR reactions were cleaned up with AMPure XP (Beckman Coulter Genomics), and pooled reaction yields were quantified using the Qubit fluorometer (Invitrogen). Library preparation was done using Nextera DNA Sample Preparation kit (Illumina) and run on the Illumina MiSeq sequencer using the 2 × 250 paired-end cycle protocol.https://github.com/najoshi/sickle) using a quality threshold of 32. The reads were then mapped to the human genome build hg19 with TopHat 2 (http://picard.sourceforge.net). Variant detection was performed using VarScan 2 , brief drying over Na2SO4, and concentration of the filtrate under reduced pressure and the residue was chromatographed on a short path silica gel column using the gradient hexane/ethyl acetate 2/1 to 1/1.5 (vol/vol) to yield desired product in more than 85% yield.To a mixture of 4-amino-2-fluoro-N-methylbenzamide (0.3 mmol) and the desired ketone  in glacial acetic acid (2 ml) was added NaCN , and the mixture was heated to 80°C overnight. The solvent was then removed under reduced pressure, and the residue was dissolved in water (20 ml) and then pH was brought to neutrality with aqueous saturated NaHCO4, concentrated, and the residue chromatographed on silica gel using the gradient system hexane/ethyl acetate 2/1 to 1.5/1 (vol/vol) to yield the desired thiohydantoin in up to 90%.Thiophosgene  is added dropwise to a solution of 5-amino-2-cyano-3-trifluoromethylpyridine or 4-amino-2-(trifluoromethyl)benzonitrile (60 μmol) and the given Strecker products above N-methyl-4--2-fluorobenzamides (60 μmol) in dry DMA (0.6 ml) under Argon at 0°C. After 5 min, the solution is stirred overnight at 60°C. At room temperature, this mixture was then diluted with MeOH (1 ml) and aqueous 2.0 N HCl (0.5 ml) and then the reaction was brought to reflux for 2 hr. After cooling to ambient temperature, the reaction mixture was poured into ice water (10 ml) and extracted with EtOAc (3 × 20 ml). The organic layer was briefly dried over MgSOThis compound was isolated as an off-white foam.1HNMR (CDCl3): δ: 8.28 , 7.79 , 7.96 , 7.84 , 7.27 , 7.17 , 6.71 , 3.07 , 2.36 , 2.16 , 1.91 , 1.56 .19FNMR (CDCl3) δ: −61.98, −110.64.23H18F4N4O2S [M+H]+ found: 491.22; calculated: 491.12LRMS for CThe compound was obtained as an off-white foam.1HNMR (CDCl3): δ: 8.27 , 7.98 , 7.93 , 7.82 , 7.19 , 7.08 , 6.70 , 3.08 , 2.07 , 1.70 .19FNMR (CDCl3) δ: −61.97, −110.92.24H20F4N4O2S [M+H]+ found: 505.30; calculated: 505.13.LRMS for CThis compound was isolated as off-white solid.1HNMR (CDCl3): δ: 8.28 , 7.98 , 7.93 , 7.82 , 7.24 , 7.14 , 6.72 , 3.08 , 2.28 , 2.17 , 1.81 , 1.60 , 1.44 , 1.32 .19FNMR ( CDCl3) δ: -61.98, −110.82.25H22F4N4O2S [M+H]+ found: 519.38; calculated: 519.15.LRMS for CRacemic DR103 was synthesized in 70% overall yield as an off-white powder.1HNMR (CDCl3): δ: 8.27 , 7.98 , 7.92 , 7.80 , 7.17 , 7.07 , 6.70 , 3.08 , 2.27 , 2.17 , 1.93 , 1.67 , 1.62 , 1.57 , 1.52 , 1.20 , 0.95 .19FNMR (CDCl3) δ: -61.98, −110.89.26H24F4N4O2S [M+H]+ found: 533.33; calculated: 533.17.LRMS for CIt was isolated as an off-white powder.1HNMR (CDCl3): δ: 8.30 , 7.98 , 7.93 , 7.82 , 7.22 , 7.11 , 6.72 , 3.08 , 2.04 , 1.93 , 1.37 , 0.99 , 0.73 .19FNMR (CDCl3) δ: −61.98, −110.75.26H24F4N4O2S [M+H]+ found: 533.33; calculated: 533.17.LRMS for CThis compound was isolated as a beige foam.1HNMR (CDCl3): δ: 8.21 , 7.90 , 7.85 , 7.73 , 7.12 , 7.02 , 6.64 , 3.01 , 1.94 , 1.62 , 1.50 , 1.17 , 0.83 .19FNMR ( CDCl3) δ: -61.98, −110.89.26H24F4N4O2S [M+H]+ found: 561.29; calculated: 561.20.LRMS for CThis compound was isolated as an off-white foam.1HNMR (CDCl3): δ: 9.06 , 8.33 , 8.29 , 7.18 , 7.07 , 6.71 , 3.08 , 2.30 , 2.18 , 1.94 , 1.72 , 1.63 , 1.57 , 1.52 , 1.20 , 0.94 .19FNMR (CDCl3) δ: -61.87, −110.71.25H23F4N5O2S [M+H]+ found: 534.31; calculated: 534.16.LRMS for CThis compound was isolated as a white to off-white powder.1HNMR (CDCl3): δ: 8.26 , 8.02 , 7.91 , 7.79 , 7.45 , 6.71 , 4.71 , 3.06 .19FNMR (CDCl3) δ: -62.05, −110.31.19H12F4N4O2S [M+H]+ found: 437.19; calculated: 437.07.LRMS for CNo structures have been solved experimentally for enzalutamide or ARN-509 in complex with AR (agonist or antagonist conformation). Therefore, three-dimensional structures of antiandrogens were first built using the computer program Gaussview   and then2, each AR–antiandrogen complex structure was energetically minimized with one round of 100-step steepest decent followed by two rounds of 100-step Adopted-Basis Newton–Raphson (ABNR) energy minimization. Harmonic constraints were reset at the beginning of each round of minimization. No nonbonded cutoff was used. Solvent effects were implicitly modeled in this stage with a distance-dependent dielectric constant.The initial AR–antiandrogen complex structures were then modeled with the molecular modeling program CHARMM , 2009. SThe all-atom MD simulations were performed with explicit solvent atoms using the program CHARMM (version 36a1). Each initial AR–antiandrogen model was first centered and overlaid with a rhombic dodecahedron-shaped water box (edge length being 88 Å) of approximately 47,000 equilibrated water molecules. Any water molecule whose oxygen atom was within 2.8 Å away from any non-hydrogen atom of AR or antiandrogen was removed. Proper amount of sodium and chloride ions were automatically added to achieve overall charge neutrality and physiological level of ion concentration (0.145 M). Their positions were optimized with 10 independent trajectories of randomly replacing water molecules and performing 50 steps of steepest decent and 125 steps of ABNR energy minimization.The molecular system including AR, antiandrogen, water, and ions was heated to 300 K and equilibrated with two rounds of 0.1-ns MD simulations under successively weaker harmonic constraints on AR or antiandrogen atoms. After the MD equilibration, three sets of random velocities were assigned to initiate three independent 10-ns MD productions. The MD equilibration and production were performed using the crystal form of rhombic dodecahedron (RHDO) and the canonical ensemble (NVT). A nonbonded cutoff of 14 Å, periodic boundary conditions in conjunction with Ewald summation method, the leapfrog Verlet integrator, and the Hoover thermostat for pressure and temperature were used. The timestep was set at 2 fs. Parallel jobs for MD simulations were run on a computer cluster of Intel Xeon X5650 series (2.66 GHz and 4 GB memory per CPU).Structural models were visualized in a molecular graphics program, UCSF Chimera . The def review process). Similarly, the author response typically shows only responses to the major concerns raised by the reviewers.eLife posts the editorial decision letter and author response on a selection of the published articles . An edited version of the letter sent to the authors after peer review is shown, indicating the substantive concerns or comments; minor concerns are not usually shown. Reviewers have the opportunity to discuss the decision before the letter is sent  From a biological standpoint, the only significant experiment considered to be missing was a test of one of the novel antagonists for suppression of tumorigenicity of the F867L prostate cancer cell lines in the xenograft model. This experiment would complete the thought that the rational drug design process ends with the predicted anti-tumor effect in vivo. After deliberation, this experiment was considered not necessary for publication given the overall depth of the studies, but it would further strengthen the manuscript if available.2) All three reviewers thought that despite the nice rendering of AR-ligand structures after MD simulations, it is not clear exactly in what way the F876L change results in altered interaction with the ENZ and ARN ligands, and where on the ligand the contact is occurring. A figure illustrating an enlargement of this region would add to the paper and perhaps enable a cogent discussion of the specific contacts the enables antagonism to is restored by altering the ligand structure.3) The paper would be strengthened by evidence that the F876L mutation does indeed occur in PCa patients undergoing ENZ therapy, and, although it may be too soon for ENZ-resistant patients to have emerged, it would be worth discussing this as a future direction, because these patients would obviously be candidates for treatment with the second-generation drug reported in this paper.4) In Figure 3, the distance of residues 876 to the bound enzalutamide need to be carefully measured and illustrated in both WT and mutated receptors. The implication of this distance needs to be discussed within the contact of receptor-ligand interactions.5) Again in Figure 4, panel A, the distance of residues 876 to the bound compounds needs to be carefully measured and illustrated in both WT and mutated receptors. The implication of this distance needs to be discussed within the context of receptor-ligand interactions.6) Results section: there is often interplay between the degree of antagonism and affinity/potency, with introduction of larger substituents engendering greater antagonism, but in most cases also lowering potency. It looks like the two new antagonists are equipotent with their ENZ and ARN parents, but this should be stated more clearly. Also, it would be reassuring and potentially interesting to have binding affinity measurements of the parent compounds, the new antagonists on both WT and F876L AR.7) In considering the value of this work as a framework for future studies, it would be useful to know what other AR mutations, if any, were identified in the drug resistant tumors listed in Table 1. Why not just sequence drug resistant tumors rather than go through the mutagenesis step. If other mutations were identified, are they also sensitive to the novel antagonists? Some additional consideration of this point is needed.8) Bicalutamide appears to be an antagonist on F876L AR in some Figures  but an agonist in others. This should be commented upon.Additional comment9) It would be of interest to separate the enantiomers of the two new antagonists, DR103 and 106. They likely have different potencies and efficacies, and if one is more potent and more agonistic than the other, it might limit the activity measured for the racemic. The authors may wish to comment on this. 1) From a biological standpoint, the only significant experiment considered to be missing was a test of one of the novel antagonists for suppression of tumorigenicity of the F867L prostate cancer cell lines in the xenograft model. This experiment would complete the thought that the rational drug design process ends with the predicted anti-tumor effect in vivo. After deliberation, this experiment was considered not necessary for publication given the overall depth of the studies, but it would further strengthen the manuscript if available.We agree that in vivo tumor xenograft studies would provide further strength to our rational drug design and we are embarking on pharmacokinetic and pharmacodynamic studies before we proceed with xenograft studies. These are lengthy experiments that will be reported later.2) All three reviewers thought that despite the nice rendering of AR-ligand structures after MD simulations, it is not clear exactly in what way the F876L change results in altered interaction with the ENZ and ARN ligands, and where on the ligand the contact is occurring. A figure illustrating an enlargement of this region would add to the paper and perhaps enable a cogent discussion of the specific contacts the enables antagonism to is restored by altering the ligand structure.Thank you for these suggestions. We have included additional figure panels  and discussion of specific AR-ligand contacts in the results to further clarify the possible mechanisms underlying the antagonism-to-agonism switch for ENZ and ARN, and the restored antagonism for newly developed ligands.3) The paper would be strengthened by evidence that the F876L mutation does indeed occur in PCa patients undergoing ENZ therapy, and, although it may be too soon for ENZ-resistant patients to have emerged, it would be worth discussing this as a future direction, because these patients would obviously be candidates for treatment with the second generation drug reported in this paper.We agree that our paper would be strengthened by clinical evidence of the mutation and we are working hard to obtain relevant clinical material. This is challenging for two reasons:First, enzalutamide was FDA approved only five months ago, so very few patients have been treated outside the original clinical trials, and, for the most part, trial investigators did not obtain tumor tissue or plasma.Second, CRPC presents unique clinical challenges in obtaining tumor tissue that have led us to focus on developing blood-based assays to detect AR mutations (CTCs and ctDNA). We are actively pursuing these studies with collaborators.We have updated the text to discuss this future direction.4) In Figure 3, the distance of residues 876 to the bound enzalutamide need to be carefully measured and illustrated in both WT and mutated receptors. The implication of this distance needs to be discussed within the contact of receptor-ligand interactions.We have included the measurements requested , and we have added discussion of these data within the text.We have indicated the distances between residues 876 on AR WT or AR F876L to the bound enzalutamide and ARN-509. The C rings are in close proximity (less than 4 Å) to position 876. Moreover, F876 (WT) was slightly closer to the C rings than L876, and clearly formed more pairwise atomic contacts with the C rings. We have added to the Discussion as described above. Meanwhile, we avoid over-interpreting the exact values of these distances, as positions of C rings in simulated structures were seen to vary even though they remained approximately at the same spot near residues 876.5) Again in Figure 4, panel A, the distance of residues 876 to the bound compounds needs to be carefully measured and illustrated in both WT and mutated receptors. The implication of this distance needs to be discussed within the context of receptor-ligand interactions. We have included the measurements requested , and we have added discussion of these data within the text.We have indicated the distances between residues 876 on AR WT or AR F876L to the bound DR103. We emphasize here that the restored antagonism was not due to recovering receptor–ligand interactions at the mutation site (residue 876 on helix 11) but rather pushing helix 12 to adopt an antagonist-like conformation as our design rationale, the D-ring hypothesis, intended. The newly added inset also indicated that there is no proof of receptor–ligand interactions at the mutation site being recovered, which might be the only implication these distances provided. For the reasons above, we chose to not discuss these distances further.6) Results section: there is often interplay between the degree of antagonism and affinity/potency, with introduction of larger substituents engendering greater antagonism, but in most cases also lowering potency. It looks like the two new antagonists are equipotent with their ENZ and ARN parents, but this should be stated more clearly. Also, it would be reassuring and potentially interesting to have binding affinity measurements of the parent compounds, the new antagonists on both WT and F876L AR.This is an important point that we have investigated with additional experiments. Under conditions of relatively low androgen concentrations (10% FBS), DR103 is equipotent to enzalutamide and ARN-509. However, as predicted by the reviewers, DR103 is less potent against WT AR under conditions of high androgen concentration as measured by reporter assays . As for binding affinity, we have included a competitive binding experiment with radiolabeled DHT in cells expressing the WT or mutant receptor, showing increased affinity of enzalutamide for F876L (comparable to DHT affinity), consistent with conversion to agonism .7) In considering the value of this work as a framework for future studies, it would be useful to know what other AR mutations, if any, were identified in the drug resistant tumors listed in Table 1. Why not just sequence drug resistant tumors rather than go through the mutagenesis step. If other mutations were identified, are they also sensitive to the novel antagonists? Some additional consideration of this point is needed.We chose the mutagenesis screen strategy based on our prior success with kinase inhibitor mutagenesis screens  and the speed with which mutations can be recovered relative to waiting for outgrowth of drug-resistant xenografts. We also believe this could be a general methodology for other NHRs.Although we cannot say that we screened to saturation, F876L is the only mutation we recovered and we recovered it multiple times. A few additional AR mutations emerged in the drug resistant xenograft tumors, but F876L was one of only 2 mutations that occurred in multiple tumors, and the only mutation that arose in both the LNCaP/AR xenograft and CWR22Pc systems. The second mutation (isolated multiple times in the xenograft model) has been reported in association with androgen insensitivity syndrome (AIS) and is therefore predicted to yield a functionally impaired AR. We are in the process of characterizing this one further.8) Bicalutamide appears to be an antagonist on F876L AR in some Figures  but an agonist in others. This should be commented upon.As noted by the reviewers, the pharmacology of bicalutamide against the mutant varies depending on the context. For example, bicalutamide is clearly not an agonist for F876L under the androgen-deprived conditions in which enzalutamide is. However, in the presence of androgen, bicalutamide at low concentrations has modest antagonist activity (as measured by our GFP reporter) that is lost at higher concentrations, presumably due to the well-documented agonism of bicalutamide against WT AR when expressed at high levels. Finally, bicalutamide has minimal antagonist activity against mutant-expressing cells in growth assays. These data are now added in a new figure  and in a new paragraph in the Results. Our conclusion from all of this is that bicalutamide is highly unlikely to provide a clinical solution to the F876L mutant; hence, the rationale for DR103.Additional comment:9) It would be of interest to separate the enantiomers of the two new antagonists, DR103 and 106. They likely have different potencies and efficacies, and if one is more potent and more agonistic than the other, it might limit the activity measured for the racemic. The authors may wish to comment on this.This is an important point with clear implications for future drug design, as suggested by the modeling reported in this paper. While work has begun to address this issue by chromatographically separating the enantiomers, we are not in a position to include pharmacological data associated with the enantiomers until their absolute conformation has been defined. We are actively working to crystallize the compounds to define the (S) and (R) enantiomers.


There has been a dramatic increase over the last decade in research on technologies for enhancing movement training and exercise for people with a disability. This paper reviews some of the recent developments in this area, using examples from a National Science Foundation initiated study of mobility research projects in Europe to illustrate important themes and key directions for future research. This paper also reviews several recent studies aimed at combining movement training with plasticity or regeneration therapies, again drawing in part from European research examples. Such combination therapies will likely involve complex interactions with motor training that must be understood in order to achieve the goal of eliminating severe motor impairment. A key working hypothesis of rehabilitation science is that use-dependent plasticity perseveres through motor system injuries and diseases. This hypothesis drives intensive, ongoing efforts to optimize rehabilitation experiences for people with a movement disability, so as to best promote use-dependent plasticity. In the past twenty years, there has been an increasing recognition that technologies, including robotics, orthotics, wearable sensors, computer vision, computer gaming, electrical stimulation, virtual reality, machine learning, and computational modeling, can play an important role in these efforts -5. In thThere are three primary motivations for developing new technology for rehabilitation therapy. First, improved technology has the potential to allow more therapy with less supervision, improving rehabilitation cost-benefit profiles. This objective can be expressed as developing technology that optimally promotes use-dependent plasticity while lowering the cost of therapy. Second, technology has the potential to more accurately quantify therapy, including patient characteristics that predict therapy success, the dose and content of therapy, and clinical outcomes. This quantification property of technology is important for improving the mechanistic understanding of rehabilitation science, clinician decision-making, and patient feedback and motivation. Third, technology has the potential to allow entirely new types of therapy. One example is the concept of providing continuous therapy with wearable devices. Rehabilitation therapists cannot be omnipresent, but smart, wearable technology almost can, providing therapy throughout the day as people participate in activities of daily living. The therapeutic effect produced by functional electrical stimulation (FES) foot drop stimulators, in which people who use the stimulators over an extended period of time exhibit improved walking ability even when they turn the stimulator off, is one example . AnotherAiming to achieve these three goals, there has been a rapid increase in the development of therapeutic technology in the past 10 years, and a rapid growth in commercial products for rehabilitation training . HoweverMost clinical trials of robot-assisted movement training have used robots to physically assist the limbs of patients as they attempt desired movements and/or play computer-guided activities and games. Thus, the robots tested so far have typically implemented a technique from physical rehabilitation called "active assist therapy", in which the patient actively tries to achieve a movement as the therapist manually assists in the movement. Besides allowing a patient to perform movements not possible without assistance, it is thought that active assist therapy may generate new patterns of sensory input that may influence brain plasticity.The first robot therapy study that illustrates the state of the field is the recent multi-center randomized controlled trial of robot-assisted therapy sponsored by the Department of Veterans Affairs . In thisIn another study, 48 people with chronic stroke who were ambulatory at study start were randomized to train walking using a treadmill and the Lokomat gait robot, or a treadmill with manual assistance from a physical therapist . For theIn a third study, 28 people with moderate to severe arm impairment due to a chronic stroke were randomized to participate in training with a passive arm exoskeleton called T-WREX or in standard table-top exercises with no technology . T-WREX One can extrapolate broader themes that characterize the general state of technology for rehabilitation therapy from these three illustrative studies. First, considering the goal of improving cost-benefit profiles, one can observe that technology-assisted exercise produced significant benefits in all three of the studies reviewed above, and that it is sometimes possible to use technology with only small amounts of therapist supervisory time, as directly measured in the T-WREX study. These observations support the premise that, indeed, some aspects of rehabilitation therapy do not require the immediate presence of a rehabilitation therapist to be effectively implemented with technology. However, the cost of the technology used for this substitution may still limit cost-benefit profiles, as was found, for example, in the cost analysis of the MIT-Manus study, indicating a need for lower cost technologies.Second, considering the goal of quantification, while it is true that there is potentially a computer record of every force or movement the participants made during training in these studies, we are just beginning to understand how to use this data to predict responders, guide therapy, or define mechanisms of recovery. For example, as mentioned above, data from MIT-Manus has been used to identify a role for sub-movement blending in movement therapy, and data from the Lokomat and rodent robotic devices was used to analyze the role of kinematic variability in training. Thus, the field is just beginning to develop ways to use data from sensors incorporated into rehabilitation technology to provide insight into use-dependent plasticity.Third, considering the goal of innovating to produce new forms of therapy that are more effective, it is apparent that some innovations in technology-based therapy are as effective as therapists for particular forms of training, few or none are more effective, and many are less effective. The reasons are complex and poorly understood at present, but a key limitation that must be overcome is improving the hardware and control design of these devices to increase efficacy. Understanding the reasons particular implementations decrement learning, while other implementations increment learning, is important. At present, one might say that the only innovation that new technologies routinely make available, besides semi-automation of training, is that of a more motivating context for rehabilitation training, by virtue of helping patients achieve movements or simulated activities that they normally could not, and by providing a computer gaming context with quantitative feedback to motivate practice.Given this current status, how can physical therapeutic technology be improved? Several key themes emerged during our panel's visit to Europe.The healthcare environment in some countries in Europe has made it easier to test therapeutic technologies earlier in rehabilitation, as patients are permitted to stay in sub-acute rehabilitation facilities much longer than in the United States. Landmark studies by the group of Dr. Stefan Hesse at Charite Hospital, Berlin, found large improvements in motor function of both the upper  and loweAnother trend in the field is to develop lower-cost devices. Professor Etienne Burdet of Imperial College has observed that there is a spectrum of complexity in technology for rehabilitation therapy, starting with simple rehabilitation objects already commonly used in rehabilitation therapy, to passive devices with sensors, to simple robotic devices for decentralized use, to complex robotic systems Figure . Moving http://www.trilcentre.org/media/news/tril-at-eric-conference.html, the Department of Electronics, Computer Sciences and Systems, at the Università Di Bologna http://www3.deis.unibo.it/en, and others. Software on cell phones combined with movement sensors could monitor exercise performance and compliance, test a user's physical status, and provide encouragement, motivation, and feedback. Gaming consoles, such as the Nintendo Wii, the Microsoft Kinect, and the Sony Playstation Move, although not technically for rehabilitation, could be adapted for training and assessment, and custom computer games can be developed as well [The work of Dr. Hesse is also of note again in this regard, as the robotic devices that produced the excellent clinical results mentioned above, which are now sold by a start-up company RehaStim, are relatively simple, low degree-of-freedom robotic devices for both the upper and lower extremities. Another world leader in commercializing therapeutic technology, Hocoma A.G., recently released a simplified arm therapy device, ArmeoBoom, based on the work at U. Twente and Roessingh Rehabilitation Center . Major c as well . DespiteAt the same time that many groups are working to develop simpler technology, other groups worldwide are increasing the mechanical sophistication of the technology to be used in rehabilitation. The rationale for this work is that training more naturalistic movements may improve functional outcomes. For the upper extremity, groups at ETH in Zurich , Scuola For the lower extremity, work is underway at ETH Zurich, University of Pisa, and Hocoma to add pelvic and ankle degrees of freedom to the Lokomat, and concepts from the simple gait-trainer developed by Hesse have been expanded in collaboration with Fraunhofer IPK to produce the Haptic Walker Gait Trainer 2 ,33. ThisAnother major trend in technology for rehabilitation therapy is to make the technology wearable. Wearable sensor systems for therapy are reviewed in a companion article in this special issue. The rationale for developing actuated, wearable orthotic systems is, again, to make training more naturalistic, and ultimately to free training from the confines of the rehabilitation clinic. This freeing of training will break down the current distinction between assistive and therapeutic technology; people will use therapeutic technology to assist them in activities of daily living, undergoing therapy at the same time as achieving desired tasks. Such technology will be designed to continuously adapt to the user, to appropriately challenge them and progress training. This dual-purposing of therapeutic technology will increase the dosage of therapy beyond levels possible in the clinic only, and increase the likelihood that what is learned during training will be useful in the real world, since training will be in the real world.Examples of wearable systems developed in Europe include the ActiGait system, sold by Neurodan/Otto Bock. ActiGait is a multi-channel, implantable functional electrical stimulation system for foot drop based on research at the University of Aalborg . AnotherThere are intensive efforts worldwide to improve the control algorithms and patient feedback algorithms for therapeutic technology. One concept is to make robotic therapy devices patient cooperative, as proposed by Professor Robert Riener at ETH Zurich , a stratAnother approach is to combine brain computer interface technology or functional electrical stimulation technology with robotic therapy. An example of the use of BCI technology for therapy comes from Dr. Pons, who is also the Project Coordinator for The BETTER project . This project is focused on improving physical rehabilitation therapies by combining brain computer interfaces (BCI) with wearable exoskeletons and robotic gait trainers, such as the Lokomat. The BCI being used is an EEG-based BCI. The goal is to encourage brain plasticity by programming the robot to exert physical stimulation at the periphery as a function of the neural activation patterns at the brain. One possible benefit of this approach is to intelligently promote active participation of patients during therapy. Training of the BCI parameters may still be possible even for a person who is completely paralyzed by tapping into the mirror neuron system . Mirror Ideally, therapeutic technology would be designed based on experimentally verified mathematical models of how limb use drives plasticity, in the same way that new materials can be designed based on a fundamental knowledge of chemistry and solid mechanics. Such models do not exist yet; the field of "neurocomputational rehabilitation" is nascent -56. One Improvements in motor performance following rehabilitation therapy, with or without technology, are often modest. While refinements in rehabilitation technology will likely improve clinical outcomes by making therapy more available, more motivating, and perhaps more targeted and effective, it is also likely that recovery will ultimately be limited unless the damaged or diseased biological systems responsible for the motor impairment are restored. We define combination therapies as rehabilitation strategies that combine drug, molecule, or cell-based therapeutics with technology for movement training. There is already evidence that loading, training, and exercise will be important for facilitating biologic therapeutics, including regeneration of skeletal and cardiac muscle, bone, and neural systems. For example, physical therapeutics appear to establish a more permissive microenvironment and help direct cell fate for regeneration . In the A key example comes from Dr. James Fawcett's group at Cambridge University, which has been working with chondroitinase ABC, a bacterial enzyme that digests molecules that help form cartilage-like barriers to axonal growth. Using a rat model of a spinal cord injury that disrupted the corticospinal tract, they found that delivering chondroitinase to the injury site without training the rat to use its impaired paw was ineffective, where the outcome measure was the number of sugar pellets the animal retrieved from a stair-cased well . They stOne interpretation of these results is as follows Figure . The plaOther work has found similar evidence of competition in training. For example, rats with lesions of the corticospinal tract who were trained in skilled reaching improved in reaching ability, but made more errors in a horizontal ladder test ,65. The Another important example is provided by the group of Prof. Gregoire Courtine of the Experimental Neurorehabilitation Lab at the University of Zurich. This group uses animal models of SCI to help inform their clinical use of robotic devices, and is investigating use of electrical stimulation of the spinal cord for motor function combined with neuropharmacological interventions, in both murine and non-human primate models. One recent study from this group with a remarkably comprehensive quantitative analysis coupled robotic locomotor training, pharmacological intervention, and epidural electrical stimulation in rats with a complete SCI . The comThis work has clear implications for engineering approaches to rehabilitation exercise. In the words of Dr. Fawcett and Dr. Armin Curt, "the plastic CNS may be very vulnerable to poorly planned rehabilitation" . PhysicaThere is an explosion in new rehabilitation technologies; however, the field is in its infancy. Beyond the fact that these technologies can in some case make rehabilitation exercise more engaging and less labor intensive, the gains delivered are still unclear. Fundamental scientific insight is needed into the learning and plasticity mechanisms that these technologies seek to stimulate; the current lack of insight makes device design somewhat haphazard. Nevertheless, promising areas of development include developing technology for delivering therapy both earlier in clinics, and later at home; investigating the relative roles of both simpler and more complex technology in promoting plasticity, thereby testing the premise that training with more naturalistic movements will better promote functional recovery; making devices wearable to extend the reach of training to the lived-in environment; improving feedback and implementing learning-based control to make training more engaging and challenging; and coordinating multiple therapeutic modalities, including robotics, FES, and BCI's to enhance the effect of training. A new field of neuro-computational rehabilitation appears to be developing, in which computational models will be used to simulate and understand use-dependent plasticity in rehabilitation therapy. Regenerative therapies may enable levels of recovery far beyond those possible with rehabilitation exercise alone, but these therapies cannot progress independently of rehabilitation exercise.Thus, the challenge of developing technologies that significantly improve on rehabilitation outcomes compared to conventional rehabilitation remains to be met. The quantification power associated with sensors incorporated into therapeutic technologies, coupled with the nascent field of neuro-computational rehabilitation will help resolve this gap. We expect there to be a "science of combination therapies" that seeks to understand the complex interactions between training, plasticity, and regeneration ,60. The David Reinkensmeyer has a financial interest in Hocoma, A.G., a company that makes robotic therapy devices. The terms of this arrangement have been reviewed and approved by the University of California, Irvine, in accordance with its conflict of interest policies.


AbstractMultiproductus and a new species Multiproductus complantussp. n. are described and illustrated. A key is given to distinguish all species of the genus.General characteristics of  Multiproductus belonging to Paralimnini of Deltocephalinae (Hemiptera: Cicadellidae), was established by Multiproductus ramosus Xing, Dai & Li, 2011, from China. Here we describe and illustrate a second new species: Multiproductus complantus Xing & Li,sp. n. from Guizhou Province, China. A key is given to distinguish all species of the genus.The Oriental leafhopper genus PageBreakSpecimens were collected by sweeping net. Dry specimens were used for the description and illustration. External morphology was observed under a stereoscopic microscope and characters were measured with an ocular micrometer. The genital segments of the examined specimens were macerated in 10% NaOH and drawn from preparations in glycerin jelly using a Leica MZ 12.5 stereomicroscope. Illustrations were scanned with Canon CanoScan LiDE 200 and imported into Adobe Photoshop CS3 for labeling and plate composition.Terminology of morphological and genital characters follow Xing, Dai & Lihttp://species-id.net/wiki/MultiproductusMultiproductus Xing, Dai & Li, 2011: 65.Multiproductus ramosus Xing, Dai & Li, 2011.Multiproductus Xing, Dai & Li, 2011 see Multiproductus is distributed in China . This genus is especially well differentiated from other genera of Paralimnini in Deltocephalinae by the unique forewing with outer subapical cell extended to costal margin, branches of vein R recurved distally, resulting in fifth (outer) apical cell. The two species of this genus are very similar in appearance. This situation is similar to the paralimnine genus Paralaevicephalus wherein all species are essentially the same in external appearance and several different species can be collected in the same location.For the relationship and diagnosis of China .Xing, Dai & Li, 2011http://species-id.net/wiki/Multiproductus_ramosusMultiproductus ramosus Xing, Dai & Li, 2011: 66–67, figs 1–15.China: 1♂ (Holotype), Guizhou Prov., Guanling County, Huajiang, 16 August 2009, coll. Jichun Xing; 2♂♂4♀♀, Guizhou Prov., Guanling County, Huajiang, 16 August 2009, coll. Jichun Xing; 1♂, Guizhou Prov., Ziyun County, Baishiyan, 28 July 2008, coll. Jichun Xing; 1♀, Guizhou Prov., Yanhe County, Mayanghe, 10 June 2007, coll. Jichun Xing; 1♀, Yunnan Prov., Menghai County, Mannong, 24 July 2008, coll. Yuehua Song; 1♂, Yunnan Prov., Baoshan City, Baihualing, 7 May 2010, coll. Yanli Zheng; 1♂1♀, Hainan Prov., Bawangling, 16 April 2013, coll. Jichun Xing.China .Xing & Lisp. n.http://zoobank.org/28A036CA-70C0-48B7-8410-D0D405913F75http://species-id.net/wiki/Multiproductus_complantusYellowish-brown species, with light veins on forewings. Crown yellowish brown with four dark brown marks on anterior margin and orange–yellow longitudinal band midway between midline and eye extending to posterior margin of pronotum. Eyes black, fairly large. Ocelli pale yellow. Face black, frontoclypeus with yellowish brown transverse stripes on both sides. Forewings pale yellow. Hind macropterous. Legs marked with brown.PageBreaktwo setae on apical transverse row; plantar surface with one row of five stout setae at middle and one row of four stout setae at lateral margin.Head slightly wider than greatest width of pronotum. Vertex with fore margin produced triangularly, median length longer than width between eyes. Ocelli on anterior margin, separated from corresponding eye by approximately their own diameter. Frontoclypeus distinctly longer than wide, anteclypeus slightly narrowed apically. Antennae arising near lower corner of eye. Pronotum with anterior margin strongly and roundly produced, posterior margin slightly concave. Scutellum triangular, slightly shorter than pronotum, with transverse suture curved and depressed. Forewing with outer subapical cell extended to costal margin, branches of vein R recurved distally, resulting in fifth (outer) apical cell, and veins of clavus appear to extend to the claval suture, 4 times as long as wide, appendix present. Hind wings with three apical cells and two anteapical cells. Profemur with 2 dorsoapical setae. Hind femur apical setal formula 2+2+1. Hind tibia flattened and nearly straight, with PD setae very long, several supernumeral setae present between AD and AV rows; AD row with somewhat thin setae between very thick macrosetae. Metabasitarsomere with three platellae and Male genitalia. Male pygofer side elongate with many large setae medially; without processes : ♂, 3.0 mm.Grasses.PageBreakHolotype ♂, China: Guizhou Prov., Ziyun County, Baishiyan, Kazha, 2 October 2013, coll. Jichun Xing (GUGC).Multiproductus ramosus Xing, Dai & Li, 2011 in appearance, but can be distinguished from the latter by the aedeagal shaft with two pairs of lateral preapical processes, the apical process of style wide and flat, sword shape, and the valve subtriangular and subgenital plate wide.This new species is similar to complantus”, referring to the apical process of style wide and flat.The species name is derived from the Latin word “PageBreak


The androgen receptor (AR) is an important determinant of normal and malignant prostate growth. Therefore, a good understanding of the factors that regulate the transactivation of the AR is essential and could provide a better strategy to control prostate tumor growth, particularly in patients suffering from the hormone-refractory and the advanced stages of the disease. However, transcriptional activation by the AR is a complex and orchestrated process requiring multiple coregulators. Several coregulators have already been identified, including proteasome components, chromatin-re-modeling complexes and heat shock proteins. Others however remain uncharacterized and their role in AR transactivation is poorly understood. One such coregulator is the nuclear-resident, AR co-activator, Bag-1L. Overexpression of Bag-1L and the amplification of its gene have been reported in the hormone-refractory and metastatic stages of prostate cancer and in androgen-independent prostate cancer cells (AIPC). However the exact mechanism of Bag-1L-mediated regulation of AR action in prostate cancer is unclear.To confirm the contribution of Bag-1L to AR response in prostate cancer, we have downregulated the expression of Bag-1L in the androgen-dependent prostate cancer cell line LNCaP using RNAi. Subsequently we performed genome-wide mapping of Bag-1L, using genome-wide chromatin immunoprecipitation (ChIP-seq). Lastly, the ability of AR and Bag-1L to interact with one another was assessed by domain mapping experiments using GST pulldown assays.Here we show that Bag-1L depletion by RNA interference in the prostate cell line LNCaP significantly reduces the hormone response of several AR-target genes. In agreement, Bag-1L and AR co-localize to a large number of regulatory regions of AR-target genes as identified by ChIP-sequencing. Furthermore, domain mapping experiments identified the first 128 N-terminal amino acids of Bag-1L as necessary for enhancing the transactivation function of the receptor. This sequence contains a duplication of a GARRPR motif, which we identified as the main interaction site between Bag-1L and AR. We were able to further confirm the importance of this motif by amino acid substitutions of the sequence, which impairs the AR and Bag-1L-mediated AR transactivation. Intriguingly, overexpression of the N-terminal sequence of Bag-1L encompassing the conserved hexapeptide sequences exerts a dominant negative effect on androgen-mediated gene expression and androgen-dependent tumor growth. The GARRPR was also identified in other regulators of AR activity, such as Huntington associated protein 1, nuclear receptor coactivator 4 and p21-activated kinase 6.We have identified a novel AR binding motif different from the previously described LXXLL and FXXLF sequences of other coactivators of AR. In the long-term we propose to use this knowledge to design novel drugs targeting this interaction site for the therapeutic intervention of prostate cancer.


Left ventricular ejection fraction (LVEF) and dimensions were determined at baseline and in 132 patients after six months of standard medical therapy excluding β-AR-blockers (not indicated as standard care at the time of completing this study).2C-AR variant were homozygous for the Del322-325 (risk) allele. The Gly389Arg polymorphism was not associated with IDC (control n = 429) , nor did it predict LVEF and cavity dimensions either before or after therapy.All patients and controls genotyped for the α2c-AR variant, the β1-AR variant neither increased the risk for IDC nor predicted its severity or progression in patients not receiving β-AR-blockers.In patients homozygous for the risk allele of the α A common polymorphism of the β1-AR gene – a substitution of glycine (β1Gly389) for arginine (β1Arg389) at amino acid 389 – occurs within a Gs-coupling domain.1Arg389 variant have a much greater ability to couple to adenyl cyclase than do those receptors with the β1Gly389 variant.1Arg389 receptor polymorphism to activate adenyl cyclase may therefore determine the natural history of progressive heart failure or its response to β-AR-blocker therapy.Persistent β-adrenoreceptor (β-AR) activation promotes progressive heart failure,1-AR gene,2c-AR gene variant, has been reported to increase the risk for developing heart failure in African-Americans.2-ARs operate as presynaptic inhibitory receptors that control the release of norepinephrine and influence the progression of heart failure.2C-AR – the deletion of four consecutive amino acids (Del322-325) – results in a substantial loss of agonist-mediated receptor function in transfected cells.2C-AR activation inhibits norepinephrine release,2C-AR Del322-325 polymorphism may result in enhanced norepinephrine release and hence increase the risk for heart failure.25Although the response to β-AR-blockers in patients with heart failure depends on the position of the 389 genotype of the βcids Del3-325 – re1-AR variant, when present with a polymorphic α2C-AR gene variant, increased the risk for heart failure in a group of African-Americans, this relationship was identified in a small study sample (n = 78 cases and n = 84 controls).n = 260 cases and n = 230 controls) or Japanese (n = 91 cases and n = 119 controls) descent, an interaction between these two gene variants and the risk of heart failure has not been confirmed.Although it appears that the β1-AR Gly389Arg and α2C-AR Del322-325 variants and (1) the presence, (2) the severity and (3) the progression of idiopathic dilated cardiomyopathy (IDC) in a relatively large sample of black South Africans studied at a time when β-AR-blocker therapy was not indicated as standard care in South Africa.The aims of the present study were therefore to assess the relationship between the βThis study was approved by the Committee for Research on Human Subjects of the University of the Witwatersrand  and conforms to the principles outlined in the Declaration of Helsinki. The clinical component of the study was conducted between 1995 and 2001 when the use of β-AR-blockers was not considered standard therapy for heart failure in South Africa. All patients gave written informed consent before study entry.1-AR and α2C-AR gene polymorphisms and IDC in this population, a case-control study was performed in which 403 consecutive patients with IDC and 429 age-matched control subjects of the same ethnic origins (African ancestry) were recruited.To assess the relationship between the βSubjects in the control group had a greater body mass index and consisted of more females After initial presentation, and following a diagnosis by clinical examination and echocardiography (screening visit), 176 of the 403 patients agreed to participate in a prospective study assessing the impact of the β-AR gene polymorphisms on LV dimensions and function. During the six-month follow up, 24 patients died and 20 were lost to follow up. Of the remaining 132 patients who were followed prospectively, 71 were newly diagnosed. The demographic and clinical characteristics of the subgroup of IDC patients on whom follow-up LV structure and function was assessed were comparable in their demography and clinical characteristics to those of the total group of IDC patients assessed These 132 patients who were followed prospectively received treatment with digoxin and diuretics (furosemide) for seven days and then angiotensin-converting enzyme inhibitors (ACEI) were added to their therapy. These patients were followed for six months. Monthly visits were scheduled for clinical assessment and evaluation of the patient’s adherence to therapeutic agents.2-AR genotype on LV systolic function, as this measurement is not subject to observer bias. To show a 10-point difference in radionuclide LVEF between groups with 80% power after six months of therapy required a sample size in each group of 21 patients.Clinical examinations, echocardiographic assessments and radionuclide studies were performed at baseline, and then repeated at six months. The primary endpoints were LVEF determined using radionuclide ventriculography, and LVEDD determined using echocardiography. Radionuclide ventriculography as opposed to echocardiography was used as the method of preference to assess the impact of βA physician assessed the NYHA functional class of the patients during the baseline and follow-up visits. The same physician evaluated all patients. A multiple-gated equilibrium cardiac blood pool scintigraphic technique was used to measure LVEF (Elscint Apex 409).Two-dimensional targeted M-mode echocardiography with doppler colour-flow mapping was performed using a Hewlett Packard Sonos 5500 echocardiograph attached to a 2.5 or 3.5 MHz transducer. All studies were performed and interpreted by the same operator and recorded on videotape. Left ventricular dimensions were measured according to the American Society of Echocardiography guidelines.Blood for genetic studies was obtained during the initial screening period. Deoxyribonucleic acid (DNA) was extracted from whole blood using standard techniques, as previously described.1-AR gene was undertaken using a polymerase chain reaction (PCR)-restriction fragment length polymorphism-based technique employing the appropriate primer pairs and restriction enzymes. DNA was amplified using 5′-CGCTCTGCTGGCTGCCCTTCTTCC-3′ and 5′-TGGGCTTCGAGTTCACCTGCTATC-3′ forward and reverse primers respectively. PCR was carried out in a total volume of 20 μl containing ~ 50 ng DNA, 1 × PCR buffer (Takara), 2 mM MgCl2, 0.2 mM dNTP, 2.5 mM forward and reverse primers, 6% dimethylsulfoxide, 1 μg.ml-1 bovine serum albumin, and 1 unit Taq polymerase (Takara).Genotyping of the Gly389Arg variant of the βI (three hours at 37°C). Cleavage of the 530-bp product into 342- and 154-bp fragments confirms the presence of this allele. BcgI (New England Biolabs) cleaves twice to excise its recognition site, accounting for the 34-bp discrepancy in the fragments generated. The restriction digests were electrophoresed on 3% agarose gels and visualised with ethidium bromide staining and ultraviolet illumination. To avoid misgenotying as a consequence of failure of restriction enzyme digestion, a known heterozygous sample for each of the polymorphisms was included in each PCR, digestion procedure and gel, and all samples were genotyped in duplicate.The PCR conditions were as follows: 94°C for four minutes, followed by 30 cycles of denaturation (94°C for one minute per cycle), annealing (60°C for 45 seconds) and extension (72°C for one minute) with a final extension step at 72°C for four minutes. The Arg389 allele PCR product contains a unique site for restriction by 1 333 units of Bcg2c-AR gene was undertaken using automated sequence analysis of PCR fragments.2, 0.2 mM dNTP, 2.5 mM forward and reverse primers, 12% dimethylsulfoxide and 1 unit Taq polymerase (Takara).Genotyping of the Del322-325 variant of the αE coli exonuclease I (Fermentas). Samples were processed using the BigDye version 3.1 Dye Terminator Cycle Sequencing Kit (Applied Biosystems) according to the manufacturer’s instructions on the Genetic analysis system SCE2410 .The PCR conditions were as follows: 94°C for four minutes, followed by 40 cycles of denaturation (94°C for 40 seconds per cycle), annealing (59°C for 30 seconds per cycle) and extension (72°C for 30 seconds per cycle) with a final extension step at 72°C for seven minutes. PCR products were purified using shrimp alkaline phosphatase and n = 50) and controls (n = 50) genotyped for the Del322-325 variant of the α2c-AR gene were homozygous for the Del322-325 allele. Hence not all patients or controls were genotyped for the Del322-325 variant of the α2c-AR gene.Analysis was performed using BaseSpectrum V2.1.1 software . All patients ]. To test for Hardy-Weinberg equilibrium, the expected genotype numbers were calculated from the allele frequencies and deviation from the observed genotype numbers determined using a χ2 test. Effects of alleles on the presence of IDC were evaluated using a χ2 test.Data are presented as mean ± SEM. Case and control group mean values were compared with the use of a two-sample Student’s t-test was used to detect changes from baseline. Analysis of covariance adjusting for baseline data, age, gender, disease duration and type of ACEI was employed to determine differences in changes in LV cavity size and function, and final LV cavity size and function between genotype groups. Genotype effects on final LV cavity size and function were assessed using MANCOVA with age, gender, BMI, disease duration and baseline data included as covariates.Genotype effects on the presence of IDC were assessed with logistic regression analysis with age, gender and body mass index (BMI) included as covariates. To assess the effect of genotype on either LVEF, or cardiac dimensions, a MANCOVA was performed with age, gender, disease duration and BMI included in the regression model. A paired Student’s No significant differences were noted in the demographic or general clinical data in genotype-specific subgroups of patients on whom LV structure and function was determined 2c-AR gene were homozygous for this variant.All cases and controls genotyped for the Del322-325 variant of the α2 values when comparing expected and actual genotype numbers were 2.72 and 1.84 for the case and the control groups respectively 1-AR genotype was not an independent predictor of IDC .Both the case and the control groups were estimated to be in Hardy-Weinberg equilibrium. The χ1-AR genotype-specific group died or were lost to follow up (data not shown). All genotype groups received similar doses and type of drug therapy (type of angiotensin-converting enzyme inhibitor is indicated in 1-AR gene failed to predict baseline LV function or cavity dimensions p < 0.0001), LVEDD decreased by 0.27 ± 0.06 cm (p < 0.02), and LV end-systolic diameter decreased by 0.38 ± 0.07 cm (p < 0.01) in all patients considered together. The increase in LVEF and decrease in LVEDD and LVESD were the same in β1-AR genotype-specific groups 1-AR genotype failed to predict LV function and cavity dimensions A similar number of patients in each β2C-AR – a deletion of four consecutive amino acids (Del322-325) – that results in a substantial loss of agonist-mediated receptor function in transfected cells1-AR gene is not associated with IDC, nor does it predict the degree of systolic dysfunction and dilatation at baseline or progression after six months of standard medical therapy (excluding β-AR blockers) in IDC.The main findings of the present study are as follows: a common coding polymorphism of the gene for the αcids Del3-325 – th1-AR gene variant at position 389 either alone or in synergy with the α2C-AR Del322-325 variant modifies the response to β-AR-blocker therapy in heart failure,2C-AR Del322-325 variant, the β1-AR gene variant at position 389 does not influence either the risk for the clinical expression of the phenotype for heart failure, the severity of heart failure, or the progression of heart failure independent of β-AR-blocker therapy.Although a number of studies have indicated that the β1-AR gene variant at position 389 modifies the response to β-AR-blocker therapy in heart failure,1-AR gene and heart failure have been inconsistent. Although studies conducted in transgenic mice have demonstrated that the β1-Arg389 variant predisposes to a depressed ventricular function and pathological fibrosis,1-AR gene with the risk for human heart failure or IDC and the progression of these diseases have produced inconsistent data.20Unlike the apparent consistency of the data indicating that the β1-AR gene and heart failure is that an α2C-AR gene variant influences the impact of the β1-AR gene variant. Indeed, the presence of an α2C-AR Del322-325 polymorphism has been shown to increase the chances that the β1Arg389 variant confers an increased risk for heart failure in 79 African-Americans with heart failure and 84 control subjects.1Arg389 and α2C-AR Del322-325 polymorphisms has also been examined in a much larger group of individuals of European descent, and in a group of patients of Japanese descent but the interaction was not reproduced.27One potential explanation for the inconsistencies in the reported relationships between the Gly389Arg polymorphism of the β1-AR and the α2C-AR gene variants in a relatively large study sample of patients (n = 403) and controls (n = 429) of African descent. In the present study we were unable to show a relationship between the β1Arg389 gene variant and IDC in black South Africans who are homozygous for the risk α2C-AR Del322-325 allele. Moreover, in a prospective study we were unable to show a relationship between the β1Arg389 variant and either the degree of systolic dysfunction or the extent of cardiac dilatation at baseline or after six months of standard medical therapy, but without β-AR-blockers in black South Africans with IDC who were homozygous for the risk α2C-AR Del322-325 allele.The present study is the first to assess the role of the β1-Arg389 and α2C-AR Del322-325 alleles produced an odds ratio for heart failure of 3.46 .1-Arg389 variant in subjects homozygous for the Del322-325 allele produced an odds ratio for heart failure of 1.03 . As with many genetic association studies, although studies with small sample sizes, such as that reported on previously,et al.1-Arg389 variant and the Del322-325 allele.In 79 African-Americans with heart failure and 84 control subjects, homozygosity for the βet al.33Lastly, it is possible that although groups of patients of African descent were studied by both Small 1-AR gene variant at position 389 has a pathophysiological role to play in the clinical expression of IDC or its progression independent of β-AR-blockers in groups of African descent, the α2C-AR Del322-325 polymorphism may nevertheless still have an important role to play in this ethnic group. Previous studies have demonstrated a substantially increased risk of heart failure in African-Americans with the α2C-AR Del322-325 allele.et al.2C-AR Del322-325 allele in all patients (n = 50) and controls (n = 50) genotyped precluded us from studying the impact of this genetic variant in isolation on IDC in this population group.Although, as the present study indicates, it is unlikely that the β2C-AR Del322-325 polymorphism. However, in the 100 individuals genotyped using sequencing techniques (50 cases and 50 controls), all individuals were homozygous for the Del322-325 allele. Second, as with all case-control studies, we did not account for population stratification. However, the selection of controls was from the same ethnic group and geographic location (Soweto) as the cases, and the study sample was relatively large. Third, prospective follow-up was for only six months. However, this period was selected because beyond six months, mortality and morbidity related to heart failure would have limited the ability to appropriately assess LV structural and functional changes.1-AR genotype on systolic function during exercise. However, the main hypothesis of the present study was related to the risk for IDC and the impact on structure and function at baseline and after six months in the absence of β-AR-blocker therapy, rather than the impact of β1-AR genotype on exercising function.The limitations of the present study were as follows: first, we did not genotype all cases and controls for the α2C-AR Del322-325 variant, and that with this high-risk genetic background for the α2C-AR Del322-325 variant,1-AR gene neither predicts an increased risk for the expression of the clinical phenotype of heart failure in IDC, nor determines disease severity or progression of IDC after six months of standard medical therapy in the absence of β-AR blockers in this population group. These data suggest that the relatively consistent relationship noted between the β1-AR Gly389Arg variant and the response to β-AR-blocker therapy and heart failure previously reported onThe present study demonstrates that black South Africans are ubiquitously homozygous for the risk α


The androgen receptor (AR) has a central role in development and maintenance of the male reproductive system and in the etiology of prostate cancer. The transcription factor Pax6 has recently been reported to act as a repressor of AR and to be hypermethylated in prostate cancer cells. SPBP is a transcriptional regulator that previously has been shown to enhance the activity of Pax6. In this study we have identified SPBP to act as a transcriptional coactivator of AR. We also show that Pax6 inhibits SPBP-mediated enhancement of AR activity on the AR target gene probasin promoter, a repression that was partly reversed by increased expression of SPBP. Enhanced expression of Pax6 reduced the amount of SPBP associated with the probasin promoter when assayed by ChIP in HeLa cells. We mapped the interaction between both AR and SPBP, and AR and Pax6 to the DNA-binding domains of the involved proteins. Further binding studies revealed that Pax6 and SPBP compete for binding to AR. These results suggest that Pax6 represses AR activity by displacing and/or inhibiting recruitment of coactivators to AR target promoters. Understanding the mechanism for inhibition of AR coactivators can give rise to molecular targeted drugs for treatment of prostate cancer. The androgen receptor (AR) and androgens have a central role in development and maintenance of the male reproductive system and in the etiology of prostate cancer SPBP significantly reduces the expression of the Ets1 target gene MMP3 in cells Stromelysin-1 PDGF-responsive element Binding Protein (SPBP) is a 220 kDa nuclear protein displaying structural and functional properties of a transcriptional regulator. It contains an N-terminal TAD, three nuclear localization signals (NLS), a DBD containing an AT-hook motif, and a C-terminal extended plant homeodomain (ePHD) PAX genes are expressed in cancer cells and tissues where they are not normally found Pax6 is an evolutionary conserved transcription factor consisting of two DBDs, the paired domain (PD) and the paired-type homeodomain (HD), separated by a glycine-rich linker sequence In vitro binding studies revealed that Pax6 and SPBP compete for binding to the AR(DBD). This suggests that Pax6 represses AR activity by displacing and/or inhibiting recruitment of coactivators to AR target promoters.In this study, we have identified SPBP as a transcriptional coactivator of AR. SPBP interacts with the DBD of AR via its own DBD. We also mapped the interaction between AR and the AR repressor and developmental transcription factor Pax6 to involve their respective DBDs. Importantly, Pax6 inhibited the SPBP-mediated enhancement of AR activity on the AR targeted probasin promoter. This repression was partly reversed by increased expression of SPBP. Chromatin immunoprecipitations showed that over-expression of Pax6 resulted in less SPBP associated with the probasin promoter. Plasmids and primers used in this study are listed in 2 in a humidified atmosphere.HeLa (ATCC CCL2), Du145, and B3 (ATCC CRL-11421) cells were grown in Eagle's minimum essential medium (MEM). HEK293 (ATCC CRL-1573), SKNBe(2), and MEF cells were grown in Dulbecco's modified Eagle's medium (DME). PC3 cells were grown in Ham's F12K supplemented with 1.5 g/l sodium bicarbonate, while Kelly and LNCaP cells were grown in RPMI 1640 medium. The medium for the LNCaP cells were supplemented with 1.5 g/l sodium bicarbonate, 4.5 g/l glucose, 10 mM HEPES, and 0.1 mM sodium pyruvate. The GFP-AR 3108 cell line −7 M synthetic androgen R1881 (Perkin-Elmer) was (if indicated) added to the cells 1 hour before transfection. All wells were cotransfected with 75 ng pDestHA-AR, 75 ng of the luciferase reporter p285PB-Luc Subconfluent HEK293 or LNCaP cells in 24-well tissue culture dishes (Becton Dickinson) were transiently transfected using Metafectene Pro (Biontex) according to the manufacturer's protocol. The cells were cultured in 5% charcoal treated serum one day before transfection. Medium with 0.5% charcoal treated serum and 10Whole cell extracts were prepared by adding 400 µl lysis buffer  to confluent cells in 10 cm culture dishes (Nunc). The lysates were sonicated, centrifuged, and stored at −70°C. The protein concentration was measured with a BioRad DC protein assay kit. Fifty µg of each lysate was run on 6 or 12% SDS-polyacrylamide gels (SDS-PAGE) in Tris-Glycine buffer . Biotinylated Protein Ladder  was used as a molecular weight marker. The proteins were subsequently immunoblotted on Hybond-ECL nitrocellulose membranes (Amersham) in Towbin buffer  at 100 V for 1 hour. The membranes were blocked in 5% non-fat dried milk for 1 hour at room temperature. Primary antibody was added overnight at 4°C. The primary antibodies used were rabbit anti-Pax6 , mouse anti-AR , rabbit anti-SPBP 1∶500, , mouse a−7 M synthetic androgen R1881 (Perkin-Elmer). Sixteen hours post transfection the cells were harvested and chromatin immunoprecipitation was performed essentially as described previously Subconfluent HeLa cells in 10 cm dishes were transiently transfected with 2.25 µg of p285-PBLUC −7 M) for 48 hours post transfection. RNA was isolated using RNAeasy Plus Minikit (QIAGEN), cDNA made using Transcriptor Universal cDNA Master (Roche), and RT-PCR performed on a STRATAGENE ×300 amplification system using FastStart Universal SYBR Green Master (Roche). Primers were PSA-fw, PSA-rev, Actin-fw and Actin-rev  and transiently transfected with 100 ng pDestCherry-Pax6 or 150 ng pDestCherry-SPBP using TransIT-LT1 (Mirus Bio) according to the manufacturer's protocol. As described previously, the cells were starved in medium with charcoal-treated serum and hormone induced with R1881. Subconfluent HeLa cells in 8-well coverglass slides were transiently co-transfected with 175 ng pDestEGFP-SPBP and 25 ng pDestmCherry-Pax6 using TransIT-LT1. Live cell images were taken the following day after transfection using a Zeiss LSM510 confocal laser scanning microscope. Colocalization was studied using the Zeiss LSM 510 software.−7 M) was added to stimulate the AR. For coimmunoprecipitation of AR and SPBP, 2×105 HeLa cells were seeded in 10 cm dishes in MEM supplied with 5% charcoal treated serum, and incubated for 18–20 hours. The cells were then transiently cotransfected with 3 µg pDestEGFP-AR and 7 µg pDestHA-SPBP, using the Calcium Phosphate transfection procedure −7 M). The cells from both experiments were harvested 20 hours post transfection and immonoprecipitaed essentially as described For coimmunoprecipitation of AR and Pax6, expression of 3×Flag-Pax6 was induced from HeLa FlpIn 3×Flag-Pax6 cells by adding 1 µg/ml tetracycline. Subconfluent cells in 10 cm dishes (Nunc) were transiently transfected with either pDestEGFP-AR or pEGFP-C1 using Metafectene Pro (Biontex) according to the manufacturer's protocol. R1881  pLysS (Novagen) and purified from extracts using glutathione-sepharose 4 fast flow beads (Amersham Biosciences). MBP and MBP fusion proteins were expressed in E. coli DH5α and purified on amylose resin (New England Biolabs). In vitro translation and dilution of 35S-labeled proteins were performed as described for in vitro coimmunoprecipitation. GST or MBP bound to beads were added to the samples for 30 minutes at 4°C on a rotating wheel to remove unspecific binding. The supernatants were subsequently mixed with 1–2 µg of the indicated fusion proteins immobilized on beads and incubated at 4°C for 1 hour. After 5 times washing in NET-N buffer, the beads were resuspended in 2× SDS gel loading buffer and boiled for 5 minutes. If indicated, 10−7 M synthetic androgen R1881 was added to the reactions. The samples were separated on 10% SDS-PAGE gels together with a molecular weight marker (New England Biolabs #P7703S), stained with Coomassie brilliant blue (CBB) and vacuum dried. Signal from 35S-labeled proteins was detected with a Fujifilm bioimaging analyzer FUJI-BAS5000.GST and GST fusion proteins were expressed in PAX6 gene to be hypermethylated in prostate cancer cells Recent reports show Pax6 to be a repressor of AR activity We have previously found that the nuclear protein SPBP acts as a coactivator of Pax6 Chromatin immunoprecipitation assays were performed to investigate whether SPBP was recruited to the AR target promoter probasin, and if Pax6 could affect this recruitment. In order to obtain expression of the three proteins in the same cells, with varying amounts of Pax6, HeLa cells were cotransfected with the probasin-luciferase promoter construct and vectors expressing AR, SPBP and/or Pax6. The results presented in As shown in Together, these results show that SPBP acts as a potent transcriptional coactivator of AR, while Pax6 acts as a repressor inhibiting recruitment of SPBP to the AR target promoter and thereby reduces the SPBP-mediated enhancement of AR activity.To further evaluate the putative association among Pax6, SPBP and AR, their nuclear distribution patterns were investigated by confocal laser scanning microscopy. The mammary adenocarcinoma cell line GFP-AR 3108 stably expressing GFP-AR www.proteinatlas.org). This correlates well with the expression pattern of AR and several AR target genes such as PSA, Elk4 (Sap-1a) and the AR-coactivator LSD1 , the 180 amino acids long central part including the DBD and the hinge region , and the 239 amino acids long C-terminal LBD (C-term) . The GSTin vitro translated Pax6. Compared to the flanking regions, full-length Pax6 interacted strongly with the DBD of AR , the 90 amino acids long DBD, and the 52 amino acids hinge region . MBP fusSince SPBP is reported to interact with ERα and here is found to function as a coactivator of AR, we asked whether SPBP was able to associate with AR in cells. HeLa cells were transiently cotransfected with EGFP-AR and HA-SPBP expressing plasmids. An anti-GFP antibody was used to precipitate EGFP-tagged AR from cell lysates, and immunoblotting performed using an anti-SPBP antibody in vitro translated proteins   . InteresCentral) . Hence, The findings that coexpression of Pax6 repressed SPBP-mediated transactivation of AR activity, inhibited association of SPBP with an AR target promoter, and that both SPBP and Pax6 interacted with the same domain of AR, prompted us to investigate whether there could be a competition between Pax6 and SPBP for AR(DBD) binding. In an attempt to study this, MBP pulldown assays were performed with increasing amounts of SPBP(1333–1960) together with constant amounts of full length Pax6 and MBP-AR(DBD) immobilized on amylose resin. The 1333–1960 region of SPBP binds equally well to AR(DBD) as the full length protein (data not shown), and was therefore used in this assay to reduce the migration differences between Pax6 and SPBP. As shown in www.proteinatlas.org), and we show that overexpressed AR and SPBP have very similar nuclear distribution patterns in cells stimulated with androgen. Interestingly, 30% of the prostate cancer samples in the Human Protein Atlas (www.proteinatlas.org) display a significant enrichment of nuclear SPBP. Since coregulators of nuclear hormone receptors often have the ability to influence the activity of multiple receptors AR is critically dependent on recruitment of coactivators and corepressors for transcriptional regulation of its target genes. The differential interaction of AR with various cofactors appears to control the fine balance between proliferation and differentiation important for maintenance of the normal prostate. Changes in cofactor levels may shift the balance between suppressing or facilitating cancer progression  binding. Several AR coactivators are reported to interact with the AR(DBD)  were cotransfected with pDestHA-AR (375 ng), pDestHA-SPBP (1.5 µg), and pDestHA-Pax6 (250 ng), and stimulated with 10−7 M R1881. The cells were harvested in 2×SDS gel loading buffer approximately 20 hours after transfection, proteins separated by SDS-PAGE and visualized by Western Blotting using mouse anti-HA  antibody. Stars indicate unspecific bands.(TIF)Click here for additional data file.Figure S2The interaction between Pax6 and AR or SPBP and AR is not dependent on DNA. GST, GST-AR, and GST-AR(DBD) immobilized on glutathione sepharose beads were used to pull down in vitro translated 35S-labeled Pax6 (A) and SPBP (B) in the presence or absence of benzonase. The strength of the interactions is unaffected by removing DNA from the reactions.(TIF)Click here for additional data file.Figure S3Members from all subgroups of the Pax family interact with the central region of AR. GST and GST-AR immobilized on glutathione sepharose beads were used to pull down in vitro translated 35S-labeled members of the Pax family. The results show that all Pax proteins tested bind to the central region of AR.(TIF)Click here for additional data file.Table S1Plasmids used in this study.(DOC)Click here for additional data file.Table S2Oligonucleotides used in this study.(DOC)Click here for additional data file.