The Androgen Receptor (AR) is a key molecule in the development, maintenance and progression of prostate cancer (PC). However, the relationship between the AR and co-regulatory proteins that facilitate AR activity in castrate resistant settings remain understudied. Here we show that protein phosphatase 1 regulatory subunits, identified from a phosphatase RNAi screen, direct PP1 catalytic subunits to a varied yet significant response in AR function. As such, we have characterised the PP1β holoenzyme, myosin phosphatase (MLCP), as a novel ligand independent regulator of the AR. Sustained MLCP activity through down-regulation of the MLCP inhibitory subunit, PPP1R14C, results in impaired AR nuclear translocation, protein stability and transcriptional activity in distinct models of PC progression, culminating in restoration of a non-malignant prostate genotype. Phenotypically, a marked reduction in cell proliferation and migration, characterised by G1 cell cycle arrest is observed, confirming PP1 holoenzyme disruption as a novel treatment approach in PC. Androgen deprivation therapy (ADT), aimed at disrupting the androgen signalling axis, is initially successful [AR gene amplification [AR somatic mutations and emergence of receptor splice variants [Prostate cancer (PC) is the most common non-cutaneous cancer in males in western countries and is fast emerging as a significant health risk in the developing world, accounting for the second highest rate of cancer related deaths in men worldwide . Figure n = 3) on luciferase activity, used as a surrogate for AR activity . As previous research has implemented RNAi depletion or small molecule inhibition of the PP1 catalytic subunits in AR activity studies, eliminating the full repertoire of PP1 holoenzymes, we sought to characterise the individual roles of regulatory subunits on AR function. This approach would enable our research to elucidate the specific PP1 holoenzymes responsible for the observed impacts on AR activity.Post-translational modifications of the AR have been widely studied to investigate the functional interplay between the AR and co-activators or co-repressors for therapeutic benefit (reviewed ). HoweveWe evaluated the expression of PP1 regulatory subunits in publicly available prostate cancer datasets. Whilst evidence existed for inter-patient variation in the expression of the PP1 regulatory subunit cohort, it became apparent that two components of the PP1β holoenzyme MLCP were consistently dysregulated in multiple datasets analysed . Furthermore, no evidence arose to suggest alteration of additional nuclear hormone receptor activity, e.g. Glucocorticoid receptor. Interestingly, genes involved in cell cycle , in particular G1-S transition , were negatively enriched following PPP1R14C depletion. Confirmation of this impact by FACS analysis revealed that PPP1R14C depletion in LNCaP cells leads to significant G1 cell cycle arrest compared to the scrambled control .To gain a greater insight into the role of MLCP on AR signalling we obtained a global gene expression signature by performing RNA sequencing following PPP1R14C RNAi knockdown in the LNCaP cell line in the presence of 10 nM DHT Figure . Data ann = 200, NES -9.3259, p < 0.001), providing mechanistic evidence to support the G1 cell cycle arrest observed in Figure As previously established, depletion of PPP1R14C is capable of enhancing the activity of MLCP towards its substrates. Consistent with recent reports that MLCP is capable of dephosphorylating RB1 at the inhibitory phospho-residues serine 807 and serine 811 , 21, we As our previous studies have identified significant repression of AR transcriptional activity and G1 cell cycle arrest, we sought to further characterise the phenotypic impact of enhanced MLCP activity in distinct PC cell line models. To address this we measured cell growth, using live cell imaging, following manipulation of PPP1R14C expression Figure . ConsistRecent evidence has highlighted the continued benefit of targeting the AR in the treatment of PC under castrate resistant settings . HoweverOur key findings, schematically summarised in Figure james.grey2@ncl.ac.uk).Further information and requests for resources and reagents should be directed to and will be fulfilled by the Lead Contact, James Grey (All cells were maintained in RPMI-1640 (Sigma Aldrich) supplemented with 10% (v/v) foetal bovine serum (Sigma Aldrich) and 2 mM L-glutamine (Sigma Aldrich) at 37°C. For steroid-depleted conditions, cells were grown in RPMI-1640 supplemented with 10% (v/v) dextran-coated charcoal-stripped foetal bovine serum (HyClone) and 2 mM L-glutamine. LNCaP-EnzR cells were maintained in the presence of 10 mM enzalutamide.Using an automated robot , 3 independent RNAi oligos targeting 291 phosphatases and 15 control targets were aliquoted into 96 well plates with a final RNAi concentration of 25 nM and stored at –80°C. Prior to the reverse transfection of cells, RNA iMAX (Invitrogen) was incubated with the RNAi for 30 minutes. Then, 5000 LNCaP-PSALuc in DCC media were added to the plates and cultured for 24 hours prior to the addition of 1 mM DHT. Following 48 hours DHT stimulation, 25 µl luciferin reagent  was added to each well prior to luminescence quantification using a FLUOstar Omega plate reader (BMG Labtech). RNAi depletion of each phosphatase target was performed in triplicate, with subsequent target identification validated by qPCR analysis.Transient RNAi transfections were carried out using RNA iMAX (Invitrogen) according to manufacturer’s protocol for a total of 72 hours. RNA was then extracted as previously described , quantifCell lysis and western blot analysis was performed as previously described .n = 3). Flow cytometry was employed to investigate the cell cycle profile of LNCaP cells. Cells were depleted of PPP1R14C for 72 hours prior to preparation and staining with propridium iodide as previously described [Cell confluency was measured using the Incucyte Zoom live cell imager (Essen Bioscience) as a surrogate for cell growth over a 96-hour period. Images were collected from various fields every 4 hours, with subsequent confluency data normalised to 0-hour time-point and presented as fold-change. Boyden chamber assays were employed to investigate cell migration as previously described  followinescribed . Propridn = 3). RNA samples were prepared using Stranded Total RNA Sample Prep Kit (Illumina), depleted of ribosomal RNA using the Ribozero Gold Kit (Illumina) and sequenced with 100 bp paired end reads (∼80 million reads/sample) on an Illumina HiSeq 2500 platform. Reads were mapped to human genome hg19 using STAR [LNCaP cells were subject to PPP1R14C RNAi depletion as previously described for a total of 72 hours, including a 24 hour 10 nM DHT stimulation following a 48-hour incubation in steroid depleted conditions. RNA was extracted with RNeasy Plus Kit extraction columns (Qiagen) and quantified with a Nanodrop (ThermoFisher). RNA integrity was calculated through the use of a 2100 Bioanalyzer (Agilent Technologies). Only samples possessing a RIN value > 9 were taken forwarded for  sequenciing STAR . Raw reaing STAR  prior toStatistical analysis was performed using GraphPad Prism V7.0. Unless otherwise specified, data are presented as mean ± SEM. Comparisons were performed with the stated statistical tests whose values are represented in the figure legends.siPPP1R14C RNAseq data to be deposited in GEO. All key resources including qPCR sequences, antibodies, RNAi sequences and small molecule reagents can be found in the


Several pathologies such as neurodegeneration and cancer are associated with aging, which is affected by many genetic and environmental factors. Healthy aging conceives human longevity, possibly due to carrying the defensive genes. For instance, FOXO (forkhead box O) genes determine human longevity. FOXO transcription factors are involved in the regulation of longevity phenomenon via insulin and insulin-like growth factor signaling. Only one FOXO gene (FOXO DAF-16) exists in invertebrates, while four FOXO genes, that is, FOXO1, FOXO3, FOXO4, and FOXO6 are found in mammals. These four transcription factors are involved in the multiple cellular pathways, which regulate growth, stress resistance, metabolism, cellular differentiation, and apoptosis in mammals. However, the accurate mode of longevity by FOXO factors is unclear until now. This article describes briefly the existing knowledge that is related to the role of FOXO factors in human longevity. Aging is related to the age-dependent impaired functioning of the cells, tissues, organs, and organ systems , 2. ThisHealthy aging is a complex phenotype and an interplay of genetic and environmental factors such as food, exercise, and habits , 6. HoweSince health status affects the lifespan, the development of chronic diseases is delayed in the long-lived individuals –9. TheseAs observed in an animal study, the first ever documented mode of aging was deregulated nutrient sensing that involved the insulin and insulin-like growth factor- (IGF-) 1 signaling (IIS) pathway . In IIS Caenorhabditis elegans (C. elegans) to mammals; only one FOXO gene exists in the invertebrates while mammals have 4 FOXO genes, FOXO1, FOXO3, FOXO4, and FOXO6 [The IIS pathway is highly influenced by the FOXO proteins , 28. Fornd FOXO6 , 33, 34.nd FOXO6 . FOXO1, nd FOXO6 . These fnd FOXO6 , 37–40. FOXO proteins act as transcription activators and are suppressed by the IIS pathway , 37–40. The genes which mediate the intracellular clearance through autophagy and the ubiquitin-proteasome system are also regulated by FOXO factors , 44, 45;Antioxidant role of FOXO is its most crucial function. Since reactive oxygen species (ROS) produce conserved deteriorating effect on cells and induce aging, FOXOs could be used to influence aging by ameliorating the antioxidant potential of cells , 61. ROSFOXO factors are known to be involved in stem cell biology. Aging is characterized with disequilibrium between removal and regeneration of cells in tissues, since the regeneration capability of adult stem cells is decreased with aging. Knockout hematopoietic stem cell (HSC) mice (mice with FOXO1/3/4-deficient hematopoietic stem cells) showed apoptosis of HSCs as well as termination of repopulation of HSCs. Likewise, FOXO3-deficient mice illustrated the reduced potential of regeneration of cells . The delThis review article narrates a summary of the prevalent knowledge that is associated to the role of FOXO factors in extending human lifespan. Until now, no study describes the exact mode of action of FOXOs in human aging. However, some studies on various populations narrate the possible role of FOXO factors in human longevity.The older the age, larger is the contribution of genetics in lifespan stating genetics as a function of human longevity. Thus, genetics is the basic parameter that discriminates the average-lived population from the centenarians , 71, 72.First study of this type narrated the association of human longevity with FOXO3A . This stSubsequently, same association was found in male centenarians from Italy , GermanyIn other study, two SNPs from FOXO1A (rs2755209 and rs2755213) and three from FOXO3A  were analyzed in Chinese centenarians . All theThe combined effect of FOXO3A and APOE on long-term living has also been reported , 16, 82.Network pharmacology is a multidisciplinary field that integrates different scientific concepts such as systems biology, cheminformatics, and bioinformatics to explore various novel bioactivities from network-based analysis. For instance, network pharmacology helps us to study gene characteristics and its functions , identifhttp://stitch.embl.de/) [https://doi.org/10.1155/2017/3494289). These protein targets were fetched into Cytoscape, and protein-protein interaction network was constructed to visualize the functionality-associated genes. The functional enrichment analysis was conducted by using the gene ontology terms (GO terms) for annotation of the biological functions of FOXO-related targets. Subsequently, Cytoscape plug-in ClueGO [STITCH 4.0 database (mbl.de/)  has beenn ClueGO  was utiln ClueGO . It leadn ClueGO . It resun ClueGO . The inin ClueGO , 93. MorFOXO3 probably induces apoptosis either upregulating the genes needed for cell death  or downrFOXO4 is involved in the regulation of various pathways associated to apoptosis, longevity, cell cycle, oxidative stress, and insulin signaling. FOXO4 are associated with longevity through IIS pathway , 99. FinIn current years, the rigorous research attention has been focused on the role of FOXO transcription factors in human longevity. In different animal models, numerous studies have been conducted to investigate the signaling pathways involved in the regulation of the FOXO factors. Moreover, the effect of FOXO-mediated processes on the cellular, tissue, or organism level functions has also been discussed. As a result, a pleiotropic nature of FOXOs' effect on longevity is established, since FOXOs participate in a number of cellular functions, including growth, stress resistance, metabolism, cellular differentiation, and apoptosis. From the above discussion, numerous strategies for future research can be predicted. For instance, the triggering of FOXO-mediated processes in the tissues with metabolically different features can be valuable to explore the mechanism of FOXO-mediated longevity. In addition, the human FOXO sequence variations and their effect on the resulting proteins should be studied, the possible findings can also reveal the underlying mechanisms of FOXO-induced health aging. The delay in age-related pathologies including cancer and neurodegenerative diseases and living long life depends on the control of morbidity. It is therefore an exciting area of study to investigate the antiaging compounds; however, their testing in clinical setup would need age markers to assess aging rate. Owing to the potential effect of FOXOs on health issues, the future therapies could be based on the FOXOs.Figure 3. Confidence view of the protein networks of FOXO1, FOXO3, FOXO4 and FOXO6. Thick lines indicate stronger associations. Grey and green lines represent the protein-protein. SIRT1 - Sirtuin 1; AKT1 - v-akt murine thymoma viral oncogene homolog 1; AKT2 - v-akt murine thymoma viral oncogene homolog 2; AKT3 - v-akt murine thymoma viral oncogene homolog 3; BCL2L11 - BCL2-like 11; CDK2 - Cyclin-dependent kinase 2; CDKN1A - Cyclin-dependent kinase inhibitor 1A; CDKN1B - Cyclin-dependent kinase inhibitor 1B; CREBBP - CREB binding protein; CTNNB1 - Catenin (cadherin-associated protein), beta 1; FHL2 - Four and a half LIM domains 2; EP300 - E1A binding protein p300; GADD45A - Growth arrest and DNA-damage-inducible, alpha; IKBKB - Inhibitor of kappa light polypeptide gene enhancer in B-cells; INS – Insulin; MAPK8 - Mitogen-activated protein kinase 8; SGK1 - Serum/glucocorticoid regulated kinase 1 (526 aa); SGK2 - Serum/glucocorticoid regulated kinase 2; SGK3 - Serum/glucocorticoid regulated kinase family, member 3; SMAD2 - SMAD family member 2; SMAD3 - SMAD family member 3; SMAD4 - SMAD family member 4; STK4 - Serine/threonine kinase 4; PRKAA2 - Protein kinase, AMP-activated, alpha 2 catalytic subunit; YWHAZ - Tyrosine 3-monooxygenase/tryptophan 5-monooxygenase activation protein, zeta polypeptide and USP7 - Ubiquitin specific peptidase 7. Table 1. Protein-protein network stats. Figure 4. Organic layout algorithm of functionally grouped networks produced through ClueGO analysis to predict the potential targets of FOXO1, FOXO3, FOXO4 and FOXO6. Each group comprises of the most significant terms only. The overlapped groups indicates their functional likeness. Table 2. GO terms and their associated genes.


Schizophrenia (SZ) and bipolar disorder (BP) have both common and distinct clinical symptomatology. Their neural bases have been explored using functional connectivity between brain regions using resting-state functional magnetic resonance imaging (rs-fMRI). However, fMRI is an indirect measure of neural activity and is modeled as a convolution of the hemodynamic response function (HRF) and latent neural activity. The HRF varies across both individuals and different brain regions within an individual. Consequently, it is plausible for two brain regions to appear synchronized in the BOLD space while being desynchronized in latent neural space and vice versa.In order to address this issue, we estimated voxel-specific HRFs by deconvolving rs-fMRI time series obtained from SZ (N=19), BP (N=35) and matched healthy individuals (N=34). The shape of the HRF was significantly different between the three groups in many regions previously implicated in SZ and BP. Specifically, we found voxels within the mediodorsal, habenular and central lateral nuclei of the thalamus to have HRFs with aberrations in all three of its shape parameters: time to peak, response height and full width half max. Therefore, we defined this region as the seed, estimated seed-based functional connectivity maps in all three groups and characterized pairwise differences between them. Further, we performed a 2-way ANOVA and estimated regions exhibiting an interaction between the group and deconvolution factors.We found voxels within the mediodorsal, habenular and central lateral nuclei of the thalamus to have HRFs with aberrations in all three of its shape parameters: time to peak, response height and full width half max. Results indicated that functional connectivity differences between the groups are inferred significantly differently with raw BOLD and deconvolved latent neural time series. Since the variability of the HRF could be driven by both neural and non-neural factors, we feel that it is preferable to estimate functional connectivity using deconvolved data.Neurochemicals such as GABA, glutamate, serotonin and nitric oxide have a role in controlling neurosignaling pathways underlying neurovascular coupling and hence the HRF. Previously documented alterations of these neurochemicals in SZ and BP could, at least in part, explain the significant differences in HRF shapes observed between the groups. Functional connectivity group differences obtained from raw BOLD data must be interpreted cautiously in the light of systematic HRF differences between groups.


In addition, the expression and activity of XDH were associated with the expression of CSC-related genes, such as CD44 or CD133, in HCC cells. These data suggest that downregulated XDH expression may be a useful clinical indicator and contribute to the development and progression of HCC.Xanthine dehydrogenase (XDH), a rate-limiting enzyme involved in purine metabolism, has an essential role in inflammatory cascades. Researchers have known for decades that XDH activity is decreased in some cancers, including hepatocellular carcinoma (HCC). However, the role of XDH in cancer pathogenesis has not been fully explored. In this study, we showed that low XDH mRNA levels were correlated with higher tumor stages and poorer prognoses in patients with HCC. Knocking down or inhibiting XDH promoted migration and invasion but not proliferation of HCC cells. The abovementioned phenotypic changes are dependent on increases in epithelial-mesenchymal transition marker gene expression and transforming growth factor-β-Smad2/3 signaling activity in HCC. XDH overexpression suppressed HCC cell invasion  However, the molecular mechanisms underlying HCC development and progression, including metastasis,5 in affected patients have not been fully elucidated. Xanthine dehydrogenase (XDH), a rate-limiting enzyme involved in purine metabolism,9 also functions as a key regulator of inflammatory cascades.10 XDH activation can produce abundant reactive oxygen or nitrogen species, which may induce DNA damage and carcinogenesis13 and promote metastasis.14 XDH-derived oxidative stress or uric acid regulates multiple intracellular signals,8 such as nuclear factor-kappaB,16 hypoxia-inducible factor-α and peroxisome proliferator-activated receptor gamma.17 XDH activity is upregulated in the liver during postnatal growth and in the breast during pregnancy and lactation, suggesting it may be a marker of differentiation for liver and mammary epithelial cells.8 In contrast to high levels in non-cancerous livers,19 decreased XDH activity is believed to confer hepatic cancer cells with selective advantages that are independent of growth rates and degrees of neoplastic histological differentiation.19 Indeed, significant decreases in XDH activity levels have been reported to be useful predictors of poor patient prognoses in cancers,8 including breast cancer,20 gastric cancer,21 ovarian cancer,22 non-small cell lung cancer23 and colorectal cancer.24 These poor patient prognoses are believed to involve increased COX-2 (cyclooxygenase-2)20 and matrix metalloprotease (MMP)-1/-3 expression.25 Despite these intriguing findings, how decreases in XDH activity or expression contribute to the development and progression of cancers, including HCC, remains poorly understood.Hepatocellular carcinoma (HCC), an inflammation-associated malignancy,26 and diabetic patients.27 Knocking out the XDH gene in mice increased kidney tissue fibrosis and upregulated transforming growth factor-β (TGFβ) and epithelial-mesenchymal transition (EMT) gene expression levels.28 The results of these studies suggested that XDH loss may be linked to TGFβ signaling pathway activity.29 Indeed, the TGFβ signaling pathway30 can increase COX-2 and MMP expression35 and promote HCC invasion and progression by inducing EMT and cancer stem cell (CSC) expression.37 Moreover, therapies targeting TGFβ signaling appear to be promising in the treatment of HCC.2 However, whether XDH deficiency induces TGFβ pathway activity, thereby promoting EMT or CSC marker gene expression in HCC, is unknown.Interestingly, XDH inhibition promotes skin wound healing in healthy individualsIn the present study, we reported that low XDH expression levels are an unfavorable clinical indicator in patients with HCC. Knocking down or inhibiting XDH resulted in TGFβ signaling pathway-dependent cell migration and invasion caused by EMT-related gene upregulation in HCC cell lines. We also found that the expression levels of CSC-related genes can be altered by the interruption of XDH expression in HCC. These data may improve our understanding of the role of XDH in the development and progression of HCC, as well as other cancers with low XDH expression or activity levels.XDH mRNA expression abundance in HCC patient samples deposited in public databases, including the Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus. As shown in XDH mRNA levels were observed in patients with liver cancer, particularly patients with advanced liver cancer (GSE6764),38 than those in healthy controls. XDH transcript levels were negatively correlated with tumor stages in HCC  showed lower protein levels than adjacent non-cancerous tissue  from TCGA LIHC. Interestingly, the mRNA expression levels of XDH were inversely correlated with the expression levels of all the genes in question . There were no signs of mycoplasma contamination in all cell lines.The indicated human HCC cell lines  were maintained in either Dulbecco’s modified Eagle’s medium  or minimum essential medium  supplemented with 10% fetal bovine serum , 100 units/ml penicillin and 100 μg/ml streptomycin at 37 °C with 5% CO52 In brief, the abovementioned cells were seeded in 96-well culture plates at a density of 2000 cells/well. To evaluate the effects of oxypurinol , a potent xanthine oxidase inhibitor,53 on cell proliferation, we incubated the cells with or without 50 μmol/l (μM) oxypurinol. Cell proliferation was monitored over a 72-h time period and measured according to the manufacturer’s instruction. All experiments were performed at least three times and in triplicate.A WST-1 Cell Proliferation and Cytotoxicity Assay Kit  was used to detect HCC cell proliferation, as described in our previous report.MHCC97H cells were transfected with an EX-Mm05336-Lv201 plasmid  encapsulated in Lipofectamine 3000 Reagent , according to a corresponding transfection protocol, to induce XDH overexpression or a pEZ-Lv201 control vector, which served as a negative control. Similarly, HepG2 cells were transfected with shRNA against XDH to knockdown XDH expression (shXDH) or control shRNA in a lentiviral vector . Stably transfected cells were selected using 1–2 μg/ml puromycin  for 2 weeks.M oxypurinol, 2 mM GW788388 , 100 nM pirfenidone  or 5 ng/ml recombinant human TGFβ1  for 48 h. Coverage percentages were determined by quantifying the open wound area percentages using CellSens microscope imaging software . For transwell invasion assays, the cells (3.0–5.0 × 105 per well) were suspended in medium without serum and seeded on 8-μm membrane inserts pre-coated with basement membrane extract . The inserts were placed in wells with complete Dulbecco’s modified Eagle’s medium containing 10% fetal bovine serum, which served as a chemoattractant. After 24–48 h, the inserts were removed, washed with phosphate-buffered saline, fixed in methanol and then stained with crystal violet (0.05% w/v in methanol). The bottom surfaces of the stained inserts were subsequently observed under a light microscope, and the numbers of stained cells were counted in five fields/insert.For scratch assays, the cells were seeded in six-well plates with regular media. Serum-free media were used to avoid the confounding effects of proliferation on the results of the assay. A single scratch was made on the cell surface within each well using the tip of a sterile 200-μl pipette tip, after which the cells were washed with phosphate-buffered saline and cultured in regular media with 10% fetal bovine serum in the presence or absence of 50 μet al.54 and Wang F et al.,55 respectively. In brief, the nude mice were injected with 8 × 105 MHCC97H cells stably overexpressing XDH or control vectors in 0.2 ml of phosphate-buffered saline via the lateral tail vein (n = 8 per group). Mice were randomized into the control vector group or XDH overexpression group. After 5 weeks, all the mice were sacrificed. Their lung tissues were dissected and fixed in 10% formalin for at least 24 h. The number of tumor colonies in each hematoxylin and eosin-stained lung tissue specimen was determined using a dissecting microscope. To evaluate in vivo tumor growth, we subcutaneously injected 8 × 106 MHCC97H cells transfected with XDH-overexpression plasmids or control vectors in 0.2 ml of phosphate-buffered saline into the left or right flanks of nude mice (n = 8 per group). These mice were sacrificed at 3 weeks post injection. The volumes of the subcutaneous tumors were blindly measured and calculated using the equation length × width × width/2. All animal experiments were approved by the Animal Care and Use Committee of Minhang Hospital, Fudan University, Shanghai.Male BALBc/nu mice (5 weeks old) were purchased from SLAC  and maintained in a specific pathogen-free environment at 25 °C under a 12-h light/dark cycle. No statistical methods were used to estimate sample size. The procedures used for the intravenous and subcutaneous injections were described previously by Zhang Y 6 cells) were homogenized on ice using a Dounce homogenizer and treated with four volumes of assay buffer. The cells were subsequently centrifuged, and the supernatant was collected for xanthine oxidase activity measurements, according to the manufacturer’s instructions.A Xanthine Oxidase Assay Kit  was used to detect XDH activity in HCC cells after oxypurinol treatment or stable XDH knockdown. In brief, the HCC cells  were separated by 10% sodium dodecyl sulfate–polyacrylamide gel electrophoresis. The resolved proteins were transferred to 0.2-μm polyvinylidene difluoride membranes, which were subsequently immersed in Quickblock blocking buffer  for 0.5–1 h at room temperature. The membranes were then incubated with the appropriate primary antibodies  at a 1:200 dilution. Images were acquired using a Nikon Eclipse 80i microscope equipped with a Sony DXC-390 P digital camera and NIS-Elements BR2.2 software.The immunohistochemical staining procedure was performed as previously described.z-scores) were retrieved from liver HCC data sets (LIHC)  in the TCGA database using the UCSC Cancer Genomics Browser54 or the cBioPortal for Cancer Genomics.58 Data pertaining to XDH expression abundance, which was found in the Gene Expression Omnibus data sets (GSE6764),38 were downloaded from the web-accessible Gene Expression across Normal and Tumor tissue (GENT) database.59 The EMT score was calculated by determining the difference between the expression levels of well-known mesenchymal marker genes and the total expression levels of known epithelial genes.39Liver cancer gene expression data . All graphs were generated, and all statistical analyses were performed using Prism software . For all analyses, P<0.05 was considered statistically significant .All results are presented as the mean±s.e.m. Statistical significance was determined using unpaired Student’s


This study describes an approach to quantification of attacking performance in football. Our procedure determines a quantitative representation of the probability of a goal being scored for every point in time at which a player is in possession of the ball–we refer to this as dangerousity. The calculation is based on the spatial constellation of the player and the ball, and comprises four components: (1) Zone describes the danger of a goal being scored from the position of the player on the ball, (2) Control stands for the extent to which the player can implement his tactical intention on the basis of the ball dynamics, (3) Pressure represents the possibility that the defending team prevent the player from completing an action with the ball and (4) Density is the chance of being able to defend the ball after the action. Other metrics can be derived from dangerousity by means of which questions relating to analysis of the play can be answered. Action Value represents the extent to which the player can make a situation more dangerous through his possession of the ball. Performance quantifies the number and quality of the attacks by a team over a period of time, while Dominance describes the difference in performance between teams. The evaluation uses the correlation between probability of winning the match (derived from betting odds) and performance indicators, and indicates that among Goal difference (r = .55), difference in Shots on Goal (r = .58), difference in Passing Accuracy (r = .56), Tackling Rate (r = .24) Ball Possession (r = .71) and Dominance (r = .82), the latter makes the largest contribution to explaining the skill of teams. We use these metrics to analyse individual actions in a match, to describe passages of play, and to characterise the performance and efficiency of teams over the season. For future studies, they provide a criterion that does not depend on chance or results to investigate the influence of central events in a match, various playing systems or tactical group concepts on success. The availability of virtually all-encompassing positional data in professional football presents new challenges for the way in which that data is analysed and interpreted. They relate equally to analysis of games in clubs, product design for reporting in the mass media, and new analytical procedures for addressing academic questions. A significant factor in this context comprises the description of the technical-tactical aspects of the events of a match by means of performance indicators . AlthougRecent years have seen an increasing number of publications that report successes in identifying tactical structures. Grunz, Memmert and Perl  use selfThis paper suggests a solution to a question that has largely been unresolved to date, namely: How can success in football be quantified? Until now, there has been no convincing procedure available by means of which the value of a piece of dribbling can be compared with a pass, or various passing options compared with one another. If a coach wants to know whether a change in defensive midfield has led to greater stability in defence, he has not so far had any quantitative criterion that would allow such an assessment. Conclusions about the general success of tactical measures against an opponent who is sitting deep, for example, also require a yardstick by which “more successful” can be measured.When we use the term “success” in the sense of performance analytics, we are not referring to the outcome of the game. Goals are scored only rarely in football, and can come about through an individual moment of loss of concentration, while a very dominant team might simply be unlucky sometimes. Rather, in order to answer the question posed above, a criterion is required that allows an evaluation of the extent to which tactical objectives were achieved. We believe that creation of situations in which there is a danger of a goal being scored or the prevention of such situations for the opponent, should be the central criterion in characterising tactical success, or “performance” in football. Shots on goal may be a better criterion than goals in this context, although they may arise in situations that are not dangerous or a player may be prevented from shooting just a few metres in front of goal. In the semi-final of the 2014 World Cup, for example, Brazil had more shots on goal than Germany (18 vs. 14) , but harDangerousity. We calculate this value for every moment during which a player is on the ball. Dangerousity is related to the construct “scoring opportunity”, but its quality is not evaluated by guesswork but by a defined process using an algorithm. Additionally, we derive other metrics from dangerousity by means of which questions relating to analysis of the play can be answered. Action Value represents the extent to which the player can make a situation more dangerous through his possession of the ball. Performance quantifies the number and quality of the attacks by a team over a period of time, while Dominance describes the difference in performance between teams.Therefore, our approach to describing success does not use events but a quantitative representation of the probability of a goal, which we describe as Zone of the ball, (2) the degree of Ball Control, (3) the Pressure that is put on the player by the opponent and (4) the Density of opponent players in front of the goal. While there are other factors, we suggest that these four components are the key indicators. To operationalize these indicators, we use mathematical functions which take spatiotemporal data as their input. We choose their functional form in a way that fulfils our analytical understanding of the game (e.g. a defender behind an attacker creates less pressure compared to a defender in front of the attacker).Our modelling procedure follows the paradigms of rationalism and deduction rather than empiricism and induction . In otheexpected position value (EPV) or an expected goal value (EGV). The approach in football determines this value on the basis of position, distance from defenders and the match context . In contrast to our procedure, which takes account of all match situations at a distance of less than 34 m from the opponent’s goal line, in EGV calculations, only the last 10 seconds before shots on goal are considered. The procedure is also based on a less explicit modelling of the individual components that make up the danger of a goal being scored. It is also worth mentioning that the company ProZone markets a construct of dangerousity [To date there have been two similar approaches in basketball  and in ferousity , but detThe aim of this paper is threefold: Firstly, it shows, how dangerousity and derived metrics are quantified. Some details of the specification are left to one side; instead, the focus is on the underlying ideas and relationships. Secondly, an evaluation of the quality of the quantification is carried out, together with the quantitative evidence for the construct’s relevance to performance. In the view of the authors, these components of validation, in particular, are not sufficiently documented by many competition information providers (CIP) even though they represent a central component in the development of performance indicators in sports. To our knowledge, this paper is the first to use the correlation with betting odds as a criterion for the relevance of performance indicators. Thirdly, the paper shows examples of how the metrics developed can be used to answer questions relating to analysis of a match with different time horizons.Dangerousity (DA) is present for every moment in which a player is in possession of the ball—and can therefore complete an action with the ball. We refer to this time span as Individual Ball Action (IBA) and to the player concerned as the IBA-player. IBA exists as soon as the distance between the player and the ball falls below a threshold and the ball is then touched. IBA ends when the ball is out of the player’s range once again. The procedure is described in detail in Hoernig, Link, Herrmann, Radig, and Lames [nd Lames .Zone (ZO), Control (CO), Pressure (PR) and Density (DE), where the first two components increase and the last two components decrease its value. Zone represents the danger of a goal being scored from the position of the IBA-player, Control stands for the extent to which the player can implement his tactical intention on the basis of the ball dynamics, Pressure represents the opportunity of the defending team to prevent the IBA-player from completing an action with the ball and Density is the chance of being able to defend the ball after the action. The value range for all of the constructs is between 0 (low) and 1 (high).Dangerousity is based on the four components 1 quantifies the extent to which these three figures reduce the value for Zone. It is selected in such a way that Zone is reduced by a maximum of a factor of 0.5. As a lack of control of the ball results in a reduction in the Dangerousity, Control is included as negated.These individual components give the Dangerousity for a moment t as the product of Zone and a linear combination of Control, Pressure and Density . The modQuantification of Zone is carried out using the position of the IBA-player on a 2 x 2 m grid that begins 34 m from the goal line . Our evarel) of ball and IBA-player in the last 0.5 s. High relative speeds occur, for example, when the player shoots on goal with just brief contact with the ball after a cross. Comparatively low relative speeds are found when the player has the ball at his feet for a longer period, when dribbling, for example, or positioning the ball for a shot on goal. We believe that at relative low relative speeds, there is an almost perfect CO near a value of 1. With increasing vrel, it gets more and more difficult to control the ball. We model this by using a quadratic function, moderated by the model constant k2  exerts pressure when his distance (dD) from the IBA-player (P) is below a threshold value rZO. The Pressure Zone (PZ) covers four sub-areas with different radii (rZO), which result from the angle (α) between IBA-player and the centre of the goal (i) creates Pressure (PRDi) in accordance with  represents the probability of a team blocking a shot, while Pass Density (PD) indicates the likelihood of intercepting an offensive pass or cross. Depending on the Centrality (C) of the IBA-player, the two components are weighted differently (Density is described by means of two components: ferently . At an aBlocking Zone (BZ) formed between the position of the IBA-player and the goal  and between the IBA-player and the defender (dDi). The smaller dDi is, the higher the density created by that player because a larger area of the goal is potentially covered. For a defender (Di), the SDDi created by him is given by . We call this difference Majority (M). For example, if there are 4 defenders and 3 attackers in the IZ, M is equal to 1   . For calPerformance (PE), of a team over a longer period, the match is divided into intervals of 5 s in length and the maximum value for DA is determined for both teams over an interval i (DAi). Performance is then given by the sum of this value for all intervals over the period (ts), as Match Performance (MP), for example (Current Performance (CP) in order to describe the course of play over a time interval. We determine this for a moment t using past values for DAi in the intervals of the last 5 minutes.In order to assess the success of the attack, which we call  example . This diDominance (DO) describes the difference in performance between the two teams . This can be calculated both over a time interval as Match Dominance (MD), for example, and for a moment as Current Dominance (CD). In both cases, this is provided by the difference in the Performance of the two teams .The calibration processes intended to optimizes the model constants kIn balancing complexity, the accuracy of the positional data and the benefit for performance diagnostics, the procedure presented here does not take account of all aspects of dangerousity. These include the movement dynamics of the players and the ball, the direction in which the players are looking, their position in relation to the ball, the extent to which teammates are available ,20 and dThis paper is based on 64 games in the German National Football League (Bundesliga) in the 2014/15 season. The positional data was collected by a CIP (TRACAB corp.) via an optical tracking system and then reviewed manually. Since each player agreed to this procedure on signing his contract of employment as a professional football player, special approval for this study from an ethics committee was not required. Nevertheless, all procedures performed in the study were in strict accordance with the Declaration of Helsinki as well as with the ethical standards of the Chair of Training Science and Sports Informatics of the Technical University of Munich.Danger Groups (DG) following their assessments by the majority principle and checked for differences using an ANOVA.In assessing the quality of the quantification, the automatic calculation of dangerousity was compared with the evaluation by semi-professional football coaches in 100 match scenarios. The sample was selected in such a way that the value range of DA was covered evenly. Three experts evaluated the scenarios independently of one another on the basis of video recordings using a scale of 1 (little danger) to 5 (very dangerous). They had no knowledge of the underlying model, but were asked to evaluate the scenarios qualitatively in their entirety. For the statistical analysis, we grouped the situations into The results show that the mean value for DA differed significantly between the groups  . All of The crucial criterion for the quality of a performance indicator is that it depicts an issue that describes an important component in the performance of a sport. This is usually checked in the performance analysis in two different ways. One possibility is to determine its capacity to forecast the outcome of a match ,23. SincGoal (G), Shot at Goal (SG), Passing Accuracy (PA), Tackling Rate (TR), Ball Possession (BP) and Match Dominance (MD) were collected. G, SG and PA represent the difference in the variable value from that of the opponent; the remaining variables already represent relative values between the teams. As an external criterion for the difference in performance between the teams, the Win Probability (WP) of a team was used, based on the odds from 13 bookmakers . In the statistical analysis, the correlation coefficients for all the pairs of variables were calculated.For the matches in the sample, the variables The highest correlation between WP and the performance indicators exists with MD (r = .82), followed by BP, SG, PA, G and TR . Of the Other evidence of validity emerges from the correlation of performance indicators with one another. Here the results seem entirely plausible: Shots on goal are completed mainly in situations with a high dangerousity, so there is a strong correlation between MD and SG (r = .83). As Dangerousity presupposes possession of the ball, MD and BP also show a strong correlation (r = .76). Possession of the ball and passing accuracy are almost entirely identical (r = .92). This is easy to understand because a poor pass leads directly to the loss of the ball.A possible application at the micro level is the analysis of small sections of game situations. As dangerousity is calculated for every frame, the value changes continuously during an IBA interval. Key situations such as outplaying an opponent in an important duel or a successful pass through the defensive line cause a big jump in DA, while periods without gaining ground lead to an even signal sequence. This can be illustrated by an attack by Bayern Munich (FCB) against TSG 1899 Hoffenheim from the Saison 2014/2015 .1, there are three realistic play options for Robben, apart from continuing to dribble. The pass options to Müller (no. 25) and Lewandowski would be evaluated almost equally by the Action Value (AVIBA_1 = .44 and .42), assuming that the spatial configuration does not change significantly, while the back pass to Thiago (no. 6) would result in a negative evaluation (AVIBA_1 = .19). Robben decides to pass to Lewandowski and gets the ball straight back from the player (AVIBA_2 = .14). After contact with the ball to take possession of it, DA increase to its maximum value in this scenario (DA = .81). There is then a stand-alone shot on goal by Robben, but from a relatively acute angle in front of the goalkeeper.The attack comprises three IBA intervals by the players Robben (no. 10), Lewandowski (no. 9) and Robben again. At the moment when Robben takes possession of the ball, there is moderate dangerousity (DA = .22). The player begins to dribble against defender Beck (no. 23) and he succeeds in beating his opponent. This results in a reduction in PR, as Beck falls back from the High Pressure Zone into the Hind Zone. At the same time, ZO increases because of the shorter distance to the goal. At the end of IBAThe diagnostic benefit in terms of performance of this analysis lies less in the evaluation of the playing behaviour in individual scenarios. This would require a multitude of other factors to be taken into consideration, such as movement dynamics, passing risk and individual skills, which could only be derived from a qualitative analysis of the film material. By contrast, it would be possible to evaluate the contribution of a player to the attacking play of his team over a longer period. It is possible that players will thus be identified who, although they have a lot of contact with the ball, contribute only little to increasing dangerousity in attacking phases.The key application for the game analysis lies in filtering video material on the basis of dangerousity. Sudden increases can be understood as disruptions or perturbations in the balance between defence and attack in line with the theory of dynamic systems ,27. The Traditional match statistics provide inadequate information to assess the course of a match correctly ,14. As aMatch 1  providesth match day. With the metrics, we manually identified eight key phases (P). Until the first goal is scored , the play can be described as very even (0 – 20th min). Then a phase of dominance (20th - 36th min) began for H96, during which they took the score to 1:1 (25th min). Between the 36th and 42nd minutes, BVB managed only the occasional attack. In the last 4 min of the first half, H96 clearly dominates play but without scoring another goal.Using the metrics Current Performance and Current Dominance, success can be assessed not only for a complete match, but also for periods of time. In this way, the effects of tactical interventions  or central events in a match can be investigated, for example. th- 57th min), play was very even up to the sending-off for H96 (55th min), with a slight advantage to H96. The dominant phase for BVB (57th-76th min) began between their second goal  and their third . This may have been the result of their superiority in numbers and/or psychological elements. This phase ended around 15 minutes before the end of the match. After conceding their second goal , BVB recorded no further successful attacks and obviously attempted to play out time. H96 was able to create a further series of dangerous plays, but without levelling the score. If dominance is considered over the two halves, it is clear that the home team was dominant after the first half (DO = 90), while the away team had the advantage in the second half (DO = -41).At the start of the second half  over a large number of matches and to put these in the context of the other teams. This is a good starting point for describing team efficiency, which can be defined as the relation between points achieved and the dominance. This allows to answer the question of the extent to which the examples of lucky victories shown in st quadrant there are teams that both dominated in matches and have had above-average success. Teams in the 2nd quadrant dominated but were less successful. Similarly, the subordinate teams in terms of play can be divided into successful (3rd quadrant) and unsuccessful (4th quadrant).Even though we have only 64 matches at our disposal for our study, the principle of the procedure can be illustrated in If one interprets the main diagonal as the number of points expected for the level of dominance, the horizontal distance of a team from this diagonal can be understood as the discrepancy between effort and success. A position above the main diagonal indicates an unfavourable ratio of dominance to success, a position below it a positive ratio. In other words, the teams below the diagonal were quite efficient, the teams above were not. In the matches examined, for example, the teams from Dortmund (BVB) and Hanover (H96) were significantly less successful than they “deserved” to be based on their dominance. Berlin (BER), Gladbach (BMG) and Cologne (KOE), on the other hand, can be happy with their points return in view of their match performance. The success of Leverkusen (LEV) and Mainz (M05) roughly corresponds to their match performance.The aim of the study was to develop, evaluate, and apply a procedure for determining dangerousity in football with real-time capability. The evaluation showed that the quantification of this construct using the spatial constellation of players and ball lies in the same range as human observers. Individual misinterpretations play only a subordinate role in the validity of diagnostic findings concerning performance, particularly with large data volumes. Like many other tactical elements in football, however, the construct does contain a certain lack of precision, with the result that a clear reference for the accuracy of the measurement in the sense of a ground truth cannot exist.The performance and dominance metrics derived are more robust in the context of the effects of chance, and map the match performance of a team more reliably than the traditional performance indicators of possession of the ball, shots on goal, tackle, and pass rates. They can be used to evaluate individual plays, to describe efficiency, represent passages of play, or compare players and teams with one another. In particular, they can help to investigate questions relating to the influence of various playing systems or tactical group concepts on success. In addition, the metrics can be used as the basis for the development of media products, e.g. the fever curve in


Androgen receptor  status has become increasingly important as both a prognostic marker and potential therapeutic target in breast cancer. AR is expressed in up to 90% of estrogen receptor (ER) positive breast cancer, and to a lesser degree, human epidermal growth factor 2 (HER2) amplified tumors. In the former, AR signaling has been correlated with a better prognosis given its inhibitory activity in estrogen dependent disease, though conversely has also been shown to increase resistance to anti-estrogen therapies such as tamoxifen. AR blockade can mitigate this resistance, and thus serves as a potential target in ER-positive breast cancer. In HER2 amplified breast cancer, studies are somewhat conflicting, though most show either no effect or are associated with poorer survival. Much of the available data on AR signaling is in triple-negative breast cancer (TNBC), which is an aggressive disease with inferior outcomes comparative to other breast cancer subtypes. At present, there are no approved targeted therapies in TNBC, making study of the AR signaling pathway compelling. Gene expression profiling studies have also identified a luminal androgen receptor (LAR) subtype that is dependent on AR signaling in TNBC. Regardless, there seems to be an association between AR expression and improved outcomes in TNBC. Despite lower pathologic complete response (pCR) rates with neoadjuvant therapy, patients with AR-expressing TNBC have been shown to have a better prognosis than those that are AR-negative. Clinical studies targeting AR have shown somewhat promising results. In this paper we review the literature on the biology of AR in breast cancer and its prognostic and predictive roles. We also present our thoughts on therapeutic strategies. Androgen receptor (AR) signaling has become increasingly important in understanding the biology of breast cancer, and serves as a potential therapeutic target in the era of precision medicine. Previously, breast cancer has been categorized based on hormone receptor (HR) status, and the presence or absence of human epidermal growth factor 2 (HER2) amplification. More recently, it has become apparent that the AR pathway is associated with breast tumor carcinogenesis, with differing mechanisms dependent on co-expression of HR or HER2 amplification ,2 AlthouThe AR is a steroid-hormone activated transcription factor belonging to the nuclear receptor superfamily, a group that also includes the estrogen receptor (ER) and progesterone receptor (PR). Upon binding of its androgen ligand, the protein translocates to the nucleus where it stimulates transcription of androgen-responsive genes ,3. More AR is found in up to 70%–90% of all breast cancers, making it more abundant than ER or PR activity ,17,18,19Gene expression profiling has also led to distinct molecular subtyping that is sometimes used to classify breast cancer, and these tumors seem to show variable rates of AR expression ,33. For In regards to AR activity in breast cancer carcinogenesis, multiple in vitro studies using several laboratory breast cancer cell lines  have shown an anti-proliferative effect of AR antagonism ,37,38,39Like AR, ER is a steroid hormone receptor. There are naturally two receptors expressed in normal breast tissue, ERα and ERβ, which are involved in the development of reproductive organs, bone density, cell cycle regulation, DNA replication and variety of other processes that occur through both genomic and non-genomic mechanisms. Its ligand is estradiol, and in normal breast tissue ERβ is the dominant receptor. In breast cancer, ERα expression increases and is implicated in tumorigenesis . The funbcl-2 proto-oncogene, which could be reversed with the addition of the anti-androgen hydroxyflutamide [Some studies show AR agonists to actually have anti-tumor effect in the setting of ERα. This has been demonstrated through in vitro modeling in which higher levels of AR confer anti-proliferative effects in the MCF-7 cell line . Some ollutamide ,51. Therlutamide . These eOverexpression of AR in the MCF-7 breast cancer cell line, as postulated by Britton and colleagues, is thought to be due to cross talk between ERα and the EGFR/MAPK pathway, which leads to a self-propogating autocrine growth-regulatory loop through ERα mediated development of AR . Yeast aER expression serves as a primary target for therapy and one of the first treatments targeting this pathway was the anti-estrogen tamoxifen, which was FDA approved in 1998. It is a selective estrogen receptor modulator (SERM) that has differential ER agonist and antagonist activity depending on the target tissue, and acts as a competitive inhibitor of estradiol . TamoxifA somewhat conflicting pre-clinical model to that of Toth-Fejel and colleagues noted in the MCF-7 cell line that overexpression of AR made ERα-positive breast cancer cells resistant to the inhibitory effects of tamoxifen in xenograft and nude mice studies, and that treatment with anti-androgen therapy could overcome this resistance . The posn = 1141) with tumors ≤5 cm from 1987 to 1997 [Several larger studies and meta-analyses reviewing the prognostic implications of AR-positive breast cancer report their findings without discussion of AR in relation to co-receptor status, or male breast cancer. Given the size of these studies, and the unique look into male breast cancer, they remain important and will be discussed briefly here prior to reviewing the significance of AR in relation to ER in this section, and HER2 co-expression versus TNBC in later sections. The largest meta-analysis to date presented by Vera-Badillo and colleagues encompassed 19 studies and 7693 patients with stage I-III disease . Specifi to 1997 . High AR to 1997 . The Nur to 1997 .Regarding male breast cancer, these cases comprise only approximately 1% of all breast cancer. In a Chinese study analyzing 116 patients from 1995 to 2008, men were found to have poorer outcomes if their breast cancers were AR-positive . Unlike In relation to ER-positive breast cancer, several studies have established that AR positivity has prognostic value. AR and ER co-expressing breast cancers generally have better outcomes in terms of time to relapse (TTR), as well as disease specific survival (DSS) as noted from a study by Castellano and colleagues . The stuA Swedish population-based prospective cohort study assessing patients from 2002 to 2012 also showed a statistically significant improvement in DFS  in breast cancers co-expressing AR and ER . Tsang eReduced AR expression in ER-positive disease can predict for an increased risk of relapse, breast-cancer associated death and worse DFS as well . A studyThe HER2 receptor in breast cancer was first noted in the late 1980s. Historically, it has been associated with poorer outcomes and is amplified in approximately 15%–25% of invasive breast cancers ,73. HER2This interplay was further elucidated by Naderi and Hughes-Davies, who showed in the cell lines MDA-MB-453 and MDA-MB-361, and in fresh tumor samples, that there is cross-regulation of certain genes between AR and HER2. In particular, there was increased expression of steroid response genes FOXA1, XBP1 and TFF3, as well as, increased cell proliferation when either AR or HER2 were stimulated. When exposed to the anti-androgen flutamide, or HER2 inhibition there were pro-apoptotic effects, which was notably additive when given in combination . Later, To further add to the complexity of AR in HER2 amplified disease, a study by Ni and colleagues looking at the AR cistrome in the MDA-MB-453 breast cancer cell line, had several interesting findings. They noted that forkhead factor binding motif FOXA1, was highly expressed in HER2 and AR-positive breast tumors, which is similar to AR-positive prostate cancers and seems to be involved in recruitment of ER and AR to their transcription regulatory elements ,79,80. AAlso identified by another group is that AR activates the Wnt/β-catenin pathway, which leads to upregulation of HER3 and has been previously implicated in breast oncogenesis . ExposurThe prognostic significance of AR in HER2 amplified breast cancer seems to either show no association with survival, or indicate poorer outcomes. However, many of these studies are limited by smaller sample sizes. One analysis looking at prognostic variables in AR expressing breast cancer showed no association with BCSS or distant metastasis free interval, though this only comprised a sample of 59 patients . A largeOther studies, including a retrospective analysis by Park et al. analyzed 931 breast cancer tissue samples in stage I–III disease without prior therapy. Forty-nine patients with AR-positive, HER2 amplified breast cancer were categorized as molecular apocrine subtype, and survival analysis revealed a trend toward poorer OS, though this did not reach statistical significance . Along tTNBC, as defined by lack of expression of ER and PR and a lack of HER2 amplification, comprises between 10% and 20% of all breast cancers ,87,88. TGene expression profiling has increasingly been used to classify invasive cancer subtypes over the last 15 years. In TNBC, the majority of cases fall into a category of basal-like subtype, first described by Perou, et al. in 2000 . ExpandeLehmann et al. initially categorized TNBC into 6 separate subtypes, including basal-like 1 (BL1), basal-like 2 (BL2), immunomodulatory (IM), mesenchymal (M), mesenchymal stem-like (MSL), and luminal androgen receptor (LAR), each with distinct gene signatures predicting for driver signaling pathways that could potentially serve as therapeutic targets . SpecifiEven non-LAR TNBC cell lines SUM159PT, HCC1806, BT549, and MDA-MB-231 seem to have a role for AR signaling. Gene microarray and ChIP-seq analysis shows AR mediated up-regulation of the EGFR ligand amphiregulin, which promotes proliferation via the EGFR pathway. This proliferative activity appeared to be blocked with the anti-androgen enzalutamide .AR positivity has been associated with more favorable prognoses in TNBC. There are several studies that show AR is associated with lower Ki-67 proliferative marker, lower mitotic score, lower histologic grade and lower clinical stage ,111,112.Other analyses have shown either no difference or worse outcomes for AR-positive TNBC. McGhan et al., looking at 119 patients with resectable disease, found patients with AR-positive cancers trended toward more advanced stages (stage II and III) breast cancer, with no differences in DSS or OS . Mrklic n = 358), compared to AR-negative tumors at 25.4% (n = 315). In multivariate analysis, AR independently predicted pCR. Interestingly, though patients with AR-negative disease had a higher chance of achieving pCR, those with AR-positive disease had similar DFS and OS whether or not pCR was achieved [n = 4) compared to 63.2% (n = 24) [More recently, pathological complete response (pCR) has become a surrogate marker for outcome in patients treated with neoadjuvant therapies . In termachieved . Specifiachieved . The patachieved . Another(n = 24) . Notably(n = 24) .n = 18) or extensive residual disease (n = 11) after neoadjuvant chemotherapy with adriamycin, cyclophosphamide and paclitaxel (ACT). Pathway databases were used to predict the impact of somatic mutations on certain pathways associated with cancer. Though no single mutation was found to be predictive of response to chemotherapy in TNBC, they did find tumors with mutations in the AR pathway and FOXA1 transcription factor networks had a significantly higher pCR (94.1% vs. 16.6%) compared to those that did not carry such mutations [Also, of interest and somewhat opposite to the above studies looking at pCR is a recent article by Jiang and colleagues in which whole exome sequencing was performed on 29 biopsy samples obtained prior to treatment of patients who were found to have either a pCR  . The samAn alternative combination target may include the use of cyclin-dependent kinases 4 and 6 (CDK4 and CDK6). These kinases are activated by cyclin D, and promote cell cycle entry by phosphorylating proteins that drive the transition from G1 to the S1 phase and when disrupted can lead to unrestricted cell proliferation in breast cancer ,130. CerPreclinical studies led to a phase II clinical trial evaluating bicalutamide in metastatic ER-negative and AR-positive cancers as a proof of concept study led by Gucalp and colleagues. Patients with >10% nuclear expression of AR by IHC were included and treated with bicalutamide 150 mg daily, with the primary endpoint being clinical benefit rate (CBR) defined as the total number of patients who showed a complete response (CR), partial response (PR) or stable disease (SD) > 6 months. The study found the CBR to be 19% for the 26 study participants, driven by SD as there were no CRs or PRs, and a median progression free survival (PFS) of 12 weeks. Though HER2 status was not an exclusion criteria, only 1 of the 26 patients had HER2 amplified cancers and 1 of the 5 patients with SD had initial negative HER2 status that was later considered positive after undergoing a curative intent mastectomy . A more Enzalutamide is a newer generation nonsteroidal anti-androgen that binds the androgen receptor with greater affinity than bicalutamide, decreases nuclear translocation, and impairs binding to androgen response elements and co-activators . An inteIn TNBC, an in vivo study by Barton and colleagues analyzed 4 TNBC cell lines  and noted that the anti-androgen enzalutamide was not only active in the LAR molecular subtype, but also in the M, MSL and BL2 subtypes. They noted that AR activation up-regulates the EGFR pathway, as in ER-positive disease noted above, which could be blocked by enzalutamide and makes it potentially applicable to a broader range of TNBC . CombinaAlso of importance is that enzalutamide has been associated with immunogenic modulation, which may increase the susceptibility of tumor cells to immune-mediated cell death . A studyTraina and colleagues shared preliminary results of a phase II clinical trial assessing enzalutamide in AR-positive metastatic TNBC . The sinAs previously discussed, patients with AR-positive TNBC have a relatively low pCR rate of 12.85% . Aimed aAbiraterone acetate is a selective, irreversible and potent inhibitor of 17α-hydroxylase and 17,20-lyase (CYP17) enzymatic activity and is commonly used in castration-resistant prostate cancer (CRPC) . It has A number of other novel nonsteroidal anti-androgen agents are currently under analysis. Orteronel (TAK-700) is a reversible, selective CYP17 inhibitor, similar to abiraterone with a higher specificity for 17,20 lyase inhibition and known activity in CRPC ,156. ThiSomewhat contradictory to other studies presenting therapeutic options, Narayanan and colleagues demonstrated in the MDA-MB-231 cell line that nonsteroidal, tissue selective androgen receptor modulators (SARMs), rather than anti-androgens could inhibit breast cancer growth . They chPoly ADP-ribose polymerase (PARP) inhibitors are a group of agents aimed at the PARP1 protein that acts to repair single strand breaks in DNA. These breaks occur frequently in the cell cycle, and rely on mechanisms such as PARP1 activity to resolve the errors via the base excision repair pathway. Patients with breast cancer susceptibility gene 1 (BRCA1) and 2 (BRCA2), as well as partner and localizer of BRCA2 (PALB2) mutations are susceptible to DNA double strand breaks, as these genes normally function to correct such breaks. In patients with these underlying mutations, the addition of a PARP inhibitor leads to cell death due to dysfunction of both repair pathways . In regaBromodomain and extraterminal (BET) signaling has emerged recently as an important pathway in AR signaling. These proteins, which are expressed by the majority of cancer cells, are involved in epigenetic activity and chromatin “reading” and include BRD2, BRD3, BRD4 and BRDT . BRD4 haBET signaling has been studied in breast cancer as well. The ER-positive MCF-7 breast cancer cell was noted to have increased T-bet activity associated with insulin exposure, which also was associated with tamoxifen-resistance . Feng anOur study aimed to describe advances in understanding of the complex AR signaling pathways in relation to co-receptor signaling, as well as prognostic and therapeutic implications. However, there are some inherent limitations to the data presented. In particular, several of the above-mentioned pre-clinical studies utilize commercially available breast cancer cell lines. Though there are advantages to the use of these classic cell line models, over time multiple cycles of cell cultures can select for certain subclones that can create variability in genetic and phenotypic expression across labs . For exaAdditionally, most in vitro studies do not distinguish whether the cell line, or cells from fresh biopsy material are early stage or metastatic in origin. Independent review of commercially available cell lines reveals that most are metastatic in origin, and often from malignant pleural fluid, which some might argue indicates particularly aggressive biology that does not reflect the general population . LobularAR remains an area of study that is rapidly evolving. The current study is a comprehensive review of the available data regarding the pathophysiology of AR-positive breast cancer, and makes important efforts to discuss the nuanced differences between AR-positive breast cancers in relation to co-receptor status. Also, prognostic implications of AR are discussed in the same manner, noting clear differences in ER-positive, HER2 amplified and TNBC. Therapeutic targets along the AR pathway are discussed with emphasis on novel agents and combination therapy with promising results. As our understanding of the complexities of AR signaling in regards to tumorigenesis becomes more refined, we will better be able to use AR expression as a prognostic marker and therapeutic target.The identification of the AR signaling pathway in breast cancer has led to an interesting and growing field, especially in regards to basic and translational research. Not only have we identified important prognostic associations with ER-positive, HER2 amplified and TNBC, but also potential therapeutic targets either with monotherapy or in unique combinations. Clearly, there is still significant room to expand the field and grow our understanding of these complex pathways, but early work is encouraging regarding the ability to use targeted therapies in new and exciting ways and we look forward to future of the field.


Prostate cancer is a leading cause of cancer-related death in men worldwide. Aberrant signaling in the androgen pathway is critical in the development and progression of prostate cancer. Despite ongoing reliance on androgen receptor (AR) signaling in castrate resistant disease, in addition to the development of potent androgen targeting drugs, patients invariably develop treatment resistance. Interactions between the AR and PI3K pathways may be a mechanism of treatment resistance and inhibitors of this pathway have been developed with variable success. Herein we outline the role of the PI3K pathway in prostate cancer and, in particular, its association with androgen receptor signaling in the pathogenesis and evolution of prostate cancer, as well as a review of the clinical utility of PI3K targeting. Prostate cancer is the second most common non-cutaneous cancer in men and the fifth cause of cancer death in men worldwide . The undHowever, resistance to these agents invariably develops via multi-factorial mechanisms ,7. It isThe AR is a ligand-dependent nuclear transcription factor expressed in a variety of tissues which, in the absence of ligand, remains in the cytosol bound to heat shock proteins (Hsps). Though numerous ligands interact with the AR, its predominant native ligands are the androgens, 5α-dihydrotestosterone (DHT) and testosterone. The binding of these ligands to the AR initiates male sexual development and pubertal changes in addition to maintaining libido, spermatogenesis, muscle mass, erythropoiesis and bone mineral density in adult males .Once the AR is engaged its effects manifest via three mechanisms. Firstly, classical AR signaling occurs when androgen binds to the ligand binding domain (LBD) to displace the Hsps triggering AR dimerization, phosphorylation and conformational change leading to exposure of the nuclear localization sequence (NLS). The AR then translocates to the nucleus and the DNA binding domain (DBD) binds to androgen responsive elements (AREs) to induce transcription of specific AR-responsive genes that recruit transcription co-activators and co-suppressors ,10. AlteIn the normal prostate gland, AR is expressed in the stromal and epithelial compartments ,17; postAberrant AR signaling is critical to the evolution of prostatic carcinogenesis. The AR has been shown to be necessary for cell proliferation, survival and invasion in early and late prostate cancer ,26,27. RThe reliance of prostate cancer on AR signaling has led to the development of potent androgen pathway targeted treatments. Despite initial responses in many however, resistance to these agents is inevitable and remains an intractable problem. Resistance to these therapies may occur broadly through at least three mechanisms ,33,34,35PI3Ks are a family of lipid kinases that regulate anabolic and catabolic activities in the cell through phosphorylation of the 3′-hydroxyl group of phosphoinositides and phosphatidylinositol. PI3Ks are divided into three classes according to their preferred substrate and sequence homology with class IA thought to be most relevant to human cancers .Class IA PI3Ks are heterodimers made up of a regulatory subunit  and a catalytic subunit  that can be activated by receptor tyrosine kinases, G-protein coupled receptors or oncogenes ,47. FollPIK3CA, PIK3CB and PIK3CD genes encode the p110α, β and δ isoforms respectively. The p110α and 110β isoforms are both widely expressed but p110δ is generally only found in leucocytes. Both the alpha and beta isoforms generate PIP3 but have differing roles: p110α is mainly found in the cytoplasm and is crucial in insulin signaling, glucose metabolism and G1 cell cycle entry while p110β is found in the nucleus and is important in DNA synthesis and replication and cell mitosis . Both isAberrations in PI3K/AKT/mTOR signaling have been identified in approximately 40% of early prostate cancer cases and 70–100% in advanced disease ,57. In pThe association of PI3K pathway activation with castrate-refractory disease suggests that a critical component of the poor prognostic value of PI3K aberrations may be its interaction with androgen signaling. Additionally, responses to AR inhibitors in prostate cancers with PTEN loss may depend on the level of PI3K pathway activation.Despite the association outlined above, the effect of PI3K activation on prostate cancer growth pre-clinically is not dichotomous as some cell lines with PTEN loss  retain sensitivity to castration, while the robust response to castration in de novo disease suggests that most PTEN null tumors retain some sensitivity to androgen deprivation. The mechanism of the interaction between these two pathways remained unclear until relatively recently.Two landmark papers defined the interplay between PTEN loss/PI3K activation and AR signaling in the development of prostate cancer ,73. CarvUtilizing a PTEN conditional murine prostate cancer model, Mulholland et al. demonstrated that PTEN loss suppresses AR transcriptional output and generally drives gene expression towards a castrate-like phenotype. To determine how PTEN loss causes suppression of AR transcriptional output, they used a doxycycline-dependent PTEN loss murine model. They found PTEN re-expression did not affect AR expression but did lead to reduced expression of EGR1 and c-JUN transcription factors, factors that are known to be up-regulated particularly in CRPC and to promote cancer growth in an androgen-depleted environment through direct interaction with and downregulation of the AR ,78. ThroGiven the complexity of the AR and PI3K pathways, they likely interact at numerous levels. AR-induced PI3K stimulation may also occur through Src-mediated non-nuclear signaling, particularly in the context of ADT ,80. AndrThough Mulholland and Carver proposed somewhat different mechanisms, they independently demonstrated with both pharmacologic and genetic approaches PI3K/AKT activation via PTEN loss promotes prostate cancer growth in the absence of AR signaling; as a result, they hypothesize that strong suppression of AR-signaling with potent anti-androgen therapy may select for tumors with PI3K pathway activation and repressed AR activity leading to CRPC. They showed that dual pathway inhibition with androgen deprivation and a PI3K, AKT or mTOR inhibitor could lead to significant tumor regression as compared to single pathway inhibition.Subsequent studies have supported the presence of AR-PI3K pathway interactions. Zhu et al. showed that conditional expression of human AR transgene in transgenic mice prostates not only induced malignancy but also resulted in decreased AKT activation in the tumor cells . They fuRecognition of the role the PI3K pathway plays in the development and propagation of cancer has led to the development of several PI3K inhibitors. Classes of drugs targeting the PI3K pathway and its downstream targets include pan-class I PI3K inhibitors, isoform-selective PI3K inhibitors, rapamycin analogues, active-site mTOR inhibitors, pan-PI3K/mTOR inhibitors and AKT inhibitors . Though There are a number of explanations for the lack of efficacy seen in these trials of single pathway inhibition. Clinical correlation of the pre-clinical data on AR and PI3K pathway crosstalk was suggested in a phase I/II trial of everolimus, an mTOR inhibitor, in combination with gefitinib in patients with metastatic CRPC . Rapid PIf the mutual inhibition of both pathways is required, and from the results above it seems that PI3K activation is not the sole route of standard androgen resistance, then the combination of AR targeting and PI3K targeting would appear to be intuitive. Studies currently underway in prostate cancer are particularly focused on using PI3K inhibitors to overcome castrate-resistance. Thus, PI3K inhibitors are largely being tested in combinations in patients who have progressed on either enzalutamide or abiraterone to test the hypothesis of emerging resistance to these agents via the PI3K pathway.Hotte et al. presented the second part of their phase 2 study of PX-866 at ASCO GU 2015; 25 patients with progressive CRPC on abiraterone/prednisone were treated with a combination of PX-866 and continued abiraterone/prednisone . Six patThese studies raise the question of whether earlier PI3K pathway inhibition, prior to development of castrate resistance or significant pre-treatment with androgen-targeted treatments, would be more efficacious. Some pre-clinical models have shown more durable responses to dual AR and PI3K pathway inhibition in castrate sensitive-cell lines as compared to castrate-resistant ,97,98. AThe prolonged responses seen in two of the patients presented by Burris et al. raise the question of whether patient selection may be another contributing factor to the lack of overall efficacy seen in many of these trials. Attempts to identify subpopulations that will yield maximum benefit from PI3K inhibitors are underway with testing for PIK3CA or AKT alterations and PTEN loss. Pre-clinical data indicate that tumors with PIK3CA mutations or PTEN loss are more sensitive to PIK3CA and AKT inhibition but the value of these markers in clinical practice is uncertain due to the complexity of the pathway and unknown effects of these agents on the tumor microenvironment . Some PIMost recently, de Bono, et al. presented data supporting PTEN loss as a predictor of response to treatment with ipatasertib in combination with abiraterone acetate in men with mCRPC . PTEN exThe androgen receptor and PI3K pathways are the two most commonly deregulated pathways in prostate cancer. There is evidence that PI3K signaling is involved in the evolution to castrate-resistant disease, a form of prostate cancer that remains lethal despite recent advances. This understanding has led to the development of several drugs targeting the PI3K pathway and its downstream targets but, unfortunately, early results overall have been disappointing. Adding complexity to early trials is the issue of interpreting a rising PSA, the most commonly measured marker of response in prostate cancer, in the context of potential activation of AR transcription with resultant PSA rises following PI3K pathway inhibition. Pre-clinical data supporting combined pathway inhibition coupled with the lack of substantial single-agent activity have prompted studies of PI3K pathway inhibition in combination with androgen pathway inhibition and/or additional downstream AKT/mTOR inhibition; the results continue to be mixed with efficacy often compromised by toxicity. There is a suggestion that earlier treatment with these agents, to prevent rather than overcome castrate-resistance, may be a useful strategy.Ongoing studies to address the optimal timing, sequence and combinations of these treatments in addition to potential predictive biomarkers are underway. Given the reciprocal activation of p110α upon p110β inhibition in PTEN null tumors, it will be interesting to see the outcomes with the isoform-specific PI3K inhibitors in combination with enzalutamide. It is unclear whether the preferred agent should target multiple nodes of the pathway, such as with LY3023414, or induce pan-isoform inhibition of a single node, such as with AZD 5363. Despite their promise, it is yet to be seen whether these strategies can successfully overcome endocrine resistance to yield a significant improvement in outcomes for patients.


Increasing studies identified podocyte injury as a key early risk factor resulting in diabetic nephropathy (DN). The ubiquitin carboxy-terminal hydrolase 1 (UCH-L1) participates in podocyte differentiation and injury, which is elevated in the podocytes of a variety of nephritis. Whether UCH-L1 expression is positively related to podocyte injury of DN remains unclear. In this study, elevated expression of UCH-L1 and its intrinsic mechanism in high glucose (HG)-stimulated murine podocytes were investigated using western blot and real-time quantitative PCR. Kidney biopsies of DN patients and health individuals were stained by immunofluorescence (IF) method. The morphological and functional changes of podocytes were tested by F-actin staining and cell migration assay. Results demonstrated that HG induced upregulation of UCH-L1 and activation of the Wnt/β-catenin signaling pathway in podocytes. However, blocking of the Wnt pathway by dickkopf related protein 1 (DKK1) eliminated the above changes. Furthermore, IF staining confirmed that, compared with healthy individuals, the expression of UCH-L1 and β-catenin were obviously increased in kidney biopsy of DN patients. Overexpression of UCH-L1 remodeled its actin cytoskeleton, increased its cell migration and impacted its important proteins. All the findings manifested that Wnt/β-catenin/UCH-L1 may be a new potential therapy method in the treatment of DN in future. Diabetic nephropathy (DN) is a major complication of diabetes mellitus (DM). The detectable early marker of DN is the appearance of microalbuminuria, followed by proteinuria, hyperfiltration, and up to reductions in the glomerular filtration rate, which manifests the destruction of the glomerular filtration barrier (GFB). Podocytes are terminally differentiated epithelial cells locating in the inner layer of Bowman’s capsule that constitute the outer layer of GFB. Their normal structure and function play a major role in maintaining normal integrity of the GFB, which explain why podocyte injury is generally associated with increasing obvious proteinuria . HG contThe ubiquitin carboxy-terminal hydrolase 1  which is an important member of the deubiquitinating enzymes family constituting the ubiquitin-proteasome system (UPS), plays an important role in the regulation of many proteins ,4. It waThe Wnt/β-catenin pathway, so-called canonical Wnt pathway, is activated through binding of Wnt ligand proteins to members of the Frizzled receptor protein family. Then such an interaction inhibits the degradation of β-catenin, followed by its translocation into the nucleus. In the nucleus, β-catenin subsequently initiates the combining with the DNA-bound T cell factor/lymphocyte enhancement factor (TCF/LEF) of many different transcription factors and then triggering transcriptional responses of a variety of Wnt target genes involved in cellular survival, proliferation and differentiation . The WntTherefore, the present study was implemented to determine whether high glucose induces podocyte injury through upregulation of UCH-L1 and to explore the possible mechanisms.The cultured podocytes were divided into the control group and the HG group which were treated with HG for 48 h. The expression of UCH-L1 in the HG group was significantly higher than that in the control one A,B. At tAn analysis of the mRNA expression of common measured Wnt genes was detected by reverse transcription-PCR (RT-PCR) approach to explore the activation status of Wnt/β-catenin signaling pathway in the control group and the HG group. As shown in To examine the biological consequence of Wnt induction in HG induced podocyte injury, the mRNA expression of β-catenin, the principal downstream mediator of the canonical Wnt signaling, was also investigated in podocytes treated with HG. As shown in In the transformed cells, β-catenin can upregulate the expression of endogenous UCH-L1 mRNA and protein . HoweverTo investigate the potential role of Wnt/β-catenin/UCH-L1 signaling in podocyte injury in vivo, immunofluorescence staining was used to explore the expression of UCH-L1 and β-catenin in podocytes of diabetic nephropathy patients. We selected typical DN slides to further assess. The typical images of DN were that parts of glomeruli experienced nodular sclerosis, together with increase of mesangial matrix, appearance of fibrin cap and thickening of capillary wall. The healthy control slides had none of the above features. As shown in To investigate the effect of increased UCH-L1 to podocyte structure in vivo, cytoskeleton was stained with F-actin staining in UCH-L1 adenoviral vector-infected podocytes and control group and control infection group. As the results shown in Further, a cell migration assay was carried to assess the motility of podocytes in UCH-L1 adenoviral vector-infected podocytes and control groups. As shown in To further investigate the effect of increased UCH-L1 in podocytes, several important molecules of podocytes were assessed after differentiated podocytes were infected with UCH-L1 overexpression adenoviral vector for 48 h. As shown in In this study, results demonstrated that HG upregulated the expression of UCH-L1 in murine podocytes, which might be mediated by the Wnt/β-catenin signaling pathway. Furthermore, IF results proved such close relationship between β-catenin and UCH-L1 in DN patients. The overexpression of UCH-L1 not only changed F-actin and hypermotility of podocytes but also changed several important proteins . All thep < 0.05). Meanwhile, UCH-L1 was obviously detected in the kidney biopsy of the DN patients  CO2, RPMI 1640, 10% (v/v) fetal bovine serum, 50–10 U/mL γ-interferon). Podocytes between passages 5 and 20 were used for the proposed experiments. Then cells were cultured under nonpermissive conditions (37 °C without γ-interferon) for 10–14 days for differentiation. After differentiation, podocytes were divided into many groups and received different treatments, including high concentration of d-glucose (30 mM) , dickkopf related protein 1 (DKK1)  or adenoviral vector infection  according to the manufacturer’s instructions.The conditionally thermosensitive SV40-transfected immortalized murine podocyte cell line MPC5  was cultured as described . In briew/v) polyacrylamide gel), transferred onto a PVDF membrane  and then blocked with 5% (v/v) nonfat dried milk in Tris buffered saline Tween . Then, the membrane was probed with primary antibodies against UCH-L1 , synaptopodin , CD2-associated protein (CD2AP) , nephrin  , Snail , Wnt5a , β-catenin  , β-Actin  and GAPDH  overnight at 4 °C followed by incubation with horseradish peroxidase -conjugated secondary antibody . The immunoreactive bands were visualized by ECL  and visualized on Kodak X-ray films. Each experiment was done at least three times. Densitometry analysis of the images obtained from X-ray films was performed using the Image J software .Western blot analysis was done as described. In brief, portions (15 μL) of the podocyte lysates including soluble cell proteins were separated by SDS-PAGE (10% (6) using TRIzol® reagent  according to the manufacturer’s instructions. Then, total RNA (500 ng/reaction) was reverse transcribed (RT) into cDNA using Transcriptor First Strand cDNA Synthesis Kit . RT-PCR was done with FastStart Taq DNA polymerase . The productions of RT-PCR were run on agarose gel. Real-time RT-PCR was done with LightCycler® FastStart DNA Master SYBR Green I (Roche) (primer sequences are given in t) method. All reactions consisted of 39 cycles of 5 s at 94 °C, 30 s at 60 °C, 20 s at 72 °C. The specificity of the amplification reactions was confirmed by melt curve analysis.Total RNA was extracted from cells  and their fasting glucose levels were more than ≥7.0 mmol/L. Kidney slices at 4 mm thickness were fixed for 15 min in 4% paraformaldehyde, followed by permeabilization with 0.2%. Triton X-100 in PBS for 10 min at room temperature. After blocking with 10% goat serum for 60 min, slides were immunostained with primary antibodies against UCH-L1 (1:100), β-catenin  and synaptopodin (1:100). To visualize the primary antibodies, slices were stained with FITC- or TRITC-conjugated secondary antibodies (Proteintech Group). The slices were viewed under a fluorescence microscope .0 h − Areaindicated time)/Area0 h.Podocytes were seeded in the 6-well plate and infected with or without UCH-L1 overexpression adenoviral vector. Then the confluent monolayers podocytes were scraped with a 0.1 mL pipette. Images of the same area were acquired at indicated time points using an inverted microscope and were analyzed using the Image J software image processing program. The percentage of cell migration area was calculated as  for 30 min at room temperature. After being countmounted with DAPI-containing mounting solution, the slides were examined with a fluorescence microscope (Olympus). Image J software was used for post-processing of the images, including merging and colocalization analysis.Podocytes were seeded on sterile cover slips in the 6-well plate and infected with or without UCH-L1 overexpression adenoviral vector for 48 h. After washing with PBS, the podocytes were fixed in 4% paraformaldehyde for 10 min, then permeabilized with 0.1% Triton X-100-PBS for 15 min, and blocked with 3% bovine serum albumin for 30 min at room temperature. F-actin was stained with phalloidin eFluort-test. Multiple means more than 2 groups were analyzed using ANOVA. Statistically significant difference was set at p < 0.05 and highly significant difference was set at p <0.01. All experiments were performed at least in triplicate.All data analysis was done with SPSS software  and was given as mean ± SEM. Paired means were analyzed using Student’s Our data demonstrated that HG could activate the canonical Wnt/β-catenin signaling pathway and then enforce the expression of UCH-L1 in high glucose-treated murine podocytes at the protein and mRNA level, which is confirmed in kidney biopsy of DN patients by IF. The increased UCH-L1 can induce morphological and functional changes of podocyte cells. All these results suggested that Wnt/β-catenin/UCH-L1 might be a new potential therapy method in the treatment of DN.