A crucial event in Prostate Cancer progression is the conversion from a hormone-sensitive to a hormone-refractory disease state. Correlating with this transition, androgen receptor (AR) amplification and mutations are often observed in patients failing hormonal ablation therapies. β-Catenin, an essential component of the canonical Wnt signaling pathway, was shown to be a coactivator of the AR signaling in the presence of androgens. However, it is not yet clear what effect the increased levels of the AR could have on the Wnt signaling pathway in these hormone-refractory prostate cells.Transient transfections of several human prostate cancer cell lines with the AR and multiple components of the Wnt signaling pathway demonstrate that the AR overexpression can potentiate the transcriptional activities of Wnt/β-Catenin signaling. In addition, the simultaneous activation of the Wnt signaling pathway and overexpression of the AR promote prostate cancer cell growth and transformation at castration levels of androgens. Interestingly, the presence of physiological levels of androgen or other AR agonists inhibits these effects. These observations are consistent with the nuclear co-localization of the AR and β-Catenin shown by immunohistochemistry in human prostate cancer samples. Furthermore, chromatin immunoprecipitation assays showed that Wnt3A can recruit the AR to the promoter regions of Myc and Cyclin D1, which are well-characterized downstream targets of the Wnt signalling pathway. The same assays demonstrated that the AR and β-Catenin can be recruited to the promoter and enhancer regions of a known AR target gene PSA upon Wnt signaling. These results suggest that the AR is promoting Wnt signaling at the chromatin level.Our findings suggest that the AR signaling through the Wnt/β-Catenin pathway should be added to the well established functional interactions between both pathways. Moreover, our data show that via this interaction the AR could promote prostate cell malignancy in a ligand-independent manner. Prostate cancer is the second leading cause of cancer-related deaths among men in the U.S., after lung cancer. Since the prostate gland is an androgen-dependent organ, prostate cancer initially responds to androgen ablation. However, this type of treatment is almost never curative, and the majority of patients will evolve from a hormone-sensitive to a lethal castration-refractory form of the disease. It has been postulated that increased levels of both the androgen receptor (AR) mRNA and protein are associated with this transition -3. In adThe Wnt family of signaling proteins plays important roles in stem cell self-renewal and multiple developmental processes. Deregulation of Wnt signaling can lead to various types of cancer ,15. The myc and cyclin D1, as well as to the promoter and enhancer regions of the androgen target gene PSA. These ChIP results indicate that the AR potentiates the Wnt signal at the transcriptional level. In sum, our finding provides a novel mechanism of the AR function, namely, promoting Wnt/β-Catenin signaling and its resulting oncogenic properties in prostate cancer cells at castration levels of androgens.Here we show that the AR can potentiate Wnt signaling in prostate cancer cells. The interaction between the AR and Wnt signaling provides a growth advantage to prostate cancer cells at castration levels of androgens. Interestingly, we found that the presence of the AR ligands attenuated the input of the AR into the Wnt signaling pathway. Physiological levels of androgens inhibited the tumor cell growth and transformation mediated by the activation of the Wnt signaling and the AR overexpression. These results are in agreement with the observation that the AR and β-Catenin can co-localize in the nucleus of human prostate cancer cells. To further explore the mechanism of the AR and Wnt interaction, we have demonstrated by the use of Chromatin Immunoprecipitation (ChIP), that Wnt can recruit the AR and β-Catenin onto the promoter regions of the Wnt target genes S37ACatenin) -thymidine incorporation assay: LNCaP cells and LNCaP-Flag-AR cells were seeded at 6000/well in 96 well plates and maintained in phenol-red free RPMI medium supplemented with 5% charcoal-stripped serum. After 24 hours, cells were treated with either 100 ng/ml Wnt3A or control (PBS with 0.2% serum). Four days after the compound treatment, cells were labeled with [3H]-thymidine for four to five hours. Plates were then harvested and counted using TOPCOUNT. Each experiment was carried out in triplicate with error bars representing standard deviation and repeated three times.[Comparison of cell numbers in cells transfected with GFP, Wnt1 or AR alone, as well as Wnt1 and AR together was conducted using one-tail paired student's t test. P < 0.05 was considered statistically significant.4 trypsinized cells were resuspended in 1 ml of RPMI containing 10%FBS and 0.3% agarose  and layered onto a 0.5 ml cushion of 0.6% agarose in RPMI supplemented with 10%FBS in 24-well plates (Costar). The next day, cells were treated with either 10 nM DHT (Sigma) or 100 ng/mL Wnt3A (R&D Systems) in RPMI with 5% charcoal-stripped serum. The medium, with or without treatments, was then renewed by gentle aspiration every 5 days. Cultures were incubated at 37°C in a humidified incubator containing 5% CO2, and, after an approximate 4 week growth period, colonies were fixed in the presence of 10% formaldehyde in PBS. Colony growth was assessed by photography, noting size and frequency in a typical field of cells using bright-field microscopy (12.5×). Each experiment was carried out in duplicate. And the experiments have been repeated three times.For analysis of anchorage-independent growth of both treated and untreated parental LNCaP and LNCaP-Flag-AR cells, a soft agarose medium was employed. 1 × 10A tissue microarray was obtained from Asterand containing 4 normal prostate tissue and 9 prostate tumors. This microarray was stained with antibodies against AR (Santa Cruz at a 0.5 ug/ml concentration) and β-Catenin , using consecutive slides for the two antibodies. For antigen retrieval, Citra Plus Solution (BioGenex) was used at 95°C for 15 minutes. Slides were stained using the BioGenex i6000 automated staining system. The DAKO Envision Plus kit was used for chromagen detection. As negative controls, isotype mouse IgG1 and rabbit IgG1 were used, and no staining was observed (data not shown).6 cells. After sonication and centrifugation, the supernatant was diluted 1:10 in IP Buffer  for immunoprecipitation with either anti-AR polyclonal antibody (custom made) or anti-β Catenin mouse monoclonal antibody  as well as negative control mouse IgG or rabbit IgG antibodies. No signals were observed in negative controls (data not shown). After overnight incubation at 4°C, protein-DNA complex was then purified with 50 uL of Ultralink Immobilized Protein A/G beads (Pierce) followed by reverse crosslinking. DNA was then isolated using a Qiagen purification kit and eluted in 35 ul volumes. Typically, 2 uL of the purified DNA was used as template in the PCR reactions. The PCR products were analyzed using a Bioanalyzer 2100 (Agilent) and a DNA 1000 kit (Agilent). The amount of PCR product was compared with the input amount to calculate the percentages of input. This experiment was repeated three times and the average of percent input was plotted with error bars representing standard deviation.LNCaP cells in RPMI with 5% charcoal-stripped serum and 1% Pen-Strep were treated with either 10 nM DHT (Sigma), 100 ng/mL Wnt3A (R&D Systems), or left untreated. After 16 hours the cells were fixed with 2% formaldehyde followed by lysis in 0.2 ml buffer  per 1 × 10The primers used were:negative control β-Actin [ β-Actin  (No signforward 5'-TCCTCCTCTTCCTCAATCTCG-3'reverse 5'-AAGGCAACTTTCGGAACGG-3'PSA Promoter and enhancer [enhancer forward 5'-TCCTGAGTGCTGGTGTCTTAG-3'reverse 5'-GCCCTATAAAACCTTCATTCCCC-3',forward 5'-ATGTTCACATTAGTACACCTTGCC-3'reverse 5'-TCTCAGATCCAGGCTTGCTTACTGTC-3'human c-myc and cyclin D1 promoter regions [ regions ,forward 5'-GCTCTCCACTTGCCCCTTTTA-3'reverse 5'-GTTCCCAATTTCTCAGCC-3'forward 5'-GGGAGGAATTCACCCTGAAA-3'reverse 5'-CCTGCCCCCAAATTAAGAAAA-3'.LS designed the experiments, coordinated the assays and the manuscript preparation. In addition, LS performed some of the luciferase reporter assays and the Guava cell count assays. CAR performed some of the luciferase reporter assays, thymidine incorporation assays and soft agar assays. TES performed CHIP assays and AR mutants generation. JSP and QW performed and analyzed IHC study using tissue array. TAL, MMG and RMA supervised and provided guidance and critical input into the study. RMA also participated in the design of the CHIP analysis. All authors have read and approved the final version of the manuscript.


The critical role of the androgen receptor (AR) in the development of prostate cancer is well recognized. The transcriptional activity of AR is partly regulated by coregulatory proteins. It has been suggested that these coregulators could also be important in the progression of prostate cancer. The aim of this study was to identify coregulators whose expression is regulated by either the androgens and/or by the expression level of AR.SRC1, TIF2, PIAS1, PIASx, ARIP4, BRCA1, β-catenin, AIB3, AIB1, CBP, STAT1, NCoR1, AES, cyclin D1, p300, ARA24, LSD1, BAG1L, gelsolin, prohibitin, JMJD2C, JMJD1A, MAK, PAK6 and MAGE11) was then measured by using real-time quantitative RT-PCR (Q-RT-PCR).We used empty vector and AR cDNA-transfected LNCaP cells , and grew them for 4 and 24 hours in the presence of dihydrotestosterone (DHT) at various concentrations. The expression of 25 AR coregulators  showed more than 2-fold induction and 5 others  less than 2-fold induction. Overexpression of AR did not affect the expression of the coregulators alone. However, overexpression of AR enhanced the DHT-stimulated expression of MAK, BRCA1, AIB1 and CBP and reduced the level of expression of β-catenin, cyclinD1 and gelsolin.Five of the coregulators (In conclusion, we identified 5 coactivators whose expression was induced by androgens suggesting that they could potentiate AR signaling. Overexpression of AR seems to sensitize cells for low levels of androgens. Prostate cancer is the most and second most common male malignancy in the USA, and Europe, respectively ,2. The aTMPRSS2:ERG fusion gene provides a model for molecular mechanisms how androgens act in promoting the early development of prostate cancer. Due to the rearrangement, the putative oncogene ERG becomes androgen regulated [AR gene [AR have also been found in antiandrogen treated prostate cancers [The molecular mechanisms by which prostate cancer cells become resistant to endocrine therapy remain incompletely known. However, the key role of androgens and androgen receptor (AR), not just in early development but also in the progression of prostate cancer has now been demonstrated . The recegulated ,9. It haegulated . Further[AR gene . Mutatio cancers ,13. And  cancers ,15.The transactivation of AR involves several coregulatory proteins ,17. LargSRC1 , TIF2 , PIAS1 , PIASx , ARIP4 ), BRCA1 , β-catenin , beta 1, 88 kDa), AIB3 , AIB1 , CBP ), STAT1 , p300 , ARA24 , LSD1  domain 2), BAG1L , gelsolin ), JMJD2C , JMJD1A , MAK , MAGE11  and 5 putative corepressors: NCoR1 (nuclear receptor co-repressor 1), AES , cyclin D1 , prohibitin (PHB) and PAK6 (p21(CDKN1A)-activated kinase 6) by using quantitative reverse transcription-PCR (Q-RT-PCR) in AR positive prostate cancer cell line LNCaP treated with different concentrations of DHT. To mimic the common overexpression of AR in hormone-refractory prostate cancer, we also stable transfected AR to LNCaP cell line. The LNCaP-ARhi cells express about 10-folds more AR mRNA and 3 to 4-folds more AR protein than that of the control (empty vector-transfected cell line: LNCaP-pcDNA3.1). The cell model was used to study whether the level of AR has an effect on the mRNA expression of the coregulators.In order to identify AR coregulators whose expression is regulated by androgens, we measured the expression of 20 putative coactivators: pcDNA3.1(+) empty expression vector  and pcDNA3.1(+) inserted with AR coding region were stable transfected into LNCaP  with Lipofectamine-Plus transfection reagent (Invitrogen Inc.). Transfected clones were selected with 400 μg/ml geneticin (G418) for 2 weeks. The mRNA level of AR was examined from purified clones using Northern blotting and Q-RT-PCR with Light-Cycler . The protein level of AR was analyzed using Western blotting with anti-AR antibody . LNCaP-pcDNA3.1 (transfected with empty pcDNA3.1-vector as a control) and LNCaP-ARhi (transfected with AR cloned into pcDNA3.1+ vector) cell lines were cultured according to the ATCC protocol with the addition of Geneticin 200 μg/ml (Invitrogen Inc.). LNCaP-ARhi has about 10 times higher mRNA level of AR and 3 to 4 times higher protein level of AR than that of the LNCaP-pcDNA3.1  FBS , 1% glutamine (Invitrogen Inc.) and 1% penicillin-streptomycin  for 4 days. The medium was then changed to phenol free RPMI1640 including 10% CCS-FBS (Hyclone Inc.), 1% Glutamine (Invitrogen Inc.), 1% Pest (Invitrogen Inc.) and 0, 0.1, 1.0, 10 or 100 nM DHT. The cells were harvested into TRIZOL reagent  after 4 h and 24 h, followed by total RNA isolation according to the manufactures protocol.2 (except for PAK6 (5 mM) and JMJD1A (3 mM)), 0.5 μM each primer, and 1× ready-to-use SYBR Green I reaction mix including Taq DNA polymerase, reaction buffer and a deoxynucleotide triphosphate mix. The cycling conditions were designed according to the manufacturer's guidelines which are given in additional file TBP) as previously described [The cDNA was synthesized with AMV Reverse Transcriptase and oligo(dT)12–18 primer according to the manufacturer's protocol . The standards were prepared mixing total RNA from untreated LNCaP cells and universal RNA  in a ratio of 1:5. After first strand cDNA synthesis, serial dilutions corresponding to 1000, 200, 40, 8, 1.6, 0.32, 0.064 μg of RNA pool were prepared and stored in aliquots. The PCR reactions were performed in LightCycler apparatus (Roche Inc.) using an LC Fast Start DNA SYBR Green I Kit . The final volume of each reaction was 20 μl containing 2 μl of cDNA sample (or standard), 4 mM MgClescribed .® semi-dry transfer cell . After blocking in PBS 0.1% Tween 5% BSA (or 5% non-fat dry milk), the membranes were incubated with primary antibody (AR: dilution 1: 200 Androgen Receptor Ab-1 (AR441) Neomarkers, Fremont, CA; β-catenin: dilution 1:2000 BD Transduction Laboratories, Inc.; MAK: dilution 1:500 MAK antibody (C-term), ABGENT San Diego, CA; CBP: dilution 1:1000, R&D Systems, Inc.) over night at +4°C. After washes and incubation with secondary antibody  the bound antibody was visualized on autogradiography film using Western Blotting Luminol Reagent  according to the manufacturer's protocol. Pan-actin antibody  was used as a reference.Cytoplasmatic and nuclear proteins were isolated from subconfluent cells of LNCaP-ARhi. Proteins were separated in 10% SDS-PAGE gel followed by transfer to a membrane  using BIORAD transblotGrubb's test was used to detect the outlier values in the repetitive runs for each gene. One-way ANOVA (Parametric) test with Bonferroni post-test was used to evaluate the statistical significance of the expression level's changes.PSA), known androgen regulated gene was first measured .To identify androgen regulated coregulators, empty vector transfected LNCaP (LNCaP-pcDNA3.1) was grown in different concentrations of DHT. The total RNA was then collected at two time points 4 h and 24 h). To confirm the success of the DHT stimulation, the expression of prostate-specific antigen . Of the coregulators, PIASx (p = 0.0601 at 4 h and p = 0.6488 at 24 h), BRCA1 (p = 0.4172 at 4 h and p = 0.0377 at 24 h), β-catenin (p = 0.0272 at 4 h and p = 0.4158 at 24 h), AIB3 (p = 0.0690 at 4 h and p = 0.1455 at 24 h), AIB1 (p = 0.0401 at 4 h and p = 0.2541 at 24 h), CBP (p = 0.0184 at 4 h and p = 0.0588 at 24 h), cyclin D1 (p = 0.2039 at 4 h and p = 0.4432 at 24 h), ARA24 (p = 0.0220 at 4 h and p = 0.2502 at 24 h) and BAG1L (p = 0.0359 at 4 h and p = 0.3981 at 24 h), showed dose dependent response to androgens, whereas SRC1, TIF2, PIAS1, ARIP4, STAT1, NCoR1, AES, p300 and LSD1 did not.Next, we screened expression of PIASx, BRCA1, β-catenin, AIB3, AIB1, CBP, cyclin D1, ARA24 and BAG1L were selected for additional Q-RT-PCR runs in triplicates. In addition, expression of gelsolin, prohibitin, JMJD2C, JMJD1A, MAK, PAK6 and MAGE11 was measured in triplicates. Figures AIB1, CBP, MAK, BRCA1, β-catenin, cyclin D1, gelsolin, prohibitin, JMJD1A, and JMJD2C. Table Gelsolin showed reduced and increased expression at 4 and 24 hour time points, respectively. Others exhibited an androgen-dependent increase in the expression of the mRNAs. However, only AIB1, CBP, MAK, BRCA1, and β-catenin showed more than 2-folds induction after stimulation with DHT.PSA response in the LNCaP-ARhi cell line at 24 hours was significantly (p < 0.0001) stronger than in the empty vector transfected cell line (LNCaP-pcDNA3.1) . The MAK, CBP, AIB1, and BRCA1. In contrast, the androgen regulation of β-catenin, cyclin D1 and gelsolin, which was apparent in LNCaP-pcDNA3.1 at 24 h was less strong in LNCaP-ARhi  other coregulators  was significantly, but less than 2-fold, induced by androgens.We systematically studied the androgen regulation of the expression of twenty-five AR coregulators. 5 (20%) coregultators showed statistically significant over 2-fold induction by DHT. These were AIB1 (Amplified in Breast Cancer 1) encodes for a well characterized protein with histone acetyltransferase activity. It is thought to be a nuclear receptor coactivator that interacts with various nuclear hormone receptors enhancing their transcriptional activity in a hormone dependent fashion. It is a member of the p160/steroid receptor coactivator (SRC) family and recruits p300/CBP-associated factor, with histone acetylation activity, and CBP (CREB binding protein) as a part of the transcription multisubunit coactivation complex [AIB1 has been found to be amplified in about 10% of breast cancers [AIB1 is nearly 2-fold induced by any concentration of DHT while at 24 hours time point a 4-fold induction was observed. The highest induction was at 1 nM DHT while at 10 nM the expression was declined. We used web-based TESS (Transcription Element Search Software) program and TRANSFAC database [AIB1. The program identified several glucocorticoid receptor (GR) responsive elements (GREs) and two putative androgen responsive elements (AREs) at -527 and at -1291 bp from the TSS. complex ,24. AIB1 cancers . Previou cancers ,27. Heredatabase  to searcAIB1, CBP was nearly 2-folds induced at 4 hours time point by any concentration of DHT while at 24 hours time point a 4-folds induction can be observed, although such induction can be seen also in 10 nM DHT concentrated media. In contrast with our results, Comuzzi et al. have suggested that CBP expression is down-regulated after treating LNCaP cells with synthetic androgen methyltrienolone (R1881) for 48 hours at concentrations of 0.01 nM and 1 nM [Similarly to and 1 nM .MAK  is a recently identified AR coactivator [MAK is transcriptionally induced by DHT in LNCaP cells showing 9-fold induction by 10 nM DHT at 24 hours [MAK promoter is a direct target of AR and identified putative ARE sites within the promoter of MAK (about -3500 bp from the TSS), and that AR is recruited to the MAK promoter after DHT stimulation according to chromatin immunoprecipitation (ChIP) analysis [MAK is regulated by androgens and since it functions as an AR co-activator, it forms a putative feedback loop augmenting the effects of androgens.ctivator  that inictivator . In addi24 hours . This is24 hours . Jia et analysis . AltogetBRCA1 (breast cancer 1) is a well characterized gene in breast cancer since mutations in this gene are responsible of at least 40% of inherited breast cancers and more than 80% of inherited ovarian cancers [BRCA1. It has previously been demonstrated that BRCA1 is an estrogen induced gene in breast and ovarian cancer cells [ cancers ,35. BRCA cancers . Our dater cells ,38.β-catenin is induced up to 2.5-folds at 24 hours time point, already at a concentration of 0.1 nM of DHT. The induction reaches then the 3-folds and declines at 2-folds at 100 nM showing a significant androgen regulation.β-catenin is an adherens junction protein with altered expression in various tumor types. Its fundamental role as a multifunctional oncoprotein has been established . The gencyclin D1, gelsolin, prohibitin, JMJD1A and JMJD2C showed a significant dose dependent effect in their expression level mainly at 24 hours time point. However, the induction was very mild, less than 2-fold, suggesting either only weak androgen effect or secondary mechanisms for the induction.In addition to the above mentioned coregulators, e.g. for PSA, which was significantly upregulated more and in lower concentrations of DHT in LNCaP-ARhi than in LNCaP-pcDNA3.1 cells. Similarly, the expression of MAK, CBP, and BRCA1 was increased more in LNCaP-ARhi than in LNCaP-pcDNA3.1, and, at least, a 10-fold sensitization was observed. For MAK and CBP this was apparent in 4 h time point, whereas for BRCA1 at 24 h time point. Interestingly, the increased expression of AR did not affect all androgen-regulated coregulators. β-catenin, cyclin D1 and gelsolin, which showed androgen-regulation in LNCaP-pcDNA3.1 at 24 hours were not regulated by androgens in LNCaP-ARhi. The data suggest that the AR overexpression has distinct effects on different target genes. It should be recognized that during the androgen withdrawal, there are still adrenal androgens left. For example, the DHT concentration is only partially depleted [It has been demonstrated that AR is commonly overexpressed in hormone-refractory prostate cancer ,46,47. Idepleted . Thus, tAIB1, CBP, MAK, BRCA1, β-catenin) that were induced more than 2-fold by DHT, showed the induction already at 4 time point in one or both cells lines (LNCaP-pcDNA3.1 and LNCaP-ARhi) suggesting direct regulation. Whereas, coregulators with lower-level of induction showed the effect variably in 4 and 24 hour points, which may also suggest secondary mechanisms of androgen regulation.The effects of androgens on gene expression were measured at two time points, 4 h and 24 h. The 4 h time points represent a time interval where direct effects of androgens administration should be seen, although the effect can be mild. On the other hand, also secondary mechanisms can already be activated at 24 hours time point. All coregulators (In conclusion, by systematic measurement of 25 AR coregulators, we identified 5 coregulators whose expression seems to be significantly androgen-regulated indicating that they could be a part of positive feedback mechanisms potentiating the AR signaling. Overexpression of AR seems to sensitize cells in terms of androgen regulation but the effect is gene-specific since not all androgen-regulated genes were up-regulated in AR overexpressing model.The authors declare that they have no competing interests.AU: acquired the data through PCR, prepared the manuscript, analyzed and interpreted the data. KW: made the cell-culture work. HM: supported the PCR work. HS: established the AR overexpression cell lines. TV: designed the study, helped preparing the manuscript and analyzing and interpreting the data. All authors read and approved the final manuscript.The pre-publication history for this paper can be accessed here:Additional Table Click here for fileAdditional Figure Click here for file


Overexpression of the de-ubiquitinating enzyme UCH-L1 leads to inclusion formation in response to proteasome impairment. These inclusions contain components of the ubiquitin-proteasome system and α-synuclein confirming that the ubiquitin-proteasome system plays an important role in protein aggregation. The processes involved are very complex and so we have chosen to take a systems biology approach to examine the system whereby we combine mathematical modelling with experiments in an iterative process. The experiments show that cells are very heterogeneous with respect to inclusion formation and so we use stochastic simulation. The model shows that the variability is partly due to stochastic effects but also depends on protein expression levels of UCH-L1 within cells. The model also indicates that the aggregation process can start even before any proteasome inhibition is present, but that proteasome inhibition greatly accelerates aggregation progression. This leads to less efficient protein degradation and hence more aggregation suggesting that there is a vicious cycle. However, proteasome inhibition may not necessarily be the initiating event. Our combined modelling and experimental approach show that stochastic effects play an important role in the aggregation process and could explain the variability in the age of disease onset. Furthermore, our model provides a valuable tool, as it can be easily modified and extended to incorporate new experimental data, test hypotheses and make testable predictions. However, as yet its substrates are unknown. It also binds to ubiquitin and stabilises ubiquitin pools UCH-L1 is susceptible to oxidative damage and when this occurs it has aberrant functions similar to mutated UCH-L1, as already mentioned. Abnormal UCH-L1 interacts with Lamp2a, Hsc70 (P11142) and Hsp90 (P07900), and may inhibit chaperone mediated autophagy (CMA)-dependent degradation causing CMA substrates, e.g. α-synuclein (P37840) and GAPDH (P04406), to accumulate in vitro that it can be degraded by the 20S proteasome in a ubiquitin-independent manner in vivo evidence that it is degraded by CMA α-synuclein is abundantly expressed in human brain . It is natively unfolded but does not self-aggregate unless it is present at very high levels in vitro studies of protein aggregation kinetics and many mechanisms and mathematical models have been proposed  in vitro studies being incorporated into the aggregates  are shown in The effects of UCH-L1 overexpression alone can be examined by studying the graphs before the time at which proteasome inhibition begins (up to 20 hours). Ubiquitin pools show a very slight increase from the start of the simulation due to increased stabilization by UCH-L1. The UCH-L1 substrate increases with time, since UCH-L1 overexpression leads to increase DUB activity of its substrate which has the effect of lowering the degradation rate. When inclusions start to form, the substrate may be sequestered into the inclusion and so levels of the substrate increase more slowly and may eventually level off or even start to decrease. The substrate may be bound by ubiquitin and UCH-L1 when it is sequestered into inclusions.Overexpression of UCH-L1 does not affect levels of the generic protein (NatP) before PI. After PI occurs, levels of NatP start to increase due to less degradation via the proteasome. When inclusions form, misfolded protein may be sequestered into the inclusion and so total protein levels increase less steeply. The effect on α-synuclein varied between simulation runs, although there was usually a slight increase in levels before PI, in some runs an increase was not seen until after PI at which point the increase was continued steeply until inclusions were formed. Since the time at which inclusions starts to form is very variable, we plotted the aggregation kinetics for six different simulations runs where UCH-L1 was overexpressed by a factor of 3 . It can In order to identify the event or chain of events that leads to inclusion formation we ran the model using a deterministic simulator and made a careful comparison of the results with the stochastic output. We examined the time course of the different species in the model making a careful distinction of events that occurred before and after proteasome inhibition. We used the model with UCH-L1 overexpressed by a factor of 2 with proteasome inhibition at 20 hours for this analysis. Our model output shows that the first event in the chain is an increase in levels of damaged UCH-L1 which binds to Lamp2a receptors leading to an increase in α-synuclein levels. The levels of α-synuclein are now sufficient to form small aggregates and the deterministic solution shows that on average a cell would have formed a small inclusion  before the proteasome is inhibited. After proteasome inhibition there is a large increase in misfolded protein which then gets sequestered into the inclusion and so it rapidly grows in size. In the stochastic model, the seed may not form until after the proteasome is inhibited and so some cells do not have detectable inclusions even by 8 h post PI whereas the deterministic model predicts all cells to have inclusions by 7.2 h post PI.We assumed that 25% of cells were not transfected and that 25% of cells incorporated more than one extra copy of the plasmid. It is not easy to measure the exact proportions and so we examined the effects of varying these proportions in our model. We found that there was little effect on the model predictions for the proportions of cells containing inclusions by 8 hours after proteasome inhibition which was always in the range of 56–62%. However, lowering the proportion of cells with an extra copy of the plasmid, led to fewer inclusions at 4 hours post PI with only 10% of cells containing inclusions if in the extreme case we assumed that no cells incorporated an extra plasmid. An alternative way to model different expression levels of UCH-L1 would be to use random numbers to decide on the proportions of cells incorporating one extra plasmid or no plasmid. This would provide a more stochastic approach to the problem although we would not expect the model predictions to be greatly affected.actUCHL1k to reflect the relative amount of wild-type and I93M UCH-L1 in the cell. Our model predicted that there was a small increase in the number of inclusions at 4 h, 6 h, and 8 h after proteasome inhibition but the difference was only significant at 6 h (p = 0.04). The reason for the slight increase in inclusion is that more of the UCH-L1 substrate ends up at the proteasome but is degraded much less efficiently and is more likely to be sequestered into inclusions. We then modified the model to allow for the possibility that the I93M mutant has lower solubility than wild-type UCH-L1 and has similar properties to oxidatively damaged UCH-L1 in addition to having lower hydrolase activity. We modelled this by including an additional species UCHL1_mut to represent the I93M mutant and assumed that this had a higher propensity to become damaged. If we assumed that the rate of damage was an order of magnitude higher, then the model predicted that inclusions containing high levels of α-synuclein and UCH-L1 started to form before proteasome inhibition with 75% of cells containing inclusions by 4 hours after proteasome inhibition with only the cells that we had assumed were not transfected without inclusions. If the rate of damage for mutant UCH-L1 was 50% higher, then the model predicted that 18% cells contained inclusions by 4 hours after proteasome inhibition, rising to about 62% by 8 hours post PI. We also ran the model without proteasome inhibition for 28 hours and in this case, 31% of cells formed inclusions by the end of the simulations. We also performed experiments in the laboratory to test the model predictions and found that the results were in close agreement with the model which assumed that the I93M mutant had a 50% greater chance of being damaged  (reviewed in It is known that proteasome efficiency declines with age and that this can result in an accumulation of damaged and misfolded proteins www.sbml.org). We used SBML shorthand and a Python script to convert the code into full SBML www.basis.ncl.ac.uk) and the Biomodels database We extended our earlier model of the ubiquitin-proteasome system The model is quite large but can be split up into eight components: a generic model of the ubiquitin-proteasome system; UCH-L1 turnover, UCH-L1 stabilisation of ubiquitin pools; UCH-L1 hydrolase activity, UCH-L1 damage; α-synuclein turnover, α-synuclein damage; and protein aggregation. Each component is described in turn and each individual component is itself a complete model which can be tested. The components are then linked together to form an integrative model. Full details of the model species and reactions are given in the supporting information in This component is based on the already published model of the ubiquitin-proteasome system We assume that UCH-L1 can be degraded by lysosomes and proteasomes. This component consists of just four reactions: synthesis, binding to the proteasome, degradation by the proteasome and degradation by lysosomes .UCH-L1 binds to ubiquitin (by monoubiquitination) and prevents ubiquitin (Ub) degradation. This is reversible, so when pools of Ub are low, Ub is released from UCH-L1. This enables Ub levels to increase rapidly before upregulation takes place which is subject to a delay due to the time required for protein synthesis. When Ub pools are sufficient again, Ub can bind to UCH-L1. We assume that the affinity of UCH-L1 to Ub is less than affinity of Ub to E1 and E2 enzymes, so that it only binds surplus pools .The substrates of UCH-L1 are currently unknown so we include a pool of a generic substrate named SUB. We assume that UCH-L1 first binds (reversibly) to the ubiquitinated (or polyubiquitinated) substrate and removes Ub processively .We assume that UCH-L1 may be oxidatively damaged by reactive oxygen species (ROS (CHEBI:26523)) which causes it to lose its activity. We assume that damaged UCH-L1 will bind to the Lamp2a receptor which prevents binding of CMA substrates to the receptor .We assume that α-synuclein is degraded by the proteasome without the need for ubiquitination (only mutated forms require ubiquitination), or chaperone-mediated autophagy which requires binding of α-synuclein to the Lamp2a receptor .We assume that α-synuclein may be damaged by ROS and it is then ubiquitinated by Parkin and degraded via the 26S proteasome .We assume that any misfolded protein can interact with another misfolded protein to form a small aggregate. An aggregate can grow in size by the addition of further misfolded proteins and may decrease in size by the removal of misfolded proteins with the aid of the chaperone machinery. However, when the aggregate reaches a certain threshold size, disaggregation can no longer take place and instead an inclusion forms. This threshold represents the seed and is assumed to be of size six based on data for amyloid fibril polymerization We carried out a sensitivity analysis to see which parameters affected the kinetics of aggregate formation. The results are reported in COS7 cells were transfected with 2 µg UCHL1-HA, S18Y-HA or I93M-HA plasmid DNA in 2% FCS containing media as previously described Text S1Further details of the model and simulation methods.(0.06 MB DOC)Click here for additional data file.Figure S1Plot of mean values for 100 runs of model under normal conditions. A Generic pool of protein. NatP  =  Native protein; TotalMisP =  unbound misfolded protein + all bound forms of misfolded protein; Total protein  =  NatP + TotalMisP. B Ubiquitin pools. Ub conjugates includes all complexes containing ubiquitin not just ubiquitinated proteins (e.g. Ub-UCHL1 complex is included in this pool). C Aggregated protein. SeqAggP =  aggregates sequestered into inclusion bodies; AggP = small unbound aggregates ; AggP_Proteasome = small aggregates bound to the proteasome. D α-synuclein levels: asyn = unbound α-synuclein; asyn_dam = total pool of damaged α-synuclein (except any that is present in inclusions); total asyn = total pool of α-synuclein. E Pool of unbound proteasomes. F UCHL1 pools: Free UCHL1 = unbound UCHL1; Total UCHL1 = total pool of UCHL1 (except any that is present in inclusions); UCHL1 substrate = total level of the UCHL1 substrate (either bound or unbound)(0.17 MB TIF)Click here for additional data file.Table S1Model species for generic UPS component.(0.05 MB DOC)Click here for additional data file.Table S2Model species for UCHL1 turnover, activity, damage and aggregation.(0.04 MB DOC)Click here for additional data file.Table S3Model species for α-synuclein turnover, damage and aggregation.(0.04 MB DOC)Click here for additional data file.Table S4Dummy species used to identify different proteins in inclusions.(0.03 MB DOC)Click here for additional data file.Table S5Reactions for generic UPS component.(0.07 MB DOC)Click here for additional data file.Table S6Reactions for UCH-L1 turnover, activity, damage and aggregation.(0.06 MB DOC)Click here for additional data file.Table S7Reactions for α-synuclein turnover, damage and aggregation.(0.06 MB DOC)Click here for additional data file.Table S8List of parameters which have an effect on inclusion formation.(0.03 MB DOC)Click here for additional data file.Table S9Results for I93M mutant. Mutant has lower hydrolase activity and has 50% higher damage rate than wild-type.(0.03 MB DOC)Click here for additional data file.Table S10Results for S18Y mutant. Mutant has higher hydrolase activity.(0.03 MB DOC)Click here for additional data file.Dataset S1SBML code of model for normal conditions.(0.01 MB TAR)Click here for additional data file.


Under in vitro models of differing environments, M. tuberculosis alters its metabolism, transcriptional profile and rate of replication. In this study, we investigated whether these phenotypic adaptations of M. tuberculosis are unique for certain environmental conditions and if they could therefore be used as differential markers. Bacilli were studied using fluorescent acid-fast auramine-rhodamine targeting the mycolic acid containing cell wall, and immunofluorescence targeting bacterial proteins using an anti-M. tuberculosis whole cell lysate polyclonal antibody. These techniques were combined and simultaneously applied to M. tuberculosis in vitro culture samples and to lung sections of M. tuberculosis infected mice and guinea pigs. Two phenotypically different subpopulations of M. tuberculosis were found in stationary culture whilst three subpopulations were found in hypoxic culture and in lung sections. Bacilli were either exclusively acid-fast positive, exclusively immunofluorescent positive or acid-fast and immunofluorescent positive. These results suggest that M. tuberculosis exists as multiple populations in most conditions, even within seemingly a single microenvironment. This is relevant information for approaches that study bacillary characteristics in pooled samples (using lipidomics and proteomics) as well as in M. tuberculosis drug development.A unique hallmark of tuberculosis is the granulomatous lesions formed in the lung. Granulomas can be heterogeneous in nature and can develop a necrotic, hypoxic core which is surrounded by an acellular, fibrotic rim. Studying bacilli in this  Mycobacterium tuberculosis, the causative agent of the disease tuberculosis (TB), has proved extremely difficult to treat for more than a century. Almost 1.8 million people died from TB in 2007 M. tuberculosis first enters the lung, the bacilli are phagocytosed by alveolar macrophages and infection is then contained by host cellular recruitment into the formation of granulomas M. tuberculosis adapts to in order to survive. When grown under hypoxic conditions in vitro in the laboratory, M. tuberculosis alters its replication rate When M. tuberculosis within granulomas which is most likely due to technological difficulties of extracting M. tuberculosis from tissue and performing proteomic and lipidomic studies on limited bacterial numbers. The goal of this study was to investigate M. tuberculosis in their in vivo environment by using differential staining techniques that target specific components of the M. tuberculosis bacillus, and whether certain bacillary populations could be identified in the different microenvironments tested in vitro and in vivo. Current published methods used to visualize and locate bacteria within infected tissue allow for detection of: 1) bacterial lipid by acid-fast staining [Ziehl-Neelsen (ZN) and auramine-rhodamine (AR) in situ hybridization (ISH) The mechanisms by which the bacilli survive in the granuloma are poorly understood. To date, there are only few studies published which investigate M. tuberculosis would be detected by each individual detection technique as numerous published studies have shown that the cell wall of M. tuberculosis can undergo alterations under certain in vitro and in vivo conditions. Deb et al showed that M. tuberculosis can lose its acid-fastness under multiple stresses in vitroin vitro study showed that altered mycolic acid ratios along with a shortened mycolic acid chain length render M. tuberculosis acid-fast negative M. tuberculosis are substantially altered M. tuberculosis can lose its ability to retain the Ziehl Nielsen acid-fast stain M. tuberculosis has been described to thicken when grown under hypoxic conditions in vitro as was shown by transmission electron microscopy M. tuberculosis changes its transcription profile significantly under different environmental conditions. Low oxygen tension, NO, or CO induce the transcription of a set of genes known as the DosR regulon, which allow the bacteria to survive under these conditions M. tuberculosis upregulates an iron-scavenging pathway and induces anaerobic respiration along with the dormancy regulon Both IHC and acid-fast staining visualize specific targets, therefore we hypothesized that only certain subpopulations of M. tuberculosis recognized by the dyes is still being elucidated. Fuchsin, the main component of Ziehl-Neelsen and Kinyoun acid-fast stains, has been shown to stain the vastly complex lipid portion of the mycobacterial cell wall M. tuberculosis studies, the exact staining target in M. tuberculosis has yet to be discovered. The IF technique described in this study uses a rabbit polyclonal antibody raised against M. tuberculosis whole cell lysate to maximize detection sensitivity.Although acid-fast stains have been around for decades, the exact cellular component of M. tuberculosis exist under different environmental conditions by staining for M. tuberculosis in culture, mice and guinea pigs; and to simultaneously detect multiple M. tuberculosis populations by detection of different targets with a combined IF-AR approach, and in addition, improving the sensitivity of the methods by using fluorescent signals. IF-AR staining revealed that there are at least three subpopulations of M. tuberculosis that exist within in vitro grown cultures and within mouse and guinea pig lung granulomas.This study had a dual goal; to investigate whether various subpopulations of All experimental protocols were approved with written consent by the Animal Care Use Committee of Colorado State University  which abides by the USDA Animal Welfare Act and the Public Health Service Policy on Humane Care and Use of Laboratory Animals.Specific-pathogen-free, 8 to 10 weeks old female C57BL/6 mice and four to five month-old, female out-bred Hartley guinea pigs (approximately 500 g in weight) were purchased from the Charles River Laboratories . The C57BL/6-Ifngtm1ts gamma interferon gene-disrupted (GKO) mice were purchased from Jackson Laboratories . Animals were maintained in the biosafety level 3 biohazard facilities at Colorado State University, and were given sterile water, bedding, and enrichment for the duration of the experiments. The specific pathogen-free nature of the animal colonies was demonstrated by testing sentinel animals.M. tuberculosis strain Erdman , was grown as previously described M. tuberculosis Erdman was grown to mid-log phase in Proskauer-Beck medium containing 0.01% Tween 80  and stored in vials frozen at −70°C until use.The virulent M. tuberculosis  is used routinely in our laboratory for guinea pig infection studies M. tuberculosis H37Rv was grown from low passage seed lots in Proskauer-Beck liquid medium containing 0.05% Tween 80 to early mid-log phase and frozen in aliquots at −70°C until needed. Cultures were diluted in sterile water prior to use.The H37Rv strain of M. tuberculosis under hypoxic conditions has been described The protocol used to grow M. tuberculosis strain Erdman (TMCC 107) in a Glass-Col inhalation exposure system  as previously described 2 inhalation and spleens and left lung lobes were aseptically removed and bacterial loads determined as previously described Mice were exposed to a low-dose aerosol infection (LDA) with M. tuberculosis in a Madison aerosol chamber device known to result in approximately 20 lesions in the lungs as previously described Female Hartley guinea pigs were exposed to a low-dose aerosol of H37Rv strain of The number of viable organisms in each organ sample was determined by plating serial dilutions of the organ homogenates on nutrient Middlebrook 7H11 agar plates . The plates were incubated at 37°C in ambient air for 4 weeks prior to the counting of the number of colony forming units (CFU) for each dilution.in situ with 10% neutral-buffered formalin and preserved for 48 hours until processed for histopathological assessment. At the time of processing, all tissues were embedded in paraffin, sectioned at 5 µm and stained with hematoxylin and eosin (H&E). The sections were examined by a veterinary pathologist and compared to the histopathology from previous animal studies completed in our laboratory At the time of sacrifice, the lower right lung lobe was infused M. tuberculosis culture and lung tissue samples were examined by immunofluorescence as follows. Samples of M. tuberculosis culture were fixed in 4% paraformaldehyde  in PBS for 30 minutes, washed in PBS then water and 1–2 µls were spotted on a glass slide. 5 µm sections of lung tissue were dewaxed in xylene and rehydrated through graded alcohols. The tissue sections and culture samples were then treated with 1 mg/ml lysozyme  and 30 U/ml achromopeptidase  in 10 mM Tris (pH 7.5) at 37°C for 40 min. Antigen retrieval was performed using the Retriever™ 2100 which pressure cooks at 121°C for 15 minutes using Target Retrieval Buffer solution S1699 . Blocking was performed with 1% goat serum in PBS  for 30 minutes. The slides were incubated at 4°C overnight with rabbit polyclonal anti-TB whole cell lysate minus LAM . Subsequently, the slides were washed using PBS and the antibody was detected with an Alexafluor 488 labeled goat anti-rabbit IgG . The slides were washed in PBS, mounted with ProLong® Gold antifade reagent  and photographed under a fluorescent microscope. When combining IF with auramine rhodamine, the coverslips were removed after IF and the slides were washed for 5 minutes in water and then stained with AR. The slides were again mounted and photographed under the same fluorescent microscope.M. tuberculosis culture and lung tissue samples were examined by auramine-rhodamine staining as follows. All samples were stained with TB Fluorescent Stain Kit T  which is a combination of auramine O and rhodamine B. Samples of M. tuberculosis culture were fixed in 4% paraformaldehyde  in PBS for 30 minutes, washed in PBS then water and 1–2 µls were spotted on a glass slide. Tissue sections were dewaxed in xylene and rehydrated through a graded alcohol series. Slides were then stained with a 1∶20 dilution of TB Auramine-Rhodamine T for 30 minutes. Slides were decolorized with TB Decolorizer TM (BD) until the stain was completely decolorized (3–5 minutes). Counterstaining was performed with hematoxylin QS  for approximately 5 seconds for tissue sections or TB potassium permanganate (BD) for in vitro samples. The slides were washed with ddH2O and mounted using ProLong® Gold antifade reagent  and reexamined using the same microscope and camera as used for IF stained slides.Extensive optimization was completed before applying IF-AR on tissue samples. Different protocols were evaluated where the sequence of AR and IF on the slides was tested either alone or in combination. Preliminary results showed that the intensity of the IF was severely reduced when the AR staining preceded the IF. In addition, AR also interfered with IF by reducing the signal when AR was applied last. Therefore, the final protocol was as follows; IF was performed first and the slides were photographed, then the coverslips were removed the slides were stained by AR and photographed again. To test this protocol and ensure that IF staining did not interfere with the subsequent AR staining, serial sections of a primary granuloma were cut and numbered. Odd numbered sections were stained with IF-AR and even numbered sections were stained with AR alone. The results showed that after IF and AR combined staining no loss of AR signal was observed when compared to AR alone.M. tuberculosis 16s ribosomal RNA. Probes used were M. tuberculosis 187 (MTB187) M. tuberculosis 223 (MTB223) (5′-CCCACACCGCTAAAGCGC-3′) and M. tuberculosis 1284 (MTB1284) (5′-GAGACCGGCTTTTAAGGATTCG-3′). Probes MTB223 and MTB1284 were newly designed in our laboratory using ARB software FISH was performed using three antisense ssDNA probes targeting M. tuberculosis culture and lung tissue samples were examined by FISH as follows. Firstly the tissue sections were dewaxed and rehydrated through graded alcohols and finally incubated in PBS. At this stage, all culture and tissue sections received the same treatment. Samples were permeabilized for 1 hour at 37°C using 10 mg/ml lysozyme  in PBS. Subsequently, the tissue sections were incubated with the prehybridization buffer for 1 hour at 37°C. Prehybridization buffer contained 20% 20X SSC , 20% dextran sulphate, 50% formamide, 1% 50X Denhardts solution , 2.5% 10 mg/ml Poly A, 2.5% 10 mg/ml ssDNA, 2.5% 10 mg/ml tRNA . After a quick rinse in 2X SSC, hybridization buffer (prehybridization buffer with probe) containing the three fluorescent rRNA probes were added to the sections, heated briefly for 5 minutes at 75°C and then incubated overnight at 37°C. All prehybridization and hybridization incubations were performed in a Hybaid OmniSlide in situ Thermal Cycler System . Thereafter, the sections were washed using a Hybaid Heated Wash Module  according to the following protocol; first a quick wash in 1X SSC at RT to remove the coverslips, followed by two washes for 15 min at 55°C with 1X SSC and another two washes for 15 min at 55°C in 0.5% SSC and finally ending with one wash for 10 min at RT in 0.5X SSC. The sections were counterstained with DAPI  and mounted in Prolong Gold .Photographs were taken on a Nikon Eclipe 80i with DAPI, FITC and TRITC filter cubes and an Optronics Microfire color fluorescent camera. Multiple photographs were taken under different focal planes when necessary and combined using Nikon NIS Elements AR 3.0 software. For confocal microscopy, a Zeiss Axio Observer confocal microscope was connected to a LSM510 META confocal laser source. A 488 nm argon laser was used with emission filter 505–550 nm. Images were captured and analyzed using Ziess LSM image analyzer version 4.0.M. tuberculosis grown aerobically to stationary phase for 55 days and cultures grown under hypoxic conditions (which is hypothesized to mimic hypoxic conditions in necrotic granulomas) for 27 days as described by Wayne in vivo samples.Samples were obtained from cultures of M. tuberculosis.Cultures were then stained with AR which showed highly fluorescent orange-red bacteria. This staining was uniform throughout the bacillus and also defined its rod-shaped form . The bacWe then evaluated whether multiple phenotypic populations could be observed under various culture conditions when combining IF with AR. This was done by comparing stained samples obtained from aerobically grown stationary culture and culture grown under hypoxic conditions. Samples were stained with the combined IF-AR procedure to simultaneously detect protein and acid-fast targets. Slides were first stained by IF and fluorescence signals (green color) were captured using a FITC filter. The slides were subsequently stained with AR (red color) and then a TRITC filter was used to capture the AR fluorescence signals. The two photographs were combined and analyzed using NIS Elements software (Nikon). Yellow signals occur when bacilli are detected by both IF and AR.M. tuberculosis were found in stationary culture; bacilli that are detected by IF alone (green color) and bacilli that are detected by IF-AR (yellow). When bacterial samples grown under hypoxic culture conditions were stained by IF-AR , AR alone (red and IF- AR+) or by the combined IF-AR technique (yellow and IF+ AR+). This dual IF-AR technique detected a higher total number of stained bacilli in hypoxic culture than using either technique alone.When IF-AR was applied to both types of culture samples, more bacilli were detected by IF than AR in both stationary and hypoxic culture. In samples from stationary phase culture, 100% of bacilli that stained positive by AR (AR+) were also positive by IF (IF+) giving a yellow color . Therefoby IF-AR , there wM. tuberculosis rRNA. Evaluation of the specificity of the two newly designed M. tuberculosis probes (MTB223 and MTB1284) was performed by fixing M. tuberculosis culture onto glass slides and detecting with FISH. When used to detect rRNA with all three probes  the bacteria appeared as positive rod-shaped signals  IF photographs of varying focal planes.The findings in this study demonstrate that in all samples M. tuberculosis populations within one microenvironment.Bacilli were shown to stain either exclusively by IF (green), exclusively by AR (red) or by both techniques concurrently (yellow). In samples from stationary phase culture, two populations of green and yellow bacilli were observed. The green bacilli were IF positive, acid fast negative (IF+ AR−) whilst the yellow population was IF+ AR+. However in hypoxic culture, three different phenotypic populations of green, red and yellow were revealed indicating that hypoxia induces phenotypic changes leading to a diverse population being detected exclusively by acid-fast AR (and therefore IF− AR+). Although previous studies have presented strong evidence indicating phenotypic alterations, this is the first study documenting the presence of multiple M. tuberculosis can alter its metabolism depending on its environment in order to survive. We hypothesized that this could be reflected in seeing different subpopulations depending on the various microenvironments mimicked in vitro and in vivo conditions. However, the results showed that under several in vitro conditions M. tuberculosis is always present as two or three different subpopulations. The same was observed in vivo, where even in the cores of the hypoxic, necrotic lesions not only one single population but three different populations of M. tuberculosis were visualized by the dual staining technique. The results suggest that M. tuberculosis may always be present in various stochastic phenotypes which could be seen as an ultimate survival strategy to adapt quickly to altering conditions M. tuberculosis persistence may be partly responsible for the difficulty of treating tuberculosis disease In mice and guinea pigs, all three subpopulations of bacilli were found homogeneous over the lung lesions studied. We estimate that, on average, about an equal proportion were present of the green and red individually stained bacilli. In addition to the single stained bacilli another subpopulation of dual stained yellow bacilli was observed which was a smaller population than either green or red. It has been a general thought that M. tuberculosis quite readily in culture and tissue sections and also stains purified cell wall components (unpublished data). Indeed, a thorough evaluation of acid-fast staining is necessary to identify the staining targets and therefore define these three different populations. Current studies are underway in our laboratory to determine which cell wall component(s) are stained by fuchsin, auramine and rhodamine.It is unclear at this time what these differences in cell wall compositions are as the exact targets of AR and IF have not been fully determined. However, in our experience, rhodamine B alone stains M. tuberculosis can alter its cell wall composition and this can lead to a loss of acid-fastness One population of bacilli was acid-fast negative. A decrease in acid-fast staining is reportedly related to mycolic acid composition. Various reports have shown that M. tuberculosis expresses a different set of surface proteins or reduces surface protein expression as the bacilli enter what is likely to be a dormant state. We are currently generating polyclonal antibodies against different stages of bacilli in order to address this question. Another reason may be protection by the polysaccharide rich capsule of M. tuberculosis which has been described by others Another population in this study was IF negative. The reason why a population is IF negative is unclear. One reason is that the anti-whole cell lysate antibodies used in this study were raised against bacilli that were in late log stage growth. It is possible that under hypoxic conditions, M. tuberculosis in vitro and in vivo by targeting M. tuberculosis 16 s ribosomal RNA. FISH yielded strong signals in hypoxic culture but resulted in only moderate signals in mice and failed to detect M. tuberculosis in guinea pigs. Of importance, these results indicate that the bacilli under the various in vitro and in vivo conditions are different in their ability to be identified by FISH. One can speculate as to why there was no signal in guinea pig tissues whereas a moderate signal was observed in mice. The lack of FISH signals in necrotic granulomas of guinea pigs could be due to a reduction of M. tuberculosis rRNA numbers in the bacteria within the necrotic lesions to below the limits of FISH detection. An alternative explanation is that the cell wall of the bacteria in these hypoxic regions might have changed and thickened, and therefore have become far less permeable to the probes used in FISH. It could also be a combination of both explanations. Of significance, these results show that the bacilli in mice and guinea pigs are not identical. Currently, we are trying to study whether the bacilli in the primary granuloma show a thickened or altered cell wall using electron microscopy, a change that has been reported in M. tuberculosis in vitroM. tuberculosis culture indicating that hypoxia alone does not decreased rRNA FISH signals. This result was also seen in another in vitro study which showed that M. tuberculosis rRNA levels were stable throughout log phase, microaerophilic nonreplicating phase I (NRP-1) and anaerobic NRP-2 stages in vitro grown bacilli under hypoxia are not identical to those found in the hypoxic, necrotic lesions of the guinea pig model.In the current study FISH was assessed for its ability to detect all populations of M. tuberculosis in vivo at a single time point after infection. It would be interesting to study whether the ratios of these different phenotypes would change over the progression of disease. An earlier published study by Seiler et al indicates that this could be the case In the present study we mainly concentrated on the cross species comparison of the location of different subpopulations of M. tuberculosis within the same microenvironment in vitro as well as in vivo reveals a new challenge. Several studies are underway trying to elucidate the microenvironments surrounding the bacilli and investigating the metabolic changes of the bacilli in these microenvironments by genomic, proteomic, metabolomic and lipidomic methodologies. A vast array of information will be gained by these studies. Although the field has started to recognize that these studies should not look at entire lungs because of differences between lesion types in most larger animal models, the results presented here indicate that the task might even be far more complicated. In order to assess an accurate measurement of protein, lipid or genetic profile of the bacilli it might be necessary to look at a per-cell basis with new technologies.The discovery of multiple phenotypes of


Altered androgen hormone homeostasis and androgen receptor (AR) activity have been implicated in ovarian carcinogenesis but the relationship between AR expression in ovarian cancer and clinical outcome remains unclear.In this study, the prognostic impact of AR expression was investigated using immunohistochemistry in tissue microarrays from 154 incident cases of epithelial ovarian cancer (EOC) in the prospective, population-based cohorts Malmö Diet and Cancer Study and Malmö Preventive Project. A subset of corresponding fallopian tubes (n = 36) with no histopathological evidence of disease was also analysed.While abundantly expressed in the majority of fallopian tubes with more than 75% positive nuclei in 16/36 (44%) cases, AR was absent in 108/154 (70%) of EOC cases. AR expression was not related to prognosis in the entire cohort, but in the serous subtype (n = 90), AR positivity (> 10% positive nuclei) was associated with a prolonged disease specific survival in univariate  and multivariate  analysis, adjusted for age, grade and clinical stage.AR expression is considerably reduced in EOC as compared to fallopian tubes, and in EOC of the serous subtype, high AR expression is a favourable prognostic factor. These results indicate that assessment of AR expression might be of value for treatment stratification of EOC patients with serous ovarian carcinoma. Epithelial ovarian carcinoma (EOC) is the second most common and the most lethal malignancy of the female reproductive tract . EtiologWhile several immunohistochemistry (IHC)-based studies have confirmed widespread AR expression in EOC -8, data in vitro data described above [The purpose of this study was to analyze the prognostic impact of AR expression in 154 EOCs collected from two population-based, prospective cohorts. Based on the ed above , our hypst 2007 were collected and histopathologically re-evaluated. The MDCS was initiated in 1991 and enrolled 17035 healthy women [Tumors (n = 154) from all incident cases of invasive EOC that had occurred in two prospective, population-based cohorts, the Malmö Diet and Cancer Study (MDCS) and Malmhy women . The MPPhy women .The standard surgical management was a total abdominal hysterectomy, bilateral salpingo-oophorectomy and omentectomy with cytological evaluation of peritoneal fluid or washings. Routine pelivic lymphadenectomy was not performed. Residual disease was resected to less than 1 cm where possible. Volume of residual disease was not availabe. Standard adjuvant therapy was combination of paclitaxel and platinum-based chemotherapy.Median age at diagnosis was 62 (range 47-83). Information on cause of death was obtained by matching with the Swedish Cause-of-Death Registry. After a median follow-up of 2.67 years (Range 0-21.14 years) 105 patients were dead, 98 from ovarian cancer. Approval was obtained from the Ethics committee at Lund University (Ref no 335-08) Study design, methodological and technical considerations, as well as data presentation were based on the REMARK criteria TMAs were constructed as previously described. Two 1.0Four μm TMA-sections and 3μm full-face sections were deparaffinised and rehydrated. Heat mediated antigen retrieval (pH = 9) was performed using the PT-link system and IHC was performed in the DAKO Autostainer system  using mouse monoclonal anti-AR antibody , anti-ER antibody , and anti-PR antibody .To control for heterogenous expression patterns, IHC was also performed on full-face sections from 15 randomly selected cases and compared to corresponding cores. AR expression was also examined on full-face sections from fallopian tubes obtained from 10 patients who had undergone hysterectomy for benign disease.2test were used to estimate the relationship between AR expression and clinicopathological parameters. Kappa-statistics were used as a measure of agreement between scoring of tissue cores and full-face sections. Kaplan-Meier analysis and log rank test were used to illustrate differences in ovarian cancer specific survival (OCSS) between strata. Cox regression proportional hazards models were used to estimate the relationship between survival and AR status, age, stage and grade. All calculations were performed using SPSS version 17.0 . P values < 0.05 were considered statistically significant.Spearman's Rho correlation and the χThirty-six of the 38 fallopian tubes were suitable for analysis. AR protein expression was evident in the majority of fallopian tubes with > 75% positivity seen in 44% n = 16) of cases  and metastatic deposits (n = 33) were suitable for analysis. Compared to tubal epithelium, AR protein expression was lower in primary tumors and metastases, with absent expression in 70% (n = 108) of primary tumors and 67% (n = 22) of metastatic deposits , suggesting that AR is a suitable protein for TMA-based analysis.No significant association was evident between AR expression in primary tumors and conventional clinicopathological parameters in the entire cohort n = 154)  revealed no relationship between increased AR expression (> 10%) in primary tumors and outcome Figure . HoweverEvaluation of AR protein expression in 154 EOC cases from two large, prospective population-based studies demonstrated frequent expression of AR in fallopian tube epithelium irrespective of the presence of ovarian cancer and decreased AR expression in primary ovarian tumors and metastatic deposits. While not conferring a prognostic value within the entire cohort, reduced AR expression was an independent predictor of decreased OCSS in serous tumors. The main limitation of this study is the absence of data on residual disease and future studies of AR expression in EOC should incorporate this in any multivariate analysis.et al. who reported PR, but not ER or AR expression as an independent predictor of good prognosis [While associated with AR expression, neither ER nor PR expression correlated with survival in this study. Such findings contrast with Lee rognosis . In theirognosis . These fAlthough androgen receptors are expressed in normal ovarian surface epithelium, we are This is to our knowledge the first report on AR expression in EOC from population-based cohorts, potentially representing a selected part of the background population. Nevertheless, as established prognostic parameters, i.e. clinical stage and histological grade, are highly significant indicators of survival in this cohort, its use for assessment of investigative prognostic markers is justified.These data demonstrate that AR is an independent marker of prolonged OCSS in patients with serous carcinoma of the ovary, and thus a potentially relevant biomarker for treatment stratification in this subgroup. Our findings also highlight the need for further studies investigating the influence of both lifestyle-related and genetic factors in relation to ovarian cancer risk in general and to AR-defined subtypes in particular.AR: Androgen Receptor; EOC: Epithelial Ovarian Cancer; OCSS: Ovarian Cancer Specific Survival; TMA: Tissue Microarray; IHC: Immunohistochemistry; ER: Estrogen Receptor; PR: Progesterone ReceptorThe authors declare that they have no competing interests.BN carried out the immunohistochemical analysis, performed the statistical analysis, and drafted the manuscript. NZ and EN carried out the immunohistochemical analysis and drafted the manuscript. JB collected the clinical data. JM participated in collection of clinical data and drafted the manuscript. DB performed the statistical analysis and drafted the manuscript. KJ participated in the conception and design of the study, performed the histopathological re-evaluaton and drafted the manuscript. All authors read and approved the final manuscript.


Arabidopsis thaliana.Grapevine is subjected to numerous pests and diseases resulting in the use of phytochemicals in large quantities. The will to decrease the use of phytochemicals leads to attempts to find alternative strategies, implying knowledge of defence mechanisms. Numerous studies have led to the identification of signalling pathways and regulatory elements involved in defence in various plant species. Nonexpressor of Pathogenesis Related 1 (NPR1) is an important regulatory component of systemic acquired resistance (SAR) in NPR1 gene were found in the two sequenced grapevine genomes available in the Genoscope database for line 40024 and in the IASMA database for Pinot noir ENTAV 115. We named these two NPR1 genes of Vitis vinifera : VvNPR1.1 and VvNPR1.2. A PCR-based strategy with primers designed on exons was used to successfully amplify NPR1 gene fragments from different Vitaceae accessions. Sequence analyses show that NPR1.1 and NPR1.2 are highly conserved among the different accessions not only V. vinifera cultivars but also other species. We report nucleotide polymorphisms in NPR1.1 and NPR1.2 from fifteen accessions belonging to the Vitaceae family. The ratio of nonsynonymous to synonymous nucleotide substitutions determines the evolutionary pressures acting on the Vitaceae NPR1 genes. These genes appear to be experiencing purifying selection. In some of the species we have analysed one of the two alleles of NPR1.1 contains a premature stop codon. The deduced amino acid sequences share structural features with known NPR1-like proteins: ankyrin repeats, BTB/POZ domains, nuclear localization signature and cysteines. Phylogenetic analyses of deduced amino acid sequences show that VvNPR1.1 belongs to a first group of NPR1 proteins known as positive regulators of SAR and VvNPR1.2 belongs to a second group of NPR1 proteins whose principal members are AtNPR3 and AtNPR4 defined as negative regulators of SAR.Two putative homologs of NPR1.1 and NPR1.2 are highly conserved among different accessions in the Vitaceae family. VvNPR1.1 and VvNPR1.2 are phylogenetically closer to the group of positive or negative SAR regulators respectively.Our study shows that This article was reviewed by Fyodor Kondrashov, Purificación López-García and George V. Shpakovski. Vitaceae family consists of approximately 700 species classified in 14 genera. Ampelopsis and Parthenocissus are two genera related to each other. The genus Vitis has been divided into two distinct sections called Euvitis and Muscadinia ", the term "mutations" was used because it is a general conclusion.We have sequenced a pool of three individuals for each species. Each PCR products was sequenced once. When polymorphism appeared after the first sequencing reaction, the PCR products were ligated into a vector and sequenced six times to generate the two polymorphic alleles, separately. We estimated that this pool is sufficient to represent the whole species studied because grapevine is multiplicated by vegetative propagation. Moreover, our reference 40024 line was also sequenced according to the same procedure, compared to the sequence available on the Genoscope database and no difference was observed. If an allele was identical to our reference but the other one was different, we took account to the polymorphic allele to consider a maximum diversity.The sentence "The NPR1 sequences  to synonymous (silent substitution) nucleotides was determined." Clearly, the word "nucleotides" should be either "substitutions" or "polymorphisms". Another such misconception is the claim that Kn/Ks < 1 can signify a recent selective sweep. I disagree: the only other thing it can signify besides negative selection is different mutation rates of synonymous and nonsynoymous sites. Even more unfortunately, is that the authors really mean Pn/Ps  throughout the manuscript and use "substitutions" (which are fixed differences) instead of "polymorphisms" (which are still segregating in the population). Also, instead of using "accessions" some other term, for example "strain" should be used: one cannot extract DNA from an accession.The language: Another unfortunate aspect of this manuscript is that it is littered with terminological inconsistencies. For example the authors say "To examine the evolutionary pressures acting on the The manuscript was improved in response to these observations in particular to "recent selective sweep" where we are agreeing with Dr Kondrashov. This sentence was suppressed.Author's response: The "accession" is frequently used in wine-growing. This term indicates a grape variety, a variety or a clone.et al., submitted to Biology Direct. Bergeault et al. identify two homologues of Arabidopsis NPR1 genes, known to be involved in general systemic resistance against pathogens or herbivores, in the genome of the grapevine Vitis vinifera. They subsequently design specific primers and amplify the corresponding genes from various grapevine cultivars. The analysis of those genes show a low level of polymorphism and, based on a ratio of synonymous versus non-synonymous substitutions lower than 1, the authors conclude that these genes are under purifying selection. Overall, the work is clear and appears well conducted. However, I think that the structure and writing of the manuscript may be improved. A few suggestions follow.Review of the article "Low level of polymorphism in two putative orthologs of NPR1 genes in the Vitaceae family by Bergeault In particular, there are many figures, some of which could be eliminated without loss of essential information. This is the case of figure V. vinifera is rather speculative in the absence of actual functional data and could be significantly shortened.The long discussion about the potential functions of NPR1 genes in V. vinifera cultivars SNP rate to introns was not significantly different to exons". Why? Could this suggest that the low SNP observed is not  due to purifying selection but to other kind of constraint acting on that particular genomic region?Bergeault et al. observed that "in six Minor comments:V. vinifera and their general genomic characteristics.- First paragraph of Background. Some references should be added. Readers may be not familiar with - Page 12, last line before "Functional hypothesis...". Sexual instead of sexuel.- Page 15, "high homology values". This expression is incorrect. Homology is an all-or-nothing quality. Either two genes are homologous (derive from a common ancestor) or they are not. "High similarity or identity values" would be more appropriate.The manuscript was improved in response to these very useful comments. In answer to the question concerning the SNP rate to introns, it is not significantly different to exons and this for the 3 introns which compose each gene. We suppose indeed that it is due to purifying selection since it is observed in 3 introns in six V. vinifera.Author's response: For the incorrect expression in the minor comments, this sentence was suppressed.NPR1 [Nonexpressor of Pathogenesis Related 1]-like genes' polymorphism in different species of the Vitaceae family. Grapevine is subjected to numerous stresses , and new knowledge on its defence mechanisms (NPR1 gene is one of the main component of systemic acquired resistance [SAR] in plants) certainly will be beneficial both for scientific community and for human society in general. The main finding of the manuscript is the fact that family of NPR genes in Vitis vinifera and probably in all other plants consists of at least 3 separate branches. These 3 subfamilies of NPR genes in plants exemplified in Arabidopsis thaliana by AtNPR1, AtNPR3 and AtNPR5 (BOP) genes, respectively. Analysis of nucleotide polymorphisms in two NPR1-like genes from fifteen accessions belonging to the Vitaceae family indicate that the genes are under purifying selection, but the AtNPR1 ortholog (VvNRP1.1) is more polymorphic. A tentative hypothesis of authors about two types (positive and negative) of regulation by different subfamilies of NPR1-genes although is interesting, but certainly needs some further experimental support. The revised version of the manuscript takes the suggestions that I previously made into account. The changes in the revised manuscript and the new title help to clarify the aim of the manuscript considerably. In my opinion, it would be better to re-name Vitis genes described by the authors on VvNRP1, VvNRP3 and VvNRP5 instead of VvNRP1.1, VvNRP1.2 and VvBOP at it is in the text. The manuscript might need some additional editing and proofreading.This is my second review of this manuscript (my previous comments were addressed by the authors in their new manuscript submission). The authors report the results of an experimental (PCR-based) and computational study of We are grateful to Dr Shpakovski for his comments and notice very judicious. Indeed, the hypothesis about their functions is essentially based on a work on literature. But, we think that it was interesting to discuss the two types of SAR regulation. Moreover, we indicate in the manuscript "Therefore, phylogenetic analysis is not sufficient to predict a positive or negative control of defence responses for VvNPR1.2."Author's response: With regard to re-name Vitis genes, another classification would make confusion. For example, where are VvNPR2 and VvNPR4? Moreover, we have at present no data concerning VvNPR1.2 which would act as a negative regulator of SAR and it would be premature to re-name it, VvNPR3.


Prostate cancer is the second most common malignancy in males and the leading cause of cancer death. Prostate cancer is initially androgen dependent and relies upon the androgen receptor (AR) to mediate the effects of androgens. The AR is also the target for therapy using antiandrogens and LHRH analogues. However, all cancers eventually become androgen independent, often referred to as hormone refractory prostate cancer. The processes involved in this transformation are yet to be fully understood but research in this area has discovered numerous potential mechanisms including AR amplification, over-expression or mutation and alterations in the AR signaling pathway. This review of the recent literature examines the current knowledge and developments in the understanding of the molecular biology of prostate cancer and hormone refractory prostate cancer, summarizing the well characterized pathways involved as well as introducing new concepts that may offer future solutions to this difficult problem. Prostate cancer is the commonest malignancy in men, accounting for 24% of all cancers in the UK in 2003. The treaAs a result, treatment for locally advanced and metastatic prostate cancer targets the AR by reducing the levels of androgens or by inhibiting the activation of the AR. Androgens are removed by either surgical or chemical methods using luteinising-hormone-releasing-hormone (LHRH) analogues with or without the addition of antiandrogens. Initially, prostate tumors regress in response to androgen deprivation in up to 80% of cases. However,Androgens are essential to the normal development and biology of the prostate. The majority of testosterone is produced by the testes, with a smaller contribution of androgens (5%) from the adrenal glands. These androgens are metabolized by 5α-reductase to dihydrotestosterone (DHT) which binds to the androgen receptor (AR). Ligand binding initiates phosphorylation, homodimerisation of the AR and dissociation of heat-shock proteins, allowing translocation of the AR complex to the nucleus. Here the AR binds to specific DNA sequences called androgen response elements (ARE) promoting transcription of androgen-responsive genes. Such genes control a range of cellular events such as growth, differentiation and apoptosis . The AR As hormone refractory prostate cancer continues to grow in the presence of antiandrogens the term hormone independence may be misleading as it implies that the AR is no longer required for growth. However, the AR is expressed throughout the progression of prostate cancer, including >80% of hormone refractory tumors, suggesting that AR signaling remains essential.11 It haset al demonstrated that over-expression of AR cDNA, mRNA and protein levels were the only consistent and significant differences.[Amplification of the AR gene is rarely identified in untreated cases of prostate cancer. Using comparative genome hybridization (CGH) and fluorescent in-situ hybridization (FISH), 30% of treated cases exhibited AR amplification.1415 Pati1417ferences. In patieferences.Despite medical or surgical castration, tumor levels of androgens in human prostate samples, in particular DHT, have been shown to remain at levels sufficient to transactivate the AR in cell line studies. AlthoughMutations in the AR are uncommon (0-4%) in untreated prostate cancer and those treated with surgical castration. However, in hormone refractory tumors the incidence of mutations increases by up to 50%. Over 70 Modulation of AR activity by co-repressors and co-activators The ARE-bound AR binds a number of proteins to enable efficient recruitment of the basal transcriptional machinery and transcription of androgen-regulated genes. The transcriptional activity of the AR is enhanced by co-activators and inhibited by co-repressors although some proteins can either promote or repress transcription depending upon the cellular context. Co-activ37et al[et al found no significant difference in expression.[The p160 co-activators are known to interact with CREB-binding protein (CBP) and its homologue p300 which have intrinsic HAT activity.40 The pret al showing pression. As yet npression.et al found a decrease in the median expression of SRC-1 suggesting that sample collection, processing and the sensitivity of the detection method may influence co-activator expression studies.[Probably the best characterized co-activator of the AR is SRC-1. In cell line studies reduction of SRC-1 expression significantly reduced growth and altered AR target gene regulation in the LNCaP cell line whereas it had no effect on the growth of the AR-negative PC-3 and DU145 prostate cancer cell lines, further emphasizing the need for an intact AR.45 However, studies.GRIP-1/TIF-2 has previously been shown to bind the steroid receptors including the AR via its LBD and promote transcription of androgen-regulated reporter genes. The AR mutation N727K results in sub-fertility at least in part by abrogating GRIP-1/TIF-2 binding. Using domain constructs it was shown that GRIP-1/TIF-2 enhances AF-2 but not AF-1 mediated AR transactivation. BicalutaExpression of RAC-3  was higher in prostate cancer cell lines expressing the AR and has been shown to promote ligand-independent activation of the Akt pathway. RAC-3 mRNA and protein expression in prostate cancer cells has been shown to correlate with tumor grade and stage and increased expression correlates with poor survival in clinical studies.Adaptor proteins associated with receptor internalization at the cell surface have also been reported to be prostate cancer biomarkers and to act as transcriptional co-regulators. Two examples of these proteins are Huntingtin Interacting Protein 1 (HIP1) and cyclin G-associated kinase (GAK), both of which were initially implicated in clathrin-mediated receptor trafficking.52 Subseq535554Steroid receptor activity can also be modified by co-repressors which inhibit transcription by blocking co-activators binding and recruiting histone deacetylases (HDACs) and repressor proteins such as Sin3A. This HDA59Classically, activation of the AR via the binding of androgens initiates receptor phosphorylation and/or acetylation, homodimerization dissociation of heat-shock proteins, allowing translocation of the AR complex to the nucleus. The AF-1 region of the N-terminal of the AR can be activated even in the absence of ligand thereby circumventing current hormonal therapies. Ligand-independent activation induces phosphorylation and acetylation of the AR altering its conformational and subsequent transactivation. Phosphorylation increases AR stability and stabilizes AR homodimers increasing AR signaling without ligand. However,The PI3K-Akt pathway is involved in processes controlling cell growth, survival, cycle regulation and apoptosis. Following growth receptor activation, PI3K phosphorylates phosphatidylinositol -bisphosphate (PIP2) to phosphatidylinositol -trisphosphate (PIP3). Akt and its activating kinases, phosphoinositide-dependent kinases 1 and 2 (PDK1 and PDK2), then localize to the membrane. Here, activated Akt can activate a myriad of substrates and consequently a vast number of intracellular events including phosphorylation of AR. A recentet al reported that although there was a slight increase in ERK and p38 in well-differentiated cancers, cells from hormone refractory prostate cancer had reduced or absent activated expression of isoforms.[et al found a decrease in activated form phospho-MAPK/ERK in high-grade tumors.[Mitogen-activated protein kinases (MAPK) are a family of serine/threonine protein kinases involved in many cellular programs such as cell proliferation, cell differentiation and apoptosis. The MAPK signaling cascades are organized hierarchically into three-tiered modules: MAPK-kinase kinases (MAPKKKs) are in activated by interaction with the family of small GTPases and/or other protein kinases. MAPKKKs are phosphorylated and activate (MAPKKs), which in turn phosphorylate and activate MAPK-kinases (MAPKs). The MAPK pathways terminate with the proteins JNK, ERK and p38 which are known to be involved in both anti- and pro-apoptotic processes. There is conflicting evidence regarding the significance of the MAPK pathway in prostate cancer progression. Initial reports suggested a significant correlation between the activation of MAPK enzymes ERK1 and ERK2 and tumor grade, with 70% of high-grade tumors exhibiting activation. In two pisoforms. Furtherme tumors.Her-2/Neu is known to play a significant role in the progression of breast cancer raising interest in this molecule as a potential target in prostate cancer. Her2/Neu can activate AR via the MAPK and PI3K-Akt pathways and over-expression in LNCaP cells inhibits growth arrest by 35% compared to wild-type LNCaP cells. The potential importance of Her-2/Neu was highlighted in a xenograft model used to produce progressively more androgen-independent tumors, in which the level of Her-2/Neu expression increased 25-fold. This is reinforced by human immunohistochemical studies that demonstrate a significantly positive correlation between Her-2/Neu expression and hormone independent status when comparing hormone-naïve and advanced hormone refractory disease.71et al compared biopsy samples from the same patient taken before and after the development of hormone refractory disease and found a significant increase in EGFR from 23 to 43% after hormone relapse.[Growth factors and their receptors have previously been shown to be essential for prostate growth and differentiation during development, in particular FGF-7 and 10. FGF-8 an relapse. Other st relapse. While thIn addition to growth factor signaling other extracellular proteins are known to activate cell surface receptors and the AR. The best characterized of these proteins is interleukin-6 (IL-6), a cytokine previously linked to a number of malignancies including renal, myeloma and prostate. IL-6 has wide-ranging cellular effects consistent with activation of multiple pathways including MAPK and PI3-Akt. Cell studies have confirmed that IL-6 can induce ligand-independent AR transactivation via a mechanism which is blocked by bicalutamide and inhibitors of MAPK and protein kinase A. When IL-2β1 and CD133 as markers.[The classical stochastic model of cancer development is based on the theory that every cell within a tumor has the potential to form a new tumor colony. However, the stem cell model of tumorigenicity proposes that it is a minority of specialized stem cells that give rise to cancer cells. Prostate markers. However,The development and progression of prostate cancer is a complex process. The androgen signaling pathway and its interaction with other pathways impacts on cellular processes from growth, cell cycle, differentiation to growth arrest and apoptosis. Through adaptation and alteration cells become tumorigenic. Initially this process can be halted by manipulating the cells’ requirement for androgens although eventually this treatment fails and cancer cells resume growth. The terms ‘androgen independent’ and ‘hormone refractory’ may be misnomers as the AR appears to maintain a role in cancer progression as demonstrated by its continued and even increased expression. There is also evidence that despite castration, both surgical and medical, the prostate retains a level of androgen that is high enough to induce AR transactivation in prostate cancer cell lines. The AR mutations and over-expression also enable transactivation to occur at low levels of androgen as well as decreasing ligand specificity. The upregulation of co-activators and possible downregulation of co-repressors further potentiate these effects. Alternative pathways involving growth factors and receptors and IL-6 have been shown to interact with the androgen signaling pathway enabling transactivation to occur even in the absence of ligand.These processes are unlikely to operate independently. In fact the heterogeneity of prostate cancer, both hormone-naïve and hormone refractory, indicate that a multifactorial, multistep process is the most plausible. This could be a double-edged sword. The presence of numerable potential targets and markers is encouraging, particularly if tumor profiling can be utilized. However, it is also an indication of the likely complexities to be faced when designing therapies for the multiple types of prostate cancers. Recent advances have highlighted many potential and targets for pathway inhibition. By targeting multiple pathways, including AR signaling, it is feasible that it may possible to treat patients with tumor-specific ‘tailor-made’ therapies in the future.