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Microarray coupled to quantitative RT–PCR analysis of androgen-regulated genes in human LNCaP prostate cancer cells

Abstract

The androgen receptor (AR) mediates the growth-stimulatory effects of androgens in prostate cancer cells. Identification of androgen-regulated genes in prostate cancer cells is therefore of considerable importance for defining the mechanisms of prostate-cancer development and progression. Although several studies have used microarrays to identify AR-regulated genes in prostate cancer cell lines and in prostate tumours, we present here the results of gene expression microarray profiling of the androgen-responsive LNCaP prostate-cancer cell line treated with R1881 for the identification of androgen-regulated genes. We show that the expression of 319 genes is stimulated by 24 h after R1881 addition, with a similar number (300) of genes being significantly repressed. Expression of the upregulated genes, as well as of 60 of the most robustly downregulated genes, was carried out using quantitative RT–PCR (Q-RT–PCR) over a time-course of R1881 treatment from 0 to 72 h. Q-RT–PCR was also carried out following treatment with other AR agonists (dihydrotestosterone, estradiol and medroxyprogesterone) and antagonists (cyproterone acetate, hydroxyflutamide and bicalutamide). This study provides a comprehensive analysis of androgen-regulated gene expression in the LNCaP prostate cancer cell line, and identifies a number of androgen-regulated genes, not described previously, as candidates for mediating androgen responses in prostate cancer cells.

Introduction

Normal male development and growth requires the action of androgens. These hormones function by activating the androgen receptor (AR), a member of the ligand-activated nuclear receptor superfamily of transcription factors (Brinkmann et al., 1999; Lu et al., 2006). The importance of AR in male development is shown by the androgen insensitivity syndromes characterized by mutations in the AR gene (Gottlieb et al., 2004). The prostate is a prototypical androgen-dependent organ (Cunha et al., 1987; Davies and Eaton, 1991) and prostate cancer, which has become the most commonly diagnosed cancer in males in the western world and is the second leading cause of male cancer death, is androgen-dependent for its growth (Carter and Coffey, 1990; McConnell, 1991). Therefore, treatment is directed at inhibiting prostate cancer growth by suppressing the action of the endogenous androgen or its production. Standard treatment involves surgical or pharmacological orchidectomy or inhibition of AR activity using anti-androgens that compete with androgen for binding to AR. Following initial response, however, almost all tumours eventually progress, as reflected by the growth of androgen-independent cells and the development of hormone-refractory disease. The continued involvement of the AR in resistant disease is evident from its continued expression in a large proportion of resistant cases, as well as from the detection of AR gene amplification and activating mutations in the AR gene and/or activation of AR through crosstalk with other signalling pathways (Feldman and Feldman, 2001; Taplin and Balk, 2004; Agoulnik and Weigel, 2006).

Androgen binding by the AR leads to its recruitment to specific gene promoters and consequent regulation of gene expression (Shang et al., 2002; Dehm and Tindall, 2006). Gene-expression microarray analysis allows the global interrogation of the complete genome for the determination of changes in gene expression, thereby permitting the identification of gene networks that may be important in mediating AR-regulated prostate-cancer cell growth, thus providing a clearer understanding of the AR function in prostate cancer, and identifying new prognostic markers and therapeutic targets. In order to identify androgen-responsive genes in prostate cancer cells, we used the LNCaP cell line as it expresses AR, shows androgen-regulated expression of androgen-responsive genes, such as the prostate cancer biomarker PSA, grows in an androgen-regulated manner in cell culture and forms androgen-dependent tumours in xenograft models (Sobel and Sadar, 2005). Earlier microarray studies for profiling androgen-regulated genes in prostate cancer cell lines have been carried out using the synthetic androgen R1881 or dihydrotestosterone (DHT), but few studies have carried out a detailed investigation of AR-regulated gene expression, in response to anti-androgens (for a review see Dehm and Tindall, 2006). In addition, AR activity can be stimulated by oestrogen (E2) and progesterone, whereas the anti-androgen cyproterone acetate (CPA) is a partial agonist for AR (Doesburg et al., 1997). Finally, some AR mutations, such as the AR-T877A mutation in LNCaP cells, increase the agonist activity of some of these weak AR agonists, as well as the anti-androgens CPA and hydroxyflutamide (OHF) (Steketee et al., 2002). However, detailed analysis of the expression of androgen-regulated genes in response to the weak agonists and AR antagonists !been confined, by and large, to reporter gene studies (Brooke et al., 2008).

To gain new insight into the regulation of gene expression by AR, we carried out microarray profiling in LNCaP cells treated with R1881 and Q-RT–PCR analysis for the genes whose expression is stimulated and for a proportion of the genes whose expression is inhibited by R1881, over a time course of R1881 treatment, and after the treatment of LNCaP cells with other agonists and anti-androgens.

Results and discussion

Identification of genes whose expression is regulated by R1881

To perform gene-expression microarray analysis of prostate-cancer cells treated with the synthetic androgen R1881, RNA prepared from three bio-replicate cultures of LNCaP cells treated with R1881 for periods of time ranging from 4 to 72 h was evaluated for the R1881 stimulation of expression of four well-characterized androgen-regulated genes (PSA, TMPRSS2, NDRG1 and GREB1). Expression of these genes was stimulated within 4 h after R1881 addition and levels continued to increase up to 24 h, after which time expression was reduced, but remained high up to 72 h (Supplementary Figure 1). On the basis of these results, RNA from each of the three replicates, for 24-h time points, was chosen for hybridization to the Applied Biosystems (ABI, Foster City, CA, USA) human genome survey microarray V2.0, which has probe sets for 29 098 genes. Raw data were quality-assessed and filtered according to the recommendations in the ABI1700 data analysis user guide and the filtered data were ‘vsn normalized’ (Huber et al., 2002). Differential expression was assessed using linear models and empirical Bayes algorithms as described (Smyth, 2004). This analysis defined 452 probes whose expression was stimulated by androgen by two-fold or greater, with positive lod scores (B values) for differential expression. We also identified 382 probes whose levels were inhibited by androgens by the same margins. Of these, 133 probes from the upregulated set and 82 probes from the downregulated set were removed from further evaluation as they represented genes that were unassigned, or represented multiple probes for the same gene. This resulted in a list of 319 and 300 annotated genes whose expression is up- and downregulated by R1881, respectively (Supplementary Table 1).

Functional categories and pathways for genes regulated by R1881

As described above, 70% of the upregulated genes and 78% of the downregulated genes encode proteins with a known or an inferred function. These gene lists were analysed for gene ontology (GO) within the ‘molecular function’ principal group (http://www.geneontology.org/). In order to maximize information from this analysis, gene ontology classifications for subcategories within the two largest categories; namely ‘binding’ and ‘catalytic activity’, were also determined. The collective results from this ontology analysis show that 38 gene ontology classifications are represented, which, by proportion, show a similar distribution in the R1881 upregulated and downregulated gene sets (Figure 1a). The exception to this is the signal transducer activity grouping (GO: 4871), which functionally represents a higher proportion of R1881 downregulated genes (4.6% representation in the upregulated gene set, compared with 9.3% in the downregulated set).

Figure 1
figure1

Functional categorization of genes regulated by R1881. (a) The genes showing >2-fold regulation in LNCaP following the addition of R1881 for 24 h were analysed for gene ontology (GO) (http://www.geneontology.org/). The number of genes in each molecular function group is shown as a percentage of all genes whose expression was stimulated by R1881, whereas genes whose expression was repressed by R1881 are shown as a percentage of genes in the GO category, relative to all the repressed genes. (b) Functional analysis of all R1881-regulated genes was carried out using the database for annotation, visualization, and integrated discovery (DAVID) resource (http://david.abcc.ncifcrf.gov/). The functional annotation clusters are shown as Pathways and Keywords/Features that had enrichment scores of 1.0, together with the number of genes represented in each cluster. CRD, Cysteine rich domain; PPAR, peroxisome proliferator-activated receptors.

The R1881 upregulated and downregulated gene lists were further combined to generate an R1881 regulated gene set and were analysed by functional annotation, using web-based tools provided by the Database for Annotation, Visualization, and Integrated Discovery (DAVID) resource (http://david.abcc.ncifcrf.gov) (Dennis et al., 2003; Huang da et al., 2007). This resulted in the identification of 64 functional annotation clusters with enrichment scores in the range 0.01–2.43, with three functional pathway clusters having enrichment scores >1 (Figure 1b).

The most significant functional-pathway cluster identified within this gene list was found to be one in which major determinants of the transforming growth factor (TGF)-β signalling pathway, including SMAD1, SMAD3, SMAD6 and SMAD7, were downregulated, whereas ID3, a candidate gene for metastatic prostate cancer (Burmester et al., 2004; Yuen et al., 2006), was upregulated. Although it has been reported that TGF-β signalling is downregulated in prostate cancer, this has largely been attributed to transcriptional regulation of TGF-β expression by AR (Qi et al., 2008), or through direct interaction of AR with SMADs, leading to inhibition of SMAD DNA-binding activity (Chipuk et al., 2002). The microarray analysis carried out here suggests that in addition to these mechanisms, androgen treatment causes a programmed inhibition of TGF-β signalling, primarily through the downregulation of key signal transduction molecules, including SMADs, and further highlights the importance of this pathway to androgen-mediated prostate-cancer cell growth and survival (Guo et al., 1997; Guo and Kyprianou, 1998, 1999).

Fatty-acid metabolism was also highlighted as an important pathway, with 16 genes being identified in this cluster. Thirteen of these genes including those for the peroxisomal enzymes acetyl-CoA acyltransferase 1 (ACAA1) and fatty acyl-CoA oxidase 3 (ACOX3), were upregulated by R1881, whereas the gene of acetyl-CoA acyltransferase 2 (ACAA2), a mitochondrial enzyme, was found to be one of the three downregulated genes in this set. This suggests that androgens preferably stimulate peroxisomal over mitochondrial branched-fatty acid β-oxidation, this being consistent with earlier observations, which show that peroxisomal branched-fatty acid β-oxidation is upregulated in prostate cancer (Zha et al., 2005), with this pathway being active in regulating prostate cancer cell growth (Zha et al., 2003). The importance of peroxisomal function as being a new androgen-regulated target is further emphasized by our finding that 10 of the 16 genes in the fatty acid-metabolism functional cluster are assigned to this organelle.

The third most significant pathway involved genes required for steroid biosynthesis. Androgen regulation of steroid-biosynthesis genes is mediated through an indirect mechanism involving the activation of sterol regulatory-element binding proteins SREBP-1 and SREBP-2 (Heemers et al., 2006). Further, kruppel-like factor 5 (KLF5) has recently been identified as an androgen-regulated gene that acts as a positive regulator of SREBP-1 function (Lee et al., 2009). In agreement with these reports, expression of SREBP-1 and SREBP-2 was not androgen-regulated in our microarray analysis, whereas KLF5 expression was stimulated 3.1-fold by R1881.

An additional eight groupings with enrichment scores 1.0 were highlighted by the DAVID analysis. These groupings feature genes with similar functions, rather than diverse genes associated with distinct pathways, and include several enzyme groups, such as phosphatases, transferases and proteins associated with secretion (endoplasmic reticulum and Golgi transport).

Quantitative RT–PCR for determining time-course of gene regulation by R1881

Real-time Q-RT–PCR was carried out for the R1881 genes identified above, using the low-density array micro-fluidic cards from ABI, which allow simultaneous Q-RT–PCR for up to 384 genes. Q-RT–PCR primers were not available for 10 of the 319 upregulated genes, hence low-density array cards were designed, containing 309 of the upregulated genes, as well as 62 genes showing the highest significance scores for downregulation by R1881, together with control genes (GAPDH, RPLPO). Q-RT–PCR was carried out for three replicate RNA preparations from LNCaP cells treated with R1881 for 0, 4, 8, 16, 24, 48 and 72 h. Fold expression relative to the control (0 h) was determined for each gene, and cluster analysis was used to determine patterns of R1881 regulation. No expression was detected for 22 of the upregulated genes and 2 of the downregulated genes at the 0-h time point. These genes were therefore excluded from further analysis, as it was not possible to make a measurement of their relative regulation by ligand. As seen in the heat maps for the up and downregulated genes (Figures 2a–c), 287 up-regulated genes could be clustered into seven groups, labelled U1–U7, and as three clusters in the downregulated gene set (see Supplementary Table 2 for names of the genes in each cluster). Plotting the average profile for each of these clusters indicates that the expression of the genes in cluster U5 is rapidly stimulated by R1881, reaching a peak at 24 h, after which time expression generally plateaus (Figure 2d). A similar profile is obtained for clusters U3 and U6, except that these clusters represent genes whose average expression reaches a considerably lower maximum than those observed for U5. U2 is interesting as expression is stimulated early, peaks at 24 h and subsequently falls to near-basal levels by 48 h. Finally, clusters U1, U4 and U7 appear to represent genes whose expression increases slowly over the time course; these genes could therefore represent indirectly androgen-regulated genes. There was little to distinguish the 60 downregulated genes, as most of the genes follow a similar time course, with repression being seen within 4–8 h, and near maximal repression being reached 16 h after R1881 addition (Figure 2e). This suggests that many of these genes represent direct targets for AR.

Figure 2
figure2

Analysis of quantitative RT–PCR for 368 androgen-regulated genes over the time course of R1881 treatment. (a) The results of quantitative RT–PCR (Q-RT–PCR) for 287 genes whose expression was stimulated >2-fold at 24 h following R1881 addition in the microarray analysis. Q-RT–PCR was carried out using TaqMan gene expression assays for three separate RNA preparations from LNCaP cells treated with 1 nM R1881 for 0, 4, 16, 24, 48 or 72 h. Fold changes in expression were determined relative to the no-ligand (0 h R1881) control. The genes were clustered using a standard correlation algorithm (GeneSpring Software, Agilent Technologies, Stockport, UK). Upregulated genes are shown in red, downregulated genes in green, non-changing genes in black, and genes for which there was no expression after 40 cycles are shown in grey. (b) The cluster analysis for Q–RT–PCR using Taqman gene expression assays for 60 genes identified from the microarray analysis as being downregulated by R1881 by >2-fold. (c) Colour scale corresponding to fold change in gene expression. (d, e) Average fold expression for all of the genes in each of the major clusters labelled in (a) and (b) is shown in the form of line graphs.

Quantitative RT–PCR for determining androgen agonist and antagonist regulation of the identified genes

Earlier gene profiling studies in LNCaP cells have focused on changes in gene expression upon the addition of R1881 or DHT (Dehm and Tindall, 2006). However, the AR is also activated by E2, as well as by progestins such as medroxyprogesterone acetate (MPA) (Brooke et al., 2008). In order to determine whether the different AR agonists act in a similar manner to regulate the expression of androgen-responsive genes, a Q-RT–PCR was carried out for the 347 androgen-regulated genes described in the section above, using total RNA prepared in triplicate from LNCaP cells following addition of DHT, E2 or MPA for 24 h. In addition, LNCaP cells were treated for 24 h with the selective androgen-receptor modulators (SARMs) CPA and OHF, which show mixed agonist/antagonist activities, and with the anti-androgen bicalutamide (BIC), also known as casodex, which has little or no agonist activity for AR (Brooke et al., 2008).

When the Q-RT–PCR data were analysed relative to the no-ligand control, most of the genes whose expression was stimulated by R1881 were also stimulated by DHT, although the level of regulation by DHT was generally lower than that for R1881 (Figure 3a). Interestingly, a small number of genes whose expression was stimulated by R1881 were repressed by DHT. The DHT-repressed genes were also repressed by the other AR activators, E2 and MPA, as well as by the anti-androgens. E2, MPA, CPA and OHF also stimulated the expression of most R1881 upregulated genes. LNCaP cells express oestrogen receptor β (ER-β), but not ER-α (Lau et al., 2000), although other studies indicate that ER-α is also expressed in LNCaP cells (Takahashi et al., 2007). In addition to direct binding of E2 by AR, it is therefore possible that some of the AR-regulated genes analysed here are also directly regulated by ER, for example GREB1 (Rae et al. 2006). An alternative mechanism by which ER regulates the expression of AR-regulated genes through interaction with AR has also been described (Arnold et al., 2007; Takahashi et al., 2007). In addition to their regulation by direct E2 binding to AR, it is possible therefore that the E2 regulation of androgen-responsive genes involves direct or indirect binding of E2–ER to promoters of androgen-responsive genes. The progestin MPA is also able to stimulate AR activity, and MPA treatment resulted in the stimulation of many of the R1881-regulated genes. As progesterone receptor (PR) and AR bind to similar DNA motifs, it is possible that PR directly regulates the expression of AR-regulated genes. Indeed, PR expression in LNCaP cells has been reported (Lau et al., 2000); hence MPA regulation of our gene set could be because of MPA stimulation of PR, as well as of AR. Interestingly, the SARMs (CPA, OHF) stimulated the expression of a larger proportion of the upregulated genes than E2 or MPA. Expression of the R1881 downregulated genes was also repressed by the other ligands (Figure 3b). Cluster analysis highlighted five groups (labelled L1–L5; see Supplementary Table 3 for the genes in each cluster). No clear breakdown could be achieved for the R1881 downregulated genes. The cluster analysis divided the R1881 upregulated genes into two broad groups: those genes whose expression is strongly stimulated by DHT (cluster L5), and those genes more which are weakly activated by DHT (L1–L4). Cluster L5 contained the majority of the genes showing rapid stimulation by R1881, with 22/40 (55%), 8/13 (61%) and 41/56 (73%) of the genes clustered in groups U2, U3 and U5, respectively, indicating that the genes showing the most potent R1881 regulation are also activated by other agonists and by SARMs. Among the genes weakly activated by DHT, genes in clusters L1 and L3 were stimulated by SARMs but not by E2 or MPA, whereas groups L2 and L4 contained genes whose expression was not stimulated by E2, MPA, or by CPA and OHF.

Figure 3
figure3

Regulation of genes identified through microarray analysis by androgen-regulated (AR) agonists and antagonists. (a) Cluster analysis of 287 R1881-responsive genes after Q-RT–PCR of three independent RNA samples prepared from LNCaP cells 24 h following the addition of R1881, dihydrotestosterone (DHT), cyproterone acetate (CPA), hydroxyflutamide (OHF), 17β-oestradiol (E2), medroxyprogesterone (MPA) and bicalutamide. Fold changes in expression were determined relative to the no-ligand (0 h R1881) control. The clusters L1–L5 are also shown. (b) The cluster analysis for Q–RT–PCR data for the RNA samples described in (a) for the 60 genes showing two-fold or greater repression at 24 h after R1881 addition in the microarray analysis. (c) Colour scale corresponding to fold change in gene expression.

Androgen and anti-androgen regulation of selected genes

The genes identified in the microarray analysis included genes identified earlier as being androgen-regulated. These included the KLK3 or PSA gene, a commonly used biomarker for prostate cancer, whose expression was maximally stimulated 12-fold at 24 h with R1881 (Figure 4). E2, MPA, CPA and OHF also stimulated KLK3 expression (Figure 5). KLK3 clustered in group U5, which contains the genes reaching the greatest stimulation in the R1881 time-course, and includes many androgen-regulated genes described earlier, including KLK2, NDRG1, TMPRSS2, FKBP5 and the proto-oncogene c-MAF (Nelson et al., 2002). These genes cluster to group L5 on ligand Q-RT–PCR analysis, with their expression being activated by DHT, CPA, OHF, E2 and MPA. Among the genes in cluster U5 were the prostate-derived ets factor SPDEF, which interacts with AR and with the androgen-regulated homeobox gene NKX-3.1 and regulates the expression of the KLK3 gene (Oettgen et al., 2000; Chen et al., 2002). NKX-3.1 was also androgen-regulated in our microarray, and by Q-RT–PCR its expression peaked at 24 h, then fell by 48 h (Figures 4 and 5). 15-Hydroxy-prostaglandin dehydrogenase (HPGD) was the most highly androgen-responsive gene in the microarray analysis. Q-RT–PCR showed that HPGD expression was stimulated 151-fold 24 h after R1881 addition and 271-fold at 72 h after treatment. DHT (53-fold), E2 (39-fold), MPA (52-fold), CPA (63-fold) and OHF (63-fold) stimulated HPGD expression strongly. Prostaglandins are growth stimulatory for many tumour types, with the prostaglandin-generating enzyme COX-2 being aberrantly expressed in many tumours. HPGD converts prostaglandin E2 to biologically inactive 15-ketoprostaglandins, hence acting in opposition to COX-2, and HPGD gene has been proposed as a tumour suppressor gene in colorectal and breast cancer, with epigenetic silencing of the HPGD gene being frequently observed (Myung et al., 2006; Wolf et al., 2006). hCAP-D3 is a non-SMC subunit of the condensing II complex required for mitotic chromosome assembly and segregation (Ono et al., 2003). It was ranked ninth in terms of significance of difference in expression by microarray analysis; its expression was stimulated 19-fold by R1881 at 24 h and was increased 1.3–3.9 fold with other ligands. Similarly, expression of the CXCR4 chemokine receptor, which is believed to play a role in cell motility and metastasis, and which has been implicated in many cancer types (Busillo and Benovic, 2007), including prostate cancer, was stimulated 19-fold by R1881 at 24 h, and was stimulated 1.9–2.9-fold by DHT, CPA, OHF and MPA, but was not stimulated by E2. NR4A1 is an orphan nuclear receptor that regulates apoptosis in many cancer cell types (Ke et al., 2004; Chintharlapalli et al., 2005) and whose expression is downregulated in hormone-refractory prostate cancer (Tamura et al., 2007). NR4A1 expression was stimulated 12-fold by R1881, with 1.9-3-fold stimulation by CPA, OHF, E2 and MPA. Another gene in cluster U5 that inhibits cell growth and induces apoptosis, its expression being stimulated 5.6-fold by R1881 at 24 h, was GADD45G. GADD45G is a member of the DNA damage-inducible gene family that is frequently silenced epigenetically in tumour cell lines (Ying et al., 2005). Although its expression was stimulated by R1881, GADD45G expression was inhibited 2–5-fold by the other ligands, including DHT (5).

Figure 4
figure4

Time course of expression of selected genes in gene cluster U5 upon R1881 treatment. The expression of selected genes that are grouped in gene cluster U5 is shown. The line graphs show the means and standard errors for Q-RT–PCR carried out with three independent RNA samples prepared for each time point.

Figure 5
figure5

Ligand regulation of the expression of selected genes after 24 h treatment. Fold expression of genes in Figures 4 and 6 in response to R1881, dihydrotestosterone (DHT), cyproterone acetate (CPA), hydroxyflutamide (OHF), 17β-estradiol (E2), medroxyprogesterone (MPA) and bicalutamide is shown. The bar graphs show the means of Q-RT–PCR for three independent RNA samples prepared following the treatment of LNCaP cells with ligands for 24 h.

The R1881 time-course cluster U2 (Figure 2), which represents genes whose expression is stimulated early after R1881 treatment and then falls by 48 h, included the androgen-regulated genes GREB1 (Rae et al., 2006) and NKX3-1 described earlier (Figure 6). The NKX3-1 homeobox gene is frequently deleted in prostate cancer and knockout mice are susceptible to prostatic intraepithelial neoplasia (Abdulkadir et al., 2002; Kim et al., 2002), indicating that NKX3-1 is a tumour suppressor gene in the prostate. NKX3-1 expression was stimulated 10-fold by R1881 and 3–7-fold by the other ligands (Figure 5). TWIST1, a bHLH transcription factor that is upregulated in prostate cancer (Kwok et al., 2005), was upregulated 1.9–4.3-fold at 24 h by the other ligands. ELL2 is an RNA polymerase II elongation factor (Shilatifard et al., 1997), which interacts with the transcription factor EAF2 (ELL associated factor 2) (Simone et al., 2003). Interestingly, ELL2 and EAF2 genes show strong co-regulation, clustering together in the R1881 time course and in the expression profile in response to the other AR ligands. EAF2 has also been shown to induce prostate cancer-cell apoptosis in xenograft tumours, and its expression is downregulated in prostate tumours (Xiao et al., 2003). CREB3L2 a cAMP-response element binding protein homologue that is fused to the FUS gene in fibromyxoid sarcomas (Storlazzi et al., 2003), was upregulated by R1881, but was not significantly upregulated by other AR ligands (Figure 5). Serum/glucocorticoid-induced protein kinase-1, which stimulates AR activity and is important for prostate cancer-cell growth, is itself androgen-regulated (Shanmugam et al., 2007), with rapid stimulation in its expression, which peaked at 24 h (25-fold) and decreased to near basal levels by 48 h. Interestingly, DHT did not stimulate serum/glucocorticoid-induced protein kinase expression at 24 h, whereas its expression was stimulated 2-, 5-, 1.8- and 3.9-fold by CPA, OHF, E2 and MPA, respectively. The protein kinase C-α subunit was similarly upregulated within 8 h of R1881 addition, with its expression peaking at 24 h (7.4-fold) and decreasing to near-basal levels at 48 h. The other ligands also stimulated PRKCA expression 2.1–3.9-fold, relative to the no-ligand control. Insulin-like growth factor 1 was another signal transduction gene whose expression increased rapidly within 24 h and then fell by 48 h with 1.4–4.3-fold stimulation by the AR ligands.

Figure 6
figure6

Time-course of expression of selected genes in gene cluster U2 upon R1881 treatment. The expression of selected genes that are grouped in gene cluster U2 is shown over the time course of R1881 treatment from 0 to 72 h. As for Figure 4, the line graphs show the means and standard errors for Q-RT–PCR carried out with three independent RNA samples prepared for each time point.

Hence, the groups of genes showing rapid induction with R1881 identified here following the microarray analysis and Q-RT–PCR include a number of genes with potential cellular growth-regulatory roles, several of which have already been implicated in prostate cancer through deregulation of their expression and epigenetic silencing. The other AR agonists and SARMs also stimulated expression of many of these genes.

The anti-androgen BIC is known to inhibit the androgen-stimulated growth of LNCaP cells and act as an AR antagonist (Veldscholte et al., 1992b; Furr and Tucker, 1996). BIC has been earlier shown to promote AR association with cytosolic heat shock protein complexes (Veldscholte et al., 1992a). By contrast, other studies have found that BIC allows nuclear re-localization of AR and recruitment to androgen-regulated gene promoters (Masiello et al., 2002; Yoon and Wong, 2006; Hodgson et al., 2007). The latter studies have shown that although AR agonists recruit co-activators and co-repressors to AR-regulated gene promoters, in the presence of BIC co-repressors are recruited but there is a lack of co-activator recruitment. In agreement with these findings, expression of the majority of R1881-stimulated genes was repressed by co-treatment with BIC (see Figures 3 and 5). Exceptions were genes that featured in the cluster L5: not only HPGD (1.1-fold relative to the no-ligand control) and NPPC (1.9-fold), both of which show strong R1881 stimulation, but also the KCNMA1, IGSF4D, FXYD3, MUC20, ANKRD37, SAT, SOCS2, UGT2B28 and HEBP2 genes (1.0–1.9-fold relative to the no-ligand control), which are only moderately upregulated by R1881 (4.3–16-fold). The most potent BIC stimulation was seen for PHLDB2, TPM1, ANXA2, respectively stimulated 3.8-, 6.9- and 5.2-fold relative to the no-ligand control (Table 1). Two of these genes PHLDB2 and TPM1, are found in the cell cytoskeleton, PHLDB2 being a phospholipid binding protein implicated in microtubule stabilization, whereas TPM1 (tropomyosin 1-α) is an actin-binding protein. Annexin A2 (ANXA2) is a member of the calcium-dependent phospholipid binding protein family, which regulate cell growth. PHLDB2 was potently and rapidly regulated by R1881 (5-fold upregulation in 4 h), and its expression was also stimulated by the other ligands. However, TPM1 and ANXA2 expression was increased only 1.7-and 1.9-fold by R1881 at 24 h. Interestingly, in addition to showing weak activation by R1881 and strong stimulation by BIC, TPM1 and ANXA2 were also strongly upregulated (4.8–10.4-fold) by the other ligands.

Table 1 Expression profiles for R1881-stimulated genes whose expression is not repressed by treatment with BIC alone

R1881-repressed genes

As mentioned earlier, most of the 60 R1881 downregulated genes showed reduced expression by at least 10% within 4 h, with greater than 50% repression by 24 h and less than 10% expression relative to the no-ligand control at 48 h after R1881 addition. The expression of these genes was reduced in the presence of the other ligands to an extent similar to the reduction seen with R1881 at 24 h, although the repression appeared to be less marked for DHT and CPA compared with OHF, E2 and MPA. Interestingly, however, although co-treatment with BIC and R1881 gave gene repression similar to that seen for R1881 alone, the expression of these genes was considerably higher on average in the presence of BIC alone, suggesting that BIC acts to reduce the AR activity on repressed AR genes, as well as on AR-activated genes.

The expression of a number of R1881 downregulated genes was not repressed, or was stimulated, by BIC (Figure 7). These include many of the genes whose expression is either stimulated by R1881 at early time points, before being repressed, or those genes whose expression is reduced only at later time points. These genes include C1orf165, PTPRR, a gene for a protein tyrosine phosphatase, and the cytokine receptor CXCR7 (aka CMKOR1). CXCR7 expression was only reduced at 16 h or more after R1881 treatment and was also inhibited by the other ligands, with the exception of BIC, which stimulated CXCR7 1.6-fold. Interestingly, C1orf165 expression was stimulated about two-fold by R1881 within 4 h, with expression falling at 8 h. C1orf165 expression was repressed by the other ligands, but stimulated 1.6-fold by BIC. Expression of PTPRR was also stimulated two-fold by R1881, fell to one-fold by 16 h and was reduced further at 48 h. PTPRR expression was stimulated by the other ligands at 24 h, including 2.5-fold by BIC.

Figure 7
figure7

Ligand regulation of R1881 downregulated genes. (a) The mean expression levels, relative to the no-ligand control as determined by Q-RT–PCR, are shown for the 60 genes whose expression was downregulated by R1881 in the microarray analysis. The error bars represent the standard errors of the mean. (b) Fold expression of selected R1881-repressed genes, relative to the no-ligand control. BIC, bicalutamide; DHT, dihydrotestosterone; CPA, cyproterone acetate; OHF, hydroxyflutamide; E2, 17β-oestradiol; MPA, medroxyprogesterone.

Conclusions

The profiling of androgen-regulated gene expression in LNCaP cells with the androgen R1881 identified more than 300 genes whose expression was upregulated, and a similar number whose expression was downregulated. The expression profiles of these genes over a timecourse of R1881 treatment highlight distinct sets of androgen-responsive genes whose expression shows rapid stimulation, as well as those genes whose expression is stimulated by R1881 over a longer time period, indicating that the former set comprises genes directly regulated by AR, whereas the latter group may include genes whose expression is indirectly regulated by AR. A comprehensive analysis of the expression of R1881-regulated genes by DHT, but also by other AR agonists oestrogen (E2) and progestin (MPA), as well as the well-characterized and clinically important anti-androgens, CPA, flutamide and bicalutamide. Most of the androgen-regulated genes identified earlier cluster together as genes whose expression is strongly regulated by R1881, other AR agonists and by SARMs. These clusters include many other genes that have not been identified earlier as androgen-responsive genes, and that may play significant roles in prostate cancer biology. Indeed, genes not identified earlier showing strong androgen regulation included the genes for nuclear receptor NR4A1, the cytokine receptor CXCR4 and insulin-like growth factor-1, which have all been implicated in prostate cancer progression (Akashi et al., 2006; Cheng et al., 2006; Tamura et al., 2007). The cluster analysis also indicates that levels of gene regulation by E2 and MPA are similar to those of CPA and OHF, suggesting that E2 and MPA act as SARMs.

Finally, pathway analyses particularly highlight genes involved in fatty-acid metabolism as particular androgen targets, whereas the potential importance of TGF-β signalling in androgen-mediated prostate-cancer progression is further strengthened by our finding that many genes that participate in TGF-β signalling are androgen regulated in LNCaP cells.

Materials and methods

Cell culture

Cell lines were maintained in RPMI-1640 medium-HEPES modification, supplemented with 10% fetal calf serum (Invitrogen Ltd., Paisley, UK). For experiments in which the effects of ligands were determined, the cells were plated in RPMI or DMEM supplemented with 10% dextran–charcoal-stripped fetal calf serum for 3 days before the addition of ligands. The final ligand concentrations were methyltrienolone (R1881; 1 nM), dihydrotestosterone (100 nm), 17β-oestradiol (E2; 100 nm), medroxyprogesterone acetate (MPA; 100 nm), cyproterone acetate (CPA; 10 μM), hydroxyflutamide (OHF; 10 μM), bicalutamide (BIC; 10 μM). As the ligands were prepared in ethanol, an equal volume of ethanol was added to the no-ligand controls. Cells were processed for determining cell number, RNA or protein preparation, as described below.

RNA extraction and reverse–transcriptase PCR (RT–PCR)

Total RNA was extracted using the QIAGEN RNeasy Mini kit (Qiagen Ltd., Crawley, UK) following DNaseI treatment, according to the manufacturer's instructions. The concentration and purity of RNA were determined by measuring spectrophotometric absorption at 260–280 nm. RNA integrity was checked by electrophoresis on 1.5% agarose gels. cDNA synthesis was carried out using 2 μg of total RNA. RNA was reverse transcribed to cDNA in a volume of 20 μl using RevertAid M-MuLV reverse transcriptase (Helena Biosciences Europe, Gateshead, UK), according to the manufacturer's protocols. PCR reactions were carried out using ReddyMix Taq polymerase (Abgene, Epsom, UK). PCR products were resolved in 1.5% agarose gels.

RNA for microarray and low-density array card analysis

R1881 (1 nM) was added 72 h after the seeding of 3.5 × 106 LNCaP cells, and total RNA was prepared as described above. Three replicates from the RNA prepared from cells treated with R1881 for 24 h were used for hybridization to the ABI Human Genome Survey Microarray V2.0. Raw data were quality assessed and filtered according to the recommendations supplied by the ABI1700 data analysis user guide and the filtered data were ‘vsn normalized’ (Huber et al., 2002). Differential expression was assessed using linear models and empirical Bayes algorithms as described (Smyth, 2004).

Q-RT–PCR analysis of 384 genes using TaqMan gene expression analysis primer sets was carried out using an ABI 7900HT fast real-time PCR system, using TaqMan gene expression assays from ABI, according to the manufacturer's instructions. Q-RT–PCR was carried out using total RNA prepared from three replicate cultures following the addition of 1 nM R1881 for varying times or the different AR ligands for 24 h. TaqMan assay details are available on request.

Conflict of interest

The authors declare no conflict of interest.

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Acknowledgements

We are grateful to the members of the group for advice and support. Our particular thanks go to Drs Greg Brooke and Charlotte Bevan for discussions, and to Dr Lev Soinov for aiding the analysis of the microarray data. This work was carried out through the support of the Joron trust, Hammersmith Hospital trustees, Prostate Cancer Charity and Cancer Research UK.

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Correspondence to S Ali or L Buluwela.

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Supplementary Information accompanies the paper on the Oncogene website (http://www.nature.com/onc)

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Ngan, S., Stronach, E., Photiou, A. et al. Microarray coupled to quantitative RT–PCR analysis of androgen-regulated genes in human LNCaP prostate cancer cells. Oncogene 28, 2051–2063 (2009). https://doi.org/10.1038/onc.2009.68

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Keywords

  • prostate cancer
  • LNCaP cells
  • androgens
  • anti-androgens
  • real-time RT–PCR
  • microarrays

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