Portal de Periódicos da CAPES

Antiandrogens Reduce Intratumoral Androgen Concentrations and Induce Androgen Receptor Expression in Castration-Resistant Prostate Cancer Xenografts

2017; Elsevier BV; Volume: 188; Issue: 1 Linguagem: Inglês

10.1016/j.ajpath.2017.08.036

1525-2191

Matias Knuuttila, Arfa Mehmood, Riikka Huhtaniemi, Emrah Yatkin, Merja R. Häkkinen, Riikka Oksala, Teemu D. Laajala, Henrik Ryberg, David J. Handelsman, Tero Aittokallio, Seppo Auriola, Claes Ohlsson, Asta Laiho, Laura L. Elo, Petra Sipilä, Sari Mäkelä, Matti Poutanen,

Cancer, Lipids, and Metabolism

The development of castration-resistant prostate cancer (CRPC) is associated with the activation of intratumoral androgen biosynthesis and an increase in androgen receptor (AR) expression. We recently demonstrated that, similarly to the clinical CRPC, orthotopically grown castration-resistant VCaP (CR-VCaP) xenografts express high levels of AR and retain intratumoral androgen concentrations similar to tumors grown in intact mice. Herein, we show that antiandrogen treatment (enzalutamide or ARN-509) significantly reduced (10-fold, P < 0.01) intratumoral testosterone and dihydrotestosterone concentrations in the CR-VCaP tumors, indicating that the reduction in intratumoral androgens is a novel mechanism by which antiandrogens mediate their effects in CRPC. Antiandrogen treatment also altered the expression of multiple enzymes potentially involved in steroid metabolism. Identical to clinical CRPC, the expression levels of the full-length AR (twofold, P < 0.05) and the AR splice variants 1 (threefold, P < 0.05) and 7 (threefold, P < 0.01) were further increased in the antiandrogen-treated tumors. Nonsignificant effects were observed in the expression of certain classic androgen-regulated genes, such as TMPRSS2 and KLK3, despite the low levels of testosterone and dihydrotestosterone. However, other genes recently identified to be highly sensitive to androgen-regulated AR action, such as NOV and ST6GalNAc1, were markedly altered, which indicated reduced androgen action. Taken together, the data indicate that, besides blocking AR, antiandrogens modify androgen signaling in CR-VCaP xenografts at multiple levels. The development of castration-resistant prostate cancer (CRPC) is associated with the activation of intratumoral androgen biosynthesis and an increase in androgen receptor (AR) expression. We recently demonstrated that, similarly to the clinical CRPC, orthotopically grown castration-resistant VCaP (CR-VCaP) xenografts express high levels of AR and retain intratumoral androgen concentrations similar to tumors grown in intact mice. Herein, we show that antiandrogen treatment (enzalutamide or ARN-509) significantly reduced (10-fold, P < 0.01) intratumoral testosterone and dihydrotestosterone concentrations in the CR-VCaP tumors, indicating that the reduction in intratumoral androgens is a novel mechanism by which antiandrogens mediate their effects in CRPC. Antiandrogen treatment also altered the expression of multiple enzymes potentially involved in steroid metabolism. Identical to clinical CRPC, the expression levels of the full-length AR (twofold, P < 0.05) and the AR splice variants 1 (threefold, P < 0.05) and 7 (threefold, P < 0.01) were further increased in the antiandrogen-treated tumors. Nonsignificant effects were observed in the expression of certain classic androgen-regulated genes, such as TMPRSS2 and KLK3, despite the low levels of testosterone and dihydrotestosterone. However, other genes recently identified to be highly sensitive to androgen-regulated AR action, such as NOV and ST6GalNAc1, were markedly altered, which indicated reduced androgen action. Taken together, the data indicate that, besides blocking AR, antiandrogens modify androgen signaling in CR-VCaP xenografts at multiple levels. Prostate cancer is one of the most common cancers in men from Western countries.1Torre L.A. Siegel R.L. Ward E.M. Jemal A. Global cancer incidence and mortality rates and trends: an update.Cancer Epidemiol Biomarkers Prev. 2016; 25: 16-27Crossref PubMed Scopus (2365) Google Scholar Most aging men develop precancerous lesions, and one of eight men are diagnosed as having prostate cancer. Androgen deprivation therapy (ADT) suppresses the growth of prostate cancer via blockade of testicular androgen production. Androgen deprivation is achieved via treatment of patients with luteinizing hormone–releasing hormone agonists or antagonists, which can be combined with antiandrogens that block the effects of any residual androgen action.2Heidenreich A. Bastian P.J. Bellmunt J. Bolla M. Joniau S. Van Der Kwast T. Mason M. Matveev V. Wiegel T. Zattoni F. Mottet N. EAU guidelines on prostate cancer, part II: treatment of advanced, relapsing, and castration-resistant prostate cancer.Eur Urol. 2014; 65: 467-479Abstract Full Text Full Text PDF PubMed Scopus (1086) Google Scholar ADT typically causes a decline in serum prostate-specific antigen (PSA), but the response is transient for a significant proportion of men; the disease eventually progresses to fatal castration-resistant prostate cancer (CRPC). The average time to develop CRPC after the initiation of ADT is 5 μg/L, and the mean serum PSA value for the study cohort was approximately 15 μg/L. Mice with tumors were castrated, causing a dramatic decline in serum PSA, which was observed 1 week after castration. Subsequently, the serum PSA concentrations started increasing, indicating CRPC-like tumor growth, and the treatment began when the serum PSA of all castrated mice reached precastration levels. The mice were allocated to the treatment arms on the basis of the following five parameters: serum PSA concentration, the change in the serum PSA concentration, body weight, cage placement, and the week at which castration occurred.17Laajala T.D. Jumppanen M. Huhtaniemi R. Fey V. Kaur A. Knuuttila M. Aho E. Oksala R. Westermarck J. Mäkelä S. Poutanen M. Aittokallio T. Optimized design and analysis of preclinical intervention studies in vivo.Sci Rep. 2016; 6: 30723Crossref PubMed Scopus (24) Google Scholar The vehicle (n = 15) or antiandrogens [20 mg/kg per day of enzalutamide (n = 14) or ARN-509 (n = 15); Matrix Scientific, Columbia, SC] were administered via gavage once daily. Previous studies suggested that a 4-week treatment time period may be optimal to mimic the effects of antiandrogen treatment in CRPC and show how CR-VCaP tumors adapt to antiandrogens.16Knuuttila M. Yatkin E. Kallio J. Savolainen S. Laajala T.D. Aittokallio T. Oksala R. Häkkinen M. Keski-Rahkonen P. Auriola S. Poutanen M. Mäkelä S. Castration induces up-regulation of intratumoral androgen biosynthesis and androgen receptor expression in an orthotopic VCaP human prostate cancer xenograft model.Am J Pathol. 2014; 184: 2163-2173Abstract Full Text Full Text PDF PubMed Scopus (48) Google Scholar The mice were sacrificed via cervical dislocation after 4 weeks of treatment, and the tumors were dissected and measured. Fresh tissue sample pieces from each tumor were collected in liquid nitrogen and fixed in 10% formalin for 24 hours before paraffin embedding. Immunodeficient male mice with s.c. CR-VCaP tumors were given a single dose of enzalutamide (n = 6, 20 mg/kg) or vehicle (n = 6). Tritium-labeled dihydrotestosterone ([1,2,4,5,6,7-3H(N)]-3H-DHT; 110 Ci/mmol; PerkinElmer, Waltham, MA), dissolved in ethanol/saline (20:80) solution, was injected i.v. into the tail vein of mice (approximately 1.6 MBq/mouse) 4 hours later. Blood samples were collected via cardiac puncture in anesthetized mice 15 minutes after the injection. Mice were sacrificed via cervical dislocation, and the tumor samples were collected. Tumors were homogenized in sterile water using an Ultra Turrax homogenizer (IKA-Werke, Staufen im Breisgau, Germany). Tumor homogenates (1.5 mL) and serum samples (100 μL) were mixed with 10 mL Ecoscint A scintillation liquid (National Diagnostics, Atlanta, GA), and the radioactivity of the samples was measured using a Wallac 1410 liquid scintillation counter (PerkinElmer). Tumor samples were homogenized in sterile water using a Tissuelyzer LT homogenizer (Qiagen, Venlo, the Netherlands), and the concentrations of androstenedione, testosterone (T), and DHT were measured from the tumor homogenates and serum samples using gas chromatography–tandem mass spectrometry.18Nilsson M.E. Vandenput L. Tivesten Å. Norlén A.-K. Lagerquist M.K. Windahl S.H. Börjesson A.E. Farman H.H. Poutanen M. Benrick A. Maliqueo M. Stener-Victorin E. Ryberg H. Ohlsson C. Measurement of a comprehensive sex steroid profile in rodent serum by high-sensitive gas chromatography-tandem mass spectrometry.Endocrinology. 2015; 156: 2492-2502Crossref PubMed Scopus (198) Google Scholar The lower limits of quantitation (LLOQs) for androstenedione, T, and DHT in mouse serum samples were 12, 8, and 2.5 pg/mL, respectively. The concentrations of pregnenolone and progesterone were measured in the tumor homogenates and serum samples using liquid chromatography–tandem mass spectrometry.19Keski-Rahkonen P. Huhtinen K. Poutanen M. Auriola S. Fast and sensitive liquid chromatography-mass spectrometry assay for seven androgenic and progestagenic steroids in human serum.J Steroid Biochem Mol Biol. 2011; 127: 396-404Crossref PubMed Scopus (96) Google Scholar The LLOQs for pregnenolone and progesterone in serum samples were 10.4 and 10.7 pg/mL, respectively. The concentrations of 3α-androstanediol (3α-diol) and 3β-androstanediol (3β-diol) were measured in the tumor homogenates using liquid chromatography–tandem mass spectrometry; the lower limit of detection (LLOD) for 3α- and 3β-diol was 400 pg/mL.20McNamara K.M. Harwood D.T. Simanainen U. Walters K.A. Jimenez M. Handelsman D.J. Measurement of sex steroids in murine blood and reproductive tissues by liquid chromatography-tandem mass spectrometry.J Steroid Biochem Mol Biol. 2010; 121: 611-618Crossref PubMed Scopus (102) Google Scholar The LLOQ was used for statistical analysis if steroid concentrations in samples were lower than the quantitation limit. One gram of tumor sample was considered equivalent to 1 mL of serum to compare intratumoral steroid levels with serum steroid levels. Total RNA for real-time quantitative RT-PCR (RT-qPCR) and RNA-sequencing (RNA-seq) analyses was extracted from tumor samples using an RNase Mini Kit (Qiagen), according to the manufacturer's instructions. RNA was DNase I treated (amplification grade; Invitrogen, Carlsbad, CA), and RNA quality was determined using a fragment analyzer (Advanced Analytical Technologies, Ankeny, IA). RNA was reverse transcribed using M-MuLV Reverse Transcriptase (New England Biolabs, Ipswich, MA) in the presence of oligo(dT) primers (Promega, Fitchburg, WI) for real-time RT-qPCR. The real-time quantitative PCRs were perfomed using a CFX96 Real-Time PCR Detection System (Bio-Rad Laboratories, Hercules, CA) and a 2× Dynamo SYBR Green qPCR kit (Thermo Fisher Scientific, Waltham, MA). The expression of genes of interest was normalized to the expression of ribosomal protein L19 (RPL19), and the expression of mRNA was quantified using the Pfaffl method. The genes analyzed by real-time RT-qPCR and sequences of the primers used are given in Table 1.Table 1Real-Time Quantitative RT-PCR Primer SequencesGenePrimer sequenceForwardReverseAR-FL5′-CTTACACGTGGACGACCAGA-3′5′-GCTGTACATCCGGGACTTGT-3′AR-V15′-CCATCTTGTCGTCTTCGGAAATGTTATGAAGC-3′5′-CTGTTGTGGATGAGCAGCTGAGAGTCT-3′AR-V75′-CCATCTTGTCGTCTTCGGAAATGTTATGAAGC-3′5′-TTTGAATGAGGCAAGTCAGCCTTTCT-3′ASF/SF25′-TCTCTGGACTGCCTCCAAGT-3′5′-GGCTTCTGCTACGACTACGG-3′FKBP55′-AAAAGGCCACCTAGCTTTTTGC-3′5′-CCCCCTGGTGAACCATAATACA-3′KLK25′-CTGCCCATTGCCTAAAGAAGAA-3′5′-GGCTTTGATGCTTCAGAAGGCT-3′KLK35′-CCAAGTTCATGCTGTGTGCT-3′5′-GGTGTCCTTGATCCACTTCC-3′NOV5′-ACCGTCAATGTGAGATGCTG-3′5′-TCTTGAACTGCAGGTGGATG-3′PMEPA15′-TGCCGTTCCATCCTGGTT-3′5′-AGACAGTGACAAGGCTAGAGAAAGC-3′RPL195′-AGGCACATGGGCATAGGTAA-3′5′-CCATGAGAATCCGCTTGTTT-3′ST6GalNAc15′-AGGCACAGACCCCAGGAAG-3′5′-TGAAGCCATAAGCACTCACC-3′SYTL25′-TCTGCCTTGAGAAAACAAACAGTT-3′5′-GCCAGTGGGTGGCACTAAAA-3′TMPRSS2-ERG5′-TAGGCGCGAGCTAAGCAGGAG-3′5′-GTAGGCACACTCAAACAACGACTGG-3′UBE2C5′-AAAAGGCCACCTAGCTTTTTGC-3′5′-CCCCCTGGTGAACCATAATACA-3′ Open table in a new tab RNA-seq analyses of vehicle (n = 15), enzalutamide (n = 14), or ARN-509 (n = 15) treated tumors were performed at the Finnish Microarray and Sequencing Center (Turku, Finland). The total RNA (300 ng) was used according to the Illumina TruSeq Stranded mRNA Sample Preparation Guide (Illumina, San Diego, CA). The samples were sequenced with an Illumina HiSeq 2500 instrument (Illumina) using TruSeq v3 paired-end sequencing chemistry with a 100-bp read length, combined into two lanes in the sequencing run. The quality of the RNA-seq data was investigated using the FastQC tool version 0.11.5 (Babraham Bioinformatics Group, Cambridge, UK). The reads were aligned to the human reference genome version hg19 (University of California, Santa Cruz, Santa Cruz, CA) using Tophat software version 2.0.10 (http://ccb.jhu.edu/software/tophat/index.shtml). The number of uniquely mapped reads associated with each gene was counted using HTSeq version 0.6.121Anders S. Pyl P.T. Huber W. HTSeq: a Python framework to work with high-throughput sequencing data.Bioinformatics. 2014; 31: 166-169Crossref PubMed Scopus (11034) Google Scholar with RefSeq annotations. The RNA-seq data are available from the Gene Expression Omnibus database (https://www.ncbi.nlm.nih.gov/geo; accession number GSE95413). The downstream analysis of the data was performed using R version 3.2.2 (R Foundation for Statistical Computing, Vienna, Austria) and Bioconductor version 2.14 (http://bioconductor.org/install). Data were normalized for library size using the trimmed mean of M-values approach implemented in the R/Bioconductor package edgeR. Data for statistical testing were further transformed using the voom approach in the Limma R/Bioconductor package. Pairwise comparisons between the enzalutamide-, ARN-509–, and vehicle-treated groups were performed to detect differentially expressed genes using the linear modeling approach with the empirical bayesian method in the R/Bioconductor package Limma. Genes with a false-discovery rate (Benjamini-Hochberg) adjusted P < 0.005 and absolute fold changes >2 were reported for each comparison. The clustering in Supplemental Figure S1, C and D, is based on hierarchical clustering (euclidean metrics with average linkage) of the normalized count data of the differentially expressed genes. Transcript abundances of full-length ARs (AR-FLs) and AR-Vs were calculated using Salmon version 0.8.1 using a transcriptome reference file downloaded from ENSEMBL (ftp://ftp.ensembl.org/pub/release87/fasta/homo_sapiens/cdna/Homo_sapiens.GRCh38.cdna.all.fa.gz; files can be opened using WinSCP or FileZilla, free download required). (Products are not endorsed by The American Journal of Pathology.) The transcripts per million values were normalized using TMM normalization. AR-interacting genes were selected on the basis of the gene list from the androgen receptor gene mutations database.22Gottlieb B. Beitel L.K. Nadarajah A. Paliouras M. Trifiro M. The androgen receptor gene mutations database: 2012 update.Hum Mutat. 2012; 33: 887-894Crossref PubMed Scopus (340) Google Scholar The gene selection for aldo-keto reductases (AKRs), CYP enzymes, short-chain dehydrogenases/reductases, and UDP-glucuronosyltransferases (UGTs) was based on Gene Names gene family indexes. The clustering is based on hierarchical clustering (euclidean metrics with ward.2 agglomeration method, pheatmap R package) using the scaled mean expression value in each group. Tumor samples were homogenized using an Ultra Turrax homogenizer (IKA-Werke) in lysis buffer containing the following: 150 mmol/L Tris-HCl, 1% NP-40, 0.5% sodium deoxycholate, 1 mmol/L EDTA, 1 mmol/L SDS, 100 μmol/L sodium orthovanadate (Sigma-Aldrich), and cOmplete Mini protease inhibitor (Roche, Basel, Switzerland). Samples were centrifuged at 10,000 × g for 20 minutes at 4°C, and total protein concentrations were measured with a bicinchoninic acid protein assay (Pierce, Rockford, IL). The samples were loaded onto an SDS-PAGE gel (10% Precast Midi protein gel; Bio-Rad Laboratories) and separated under reducing conditions, followed by transfer onto an iBlot Transfer Stack membrane by an iBlot Dry Blotting System (Invitrogen). The membranes were probed with rabbit anti-AR antibody (dilution, 1:1000; sc-816; Santa Cruz Biotechnology, Dallas, TX) and an anti–AR-V7 antibody (dilution, 1:500; AG10008; Precision Antibody, Columbia, MD). For AR and AR-V7, 20 and 40 μg of sample were loaded in each well, respectively. Enhanced chemiluminescence plex goat–anti-rabbit IgG-Cy5 for anti-AR (dilution, 1:2500) and anti-mouse IgG-Cy3 for AR-V7 (dilution, 1:5000) were used as secondary antibodies, and the membrane was visualized using Cy5 and Cy3 detection using a Typhoon laser scanner (GE Healthcare Life Sciences, Little Chalfont, UK). Formalin-fixed, paraffin-embedded tumor samples were divided into sections before deparaffinization and rehydration. The sections were exposed to antigen retrieval in a pressure cooker in Target Retrieval Solution sodium citrate buffer (Dako, Glostrup, Denmark) for 30 minutes. The blocking reaction for nonspecific binding was followed by overnight incubation with the primary antibody against the N-terminus of the AR (dilution, 1:250; sc-816; Santa Cruz Biotechnology) at 4°C. Endogenous peroxidase activity was blocked via application of 1% H2O2 for 20 minutes at room temperature, and the sections were incubated for 30 minutes with an anti-rabbit antibody conjugated with polymer–horseradish peroxidase (Dako), washed, and visualized with Envision + System-HRP diaminobenzidine staining (Dako). The sections were counterstained with hematoxylin, mounted, and digitized using a Pannoramic 250-slide scanner (3DHISTECH, Budapest, Hungary). The intensity of AR immunohistochemical nuclear staining was determined using CaseViewer 2.0 software including the QuantCenter and NuclearQuant modules (3DHISTECH). The nuclei were scored into three equally distributed categories: strong staining, medium staining, and weak staining (based on the range of staining intensity on the chromogen). The number of positive and negative stained cells was calculated, and the AR index was calculated by comparing the number of strong positive cells with the total number of positive cells of each section. Glucuronidation activity was measured using 3H-DHT as the substrate. For each reaction, 3H-DHT (500,000 counts per minute/reaction) was placed into a small glass tube, evaporated under nitrogen flow, and dissolved in Tris-MgCl2 buffer (50 mmol/L Tris and 10 mmol/L MgCl2) supplemented with l-α-phosphatidylcholine (100 μg/mL; Sigma-Aldrich). Total protein (100 μg) from vehicle- or antiandrogen-treated VCaP tumor homogenates was added to the reaction, and the final volume was adjusted with the assay buffer to 150 μL. Uridine 5′-diphosphoglucuronic acid (1 mmol/L; Sigma-Aldrich), a cofactor for the reaction, was added, the samples were incubated at 37°C for 4 hours, and the reaction was terminated by rapid freezing. Diethyl ether (Uvasol; Merck, Darmstadt, Germany) extraction was performed to separate the free 3H-DHT from the 3H-DHT-glucuronidates present in the aqueous phase. The organic phase with 3H-DHT was evaporated under nitrogen flow and dissolved in 100 μL ethanol. Samples were mixed with 10 mL Ecoscint A scintillation liquid (National Diagnostics) and measured using a Wallac 1410 liquid scintillation counter (PerkinElmer). Nonparamet