Molecular Alterations in Primary Prostate Cancer After Androgen Ablation Therapy Carolynj.M

Human Cancer Biology

Molecular Alterations in Primary Prostate Cancer after Androgen Ablation Therapy CarolynJ.M. Best,1John W. Gillespie,1, 5 Yajun Yi, 6 Gadisetti V.R. Chandramouli,8 MarkA. Perlmutter, 1 Yvonne Gathright,1Heidi S. Erickson,1Lauren Georgevich,1Michael A.Tangrea,1Paul H. Duray,2 Sergio Gonza¤ lez,9 Alfredo Velasco,10 W. Marston Linehan,3 RobertJ. Matusik,7 Douglas K. Price,4 William D. Figg,4 Michael R. Emmert-Buck,1and Rodrigo F. Chuaqui1

Abstract Purpose: After an initial response to androgen ablation, most prostate tumors recur, ultimately progressing to highly aggressive androgen-independent cancer. The molecular mechanisms underlying progression are not well known in part due to the rarity of androgen-independent samples from primary and metastatic sites. Experimental Design:We compared the gene expression profiles of 10 androgen-independent primary prostate tumor biopsies with 10 primary, untreated androgen-dependent tumors. Samples were laser capture microdissected, the RNA was amplified, and gene expression was assessed using Affymetrix Human Genome U133A GeneChip. Differential expression was examined with principal component analysis, hierarchical clustering, and Student’s t testing. Anal- ysis of gene ontology was done with Expression Analysis Systematic Explorer and gene expression data were integrated with genomic alterations with Differential Gene Locus Mapping. Results: Unsupervised principal component analysis showed that the androgen-dependent and androgen-independent tumors segregated from one another. After filtering the data, 239 differentially expressed genes were identified.Two main gene ontologies were found discordant between androgen-independent and androgen-dependent tumors: macromolecule biosynthesis was down-regulated and cell adhesion was up-regulated in androgen-independent tumors. Other differentially expressed genes were related to interleukin-6 signaling as well as angiogenesis, cell adhesion, apoptosis, oxidative stress, and hormone response. The Differential Gene Locus Mapping analysis identified nine regions of potential chromosomal deletion in the androgen- independent tumors, including1p36, 3p21,6p21,8p21,11p15,11q12,12q23,16q12,and16q21. Conclusions: Taken together, these data identify several unique characteristics of androgen- independent prostate cancer that may hold potential for the development of targeted therapeutic intervention.

Carcinoma of the prostate accounts for approximately one Authors’ Affiliations: 1Pathogenetics Unit, Laboratory of Pathology; 2Laboratory third of all cancers diagnosed in men in the United States of Pathology; 3Urologic Oncology Branch; and 4Molecular Pharmacology Section, and remains the second most common cause of cancer death CancerTherapeutics Branch, National Cancer Institute, NIH, Bethesda, Maryland; in this group (American Cancer Society Cancer Facts & 5Science Applications International Corporation-Frederick, Inc., National Cancer Figures 2004; http://www.cancer.org/docroot/STT/stt_0.asp). 6 Institute at Frederick, Frederick, Maryland; Division Genetic Medicine, The survival and growth of prostate cancer cells is initially Department of Medicine and 7Department of Urologic Surgery,Vanderbilt-Ingram Cancer Center,Vanderbilt University, Nashville,Tennessee; 8Advanced Technology dependent on the presence of androgens, and virtually all Center, National Cancer Institute, Gaithersburg, Maryland; and Departments of prostate cancer patients respond when first treated with 9Pathology and 10Urology, Catholic University, Santiago, Chile androgen ablation. However, resistance to hormone blockade Received 3/16/05; revised 6/24/05; accepted 7/13/05. ultimately results in the recurrence of highly aggressive and Grant support: National Cancer Institute grant R01 CA76142-06 and Frances Preston Laboratories of the T.J. Martell Foundation (R.J. Matusik). This research metastatic prostate cancer that is androgen independent (1). was supported in part by the Intramural Research Program of the NIH, National Androgen-independent prostate cancer (AIPC) is therefore Cancer Institute Center for Cancer Research. clinically defined as the progression of the disease under The costs of publication of this article were defrayed in part by the payment of page hormonal ablation. charges. This article must therefore be hereby marked advertisement in accordance Although several hypothesized mechanisms exist for the with 18 U.S.C. Section 1734 solely to indicate this fact. Note: C.J.M. Best is currently at the Molecular Therapeutics Program, National development of AIPC (reviewed in ref. 2), and recent studies Cancer Institute, NIH, Building 37, Room 1-122, 9000 Rockville Pike, Bethesda, using prostate cancer models have shed additional light on the MD 20892. process (3), our understanding of the disease in patients Requests for reprints: Carolyn J.M. Best, Pathogenetics Unit, Laboratory of remains incomplete at the molecular level, and the key genes Pathology, National Cancer Institute, NIH, Bethesda, MD 20892. Phone: 301-451- 8544; Fax: 301-402-8910; E-mail: [email protected]. involved are still largely unknown. Expression analysis of F 2005 American Association for Cancer Research. prostate cancer before and after hormone therapy may identify doi:10.1158/1078-0432.CCR-05-0585 genes and pathways that are critical to its progression. Over the

www.aacrjournals.org 6823 Clin Cancer Res 2005;11(19) October 1, 2005 Downloaded from clincancerres.aacrjournals.org on September 26, 2021. © 2005 American Association for Cancer Research. Human Cancer Biology past few years, numerous studies have been published on the specific antigen levels (prostate-specific antigen z 5.0), at least one molecular profiles of human prostate cancer tissue. Several of new lesion on bone scan, or progressive measurable disease. In these have included metastatic lesions (4–9); however, few have addition, in the absence of surgical castration, a serum testosterone of analyzed androgen-independent tumor cells from the site of the <50 ng/mL and continuance on gonadotropin-releasing hormone antagonist was required. Clinical details, including treatment history primary lesion. As an example, Holzbeierlein et al. compared before androgen-independent disease, for each of the androgen- the gene expression profiles of normal prostate, primary tumors independent cases are provided in Table 1. before and during hormone therapy, and metastatic tumors, Laser capture microdissection and RNA isolation. Each of the 20 three of which were androgen independent (8). Although the frozen tissue blocks was recut into 8-Am thick sections onto glass slides androgen-independent tumor group was small, they identified a and stored at À80jC. Each section was individually removed from pattern of gene expression, independent of treatment and storage and immediately stained as follows: 70% ethanol for 15 metastatic status, unique to AIPC. Studies that delineate the seconds, deionized water for 10 seconds, Mayer’s hematoxylin molecular profile of androgen-independent tumors may be (Sigma-Aldrich, St. Louis, MO) for 15 seconds, deionized water uniquely valuable in designing therapeutic interventions. and bluing solution (Sigma-Aldrich) for 10 seconds each, and eosin In the present study, we directly compared the gene (Sigma-Aldrich) for 5 seconds followed by dehydration for 10 seconds each in increasing concentrations of ethanol. Finally, expression profiles of 10 androgen-independent tumor biop- the tissue was completely dehydrated in xylenes for 20 seconds. Cells sies, taken from the primary site of prostate cancer, with 10 from each case were microdissected by laser capture microdissection primary, untreated prostate tumors. Each sample was micro- (10) with the PixCell IIe according to the manufacturer’s protocol dissected to eliminate gene expression changes that could (Arcturus Engineering, Inc., Mountain View, CA), and total RNA was derive from cell types other than tumor. Expression patterns isolated with the PicoPure RNA Isolation kit (Arcturus Engineering). were evaluated with respect to metabolic pathways, gene The samples were subjected to DNase treatment for 15 minutes, and ontologies, and genomic alterations. RNA quality and quantity were assessed with the Bioanalyzer 2100 (Agilent Technologies, Inc., Palo Alto, CA) and Degradometer software version 1.2 (http://www.dnaarrays.org; ref. 11). Materials and Methods RNA amplification, microarray sample synthesis, and hybridization. RNA was amplified by modifying a previously established protocol Tissue specimens. Androgen-dependent prostate carcinoma speci- that combines the RiboAmp (Arcturus Engineering) and Affymetrix mens were obtained from patients undergoing prostatectomy as first- (Affymetrix, Inc., Santa Clara, CA) systems (12), resulting in biotin- line therapy at either Catholic University in Santiago, Chile (cases 1-9) labeled antisense cRNA. Total RNA was used for amplification, or University of North Carolina (case 10). The tumors were excised because this approach has been shown to introduce less bias than and one section was frozen, whereas the remainder was processed for when mRNA is used (13). Total RNA (1-10 ng) from each sample was diagnosis. A total of 16 frozen cases were collected, anonymized, and subjected to two rounds of linear amplification with the RiboAmp HS transferred to the National Cancer Institute. Ten of the samples had kit. Antisense RNA (2 Ag) from the second round of amplification was sufficient tumor for inclusion in the study. The tumors were evaluated then used to synthesize double-stranded cDNA with the regular by two pathologists (J.W.G. and R.F.C.) and assigned Gleason scores RiboAmp kit, because the RiboAmp HS kit has a maximum RNA of 5 (n = 2), 6 (n = 4), 7 (n = 1), 8 (n = 2), and 9 (n = 1). For the input capacity of only 250 ng. The resulting cDNA was then used as comparison group of AIPC, we retrospectively obtained baseline, template for the synthesis of antisense cRNA labeled with biotinylated primary-site biopsies from patients who had participated in an UTP and CTP by in vitro transcription using the BioArray High-Yield institutional review board–approved National Cancer Institute phase RNA Transcript Labeling kit (Enzo Life Sciences, Inc., Farmingdale, II trial studying docetaxel and thalidomide in metastatic AIPC. We NY). In total, each sample underwent three rounds of amplification, examined a total of 82 snap-frozen biopsies from 30 cases, of which which has been shown previously to decrease the average distribution 23 cases contained cancer. We then selected the 10 cases with the size of antisense RNA without affecting reproducibility on oligonu- highest amount of tumor and quality RNA preservation. All patients cleotide arrays (14). Each labeled sample (15 Ag) was then fragmented from whom the androgen-independent samples were obtained met at according to protocol (Affymetrix) and hybridized to Human Genome least one of the following variables for clinically progressing, U133A GeneChip arrays for 16 hours. Microarrays were washed and androgen-independent disease: two consecutively rising prostate- stained using the ‘‘EuKGE-WS2v4’’ protocol and then scanned using

Table 1. Clinical data forAIPC specimens

Case Race Age at Gleason Stage at Time from Tr e a t m e n t Radiation Survival diagnosis (y) at diagnosis diagnosis diagnosis to history therapy after biopsy (y) biopsy (y)

AI-1 Caucasian 69 7 T2-T3 4 Zoladex, Flutamide Yes 0.8 AI-2 Caucasian 57 8 D2 6.5 Lupron, Flutamide No 1 AI-3 Caucasian 40 8 D2 1.3 Lupron, Casodex No 1.3 AI-4 African American 69 8 T2-T3 7 Lupron, Flutamide Yes 2.8 AI-5 Caucasian 73 9 T2-T3 7.2 Lupron, Flutamide Yes 0.8 AI-6 Caucasian 55 7 T2-T3 12.7 Lupron, Flutamide Yes N/A AI-7 Caucasian 66 8 T2-T3 10.8 Orchiectomy Yes 2.4 AI-8 African American 63 8 T2-T3 7.8 Lupron, orchiectomy Yes 4.8 AI-9 Caucasian 54 7 N1-2, D2 17 Orchiectomy, Flutamide Yes N/A AI-10 Caucasian 62 9 T2-T3 7.9 Zoladex, Casodex Yes 0.5

Clin Cancer Res 2005;11(19) October 1, 2005 6824 www.aacrjournals.org Downloaded from clincancerres.aacrjournals.org on September 26, 2021. © 2005 American Association for Cancer Research. Androgen-Independent Prostate Cancer the Affymetrix GeneChip Scanner 3000. The raw microarray data were expression (11, 18). However, these studies also showed that uploaded to the Gene Expression Omnibus public repository (http:// the 28S/18S ratio (provided by the Bioanalyzer software) is not www.ncbi.nlm.nih.gov/geo/; Gene Expression Omnibus series no. a reliable indicator of RNA quality. Thus, we chose to GSE2443). additionally employ a quantitative measurement of RNA Data filtering and normalization, clustering, and statistical analysis. degradation to ensure that the RNA from the two tumor Expression profile data were prepared for analysis using Microarray Analysis Suite version 5.0 software (Affymetrix), setting the scaling of all groups was of similar quality. The Degradometer software (11) probe sets on all chips to a constant value of 1,000. The data were then uses the ratio of the average value of all degradation peak filtered to include only those probe sets having ‘‘present’’ or ‘‘marginal’’ signals to the 18S peak signal multiplied by 100 to calculate an calls (detection P < 0.065) in at least 10% of the samples. The global objective, quantitative degradation factor and showed no expression patterns were studied by principal component analysis significant difference between the two sample groups (an considering one dimension for each gene on the array (Partekpro 5.0 average of 20.0 for the biopsies and 21.8 for the whole tumors), software, Partek, Inc., St. Charles, MO). Principal component analysis although six of the needle biopsies had insufficient concen- determines a set of principal components as linear combinations of trations for the calculation of a degradation factor. original dimensions such that the first principal component is in the The technical variables for microarray hybridization showed direction of highest variance of the distribution, the next principal high consistency among all samples with respect to background component is in the direction of highest of remaining variance, and so on (15). Eigen analysis of correlation matrix was used. A projection on and noise, with all values well within the manufacturer’s the first three principal component’s covering highest variance permits recommended maximums of 200 and 5, respectively. Further, dimension reduction of multidimensional data for graphical visualiza- the scale factors, which can indicate skewing of the data tion. In this three-dimensional plot, a point represents a tissue sample, between groups, potentially introducing error into differential whereas the close clustering of points indicates similar gene expression expression comparisons, showed no statistically significant patterns. difference. The manufacturer’s recommended maximum value Analysis of gene ontology representation. Genes showing significant for the 3V/5V ratios for housekeeping genes glyceraldehyde-3- differential expression were categorized by their ontologies using phosphate dehydrogenase and b-actin is 3.0, which typically Expression Analysis Systematic Explorer software (16). The number of assumes high quality, unamplified RNA. The protocol genes assigned to each ontology term was compared with the total employed here resulted in much higher ratios averaging 7.5 population on the microarray to identify the probability of overrepresentation of each ontology. Overrepresentation analysis calculated for and 9.6 for glyceraldehyde-3-phosphate dehydrogenase and h each of the gene ontology terms provided an Expression Analysis 32.2 and 26.9 for -actin. Similar observations have been Systematic Explorer score, which was the upper boundary of the reported by others using amplified RNA (12), as each round of distribution of Jackknife Fisher exact probabilities. The gene ontologies amplification shortens RNA transcript lengths, eventually having an Expression Analysis Systematic Explorer score of <0.05 were resulting in the loss of 5V regions and increasing the ratio of considered significantly overrepresented. signal between the 3V and 5V probe sets. The percentage of Identification of potential chromosomal deletion regions. The probe sets called present was not statistically different between normalized and filtered data set was subjected to Differential Gene the two tumor groups and was within the manufacturer’s Locus Mapping (DIGMAP) analysis as described previously (17). recommended range expected for human tissue. Briefly, the gene locations were first mapped through the Gene Annotation Project database. UniGene clusters and their genomic Finally, we examined the possibility that gene expression locations in the data set were annotated, and information from this step differences could result from the genetic variation between the was used to generate a DIGMAP source file that was used in the patients, because the samples were derived from patients in two subsequent analysis. Next, a viewer program (DIGMAPviewer) read the separate countries (i.e., the United States and Chile). One of the DIGMAP source file, and DIGMAP partitioned the microarray data into samples in the androgen-dependent group originated within subsets by chromosome number and subchromosomal locations. A the United States (AD-10), whereas the rest derived from Chile, graphical presentation was generated using a heat map to represent yet this tumor clustered well within the androgen-dependent each data point with a colored cell that quantitatively reflected the tumor group when analyzed by hierarchical clustering (data not original differential expression value. Genomic regions exhibiting shown), indicating no obvious difference on this account. differential gene expression were marked as differential flag regions Differential gene expression between tumor groups. Unsuper- by visual inspection of the graphical displays. vised principal component analysis based on the largest three principal components revealed separate clustering of the androgen-dependent and androgen-independent tumor Results groups along principal component 2 (9.35% variance) as shown in Fig. 1. This indicates the presence of a large number Technical variables. To assess the reliability and reproduc- of genes (f1,000 if the variance is equal for all genes) ibility of the protocol, each sample was evaluated following distinguishing the two tumor groups. In general, the each step (Table 2). The amount of dissection was similar for androgen-dependent tumors clustered more tightly together, most samples; however, the needle biopsies provided less RNA whereas the androgen-independent tumors, although predom- than the whole tumors, an average of 8.7 versus 38.6 ng, inantly separate from the androgen-dependent tumors, clus- respectively. This may have been due to a lower density of cells tered more loosely. This likely represents the relative clinical per shot in the biopsies compared with the whole tumors. The similarity of the tumors within each group, with the Bioanalyzer electropherograms for all samples in the study androgen-dependent tumors being from newly diagnosed, showed dominant 18S and 28S ribosomal peaks and no untreated patients and the androgen-independent tumors obvious degradation peaks. Two recent studies showed that being from patients having undergone various treatments consistency in RNA quality, rather than undiminished integrity, (i.e., radiation, orchiectomy, flutamide, or combinations) is the critical determinant for avoiding artifactual differential while progressing to androgen-independent disease status.

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Table 2. Microdissection, RNA yield, RNA amplification, and microarray performance

Case Laser capture RNA quality RNA Round 1 Round 1 Round 2 microdissection shots assessment* quantity (ng) template (ng) antisense RNA (ng) antisense RNA (Mg) Androgen-dependent tumors AD-1 3,100 67 34.5 10.0 61 104 AD-2 3,000 29 18.1 10.0 72 87 AD-3 3,100 17 77.8 10.0 61 105 AD-4 3,100 18 32.1 10.0 208 77 AD-5 3,000 15 26.4 10.0 70 65 AD-6 3,100 15 18.8 10.0 536 77 AD-7 3,000 14 48.1 10.0 89 103 AD-8 3,100 17 52.2 10.0 55 85 AD-9 3,200 21 28.2 10.0 35 64 AD-10 3,000 5 50.0 10.0 64 79 AD average 21.8 38.6 10.0 125.1 84.6 Androgen-independent biopsies AI-1 3,100 N/A 2.6 2.6 12 24 AI-2 3,050 N/A 14.0 10.0 44 39 AI-3 3,150 N/A 12.8 10.0 80 62 AI-4 3,100 N/A 5.3 5.3 27 88 AI-5 1,400 N/A 1.0 1.0 10 41 AI-6 3,000 N/A 13.0 10.0 58 73 AI-7 3,200 17 15.0 10.0 31 33 AI-8 3,050 12 9.3 9.3 242 44 AI-9 2,200 9 5.9 5.9 39 81 AI-10 3,050 42 7.8 7.8 57 79 AI average 20.0 8.7 7.2 60.0 56.4

*Based on Degradometer calculations, lower values indicate higher quality (i.e., less degradation). Samples with RNA concentrations below the level needed to employ the Degradometer were designated ‘‘N/A’’ for none available, although the Bioanalyzer electropherograms for these samples were similar to the other biopsies.

We found no correlation between treatment histories and gene biosynthesis. The genes in this group predominantly (20 of 31) expression profiles in this study. showed lower expression in AIPC. The second group included To identify the specific genes that were differentially genes involved in the extracellular matrix (ECM) and cell expressed between the two tumor groups, the normalized data adhesion molecule activity and showed predominantly (15 of were filtered to remove all probe sets not called present in at 19) increased expression. In addition, by a review of literature least 20% of the samples, which resulted in 10,041 probe sets for the differentially expressed genes, we found the signaling remaining. Two-sample Student’s t testing identified 256 probe pathway of the proinflammatory cytokine interleukin-6 (IL-6) sets showing differential expression at P < 0.005 between the and genes whose expression related to IL-6 to be overrepre- two groups (see the Supplementary Material for the unabridged sented (Table 4, bottom). list). These probe sets represented 239 genes, as several genes Identification of potential chromosomal deletion regions. A were identified by multiple probe sets. Approximately 61.3% total number of 7,002 distinct UniGene clusters and their of the genes showed down-regulation in the androgen- genomic locations were annotated from the data set. A independent tumor cells, whereas 38.7% showed up-regulation. graphical presentation was generated using a heat map to Many of the genes are involved in processes of carcinogenesis, show the quantitative differential expression for each probe such as angiogenesis, cell adhesion and the microenvironment, set at its chromosomal location. The 20 samples were cell death including apoptosis, hormone response, oxidative clustered according to similarity in differential expression stress and cancer cell metabolism, key signaling pathways, and patterns. Five of the androgen-independent tumors (AI-1, metastasis. A list of selected differentially expressed genes is AI-2, AI-5, AI-6, and AI-7) and six of the androgen-dependent presented in Table 3. tumors (AD-1, AD-3, AD-4, AD-5, AD-7, and AD-8) were Identification of overly represented gene ontologies. The list of included for subsequent analysis due to the similar expression 256 probe sets representing the genes showing significant pattern within the samples of each group and because differential expression was analyzed for overrepresentation of chromosomal deletions typically occur in only a subset of specific gene ontologies using the Expression Analysis System- any given tumor type. Based on these remaining samples, nine atic Explorer software. Two major biological groups were differential flag regions showed concordant down-regulation identified (Table 4, top). The first group included genes that in the androgen-independent samples (Table 5), representing are involved in ribonucleoprotein complexes, are structural regions of potential chromosomal deletion. To estimate the constituents of ribosomes, or are otherwise involved in protein known significance of each region in prostate cancer, literature

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Table 2. Microdissection, RNA yield, RNA amplification, and microarray performance (Cont’d)

Round 3 Final Background Noise Mean P Scale Glyceraldehyde-3-phosphate Actin % Present template (Mg) cRNA (Mg) signal call signal factor dehydrogenase 3 V/5V 3V/5V

2 44 50.7 2.7 2,306.7 13.9 6.5 22.2 29.1 2 37 60.3 3.6 1,871.6 8.1 7.1 53.3 33.4 2 43 46.7 2.8 2,318.4 12.2 9.0 37.6 29.5 2 51 45.1 2.5 2,690.2 17.8 7.8 23.5 28.8 2 81 50.2 2.7 2,258.5 14.1 4.6 25.7 29.1 2 45 56.1 3.4 1,940.9 6.1 5.8 34.8 36.5 2 71 58.4 3.2 2,440.6 12.2 10.0 25.1 32.5 2 94 54.7 3.1 2,299.6 11.3 9.1 75.0 31.8 2 104 131.7 10.1 2,353.8 7.7 8.0 15.4 29.2 2 67 68.7 4.4 2,203.9 6.6 7.0 8.9 33.1 2 63.7 62.3 3.9 2,268.4 11.0 7.5 32.2 31.3

2 48 49.0 2.7 2,135.3 10.5 14.7 10.7 31.4 2 52 56.5 3.8 1,756.6 5.2 10.5 22.2 38.1 25152.13.41,984.88.76.229.633.6 2 57 62.7 4.3 1,889.3 6.1 8.6 20.5 34.1 2 51 61.2 3.5 2,060.1 9.2 8.5 17.8 32.8 2 43 47.9 2.6 2,064.1 17.9 6.0 76.9 26.7 2 70 46.9 2.9 1,917.1 5.3 10.9 30.9 36.3 2 76 50.7 2.9 1,970.5 9.1 6.5 10.1 32.9 2 57 61.1 3.5 2,261.7 9.2 9.6 18.5 31.5 2 59 149.3 12.1 2,086.5 7.6 14.0 31.8 26.4 2 56.4 63.7 4.2 2,012.6 8.9 9.6 26.9 32.4

searches using PubMed (http://www.ncbi.nlm.nih.gov/entrez/ tumor cells and metastatic androgen-independent tumors as query.fcgi) were done to identify the prevalence of each region separate entities with regards to hormone therapy. Both are in the cancer research literature and those specific to prostate. androgen independent; however, the primary lesions grow Regions 1p36, 8p21, and 16q21 showed the highest degree of slowly and ‘‘persist’’ without androgens, whereas the meta- known significance in prostate cancer. The 16q21-16q24.3 static lesions grow rapidly and significantly expand the tumor region typified the differential flag regions in this study and is burden of patients. This distinction is consequential as the presented in Fig. 2. androgen-independent primary tumor expression data set may The gene lists for each region were compared with the list of reveal molecular changes more closely associated with 239 genes identified in the initial analysis of differential ‘‘effective androgen ablation therapy’’ as opposed to those expression. Each region contained one or more genes that related with treatment failure and subsequent clinical break- were identified by both analyses as follows: 3p, one gene; 4q, through. one gene; 6p, two genes; 8p, one gene; 11p, three genes; 11q, The expression array analysis generated a large amount of two genes; and 16q, eight genes. The common genes in region interesting data and identified many individual genes that 16q21-24.3 are indicated in Fig. 2. were differentially regulated between androgen-independent and androgen-dependent primary-site prostate tumor cells. Discussion These included genes involved in angiogenesis, apoptosis, oxidative stress, and hormone response. All of the differen- In the present study, the gene expression profiles of newly tially expressed genes are of potential interest for follow-up diagnosed, androgen-dependent primary prostate tumors were studies, and some have been identified previously to have compared with those of prostate biopsies from patients who potential as clinical biomarkers. However, to better under- progressed to develop metastases and were treated with stand the functional themes related to androgen withdrawal, hormone ablation therapy. This latter group of clinical we searched for patterns of gene expression using gene specimens represents a unique and precious resource, as very ontology analysis. Two main groups that differed between few patients undergo surgical procedures after establishment androgen-independent and androgen-dependent tumors were of advanced disease. The study examined one step in the identified: those associated with ribosomes and protein overall progression of prostate cancer, specifically the effect of synthesis and those associated with cell adhesion and the androgen ablation therapy on primary tumor cells. This differs ECM. Although aggressive tumors are generally expected to from an analysis of metastatic, rapidly growing tumor cells, have higher expression and activity of the protein synthesis and it is important to consider primary androgen-independent machinery, we found the converse, with the majority of these

www.aacrjournals.org 6827 Clin Cancer Res 2005;11(19) October 1, 2005 Downloaded from clincancerres.aacrjournals.org on September 26, 2021. © 2005 American Association for Cancer Research. Human Cancer Biology genes showing lower expression in androgen-independent In addition, other genes that we found to be up-regulated in cells. The second dominant ontological group, genes associ- AIPC, including JAK1, CDH11, and TIE2/TEK, have been ated with cell adhesion and ECM, showed a nearly uniform found previously to be overexpressed in microvascular increased expression in the androgen-independent cells. This endothelial cells (24) or endothelial morphogenesis (23, was also unexpected, because the literature shows a mixture 25). The origin of this gene expression is puzzling, because of up-regulation and down-regulation of ECM and adhesion endothelial cells were excluded during microdissection and molecules during prostate cancer progression. Thus, androgen because tumors treated with androgen deprivation have been blockade initially seems to act in clinical prostate samples, at shown to display decreased microvessel density (22). Prostate least in part, by facilitating a more normal phenotype tumor cells may participate in vasculogenic mimicry, whereby through the reversal of two critical cancer-related activities: tumor cells themselves express endothelial-associated markers increased protein synthesis (19) and decreased adhesion. and form vasculogenic networks both in vitro and in vivo (26), Review of the literature indicates that this is not without which could account for the higher expression of these genes precedent. In a recent study, Patriarca et al. described up- in AIPC. regulation of E-cadherin and a/h-catenin in prostate tumors Gene expression related to IL-6 and its signaling pathway was after hormonal ablation and suggested that a more differen- also a central theme represented in the data. There is an tiated phenotype results after the treatment (20). It has also increasing body of evidence suggesting that IL-6 is involved in been recently suggested that telomerase expression patterns the progression of prostate cancer (27) and may even have are reverted toward a normal phenotype after hormone utility as a diagnostic marker for predicting progression (28). ablation, particularly in high-grade tumors (21). Moreover, a IL-6 signaling involves activation of signal transducer and review of protein expression changes after androgen depriva- activator of transcription (STAT) proteins by the Janus kinases tion therapy showed decreased proliferation markers (22), (JAK). Both JAK1 and STAT5B were differentially regulated in which seems to agree with our findings of a generalized this study, indicating perturbation of this pathway in AIPC. We decrease in protein synthesis. found previously that STAT5B was down-regulated in high- It is important to note, however, that several of the up- grade androgen-dependent tumors compared with moderate regulated adhesion and ECM genes are associated with grade (29). Because STAT5B was even further down-regulated endothelial cells (i.e., VWF, PECAM1 (CD31), COL5A2, in the AIPC cells, it may have potential as both a marker for COL15A1, LAMB1, FN1, THBS1, and SPARC; refs. 23–25). progression and a therapeutic target. In addition to IL-6

Fig. 1. Principal component analysis of androgen-dependent (red) and androgen-independent (green) prostate cancer.The probe sets were filtered to include only the11,663 transcripts detected in atleast10% ofall the samples.Theprojectiononthree principal components of greatest variation covering 34.7% of the total variance is shown.

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Table 3. Selected differentially expressed genes between androgen-dependent and androgen-independent tumor groups

Gene Probe set Fold change Parametric Description Map Significant symbol androgen-independent/ P reference androgen-dependent Angiogenesis LMO2 204249 _ s _ at 1.67 0.0011 LIM domain-only 2 11p13 (4 9) (rhombotin-like 1) VWF 202112 _ at 4.63 0.0014 vonWillebrand factor 12p13.3 (50) PECAM1 208982 _ at 2.62 0.0001 Platelet/endothelial cell 17 q 2 3 (5 0) adhesion molecule (CD31) THSP1 201108 _ s _ at 2.18 0.0038 Thrombospondin-1 15q15 (51) EDG4 206723 _ s _ at 0.57 0.0043 Endothelial differentiation, 19p12 (52) lysophosphatidic acid G-protein-coupled receptor, 4 SDC2 212158 _ at 3.13 0.0008 Syndecan-2 8q22-q23 (53) (heparan sulfate proteoglycan-1, cell surface ^ associated, fibroglycan) TEK 206702 _ at 2.82 0.0015 Tyrosine kinase, endothelial 9p21 (25) Cell adhesion BPAG1 212254 _ s _ at 2.78 0.0001 Bullous pemphigoid 6p12-p11 (39, 54) antigen 1, 230/240 kDa CDH11 207173 _ x _ at 3.10 0.0004 Cadherin-11,type 2, 16q22.1 (38) OB-cadherin (osteoblast) FN1 211719 _ x _ at 2.72 0.0007 Fibronectin-1 2q34 (55) Apoptosis/cell death TRAF5 204352 _ at 1.85 0.0019 Tumor necrosis factor 1q 3 2 (5 6 ) receptor-associated factor 5 GRIM19 220864 _ s _ at 0.21 0.0020 Cell death ^ regulatory protein GRIM19 19p13.2 (57) NMP200 203103 _ s _ at 0.45 0.0001 Nuclear matrix protein 11q12.2 (58) related to splicing factor PRP19 MCL1 200797 _ s _ at 0.48 0.0005 Myeloid cell leukemia 1q 2 1 (5 9 , 6 0 ) sequence1 (BCL2-related) GADD45B 207574 _ s _ at 0.26 0.0031 Growth arrest and DNA 19p13.3 (6 1) damage-inducible, h GADD45G 204121 _ at 0.23 0.0001 Growth arrest and DNA 9q22.1-q22.2 (61) damage-inducible, g Hormone response REA 201600 _ at 0.67 0.0042 Repressor of estrogen receptor activity 12p13 (62) KLK2 210339 _ s _ at 0.53 0.0011 Kallikrein-2, prostatic 19q13.41 (63) KLK3 204582 _ s _ at 0.29 0.0006 Kallikrein-3 (prostate specific antigen) 19q13.41 (63) GREB1 205862 _ at 0.18 0.0019 GREB1protein 2p25.1 (64) Oxidative stress COX8 2 0 1119 _ s _ at 0.57 0.0024 Cytochrome c oxidase subunitVIII 11q12-q13 (65) COX7C 217491 _ x_at 0.51 0.0041 Cytochrome c oxidase subunitVIIc 5q14 (65) SOD2 215078 _ at 0.11 0.0005 Superoxide dismutase-2, mitochondrial 6q25.3 (36, 37) Metastasis EIF4EL3 213571 _ s _ at 0.73 0.0027 Eukaryotic translation initiation factor 4E-like 3 2q37.1 (66) Prostate cancer associated NOV 214321 _ at 3.80 0.0016 Nephroblastoma overexpressed gene 8q24.1 (46) MIF 217871 _ s _ at 0.58 0.0037 Macrophage migration inhibitory factor 22q11.23 (47) (glycosylation-inhibiting factor) TACSTD2 202286 _ s _ at 0.51 0.0049 Tumor-associated calcium signal transducer 2 1p32-p31 (29) STAT5B 212550 _ at 0.71 0.0001 Signal transducer and 17q11.2 (29) activator of transcription 5B

NOTE: For genes where multiple probe sets were identified as differentially expressed, only one probe set was included. Only genes identified previously in the cancer literature are included. Most genes relating to the overrepresented genes ontologies, including genes relating to IL-6, are presented only inTable 4.

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Table 4. Overrepresented ontologies of genes differentially expressed in AIPC

Gene Fold Description Parametric P Probe set Gene ontology or symbol change relationship to IL-6

ST3GALVI 3.44 a2,3-Sialyltransferase 0.0045 213355 _ at PB, MB LUC7A 2.75 Cisplatin resistance ^ associated overexpressed protein 0.0007 220044 _ x _ at RC SF3B1 2.04 Splicing factor 3b, subunit1,155 kDa 0.0013 201071 _ x _ at RC KIAA0970 1.92 KIAA0970 protein 0.0031 202304 _ at RC, SCR PNAS4 1.92 CGI-146 protein 0.0003 212371 _ at RC, R SFRS11 1.91 Splicing factor, arginine/serine ^ rich11 0.0035 200685 _ at RC HNRPH3 1.73 Heterogeneous nuclear ribonucleoprotein H3 (2H9) 0.0011 208990 _ s _ at RC PTMA 1.59 Prothymosin, a (gene sequence 28) 0.0017 200773 _ x _ at RC, SCR UBE3A 1.57 Ubiquitin protein ligase E3A (human papilloma virus 0.0014 211575 _ s _ at PB E6-associated protein, Angelman syndrome) SFRS7 1.56 Splicing factor, arginine/serine-rich 7, 35 kDa 0.0044 201129 _ at RC FLJ10283 1.51 Hypothetical protein FLJ10283 0.0022 218534 _ s _ at RC EIF4EL3 0.73 Eukaryotic translation initiation factor 4E-like 3 0.0027 213571 _ s _ at PB NMT2 0.72 N-myristoyltransferase 2 0.0043 215069 _ at PB COPS6 0.72 COP9 subunit 6 (MOV34 homologue, 34 kDa) 0.0032 213504 _ at PB KIAA0759 0.71 KIAA0759 protein 0.0022 36865 _ at PB, RC MRP63 0.66 Mitochondrial ribosomal protein 63 0.0039 221995 _ s _ at SCR MRPL20 0.65 Mitochondrial ribosomal protein L20 0.0002 220526 _ s _ at RC,SCR,PB HNRPA0 0.65 Heterogeneous nuclear ribonucleoprotein A0 0.0007 201055 _ s _ at RC EIF3S9 0.65 Eukaryotic translation initiation factor 3, subunit 9, D,116 kDa 0.0001 203462 _ x _ at PB RPL34 0.65 Ribosomal protein L34 0.0010 200026 _ at RC,SCR,PB RPL39 0.63 Ribosomal protein L39 0.0015 208695 _ s _ at RC,SCR,PB RPL36 0.60 Ribosomal protein L36 0.0045 219762 _ s _ at RC.SCR,PB RPS21 0.55 Ribosomal protein S21 0.0028 200834 _ s _ at RC,SCR,PB RPS14 0.53 Ribosomal protein S14 0.0006 208646 _ at RC,SCR,PB RPL35A 0.53 Ribosomal protein L35a 0.0029 213687 _ s _ at RC,SCR,PB MRP63 0.51 Mitochondrial ribosomal protein 63 0.0009 204386 _ s _ at SCR 0.50 Similar to 40S ribosomal protein S18 0.0023 201049 _ s _ at RC,SCR,PB RPS16 0.45 Ribosomal protein S16 0.0046 213890 _ x _ at RC,SCR,PB RPS29 0.40 Ribosomal protein S29 0.0018 201094 _ at RC,SCR,PB GADD45B 0.28 Growth arrest and DNA damage-inducible, h 0.003 1 207574 _ s _ at RC,SCR,PB GADD45G 0.23 Growth arrest and DNA damage-inducible, g 0.0001 204121 _ at RC,SCR,PB

Abbreviations: RC, ribonucleoprotein complex; PB, protein biosynthesis; MB, macromolecule biosynthesis; R, ribosome; SCR, structural constituent of ribosome; CAMA, cell adhesion molecule activity. signaling, the down-regulation of IL-6 is likely related to the It is also important to compare the genes identified in this differential regulation of several of the other genes, including study with those hypothesized to be involved in the potential MCL1 (30), JUND and JUNB (31), and SDC2 (32). A mechanisms for the development of androgen-independence. potentially critical facet of IL-6 in prostate cancer is its ability Chen et al. recently showed that, in seven pairs of xenograft to independently activate the androgen receptor (AR; reviewed tumors before and after the development of androgen indepen- in ref. 33). Thus, it seems logical that the expression of the dence, only the AR gene was differentially expressed. In the androgen-responsive genes KLK2 and KLK3, and GADD45B study presented here, AR expression was not significantly and GADD45G, was lower in the AIPC cells in this study, different between the two groups. However, because the data because IL-6 was also decreased. Finally, neuroendocrine were analyzed for gene expression changes consistent among the differentiation may be involved in the development of AIPC tumors in each group, it is possible that increased AR expression (28), and IL-6 has been shown to promote neuroendocrine was present in a subset of the tumors, as a nonsignificant trend differentiation in prostate cancer cells (34). Because the AIPC of AR overexpression was present in the androgen-independent tumors showed differential expression of genes in the IL-6 group. However, although the model presented by Chen et al. pathway, we examined the data for the neuroendocrine markers showed that overexpression of AR alone was sufficient for the synaptophysin and chromogranin A. We found a trend of development of androgen independence, there are numerous increased chromogranin A expression (2.4-fold; P < 0.07) in the genes identified in the literature to be involved in this process. androgen-independent tumors, which concurs with others Feldman and Feldman (2) present a concise review of the showing more significant increases in neuroendocrine differ- potential mechanisms for the development of AIPC, and several entiation in androgen-independent disease (35). of the genes identified in the study presented here may fit these

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Table 4. Overrepresented ontologies of genes differentially expressed in AIPC (Cont’d)

Gene Fold Description Parametric P Probe set Gene ontology or symbol change relationship to IL-6 VWF 4.63 vonWillebrand factor 0.0014 202112 _ at ECM, CAMA CSPG2 3.10 Chondroitin sulfate proteoglycan 2 (versican) 0.0010 204619 _ s _ at ECM CDH11 3.10 Cadherin11,type 2, OB-cadherin (osteoblast) 0.0004 207173 _ x _ at CAMA LAMB1 3.01 Laminin, h1 0.0047 201505 _ at ECM, CAMA ASPN 2.87 Asporin (LRR class1) 0.0017 219087 _ at ECM FN1 2.72 Fibronectin1 0.0007 211719 _ x _ at ECM, CAMA COL15A1 2.67 Collagen, type XV, a1 0.0006 203477 _ at ECM, CAMA PECAM1 2.62 Platelet/endothelial cell adhesion molecule (CD31) 0.0001 208982 _ at CAMA FLJ20736 2.46 Hypothetical protein FLJ20736 0.0022 218244 _ at ECM COL5A2 2.30 Collagen, typeV, a20.0043221729_ at ECM SPARC 2.29 Secreted protein, acidic, cysteine-rich (osteonectin) 0.0045 212667 _ at ECM ECM2 2.25 ECM protein 2, female organ and adipocyte specific 0.0040 206101 _ at ECM THBS1 2.18 Thrombospondin1 0.0038 201108 _ s _ at ECM, CAMA LAMA4 2.13 Laminin, a4 0.0040 202202 _ s _ at ECM, CAMA LTBP2 1.61 Latent transforming growth factor-h binding protein 2 0.0050 204682 _ at ECM GNE 0.67 UDP-N-acetylglucosamine-2-epimerase/ 0.0027 205042 _ at CAMA N-acetylmannosamine kinase ICAM3 0.60 Intercellular adhesion molecule 3 0.0043 204949 _ at CAMA CD84 0.58 CD84 antigen (leukocyte antigen) 0.0032 211189_ _ x_ _ at CAMA BAIAP2 0.40 BAI1-associated protein 2 0.0012 209502 _ s _ at CAMA IL6 0.62 Interleukin-6 (IFN, h2) 0.0034 205207 _ at JAK1 2.30 Janus kinase1 (a protein tyrosine kinase) 0.0009 201648 _ at Signal transduction (27) STAT5B 0.71 Signal transducer and activator of transcription 5B 0.0001 212550 _ at Signal transduction (27) JUNB 0.45 junB proto-oncogene 0.0035 201473 _ at Gene expression (31) JUND 0.39 junD proto-oncogene 0.0002 203752 _ s _ at Gene expression (31) MCL1 0.48 Myeloid cell leukemia sequence1 (BCL2-related) 0.0005 200797 _ s_at Gene expression (30) SDC2 3.13 Syndecan-2 (heparan sulfate proteoglycan1, 0.0008 212158 _ at Gene expression (32) cell surface ^ associated, fibroglycan) LUC7A 2.75 Cisplatin resistance ^ associated 0.0007 220044 _ x _ at Chemosensitivity (67) overexpressed protein KLK2 0.53 Kallikrein-2, prostatic 0.0011 210339 _ s_ _ at AR activation (33) KLK3 0.29 Kallikrein-3 (prostate-specific antigen) 0.0006 204582 _ s _ at AR activation (68) GADD45B 0.26 Growth arrest and DNA-damage inducible, h 0.0031 207574 _ s _ at AR activation (33) GADD45G 0.23 Growth arrest and DNA-damage inducible, g 0.0001 204121 _ at AR activation (33)

postulated mechanisms. For example, the antioxidant enzyme maintenance of the androgen-independent phenotype are superoxide dismutase-2 was down-regulated 9-fold in the necessary. androgen-independent tumors and has been shown to inversely Standard approaches to the analysis of microarray data, correlate with prostate cancer progression in cell models (36) including our own as discussed above, cluster genes based on and in tissue (37), fitting the model of a decrease in protective transcriptional profiles and thus overlook gene expression enzymes that may cause an increase in the frequency of patterns of contiguous chromosomal regions. Using the mutation. Another potential mechanism for the development newly developed DIGMAP approach, we identified nine of AIPC is the ‘‘outlaw pathway,’’ whereby the AR is stimulated by genomic regions of interest in AIPC. Most of the regions nonandrogen growth factors, and IL-6, discussed above, fits appear from the literature to be frequent deletions in a this model, as do several genes downstream of AR activation variety of human cancers, and regions 1p36, 8p21, and (e.g. KLK2, KLK3, and GADD45), which were differentially 16q21 have additional significance in prostate cancer. These expressed. In addition, CDH11 has been shown previously to regions are generally hypothesized to include tumor suppres- be up-regulated in hormone-refractory prostate cancer cell sor genes or other genes required for maintenance of a lines (38) and showed 3-fold higher expression in the AIPC normal or less aggressive phenotype. For example, chromo- cells in this study. BPAG1 also showed increased expression of somal deletions at 16q have been correlated with more f3-fold in the AIPC cells. BPAG1 is a hemidesmosome malignant grade tumors (40) and with tumors with poor protein whose expression becomes up-regulated with the onset clinical outcomes (41), which agrees with our findings that of invasive growth (39). Further studies examining the specific this region may be increasingly affected during progression to roles of the genes identified here in the development or the androgen-independent state.

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Table 5. Chromosomal regions of down-regulation in AIPC

Chromosome region No. genes Citations in prostate Citations in all cancers Prostate/all cancers (%) 1p36.1-1p36.33 26 18 56 32 3p21.2-3p21.31 81 4 443 1 6p21.31-6p21.33 160 2 188 1 8p21.2-8p23.3 221 92 356 26 11p15.3-11p15.5 247 4 460 1 11q12 . 3 -11q13 . 5 3 5 0 3 51 6 12q23-12q24.31 9 2 56 4 16q12.1-16q13 50 3 52 6 16q21-16q24.3 333 46 354 13

Overall, comparison of the expression data relative to the genome is intriguing. The androgen-independent tumor cells show decreased expression of several genes that map to distinct genomic regions, including known hotspots for prostate cancer. Mechanistically, this could occur via either DNA deletions and/or epigenetic phenomenon, such as gene promoter methylation. There are two possible implications of this finding. First, although androgen withdrawal therapy is effective at slowing the progression of prostate cancer clinically, it does not stop the continued progression of expression changes related to genomic alterations. Alternative- ly, there may be inherent differences in genomic status between patients where the majority will not recur after treatment (the androgen-dependent group in this study) and those that are clearly aggressive (the androgen-independent group). This is an enticing possibility, as it would suggest that, for prognostic purposes, the two patient groups could be stratified based on genome-related expression data. However, an important caveat is that the androgen-independent and androgen-dependent tumor groups in this study differ in that, in addition to the status of androgen-dependence, one group became clinically aggressive and the other may not. Consequently, the expression differences could be due to this clinical behavior rather than to hormonal therapy and androgen independence. There are numerous studies in the prostate cancer literature that compare recurrent tumors with tumors before recurrence, without separating out the tumors that would never recur, and this complicates the conclusions that can be drawn. Identifying gene expression profiles that segregate the androgen-dependent tumor that will recur from those that will not is an area of great interest (42) and will make an important contribution to prostate cancer prognostics. Approaches that emphasize the identification of key groups of genes, such as the gene ontology analysis we present here, may shed light on the identification of recurrent tumors and how they respond to therapy. These data provide a significant contribution to our knowledge of the molecular characteristics of AIPC; however, Fig. 2. Chromosomal view of differential gene expression in androgen-independent the potential weaknesses of the study warrant discussion. and androgen-dependent prostate cancer. Microarray data from five androgen-independent samples and six androgen-dependent samples are displayed First, because the AIPC biopsy specimens contained relatively in columns. Rows represent ordered mapped chromosome locations derived from few tumor cells and most were completely exhausted in part of chromosome16 (16q21-16q24.3 or 56-89 Mb). Fluorescence ratios were obtaining the RNA for microarray analysis, it was not calculated at a specific gene level across all samples (tumor/tumor sample mean) and plotted on a log2 scale.The red color represents an expression level above possible to conduct traditional validation experiments, such the mean expression of a gene across all samples, the blackcolor represents as quantitative reverse transcription-PCR. However, the use of mean expression, and the green color represents expression lower than the mean.

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RNA amplification in conjunction with microarray analysis androgen-independent specimens, and processing of whole has been repeatedly validated in the literature (43–45), and prostatectomies and core biopsies, although both frozen, are the protocol we used provided high efficiency and little intrinsically different as we have studied previously (48). technical variation between the samples both within and Thus, although the resulting data show significant corrobora- between the tumor groups. In addition, in silico validation tion in the literature regarding differential expression of showed that several of the genes identified in this study [e.g., individual genes, and the genes could be grouped by gene NOV (46) and MIF (47)] have been shown previously to be ontology analysis and regions of potential chromosomal differentially expressed in androgen-independent cells or with deletion, it is still possible that the results were influenced increasing prostate tumor grade, and Table 3 (column 7) by bias error. In spite of this, understanding androgen inde- frequently cites a report validating the findings in this study. pendence as it develops in patients is of critical importance A second concern was that the differentially expressed genes and must be moved forward even with its inherent challenges. could have resulted from the treatment that the AIPC patients Thus, this initial study is a screening effort to identify had undergone rather than being a characteristic of AIPC potential biomarker and therapeutic candidates, some of itself. However, because the AIPC biopsies included in this which may be false positives. The design of subsequent study derived from patients who had undergone a diverse validation studies will benefit by including such sample array of treatment, it was unlikely that treatment alone sets as those with larger numbers of cases, most of which produced the consistent differential expression we identified. will be formalin-fixed, patient-matched series and autopsy A third concern was that the differentially expressed genes specimens. could have resulted from the different processing that In conclusion, this study defines the effects of androgen biopsies undergo compared with whole prostatectomies. ablation therapy on the gene expression profile of primary However, the RNA isolated from all samples was of similar prostate cancer cells that are resistant to treatment. These data quality. Finally, the ratios of differential expression are establish the state of the transcriptome of a discrete and modest in comparison with studies using little or no RNA important step in the process of prostate cancer progression, amplification. However, RNA amplification dampens the beyond an untreated high-grade lesion yet before an androgen- variation of gene expression (13), which likely reduced the independent metastatic lesion, and may be critical to developing dynamic range of the data while still allowing for the intervention strategies for this advanced disease. statistically significant separation of gene expression between the two groups. Acknowledgments The various potential biases in the study, although addressed to the best of our ability, remain a source of concern. We were We thankDr. David D. Roberts (Biochemical Pathology Section, Center for not able to obtain patient-matched, androgen-dependent and Cancer Research, National Cancer Institute) for valuable discussion.

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Clin Cancer Res 2005;11(19) October 1, 2005 6834 www.aacrjournals.org Downloaded from clincancerres.aacrjournals.org on September 26, 2021. © 2005 American Association for Cancer Research. Molecular Alterations in Primary Prostate Cancer after Androgen Ablation Therapy

Carolyn J.M. Best, John W. Gillespie, Yajun Yi, et al.

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