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Original Contribution |

α-Methylacyl Coenzyme A Racemase as a Tissue Biomarker for Prostate Cancer FREE

Mark A. Rubin, MD; Ming Zhou, MD, PhD; Saravana M. Dhanasekaran, PhD; Sooryanarayana Varambally, PhD; Terrence R. Barrette; Martin G. Sanda, MD; Kenneth J. Pienta, MD; Debashis Ghosh, PhD; Arul M. Chinnaiyan, MD, PhD
[+] Author Affiliations

Author Affiliations: Departments of Pathology (Drs Rubin, Zhou, Dhanasekaran, Varambally, and Chinnaiyan and Mr Barrette), Urology (Drs Rubin, Sanda, Pienta, and Chinnaiyan), Internal Medicine (Dr Pienta), and Biostatistics (Dr Ghosh) and Comprehensive Cancer Center (Drs Rubin, Sanda, Pienta, and Chinnaiyan), University of Michigan Medical School, Ann Arbor.


JAMA. 2002;287(13):1662-1670. doi:10.1001/jama.287.13.1662.
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Published online

Context Molecular profiling of prostate cancer has led to the identification of candidate biomarkers and regulatory genes. Discoveries from these genome-scale approaches may have applicability in the analysis of diagnostic prostate specimens.

Objectives To determine the expression and clinical utility of α-methylacyl coenzyme A racemase (AMACR), a gene identified as being overexpressed in prostate cancer by global profiling strategies.

Design Four gene expression data sets from independent DNA microarray analyses were examined to identify genes expressed in prostate cancer (n = 128 specimens). A lead candidate gene, AMACR, was validated at the transcript level by reverse transcriptase polymerase chain reaction (RT-PCR) and at the protein level by immunoblot and immunohistochemical analysis. AMACR levels were examined using prostate cancer tissue microarrays in 342 samples representing different stages of prostate cancer progression. Protein expression was characterized as negative (score = 1), weak (2), moderate (3), or strong (4). Clinical utility of AMACR was evaluated using 94 prostate needle biopsy specimens.

Main Outcome Measures Messenger RNA transcript and protein levels of AMACR; sensitivity and specificity of AMACR as a tissue biomarker for prostate cancer in needle biopsy specimens.

Results Three of 4 independent DNA microarray analyses (n = 128 specimens) revealed significant overexpression of AMACR in prostate cancer (P<.001). AMACR up-regulation in prostate cancer was confirmed by both RT-PCR and immunoblot analysis. Immunohistochemical analysis demonstrated an increased expression of AMACR in malignant prostate epithelia relative to benign epithelia. Tissue microarrays to assess AMACR expression in specimens consisting of benign prostate (n = 108 samples), atrophic prostate (n = 26), prostatic intraepithelial neoplasia (n = 75), localized prostate cancer (n = 116), and metastatic prostate cancer (n = 17) demonstrated mean AMACR protein staining intensity of 1.31 (95% confidence interval, 1.23-1.40), 2.33 (95% CI, 2.13-2.52), 2.67 (95% CI, 2.52-2.81), 3.20 (95% CI, 3.10-3.28), and 2.50 (95% CI, 2.20-2.80), respectively (P<.001). Pairwise comparisons demonstrated significant differences in staining intensity between clinically localized prostate cancer compared with benign prostate tissue, with mean expression scores of 3.2 and 1.3, respectively (mean difference, 1.9; 95% CI, 1.7-2.1; P<.001). Using moderate or strong staining intensity as positive (score = 3 or 4), evaluation of AMACR protein expression in 94 prostate needle biopsy specimens demonstrated 97% sensitivity and 100% specificity for detecting prostate cancer.

Conclusions AMACR was shown to be overexpressed in prostate cancer using independent experimental methods and prostate cancer specimens. AMACR may be useful in the interpretation of prostate needle biopsy specimens that are diagnostically challenging.

Figures in this Article

Prostate cancer affects 1 of 9 men older than 65 years and is a leading cause of cancer-related death in men, second only to lung cancer.1,2 While the advent of prostate-specific antigen (PSA) screening has led to earlier detection of prostate cancer,3 the impact of PSA screening on cancer-specific mortality is unknown, pending the results of prospective randomized screening studies.46 A major limitation of the serum PSA test is a lack of prostate cancer sensitivity and specificity, especially in the intermediate range of PSA detection (4-10 ng/mL). Coincident with increased serum PSA testing, there has been a significant increase both in the number of prostate needle biopsies performed7 and in the number of equivocal prostate needle biopsy specimens.8 Thus, development of additional serum and tissue biomarkers to supplement PSA screening is needed.

Molecular profiling establishes a new perspective in the study of cancer.9 Recent studies have suggested that it is possible to study cancer with a global perspective, taking advantage of DNA1013 and protein microarrays14 as "windows" into the expressed human genome. Several groups recently implemented DNA microarrays to analyze prostate cancer specimens.1518 Different laboratories, using distinct microarray platforms and reference controls, identified and validated hepsin as a serine protease up-regulated in prostate cancer.1518 Using high-density tissue microarrays (TMAs), our group15 reported that both hepsin and another protein, pim-1 kinase, are down-regulated in a sample of aggressive, localized prostate cancer specimens, making these biomarkers potentially useful for predicting prognosis but less applicable for diagnosing prostate cancer in tissue sections.

In this study, we examined α-methylacyl coenzyme A racemase (AMACR), a peroxisomal and mitochondrial enzyme that was found to be up-regulated in prostate cancer..15,16,18 Although the precise physiologic roles of AMACR are not clear, this enzyme has an important role in bile acid biosynthesis and β-oxidation of branched-chain fatty acids19,20 and mediates the interconversion of (R)- and (S)-2-methyl-branched-chain fatty acyl coenzyme As.19 Mutations of the AMACR gene have been shown to cause adult-onset sensory motor neuropathy,21 but, to our knowledge, a link to prostate cancer has not been made.

Microarray Data Analysis

Our overall approach of discovery and validation of candidate biomarkers and regulatory genes in prostate cancer is shown in Figure 1.22 By using DNA microarrays, we can examine thousands of genes in the context of prostate cancer (Figure 1B-D). Combining this approach with tissue microarrays, we can simultaneously examine hundreds of clinically stratified patient specimens effectively (Figure 1F-H). Thus, the development and coordination of these technologies allows the survey of thousands of genes in many patients in a high-throughput fashion.

Figure 1. Schematic of DNA and Tissue Microarray Approach
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First, we examined 4 independent gene expression data sets, including our own.15,16,18 To investigate the statistical significance associated with the differential expression of AMACR across 3 independent microarray studies, we used standard methods from meta-analysis23 to combine the results. For each of the studies, we computed a t statistic (with the 2 groups being benign tissue compared against localized prostate cancer tissue) and transformed the associated P values using a negative logarithmic transformation. These numbers were then doubled and added to arrive at a summary measure of differential gene expression across the 3 studies. To assess the statistical significance associated with this summary measure, a permutation-based approach was used.23 Tissue types were permutated within studies, the summary measure was computed for the permutated data, and a P value was computed using the permutation distribution of the summary measure. One million resamplings from the permutation distribution were implemented. Two of the 3 studies used the spotted complementary DNA (cDNA) microarray technology, whereas Affymetrix oligonucleotide microarrays (GeneChip) were used for the third study. To address whether t statistics from the 3 studies are comparable, we used the Wilcoxon-Mann-Whitney statistic separately for the 3 studies.

Prostate Sample Collection

To examine the widest range of prostate cancer specimens, clinical samples were obtained from the radical prostatectomy series at the University of Michigan and from the Rapid Autopsy Program.

Prostatectomy cases for the TMA outcomes array were selected from a cohort of 632 patients, who underwent radical retropubic prostatectomy at the University of Michigan as a primary therapy (ie, no preceding hormonal or radiation therapy) for clinically localized prostate cancer from 1994 to 1998. Consecutive cases were taken from 1995 and 1996 to ensure sufficient clinical follow-up. Clinical and pathologic data for all patients were acquired with approval from the Institutional Review Board at the University of Michigan. Detailed clinical, pathologic, and TMA data are maintained on a secure relational database.24

The prostate specimens were transported to the frozen section room located adjacent to the operating rooms and processed within approximately 15 to 20 minutes after surgical resection. The prostate specimens were partially sampled with approximately 50% of the tissue used for research. This protocol has been evaluated in a formal study to ensure that partial sampling does not impair accurate staging and evaluation of the surgical margins.25

The Rapid Autopsy Protocol has been described previously.26 In brief, patients with advanced hormone-refractory prostate cancer are asked to participate in this posthumous, institutional review board–approved tumor donor program, and permission for autopsy is obtained before death, with consent provided by the patient or next of kin. Twenty-three complete autopsies have been performed as part of this program, with a median time from death to autopsy of 3 hours. Hormone-refractory primary and metastatic prostate cancer samples are collected. Half of each specimen is snap frozen in liquid nitrogen and the other half is placed in 10% buffered formalin. The fixed samples are embedded in paraffin and used for the development of TMAs. As with the prostatectomy samples, the study pathologist (M.A.R.) reviewed the glass slides, circled areas of viable prostate cancer, avoiding areas of necrosis, and used these slides as a template for TMA construction.

Pathologic Examination and Evaluation

Prostate gland specimens were inked before pathological assessment of surgical margins. Surgical margins from the apex and base were cut perpendicular to the prostatic urethral axis. The seminal vesicles were cut perpendicular to their entry into the prostate gland and submitted as the seminal vesicle margin. The prostate specimens for this study were all partially embedded, taking alternate full sections from the apex, mid, and base. Detailed prostatectomy pathology reports included the presence or absence of surgical margin involvement by tumor (surgical margin status), the presence of extraprostatic extension, and seminal vesicle invasion. Tumors were staged using the TNM system, which includes extraprostatic extension and seminal vesicle invasion but does not take into account surgical margin status.27 Tumors were graded using the Gleason grading system.28,29 As preparation for the construction of the TMAs, all glass slides were reexamined to identify areas of benign prostate, prostatic atrophy, high-grade PIN, and prostate cancer. To optimize the transfer of these designated tissues to the arrays, the area of tumor involvement was encircled on the glass slide template as tightly around each lesion as possible. Areas with infiltrating tumor adjacent to benign glands were avoided.

Reverse Transcriptase Polymerase Chain Reaction

Total RNA integrity was judged by denaturing-formaldehyde agarose gel electrophoresis. Complementary DNA was prepared using 1 µg of total RNA isolated from prostate tissue specimens. Primers used to amplify specific gene products were as follows: AMACR sense, 5′-CGTATGCCCCGCTGAATCTCGTG-3′; AMACR antisense, 5′-TGGCCAATCATCCGTGCTCATCTG-3′; glyceraldehyde-3-phosphate dehydrogenase (GAPDH) sense, 5′-CGGAGTCAACGGATTTGGTCGTAT-3′; and GAPDH antisense, 5′-AGCCTTCTCCATGGTGGTGAAGAC-3′. Reverse transcriptase polymerase chain reaction (RT-PCR) conditions for AMACR and GAPDH were 94°C for 5 minutes, 28 cycles of 95°C for 1 minute, 60°C for 1 minute (annealing), 72°C for 1 minute, and a final elongation step of 72°C for 7 minutes. The RT-PCR reactions used a volume of 50 µL, with 1 unit of Taq DNA polymerase (Invitrogen, Carlsbad, Calif). Amplification products (5 µL) were separated by 2% agarose gel electrophoresis and visualized by UV light.

Immunoblot Analysis

Representative prostate tissue specimens that were previously profiled using DNA microarrays15 were used for Western blot analysis. Tissues were homogenized in NP-40 lysis buffer containing 50 mM Tris hydrochloride, pH 7.4, 1% Nonidet P-40 (Sigma, St Louis, Mo), and complete proteinase inhibitor cocktail (Roche, Indianapolis, Ind). Fifteen micrograms of protein extracts was mixed with sodium dodecyl sulfate sample buffer and electrophoresed onto a 10% sodium dodecyl sulfate–polyacrylamide gel under reducing conditions. The separated proteins were transferred onto nitrocellulose membranes (Amersham Pharmacia Biotech, Piscataway, NJ). The membrane was incubated for 1 hour in blocking buffer (Tris-buffered saline with 0.1% Tween and 5% nonfat dry milk). The AMACR antibody (a gift of Ronald J. A. Wanders) was applied at 1:10 000 diluted in blocking buffer overnight at 4°C. After washing 3 times with Tris-buffered saline with 0.1% Tween buffer, the membrane was incubated with horseradish peroxidase–linked donkey anti–rabbit IgG antibody (Amersham Pharmacia Biotech) at 1:5000 for 1 hour at room temperature. The signals were visualized with the ECL detection system (Amersham Pharmacia Biotech) and autoradiography.

Immunohistochemical Analysis

Standard indirect biotin-avidin immunohistochemical analysis was performed to evaluate AMACR protein expression using a polyclonal anti-AMACR antibody (1:5000 dilution, a gift of Ronald J. A. Wanders). Protein expression was scored as negative (score = 1), weak (2), moderate (3), and strong (4).

TMA Construction, Digital Image Capture, and Analysis

Five TMAs were used for this study. Three contained tissue from consecutive prostatectomies from 1996 and 2 contained hormone-refractory prostate cancer from the Rapid Autopsy Program. The TMAs were assembled using the manual tissue arrayer (Beecher Instruments, Silver Spring, Md) as previously described.30,31 Tissue cores from the circled areas (as described herein) were targeted for transfer to the recipient array blocks. Five replicate tissue cores were sampled from each of the selected tissue types. The 0.6-mm-diameter TMA cores were each spaced at 0.8 mm from core center to core center. After construction, 4-µm sections were cut, and hematoxylin-eosin staining was performed on the initial slide to verify the histologic diagnosis.

AMACR protein expression was evaluated using the BLISS Imaging System (Bacus Lab, Lombard, Ill) in a blinded manner. All images were scored for AMACR protein expression intensity. In addition, all TMA samples were assigned a diagnosis (eg, benign, atrophy, PIN, or prostate cancer), with verification required at each step. The TMA slides were evaluated for proliferation index using the CAS200 Cell Analysis System (Bacus Lab). Selected areas were evaluated under the ×40 objective. Measurements were recorded as the percentage of total nuclear area that was positively stained. All positive nuclear staining, regardless of the intensity, was measured. Sites for analysis were selected to minimize the presence of stromal and basal cells; only tumor epithelium was evaluated. Specimens were evaluated for Ki-67 expression as previously described.31 Each measurement was based on approximately 50 to 100 epithelial nuclei. Because of the fixed size of TMA samples, 5 repeat nonoverlapping measurements were the maximum attainable.

Differences in AMACR protein expression were evaluated statistically using the mean score results from each case for each prostate tissue type (eg, benign, atrophy, high-grade prostatic intraepithelial neoplasia, localized prostate cancer, and hormone-refractory prostate cancer). To test for significant differences in the mean AMACR protein expression among all tissue types, we performed a 1-way analysis of variance (ANOVA) test. To determine differences between all pairs (eg, localized prostate cancer vs benign), we performed a post hoc analysis using the Scheffe method.32 The mean expression scores for all examined cases were presented in a graphical format using error bars with 95% confidence intervals (CIs). For the clinically localized prostate cancer samples, AMACR protein expression was evaluated for associations with pathology parameters (eg, advanced tumor stage and surgical margin involvement) and clinical outcome as measured by postsurgical PSA progression (PSA >0.2 ng/mL) by Cox hazards regression analysis.

Analysis of Prostate Needle Biopsy Specimens

To evaluate the usefulness of AMACR expression in diagnostic, 18-gauge needle biopsy specimens, we collected 100 consecutive biopsy specimens with prostate cancer or atypia that required further workup from one calendar year (2001). All cases were immunostained using 2 basal cell–specific markers (34βE12 and p63) and AMACR. Twenty-six of these cases were seen in consultation by one of the authors (M.A.R.) and are considered diagnostically difficult, requiring expert review and additional characterization. Six cases did not have sufficient tissue for further evaluation by AMACR.

Specificity, sensitivity, and positive and negative predictive values were determined. The criterion standard for accurately diagnosing prostate cancer was reviewed by an experienced genitourinary pathologist (in this case, M.A.R.) using a combination of routine hematoxylin-eosin–stained slides and a basal cell–specific marker (eg, p63 or 34βE12). All diagnoses made on needle biopsy specimens have been confirmed by pathologic review of prostatectomy specimens.

Gene Expression Data Sets

By examining our gene expression data set,15 we identified an interesting candidate gene, AMACR, that was consistently overexpressed in prostate cancer. Evaluation of AMACR transcript levels as determined by DNA microarray analysis of 57 prostate cancer specimens showed that in relation to benign prostate tissues, localized prostate cancer and metastatic prostate cancer were 3.1-fold (Mann-Whitney test, P<.001) and 1.67-fold (Mann-Whitney test, P<.004) up-regulated, respectively (represented as Cy5/Cy3 ratios) (Figure 2).

Figure 2. DNA Microarray Analysis and Up-regulation of AMACR in Prostate Cancer
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α-Methylacyl coenzyme A racemase (AMACR) transcripts as determined by DNA microarray analysis from 57 prostate samples15 were grouped according to sample type and averaged. The experimental sample was labeled with Cy5 fluorescent dye, whereas the reference sample (pool of benign prostate tissue) was labeled with Cy3 fluorescent dye. The box plot demonstrates the range of AMACR expression within each group. The middle horizontal bars indicate median values; the upper and lower limits of the boxes, interquartile ranges; and the error bars, 95% confidence intervals.

Summary of findings from 3 studies that used high-density DNA microarrays to analyze prostate cancer and measured AMACR gene expression showed a statistically significant differential expression of AMACR between benign prostate and prostate cancer (Table 1).

Table Graphic Jump LocationTable. Statistical Analysis of α-Methylacyl Coenzyme A Racemase (AMACR) Expression in Independent Prostate Cancer Gene Expression Data Sets
AMACR Transcript and Protein

Using AMACR-specific primers, RT-PCR performed on the various RNA samples from 28 prostate tissue specimens and 6 prostate cell lines (Figure 3A) showed that an RT-PCR product was observed in the 20 localized prostate cancer samples but not in the benign samples examined. Metastatic prostate cancer and prostate cell lines displayed varying levels of AMACR transcript compared with localized prostate cancer. Immunoblot analysis on selected prostate tissue extracts showed overexpression of AMACR protein in malignant prostate tissue relative to benign prostate tissue (Figure 3B).

Figure 3.AMACR Transcript and Protein Levels in Prostate Cancer
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A, Reverse transcriptase polymerase chain reaction (RT-PCR) was used to detect α-methylacyl coenzyme A racemase (AMACR) transcript levels in RNA preparations from prostate tissue extracts. Glyceraldehyde-3-phosphate dehydrogenase (GAPDH) served as the internal control. B, Immunoblot analysis of AMACR in prostate tissue extracts. β-Tubulin serves as control for sample loading. Pool indicates RNA from normal prostate tissues obtained from a commercial source; BPH, benign prostatic hyperplasia; NAP, normal adjacent prostate tissue from a patient who has prostate cancer; and 3 + 3, 3 + 4, 4 + 4, the major and minor Gleason patterns of the clinically localized prostate cancer examined. Various prostate cell lines were also examined. RT-PCR without enzyme (−RT) served as a negative control.
AMACR Protein Expression

In separate prostate samples than those used in the cDNA expression array analysis, high-density TMAs revealed moderate-to-strong AMACR protein expression in clinically localized prostate cancer samples with predominately cytoplasmic localization (Figure 4). Levels of AMACR protein expression in malignant epithelia were greater than in adjacent benign epithelia (Figure 3B). Both PIN and some atrophic lesions, which are thought to be potentially precancerous lesions,33,34 demonstrated cytoplasmic staining of AMACR. High-grade prostate cancer (Gleason score, 4 + 4 = 8) and low-grade prostate cancer (not shown) demonstrated strong cytoplasmic staining (Figure 3C). However, no association was identified with AMACR staining intensity and Gleason (tumor) score (data not shown). Many hormone-refractory, metastatic prostate cancer samples (from the Rapid Autopsy Protocol) demonstrated only weak AMACR expression (Figure 3D) but uniform PSA immunostaining (data not shown), confirming the immunogenicity of these samples.

Figure 4. Characterization of AMACR Protein Expression Using Prostate Cancer Tissue Microarrays
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α-Methylacyl coenzyme A racemase (AMACR) protein expression by standard biotin-avidin immunohistochemical analysis using a polyclonal mouse antibody to AMACR was evaluated on a wide range of prostate tissues using high-density tissue microarrays. Brown chromogen indicates positive staining. Near uniform moderate-to-strong AMACR protein expression (score = 3 and 4, respectively) was observed in prostate cancer samples from men with clinically localized prostate cancer (A, B). Adjacent areas of benign prostate tissue (A, B, arrowheads) did not express AMACR, making AMACR a highly specific prostate cancer marker. Strong staining was also observed in high-grade (Gleason score, 4 + 4 = 8) tumors (C) but was significantly weaker in hormone-refractory metastatic prostate cancer samples (D). (Counterstain, hematoxylin; original magnifications ×200).

Quantitation of TMA data in benign prostate tissue (n = 108 samples), atrophic prostate (n = 26), PIN (n = 75), localized prostate cancer (n = 116), and metastatic prostate cancer (n = 17) demonstrated mean AMACR protein staining intensity of 1.31 (SE, 0.041; 95% CI, 1.23-1.40), 2.33 (SE, 0.096; 95% CI, 2.13-2.52), 2.67 (SE, 0.071; 95% CI, 2.52-2.81), 3.20 (SE, 0.046; 95% CI, 3.10-3.28), and 2.50 (SE, 0.14; 95% CI, 2.20-2.80), respectively (1-way ANOVA, P<.001). Pairwise comparisons demonstrated differences in staining intensity between clinically localized prostate cancer with respect to benign prostate tissue, with mean expression scores of 3.2 and 1.3, respectively (ANOVA post hoc analysis using Scheffé method; mean difference, 1.9; 95% CI, 1.7-2.1; P<.001). Significant differences were also seen between benign tissue and PIN (1.4; 95% CI, 1.1-1.6; P<.001) and benign and prostatic atrophy (1.02; 95% CI, 0.70-1.36; P<.001). No significant differences in AMACR protein expression were identified between prostatic intraepithelial neoplasia and prostatic atrophy (0.34; 95% CI, –0.017 to 0.698; P = .12). A significant decrease in AMACR protein expression was observed in the metastatic hormone-refractory prostate cancer samples compared with clinically localized prostate cancer (0.699; 95% CI, 0.292-1.107; P<.001) (Figure 5).

Figure 5. Mean AMACR Protein Staining Intensity
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AMACR indicates α-methylacyl coenzyme A racemase; PAH, prostatic atrophic hyperplasia; PIN, prostatic intraepithelial neoplasia; and error bars, 95% confidence intervals.

There was no significant association between AMACR expression and Ki-67 expression (a marker of tumor proliferation)30 (r = 0.13; P = .22). There were no significant associations between AMACR protein expression and pathology parameters, such as radical prostatectomy Gleason score, tumor stage, tumor size (in centimeters), or surgical margin status (data not shown). α-Methylacyl coenzyme A racemaseprotein levels were not associated with PSA recurrence following surgery in 120 prostatectomy cases within a median follow-up time of 3 years (data not shown). α-Methylacyl coenzyme A racemase demonstrated uniform moderate-to-strong expression in clinically localized prostate cancer with high tumor sensitivity and specificity.

Clinical Utility of

In evaluation of the clinical utility of AMACR immunostaining on 94 prostate needle biopsy specimens (Figure 6), we considered moderate or strong staining intensity to be positive. We were not convinced that weak staining intensity could be reliably distinguished from negative staining with faint background staining. Of the 94 specimens, 70 were diagnosed as prostate cancer by pathologic review. Of these, AMACR protein was considered positive in 68, was falsely negative in 2, and was negative in 24. The sensitivity and specificity were calculated as 97% and 100%, respectively. The positive predictive value was 100% and the negative predictive value was 92%. These results included 26 cases for which the final diagnosis required expert pathologic review and the use of a basal cell–specific immunohistochemical marker (eg, 34βE12 or p63). These 26 cases were particularly difficult diagnostically for several reasons. For example, the atypical focus in question often consisted of only 4 or 5 glands. Furthermore, some cases demonstrated bland nuclear features, making the diagnosis more challenging, whereas some required distinguishing a cancerous lesion from PIN.

Figure 6. AMACR Utility in Diagnosing Prostate Cancer on Needle Biopsy Specimens
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In prostate needle biopsy specimens with a small amount of prostate cancer (A, B), a basal cell–specific marker, such as p63 (C) or 34βE12 (not shown), can be used to identify benign prostatic glands (brown chromogen). C, Absence of staining confirms that the small atypical area is prostate cancer. D, Using α-methylacyl coenzyme A racemase (AMACR) immunohistochemical analysis, however, positive staining (brown chromogen) is present in prostate cancer but not in the benign glands (compare with C). (A and B, hematoxylin-eosin; C, immunohistochemical stain using monoclonal antibody for p63 and hematoxylin counterstain; D, standard biotin-avidin complex immunohistochemistry using a polyclonal mouse antibody to AMACR and hematoxylin counterstain. Original magnifications: A, ×100; B, ×400; C, ×200; and D, ×200).

This approach to discovery and validation of biologically and clinically relevant genes in prostate cancer involves DNA microarrays serving as a discovery "engine" to identify novel candidate genes and TMAs to validate and characterize genes in patient specimens.

In this study, we examined gene expression data sets from 3 independent groups (including our own) and identified AMACR as a gene consistently up-regulated in prostate cancer across all 3 studies. Grouping tissue samples into benign prostate, benign prostatic hyperplasia, localized prostate cancer, and metastatic prostate cancer allowed us to evaluate AMACR expression along a line of prostate cancer progression. In this context, TMA analysis provided important data on the in situ protein expression of AMACR, suggesting that it was prostate cancer specific.

α-Methylacyl coenzyme A racemase encodes an enzyme that catalyzes the racemization of α-methyl–branched carboxylic coenzyme A thioesters19 and is localized in peroxisomes and mitochondria.19,20 Deficiency of AMACR has been linked to certain adult-onset sensory motor neuropathies; however, clinical symptoms are often mild and the condition presumably remains undiagnosed in many affected individuals.21,35 Identification of the overexpression of AMACR in prostate cancer may have clinical implications beyond potential diagnostic uses. For example, AMACR activity may be required for prostate cancer growth and, by virtue of its specificity, may serve as an attractive therapeutic target. Presumably, specific inhibition of AMACR activity may have minimal toxic effects, because individuals with AMACR deficiency exhibit only mild clinical manifestations.21,35

Screening tests for prostate cancer include serum PSA level, digital rectal examination, and transrectal ultrasound. A positive screening test result, in combination with other clinical factors (eg, patient age), is an indication for prostate needle biopsy. Based on the architectural pattern of the cancerous glands, pathologists assign a Gleason grade, which is associated with clinical outcome.36 In diagnostically challenging cases, pathologists often use the basal cell markers 34βE123739 or p63,40,41 which stain the basal cell layer of benign glands, which is not present in malignant glands (Figure 6). Thus, in some biopsy specimens, the pathologist must rely on absence of staining to make the final diagnosis of prostate cancer.

Unlike AMACR, immunohistochemical stains for PSA, a prototypic cancer biomarker, highlight both normal and malignant prostatic epithelium. Thus, in this context, AMACR may have potential clinical utility for prostate needle biopsy specimens. The results of this study suggest that AMACR may be a useful addition to current diagnostic tools for detecting prostate cancer, although these findings require further evaluation in larger studies. We did note that the precancerous lesion, high-grade PIN, demonstrated AMACR protein expression, preventing us from being able to use AMACR alone in diagnostically challenging prostate needle biopsy specimens. However, in combination with basal cell–specific markers, such as 34βE12 or p63, we suspect that few cases will be diagnosed as "atypical without a definitive diagnosis." This positive marker also may be helpful for general surgical pathologists, because the absence of a basal staining may be due to lack of basal cells or failure of the antibody to work in the area critical for diagnosis.

In this study, we used high-throughput molecular and tissue technologies to identify AMACR as a biomarker for prostate cancer. Further research regarding AMACR overexpression in prostate cancer may lead to improved diagnostic and therapeutic modalities for this common disease.

Abate-Shen C, Shen MM. Molecular genetics of prostate cancer.  Genes Dev.2000;14:2410-2434.
Ruijter E, van de Kaa C, Miller G, Ruiter D, Debruyne F, Schalken J. Molecular genetics and epidemiology of prostate carcinoma.  Endocr Rev.1999;20:22-45.
Catalona WJ, Richie JP, Ahmann FR.  et al.  Comparison of digital rectal examination and serum prostate specific antigen in the early detection of prostate cancer: results of a multicenter clinical trial of 6,630 men.  J Urol.1994;151:1283-1290.
Etzioni R, Legler JM, Feuer EJ, Merrill RM, Cronin KA, Hankey BF. Cancer surveillance series: interpreting trends in prostate cancer, part III: quantifying the link between population prostate-specific antigen testing and recent declines in prostate cancer mortality.  J Natl Cancer Inst.1999;91:1033-1039.
Maattanen L, Auvinen A, Stenman UH.  et al.  European randomized study of prostate cancer screening: first-year results of the Finnish trial.  Br J Cancer.1999;79:1210-1214.
Schroder FH, van der Maas P, Beemsterboer P.  et al.  Evaluation of the digital rectal examination as a screening test for prostate cancer: Rotterdam section of the European Randomized Study of Screening for Prostate Cancer.  J Natl Cancer Inst.1998;90:1817-1823.
Jacobsen SJ, Katusic SK, Bergstralh EJ.  et al.  Incidence of prostate cancer diagnosis in the eras before and after serum prostate-specific antigen testing.  JAMA.1995;274:1445-1449.
Epstein JI, Potter SR. The pathological interpretation and significance of prostate needle biopsy findings: implications and current controversies.  J Urol.2001;166:402-410.
Liotta L, Petricoin E. Molecular profiling of human cancer.  Nat Rev Genet.2000;1:48-56.
Golub TR, Slonim DK, Tamayo P.  et al.  Molecular classification of cancer: class discovery and class prediction by gene expression monitoring.  Science.1999;286:531-537.
Perou CM, Sorlie T, Eisen MB.  et al.  Molecular portraits of human breast tumours.  Nature.2000;406:747-752.
Bittner M, Meltzer P, Chen Y.  et al.  Molecular classification of cutaneous malignant melanoma by gene expression profiling.  Nature.2000;406:536-540.
Alizadeh AA, Eisen MB, Davis RE.  et al.  Distinct types of diffuse large B-cell lymphoma identified by gene expression profiling.  Nature.2000;403:503-511.
Sreekumar A, Nyati MK, Varambally S.  et al.  Profiling of cancer cells using protein microarrays: discovery of novel radiation-regulated proteins.  Cancer Res.2001;61:7585-7593.
Dhanasekaran SM, Barrette TR, Ghosh D.  et al.  Delineation of prognostic biomarkers in prostate cancer.  Nature.2001;412:822-826.
Luo J, Duggan DJ, Chen Y.  et al.  Human prostate cancer and benign prostatic hyperplasia: molecular dissection by gene expression profiling.  Cancer Res.2001;61:4683-4688.
Magee JA, Araki T, Patil S.  et al.  Expression profiling reveals hepsin overexpression in prostate cancer.  Cancer Res.2001;61:5692-5696.
Welsh JB, Sapinoso LM, Su AI.  et al.  Analysis of gene expression identifies candidate markers and pharmacological targets in prostate cancer.  Cancer Res.2001;61:5974-5978.
Ferdinandusse S, Denis S, Li J, Dacremont G, Waterham HR, Wanders RJ. Subcellular localization and physiological role of alpha-methylacyl-CoA racemase.  J Lipid Res.2000;41:1890-1896.
Kotti TJ, Savolainen K, Helander HM.  et al.  In mouse alpha-methylacyl-CoA racemase, the same gene product is simultaneously located in mitochondria and peroxisomes.  J Biol Chem.2000;275:20887-20895.
Ferdinandusse S, Denis S, Clayton PT.  et al.  Mutations in the gene encoding peroxisomal alpha-methylacyl-CoA racemase cause adult-onset sensory motor neuropathy.  Nat Genet.2000;24:188-191.
Eisen MB, Spellman PT, Brown PO, Botstein D. Cluster analysis and display of genome-wide expression patterns.  Proc Natl Acad Sci U S A.1998;95:14863-14868.
Hedges L, Olkin IV. Statistical Methods for Meta-AnalysisNew York, NY: Academic Press; 1985.
Manley S, Mucci NR, De Marzo AM, Rubin MA. Relational database structure to manage high-density tissue microarray data and images for pathology studies focusing on clinical outcome: the prostate specialized program of research excellence model.  Am J Pathol.2001;159:837-843.
Hollenbeck BK, Bassily N, Wei JT.  et al.  Whole mounted radical prostatectomy specimens do not increase detection of adverse pathological features.  J Urol.2000;164:1583-1586.
Rubin MA, Putzi M, Mucci N.  et al.  Rapid ("warm") autopsy study for procurement of metastatic prostate cancer.  Clin Cancer Res.2000;6:1038-1045.
Bostwick DG, Foster CS. Predictive factors in prostate cancer: current concepts from the 1999 College of American Pathologists Conference on Solid Tumor Prognostic Factors and the 1999 World Health Organization Second International Consultation on Prostate Cancer.  Semin Urol Oncol.1999;17:222-272.
Gleason DF. Classification of prostatic carcinomas.  Cancer Chemother Rep.1966;50:125-128.
Gleason D and the Veterans Administration Cooperative Urological Research Group.  Histologic grading and clinical staging of prostate carcinoma. In: Tannenbaum M, ed. Urologic Pathology: The Prostate. Philadelphia, Pa: Lea & Febiger; 1977:171-198.
Kononen J, Bubendorf L, Kallioniemi A.  et al.  Tissue microarrays for high-throughput molecular profiling of tumor specimens.  Nat Med.1998;4:844-847.
Perrone EE, Theoharis C, Mucci NR.  et al.  Tissue microarray assessment of prostate cancer tumor proliferation in African-American and white men.  J Natl Cancer Inst.2000;92:937-939.
Scheffe H. The Analysis of VarianceNew York, NY: John Wiley & Sons; 1959.
Putzi MJ, De Marzo AM. Morphologic transitions between proliferative inflammatory atrophy and high-grade prostatic intraepithelial neoplasia.  Urology.2000;56:828-832.
Shah R, Mucci NR, Amin A, Macoska JA, Rubin MA. Postatrophic hyperplasia of the prostate gland: neoplastic precursor or innocent bystander?  Am J Pathol.2001;158:1767-1773.
Ferdinandusse S, Overmars H, Denis S, Waterham HR, Wanders RJ, Vreken P. Plasma analysis of di- and trihydroxycholestanoic acid diastereoisomers in peroxisomal alpha-methylacyl-CoA racemase deficiency.  J Lipid Res.2001;42:137-141.
Gleason DF. Histologic grading of prostate cancer: a perspective.  Hum Pathol.1992;23:273-279.
O'Malley FP, Grignon DJ, Shum DT. Usefulness of immunoperoxidase staining with high-molecular-weight cytokeratin in the differential diagnosis of small-acinar lesions of the prostate gland.  Virchows Arch A Pathol Anat Histopathol.1990;417:191-196.
Wojno KJ, Epstein JI. The utility of basal cell-specific anti-cytokeratin antibody (34 beta E12) in the diagnosis of prostate cancer: a review of 228 cases.  Am J Surg Pathol.1995;19:251-260.
Googe PB, McGinley KM, Fitzgibbon JF. Anticytokeratin antibody 34 beta E12 staining in prostate carcinoma.  Am J Clin Pathol.1997;107:219-223.
Parsons JK, Gage WR, Nelson WG, De Marzo AM. p63 Protein expression is rare in prostate adenocarcinoma: implications for cancer diagnosis and carcinogenesis.  Urology.2001;58:619-624.
Signoretti S, Waltregny D, Dilks J.  et al.  p63 Is a prostate basal cell marker and is required for prostate development.  Am J Pathol.2000;157:1769-1775.

Figures

Figure 1. Schematic of DNA and Tissue Microarray Approach
Graphic Jump Location
Figure 2. DNA Microarray Analysis and Up-regulation of AMACR in Prostate Cancer
Graphic Jump Location
α-Methylacyl coenzyme A racemase (AMACR) transcripts as determined by DNA microarray analysis from 57 prostate samples15 were grouped according to sample type and averaged. The experimental sample was labeled with Cy5 fluorescent dye, whereas the reference sample (pool of benign prostate tissue) was labeled with Cy3 fluorescent dye. The box plot demonstrates the range of AMACR expression within each group. The middle horizontal bars indicate median values; the upper and lower limits of the boxes, interquartile ranges; and the error bars, 95% confidence intervals.
Figure 3.AMACR Transcript and Protein Levels in Prostate Cancer
Graphic Jump Location
A, Reverse transcriptase polymerase chain reaction (RT-PCR) was used to detect α-methylacyl coenzyme A racemase (AMACR) transcript levels in RNA preparations from prostate tissue extracts. Glyceraldehyde-3-phosphate dehydrogenase (GAPDH) served as the internal control. B, Immunoblot analysis of AMACR in prostate tissue extracts. β-Tubulin serves as control for sample loading. Pool indicates RNA from normal prostate tissues obtained from a commercial source; BPH, benign prostatic hyperplasia; NAP, normal adjacent prostate tissue from a patient who has prostate cancer; and 3 + 3, 3 + 4, 4 + 4, the major and minor Gleason patterns of the clinically localized prostate cancer examined. Various prostate cell lines were also examined. RT-PCR without enzyme (−RT) served as a negative control.
Figure 4. Characterization of AMACR Protein Expression Using Prostate Cancer Tissue Microarrays
Graphic Jump Location
α-Methylacyl coenzyme A racemase (AMACR) protein expression by standard biotin-avidin immunohistochemical analysis using a polyclonal mouse antibody to AMACR was evaluated on a wide range of prostate tissues using high-density tissue microarrays. Brown chromogen indicates positive staining. Near uniform moderate-to-strong AMACR protein expression (score = 3 and 4, respectively) was observed in prostate cancer samples from men with clinically localized prostate cancer (A, B). Adjacent areas of benign prostate tissue (A, B, arrowheads) did not express AMACR, making AMACR a highly specific prostate cancer marker. Strong staining was also observed in high-grade (Gleason score, 4 + 4 = 8) tumors (C) but was significantly weaker in hormone-refractory metastatic prostate cancer samples (D). (Counterstain, hematoxylin; original magnifications ×200).
Figure 5. Mean AMACR Protein Staining Intensity
Graphic Jump Location
AMACR indicates α-methylacyl coenzyme A racemase; PAH, prostatic atrophic hyperplasia; PIN, prostatic intraepithelial neoplasia; and error bars, 95% confidence intervals.
Figure 6. AMACR Utility in Diagnosing Prostate Cancer on Needle Biopsy Specimens
Graphic Jump Location
In prostate needle biopsy specimens with a small amount of prostate cancer (A, B), a basal cell–specific marker, such as p63 (C) or 34βE12 (not shown), can be used to identify benign prostatic glands (brown chromogen). C, Absence of staining confirms that the small atypical area is prostate cancer. D, Using α-methylacyl coenzyme A racemase (AMACR) immunohistochemical analysis, however, positive staining (brown chromogen) is present in prostate cancer but not in the benign glands (compare with C). (A and B, hematoxylin-eosin; C, immunohistochemical stain using monoclonal antibody for p63 and hematoxylin counterstain; D, standard biotin-avidin complex immunohistochemistry using a polyclonal mouse antibody to AMACR and hematoxylin counterstain. Original magnifications: A, ×100; B, ×400; C, ×200; and D, ×200).

Tables

Table Graphic Jump LocationTable. Statistical Analysis of α-Methylacyl Coenzyme A Racemase (AMACR) Expression in Independent Prostate Cancer Gene Expression Data Sets

References

Abate-Shen C, Shen MM. Molecular genetics of prostate cancer.  Genes Dev.2000;14:2410-2434.
Ruijter E, van de Kaa C, Miller G, Ruiter D, Debruyne F, Schalken J. Molecular genetics and epidemiology of prostate carcinoma.  Endocr Rev.1999;20:22-45.
Catalona WJ, Richie JP, Ahmann FR.  et al.  Comparison of digital rectal examination and serum prostate specific antigen in the early detection of prostate cancer: results of a multicenter clinical trial of 6,630 men.  J Urol.1994;151:1283-1290.
Etzioni R, Legler JM, Feuer EJ, Merrill RM, Cronin KA, Hankey BF. Cancer surveillance series: interpreting trends in prostate cancer, part III: quantifying the link between population prostate-specific antigen testing and recent declines in prostate cancer mortality.  J Natl Cancer Inst.1999;91:1033-1039.
Maattanen L, Auvinen A, Stenman UH.  et al.  European randomized study of prostate cancer screening: first-year results of the Finnish trial.  Br J Cancer.1999;79:1210-1214.
Schroder FH, van der Maas P, Beemsterboer P.  et al.  Evaluation of the digital rectal examination as a screening test for prostate cancer: Rotterdam section of the European Randomized Study of Screening for Prostate Cancer.  J Natl Cancer Inst.1998;90:1817-1823.
Jacobsen SJ, Katusic SK, Bergstralh EJ.  et al.  Incidence of prostate cancer diagnosis in the eras before and after serum prostate-specific antigen testing.  JAMA.1995;274:1445-1449.
Epstein JI, Potter SR. The pathological interpretation and significance of prostate needle biopsy findings: implications and current controversies.  J Urol.2001;166:402-410.
Liotta L, Petricoin E. Molecular profiling of human cancer.  Nat Rev Genet.2000;1:48-56.
Golub TR, Slonim DK, Tamayo P.  et al.  Molecular classification of cancer: class discovery and class prediction by gene expression monitoring.  Science.1999;286:531-537.
Perou CM, Sorlie T, Eisen MB.  et al.  Molecular portraits of human breast tumours.  Nature.2000;406:747-752.
Bittner M, Meltzer P, Chen Y.  et al.  Molecular classification of cutaneous malignant melanoma by gene expression profiling.  Nature.2000;406:536-540.
Alizadeh AA, Eisen MB, Davis RE.  et al.  Distinct types of diffuse large B-cell lymphoma identified by gene expression profiling.  Nature.2000;403:503-511.
Sreekumar A, Nyati MK, Varambally S.  et al.  Profiling of cancer cells using protein microarrays: discovery of novel radiation-regulated proteins.  Cancer Res.2001;61:7585-7593.
Dhanasekaran SM, Barrette TR, Ghosh D.  et al.  Delineation of prognostic biomarkers in prostate cancer.  Nature.2001;412:822-826.
Luo J, Duggan DJ, Chen Y.  et al.  Human prostate cancer and benign prostatic hyperplasia: molecular dissection by gene expression profiling.  Cancer Res.2001;61:4683-4688.
Magee JA, Araki T, Patil S.  et al.  Expression profiling reveals hepsin overexpression in prostate cancer.  Cancer Res.2001;61:5692-5696.
Welsh JB, Sapinoso LM, Su AI.  et al.  Analysis of gene expression identifies candidate markers and pharmacological targets in prostate cancer.  Cancer Res.2001;61:5974-5978.
Ferdinandusse S, Denis S, Li J, Dacremont G, Waterham HR, Wanders RJ. Subcellular localization and physiological role of alpha-methylacyl-CoA racemase.  J Lipid Res.2000;41:1890-1896.
Kotti TJ, Savolainen K, Helander HM.  et al.  In mouse alpha-methylacyl-CoA racemase, the same gene product is simultaneously located in mitochondria and peroxisomes.  J Biol Chem.2000;275:20887-20895.
Ferdinandusse S, Denis S, Clayton PT.  et al.  Mutations in the gene encoding peroxisomal alpha-methylacyl-CoA racemase cause adult-onset sensory motor neuropathy.  Nat Genet.2000;24:188-191.
Eisen MB, Spellman PT, Brown PO, Botstein D. Cluster analysis and display of genome-wide expression patterns.  Proc Natl Acad Sci U S A.1998;95:14863-14868.
Hedges L, Olkin IV. Statistical Methods for Meta-AnalysisNew York, NY: Academic Press; 1985.
Manley S, Mucci NR, De Marzo AM, Rubin MA. Relational database structure to manage high-density tissue microarray data and images for pathology studies focusing on clinical outcome: the prostate specialized program of research excellence model.  Am J Pathol.2001;159:837-843.
Hollenbeck BK, Bassily N, Wei JT.  et al.  Whole mounted radical prostatectomy specimens do not increase detection of adverse pathological features.  J Urol.2000;164:1583-1586.
Rubin MA, Putzi M, Mucci N.  et al.  Rapid ("warm") autopsy study for procurement of metastatic prostate cancer.  Clin Cancer Res.2000;6:1038-1045.
Bostwick DG, Foster CS. Predictive factors in prostate cancer: current concepts from the 1999 College of American Pathologists Conference on Solid Tumor Prognostic Factors and the 1999 World Health Organization Second International Consultation on Prostate Cancer.  Semin Urol Oncol.1999;17:222-272.
Gleason DF. Classification of prostatic carcinomas.  Cancer Chemother Rep.1966;50:125-128.
Gleason D and the Veterans Administration Cooperative Urological Research Group.  Histologic grading and clinical staging of prostate carcinoma. In: Tannenbaum M, ed. Urologic Pathology: The Prostate. Philadelphia, Pa: Lea & Febiger; 1977:171-198.
Kononen J, Bubendorf L, Kallioniemi A.  et al.  Tissue microarrays for high-throughput molecular profiling of tumor specimens.  Nat Med.1998;4:844-847.
Perrone EE, Theoharis C, Mucci NR.  et al.  Tissue microarray assessment of prostate cancer tumor proliferation in African-American and white men.  J Natl Cancer Inst.2000;92:937-939.
Scheffe H. The Analysis of VarianceNew York, NY: John Wiley & Sons; 1959.
Putzi MJ, De Marzo AM. Morphologic transitions between proliferative inflammatory atrophy and high-grade prostatic intraepithelial neoplasia.  Urology.2000;56:828-832.
Shah R, Mucci NR, Amin A, Macoska JA, Rubin MA. Postatrophic hyperplasia of the prostate gland: neoplastic precursor or innocent bystander?  Am J Pathol.2001;158:1767-1773.
Ferdinandusse S, Overmars H, Denis S, Waterham HR, Wanders RJ, Vreken P. Plasma analysis of di- and trihydroxycholestanoic acid diastereoisomers in peroxisomal alpha-methylacyl-CoA racemase deficiency.  J Lipid Res.2001;42:137-141.
Gleason DF. Histologic grading of prostate cancer: a perspective.  Hum Pathol.1992;23:273-279.
O'Malley FP, Grignon DJ, Shum DT. Usefulness of immunoperoxidase staining with high-molecular-weight cytokeratin in the differential diagnosis of small-acinar lesions of the prostate gland.  Virchows Arch A Pathol Anat Histopathol.1990;417:191-196.
Wojno KJ, Epstein JI. The utility of basal cell-specific anti-cytokeratin antibody (34 beta E12) in the diagnosis of prostate cancer: a review of 228 cases.  Am J Surg Pathol.1995;19:251-260.
Googe PB, McGinley KM, Fitzgibbon JF. Anticytokeratin antibody 34 beta E12 staining in prostate carcinoma.  Am J Clin Pathol.1997;107:219-223.
Parsons JK, Gage WR, Nelson WG, De Marzo AM. p63 Protein expression is rare in prostate adenocarcinoma: implications for cancer diagnosis and carcinogenesis.  Urology.2001;58:619-624.
Signoretti S, Waltregny D, Dilks J.  et al.  p63 Is a prostate basal cell marker and is required for prostate development.  Am J Pathol.2000;157:1769-1775.

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