α-Methylacyl-CoA racemase (AMACR) is an enzyme involved in the metabolism of fatty acids and is an important tissue biomarker in the prostate to distinguish normal glands from prostate cancer. Here, for the first time, we evaluated the expression of AMACR protein in normal breast, ductal carcinoma in situ, and invasive carcinomas. By immunofluorescence and immunohistochemistry, AMACR was seen in cytoplasmic granules consistent with a mitochondrial and peroxisomal localization. AMACR expression was determined by immunohistochemistry on 160 invasive carcinomas with long follow-up, using a high-density tissue microarray, and evaluated by two methods: standard pathology review and quantitative image analysis. AMACR was overexpressed in 42 of 160 (26%) invasive carcinomas, and it was associated with a decrease in tumor differentiation, a feature of aggressive breast cancer. Quantitative analysis allowed for better discrimination and more accurate evaluation of low-intensity staining. In conclusion, AMACR protein is expressed in normal breast and its expression seems to increase in invasive carcinomas. We observed stronger AMACR protein expression in high-grade carcinomas when compared with low-grade ones. Quantitative image analysis is a novel way to accurately and reproducibly evaluate immunohistochemistry in breast tissue samples using high-density tissue microarrays.

Epidemiologic studies show that red meat and diary products, which are both sources of branched chain fatty acids, are associated with breast cancer risk. Case control studies from geographically disparate areas have found a significant positive association between the intake of meat, red meat, and high-fat meat and the risk of developing breast cancer (1-3). Breast cancer incidence is associated with per capita fat consumption and, interestingly, these rates change among migrating populations and provide additional evidence implicating a high-fat diet in cancer development (4).

α-Methylacyl-CoA racemase (AMACR) is a mitochondrial and peroxisomal enzyme that plays an important role in bile acid biosynthesis and β-oxidation of branched-chain fatty acids (5). Elevated levels of branched-chain fatty acids in the diet may contribute to induction and an increase in AMACR activity. AMACR levels increase in response to branched-chain fatty acids in dairy and beef products. However, the link of AMACR expression and neoplasia has only recently been made. Using high-throughput molecular and tissue technologies, it has been shown that AMACR is an important biological marker for prostate cancer, being overexpressed at the transcript and protein levels (6). AMACR is used in surgical pathology practice as a marker to distinguish benign prostatic glands form prostate cancer (7-12). In contrast with prostate cancer, very little is known about AMACR expression in normal breast and in breast cancer.

At this time, pathologist-based analysis is the current standard for the evaluation of immunohistochemistry; however, because of its semiquantitative nature, it is at times difficult to reproduce by different observers. For example, the interpretation of HER-2/neu by immunohistochemistry using the Hecept test varies among pathologists, raising doubts about the reproducibility of the results. Image analysis offers more reproducible results of target signal expression with a continuous, rather than nominal scale (13-22). Quantitative image analysis has not been fully evaluated in the assessment to tissue biomakers, especially when using high-density tissue microarrays.

The goals of our study were two-fold. First, we set out to characterize for the first time the expression of AMACR in normal breast, invasive carcinoma and its precursor lesion, ductal carcinoma in situ using tissue microarrays. The second aim of our work was to determine AMACR protein expression throughout a continuous range in a wide variety of breast samples and compare it to the pathologist-based, semiquantitative evaluation.

Case Selection and Tissue Microarray Construction

Breast tissues for tissue microarray construction were obtained from the surgical pathology files at the University of Michigan with Institutional Review Board approval. Two tissue microarrays were constructed. The first tissue microarray contained a wide spectrum of breast tissues, including normal breast and fibrocystic changes (15 cases), ductal carcinoma in situ (4 cases), invasive carcinomas (14 cases), and distant breast cancer metastases (10 cases). The second tissue microarray contained tissues derived from 160 consecutive patients with invasive carcinomas of the breast, with follow-up information treated at the University of Michigan from 1987 to 1991. Clinical and pathologic variables were determined following well-established criteria. All invasive carcinomas were graded according to the method described by Elston and Ellis (23); angiolymphatic invasion was classified as either present or absent. The tissue microarrays were constructed as previously described using a tissue arrayer (Beecher Instruments, Silver Spring, MD). Three tissue cores (0.6 mm diameter) were sampled from each block to account for tumor and tissue heterogeneity and transferred to the recipient block. Clinical and treatment information was extracted by chart review, done by the surgeon (M.S. Sabel) with Institutional Review Board approval.

Immunofluorescence for AMACR in Tissue Sections

A section of the tissue microarray containing normal breast, fibrocystic changes, ductal carcinoma in situ, invasive carcinomas, and breast cancer metastases was used for immunofluorescence analysis of AMACR. In addition, we also used five whole sections of normal breast derived from mammoplasty procedures and of breast cancer. The slides were soaked in xylene for 15 minutes to remove paraffin and then hydrated with graded ethanol. Pretreatment included placing the slide in a citrate buffer (pH 6.0) and heating in pressure cooker for 15 minutes. After blocking the slide in PBS containing 5% normal donkey serum and 0.1% Tween 20, the rabbit antibody against AMACR at 1:2,000 (kind gift of Prof. Ronald Wanders, Department of Clinical Chemistry, University of Amsterdam, the Netherlands), and mouse monoclonal E-cadherin (BD Biosciences, San Jose, CA) at 1:400 were applied (in PBST with 5% donkey serum) and incubated overnight at 4°C. After washing the slides, secondary donkey anti-rabbit Alexa 488 and donkey anti-mouse Alexa 555 (Molecular Probes, Eugene, OR) mixture was applied at 1:500 dilution and incubated in the dark for 1 hour. After washing the slides, anti-fade with 4′,6-diamidino-2-phenylindole was applied (Vectashield) and covered with a glass coverslip. Regular fluorescence images were taken using Zeiss Axioplan 2 microscope and confocal images were taken using Ziess LSM 510 META confocal microscope.

Immunohistochemistry for AMACR

To test the expression of AMACR in relation to clinical and pathologic features of breast cancers, a 4-μm-thick paraffin-embedded tissue section of the tissue microarray was immunostained using a primary rabbit monoclonal antibody (p504S, dilution 1:25, Zeta Corporation, Sierra Madre, CA). Subsequently, slides were incubated sequentially with biotinylated secondary antibody, avidin-biotin complex, and chromogenic substrate 3,3′-diaminobenzidine. Slides were evaluated for adequacy using a standard bright field microscope. The majority of array spots contained tissue sufficient for the evaluation. Digital images were then acquired using the BLISS Imaging System (Bacus Lab, Lombard, IL). The tissue microarray was immunostained for estrogen and progesterone receptors and for HER-2/neu by using well-described and validated procedures (24, 25). For estrogen receptor staining, we used estrogen receptor antibody clone 6F11 (prediluted, Ventana Medical Systems, Tucson, AZ) and for progesterone receptor antibody 636 (DAKO, 1:400 dilution). HER2/neu immunostaining was done using CB11 antibody (1:40 dilution, NovoCastra, Burlingame, CA). Hormone receptor status was reported as positive or negative when >10% of the neoplastic cells exhibited nuclear staining (26). HER-2/neu status was reported as 0 to 3+ (27).

Pathologist Scoring of AMACR Protein Expression

AMACR protein expression was scored using a standard, pathologist-based 4-tiered scoring system previously validated as negative (score = 1), weak (score = 2) when there was faint cytoplasmic staining or granular apical staining, moderate (score = 3) when there was diffuse granular cytoplasmic stain, and strong (score = 4) when there was diffuse intense cytoplasmic stain (6). Moderate and strong staining was considered as positive staining based on prior work. Because of tissue heterogeneity, the pathologist assigned a score only to the invasive carcinoma in each tissue microarray core. This ensured that only invasive carcinomas were scored, and not the surrounding benign glands or stroma.

Quantitative Image Analysis of AMACR Protein Expression

The same tissue section, previously analyzed qualitatively and semiquantitatively by the pathologist, was scanned, and the tissue images were converted to digital files using the ACIS (ChromaVision Medical Systems, Inc., San Juan Capistrano, CA). This system consists of an automated robotic bright-field microscope module that is linked to a computer through a Microsoft Windows NT-based software interface. Proprietary software is used to detect the brown stain intensity of the chromogen used for the immunohistochemical analysis and compares this value to blue counterstain used as background. The ACIS II system is highly sensitive and can analyze stain intensity levels in a precise manner (range of 0-255 units). This system has been used previously to analyze immunohistochemistry on whole tissue sections and on tissue microarrays (13-22). We have tested the reproducibility of the ACIS II in pilot experiments before this study by scoring several tissue microarrays on separate occasions. The correlation coefficient for these experiments was r2 = 0.973. For the current study, the desired areas of each core were characterized for precise intensity scoring. Taking into account tissue heterogeneity, we encircled the area of invasive carcinoma under the guidance of a pathologist with special interest and experience in breast pathology using the ACIS II software. Thus, only invasive carcinomas were assigned an intensity measurement; the surrounding benign glands or stroma were not scored. AMACR staining intensity was evaluated using ChromaVision on a scale of 0 to 255. The score assigned to each tissue microarray sample was automatically transferred by the ACIS II software to an excel spreadsheet. The biostatistician in the study (R. Shen) then analyzed the mean, minimum, and median of those values for each tumor. Investigators were blinded to all clinical outcome data.

Statistical Analysis

The association between AMACR protein expression and the clinical and pathologic characteristics was assessed using the general estimating equation. The ordinal expression categories for AMACR were modeled using the multinomial distribution with the cumulative logit link. Tissue microarray elements were grouped by specimen (patient). The model calculates the odds of a higher expression score versus a lower score, with the odds ratio and 95% confidence intervals reported. To identify an optimal dichotomization of AMACR intensity that best differentiates survival outcome, sensitivity analysis on various cut points of the normalized intensity was applied. In particular, a series of equal-spaced threshold points ranging from the lower quartile to the upper quartile of the normalized intensity was used to dichotomize AMACR into low- and high-expressing categories. Using death or disease recurrence as patient outcome parameter, Kaplan-Meier estimates of the survival probabilities were computed and P values from log-rank tests were obtained to assess the discriminative power of the dichotomized marker. The optimal threshold point of dichotomization was then chosen to minimize the log-rank test P values.

AMACR Expression in Normal Epithelial Cells and in Breast Cancer

By immunofluorescence, AMACR was found in the cytoplasm of normal and cancerous epithelial cells, including ductal carcinoma in situ and invasive carcinoma, in a granular pattern consistent with a mitochondrial and peroxisomal localization. As shown in Fig. 1, AMACR is present in the cytoplasm of normal ductal and myoepithelial cells and not in the stromal fibroblasts. AMACR is expressed in ductal carcinoma in situ and in invasive carcinomas.

Figure 1.

Immunofluorescence detects AMACR protein expression in the cytoplasm of normal epithelial cells (A and E), ductal carcinoma in situ (B and F), and invasive breast carcinoma (C and G). (D) and (H) are from a prostate carcinoma overexpressing AMACR, which is used as positive control, and from normal prostatic glands (arrow), which serve as negative control. AMACR protein is visualized in green; E-cadherin staining (red) highlights the cytoplasmic membranes; and nuclei are stained with blue (4′,6-diamidino-2-phenylindole). Confocal images were taken using Ziess LSM 510 META confocal microscope.

Figure 1.

Immunofluorescence detects AMACR protein expression in the cytoplasm of normal epithelial cells (A and E), ductal carcinoma in situ (B and F), and invasive breast carcinoma (C and G). (D) and (H) are from a prostate carcinoma overexpressing AMACR, which is used as positive control, and from normal prostatic glands (arrow), which serve as negative control. AMACR protein is visualized in green; E-cadherin staining (red) highlights the cytoplasmic membranes; and nuclei are stained with blue (4′,6-diamidino-2-phenylindole). Confocal images were taken using Ziess LSM 510 META confocal microscope.

Close modal

Using high-density tissue microarrays, we next evaluated the expression of AMACR protein in 160 consecutive invasive breast carcinomas with long follow-up information by immunohistochemistry (Fig. 2). Table 1 shows the clinicopathologic characteristics of the patients. Of the 160 invasive carcinomas, 149 had available cores for evaluation. The association between AMACR protein levels and clinical and pathologic characteristics is shown in Table 2. Using both categorical pathologist evaluation and quantitative image analysis, increased expression of AMACR was associated with higher histologic grade, a well-known feature of aggressive breast cancer (ANOVA, P = 0.04; Table 2). AMACR expression increased with the grade of the invasive carcinoma. Pathologist-based evaluation of the immunohistochemical staining showed mean AMACR protein staining intensity of 1.75 (SE = 0.31) for grade 1, 2.24 (SE = 0.12) for grade 2, and 2.65 (SE = 0.13) for grade 3 tumors (ANOVA, P = 0.01). In agreement, image analyzer–assisted immunohistochemical quantitation revealed a mean staining intensity of 144.1 (SE = 9.6) for grade 1, 149.4 (SE = 16) for grade 2, and 154.1 (SE = 14.8) for grade 3 invasive carcinomas (ANOVA, P = 0.04), suggesting a relationship between levels of AMACR protein and tumor differentiation.

Figure 2.

Immunohistochemistry and evaluation of AMACR on tissue microarrays. A. Digital image of scanned tissue microarray on a computer screen of the image analysis system. The diagnostic areas were selected on each core for precise intensity scoring. B. An example of a “hot spot” for AMACR expression as determined by quantitative image analysis. C. Tissue cores of low– and high–histologic grade adenocarcinomas with low-, moderate-, and high-intensity staining for AMACR. The mean intensity of staining is shown below the corresponding images.

Figure 2.

Immunohistochemistry and evaluation of AMACR on tissue microarrays. A. Digital image of scanned tissue microarray on a computer screen of the image analysis system. The diagnostic areas were selected on each core for precise intensity scoring. B. An example of a “hot spot” for AMACR expression as determined by quantitative image analysis. C. Tissue cores of low– and high–histologic grade adenocarcinomas with low-, moderate-, and high-intensity staining for AMACR. The mean intensity of staining is shown below the corresponding images.

Close modal
Table 1.

Clinical and pathologic characteristics of the 160 patients with breast cancer

Median age, y (range) 58 (28-89) 
Follow-up/y, median (range) 8.2 y (5 mo-14 y) 
Pathologic stage, n (%)  
    I 47 of 121 (38.8%) 
    II 47 of 121 (38.8%) 
    III 25 of 121 (20.7%) 
    IV 2 of 121 (1.7%) 
Tumor size, cm (range) 2.4 (0.3-6.7) 
Lymph node status, n (%)  
    Negative 55 of 132 (41.7%) 
    Positive 77 of 132 (58.3%) 
Estrogen receptor status  
    Negative, n (%) 50 of 146 (34.2%) 
    Positive, n (%) 96 of 146 (65.8%) 
Progesterone receptor status  
    Negative, n (%) 69 of 149 (46.3%) 
    Positive, n (%) 80 of 149 (53.7%) 
HER-2/neu status  
    Negative, n (%) 128 of 148 (86.5%) 
    Positive, n (%) 20 of 148 (13.5%) 
Median age, y (range) 58 (28-89) 
Follow-up/y, median (range) 8.2 y (5 mo-14 y) 
Pathologic stage, n (%)  
    I 47 of 121 (38.8%) 
    II 47 of 121 (38.8%) 
    III 25 of 121 (20.7%) 
    IV 2 of 121 (1.7%) 
Tumor size, cm (range) 2.4 (0.3-6.7) 
Lymph node status, n (%)  
    Negative 55 of 132 (41.7%) 
    Positive 77 of 132 (58.3%) 
Estrogen receptor status  
    Negative, n (%) 50 of 146 (34.2%) 
    Positive, n (%) 96 of 146 (65.8%) 
Progesterone receptor status  
    Negative, n (%) 69 of 149 (46.3%) 
    Positive, n (%) 80 of 149 (53.7%) 
HER-2/neu status  
    Negative, n (%) 128 of 148 (86.5%) 
    Positive, n (%) 20 of 148 (13.5%) 
Table 2.

Association between AMACR protein expression and clinical and pathologic characteristics

Parametern (%)Mean AMACR intensityP
Tumor size (cm)    
    ≤2 71 (56.8) 149.8 ± 15.6 0.17 
    >2 54 (43.2) 153.5 ± 15.0  
Lymph node status    
    Negative 50 (39.4) 151.7 ± 15.2 0.85 
    Positive 77 (60.6) 152.2 ± 14.2  
Histologic grade    
    1 12 (8.6) 144.1 ± 9.6 0.04 
    2 62 (44.6) 149.4 ± 16.0  
    3 65 (46.8) 154.1 ± 14.8  
Angiolymphatic invasion    
    Absent 92 (64.3) 150.3 ± 14.8 0.23 
    Present 51 (35.7) 153.5 ± 15.5  
Estrogen receptor    
    Negative 50 (34.2) 152.1 ± 15.9 0.59 
    Positive 96 (65.8) 150.7 ± 14.8  
Progesterone receptor    
    Negative 69 (46.3) 152.8 ± 15.7 0.26 
    Positive 80 (53.7) 149.9 ± 14.5  
HER-2/neu    
    0 99 (70.7) 149.4 ± 14.4 0.05 
    1 21 (15.0) 151.2 ± 11.7  
    2 2 (1.4) 156.3 ± 9.5  
    3 18 (12.9) 159.8 ± 18.7  
Parametern (%)Mean AMACR intensityP
Tumor size (cm)    
    ≤2 71 (56.8) 149.8 ± 15.6 0.17 
    >2 54 (43.2) 153.5 ± 15.0  
Lymph node status    
    Negative 50 (39.4) 151.7 ± 15.2 0.85 
    Positive 77 (60.6) 152.2 ± 14.2  
Histologic grade    
    1 12 (8.6) 144.1 ± 9.6 0.04 
    2 62 (44.6) 149.4 ± 16.0  
    3 65 (46.8) 154.1 ± 14.8  
Angiolymphatic invasion    
    Absent 92 (64.3) 150.3 ± 14.8 0.23 
    Present 51 (35.7) 153.5 ± 15.5  
Estrogen receptor    
    Negative 50 (34.2) 152.1 ± 15.9 0.59 
    Positive 96 (65.8) 150.7 ± 14.8  
Progesterone receptor    
    Negative 69 (46.3) 152.8 ± 15.7 0.26 
    Positive 80 (53.7) 149.9 ± 14.5  
HER-2/neu    
    0 99 (70.7) 149.4 ± 14.4 0.05 
    1 21 (15.0) 151.2 ± 11.7  
    2 2 (1.4) 156.3 ± 9.5  
    3 18 (12.9) 159.8 ± 18.7  

Comparison of AMACR Expression Using Standard Pathology Review versus Quantitative Image Analysis

Pathologist-based and image analyses had a linear trend of association and overall good correlation (correlation coefficient 0.34, P < 0.0001). The pathologist could reliably distinguish between low and high intensity of AMACR expression (r2 = 0.47), but was less accurate in discerning differences at low intensity of staining (Fig. 3A). The quantitative analysis system, because it provides continuous rather than categorical data, allowed for wider range of staining detection and more accurate evaluation of low-intensity staining (Fig. 3A). Using the Kaplan-Meier estimates of the survival probabilities, image analysis was able to better discern between patients with better and worse disease-free survival when compared with pathologist-based analysis. Image analysis evaluation suggested a trend for tumors with high AMACR expression to have a worse clinical outcome, but did not reach statistical significance (Fig. 3B). To further evaluate whether AMACR expression levels add prognostic value over the already established significance of the histologic grade of the invasive carcinomas, we calculated the c-index (concordance index). We found that when adding AMACR levels determined by image analysis, the prediction accuracy of the model, reflected by the magnitude of the c-index, improved slightly (c = 0.13) over the univariate models (grade: c = 0.11, AMACR: c = 0.04).

Figure 3.

Evaluation of AMACR protein expression by pathologist and semiautomated quantitative evaluation (ChromaVision system). A. The histogram shows the distribution of the 4-tiered categorical pathology score (left) compared with the continuous and quantitative evaluation (center). Right, direct comparison of the pathologist review with the quantitative analysis of the same cases. The pathologist could reliably distinguish between low and high intensity of the AMACR expression (r2 = 0.47), but was less accurate in detecting differences at low intensity of staining. The quantitative analysis system allowed for wider range of staining detection and more accurate evaluation of low-intensity staining (error bars with 95% confidence interval). B. Kaplan Meier graphs of disease-free survival show that, by image analysis, there was a trend for AMACR-positive carcinomas to have a worse prognosis than AMACR-negative tumors, but the difference did not reach statistical significance.

Figure 3.

Evaluation of AMACR protein expression by pathologist and semiautomated quantitative evaluation (ChromaVision system). A. The histogram shows the distribution of the 4-tiered categorical pathology score (left) compared with the continuous and quantitative evaluation (center). Right, direct comparison of the pathologist review with the quantitative analysis of the same cases. The pathologist could reliably distinguish between low and high intensity of the AMACR expression (r2 = 0.47), but was less accurate in detecting differences at low intensity of staining. The quantitative analysis system allowed for wider range of staining detection and more accurate evaluation of low-intensity staining (error bars with 95% confidence interval). B. Kaplan Meier graphs of disease-free survival show that, by image analysis, there was a trend for AMACR-positive carcinomas to have a worse prognosis than AMACR-negative tumors, but the difference did not reach statistical significance.

Close modal

In the present study, we characterized the expression of AMACR in breast tissues, which was unknown. Although AMACR has been extensively studied in the context of prostate cancer, there is little data on its expression and significance in breast adenocarcinomas, and a previous report consisted of too few cases to analyze its relationship to clinical and pathologic characteristics and prognostic factors (28). In prostate cancer, detection of AMACR by immunohistochemistry is useful to distinguish benign prostate glands from prostatic adenocarcinoma (6, 8-11, 29). AMACR is also expressed in early prostate cancer precursor lesions, such as high-grade prostatic intraepithelial neoplasia, and has been suggested to be a harbinger alteration in the earliest phases of prostate cancer development (6, 8-11, 29). In contrast to prostate glands, we found, by immunofluorescence, that normal breast epithelium also expresses AMACR protein.

To further characterize AMACR expression in situ, we evaluated its expression in tissues from a large group of breast cancer patients and explored the associations between AMACR and histologic and clinical characteristics. AMACR was expressed in the cytoplasm of the invasive carcinoma cells with a granular and punctate staining. This observation was confirmed by immunofluorescence and is consistent with peroxisomal and mitochondrial localization.

In invasive carcinomas of the breast, AMACR protein levels increased with increasing histologic tumor grade, a measure of tumor differentiation and an indicator of a biologically aggressive phenotype (23, 30, 31). Numerous studies have found that patients with high-grade (poorly differentiated) carcinomas have higher rates of distant metastasis and worse survival than patients with low-grade (well-differentiated) carcinomas (23, 30, 31). Histologic grade was found to be an independent predictor or survival (30). A role for AMACR in tumor differentiation has been suggested by previous studies on prostate and colon carcinomas (12, 32). In prostate cancer, AMACR is moderately to highly expressed in well-differentiated tumors, and its expression decreased in hormone-refractory prostate cancer (12). Similarly, well and moderately differentiated colonic adenocarcinomas expressed moderate to high levels of AMACR protein, whereas anaplastic carcinomas of the colon had weak or no expression (12, 32). Notably, we found the opposite effect in breast cancer, as AMACR expression was inversely related to the degree of tumor differentiation. Poorly differentiated (grade 3) invasive carcinomas had the highest AMACR expression and well-differentiated (grade 1) tumors had the lowest. AMACR is not the only protein involved in lipid metabolism that has been found to be associated with, and perhaps to play a role in tumor differentiation. Several investigators found that the peroxisome proliferator-activated receptor-γ controls differentiation in breast, prostate, and colon cancer (33-35). Thus, our results strengthen the possible link between lipid metabolism and the process of tumor differentiation and support the hypothesis that this intriguing role of AMACR may be tissue specific. This hypothesis warrants further investigation.

Finally, we used two methods of scoring the immunohistochemical results: a standard pathologist-based, qualitative, and semiquantitative assessment, and an image-assisted quantitative system. The main difference between these methods is that the image analysis provides continuous data whereas the pathologist scoring results in categorical data. The continuous staining intensity values provided by the quantitative image analysis allows for better discrimination of subtle protein expression differences, which may not be apparent in the pathologist categorical evaluation. Our results show that whereas there was a good correlation between the two systems, the semiautomated quantitative analysis system allowed for a wider range of staining detection and more accurate evaluation of low-intensity staining. It was confirmed by numerous published studies that automated image analysis allows for detection of low expression staining not definable by manual scoring (13-22). Thus, we believe that it may be useful in the automated screening and evaluation of novel biomarkers in breast cancer.

In summary, we have characterized the expression of AMACR protein in normal breast and in breast cancer, and have explored the associations between AMACR expression and clinical and pathologic characteristics in a large group of invasive carcinomas of the breast using tissue microarrays, and two independent scoring systems: a standard pathologist-based approach and a quantitative analysis system. We found that AMACR is expressed in normal breast epithelium, in invasive carcinomas, and their precursor lesion ductal carcinoma in situ. In the group of invasive carcinomas, although AMACR does not have independent prognostic significance, its expression levels are associated with the degree of tumor differentiation. We provide further evidence for a link between proteins involved in lipid metabolism and tumor differentiation in breast cancer.Lastly, quantitative image analysis is a novel way to accurately and reproducibly evaluate immunohistochemistry in breast tissue samples using high-density tissue microarrays.

Grant support: National Cancer Institute grants K08 CA 090876 and R01 CA10746 (C.G. Kleer), and R01AG21404 (M.A. Rubin and A.M. Chinnaiyan); Department of Defense grants DAMD17-01-1-490 and DAMD17-01-1-491 (C.G. Kleer); and a John and Suzanne Munn Award from University of Michigan (C.G. Kleer).

The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.

We thank Robin Kunkel for artwork and Karilynn Schneider for secretarial assistance.

1
Ronco A, De Stefani E, Mendilaharsu M, Deneo-Pellegrini H. Meat, fat and risk of breast cancer: a case-control study from Uruguay.
Int J Cancer
1996
;
65
:
328
–31.
2
Richardson S, Gerber M, Cenee S. The role of fat, animal protein and some vitamin consumption in breast cancer: a case control study in southern France.
Int J Cancer
1991
;
48
:
1
–9.
3
Mobley JA, Leav I, Zielie P, et al. Branched fatty acids in dairy and beef products markedly enhance α-methylacyl-CoA racemase expression in prostate cancer cells in vitro.
Cancer Epidemiol Biomarkers Prev
2003
;
12
:
775
–83.
4
Willett WC. Diet and cancer: one view at the start of the millennium.
Cancer Epidemiol Biomarkers Prev
2001
;
10
:
3
–8.
5
Amery L, Fransen M, De Nys K, Mannaerts GP, Van Veldhoven PP. Mitochondrial and peroxisomal targeting of 2-methylacyl-CoA racemase in humans.
J Lipid Res
2000
;
41
:
1752
–9.
6
Rubin MA, Zhou M, Dhanasekaran SM, et al. α-Methylacyl coenzyme A racemase as a tissue biomarker for prostate cancer.
JAMA
2002
;
287
:
1662
–70.
7
Beach R, Gown AM, De Peralta-Venturina MN, et al. P504S immunohistochemical detection in 405 prostatic specimens including 376 18-gauge needle biopsies.
Am J Surg Pathol
2002
;
26
:
1588
–96.
8
Jiang Z, Woda BA, Yang XJ. α-Methylacyl coenzyme A racemase as a marker for prostate cancer.
JAMA
2002
;
287
:
3080
–1; author reply 3081.
9
Jiang Z, Iczkowski KA, Woda BA, Tretiakova M, Yang XJ. P504S immunostaining boosts diagnostic resolution of “suspicious” foci in prostatic needle biopsy specimens.
Am J Clin Pathol
2004
;
121
:
99
–107.
10
Jiang Z, Fanger GR, Woda BA, et al. Expression of α-methylacyl-CoA racemase (P504s) in various malignant neoplasms and normal tissues: a study of 761 cases.
Hum Pathol
2003
;
34
:
792
–6.
11
Magi-Galluzzi C, Luo J, Isaacs WB, Hicks JL, de Marzo AM, Epstein JI. α-Methylacyl-CoA racemase: a variably sensitive immunohistochemical marker for the diagnosis of small prostate cancer foci on needle biopsy.
Am J Surg Pathol
2003
;
27
:
1128
–33.
12
Kuefer R, Varambally S, Zhou M, et al. α-Methylacyl-CoA racemase: expression levels of this novel cancer biomarker depend on tumor differentiation.
Am J Pathol
2002
;
161
:
841
–8.
13
Shah RB, Mehra R, Chinnaiyan AM, et al. Androgen-independent prostate cancer is a heterogeneous group of diseases: lessons from a rapid autopsy program.
Cancer Res
2004
;
64
:
9209
–16.
14
Santagata S, Demichelis F, Riva A, et al. JAGGED1 expression is associated with prostate cancer metastasis and recurrence.
Cancer Res
2004
;
64
:
6854
–7.
15
Wang S, Saboorian MH, Frenkel EP, et al. Assessment of HER-2/neu status in breast cancer. Automated Cellular Imaging System (ACIS)-assisted quantitation of immunohistochemical assay achieves high accuracy in comparison with fluorescence in situ hybridization assay as the standard.
Am J Clin Pathol
2001
;
116
:
495
–503.
16
Camp RL, Dolled-Filhart M, King BL, Rimm DL. Quantitative analysis of breast cancer tissue microarrays shows that both high and normal levels of HER2 expression are associated with poor outcome.
Cancer Res
2003
;
163
:
1445
–8.
17
Divito KA, Berger AJ, Camp RL, Dolled-Filhart M, Rimm DL, Kluger HM. Automated quantitative analysis of tissue microarrays reveals an association between high Bcl-2 expression and improved outcome in melanoma.
Cancer Res
2004
;
64
:
8773
–7.
18
Ayala G, Wang D, Wulf G, et al. The prolyl isomerase Pin1 is a novel prognostic marker in human prostate cancer.
Cancer Res
2003
;
63
:
6244
–51.
19
Weaver DL, Krag DN, Manna EA, Ashikaga T, Harlow SP, Bauer KD. Comparison of pathologist-detected and automated computer-assisted image analysis detected sentinel lymph node micrometastases in breast cancer.
Mod Pathol
2003
;
16
:
1159
–63.
20
Laitakari J, Harrison D, Stenback F. Automated image analysis of proliferating cells in carcinoma of the larynx.
Acta Otolaryngol
2003
;
123
:
759
–66.
21
Pierga JY, Bonneton C, Vincent-Salomon A, et al. Clinical significance of immunocytochemical detection of tumor cells using digital microscopy in peripheral blood and bone marrow of breast cancer patients.
Clin Cancer Res
2004
;
10
:
1392
–400.
22
Pierga JY, Bonneton C, Magdelenat H, et al. Clinical significance of proliferative potential of occult metastatic cells in bone marrow of patients with breast cancer.
Br J Cancer
2003
;
89
:
539
–45.
23
Elston CW, Ellis IO. Pathological prognostic factors in breast cancer. I. The value of histological grade in breast cancer: experience from a large study with long-term follow-up.
Histopathology
1991
;
19
:
403
–10.
24
Kleer CG, van Golen KL, Zhang Y, Wu ZF, Rubin MA, Merajver SD. Characterization of RhoC expression in benign and malignant breast disease: a potential new marker for small breast carcinomas with metastatic ability.
Am J Pathol
2002
;
160
:
579
–84.
25
Kleer CG, Cao Q, Varambally S, et al. EZH2 is a marker of aggressive breast cancer and promotes neoplastic transformation of breast epithelial cells.
Proc Natl Acad Sci U S A
2003
;
100
:
11606
–11.
26
Harvey JM, Clark GM, Osborne CK, Allred DC. Estrogen receptor status by immunohistochemistry is superior to the ligand-binding assay for predicting response to adjuvant endocrine therapy in breast cancer.
J Clin Oncol
1999
;
17
:
1474
–81.
27
Jacobs TW, Gown AM, Yaziji H, Barnes MJ, Schnitt SJ. Specificity of HercepTest in determining HER-2/neu status of breast cancers using the United States Food and Drug Administration-approved scoring system.
J Clin Oncol
1999
;
17
:
1983
–7.
28
Zhou M, Chinnaiyan AM, Kleer CG, Lucas PC, Rubin MA. α-Methylacyl-CoA racemase: a novel tumor marker over-expressed in several human cancers and their precursor lesions.
Am J Surg Pathol
2002
;
26
:
926
–31.
29
Luo J, Zha S, Gage WR, et al. α-Methylacyl-CoA racemase: a new molecular marker for prostate cancer.
Cancer Res
2002
;
62
:
2220
–6.
30
Henson DE, Ries L, Freedman LS, Carriaga M. Relationship among outcome, stage of disease, and histologic grade for 22,616 cases of breast cancer. The basis for a prognostic index.
Cancer
1991
;
68
:
2142
–9.
31
Fisher ER, Anderson S, Redmond C, Fisher B. Pathologic findings from the National Surgical Adjuvant Breast Project protocol B-06. 10-year pathologic and clinical prognostic discriminants.
Cancer
1993
;
71
:
2507
–14.
32
Jiang Z, Fanger GR, Banner BF, et al. A dietary enzyme: α-Methylacyl-CoA racemase/P504S is overexpressed in colon carcinoma.
Cancer Detect Prev
2003
;
27
:
422
–6.
33
Mueller E, Sarraf P, Tontonoz P, et al. Terminal differentiation of human breast cancer through PPARγ.
Mol Cell
1998
;
1
:
465
–70.
34
Koeffler HP. Peroxisome proliferator-activated receptor γ and cancers.
Clin Cancer Res
2003
;
9
:
1
–9.
35
Lee SS, Pineau T, Drago J, et al. Targeted disruption of the α isoform of the peroxisome proliferator-activated receptor gene in mice results in abolishment of the pleiotropic effects of peroxisome proliferators.
Mol Cell Biol
1995
;
15
:
3012
–22.