Quantitative determination of expression of the prostate cancer protein alpha-methylacyl-CoA racemase using automated quantitative analysis (AQUA): a novel paradigm for automated and continuous biomarker measurements

Abstract

Despite years of discovery and attempts at validation, few molecular biomarkers achieve acceptance in the clinical setting. Tissue-based markers evaluated by immunohistochemistry suffer from a high degree of inter- and intraobserver variability. One recent advance in this field that promises to automate this process is the development of AQUA, a molecular-based method of quantitative assessment of protein expression. This system integrates a set of algorithms that allows for the rapid, automated, continuous, and quantitative analysis of tissue samples, including the separation of tumor from stromal elements and the subcellular localization of signals. This study uses the AQUA system to assess a recently described prostate cancer biomarker, alpha-methylacyl-CoA-racemase (AMACR), and to determine the effectiveness of the quantitative measurement of this marker as a means for making the diagnosis of prostate cancer. Using a prostate cancer progression tissue microarray containing a wide range of prostate tissues, AQUA was directly compared to standard immunohistochemical evaluation for AMACR protein expression using the p504s monoclonal antibody. Both methods produced similar results showing AMACR protein expression to be strongest in the clinically localized prostate cancer, followed by the metastatic tumor samples. Benign prostate tissue was categorized as negative for most tissue samples by immunohistochemistry. However, AMACR was detectable using the AQUA system at low levels using the standard 1:25 dilution but also at 1:250 dilution, which is not detectable by light microscopy. The AQUA system was also able to discriminate foamy gland prostate cancers, which are known to have a lower AMACR expression than typical acinar prostate cancers, from benign prostate tissue samples. Finally, a receiver-operating-characteristic curve was plotted to determine the specificity of the AMACR AQUA Z-score (normalized AQUA score) to predict that a given tissue microarray sample contains cancer. The area under the curve was calculated at 0.90 (P < 0.00001; 95% CI, 0.84 to 0.95). At an AMACR AQUA Z-score score of -0.3, 91% of the 70 samples classified as prostate cancer were correctly categorized without the intervention of a pathologist reviewing the tissue microarray slide. In conclusion, the AQUA system provides a continuous measurement of AMACR on a wide range of prostate tissue samples. In the future, the AMACR AQUA Z-score may be useful in the automated screening and evaluation of prostate tissue biomarkers.

Figure 1

A–D: Prostate cancer progression chip to measure AMACR expression in benign and neoplastic prostate tissue samples. A prostate cancer progression tissue microarray was designed composed of benign prostate sectors (dark blue), clinically localized prostate cancer sectors (red), regional lymph node metastatic prostate tumors (green), and distant hormone-refractory metastatic prostate tumors (light blue). A: AMACR expression can be seen at the macroscopic level with strong brown expression seen in the prostate cancer sectors. Rare focal expression can be appreciated in the benign section (blue square and TMA sample) and at a similar intensity as seen in an example of clinically localized prostate cancer (red square and TMA sample). C: This sample demonstrates high-grade PIN, a precursor lesion to prostate cancer. D: This area of high-grade PIN demonstrates moderate levels of AMACR expression. Original magnifications: ×200 (A, B); ×630 (C, D).

Figure 2

A–H: Schematic view for using AQUA to measure AMACR in prostate samples. A: Prostate cancers are heterogeneous with a mixture of benign and infiltrating cancer cells. B: Using a single antibody against keratin, the AQUA algorithm can measure the intensity and area of keratin-positive cells using fluorescent dyes. This area is shown in yellow. C: A second antibody against AMACR (p504s) is used to target neoplastic prostate glands. This area is shown in red. D: The fluorescent dyes allow for the simultaneous evaluation of up to four antibodies. In this example AMACR and keratin are shown. The area for each marker is measured by the system (E and F) and can be considered a virtual compartment representing a keratin-positive area and AMACR-positive area (G). Dual expression of keratin and AMACR define a neoplastic compartment (ie, prostate cancer or prostatic intraepithelial neoplasia). Keratin-positive and AMACR-negative areas are consistent with benign epithelial compartment. Negative staining for both AMACR and keratin are consistent with a stromal compartment. Using these definitions, the intensities of different compartments can be measured using arbitrary units (H).

Figure 3

A–G: AMACR expression as determined by AQUA and standard pathology review. A to C demonstrate how AQUA identifies prostate cancer from benign tissue in a tissue microarray sample (0.6 mm diameter). A: Using DAPI staining, all nucleated cells in both the stroma and epithelial compartments are identified. The cytokeratin-positive compartment identifies all epithelial cells (B) and Cy-5 expression (red) demonstrates the area of AMACR expression (C). The staining area and intensity of each compartment can be calculated. The AMACR-positive area, which overlaps with the cytokeratin mask is equivalent to the prostate cancer compartment. D: AMACR (p504s) protein expression by standard pathology review using immunohistochemistry. The expression of AMACR (p504s) was determined using the prostate cancer progression tissue microarray. Expression was scored as negative (score = 1), weak (score = 2), moderate (score = 3), and strong (score = 4). The results for each tissue type are presented as error bars of AMACR (p504s) protein expression with 95% confidence intervals. E: AQUA evaluation of AMACR expression using the prostate cancer progression tissue microarray at two antibody concentrations. AQUA measured similar AMACR protein expression levels for the different tissue categories [ie, benign, localized prostate cancer (PCa), metastatic prostate cancer to regional lymph nodes (Mets), and distant hormone-refractory metastatic prostate cancer (HR Mets)] at standard antibody concentrations (1:25) and at a concentration that would not be visible using standard immunohistochemistry (1:250). The intensity is corrected for area for each tissue microarray spot and measured using arbitrary units. The errors bars demonstrate that within 95% confidence intervals, benign prostate tissue does not score greater than 10 units. F: AMACR protein expression histogram for AQUA analysis. Using the arbitrary unit, this histogram demonstrates a relatively normal distribution of AMACR protein expression using samples from the prostate progression chip. This demonstrates the ability of the AQUA system to give a continuous readout of protein expression. G: Variable AMACR protein expression is appreciated by presenting the individual staining intensities for each sample based on tissue category. Although AMACR protein expression for the clinically localized prostate tumors is significantly higher than the population of benign samples, AMACR expression is still observed in benign tissues and can also be found to be low in other categories.

Figure 4

Evaluation of normalized AMACR-AQUA scores and ability to predict the presence of prostate cancer. The AQUA results were normalized creating an AMACR AQUA Z-score (left). Expression results demonstrate measurable levels of AMACR in the foamy gland tumor population that are statistically significantly higher than the benign prostate tissue population as demonstrated by nonoverlapping error bars with 95% confidence intervals. A ROC plot demonstrates the sensitivity and specificity of using an AMACR AQUA Z-score to diagnose prostate cancer in an unsupervised manner (ie, without previous review by a pathologist) (right). The area under the ROC curve is 0.90 (P < 0.00001; 95% CI, 0.84 to 0.95). An area under the curve of 1.00 represents perfect discrimination of the test to predict prostate cancer and 0.50 no discriminatory power.