Automated Quantitative Analysis Score Research Articles

Quantitative analysis of tumor-specific BCL2 expression in DLBCL: refinement of prognostic relevance of BCL2

BCL2 overexpression has been reported to be associated with poor prognosis in patients with diffuse large B-cell lymphoma (DLBCL). However, currently there is no consensus on the evaluation of BCL2 expression and only the proportion of BCL2 positive cells are evaluated for the determination of BCL2 positivity. This study aimed to define BCL2 positivity by quantitative analysis integrating both the intensity and proportion of BCL2 expression. BCL2 expression of 332 patients (221 patients for the training set and 111 patients for the validation set) with newly diagnosed DLBCL who received R-CHOP (rituximab, cyclophosphamide, doxorubicin, vincristine, and prednisone) were analyzed using the tumor-specific automated quantitative analysis (AQUA) scoring method based on multiplex immunofluorescence. In the training set, high BCL2 AQUA score (N = 86, 38.9%) was significantly associated with poor prognosis (p = 0.01, HR 2.00; 95% CI [1.15–3.49]) independent of international prognostic index, cell of origin, and MYC expression. The poor prognostic impact of the high BCL2 AQUA score was validated in the validation set. AQUA scoring of BCL2 expression incorporating both the intensity and proportion of BCL2 positive cells was independently associated with survival outcomes of patients with primary DLBCL treated with R-CHOP.

Quantitative Analysis of Tumor-Specific BCL2 Expression in DLBCL: Refinement of Prognostic Relevance of BCL2

Introduction Diffuse large B-cell lymphoma (DLBCL) is the most common subtype of non-Hodgkin lymphoma and a heterogeneous disease with a variety of molecular aberrations and diverse clinical outcomes. BCL2 expression has been implicated for a poor prognosis among patients with DLBCL. However, there is no consensus regarding the interpretation of BCL2 expression in DLBCL. In previous studies, the range of BCL2-positive cases, determined by immunohistochemistry (IHC), was highly variable (24 - 80%) due to subjective and semiquantitative interpretation and the absence of the established cutoff value for BCL2 expression. Consequently, the prognostic impact of BCL2 varies between studies. In addition, only the proportion of BCL2 positive tumor cells are considered in determining the BCL2 positivity. We aimed to define BCL2 positivity by quantitative analysis integrating both the intensity and proportion of BCL2 expression. Methods We retrospectively collected formalin-fixed, paraffin-embedded (FFPE) diagnostic biopsies from 221 patients with de novo DLBCL between January 2007 and December 2012 at our institute. All patients were treated with R-CHOP (rituximab, cyclophosphamide, doxorubicin, vincristine, and prednisone) as first-line treatment. A separate validation set included 111 patients with de novo DLBCL who received first-line R-CHOP at another tertiary hospital in South Korea. BCL2 expression was analyzed using the tumor-specific Automated Quantitative Analysis (AQUA) scoring system based on multiplex immunofluorescence. The tumor-specific quantified intensity information in pixels was converted to protein expression information on a cell basis using the AQUA scoring system. The AQUA scores for BCL2 was calculated as the signal intensities of BCL2 in the target compartment divided by the pixel area of the target compartment. Cell of origin (COO) was determined according to the Hans classification using IHC. Results Ninety-eight patients (44.3%) were > 60 years old of age, 126 patients (57.0%) were male and 81 patients (36.7%) had an International Prognostic Index of 3-5 in the training set. With a median follow-up duration of 59 months, the 5-year event-free survival (EFS) and overall survival (OS) rate were 62.2% and 69.0%, respectively. The BCL2 AQUA score of 41.47 was determined as the optimal cutoff value in the ROC analysis. A total of 86 patients (38.9%) were classified as high BCL2 AQUA score group according to the determined cutoff value. High BCL2 AQUA score was significantly associated with worse OS and EFS (P = 0.00015; OS, P = 0.00012; EFS) (Figure 1A, B). Multivariate analysis revealed that high BCL2 AQUA score was a significant poor prognostic factor for both OS and EFS independent of the IPI, and COO (P = 0.01; OS, P = 0.015; EFS). The high BCL2 AQUA score group in the validation set was also significantly associated with worse OS and EFS (P = 0.0075; OS, P = 0.0049; EFS) (Figure 1C, D). The poor prognostic impact of BCL2 AQUA score was also in good correlation with both OS and EFS in the entire cohort (P < 0.0001; OS, P < 0.0001; EFS) (Figure 1E, F). The adverse impact of high BCL2 AQUA score was identified within both low (IPI 0-2) and high IPI (IPI 3-5) groups (Figure 2A-D). The high BCL2 AQUA score was also associated with poor prognosis within both GCB (P = 0.0077; OS, P = 0.0055; EFS) and non-GCB type DLBCL (P = 0.059; OS, P = 0.04; EFS), although a marginal statistical significance was observed regarding OS in the non-GCB type (Figure 2E-H). Conclusion Our study demonstrated that BCL2 expression analyzed by AQUA scoring system, incorporating both intensity and proportion, is an independent prognostic factor for patients with DLBCL. Given the growing clinical implications of BCL2 and the therapeutic progress in targeting BCL2 in hematologic malignancies, the concrete definition of BCL2 positivity in DLBCL holds great promise for the study of the pathophysiology of DLBCL and could be used to establish new therapeutic strategies. Disclosures No relevant conflicts of interest to declare.

Automated measurement of estrogen receptor in breast cancer: a comparison of fluorescent and chromogenic methods of measurement

Whereas FDA-approved methods of assessment of estrogen receptor (ER) are ‘fit for purpose', they represent a 30-year-old technology. New quantitative methods, both chromogenic and fluorescent, have been developed and studies have shown that these methods increase the accuracy of assessment of ER. Here, we compare three methods of ER detection and assessment on two retrospective tissue microarray (TMA) cohorts of breast cancer patients: estimates of percent nuclei positive by pathologists and by Aperio's nuclear algorithm (standard chromogenic immunostaining), and immunofluorescence as quantified with the automated quantitative analysis (AQUA) method of quantitative immunofluorescence (QIF). Reproducibility was excellent (R2>0.95) between users for both automated analysis methods, and the Aperio and QIF scoring results were also highly correlated, despite the different detection systems. The subjective readings show lower levels of reproducibility and a discontinuous, bimodal distribution of scores not seen by either mechanized method. Kaplan–Meier analysis of 10-year disease-free survival was significant for each method (Pathologist, P=0.0019; Aperio, P=0.0053, AQUA, P=0.0026); however, there were discrepancies in patient classification in 19 out of 233 cases analyzed. Out of these, 11 were visually positive by both chromogenic and fluorescent detection. In 10 cases, the Aperio nuclear algorithm labeled the nuclei as negative; in 1 case, the AQUA score was just under the cutoff for positivity (determined by an Index TMA). In contrast, 8 out of 19 discrepant cases had clear nuclear positivity by fluorescence that was unable to be visualized by chromogenic detection, perhaps because of low positivity masked by the hematoxylin counterstain. These results demonstrate that automated systems enable objective, precise quantification of ER. Furthermore, immunofluorescence detection offers the additional advantage of a signal that cannot be masked by a counterstaining agent. These data support the usage of automated methods for measurement of this and other biomarkers that may be used in companion diagnostic tests.

Multiplexed quantitative analysis of CD3, CD8, and CD20 predicts response to neoadjuvant chemotherapy in breast cancer.

Although tumor-infiltrating lymphocytes (TIL) have been associated with response to neoadjuvant therapy, measurement typically is subjective, semiquantitative, and unable to differentiate among subpopulations. Here, we describe a quantitative objective method for analyzing lymphocyte subpopulations and assessing their predictive value. We developed a quantitative immunofluorescence assay to measure stromal expression of CD3, CD8, and CD20 on one slide. We validated this assay by comparison with flow cytometry on tonsil specimens and assessed predictive value in breast cancer on a neoadjuvant cohort (n = 95). Then, each marker was tested for prediction of pathologic complete response (pCR) compared with pathologist estimation of the percentage of lymphocyte infiltrate. The lymphocyte percentage and CD3, CD8, and CD20 proportions were similar between flow cytometry and quantitative immunofluorescence on tonsil specimens. Pathologist TIL count predicted pCR [P = 0.043; OR, 4.77; 95% confidence interval (CI), 1.05-21.6] despite fair interobserver reproducibility (κ = 0.393). Stromal AQUA (automated quantitative analysis) scores for CD3 (P = 0.023; OR, 2.51; 95% CI, 1.13-5.57), CD8 (P = 0.029; OR, 2.00; 95% CI, 1.08-3.72), and CD20 (P = 0.005; OR, 1.80; 95% CI, 1.19-2.72) predicted pCR in univariate analysis. CD20 AQUA score predicted pCR (P = 0.019; OR, 5.37; 95% CI, 1.32-21.8) independently of age, size, nuclear grade, nodal status, ER, PR, HER2, and Ki-67, whereas CD3, CD8, and pathologist estimation did not. We have developed and validated an objective, quantitative assay measuring TILs in breast cancer. Although this work provides analytic validity, future larger studies will be required to prove clinical utility.

136IN - How to Quantify Immuohistochemical Slides

ABSTRACT The quantitative interpretation of immunohistochemistry (IHC) is typically performed by a subjective evaluation based either on binary positive-negative or semi-quantitative assessments using intensity and percentage of positive cells. A typical example is the evaluation of HER2 expression in breast cancer, which considers also a third variable, i.e. the pattern of membrane staining. All these approaches do not provide true evaluation of the quantity of protein expression and are poorly reproducible. Assays for true protein quantification based on protein extraction, such as enzyme-linked immunosorbent assay, carry as a major drawback the loss of tissue morphology, therefore the protein expression heterogeneity cannot be evaluated. Computer-based automated analyses on classical IHC staining help eliminate the variability of pathologist-based scoring, but do not perform well in terms of quantification and are often time consuming. Some have explored the use of an automated scoring system to assess biomarker expression in tissue sections called the automated quantitative analysis (AQUA) system. This system exploits the pixel-based locale assignment for compartmentalization of expression and utilizes fluorescent tags to distinguish tumor cells from stroma, as well as to define subcellular compartments. The output variable (AQUA score) is a ‘‘pixel intensity/pixel area’’ value ranging from 0 to 255, based on the average intensity for all pixels evaluated, therefore the result is a quantitative score of immunofluorescence intensity for the tumor. It has been shown that AQUA scores are directly proportional to in situ protein concentrations. As an alternative, a technique with a high potential for better definition of protein expression is the Proximity Ligation Assay (PLA). PLA can detect single protein events such as protein protein interactions (e.g. protein dimerization) and modifications (e.g. protein phosphorylation) in tissue and cell samples prepared for microscopy. Each detected signal is visualized as an individual fluorescent dot, these signals can be quantified (counted) and assigned to a specific subcellular location based on microscopy images. Disclosure: All authors have declared no conflicts of interest.

Activity of cetuximab (C) in head and neck squamous cell carcinoma (HNSCC) patients (pts) with PTEN loss or PIK3CA mutation treated on E5397, a phase III trial of cisplatin (CDDP) with placebo (P) or C.

6028 Background: Abnormalities in EGFR signaling targets are associated with C resistance but no biomarker of C resistance has been identified in HNSCC. We hypothesized that cases with loss of PTEN protein expression (PTEN null) or PIK3CA mutation would display C resistance in HNSCC. Methods: E5397 was a phase III trial of CDDP plus P or CDDP plus C and enrolled 117 eligible and evaluable pts. PIK3CA and PTEN were analyzed for 52 and 67 consented pts, respectively. PTEN expression (PTEN Cell Signaling Technology, Cat. 9559) was determined by automated quantitative analysis (AQUA) on the PM-2000 (HistoRx, New Haven) using a cutpoint generated in 5 HNSCC tissue microarrays, each consisting of HNSCC as well as positive (small intestine, median AQUA score 2833.2) and negative controls (breast and colon carcinoma, median AQUA score 205.5). A cutpoint of 570 provides 100% specificity, 100% sensitivity, and identified 30% of the HNSCCs as PTEN null, consonant with the literature. The 3 most common PIK3CA mutations (E542K and E545K in exon 9 and H1047R in exon 20) were determined by BEAMing (Inostics, Heidelberg, Germany). Response, overall survival (OS) and progression-free survival (PFS) were compared between PTEN null or PIK3CA mutated pts and all others. Log rank and multivariable Cox proportional hazards modeling were used to calculate p values. Results: 23/67 (34%) tumors were PTEN null and 2/52 (4%) had PIK3CA mutations (E542K and E545K). Both tumors with PIK3CA mutation had PTEN expression. No statistically significant differences in response, OS or PFS were noted in this small sample. However, among PTEN expressing/PIK3CA WT pts, median PFS increased to 4.2 months (m) for C (N=22) from 2.9 m for P (N=26) (Wald p=0.07), compared with 4.6 m for C (N=12) and 3.5 m for P (n=13) among the PTEN null/PIK3CA mutated (Wald p=0.60). Conclusions: The PTEN loss or PIK3CA mutation signature warrants further investigation as a predictor of C resistance.

Heterogeneity Mapping of Protein Expression in Tumors using Quantitative Immunofluorescence

Morphologic heterogeneity within an individual tumor is well-recognized by histopathologists in surgical practice. While this often takes the form of areas of distinct differentiation into recognized histological subtypes, or different pathological grade, often there are more subtle differences in phenotype which defy accurate classification (Figure 1). Ultimately, since morphology is dictated by the underlying molecular phenotype, areas with visible differences are likely to be accompanied by differences in the expression of proteins which orchestrate cellular function and behavior, and therefore, appearance. The significance of visible and invisible (molecular) heterogeneity for prognosis is unknown, but recent evidence suggests that, at least at the genetic level, heterogeneity exists in the primary tumor1,2, and some of these sub-clones give rise to metastatic (and therefore lethal) disease. Moreover, some proteins are measured as biomarkers because they are the targets of therapy (for instance ER and HER2 for tamoxifen and trastuzumab (Herceptin), respectively). If these proteins show variable expression within a tumor then therapeutic responses may also be variable. The widely used histopathologic scoring schemes for immunohistochemistry either ignore, or numerically homogenize the quantification of protein expression. Similarly, in destructive techniques, where the tumor samples are homogenized (such as gene expression profiling), quantitative information can be elucidated, but spatial information is lost. Genetic heterogeneity mapping approaches in pancreatic cancer have relied either on generation of a single cell suspension3, or on macrodissection4. A recent study has used quantum dots in order to map morphologic and molecular heterogeneity in prostate cancer tissue5, providing proof of principle that morphology and molecular mapping is feasible, but falling short of quantifying the heterogeneity. Since immunohistochemistry is, at best, only semi-quantitative and subject to intra- and inter-observer bias, more sensitive and quantitative methodologies are required in order to accurately map and quantify tissue heterogeneity in situ.We have developed and applied an experimental and statistical methodology in order to systematically quantify the heterogeneity of protein expression in whole tissue sections of tumors, based on the Automated QUantitative Analysis (AQUA) system6. Tissue sections are labeled with specific antibodies directed against cytokeratins and targets of interest, coupled to fluorophore-labeled secondary antibodies. Slides are imaged using a whole-slide fluorescence scanner. Images are subdivided into hundreds to thousands of tiles, and each tile is then assigned an AQUA score which is a measure of protein concentration within the epithelial (tumor) component of the tissue. Heatmaps are generated to represent tissue expression of the proteins and a heterogeneity score assigned, using a statistical measure of heterogeneity originally used in ecology, based on the Simpson's biodiversity index7.To date there have been no attempts to systematically map and quantify this variability in tandem with protein expression, in histological preparations. Here, we illustrate the first use of the method applied to ER and HER2 biomarker expression in ovarian cancer. Using this method paves the way for analyzing heterogeneity as an independent variable in studies of biomarker expression in translational studies, in order to establish the significance of heterogeneity in prognosis and prediction of responses to therapy.

Comparative Prognostic Value of Epidermal Growth Factor Quantitative Protein Expression Compared with FISH for Head and Neck Squamous Cell Carcinoma

Epidermal growth factor receptor (EGFR) overexpression correlates with recurrence and with treatment resistance in head and neck squamous cell carcinoma (HNSCC). The aim of this study was to evaluate the relationship of EGFR gene copy number utilizing FISH and protein expression with automated quantitative analysis (AQUA) and to correlate those with patient outcome. A tissue microarray composed of 102 HNSCC treated with (chemo)radiation was constructed and analyzed for EGFR copy number by FISH (Vysis; Abbott Laboratories) and EGFR protein expression using AQUA analysis of EGFR staining scored on a scale of 0 to 255. We evaluated associations of EGFR FISH status and AQUA score with clinicopathologic parameters and survival prognosis. Eleven (17.2%) of 64 tumors with FISH results showed EGFR high polysomy and/or gene amplification (FISH positive). Protein levels assessed by AQUA in FISH-positive cases were significantly higher (P = 0.04) than in FISH-negative cases. Using the continuous AQUA scores for EGFR expression, AQUA and FISH showed significant agreement (Pearson's ρ = 0.353, P = 0.04). Patients with high tumor EGFR protein expression had inferior 5-year overall survival (27.7%) compared with those with low tumor EGFR expression (54%; P = 0.029). There was no significant association between EGFR FISH status and overall survival (P = 0.201). In the multivariate model, high tumor EGFR protein expression status remained an independent prognostic factor for overall survival (P = 0.047). EGFR protein content correlates with gene copy number if protein content is quantitated and automatically analyzed, as with AQUA. EGFR protein levels assessed by AQUA strongly predict for patient outcome in HNSCC, whereas EGFR FISH status does not provide prognostic information.

Abstract 349: Fascin expression in colorectal cancer metastases predicts survival after curative-intent surgery

Abstract Background: Patients with metastatic colorectal cancer that is limited to a few lesions in the lungs or liver may benefit from the complete surgical removal of all deposits of metastatic cancer (referred to as a curative metastasectomy). Although the outcome after this curative-intent surgery is considerably better than patients with more extensive metastatic cancer, only a third of the surgical patients are actually cured. As a result, there is a great need for a mechanism to predict outcome after surgery for limited metastatic cancer, in order to better match patients with effective therapy. Fascin is an actin bundling protein linked to epithelial to mesenchymal transformation and metastatic progression. Fascin expression has previously demonstrated prognostic potential in patients with extensive metastatic colorectal cancer. We hypothesized that Fascin expression within surgically removed colorectal cancer metastases would correlate with survival after curative-intent surgery. Methods: 82 paraffin embedded colorectal metastases collected after curative-intent surgery between 1990 and 2008 were incorporated into tissue microarrays (TMAs) in two fold redundancy. Fascin expression within the metastases was determined by quantitative immunofluorescence using Automated Quantitative Analysis (AQUA), and normalized based on a panel of cell lines (AQUA score range 0-72). The median follow up was 2.8 years and thus far 51 patients have died (62%). Results: The majority of colorectal cancer metastases had been removed from the liver (70 patients), while 12 represented pulmonary metastases. There were no differences in survival by location of metastases (p = .65). Survival was analyzed based on high (top quartile, n = 21) and low (bottom three quartiles, n = 61) expression of Fascin (AQUA score cut point of 3.4). High expression of Fascin correlated with a worse prognosis, HR 1.97; 95% CI 1.07-3.62 p = .009. Conclusions: Fascin expression within colorectal cancer metastases may be used to predict outcome after curative-intent surgery. Patients with high Fascin expression may be considered for additional therapy or may be advised against particularly high risk procedures. Further study is warranted to validate the role of Fascin expression analysis in this patient cohort. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 349. doi:10.1158/1538-7445.AM2011-349

Melanoma Prognostic Model Using Tissue Microarrays and Genetic Algorithms

Purpose As a result of the questionable risk-to-benefit ratio of adjuvant therapies, stage II melanoma is currently managed by observation because available clinicopathologic parameters cannot identify the 20% to 60% of such patients likely to develop metastatic disease. Here, we propose a multimarker molecular prognostic assay that can help triage patients at increased risk of recurrence. Methods Protein expression for 38 candidates relevant to melanoma oncogenesis was evaluated using the automated quantitative analysis (AQUA) method for immunofluorescence-based immunohistochemistry in formalin-fixed, paraffin-embedded specimens from a cohort of 192 primary melanomas collected during 1959 to 1994. The prognostic assay was built using a genetic algorithm and validated on an independent cohort of 246 serial primary melanomas collected from 1997 to 2004. Results Multiple iterations of the genetic algorithm yielded a consistent five-marker solution. A favorable prognosis was predicted by ATF2 ln(non-nuclear/nuclear AQUA score ratio) of more than –0.052, p21WAF1 nuclear compartment AQUA score of more than 12.98, p16INK4A ln(non-nuclear/nuclear AQUA score ratio) of ≤ −0.083, β-catenin total AQUA score of more than 38.68, and fibronectin total AQUA score of ≤ 57.93. Primary tumors that met at least four of these five conditions were considered a low-risk group, and those that met three or fewer conditions formed a high-risk group (log-rank P < .0001). Multivariable proportional hazards analysis adjusting for clinicopathologic parameters shows that the high-risk group has significantly reduced survival on both the discovery (hazard ratio = 2.84; 95% CI, 1.46 to 5.49; P = .002) and validation (hazard ratio = 2.72; 95% CI, 1.12 to 6.58; P = .027) cohorts. Conclusion This multimarker prognostic assay, an independent determinant of melanoma survival, might be beneficial in improving the selection of stage II patients for adjuvant therapy.

Expression of the Bcl-2 Family of Regulatory Proteins by Quantitative Immunohistochemistry (AQUA) in Follicular Lymphoma.

Abstract 4996 IntroductionThe indolent and incurable nature of follicular lymphoma (FL) is characterized by defects in cellular apoptosis. The ubiquitous overexpression of bcl-2 in FL favors cell survival, but differences in the expression levels and interactions with other bcl-2 family members may account for the clinical heterogeneity observed in FL. Regulation of apoptosis is the result of the interaction of multiple anti-apoptotic and pro-apoptotic members. We evaluated the use of high through-put quantitative immunofluorescence staining with automated quantitative analysis (AQUA) technology to evaluate multiple pro- and anti-apoptotic bcl-2 proteins on a FL tissue microarray. Quantitative levels of apoptotic proteins were correlated with IPI and FLIPI scores and survival. Patients and methodsSeventy-six FL patients evaluated at our institution between 1986 and 1996 with diagnostic biopsies available in paraffin tissue were identified, and diagnostic biopsies incorporated into a tissue microarray. Immunofluorescent antibodies to the anti-apoptotic proteins bcl-2, mcl-1, bcl-XL and the pro-apoptotic proteins BAX, BAD, BAK were applied to the tissue microarray and expression quantified by AQUA technology. Each section was co-stained with CD20, and a CD20 mask or gate applied to limit examination of protein expression to tumor cells. Intensity of fluorescence staining in each sample was expressed as an AQUA score. The AQUA score was analyzed for each protein as a continuous variable. ResultsThe mean age was 56.7 years (range 21.7-84.8), with 55% of patients under the age of 60. Sixty-two percent of patients were men and 66% of patients had stage ≥3 disease at diagnosis. Median duration of follow-up was 9.4 years (range 0.7-33.6 years). Complete data for determining IPI and FLIPI status were available for 63 patients. All bcl-2 family protein biomarkers were expressed as logarithms of the AQUA score. There was a wide range of expression of both pro- and anti-apoptotic proteins between cases, with up to 1000 fold differences in expression levels for all proteins, including bcl-2. In general, there was no association between levels of pro- and anti-apoptotic protein expression and IPI or FLIPI score or survival. In univariate analysis, the hazard ratio for individual biomarkers shows the estimated relative risk of dying for patients, estimating risk based on a one unit increase in the log expression for a biomarker. No individual biomarker was predictive of survival. Age and IPI and FLIPI risk groups were predictive of survival (Table 1). Multivariate analysis showed that biomarkers were not predictive for survival after adjusting for other variables. ConclusionsAQUA quantification of pro- and anti-apoptotic proteins identified marked heterogeneity in protein expression, including bcl-2, in these follicular lymphoma samples. However, there was no clear relationship between the bcl-2 family of biomarkers and FLIPI/IPI status or survival. Use of AQUA technology on a microarray of paraffin-embedded tissue was feasible, but was not useful in predicting clinical outcome in these cases.Table 1Univariate analysis for biomarkers, age, stage, IPI, and FLIPI using Cox hazard regression model.VariableHazard ratio95% CIP-valueLog BAK1.120.61-2.060.71Log BAX1.230.84-1.800.28Log BAD1.070.71-1.630.74Log bcl-XL1.070.65-1.770.78Log mcl-10.840.46-1.530.57Log bcl-21.040.79-1.380.76Age ≥60 (vs <60)2.321.32-4.060.003Stage ≥3 (vs stage <3)0.990.56-1.760.97IPI intermediate/high risk (vs low risk)2.041.14-3.660.02FLIPI intermediate risk (vs low risk)0.770.39-1.550.47FLIPI high risk (vs low risk)2.351.08-5.100.03 DisclosuresNo relevant conflicts of interest to declare.

Nuclear to non-nuclear Pmel17/gp100 expression (HMB45 staining) as a discriminator between benign and malignant melanocytic lesions

HMB45 is a mouse monoclonal antibody raised against Pmel17/gp100, a melanoma-specific marker, which is routinely used in the diagnosis of primary cutaneous malignant melanoma. The standard expression pattern for a positive HMB45 staining result on immunohistochemistry is based upon the results of chromogenic-based methods. We re-evaluated the patterns of HMB45 staining across the 480-core ‘SPORE melanoma progression array’ containing lesions representing the spectrum of melanocytic lesions ranging from thin nevus to visceral metastasis using the fluorescence-based staining technique and automated quantitative analysis (AQUA) of the obtained digital images. The methods validated the expected cytoplasmic HMB45 staining pattern in 70/108 malignant lesions and in the epithelial components of nevus specimens. However, the fluorescence-based approach revealed a nuclear gp100 localization present in the dermal component of all nevi that was not seen before. This nuclear localization could not be observed on routine chromogenic stains, because the standard hematoxylin nuclear counterstain overwhelms the weak nuclear HMB45 stain. The thin (0.450±0.253) and thick (0.513±0.227) nevi had strongly positive mean ln(nuclear/non-nuclear AQUA score ratios), which are significantly higher than those from the group of malignant lesions (P<0.0001). This finding was reproduced on a smaller but independent progression array composed of nevi and melanomas from the Yale Pathology archives (P<0.01). The odds ratio associated with a sample being a nevus was 2.24 (95% CI: 1.87–2.69, P<0.0001) for each 0.1 unit increase of the ln(nuclear/non-nuclear AQUA score ratio) to yield an ROC curve with 0.93 units of area and a simultaneously maximized sensitivity of 0.92 and specificity of 0.80 for distinguishing benign nevi from malignant melanomas. On the basis of this preliminary study, we propose that the ratio of nuclear to non-nuclear HMB45 staining may be useful for diagnostic challenges in melanocytic lesions.

Quantitative Determination of Expression of the Prostate Cancer Protein α-Methylacyl-CoA Racemase Using Automated Quantitative Analysis (AQUA): A Novel Paradigm for Automated and Continuous Biomarker Measurements

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.