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.

Vascular endothelial growth factor has been shown to be upregulated in breast cancers. VEGFR-1 and VEGFR-2 are the principal mediators of its effects. Together with VEGFR-1 and VEGFR-2, neuropilin-1 may act as a co-receptor for VEGF. Although VEGF exerts important effects on endothelial cells, VEGFRs are likely present on tumor cells as well. We used AQUA to analyze tumor-specific expression of VEGF, VEGFR-1, VEGFR-2, and neuropilin-1 on a large cohort breast cancer tissue microarray. Two-fold redundant arrays were constructed from 642 cases of primary breast adenocarcinomas. Automated image analysis with AQUA was then performed to determine a quantitative expression score. Scores from redundant arrays were normalized and averaged. Kaplan-Meier survival analysis showed that high levels of VEGF, VEGFR-1, VEGFR-2, and neuropilin-1 were all significantly associated with survival (Miller Siegmeund corrected P value 0.0020, 0.0160, and 0.0320 respectively). In addition, VEGF and neuropilin-1 retained a significant association with survival independent of other standard prognostic factors. VEGF, VEGFR-1 and 2, and neuropilin-1 are expressed to varying degrees in primary breast cancers and have prognostic significance. Further study of the functional significance of this finding is warranted as well as the prognostic value of these biomarkers in other tumor microenvironment-specific compartments (e.g. vessels).

Immunohistochemical analyses (IHC) of biomarkers are extensively used for tumor characterization and as prognostic and predictive measures. The current standard of single slide analysis assumes that one 5 mM section is representative of the entire tumor. We used our automated image analysis technology (AQUA) using a modified IHC technique with fluorophores to compare estrogen receptor (ER) expression in multiple blocks/slides from cases of primary breast cancer with the objective of quantifying tumor heterogeneity within sections and between blocks. To normalize our ER scores and allow slide-to-slide comparisons, 0.6 mm histospots of representative breast cancer cases with known ER scores were assembled into a 'gold standard array' (GSA) and placed adjacently to each whole section. Overall, there was excellent correlation between AQUA scores and the pathologist's scores and reproducibility of GSA scores (mean linear regression R value 0.8903). Twenty-nine slides from 11 surgical cases were then analyzed totaling over 2000 AQUA images. Using standard binary assignments of AQUA (410) and pathologist's (410%) scores as being positive, there was fair concordancy between AQUA and pathologist scores (73%) and between slides from different blocks from the same cases (75%). However using continuous AQUA scores, agreement between AQUA and pathologist was far lower and between slides from different blocks from the same cases only 19%. Within individual slides there was also significant heterogeneity in a scattered pattern, most notably for slides with the highest AQUA scores. In sum, using a quantitative measure of ER expression, significant block-to-block heterogeneity was found in 81% of cases. These results most likely reflect both laboratory-based variability due to lack of standardization of immunohistochemistry and true biological heterogeneity. It is also likely to be dependent on the biomarker analyzed and suggests further studies should be carried out to determine how these findings may affect clinical decision-making processes.

Diagnostic criteria for non‐overt disseminated intravascular coagulation (DIC) have been proposed by the International Society of Thrombosis and Hemostasis, but are not useful for the diagnosis of early phase of overt‐DIC (pre‐DIC). Therefore, in the current study the non‐overt DIC diagnostic criteria were modified using the global coagulation tests, the change rate in the global coagulation tests and molecular hemostatic markers to detect the pre‐DIC state and were prospectively evaluated in 613 patients with underlying DIC disease. The frequencies of patients with DIC (DIC positive), late onset DIC, and without DIC (DIC absent) were 29.5%, 7.2%, and 63.3%, respectively. The modified non‐overt‐DIC criteria can correctly predict 43/44 patients (97.7%) who were DIC absent at admission and became DIC positive, within a week (late onset DIC state). The mortality rate was higher in DIC positive compared with pre‐DIC (37.6% vs. 22.7%, P < 0.05) or DIC negative (37.6 vs. 13.7%, P < 0.01). It was also significantly higher in pre‐DIC compared with DIC negative (P < 0.05). Thus, these modified non‐overt DIC diagnostic criteria might therefore be useful for the diagnosis of early‐phase DIC. © 2010 Wiley‐Liss, Inc. Am. J. Hematol.

Epidemiologic and preclinical studies suggest that cyclooxygenase-2 (Cox-2) may promote tumor growth and spread by affecting angiogenesis and apoptosis in breast cancer. Using a tissue microarray (TMA), we analyzed the expression and subcellular localization of Cox-2 by AQUA and X-tile, our algorithms for quantitative analysis of protein expression and determination of optimal cutpoints. Our TMA consisted of 669 Stage I-III primary breast cancers. The total tumor and subcellular expression of Cox-2 were then correlated with clinicopathologic factors and with survival. Cox-2 expression appeared higher in malignant than in benign tissue and was predominantly membrane/cytoplasmic (i.e. non-nuclear). X-tile determines an optimum cutpoint on a training set then uses this cutpoint on a validation set. This cutpoint was 19.3 (top 44 percent defined as positive) with high nonnuclear Cox-2 expressers having significantly worse survival. Cox-2 expression also was inversely associated with estrogen receptor (ER) and progesterone receptor (PR), and directly associated with nuclear grade. Multivariate analysis showed that Cox-2 remained a significant prognostic factor for survival independent of tumor size, nodal status, ER, Her2/neu, and grade. In summary, Cox-2 is overexpressed in breast neoplasms, is associated with other markers of poor prognosis, and is significantly associated with worse survival independent of known prognostic factors. Furthermore, AQUA and X-tile analysis suggest an optimal cutpoint that may be helpful in future investigations of Cox-2 and specifically, in studies looking at its expression as a predictive biomarker in clinical trials of Cox-2 inhibitors in breast cancer.