Quality Assessment of Proteins and RNA Following Storage in Archival Formalin-Fixed Paraffin-Embedded Human Breast Cancer Tissue Microarray Sections.

Although the immunogenicity of formalin-fixed paraffin-embedded tissue sections can decrease during storage and transport, the exact mechanism of antigenic loss and how to prevent it are not clear. Herein, we investigated changes in the expression of estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 2 (HER-2), E-cadherin, and Ki-67 in human breast tissue microarray (TMA) tissue sections stored for up to 3 months in dry and wet conditions. The positive rates of ER and PR expression were minimally changed after 3 months of storage, but the Allred scores of ER and PR stored in humid conditions decreased remarkably in comparison to fresh-cut tissue. The HER-2 antigenicity and RNA integrity of breast TMA sections stored in dry conditions diminished gradually with storage time, whereas the immunoreactivity and RNA quality of HER-2 in humid conditions decreased sharply as storage length increased. The area and intensity of E-cadherin staining in tissue sections stored in dry conditions did not change significantly and were minimally changed after 3 months, respectively. In contrast, the area and intensity of E-cadherin staining in tissue sections stored in humid conditions decreased significantly as storage length increased. Finally, the Ki-67 labeling index of tissue sections stored for 3 months in dry (9% decrease) and wet (31.9% decrease) conditions was decreased in comparison to fresh sections. In conclusion, these results indicate that water is a crucial factor for protein and RNA degradation in stored tissue sections, and detailed guidelines are required in the clinic.

Report on computational assessment of Tumor Infiltrating Lymphocytes from the International Immuno-Oncology Biomarker Working Group.

Assessment of tumor-infiltrating lymphocytes (TILs) is increasingly recognized as an integral part of the prognostic workflow in triple-negative (TNBC) and HER2-positive breast cancer, as well as many other solid tumors. This recognition has come about thanks to standardized visual reporting guidelines, which helped to reduce inter-reader variability. Now, there are ripe opportunities to employ computational methods that extract spatio-morphologic predictive features, enabling computer-aided diagnostics. We detail the benefits of computational TILs assessment, the readiness of TILs scoring for computational assessment, and outline considerations for overcoming key barriers to clinical translation in this arena. Specifically, we discuss: 1. ensuring computational workflows closely capture visual guidelines and standards; 2. challenges and thoughts standards for assessment of algorithms including training, preanalytical, analytical, and clinical validation; 3. perspectives on how to realize the potential of machine learning models and to overcome the perceptual and practical limits of visual scoring.

Racial Differences in the Association Between Luminal Master Regulator Gene Expression Levels and Breast Cancer Survival.

PURPOSE: Compared with their European American (EA) counterparts, African American (AA) women are more likely to die from breast cancer in the United States. This disparity is greatest in hormone receptor-positive subtypes. Here we uncover biological factors underlying this disparity by comparing functional expression and prognostic significance of master transcriptional regulators of luminal differentiation. EXPERIMENTAL DESIGN: Data and biospecimens from 262 AA and 293 EA patients diagnosed with breast cancer from 2001 to 2010 at a major medical center were analyzed by IHC for functional biomarkers of luminal differentiation, including estrogen receptor (ESR1) and its pioneer factors, FOXA1 and GATA3. Integrated comparison of protein levels with network-level gene expression analysis uncovered predictive correlations with race and survival. RESULTS: Univariate or multivariate HRs for overall survival, estimated from digital IHC scoring of nuclear antigen, show distinct differences in the magnitude and significance of these biomarkers to predict survival based on race: ESR1 [EA HR = 0.47; 95% confidence interval (CI), 0.31-0.72 and AA HR = 0.77; 95% CI, 0.48-1.18]; FOXA1 (EA HR = 0.38; 95% CI, 0.23-0.63 and AA HR = 0.53; 95% CI, 0.31-0.88), and GATA3 (EA HR = 0.36; 95% CI, 0.23-0.56; AA HR = 0.57; CI, 0.56-1.4). In addition, we identify genes in the downstream regulons of these biomarkers highly correlated with race and survival. CONCLUSIONS: Even within clinically homogeneous tumor groups, regulatory networks that drive mammary luminal differentiation reveal race-specific differences in their association with clinical outcome. Understanding these biomarkers and their downstream regulons will elucidate the intrinsic mechanisms that drive racial disparities in breast cancer survival.

Agreement in Histological Assessment of Mitotic Activity Between Microscopy and Digital Whole Slide Images Informs Conversion for Clinical Diagnosis.

Validating digital pathology as substitute for conventional microscopy in diagnosis remains a priority to assure effectiveness. Intermodality concordance studies typically focus on achieving the same diagnosis by digital display of whole slide images and conventional microscopy. Assessment of discrete histological features in whole slide images, such as mitotic figures, has not been thoroughly evaluated in diagnostic practice. To further gauge the interchangeability of conventional microscopy with digital display for primary diagnosis, 12 pathologists examined 113 canine naturally occurring mucosal melanomas exhibiting a wide range of mitotic activity. Design reflected diverse diagnostic settings and investigated independent location, interpretation, and enumeration of mitotic figures. Intermodality agreement was assessed employing conventional microscopy (CM40×), and whole slide image specimens scanned at 20× (WSI20×) and at 40× (WSI40×) objective magnifications. An aggregate 1647 mitotic figure count observations were available from conventional microscopy and whole slide images for comparison. The intraobserver concordance rate of paired observations was 0.785 to 0.801; interobserver rate was 0.784 to 0.794. Correlation coefficients between the 2 digital modes, and as compared to conventional microscopy, were similar and suggest noninferiority among modalities, including whole slide image acquired at lower 20× resolution. As mitotic figure counts serve for prognostic grading of several tumor types, including melanoma, 6 of 8 pathologists retrospectively predicted survival prognosis using whole slide images, compared to 9 of 10 by conventional microscopy, a first evaluation of whole slide image for mitotic figure prognostic grading. This study demonstrated agreement of replicate reads obtained across conventional microscopy and whole slide images. Hence, quantifying mitotic figures served as surrogate histological feature with which to further credential the interchangeability of whole slide images for primary diagnosis.

Reproducibility and Feasibility of Strategies for Morphologic Assessment of Renal Biopsies Using the Nephrotic Syndrome Study Network Digital Pathology Scoring System.

Context Testing reproducibility is critical for the development of methodologies for morphologic assessment. Our previous study using the descriptor-based Nephrotic Syndrome Study Network Digital Pathology Scoring System (NDPSS) on glomerular images revealed variable reproducibility. Objective To test reproducibility and feasibility of alternative scoring strategies for digital morphologic assessment of glomeruli and explore use of alternative agreement statistics. Design The original NDPSS was modified (NDPSS1 and NDPSS2) to evaluate (1) independent scoring of each individual biopsy level, (2) use of continuous measures, (3) groupings of individual descriptors into classes and subclasses prior to scoring, and (4) indication of pathologists' confidence/uncertainty for any given score. Three and 5 pathologists scored 157 and 79 glomeruli using the NDPSS1 and NDPSS2, respectively. Agreement was tested using conventional (Cohen κ) and alternative (Gwet agreement coefficient 1 [AC1]) agreement statistics and compared with previously published data (original NDPSS). Results Overall, pathologists' uncertainty was low, favoring application of the Gwet AC1. Greater agreement was achieved using the Gwet AC1 compared with the Cohen κ across all scoring methodologies. Mean (standard deviation) differences in agreement estimates using the NDPSS1 and NDPSS2 compared with the single-level original NDPSS were -0.09 (0.17) and -0.17 (0.17), respectively. Using the Gwet AC1, 79% of the original NDPSS descriptors had good or excellent agreement. Pathologist feedback indicated the NDPSS1 and NDPSS2 were time-consuming. Conclusions The NDPSS1 and NDPSS2 increased pathologists' scoring burden without improving reproducibility. Use of alternative agreement statistics was strongly supported. We suggest using the original NDPSS on whole slide images for glomerular morphology assessment and for guiding future automated technologies.

Assessment of a panel of tumor markers for the differential diagnosis of benign and malignant effusions by well-based reverse phase protein array.

BACKGROUND: The differential diagnosis of benign and malignant effusion is often hampered by low cell content or insufficiently preserved tumor cells. In this study, we evaluated the combined diagnostic value of six tumor markers measured by well-based reverse-phase protein array (RPPA) for diagnosis of malignant effusion. METHODS: A total of 114 patients (46 with malignant effusions, 32 with probable malignant effusions, and 36 with benign effusions) were enrolled. Expressional levels of MUC1, EMA, Pan-CK, HSP90, TGF-ß and CA125 were determined by well-based RPPA. RESULTS: Median relative expression of MUC1, Pan-CK and EMA were significantly higher in malignant effusion than those in probable malignant or benign (p < 0.001, p = 0.003, p < 0.001, respectively), whereas the level of TGF-ß in malignant effusions were significantly lower than that in the other groups (p = 0.005). For predicting malignancy, EMA presented the best areas under the curve of 0.728 followed by MUC1 of 0.701. The sensitivity of 52.0% for MUC1 and 48.0% for EMA were not better than cytology. However, sensitivity, negative predictive value, and accuracy of the tumor marker panel were better than cytology by 14.7%, 7.5%, and 6.1%, respectively. CONCLUSIONS: Tumor marker panel measured by well-based RPPA showed values in the differential diagnosis between benign and malignant effusions. Further large scale studies need to be performed to evaluate the utility of this panel of markers. VIRTUAL SLIDES: The virtual slide(s) for this article can be found here: http://www.diagnosticpathology.diagnomx.eu/vs/1433424467160224.

Assessment of vascular endothelial growth factor in formalin fixed, paraffin embedded colon cancer specimens by means of a well-based reverse phase protein array.

BACKGROUND: Vascular endothelial growth factor (VEGF) is a critical pro-angiogenic factor, found in a number of cancers, and a target of therapy. It is typically assessed by immunohistochemistry (IHC) in clinical research. However, IHC is not a quantitative assay and is rarely reproducible. We compared VEGF levels in colon cancer by IHC and a quantitative immunoassay on proteins isolated from formalin fixed, paraffin embedded tissues. RESULTS: VEGF expression was studied by means of a well-based reverse phase protein array (RPPA) and immunohistochemistry in 69 colon cancer cases, and compared with various clinicopathologic factors. Protein lysates derived from formalin fixed, paraffin embedded tissue contained measurable immunoreactive VEGF molecules. The VEGF expression level of well differentiated colon cancer was significantly higher than those with moderately and poorly differentiated carcinomas by immunohistochemistry (P = 0.04) and well-based RPPA (P = 0.04). VEGF quantification by well-based RPPA also demonstrated an association with nodal metastasis status (P = 0.05). In addition, the normalized VEGF value by well-based RPPA correlated (r = 0.283, P = 0.018). Furthermore, subgroup analysis by histologic type revealed that adenocarcinoma cases showed significant correlation (r = 0.315, P = 0.031) between well-based RPPA and IHC. CONCLUSIONS: The well-based RPPA method is a high throughput and sensitive approach, is an excellent tool for quantification of marker proteins. Notably, this method may be helpful for more objective evaluation of protein expression in cancer patients.

HER-2 assessment in formalin-fixed paraffin-embedded breast cancer tissue by well-based reverse phase protein array.

BACKGROUND: The human epidermal growth factor receptor-2 (HER-2) expression level is a critical element for determining the prognosis and management of breast cancer. HER-2 targeted therapy in breast cancer depends on the reliable assessment of HER-2 expression status but current standard methods are lacking a rigorous quantitative assay. To address this challenge, we developed an assessment of HER-2 expression method by well-based reverse phase protein array (RPPA). RESULTS: Well-based RPPA is based on a robust protein isolation methodology paired with a novel electrochemiluminescence detection system. HER-2 value of well-based RPPA significantly correlated with dot blotting results (R(2) = 0.939). By well-based RPPA, we successfully detected HER-2 expression in 76 human breast formalin-fixed paraffin-embedded tissue samples. We observed 93.4% (71/76) concordance between well-based RPPA and current HER-2 immunohistochemical assessment guideline. When the cutoff level of HER-2 value was set to 0.689 (HER-2/GAPDH) on the basis of receiver-operating characteristic curve, the area under the curve was 0.975 (95% CI, 0.941-1.000). Sensitivity and specificity of well-based RPPA was 92.1% and 94.7%, respectively. CONCLUSIONS: HER-2 value by well-based RPPA was correlated with the current HER-2 status guideline, suggesting that this normalized HER-2 assessment may offer advantages over unnormalized current immunohistochemical assessment methods.

Reproducibility in the automated quantitative assessment of HER2/neu for breast cancer.

BACKGROUND: With the emerging role of digital imaging in pathology and the application of automated image-based algorithms to a number of quantitative tasks, there is a need to examine factors that may affect the reproducibility of results. These factors include the imaging properties of whole slide imaging (WSI) systems and their effect on the performance of quantitative tools. This manuscript examines inter-scanner and inter-algorithm variability in the assessment of the commonly used HER2/neu tissue-based biomarker for breast cancer with emphasis on the effect of algorithm training. MATERIALS AND METHODS: A total of 241 regions of interest from 64 breast cancer tissue glass slides were scanned using three different whole-slide images and were analyzed using two different automated image analysis algorithms, one with preset parameters and another incorporating a procedure for objective parameter optimization. Ground truth from a panel of seven pathologists was available from a previous study. Agreement analysis was used to compare the resulting HER2/neu scores. RESULTS: The results of our study showed that inter-scanner agreement in the assessment of HER2/neu for breast cancer in selected fields of view when analyzed with any of the two algorithms examined in this study was equal or better than the inter-observer agreement previously reported on the same set of data. Results also showed that discrepancies observed between algorithm results on data from different scanners were significantly reduced when the alternative algorithm that incorporated an objective re-training procedure was used, compared to the commercial algorithm with preset parameters. CONCLUSION: Our study supports the use of objective procedures for algorithm training to account for differences in image properties between WSI systems.

Prognostic assessment of hypoxia and metabolic markers in cervical cancer using automated digital image analysis of immunohistochemistry.

BACKGROUND: Hypoxia inducible factor-1 alpha (HIF-1α), induced by tumor hypoxia, regulates tumor cell metabolism and metastasis by up-regulation of c-Met, carbonic anhydrase 9 (CA9) and glucose transporter 1 (GLUT1). The prognostic significance of hypoxia and metabolic markers is not clearly defined in cervical cancer. Here, we have examined the primary players in the hypoxia signaling pathway, by immunohistochemistry, but confirming their interactions, as well as defining which proteins are associated with outcome. METHODS: The study subjects were comprised of cervical intraepithelial neoplasia (CIN, n = 209), carcinoma in situ (CIS, n = 74), cervical cancer (n = 179), and matched nonadjacent normal tissues (n = 357). Immunohistochemistry (IHC) was performed to identify HIF-1α, c-Met, CA9, and GLUT1. IHC scoring was performed using automated digital image analysis and the association of hypoxic markers with prognostic outcome was evaluated. RESULTS: HIF-1α, c-Met, CA9 and GLUT1 expression were higher in cervical cancer than in CIN and normal cervix (all P < 0.001). Among these markers, expression of HIF-1α and c-Met were significantly different in FIGO stage (P < 0.001 and P = 0.019, respectively) and patients with lymph node metastasis (P < 0.001 and P = 0.010, respectively). HIF-1α expression was correlated with c-Met expression in cervical cancer (P < 0.001). High expression of HIF-1α and c-Met showed worse 5-year overall survival rate (P = 0.047 and P = 0.005, respectively) than low expression group, but CA9 and GLUT1 did not show significant survival difference. After adjusting the prognostic covariates, c-Met was found to be an independent risk factor (HR=3.27; 95% CI, 1.05-10.23, P = 0.041) for overall survival in cervical cancer. CONCLUSIONS: We demonstrate that c-Met correlates with HIF-1α and is a poor prognostic factor in survival in cervical cancer.

Assessment of automated image analysis of breast cancer tissue microarrays for epidemiologic studies.

BACKGROUND: A major challenge in studies of etiologic heterogeneity in breast cancer has been the limited throughput, accuracy, and reproducibility of measuring tissue markers. Computerized image analysis systems may help address these concerns, but published reports of their use are limited. We assessed agreement between automated and pathologist scores of a diverse set of immunohistochemical assays done on breast cancer tissue microarrays (TMA). METHODS: TMAs of 440 breast cancers previously stained for estrogen receptor (ER)-alpha, progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2), ER-beta, and aromatase were independently scored by two pathologists and three automated systems (TMALab II, TMAx, and Ariol). Agreement between automated and pathologist scores of negative/positive was measured using the area under the receiver operating characteristics curve (AUC) and weighted kappa statistics for categorical scores. We also investigated the correlation between immunohistochemical scores and mRNA expression levels. RESULTS: Agreement between pathologist and automated negative/positive and categorical scores was excellent for ER-alpha and PR (AUC range = 0.98-0.99; kappa range = 0.86-0.91). Lower levels of agreement were seen for ER-beta categorical scores (AUC = 0.99-1.0; kappa = 0.80-0.86) and both negative/positive and categorical scores for aromatase (AUC = 0.85-0.96; kappa = 0.41-0.67) and HER2 (AUC = 0.94-0.97; kappa = 0.53-0.72). For ER-alpha and PR, there was a strong correlation between mRNA levels and automated (rho = 0.67-0.74) and pathologist immunohistochemical scores (rho = 0.67-0.77). HER2 mRNA levels were more strongly correlated with pathologist (rho = 0.63) than automated immunohistochemical scores (rho = 0.41-0.49). CONCLUSIONS: Automated analysis of immunohistochemical markers is a promising approach for scoring large numbers of breast cancer tissues in epidemiologic investigations. This would facilitate studies of etiologic heterogeneity, which ultimately may allow improved risk prediction and better prevention approaches.

Automated quantitative assessment of HER-2/neu immunohistochemical expression in breast cancer.

The expression of the HER-2/neu (HER2) gene, a member of the epidermal growth factor receptor family, has been shown to be a valuable prognostic indicator for breast cancer. However, interobserver variability has been reported in the evaluation of HER2 with immunohistochemistry. It has been suggested that automated computer-based evaluation can provide a consistent and objective evaluation of HER2 expression. In this manuscript, we present an automated method for the quantitative assessment of HER2 using digital microscopy. The method processes microscopy images from tissue slides with a multistage algorithm, including steps of color pixel classification, nuclei segmentation, and cell membrane modeling, and extracts quantitative, continuous measures of cell membrane staining intensity and completeness. A minimum cluster distance classifier merges the features to classify the slides into HER2 categories. An evaluation based on agreement analysis with pathologist-derived HER2 scores, showed good agreement with the provided truth. Agreement varied within the different classes with highest agreement (up to 90%) for positive (3+) slides, and lowest agreement (72%-78%) for equivocal (2+) slides which contained ambiguous scoring. The developed automated method has the potential to be used as a computer aid for the immunohistochemical evaluation of HER2 expression with the objective of increasing observer reproducibility.

Pharmacodynamic assessment of histone deacetylase inhibitors: infrared vibrational spectroscopic imaging of protein acetylation.

Infrared spectroscopy identifies molecules by detection of vibrational patterns characteristic of molecular bonds. We apply this approach to measure protein acetylation after treatment with histone deacetylase inhibitors. The anticancer activity of histone deacetylase inhibitors (HDACi) is ascribed to the hyperacetylation of both core nucleosomal histones and nonhistone proteins critical to the maintenance of the malignant phenotype (Marks, P. A.; Richon, V. M.; Breslow, R.; Rifkind, R. A. Curr. Opin. Oncol. 2001, 13, 477-483; Mai, A.; Massa, S.; Rotili, D.; Cerbara, I.; Valente, S.; Pezzi, R.; Simeoni, S.; Ragno, R. Med. Res. Rev. 2005, 25, 261-309). After incubation of the peripheral blood mononuclear cells (PBMCs) in vitro with the HDACi SNDX-275, a benzamide drug derivative, vibrational spectral changes in the methyl and methylene stretching mode regions, which reflect concentration-dependent increases in protein acetylation, were detected and quantified. We applied these metrics, based upon spectral differences, to peripheral blood mononuclear cells from patients treated in vivo with this agent. The data demonstrate a new approach to a sensitive assessment of global molecular modifications that is independent of antibodies, requires minimal cell processing, and is easily adapted to high-throughput screening.

High throughput assessment of cells and tissues: Bayesian classification of spectral metrics from infrared vibrational spectroscopic imaging data.

Vibrational spectroscopy allows a visualization of tissue constituents based on intrinsic chemical composition and provides a potential route to obtaining diagnostic markers of diseases. Characterizations utilizing infrared vibrational spectroscopy, in particular, are conventionally low throughput in data acquisition, generally lacking in spatial resolution with the resulting data requiring intensive numerical computations to extract information. These factors impair the ability of infrared spectroscopic measurements to represent accurately the spatial heterogeneity in tissue, to incorporate robustly the diversity introduced by patient cohorts or preparative artifacts and to validate developed protocols in large population studies. In this manuscript, we demonstrate a combination of Fourier transform infrared (FTIR) spectroscopic imaging, tissue microarrays (TMAs) and fast numerical analysis as a paradigm for the rapid analysis, development and validation of high throughput spectroscopic characterization protocols. We provide an extended description of the data treatment algorithm and a discussion of various factors that may influence decision-making using this approach. Finally, a number of prostate tissue biopsies, arranged in an array modality, are employed to examine the efficacy of this approach in histologic recognition of epithelial cell polarization in patients displaying a variety of normal, malignant and hyperplastic conditions. An index of epithelial cell polarization, derived from a combined spectral and morphological analysis, is determined to be a potentially useful diagnostic marker.